The thesis, in my opinion, has reached the necessary standard by fulfilling the requirement for the award of the Doctor of Philosophy degree. Depth distribution of (a) Total Si, (b) Total Fe, (c) Total Mn of sediment core samples at site 1B. d) PCA plot of total metal concentrations for sediment samples in 1B. Sediment core samples at site 1C. d) PCA plot of total metal concentrations for sediment samples at 1C.
List of Tables
Input parameters for the PHREEQC surface complexation model in amorphous Fe oxides for surface densities (mol sites/mol Fe) for sample 1A. 185 Table A 7.1 Phreeqc input for SCM model Fe-oxides amorphous 186 Table A 7.2 Phreeqc input for SCM model Fe-oxides crystalline (Goethite) 186 Table A 7.3 Phreeqc model output for SCM model Fe-oxides amorphous 187 Table A 7.4 Phreeqc model output for SCM model Fe oxides crystalline 189.
Introduction
- Statement of purpose
- Objectives and hypothesis
- Significance of the research work
- Thesis structure
To investigate the hydrogeochemical processes that contribute to the release and mobilization of arsenic in the aquifers of the study area. The current As sinks identified in the sediments of the Assam plains will lead to a greater understanding of As partitioning within the solid phase.
Literature review
General properties of Arsenic .1 Elemental characteristics
Most ingested As is rapidly excreted via the kidneys within a few days, however, high levels of As are maintained for longer periods of time in the bones, skin, hair and nails of exposed humans (Mandal et al., 2003; Bhattacharya et al., 2007). India has adopted the WHO limits of 10 µg/l by the Bureau of Indian Standards (BIS) in September 2003 (Chakraborti et al., 2011) and in Bangladesh, the guideline value for As in drinking water is still 50 µg/ l.
Sources of Arsenic in the environment .1 Natural occurrence
Background As the concentration in groundwater for most of the countries is less than 10 µg/l (Edmunds et al., 1989 for the UK; Welch et al., 2000 for the USA) and sometimes significantly lower. Oxidizing conditions also favor the higher As concentration in the groundwater, where As(V) dominates with relatively higher pH (Bhattacharya et al., 2006).
Arsenic aquatic chemistry
Recent studies indicate the occurrence of geogenic arsenic in Central/Middle Gangetic Plains of Uttar Pradesh, Bihar, Jharkhand, Assam (Chakraborti et al. Mukherjee et al., 2006; Nickson et al., 2007). In 2001, groundwater arsenic contamination of the sedimentary aquifers of the Terai belt in southern Nepal was noted (Shrestha et al., 2003).
Geochemical processes in aquifers involving Arsenic
As(III) and As(V) sorbed to siderite, green rust and magnetite by forming inner-sphere surface complexes, but no evidence of As(III) oxidation as well as reduction of As(V) was noted (Nickson et al. , 2000; Jonsson and Sherman, 2008). However, adsorption of As(III) is largely controlled by the oxidized iron content of the mineral (Deschamps et al., 2005).
Immobilization of Arsenic in the aquifers
The pseudo-second-order model is based on the assumption of chemisorption of the adsorbate on the adsorbents. Good linearization of the data is observed for the initial phase of the reaction, consistent with expected behavior if intraparticle diffusion is the rate-limiting step (Pootset al., 1976).
Study area
Location and environmental conditions .1 Study area in the Darrang district
Land use/land cover mapping of Jorhat district identifies the study area under cropland of kharif plant and plantation category (ARSAC, 1990b).
Geological setting .1 Darrang district
Hydrogeology .1 Darrang district
Previous investigation
Aquifer lithologs
Groundwater and sediment sampling
Sediment samples were identified from locations 1A, 1B and 1C, which cover the target tube well-1, which has a high concentration of As in the groundwater (Figure 4.1). A total of 13 sediment samples were collected from boreholes in the study area, with 6 borehole samples from location_1, 2 soil samples from location_2, 3 soil samples from location_3, and 2 borehole samples from location_4.
Groundwater analysis
Microprocessor Based Flame Photometer 128 Systronics, Ahmedabad, India Digital Spectrophotometer 166 Systronics, Ahmedabad, India UV Visible Spectrophotometer Cary 50 Bio, Varian.
Solid phase analysis
Laser particle size analyzer (Mastersizer 2000) was used to find the specific surface area (SSA) of the soil samples. Then, the bound arsenic species were desorbed by adding 25 ml of 0.2M oxalic acid after removing the supernatant (Amirbahman et al., 2006).
Statistical analysis
Geochemical modeling (PHREEQC)
Therefore, the chemical composition of groundwater reveals its evolution from the geological mineral interactions in the aquifers. Inverse modeling was performed with a known initial solution concentration of the river water flowing near Site_1. The potential mineral phases for the model input were selected from the XRD, SEM and chemical analysis of the sediment samples.
The inverse model simulations were bounded within the specified uncertainty bound, which was taken as 7% in the model run. The sum of the residuals is the sum of the uncertainty of the unknowns weighted by the inverse of the uncertainty bound (for this application <8). The delta/uncertainty sum is the sum of the adjustments for each element concentration weighted by the inverse of the uncertainty margin (for this application . <8).
