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Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Fakultät: Geowissenschaften, Geotechnik und Bergbau
Studiengang: Master Groundwatermanagement (MGWM)
TITLE OF THE MASTER THESIS:
TRACE ELEMENTS IN THE SOIL SOLUTION AT DAVIDSCHACHT MINE
TAILING FREIBERG GERMANY.
bearbeitet von: Obunadike Callistus Ebuka
Geboren am 08.05.1986 in Onitsha
Matrikelnummer: 58407
zur Erlangung des akademischen Grades: Master of Science (M.Sc)
1. Prüfer / Gutachter: Prof. Dr. Broder Merkel
2. Prüfer / Gutachter: Prof. Dr. Hermann Heilmeier
Betreuer: Dr. Oliver Wiche
Übergabetermin des Masterarbeitthemas: 01.07.16
Abgabetermin der Masterarbeit: 31.01.17
Prof. Dr. J.C. Bongaerts Prof. Dr. H. Heilmeier
Vorsitzender des Prüfungsausschusses Prüfer/Gutachter
CONTENTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Contents
LIST OF FIGURES ...................................................................................................................... II
LIST OF TABLES ......................................................................................................................III
ABBREVIATIONS .................................................................................................................... VI
1 Introduction ...................................................................................................................................1
1.1 Definition and function of trace elements ...............................................................................3
2 Regional Geology of the Investigation Area ................................................................................5
2.1 Regional Geology of Saxony ..................................................................................................5
2.2 Geology of Freiberg ................................................................................................................6
2.3 History of Mining in Freiberg .................................................................................................8
2.4 Characterization of the Davidschacht mine tailings ................................................................9
2.5 Hydrogeology and Hydrology of Freiberg and its region .....................................................12
2.6 Climate ..................................................................................................................................12
2.7 Natural attenuation in acid mine drainage .............................................................................13
2.8 Mineralogical and geochemical behavior of Mine Tailings ..................................................14
3 Methods.......................................................................................................................................17
3.1 Drying and determination of the dry mass content ...............................................................20
3.1.1 Grinding and homogenizing ......................................................................................21
3.1.2 Organic content ..........................................................................................................21
3.1.3 Total decomposition / melting digestion .........................................................................21
3.2 Soil Solution and Soil Samples ..........................................................................................21
3.2.1 Sampling of Soil Solution ................................................................................................21
3.2.2 Collection of Soil Solution ........................................................................................22
3.2.3 Preparation of Soil Solutions for ICP-MS Measurement ..........................................22
3.2.4 Collection of Soil Samples ........................................................................................22
3.2.5 Trace element content determination ........................................................................23
3.3 Determination of phosphate, and mineral N in soil samples and soil solution .....................23
3.3.1 Determination of phosphates in soil solution ............................................................23
3.3.2 Determination of mineral N .......................................................................................24
3.3.3 ICP-MS ......................................................................................................................24
3.4 Statistical evaluation ..............................................................................................................25
4 Results .........................................................................................................................................26
4.1 Trace Elements in soil samples chemistry from the study area........................................27
4.2 pH in soil solution ..............................................................................................................28
CONTENTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
4.3 Electrical conductivity in soil solution ...............................................................................30
4.4 Nutrients in soil solution (P, Mn, Fe, Cu, Zn) ...................................................................36
4.4.1 Phosphorus in soil solution ..............................................................................................36
4.4.2 Manganese in soil solution ........................................................................................36
4.4.3 Zinc in soil solution ...................................................................................................37
4.4.4 Iron in soil solution ..........................................................................................................38
4.4.5 Copper in soil solution ...............................................................................................39
4.5 Toxic/heavy metals in soil solution (As, Pb, Cd) ..............................................................42
4.5.1 Arsenic in soil solution ....................................................................................................42
4.5.2 Lead in soil solution ..................................................................................................43
4.5.3 Cadmium in soil solution .................................................................................................43
4.6 Economic elements/ Rare Earth Elements (Ge, La, Nd, Gd, Er) .......................................48
4.6.1 Germanium and REE in soil solution ..............................................................................48
4.7 Primary nutrients in soil solution ..........................................................................................52
4.7.1 Ammonium in soil solution .............................................................................................52
4.7.2 Nitrate in soil solution ...............................................................................................53
5 Discussion ..........................................................................................................................59
5.0.1 Nutrients (P, Mn, Fe, Cu, Zn) in soil solution chemistry ................................................59
5.0.2 Primary nutrients in soil solution chemistry ....................................................................62
5.0.3 Toxic Elements in soil solution chemistry .......................................................................63
5.0.4 Ge and REE in soil solution chemistry from the study area. ...........................................66
5.1 Discussion on site 1 ...............................................................................................................71
5.1.1 Analysed Trace elements at Upper Horizon ....................................................................71
5.1.2 Analysed Trace elements at lower Horizon .....................................................................73
5.2 Discussion on site 2 ...............................................................................................................76
5.2.1 Analysed Trace elements at Upper Horizon ....................................................................76
5.2.2 Analysed Trace elements at lower Horizon .....................................................................77
5.3 Discussion on site 3 ...............................................................................................................79
5.3.1 Analysed Trace elements at Upper Horizon (ref. site) ....................................................79
5.4 Discussion on site 4 ...............................................................................................................81
5.4.1 Analysed Trace elements at lower Horizon (ref. site) .....................................................81
Lead content at lower Horizon (Site 4) .......................................................................................85
5.5 REE and Germanium content at upper horizon (HA) ...........................................................85
5.5.1 REE and Germanium content at lower horizon (HD) .....................................................85
CONTENTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
5.5.2 Ammonium content in soil solution ................................................................................86
5.5.3 Nitrate content in soil solution .........................................................................................86
5.6 General discussion of the Analyzed Trace elements in soil solution ....................................88
6 Summary .....................................................................................................................................89
7 Abstract .......................................................................................................................................91
Publication bibliography ................................................................................................................93
Appendix ...................................................................................................................................105
A EQUIPMENT, CHEMICALS, PLOT-PLAN .......................................................................105
A1 Used equipment ...................................................................................................................105
A2 ICP-MS Device parts and its functions XSERIES 2 ...........................................................106
A3 Chemicals used ....................................................................................................................107
B: RESULTS OF THE SOIL SOLUTION ...............................................................................108
B1: pH VALUES .......................................................................................................................108
B2: Total dissolve solvent [mg/l] ..............................................................................................109
B3: Electrical conductivity [µS·cm-1] ......................................................................................110
B4: Concentrations of elements in soil solution ........................................................................111
C: RESULTS OF THE SOIL SAMPLES .................................................................................120
Acknowledgement .....................................................................................................................123
Declaration ................................................................................................................................124
LIST OF FIGURES
II
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
LIST OF FIGURES
Figure 1: The position of the Erzgebirge in the European Variscides…….……….……...….…5
Figure 2: Location map and aerial photograph (taken in 2007) of the study area……...….….11
Figure 3: ICP-MS-Meter XSERIES 2 with autosampler………………………………………24
Figure 4: Showing differences in pH values in upper and lower horizon, throughout the
investigation period time …………………………………………………...……….27
Figure 5: Showing differences in Ec values in upper and lower horizon, throughout the
investigation time period ………………………………………………………...….29
Figure 6: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of soil nutrients (P, Mn), within upper and lower
horizon, throughout the investigation period ………...………………………………..... 31
Figure 7: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of soil nutrients (Cu, Zn), within upper and lower
horizon, throughout the investigation period…………………………..…………….....32
Figure 8: Soil solution chemistry at the investigated site (2-4), showing differences and
distributions in the concentrations of soil nutrients (Zn, Fe), within upper and lower
horizon, throughout the investigation period ……………………..……………….…....33
Figure 9: Soil solution chemistry at the investigated site 1, showing differences and
distributions in the concentrations of soil nutrients (Fe), within upper and lower
horizon, throughout the investigation period ……………………………………….....34
Figure 10: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of toxic elements (As, Pb), within upper and lower
horizon, throughout the investigation period…….……………………….…………....39
Figure 11: Soil solution chemistry at the investigated site 1, showing differences and
distributions in the concentrations of toxic element (Cd), within upper and lower
horizon, throughout the investigation period ……………………….……………….....34
Figure 12: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of REE (La, Nd), within upper and lower horizon,
throughout the investigation period ………………………………...……………….....44
Figure 13: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of REE (Er, Gd), within upper and lower horizon,
throughout the investigation period …………………………………….…………….....45
LIST OF FIGURES
II
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 14: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of germanium within upper and lower horizon,
throughout the investigation period ………………..………………………………….......46
Figure 15: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of NH4+ and NO3- -within upper and lower horizon,
throughout the investigation period ……………………...…………………………….....50
Figure 16: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of NO3- and PO43- within upper and lower horizon,
throughout the investigation period …………………………………………………….....51
Figure 17: Nitrogen conversion process in the soil………………….…………..……….…….62
Figure 18: Soil solution chemistry at the investigated site (1-4), showing differences and
distributions in the concentrations of PO43- within upper and lower horizon,
throughout the investigation period ……………………………………………………...122
LIST OF TABLES
III
LIST OF TABLES
Table 1: Essentiality and potential toxicity of trace elements to plants and animals in the
terrestrial environment……………………………………………………….……….4
Table 2: Showing the air-temperature and cumulative precipitation from Reiche-Zeiche
weather station Freiberg during the measuring time period in davidschacht mine
dump (Source Tu-Bergeakademie webpage) …………………………………….…13
Table 3: Schematic relative resistance to alteration of sulphides and magnetite in oxidized
tailings………………………………………………………………………..……...16
Table 4: Sulfide alteration Index (SAI) of Sheridon tailings…………………………………16
Table 5: Soil and vegetation composition found in David-shaft mine-dump and its
environment………………………………………………………………………….18
Table 6: On-site parameters of the soil samples for Upper horizon, and Lower horizon for the
two-measuring time period [117 to 125. DoY]……..……………………………....25
Table 7: Target values and soil remediation intervention values and background conc.
soil/sediment and groundwater for metals. Source www.esdat.net (Dutch
environmental standards)………………………………………………….………...26
Table 8: Concentrations of selected elements [mg·kg-1] in the soil samples for Upper horizon,
and Lower horizon for the first measuring time period [117 to 125. DoY] …...……27
Table 9: Showing the P-Values for Horizon A (HA), at different time periods (T1-T4) within
Site 1 and Site 2 (S1-S2) at 95% confidence level...…………………………...…….54
Table 10: Showing the P-Values for Horizon D (HD), at different time periods (T1-T4) within
Site 1 and Site 2 (S1-S2) at 95% confidence level ………..…………………...…….55
Table 11: Showing the P-Values of different vegetation for the Six (5) time periods T1-T5
within Site 1 and Site 2 (S1-S2) at 95% confidence level...………………………….56
Table 12: Spearman rank correlation for the concentrations of toxic elements (As, Cd, Pd) and
REE (Ge, La, and Gd) for S1 and S2 of different time ……….....…..……..………..58
Table A1: Overview of the devices used………………………..…………………………….100
Table A2: Overview of the ICP-MS device parts and its functions in XSERIES 2………..…101
LIST OF TABLES
IV
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Table A3: Overview of the chemicals used…………………………………………..……….102
Table B1: Measured pH value in the soil solutions over the period of the experiment (T1 to T6).
……………………….………………………………………………………...…...103
Table B2: Total dissolve solvent [mg/l] in the soil solutions over the period of the experiment
[T1 to T6] …………...……………………………………………………...…...….104
Table B3: Electrical Conductivity [Ec.] [µS·cm-1] in the soil solutions over the period of the
experiment [T1 to T6] ………………...………………………………………....…105
Table B4: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at first measuring time period [T1] ….................................................................…106
Table B5: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at first measuring time period [T1] ….................................................................…107
Table B6: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at second measuring time period [T2] ..................................................................…108
Table B7: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at second measuring time period [T2] …..............................................................…109
Table B8: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at third measuring time period [T3] …..................................................................…110
Table B9: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at third measuring time period [T3] …..................................................................…111
Table B10: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at fouth measuring time period [T4] ….................................................................…112
Table B11: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at fourth measuring time period [T4] …....................................................................113
Table B12: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at fifth measuring time period [T5] …...................................................................…114
Table B13: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at fifth measuring time period [T5] …...................................................................…115
Table B14: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon A [HA]
at sixth measuring time period [T6] …..................................................................…116
Table B15: Concentrations of selected elements [μg·L-1] in the soil solutions for horizon D [HD]
at sixth measuring time period [T6] …..................................................................…117
LIST OF TABLES
V
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Table B16: Showing the highest and lowest concentration values of the measured soil solution in
different vegetation with respect to the location, horizon and time throughout the
study area…………………………………………………………………………..118
Table C1: Concentrations of selected elements [mg·kg-1] in the soil samples for Upper horizon,
where BS [Site code; A code given by German students on past work conducted in
David-Shaft] …………………………………………………………...………...120
Table C2: Concentrations of selected elements [mg·kg-1] in the soil samples fo Lower horizon,
where BS [Site code; A code given by German students on past work conducted in
David-Shaft] …………………………………………………………….……….121
ABBREVIATIONS VI
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
ABBREVIATIONS
General Abbreviation
SSa Soil samples
SSn Soil Solution
PPM Parts per million/milligram/liter
PPB Parts per billion/ microgram/liter
S 1-4 Site numbers [1, 2, 3, and 4]
HA Horizon A
HD Horizon D
T1-6 Sampling Time Period [1, 2, 3, 4, 5, 6]
ANOVA Analysis of Variance
REE Rare Earth Elements
Nm Not measured
BDL Below detected level
ICP-MS Inductively coupled plasma mass spectrometry
EC Electric conductivity
TDS Total dissolved solute
REE Rare Earth Elements
ToY Time of the year
DoY Days of the year
nSSD not statistically significantly difference
SSD statistically significantly difference
T1 158th day of the year 2016
T2 172th day of the year 2016
T3 179th day of the year 2016
T4 186th day of the year 2016
T5 200th day of the year 2016
T6 214th day of the year 2016
Va Vegetation “a” (no vegetation)
Vb Vegetation “b” (sparse vegetation)
Vc Vegetation “c” (dense vegetation)
RIVM National Institute for Public Health and Environmental Protection
MPR Maximum Permissible Risk
TDI Tolerable Daily Intake
ABBREVIATIONS VII
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
pH - log [H+] or [OH-]
Ec Electrical conductivity
Tds Total dissolved solute
Temp. Temperature
SOM Soil Organic Matters
Nm Not measured
CEC Cation Exchange Capacity
Redox Reduction-Oxidation
Eh Redox potential
BDL Below Detection Limit
INTRODUCTION 1
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
1 Introduction
Freiberg is located in the eastern part of Germany about 240km south of the capital of Berlin,
which is close to the border of Czech Republic in the federal state of saxonia. The Freiberg,
Zwickau and United trough covers an area of about 7600 km², which includes the Freiberger
metals and mining province, they are considered the main source for heavy metals in the river
Elbe (Martin et al., 1994). There are several mining locations in Freiberg and environs, of
which Himmelfahrt mine is one of them. The Himmelfahrt mine consists of shafts like
Abraham-shaft, David-shaft and Thurmhof-shaft. Reiche Zeiche mine and Alte Elisabeth mine
are also parts of Himmelfahrt mine in Freiberg. In this research, the data were collected at
David-shaft, which is within the Himmelfahrt mine of Freiberg. David-shaft is bounded by
latitude 50° 55' 25" N to 50° 55' 32" N and longitude 13° 22' 00" E to 13° 22' 12" E.
Over the past century, mining, manufacturing and urban activities have all contributed to
extensive soil contamination. Various physical, chemical and biological processes are already
been used to remediate contaminated soils (Cunningham et al., 1995). Most plants growing on
contaminated soils effectively exclude heavy metals from their tissues. According to Jeffery,
(1987) although plants take up and accumulate certain essential nutrients from soils to
concentrations as high as l-3%, levels of heavy metals only accumulate to 0.1 -100mg/kg in
most plants.
According to Angel & Linacre, (2005) phyto-mining is applied during the removal of the heavy
metals and metalloids, through the extraction of metals by plants or hyper accumulating plants.
The bioavailability of the heavy metals and metalloids in the soil is more at acidic pH and it can
also be facilitated by addition of artificial chelates (e.g. EDTA) (Friesl-hanl et al., 2006). Thus,
heavy metals and metalloids can also be mobilized and thus made potentially available to plants
which are more strongly bound in the soil (Friesl-hanl et al., 2006). Subsequently, the heavy
metals and metalloids are transferred to suitable plants (Salt et al., 1998). Metals accumulated in
soils are depleted slowly by leaching, plant uptake, erosion, or deflation (Kabata-Pendias &
Pendias, 2000). A high rate of trace metal mobility in soils affects the increase of both
bioavailability and leaching down soil profiles into water systems (Kabata-Pendias & Pendias,
2000). Some plants take up (absorb) heavy metals and metalloids from the soil into their biomass
(Kumar et al. 1995).
According to (Han & Singer, 2007) soil solution is the aqueous phase of soil, it is in the pore
space of soils and includes soil water and soluble constituents, such as dissolved inorganic ions
and dissolved organic solutes. Soil solution provides the source and a channel for movement and
INTRODUCTION 2
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
transport of nutrients and trace elements and regulates their bioavailability in soils to plants (Han
& Singer, 2007).
According to (Han & Singer, 2007) soil solution analysis can be used for prediction of plant
response (bioavailability) to nutrients and trace elements in the soil. An understanding of soil
solution composition can also be helpful in estimating the speciation and forms of trace
elements and nutrients which may be transported into surface and groundwater (Wolt, 1994).
Soil solution composition reflects the intensity and distribution of trace elements in the soil
aqueous phase and represents the integration of multiple physical, chemical and biological
processes occurring concurrently within the soil (Wolt, 1994).
The composition of soil solution is mainly influenced by various factors like soil moisture,
seasonal changes, temperature, pH and anthropogenic activities (Han & Singer, 2007). The
concentration of trace elements significantly differs among, soil of the same group and
geographic regions (Sumner, 2000). Further, during recent decades trace inorganic pollutants
have been distributed so widely that even soils in remote regions show increased levels of certain
trace elements of anthropogenic origin (Sposito et al., 1984). Trace elements can enter the soils
by a number of pathways, and their behavior and fate in soils differ according to their source and
species (Adriano, 1986).
The main objectives of this review were as follows: to evaluate the trace elements composition
of David-shaft mine dump by sampling and analyzing soil, to investigate the mobility of the
elements in soils over time, by sampling soil solution from suction cups installed at different
soil depths and finally, to investigate the effects of different vegetation types on these
parameters. Several selected trace elements were determined with the aid of ICP-MS. The
concentrations of these selected trace elements (P, Mn, Fe, Cu, Zn, As, Pb, Cd, Ge, Gd, La, Nd,
Er) in soil solution of the David-shaft mine tailing were investigated as well as the effects of
vegetation on soil solution chemistry. Dissolution, sorption, complexation, migration,
precipitation, occlusion, diffussion (into minerals), binding by organic substances, absorption
and sorption by microbiota, violatization, all these processes are governed by several soil
properties, of which soil pH and redox potential are known to be the most important
parameters. Thus, the solubility of trace metals is often shown as a function of pH affected by
the amount and kind of organic matter (Kabata-Pendias & Pendias, 2000).
According to Sánchez España et al., (2007) long term changes in soil quality can be induced
when trace elements inputs are sustained over long period of time and when they exceed the
rate of loss from the system. Although some trace elements are essential plant micronutrients,
excessive concentrations of them in soils are a general matter of concern to society as they may
INTRODUCTION 3
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
adversely affect the quality of our ecosystem or leach down to groundwater and contaminate
drinking water resource, and may cause, in both cases, hazards to the health of humans and
animals (Nriagu, 1998). The greatly increased circulation of hazardous trace elements in soils,
water and air implies an inevitable build-up of trace elements in the ecosystem (Swaine, 1962).
Minamata (methyl mercury poisoning) and Itai-Itai (Cd) diseases in Japan awakened the public
conscience to focus attention on the hazardous role of trace elements in human health (Todd &
Mays, 2005; Drasch, 1983; Patterson, 1980).
1.1 Definition and function of trace elements
The term “trace element” is often used in the literature and may have different meanings in
various scientific disciplines. It refers to elements that occur in minute concentrations in natural
and artificial systems. Often it defines elements that are essential or toxic in small quantities to
microorganisms, plants and animal, including humans. A general consensus exists on
considering “trace” an element which is present in the system e.g., soil and introduced
materials, at levels of less than 0.1% (Mertz, 1981). In this review, the term “trace elements” is
used for elements that naturally occur in the soil and are applied to it by anthropogenic sources
(past mine activities) and when present in sufficient concentrations, become hazardous for the
ecosystem in general. In Table 1, a summary is provided for essential, uncertain and potentially
toxic (trace elements) to plants and animals according to Adriano, (1986).
The availability of ICP-MS and other analytical techniques have facilitated the rapid and
reliable analysis of trace elements. According to Adriano, (1986) reliable analytical data on
chemical forms, speciation and bioavailability of trace elements in different areas and a valid
estimation of their background levels are absolutely necessary to the legislators for introducing
mandatory or guideline levels which are realistic and appropriate.
Problems of data interpretation are especially pertinent when “contamination” or “pollution” by
trace elements is discussed. According to Voisin, (1959) a “contaminant” trace element for
soil may be defined as an element found in a given soil at a concentration higher than that of its
“natural” level in the soil, and where the source of the additional concentration of the element
appears to be human activity. The problem is that human activity tends to generate widespread,
low level contamination, and, therefore, even at locations far from any known anthropogenic
sources, the trace element contents of soils (and plants) are not necessarily “natural” (Voisin,
1959; Piispanen, 1989). Another important question in evaluating contamination, or pollution,
by trace elements is whether the observed concentration of the contaminant is harmful, and
harmful to which system. A trace element which is harmful to one organism may not be
harmful, and even be beneficial, to another one at that same concentration (Piispanen, 1989).
INTRODUCTION 4
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
There is no doubt that trace element content and status of soils may influence plant uptake and
concentration of the element in the tissues of food and fodder crops, thus affecting the quality
of food and potable waters with potential implications to human health, on a mine dump.
Voisin, (1959) suggested that, human cancer might be linked to the soil environment, especially
through copper. Several efforts have been made in comparing disease maps with geochemical
maps, and noticeable resemblances have been found (Piispanen, 1989).
Table 1. Essentiality and potential toxicity of trace elements to plants and animals in the terrestrial environment modified after
Adriano, (1986).
Elements
Essential or beneficial to
Plants Animals
Potentially toxic to
Plants Animals
Comments
As
No Yes
Yes Yes
Potential carcinogenic
Cd
No No
Yes Yes
Enriched in food chain;
carcinogenic; Itai-Itai
disease
Co
Yes Yes
Yes Yes
Relatively non-toxic;
high enrichment factor;
carcinogenic
Cu
Yes Yes
Yes
Toxic at ˃ 20mg/kg
F
No Yes
Yes
Accumulative toxicity for
plants and animals;
fluorosis
Mn
Yes Yes
Yes(pH˂5)
Among the least toxic
Mo
Yes Yes
Yes
High enrichment in
plants; Toxic for
animals at ˃ 20mg/kg
Ni
No Yes
Yes Yes
Toxic for plants at ˃
50mg/kg; carcinogenic
Pb
No No
Yes Yes
Cumulative poison
Zn
Yes Yes
Toxic at ˃ 200mg/kg
LITERATURE REVIEW 5
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
2 Regional Geology of the Investigation Area
The Erzgebirge (Saxonian Erzgebirge and Bohemian-Krušnéhory) is part of the metamorphic
basement of the internal Mid-European Variscides on the NW-border of the crystalline
Bohemian Massif core complex (Seifert et al., 2006). It represents an antiformal mega structure
with a large core composed of medium to high-grade metamorphic mica-schists and gneisses
with intercalations of eclogite (Schmädicke, 1994; Mingram et al., 2004; Sebastian, 1995). The
peak P–T conditions in the Gneiss–Eclogite unit were dated by (Willner et al. 1997) and
(Tichomirowa, 2001) at 340 and 330 Ma, respectively. According to these authors and age data
of the post-kinematic magmatism in the Erzgebirge (Seifert, in press), an extremely fast
tectonic exhumation of the Erzgebirge complex between 340 and 330 Ma can be postulated.
According to Seifert et al., (2006) the polymetallic sulphide veins of the base metal deposits in
the Erzgebirge are hosted by ortho-(Freiberg district) and paragneisses (Marienberg, Annaberg,
and Hora Sv. Kateriny districts), mica schists (northern part of the Freiberg district,
Johanngeorgenstadt), and sub-ordinately by post-kinematic granites (Schneeberg and eastern
part of the Freiberg district).
2.1 Regional Geology of Saxony
Figure 1: The position of the Erzgebirge in the European Variscides (modified from the compilation of McKerrow et al., 2000).
Saxo-Thur = Saxo-Thuringian Zone; Tep-Barr = Tepla-Barrandian Zone. (Seifert et al., 2006)
Late Variscan acidic and lamprophyric (sub) volcanic intruded into the Erzgebirge
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metamorphic core complex and the older stage of post-kinematic granite intrusions. The
evolution of the post-kinematic magmatism is related to late- and post-collisional extension on
the NW-borderline of the Bohemian Massif (Seifert et al., 2006). The post-collisional
magmatism is controlled by deep fracture zones (Seifert, & Kempe 1994) and is associated with
different types of tin and polymetallic sulphide mineralization. The intrusion of Permo–
Carboniferous lamprophyric dikes in the Erzgebirge indicates mantle-induced high-energy and
fluid pulses during the Late Variscan. It is important to realize that the large base metal deposits
and lamprophyric dikes are affiliated and occur together at cross-cutting deep fault zones
(Freiberg, Marienberg, and Annaberg districts; cf. (Seifert, & Baumann 1994).
2.2 Geology of Freiberg
The polymetallic vein-type deposits in the Freiberg district are subdivided into certain mining
areas (ore fields) including the North (Obergruna, Kleinvoigtsberg, Mohorn), Central
(Halsbrücke, Freiberg, Muldenhütten), and South sub-district (Zug, Brand–Erbisdorf, Brand)
(Baumann et al., 2000). The Ag-base metal veins of the Central and South sub-district are
mainly hosted by orthogneisses (‘Freiberg gneiss’ and ‘Brand gneiss’. In the southern part of
the South sub-district (‘Himmelsfahrt’ mine, the ore veins crosscut garnet-bearing mica-schists.
South of this mica-schist zone, no ore veins were identified (Gotte, 1956; Baumann, 1957). In
the North sub-district, the veins are mainly hosted by mica-schists and paragneisses, partly with
intercalations of meta-black-shales (Müller, 1901; Baumann et al., 2000). Minor occurrences
of the Freiberg veins are hosted by ‘red gneisses’, gabbros, and Permo–Carboniferous granites,
rhyolites and lamprophyres. Approximately 1100 polymetallic sulphide veins were mined up to
800 m depth.
According to (Baumann, & Hofmann 1967), the Freiberg ore vein system is developed within
the paracrystalline joint system. The so-called ‘Freiberg vein network’ is characterized by two
(NNE–SSW to N–S and E–W to ENE–WSW) shear systems, and spatial associated fissure
veins. The mineralized ‘central shear fault zone’ shows a NNE–SSW striking distance of about
14 km. This steeply dipping shear vein is characterized by ore lenses with a thickness of up to
10 m (Baumann, 1957, 1960), and was mined in the central and southern district. In the mining
area of the important ‘Himmelfahrt’ mine (northeastern of the town of Freiberg) it is called
‘Hauptstollengang Stehender’. The elements indium and germanium were discovered in 1863
and 1886, respectively at the Bergakademie Freiberg, from ores of the local Freiberg district
(eastern Erzgebirge, Saxony, Germany). Silver-rich polymetallic vein-type deposits were mined
from about 1168 to 1969 in an area of approximately 3520 km. During the study for the source
of thallium in local ores of the Freiberg mining district, Reich and Richter, (1863b) observed an
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indigo-blue line with the spectroscope which did not correspond to any known element. They
then isolated the new material as chloride, oxide hydrate, and metal. Because of this
characteristic color, the new element was named indium. According to Reich and Richter,
(1864), only the Freiberg sphalerite showed significant In contents of about 0.1 wt. %. Winkler,
(1865) measured an In content of 0.0448 wt. % in sphalerites from the polymetallic sulphide
veins of the Freiberg district.
In 1885, an unknown mineral was found at the Himmelsfahrt mine in the southern part of the
Freiberg district. Weisbach, (1886) named this new mineral argyrodite. The discovery vein was
named therefore “Argyrodit Spat”. Clemens Winkler in (Weisbach, 1886) inspected this
mineral and found 75 wt. % Ag and 18 wt. % S, but 7 wt. % could not be identified. After long
and difficult analyses, he discovered the element germanium in 1886. This element had already
been predicted in 1872 by D. Mendelev as “Ekasilizium”, when setting up his periodic system
of the elements. According to Winkler (1886), the Freiberg argyrodite (Ag8GeS6) has an
average composition of 74.72 wt.% Ag, 6.93 wt.% Ge, 17.13 wt.% S, 0.66 wt.% Fe, and 0.22
wt.% Zn.
Hydrothermal Ag-rich base metal vein-type deposits were mined in the Eastern Erzgebirge
(Freiberg district), Central Erzgebirge (Marienberg, Annaberg, and Hora Sv. Katerˇiny
districts), and Western Erzgebirge (Johanngeorgenstadt, and Schneeberg districts) from the
early Middle Ages to the 20th Century (Baumann et al., 2000). The Freiberg vein field was one
of the largest base metal districts in Europe with a production of more than 5000t of silver
metal from the end of the 12th Century to the end of the 19th Century, as well as small-scale
mining of copper and tin. Uranium exploration from the Russian mining company “SAG
Wismut” was active from 1945 to 1950, and resulted in the production of about 10 t of U metal
mined from the southern part of the district (Seifert et al., 1996b). From 1950 to 1969 about
95,000t of Pb metal, 59,000t of Zn metal, and 251 t of Ag metal were produced. Ge, In, Cd, Bi,
Au, Tl, and pyrite were concentrated as by-products (unpublished material of the ‘VEB
Bergbau-und Hüttenkombinat Albert Funk’, Freiberg). Residues from Zn smelting averaging
0.35 wt. % Cd, 0.1 wt. % In, 150 g/t Tl, and 28 g/t Ge were leached with sulphuric acid for
recovery of Cd and In. From 1965 to 1972 about 470t of Cd metal and an unknown quantity of
In metal were produced by the Freiberg mining and smelter company. Since 1969, all base
metal and Ag mining activities were closed down. There are, however, still ore reserves of
about 4,868,500t of ore (averaging 3.2 wt. % Pb, 4.5wt. % Zn, 1.7wt. % As, and 72g/t Ag) in
the central and southern part of the Freiberg district.
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2.3 History of Mining in Freiberg
The Freiberg camp is situated in Germany at the northwestern edge of the Erzgebirge (Ore
Mountains in English). Most of the historical and geological information on the camp contained
here is from (Cotta 1870; Phillips 1884; Bernard et al. 1968; Lieber, & Leyerzapf 1986;
Baumann 1994).(Lieber, & Leyerzapf 1986), summarized the early history and significance of
the camp as follows: Mineral collectors throughout the world are well acquainted with the
beautiful silver minerals from Freiberg, Saxony. Intensive exploration and mining were carried
out and an increasingly large number of silver veins became known. The district grew to 20
kilometers north-south and 10 kilometers east-west, 200 square kilometers virtually covered
with mining operations.”
Miners from Rammelsberg and the Harz Mountains commenced work at Freiberg in 1168 after
native silver was noticed in a cart track by men transporting salt to Bohemia. Silver mining was
flourishing by 1181 and it was designated as a ‘free city’ in 1221. Activity declined after the
easy surface ore was removed, but a second period of prosperity began in the 14th century after
drainage was driven beneath the old mines to prevent flooding. The scope of the water problem
is indicated by the 2,100 horses and 250 miners who were kept busy lifting water to surface in
1569. Production was often disrupted by frequent regional problems such as wars and plagues
that will be discussed later in connection with the Rammelsberg mine.
A third period of intensive activity took place from 1750 through the 1800s. Most of the ore
was obtained from narrow, short veins, although others up to five kilometers long and a meter
wide were also mined. By 1900, only 28 mines remained active and they closed with the
outbreak of the Great War in 1914. A few mines operated temporarily in 1937 and after World
War II, but the last mine closed in 1969. Total historic silver production has been reported as
about 5,250 tonnes (Lieber & Leyerzapf, 1986), 5,700 tonnes (Freels et al., 1995.), and greater
than 7,000 tonnes (Beaudoin & Sangstar, 1992). In addition to silver, Cu, Pb, Zn, As, pyrite,
and small amounts of Au, U, Cd, Ge, In, Bi, and Sn were also produced.
The Freiberg vein swarm is hosted by an Upper Proterozoic and Cambro-Ordovician
sedimentary sequence that was metamorphosed into a gneiss dome. Most of the silver was
present as fine disseminations in argentiferous galena. Common silver minerals were native
silver, argentite, polybasite, pyrargyrite, stephanite, miargyrite, and tetrahedrite. The latter,
called ‘grey copper’ by prospectors, or fahlore (fahlerz in German), was probably the most
important. It is a complex mineral in which Ag and Cu can substitute for each other. A rare
variety of tetrahedrite, in which the amount of Ag exceeds that of Cu, was named freibergite
after the town. Unfortunately, no information was found in English on the silver content of the
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freibergite at Freiberg. At the Keno Hill camp, Yukon, for comparison, freibergite returned
assays as high as 25.5 weight % (255,000 g/t, or 7,500 oz/ton).
One of the most noteworthy events in the history of the city was the founding of the Freiberg
School of Mines (also referred to as the Mining Academy; Bergakademie in German) in 1765
(Phillips gave the date as 1702). It grew into the premier mining school in Europe, drawing
students from all over the world, and soon became famous for the study of vein deposits,
including important theories on their genesis. In the words of (Baumann, 1994). “Wherever
mining specialists and metallurgists meet, the name of Freiberg will be known to them. All over
the world, this name is associated with the scientific and technological achievements of
generations of scientists and mining engineers which for centuries have been part of the cultural
heritage of mankind” (Baumann 1964).
In order to better understand the complex relationship between mineralization and individual
veins, several classification systems, based on paragenesis, were developed at the School of
Mines over the years. The first systems were presented by Charpentier in 1778 and Werner in
1791. The most recent is Baumann’s widely respected 1964 classification that divided the
mineralization contained in 1,100 veins into nine ‘ore associations’ according to their
mineralogy, relative age, and vein orientation. That allowed the ore formations to be subdivided
into five that accompanied the Hercynian orogeny (320 to 280 Ma), and four later ones that
were dated between 250 and 30 Ma. Isotopic studies and age dating showed that a granitic
pluton that outcrops on the eastern margin of the camp is not genetically related to the vein
mineralization, which was derived from the metasedimentary host rocks.
Whereas Freiberg is essentially a primary silver camp that produced other metals as by-
products, several other mining camps are present in the Erzgebirge in which silver was
historically important but not as dominant. These include, on the Czech side of the Erzgebirge
(called the Krušnéhory), Jachymov (Joachimsthal), which was discovered in 1516, and later
became important as a producer of uranium (Cathro, 2005). On the German side, Schneeberg,
Annaberg, Marienberg, and Johanngeorgenstadt are also noteworthy examples. According to
(Freels et al., 1995.), total production on the German side of the border was about 8,000 tonnes
of Ag and 270,800 tonnes of Pb, and about 2,000 tonnes of Ag and 29,000 tonnes of Pb from
the Czech side of the Erzgebirge.
2.4 Characterization of the Davidschacht mine tailings
According to Mostafa, (2011) since the past 800 years, the polymetallic sulfide deposits of
Freiberg have been mined for silver, lead, copper, and zinc (Ag-Pb-Cu-Zn). The host rock in
the Freiberg district includes gneiss, mica-schist, and amphibolite (Baumann et al., 2000). The
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Late Variscan polymetallic sulfide mineralization is characterized by two types of ore para-
genesis. The first ore para-genesis includes sulfides and quartz with some carbonates formed
during hydrothermal reactivation, whereas the later one results from pre-deposition of sulfides,
carbonates and/or barite (Tichomirowa et al., 2002). The David-shaft mine tailings
impoundment is located to the north of its shaft and has an artificial dam downslope to the
North and East (Baumann et al., 2000; Tichomirowa, 2001; Tichomirowa et al., 2002). See Fig.
1. The tailings were deposited from 1951 to 1964. Most of the tailings materials originate from
the mining of ore from the first ore paragenesis (pyritic lead formation ‘Kb’, which is a quartz-
bearing As(–Au)–Zn–Cu(–In–Cd)–Sn–Pb–Ag–Bi–Sb ore, containing arsenopyrite,
pyrite/marcasite, pyrrhotite, Fe-rich sphalerite, stannite, chalcopyrite, cassiterite, tetrahedrite,
bornite, and galena (Mostafa, 2011). Quartz is the main gangue mineral, which also contains
small amounts of carbonates such as calcite, dolomite, siderite, and rhodochrosite (Seifert et al.,
2006). Limestone from Hermsdorf was added to the impoundment. The feed was mainly done
from the dam, but also from the west, using pre-separated coarser material as a wall (G.E.O.S.
report, 1993). During the spilling processes, fractionations in grain size and mineral content
developed at the spigot point along and across the spilling direction (Robertson, 1994).
Laminae stratification developed, each one being different in grain size and composition. The
impoundment covers a surface area of 7.5 ha and reaches a height of 60 m. The volume of
tailings material stored at this site was estimated to be approx. 1.3 Mt (G.E.O.S. report, 1993).
The average metal content of the heap material was determined to be 0.25 wt. % Pb, 0.24 wt. %
Zn, and 5.57 wt.% S (G.E.O.S. report, 1993) .The tailings impoundment was partly covered
with coarse sand, topsoil (thickness of cover: 0–0.2 m) and plants (Mostafa, 2011). The tailings
impoundment contains oxidized layers and hardpans at the western flank, and generally also at
the top of the impoundment below the plant cover, which indicates that the top soil was added
after oxidation had begun (Mostafa, 2011). The colors range from dark orange to dark
brownish, and from violet-whitish gray to dark gray (Mostafa, 2011). Environmental
contamination may occur due to rock drainage, exhalations, as well as wind transport of
aerosols, dust, and fines, and sometimes dam failure (Mostafa, 2011).
After extraction of the economically important minerals from the sulfide ores by flotation, a
large volume of sand- to silt-sized residual material is usually transported in the form of a
suspension to tailings impoundments for final deposition (Blowes et al., 1995; Robertson,
1994). After deposition, these materials are affected by various alteration and diagenesis
processes. Sulfate, ferrous iron, and other metals and metalloids, leaches and percolates into
groundwater or rivers (Johnson et al., 2000; Blowes et al., 1995; Courtin-Nomade et al., 2009).
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The interaction of sulfide-bearing tailings with water and oxygen causes the formation and
release of acid rock drainage, which is strongly enriched in sulfate, ferrous iron, and other
metals and metalloids, into groundwater or rivers (Blowes et al., 1990;Johnson et al., 2000;
Courtin-Nomade et al., 2009). In addition, the finest particles may spread out by wind or by
exhalation of volatile products (Rammlmair et al., 2000; Rammlmair, 2000). In some sulfide-
bearing mine tailings, an interesting feature can be observed as a result of
oxidation/cementation processes, namely the formation of hardpans or cemented layers
(Thornber et al., 1987; Blowes et al., 1995; McGregor et al., 1998; Rammlmair, 2000;
Graupner et al., 2007; Rammlmair et al., 2012).
Figure 2: Location map and aerial photograph (taken in 2007) of the study area, with the sampling location indicated by an
arrow (ATKIS® — DOP, © Staatsbetrieb Geobasis information und Vermessung Sachsen 2008). Modified after
(Mostafa, 2011).
The sulphides are oxidized at the surface, in an aerobic environment due to its unstable nature.
From the pits, then acidic water containing high sulfate can cause heavy metal concentrations
as pollutant loads (Blowes et al., 1990). According to (Blowes, & Jambor 1990) abandoned
mines have a very long-term effect on metal discharge which increases within the
environments, which in turn is the major source of pollution (escaping mine water) and the
direct entry in flowing waters.
Additionally, smelting and mining ore processing are usually connected to regional dispersion
of metals on the earth's surface (For example, emissions, tailings). According to Schräber et al.,
(1990) the environmental impact of the trace elements around Freiberg and its region with
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heavy metals and arsenic is caused in this way, by mining, mineral processing and smelting.
Locally, this industry originated in the sequence of Centuries of recovery of Ag, Pb and Zn
from the Freiberg polysulfide Gang deposit (Fig. 1). The hydrothermally formed veins run
mainly sulphides of Fe, As, Zn, Pb, Cu and Ag. After the closure of the mine (1970) and the
decline of the mining industry (1990), it is mainly dumps, tailings and open Mines, from which
dissolved heavy metals and arsenic and shifted via the water path.
2.5 Hydrogeology and Hydrology of Freiberg and its region
The annual rainfall in humid Climate of Freiberg region is approximately 840 mm (Berrios,
1995). The Thickness of the base layer has good water permeability, which varies strongly
between 0 to several meters. It is well understood from a saturated groundwater zone in fissure
water aquifer of gneiss body (Berrios, 1995; Schräber et al., 1990). The Clefts in the broad sense
have very different properties. The high water absorption capacity of open mines relieve the
aquifer locally by the depression of groundwater level through flooding (Milde, 1973).
Additionally, they provide the leachate, groundwater, and intermediate drain the ideal
pedosphere pathways. The mine water is partly over old Stolln the Freiberger Mülde (320 m NN)
supplied. The deep Rothschönberger Stolln marked at 200 m above sea level, the Surface of the
ground water in the flooded part of the pit. It takes the flooding waters of the overflows of the
Freiberg mining and other parts of the pit deposit on and drained into the river Triebisch at
Meißen (Milde, 1973).
2.6 Climate
The area around Freiberg is mainly influenced by a continental climate, characterized by hot
dry summers and cold, wet winters. In 2008, a total rain precipitation of 945 mm/year was
reported with an average temperature of 21.3 °C. The climatic condition during the sampling
time period were collected from the weather station of “Reiche Zeiche”. (See Table 2)
Table 2: Showing the air-temperation and cumulative precipitation from Reiche-Zeiche weather station Freiberg during the
measuring time period in David-shaft mine dump (Source TU-Bergeakademie webpage).
Month/Year
T Max. (°C)
T Min. (°C)
Cumm.Precipitation
08/16
33.0
7.2
28.5
07/16
33.4
9.8
74.4
06/16
33.8
10.8
102.1
05/16
27.3
2.6
78.5
04/16
22.4
-0.8
35.9
03/16
14.9
-2.4
53.9
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2.7 Natural attenuation in acid mine drainage
The study of natural attenuation (NA) processes on Acid Mine Drainage (AMD) formation in
mine waste deposits is of great importance, because NA may counteract serious pollution
threats to the water systems (Graupner et al. 2007). Mobilisation of As, Zn and Pb from
metallic mine tailings is known to be induced by oxidative weathering of metal sulfides. For
example, oxidation of arsenopyrite (FeAsS) and Fe2+ bearing sphalerite ((Zn, Fe) S) results in
AMD containing H2SO4, Fe(III) as amorphous ferric oxyhydroxide precipitates, Fe(II) as
soluble Fe species, As(III) as arsenite (AsO33-), As(V) as arsenate (AsO43-), and Zn(II).
(Graupner et al., 2007).
Microorganisms like (Thiobacillus i.e. Fe-oxidizing bacteria) and (Metallogenium i.e Mn-
oxidizing bacteria ) can tolerate high concentrations of several trace elements and also they
catalyze sulfide oxidation (Blowes et al., 1995). Several contaminant attenuation processes in
mine waste deposits must be considered, like precipitation, sorption, and ion substitution. For
example, arsenate may precipitate as scorodite, FeAsO4.2H2O (Ehrlich, 2002), or more
commonly as ferric arsenate (Paktunc, & Dutrizac 2003; Paktunc et al. 2004), sorb to
amorphous ferric oxyhydroxide phases and clay minerals (Korte, & Fernando 1991) , or
substitute for sulfate in jarosite, KFe3(SO4)2(OH)6 (Paktunc, & Dutrizac 2003). Because
hardpans and cemented layers may consist of reactive secondary minerals, they are expected to
play a crucial role in contaminant attenuation.
Cemented, indurated layers in sulfide-bearing mine tailings (so-called hardpans) have been
studied for their physical, chemical and mineralogical properties (Blowes et al. 1995;
McGregor et al. 1998; Johnson et al. 2000; Courtin-Nomade et al. 2009; Courtin-Nomade et al.
2003; Mostafa 2011).
Field studies have reported on hardpans in e.g. Canadian tailings impoundments (Moncur et al.,
2009; McGregor et al., 1998). The thickness of the hardpans varied from a few cm up to
approximately 4 m. They consisted of ferrihydrite (Fe2O3.0.5H2O), gypsum (CaSO4.2H2O),
jarosite, lepidocrocite(y-FeOOH), melanterite (FeSO4.7H2O), and rozenite (FeSO4.4H2O.
Column experiments verified that hardpans that are situated between reactive tailings and cover
material, improved leachate water quality and reduced the rate of sulfide oxidation (Gilbert et
al., 2003). A combination of processes such as dissolution of primary mineral phases, transport
processes, and precipitation of secondary phases seems to be responsible for hardpan/cemented
layer formation in mine tailings.
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Pyrite [FeS2] is the most abundant metal sulfide associated with the Earth’s crust (Rimstidt, &
Vaughan 2003; Murphy, and Strongin 2009) and contributes significantly to the world’s acid
drainage through natural weathering or from anthropogenic activities. However, in many
mineral deposits, pyrrhotite [Fe1_xS] is also a significant contributor of acid drainage. The
oxidation of Fe-sulfide minerals and the subsequent generation of acidity may lead to
destructive impacts to receiving ground and surface waters (Blowes, & Jambor 1990;
Nordstrom, & Alpers 1999; Johnson et al. 2000; Levings et al. 2005; Moncur et al. 2005;
Moncur et al. 2006.). Low-pH effluent is the primary concern in wastes from sulfide-bearing
metalliferous deposits where potentially toxic metals and metalloids are solubilized and become
mobile in the low-pH pore waters.
2.8 Mineralogical and geochemical behavior of Mine Tailings
The relative resistance of various sulfide minerals to oxidation in tailings impoundments
has been documented previously (Jambor, 1994; Blowes et al., 1998; Plumlee, 1999; Gunsinger
et al., 2006). An updated version of the relative resistance, as observed by optical microscopy
of field samples from several tailings sites is presented in Table 4. The listing serves as a guide
to the susceptibility of the sulfide mineral to oxidation where the textures and grain sizes are
similar. It is also important to recognize that: (i) a ‘persistence’ effect may be present and (ii)
the order applies to primary minerals. An example of the persistence effect would be the
opposite behaviors of galena [PbS] and sphalerite during oxidation. Although exceptions are
common in carbonate-rich environments, where the replacement of Fe-bearing sphalerite is by
Fe oxyhydroxides (Bertorino et al. 1995; Fanfani et al. 1997; Boulet, & Larocque 1998) or Fe
oxyhydroxides and sulfur (Jeong, & Lee 2003.), in sulfate-rich systems derived from sulfide
mine wastes that generate acid drainage, the dissolution of sphalerite typically occurs without
the formation of alteration rims that partly or completely pseudomorph the sphalerite.
The solubilization of sphalerite typically occurs by particle-size reduction rather than
replacement by secondary minerals. Sphalerite dissolution and the subsequent precipitation of
smithsonite[ZnCO3] has been suggested as a control for dissolved Zn concentrations
(Nordstrom, & Alpers 1999; Bain et al. 2001; Malmstrom et al. 2008), however, secondary
smithsonite has not been identified in sulfide-containing tailings impoundments. The absence of
secondary smithsonite in sulfide tailings could be due to difficulties in identifying minute
masses of secondary smithsonite or due to the high solubility of smithsonite in low-pH waters.
Alternatively, Zn concentrations could also be controlled by the precipitation of other Zn
bearing minerals, such as Fe oxyhydroxides. The behavior of magnetite seems to be similar to
that of sphalerite, but because the magnetite content of most non-calcareous sulfide deposits is
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low, the first appearance of magnetite is typically below the zone of intense oxidation. The
‘persistence’ effect is demonstrated by galena, when compared to sphalerite, which forms a rim
of anglesite [PbSO4] during oxidation. Due to the lower solubility of galena, the formation of
secondary anglesite rims slows the progress of further replacement but does not completely
retard it. Therefore, although galena and sphalerite are similar in reactivity, galena may persist
in a strongly oxidized environment that has removed sphalerite. Similar alteration rim or
retardation applies to other minerals, such as pyrrhotite and arsenopyrite, except for enargite
[Cu3AsS4], where the effects are much less pronounced. The limitation concerning the
oxidation of primary minerals is marcasite [FeS2]. Laboratory experiments have shown a
similar (Wiersma, & Rimstidt 1984) or greater reactivity for marcasite than for pyrite (Rinker et
al. 1997; McGuire et al. 2001; Uhlig et al. 2001; Elsetinow et al. 2003) but the reaction rates
vary widely. The placement of marcasite in Table 3 refers only to primary marcasite of a
homogeneous texture and grain size like that of the associated pyrite. This condition is stressed
because marcasite is commonly a secondary mineral that forms rims and pseudomorphs after
pyrrhotite in the early stage of oxidation (Blowes, & Jambor 1990). This type of marcasite is
typically heterogeneous on an lm or finer scale, and in this form it seems to be a metastable
transitional mineral that very readily alters to goethite (Jambor, 2003).
Table 3: Schematic relative resistance to alteration of sulphides and magnetite in oxidized tailings (Moncur et al. 2009)
Pyrrhotite
Fe1-xS
Low resistance
Galena
PbS
Sphalerite
(Zn, Fe)S
Bornite
Cu5FeS4
Pentlandite
(Fe, Ni)9S8
Arsenopyrite
FeAsS
Marcasite
FeS2
Pyrite
FeS2
Chalcopyrite
CuFeS2
Magnetite
Fe3O4
Molybdenite
MoS2
High resistance
Table 4: Sulfide alteration Index (SAI) of Sheridon tailings (Blowes, & Jambor 1990; Moncur et al. 2009; Moncur et al. 2006.)
Index
Alteration
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Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
The stabilities of the various sulfide minerals can be illustrated by the sulfide alteration index
(SAI), see Table 4, which is a practical method of mapping the changes observed in the
appearance and disappearance of the sulfide minerals through a vertical profile of a tailing
impoundment.
The SAI was first constructed by (Blowes, & Jambor 1990) for a series of cores through the
Waite Amulet tailings impoundment near Noranda (Quebec, Canada). An example of a SAI
for the tailings from the Sherritt–Gordon mine at Sherridon (Manitoba, Canada) is described
and illustrated in Table 4. At both sites the ore deposit consisted of volcanogenic massive
sulfides and the tailings contain pyrite and pyrrhotite. The Sherridon site is used to illustrate
the mineralogical and geochemical changes that typically occur in a sulfide oxidation profile.
The Sherritt–Gordon mine at Sherridon operated from 1931– 1932 and from 1937–1951,
during which 7.7 Mt of pyritic ore grading 2.45% Cu, 2.97% Zn, 19.9 g tons-1 Ag and 0.62 g
tons-1 Au were milled, however a Zn concentrate was not produced until 1942 (Farley 1949).
The sulfide assemblage consisted of mainly pyrite and pyrrhotite with lesser amounts of
chalcopyrite, sphalerite, and minor amounts of only a few other minerals, including
arsenopyrite [FeAsS], cubanite [CuFe2S3] and local occurrences of galena. The unsaturated
zone above the hardpan has a high SAI, is depleted in sulfides and carbonates, and the pore
gas-phase O2 concentrations show a rapid downward decrease to a depth of 0.5 m that reflects
O2 consumption by sulfide oxidation.
10
Almost complete oxidation of sulfides; traces of chalcopyrite ± pyrite
9
Only sparse pyrite and chalcopyrite; no pyrrhotite or sphalerite
8
Pyrite and chalcopyrite common, but chalcopyrite proportion higher than
normal possibly because of pyrite dissolution; no pyrrhotite or sphalerite
7
Pyrite and chalcopyrite proportions normal; pyrrhotite absent but sparse
sphalerite present
6
Pyrrhotite absent but sphalerite common
5
Pyrrhotite represented by marcasite pseudomorphs
4
First appearance of pyrrhotite, but only as remnant cores
3
Cores of pyrrhotite abundant
2
Well-developed cores of pyrrhotite, with narrower alteration rims;
replacement by marcasite decreasing, and pseudomorphs are absent
1
Alteration restricted to narrow rims on pyrrhotite
METHODS 17
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
3 Methods
For the present investigations, 4 different sites were selected on the David-shaft mine tailing
(see Fig. 1). These sites have different vegetation, soil texture, trees and tailing impoundments.
Each study site was characterized by homogeneous chemical and physical substrate properties
but differing vegetation structures. At each site the impact of vegetation on the chemical
composition of the soil solution was investigated along a transect characterized by a changing
density of vegetation and species composition. During the investigation time period, soil
solution and soil samples were collected. First, soil samples were taken at different soil depths,
followed by identification of vegetation types at different sites. The vegetation types were
identified, to be growing on a homogenous soil. Lastly, at each site (and each vegetation type)
suction cups were installed at different soil horizon. From these suction cups, soil solution was
sampled on six (6) different occasions starting from the first sampling date to the last sampling
date, with an interval of one week for the first-three sampling dates i.e., 158, 172, 179 days of
the year (doY) and two-week interval for the last three dates (i.e., 186, 200, 214 doY)
respectively. Suction cups were installed at two different soil depths i.e. Upper depth of about
(≤ 20cm) and a lower depth of about (20 to ≥ 50cm) with different codes assigned to the
collection tubes (e.g. IaA1, IbA2, IcA3 and IaD1, IbD2, IcD3) where I, II, III, IV represents the
Location of the sites, while a, b, c represents the vegetation types, whereas A and D represents
Horizon (i.e. Upper and Lower) and finally 1,2,3 represents the replication for different horizon
(e.g IaA1, IaA2, IaA3). These codes were assigned to avoid error due to complexity of the data.
With respect to vegetation structure, at site I, the sparse vegetation (Vb) and dense vegetation (
Vc) were already present from the outset of the investigation, while areas without vegetation
(Va) was artificially created by removing the vegetation layer. At the other sites (i.e., from site
2 to site 4), as at the time of investigation period, the different vegetation types occurred
naturally. Vegetation (Va) signifies that the area has no vegetation or lacks vegetation cover,
while vegetation (Vb) signifies sparse or average covering, whereas vegetation (Vc) signifies a
high vegetation density. The presence of shrubs and trees were designated for sites II and III.
The composition of species at each site is shown in Table 5.
Brief description of site 1: In site 1, the vegetation was predominantly grassland and suction cups
for the sampling of soil water, were installed in areas without vegetation (artificially removed -
Va), in areas with a sparse layer of grasses (Vb) and areas with a dense layer of grasses (Vc).
METHODS 18
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Brief description of site 2: In site 2, the vegetation were mixtures of grassland, trees, shrubs and
bare vegetation, suction cups for the sampling of soil water, were installed in areas without
vegetation (not artificially removed - Va), in areas with a sparse layer of grasses (Vb) and areas
with a dense layer of grasses, trees, and shrubs (Vc).
Brief description of site 3: In site 3, the vegetation were mixtures of grassland, trees, shrubs,
suction cups for the sampling of soil water, were only installed in areas with a dense layer of
grasses, trees, and shrubs (Vc).
METHODS 19
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Brief description of site 4: In site 4, the vegetation was predominantly bare vegetation and
suction cups for the sampling of soil water, were installed in areas without vegetation (not
artificially removed - Va). See Table 5.
Table 5:Soil and vegetation composition found in Davidschacht mine-dump and its environment.
Sites
Soil and Vegetation Composition found within different Site.
CODE
I
Combination of sandy soils and highly deposition of mine tailing.
Presence of vegetation, predominantly grassland.
Betula Pendula, Populus tremula, Pyrus communis, dactylis glomerata,
Arrhenatherum elatius, Elymus repens, phalaris arundinacea,
Ia, Ib, Ic
METHODS 20
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
equisetum arvense, gallium album, tenacetum vulgare, deschampsia
flexuosa, festuca rubra.
II
Presence of trees, vegetation and cemented or compacted sandy clay.
Agrostis capillaris, Betula Pendula, Pinus Sylvestris, Quercus robur,
Holcus lanatus, deschampsia flexuosa. hypochoeris radicata, populous
tremula.
IIa,IIb,
IIc
III
Presence of trees, vegetation and fine - coarse grain sandy soil.
Agrostis capillaris, Betula Pendula, Pinus Sylvestris, Quercus robur,
festica rubra, salix caprea, lotus Corniculatus, deschampsia flexuosa.
IIIc
IV
No vegetation and fine grain sandy soil
Agrostis capillaris, Calluna vulgaris, Rubus fruticosus, daucus carota,
hypochoeris radicata, rumex acetosella, tussilago farfara,
scorzoneroides autumnalis, deschampsia flexuosa, Betula Pendula,
Pinus Sylvestris, Quercus robur, lotus Corniculatus
IVa
Several methods were employed during the data collection. At each site soil samples were
collected to characterize selected chemical substrate properties. The methods for sample
preparations and measurements are given in section 3.2.3. The on-site parameters like pH and
electrical conductivity in the soil solution were measured at all the investigated sites (I-IV)
using specific devices like, electrode kinick Portatest 655 pH and Conductivity-Meter LF 39
respectively (see Appendix B1 and B3).
3.1 Drying and determination of the dry mass content
Fresh soil is mainly used for the measurement of soil nutrients in soil while dry soil is used for
the determination or measurements of trace elements in the soil. The collected soil samples
were dried for all subsequent processing and analysis steps as well as the determination of the
dry mass content (TM content) [%].
To determine the TM content, 10 g of the soil samples to be investigated were weighed into
paper sachets and their fresh weight (FW) in [g] was recorded. The samples were then dried at
60 ° C. in the drying cabinet to constant weight. In addition, 20 g of the soil samples were
weighed into paper bags, the FW of which was recorded, and the samples dried to constant
weight at 105 ° C. The dry mass [g] of the samples was determined and the TM content was
determined. The dried and homogenized sample at 60°C were subjected to sequential extraction
and used to determine the cation exchange capacity. The dried and homogenized at 105°C were
METHODS 21
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
subjected to a total digestion and were used to determine the organic content. The element
concentrations were measured using ICP-MS see Chapter 4 and 5.
3.1.1 Grinding and homogenizing
Since the analysis of the element concentrations in the soil samples using ICP-MS requires the
transfer of the biological solids in solution, the samples were physically processed. For this
purpose, the samples (dried at 60 ° C or 105 ° C.) were first ground using a mortar and then
sieved. The fine-grained, homogenized samples were stored in plastic tubes.
3.1.2 Organic content
For the determination of the organic portion, approximately 1 to 3 g of lutro-dried soil sample
were weighed. The annealing was then carried out at 600 ° C. over a period of one hour. After
annealing, a cooling to room temperature and the weighing took place. The organic substance
was calculated according to the following formula:
GV - Loss on ignition, organic matter [%]. LG - Empty weight of incandescent [g]
TG - dry weight with incandescent [g]. GG - weight after annealing with incandescent [g]
3.1.3 Total decomposition / melting digestion
The total breakdown of soil samples was based on Alfassi and Wai, (1992). For the digestion,
0.5 g of the homogenized soil sample dried at 105 ° C. were weighed into a nickel crucible. For
the evaluation of the method, an appropriate laboratory-internal reference sample with known
element concentrations was additionally carried along with each decomposition. This was
followed by the addition of 2 g of melting agent (mixture of Na2CO3 and K2CO3 in a ratio of 1:
1) and homogenization of the mixture. The sample was melted for 30 minutes at about 900°C in
the melting furnace and after a short cooling phase, an addition of 0.5 M citric acid and 2 M
HNO3. The mixture was stirred until it had completely mixed. The thus dissolved sample was
transferred into a 50 ml plastic tube and filled to 50 ml with distilled water. The sample, were
then diluted in the ratio of 1:50, and further treated with an internal standard (each 10 μg·L-1 Re
and Rh in concentrated HNO3) and was available for measurement by means of ICP-MS.
3.2 Soil Solution and Soil Samples
3.2.1 Sampling of Soil Solution
During the sampling of soil solution, 47 plastic suction cups with polyamide membrane from
(eco-tech Bonn, Germany) were installed at two different soil depth of approximately 20cm
(HA) and 50 cm (HD) respectively. After the installation of the suction cups a negative pressure
of 60 kPa was immediately applied to maintain a constant pressure over head. The suction was
METHODS 22
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
maintained over the duration of the experiment and was only interrupted for sampling soil
solution for analysis by ICP-MS. The buried suction cups were further protected from sunlight
to avoid drastic changes on the temperature. From these polypropylene bottles, soil solution for
the first three time periods (T1–T3) were sampled on weekly basis and the last three time
periods(T4-T6) were sampled with a space of two-week interval.
3.2.2 Collection of Soil Solution
Percolated or infiltrated soil-water solutions were collected from different encoded collection
tubes. These soil-water solutions were further transferred into laboratory 50 ml and 10 ml tubes
which were used for nutrient content (NO3-, PO43- and NH4+) and ICP-MS analysis respectively.
The samples were stored in refrigerator at different temperatures. The 50 ml samples were
frozen at -20°C to avoid the alteration of the composition of nutrients, while the 10 ml samples
were further acidified with 100 μl of conc. HNO3 (nitric acid) and stored at about at 4°C for
trace elements analysis. Due to the unstable nature NO3-, PO43- and NH4+, it is advised to store
the samples under dark and cool temperature to avoid distortion of its unmeasured content.
3.2.3 Preparation of Soil Solutions for ICP-MS Measurement
Each of the soil solution samples, were carefully prepared by adding 1ml of the soil solution to
9ml of de-ionized (distilled water), together with 100 µl of internal standard composition and
finally transferred into a new 10ml tube and thoroughly shake. The samples were then analyzed
by ICP-MS (Xseries 2, Thermo scientific) and the results are well discussed in Chapter 4 and 5.
3.2.4 Collection of Soil Samples
The collection of soil samples was very important because our experiment design assumes
homogeneity of soil properties among vegetation types within the study area. For this purpose,
2 drill stock samples were collected at each site per vegetation unit. In addition, a soil sample
was taken from the first horizon and transferred into PE bags for element and nutrient
cleansing. A total of 3 horizons were found for sites II to IV. The first horizon was the soils of
sandy loamy silt (Uls) with reddish coloration, the second horizon was a weak silty sandstone
(Ut2) with greyish coloration and the third horizon is characterized as weak clay (Sl2). The
sampling of soil samples was carried out with the help of a Pürckhauer drillstock of approx. 20
cm depth. From each of the relevant 55 plots soil (50 to 70 g) was removed from the soil at the
beginning of the trial (117th doY) and trial end (125th doY) at different places and filled into a
Polyethylene (PE) bag. In order to characterize the present soil substrate and to investigate
homogeneity regarding the nutrient content (nitrate, ammonium and phosphate) and the element
concentration, a total of 55 soil samples were taken during the experiment (117th and 125th
METHODS 23
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
days of the year). All samples taken from the soil were stored in the freezer at -20°C until
further use.
3.2.5 Trace element content determination
The concentrations of selected elements were determined both in the soil samples and the soil
solution. Of particular interest were the elements of lead (Pb), zinc (Zn), cadmium (Cd) and
arsenic (As), as well as the micronutrient iron (Fe), phosphorus (P), manganese (Mn), copper
(Cu), germanium (Ge) and the rare earths (La, Er, Nd, Gd) were investigated. The element
contents were determined by ICP-MS (Thermo Scientific, XSeriesII). For the correction of
matrix effects 0.1 ml of internal standard consisting of rhenium, rhodium and nitric acid (supra
pure) were added to the samples during the measurement.
3.3 Determination of phosphate, and mineral N in soil samples and soil solution
Using the spectrophotometer SPECORD 30 from the manufacturer Analytik Jena the nutrient
contents were determined. Soil eluates had to be prepared in advance from the respective soil
samples. Phosphate was determined, by measuring 10 g of soil and adding 100 ml of Ca-lactate
solution, it was properly shaken and allowed to settle for about 2 hours. To prepare the eluates
for ammonium determination, 10 g of soil were also weighed in and 100 ml of 1M KCl solution
were added, and the mixture was shaken for 2 hours. For the eluates intended for nitrate
determination, 10 g of soil were mixed with 100 ml of distilled water and shaken for 2 hours. If
necessary, the soil eluates thus produced were then centrifuged to lower suspended matter. The
pH was then measured with the electrode knick Portatest 655 pH meter and the conductivity
with Conductivity Meter (Meinsberg LF 39) in the eluate for nitrate.
3.3.1 Determination of phosphates in soil solution
The phosphate determination was carried out by molybdenum blue according to DIN EN ISO
6878. The soil eluates obtained by the DL method were diluted 1: 1 with distilled water before
the start of the measurement; 4 ml of bottom eluate were made up to 8 ml with distilled water
and then 0.2 ml of reagent 1 (ascorbic acid, 100 g/l) was added and vigorously shaken.
Thereafter 0.4 ml of reagent 2 previously prepared from ammoniumheptamolybdenum-
tetrahydrate (26 g/l) and potassium antimony (III) oxide tartrate hemihydrate (700 mg/l) in 60%
sulfuric acid was added to the solution. The blank was mixed with 4 ml of the working solution
and 4 ml of distilled water and, as above, with the above-mentioned reagents. After about 10
minutes to about 30 minutes after preparation, the extinction was measured with the SPECORD
30 spectrophotometer at 880 nm.
METHODS 24
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
3.3.2 Determination of mineral N
For the analysis of mineral N, NO3- and NH4+ were extracted from soil samples with deionized
water and 1 M KCl, respectively, and photometrically determined according to Bolleter et al.,
(1961) and Hartley and Asai (1963). Plant available mineral (N) in soil was calculated as the
sum of NO3--N and NH4+-N. The nitrate content was determined by means of 4-nitro-2,6-
dimethylphenol according to DIN 38405-9. To this was added 0.5 ml of bottom eluate with 4
ml of the first reagent, consisting of concentrated sulfuric acid and concentrated phosphoric
acid in a ratio of 1: 1. Then, 0.5 ml of the second reagent consisting of 1.2 g/l of
dimethylphenol in 100 ml of concentrated acetic acid was added. The sample was shaken
vigorously. The required blank value was blended from 0.5 distilled water and as described
above, with reagent 1 and 2. After 5-15 minutes of waiting, the extinction was measured at 338
nm wavelength.
The determination of the ammonium content was carried out via indophenol in accordance with
DIN 38406/5. From the prepared soil eluate, 10 ml were removed and mixed with 1 ml of
reagent 1, which consisted of sodium salicylate (130 g/l) with trisodium citrate (130 g/l) and
sodium pentacyanonitrosyl ferrate (968 mg/l), and then shaken. After an hour of waiting time,
the extinction was measured at a wavelength of 655 nm.
3.3.3 ICP-MS
With the help of the ICP-MS, low element concentrations in samples can also be analyzed. It is
a very strong analytical method whose detection limit for Ge is 0.01 μg /l and for the SE is
0.001 μg/l. The device XSERIES 2 from Thermo Fisher Scientific (Figure 3), which contains
an inductively coupled plasma with a quadrupole mass spectrometer, was used for the analysis
of plant and soil samples as well as soil solutions. The technical data for the device are listed in
Table (Annex). In addition, an overloading of the plasma is thus pre-determined. An internal
standard of 10μg /l rhenium (Re) and rhodium (Rh) was then added to each sample. All values
obtained were related to the concentrations of the internal standard, thus counteracting the
fluctuations in the concentrations which occur over longer measurements, and the matrix
effects are largely circumvented. After homogenization of the samples, the sample tubes were
placed in the autosampler. Before the samples were measured, the ICP-MS instrument was
calibrated with standard solutions of different elements (P, Mn, Cu, Zn Fe, As, Pb, Cd, Ge, Gd,
La, Er and Nd) in various concentrations. The final measurement of the samples was
automated.
METHODS 25
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 3: ICP-MS-Meter XSERIES 2 at the Institute for Geology. Chair of Hydrogeology, Freiberg with autosampler
3.4 Statistical evaluation
The data were evaluated using Microsoft Office Excel 2013 and Statgraphics Centurion XVI.
For all analyzes a significance level of p <0.05 was determined. In order to investigate the
course over time at upper horizon and lower horizon and vegetation, a multiple-sample
comparison (ANOVA) was carried out. The effect of time at different sites was evaluated
comparing the concentrations of elements at a certain sampling date. In order to determine
the strength of a correlation of two variables, spearman rank correlation was used. These
correlation coefficients (rS) range between -1 and +1 and measure the strength of the
association between the variables. Also shown in parentheses is the number of pairs of data
values used to compute each coefficient. The third number in each location of the table is a
P-value, which tests the statistical significance of the estimated correlations. P-values below
0.05 indicate statistically significant non-zero correlations at the 95.0% confidence level.
RESULTS 26
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
4 Results
In this chapter, results from soil samples and soil solutions from the study area (Davidschacht
mine-dump) were analyzed. Initially, the element concentrations in the soil samples were
measured only in two sampling dates (i.e. 117 and 125doY), while the element concentrations
from soil solution were measured in six sampling dates (i.e. 158, 172, 179, 186, 200 and 214
doY) respectively. The influence of vegetation and horizon on the bioavailability and mobility of
trace elements in soils were analyzed (see chapter 5). This is followed by the consideration of
the temporal change in the element concentrations as well as the pH value in the soil solutions
taken weekly for the first to third sampling dates (158, 172 and 179 doY) and in two weeks’
interval for the final last three sampling dates (186, 200 and 214 doY). Finally, it is investigated
whether and to what extent the vegetation types influenced the concentration of trace elements
on the soil solutions with respect to the temporal changes.
The plotted diagrams, for the concentration of Ge and REE were very similar in their properties
(see chapter 4.3.1 to 4.35 and fig 12, 13 and 14), La and Nd were chosen as representative for
the LREE and Gd and Er as representatives for the HREE.
The focus was on Ge and the REEs (La, Nd, Gd and Er). In addition, some important plant
nutrition elements (P, Zn, Fe, Mn and Cu) as well as relevant toxic heavy metals and trace
metals (As, Pb, Cd,) were investigated. The supporting data for both the soil samples and soil
solution are shown on the appendix.
Table 6: Onsite-parameters of the soil samples for Upper horizon, and Lower horizon for the two measuring time [117 to 125.
DoY]
For the calculation of the mean values of the soil samples, the mean values differs for each site,
both at the upper and lower horizon. For the upper horizon, the mean values were calculated as
Element Concentration [mg/kg]
Mean Value ± Standard deviation
Upper Horizon
Site
1
2
3
4
pH
4.3 ± 0.37
3.7 ± 0.07
4.2 ± 0.69
5.5 ± 0.19
EC (µS/cm)
88.41 ± 49.6
229.2 ± 155.4
445.6 ± 421.2
117.9 ± 95.1
Temp (ᵒC)
20.6 ± 0.21
20.6 ± 0.45
20.71 ± 0.38
20.5 ± 0.4
TDS (mg/l)
57.4 ± 32.2
149.0 ± 101.0
289.6 ± 273.8
76.6 ± 61.8
Lower Horizon
pH
4.9 ± 0.47
5.2 ± 0.90
4.7 ± 0.89
6.8 ± 0.19
EC (µS/cm)
308.4 ± 182.4
228.5 ± 132.8
653.3 ± 119.2
53.5 ± 14.7
Temp (ᵒC)
20.6 ± 0.21
20.5 ± 0.25
21.4 ± 0.25
20.7 ± 0.09
TDS (mg/l)
200.5 ± 118.5
148.5 ± 86.38
424.6 ± 77.5
34.8 ± 9.6
RESULTS 27
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
follows (site1 n= 7, site2 n= 6, site3 n= 6, site4 n= 4), while that of the lower horizon are as
follows (site1 n= 8, site2 n= 17, site3 n= 3, site4 n= 4). A strong agreement and relationship
were seen in the pH values for both soil samples and soil solutions both at upper and lower
horizon during the investigation time. In upper horizon, the lowest pH value occurred at site 2,
with a pH value of 3.7, while the highest pH value was at site 4, with a value of 5.5.
In lower horizon, the lowest pH value occurred at site 3, with a pH value of 4.7, while the
highest pH value was at site 4, with a value of 6.8. The total dissolve solute was calculated from
the electrical conductivity values (i.e. TDS = EC * 0.65). In otherwise, increase in EC, increases
TDS and vice versa. In upper horizon, the values of EC and TDS shows the following trend site
3 ˃ site 2 ˃ site 4 ˃ site 1, whereas in lower horizon site 3 ˃ site 1 ˃ site 2 ˃ site 4. See Table 6.
4.1 Trace Elements in soil samples chemistry from the study area.
A comparison of the measured concentration of soil samples from David-shaft mine dump and
that of the Dutch environmental standards was compared to see the difference in the
concentration values, of some selected trace elements. The high concentration values, of the
study area, was because of the past anthropogenic activities within Freiberg and its environment
during the mining era. Table 7 shows the target values, natural background values and
intervention values, while that of Table 8, shows some of the selected trace elements in David-
shaft mine tailing. Arsenic concentrations are 100% or higher in all locations compared to the
above target and intervention standards. The soils of the study area show very high values for all
measured trace elements and therefore poses a major threat for the surrounding ecosystem and
groundwater. Water from the surface, through infiltration, percolates through the soil horizon to
contaminate the groundwater table. Since the concentration values of the measured soil samples
exceeds the intervention values (see table 7), it is very vital to remediate and reclaim the
contaminated and polluted soils of David-shaft to reduce its negative impact to the ecosystem
and groundwater. Kobayashi, (1971) reported that some of the first actions for soil remediation
were in Japan, where an excess of soil Cd was removed by repeated treatment with EDTA
solution and lime (the Cd content of the surface soil decreased from 27.9 to 14.4 mg/kg).
According to Rulkens et al., (1995) five main procedures for contaminated soil cleanup are as
follows (a) removal of contaminants by molecular separation (i.e. extraction and desorption
treatments) (b) removal of particulate contaminants by phase separation. Froth flotation and
other extractive Treatments (c) removal of contaminants by chemical/thermal destruction. In situ
vapor extraction and other treatments. (d) Removal of contaminants by biodegradation of
substances containing trace metals. (e) Removal of contaminants by biological absorption
(phyto-extraction) or biological mobilization.
RESULTS 28
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Saxen et al., (1999) described most commonly used technologies as follows: soil flushing,
Pneumatic fracturing, solidification/stabilization, Vitrification, Electrokinetics, Chemical
reduction/oxidation, Soil washing and Extravagation, off-site disposal. At present, there is
extraordinary interest in bioextraction methods using bioremediation, phytomelioration, and
phytomining (Kabata-Pendias 2011; Kabata-Pendias, & Pendias 2000).
Table 7: Target values, soil remediation and intervention values, background concentrations soil/sediment, and groundwater for
metals. Values for soil/sediment have been expressed as the concentration in a standard soil (10% organic matter and
25% clay). Modified from www.esdat.net (Dutch environmental standards).
Metals
EARTH/SEDIMENT
(mg/kg dry matter)
GROUNDWATER
(µg/l in solution)
national
background
concentrations
target
value
intervention
value
target
value
national
background
concentratio
ns
target value
intervention
value
Arsenic
29
29
55
10
7
7.2
60
Lead
85
85
530
15
1.6
1.7
75
Cadmium
0.8
0.8
12
0.4
0.06
0.06
6
Zinc
140
140
720
65
24
24
800
Copper
36
36
190
15
1.3
1.3
75
Chromium
100
100
380
1
2.4
2.5
30
Cobalt
9
9
240
20
0.6
0.7
100
Mercury
0.3
0.3
10
0.05
-
0.001
0.3
Molybdenum
0.5
3
200
5
0.7
3.6
300
Nickel
35
35
210
15
2.1
2.1
75
Antimony
3
3
15
-
0.09
0.15
20
Barium
160
160
625
50
200
200
625
The target values indicate the level at which there is a sustainable soil quality. It also gives an
indication of the benchmark for environmental quality in the long term on the assumption of
negligible risks to the ecosystem. While the soil remediation and intervention values indicate
when the functional properties of the soil for human, plants and animal life (ecosystem), is
seriously impaired or threatened. They are representatives of the level of contamination above
which there is a serious case of soil contamination (RIVM). The intervention values for
groundwater are not based on any separate risk evaluation concerning the presence of
contaminants in groundwater but are derived from the values for soil/sediments (RIVM).
RESULTS 29
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Table 8: Concentrations of selected elements [mg·kg-1] in the soil samples for Upper horizon, and Lower horizon for the two
measuring time [117 to 125. DoY].
Locations
Concentrations in Upper Horizon [HA]
(mg/kg )
Concentrations in