The surface composition of the sediments was kept in balance with the average groundwater quality of the pipes-1 (T-1) and the pipe-2 (T-2) of Site_1.
Results and discussion
Groundwater geochemistry
The higher concentration of Na+ and Ca2+ in groundwater may also be the result of incongruent dissolution of plagioclase clays (Eby, 2004; Appelo and Postma, 2005). Ground water in Jorhat district was found to be more mineralized as compared to Darrang district. Large spatial variations in groundwater quality parameters were also observed at these different locations.
Higher concentrations of Na+ in the groundwater may be the result of silicate weathering (Appelo and Postma, 2005). The concentration of Mn2+ in the samples was low (on average ~ 0.23 mg/l), therefore the groundwater was undersaturated with rhodochrosite (MnCO3) in most of the samples. The precipitation of siderite (FeCO3) shown in Figure 5.2(a-b) and Figure 5.5(a-d) can act as a temporary sink for the As in the groundwater.
In the inverse geochemical model, the organic carbon was forced to dissolve because the groundwater was found to be in a greatly reduced state.
Sediment characteristics
In the redox process, organic material (CH2O) is oxidized to provide the necessary electrons and the redox-sensitive solutes (NO3-, Mn(IV), Fe3+ and SO42-). The XRD results indicate similarity in the nature of the diffactograms for most sediment samples. The organic carbon distribution and sediment surface area showed a similar trend in the depth profile.
Iron (Fe) in the sediment was found to be well correlated with Ca, Cu, LOI and K. The sediment samples from 2G showed variability in the distribution of As and other components along the depths of the core (Figure 5.19a,b,c). The distribution of As phases in the sediments is highly variable due to the heterogeneity of the sediment.
The highest fraction obtained was the remaining fraction (step_5) of Fe in the sediment samples.
Arsenic attenuation study
In a study of batch adsorption of As(III), a low concentration of aqueous As(V) was found. The greatest decrease in adsorption capacity was observed in the reduced sediment sample C_50 (gray colored sediment). The combined effects of anions showed the greatest decrease in the adsorption capacities of the sediment samples.
We see (5.42a,b) that the greater part of the aqueous As(III) (25%) is removed from the solution by adsorption (more solid As(III)), and a smaller amount (16%) by the oxidation of As(III) to As( V), which is in the form of solid As(V) in the sediment. The equilibrium surface complexation model (SCM) PHREEQC (Parkhurst and Appelo, 1999) was used to predict the differences between sorbed As on Hfo (iron oxide) phases as well as goethite (a more crystalline phase), which were derived from selective sequence extraction data (SSE) and modeled simulations. The model was run using As data obtained from SSE targeting amorphous Fe-oxides and more crystalline Fe-oxides. Rather than truly defining the surface area of available mineral phases, extraction and subsequent calculations estimate the potential number of sorption sites that form metal atoms (Miller, 2001). The amount of observed arsenic from the PHREEQC SCM was compared with the arsenic concentration from the same extraction step.
High concentrations of amorphous and crystalline Fe oxides were found in the sediment from the study area.
Summary and conclusions
Sequential Selective Extraction (SSE) was used to assess the distribution of As among different chemical phases in the sediments. Batch experiments suggested that the sediment samples could adsorb As(V) and As(III) at approximately neutral pH, where groundwater existed in the study area. C_70 and C_150 had relatively more Mn extractable, and the oxidation of As(III) via MnO2 is one of the most effective ways to reduce the toxicity and mobility of As in the subsurface environment.
The surface complexation model (SCM) using component additivity (CA) approach was used to predict solid phase as in the sediment samples. The SSE, hydrogeochemical conditions, mineral saturation, and the redox environment suggested reductive dissolution of Fe oxides as the dominant As release mechanism in the study area. The amount of extractable As fractions (%) of the sediment in the selective sequential extraction (SSE) plays a major role in the enrichment of As in the groundwater.
The As(III) to As(V) oxidation experiment showed that aqueous As(III) oxidation to solid As(V) at the oxidative sites of the sediments was the dominant As removal mechanism for oxidized sediment (C_70) and moderate sediment (C_150).
Evaluation of arsenic and other physicochemical parameters of surface and groundwater of Jamshoro, Pakistan. Comparison of the sorption of arsenic (V) and arsenic (III) on iron oxide minerals: implications for arsenic mobility. Mobility of arsenic in the aquifers of West Bengal introducing arsenic into low and high groundwater. Part II: comparative geochemical profile and leaching study.
Geochemical characterization of arsenic-affected alluvial aquifers of the Bengal Delta (West Bengal and Bangladesh) and Chianan Plains (SW Taiwan): Implications for human health. Distribution and behavior of arsenic in soil and water near the former Salanfe gold and arsenic mine in western Switzerland. Quaternary stratigraphy, sediment characteristics and geochemistry of arsenic-contaminated alluvial aquifers in the Ganges–Brahmaputra floodplain of central Bangladesh.
Mobility of arsenic in a Bangladesh aquifer: inferences from geochemical profiles, leaching data and mineralogical characterization.
Appendix - A 2
Appendix – A 3
Appendix - A 4
Appendix - A 7
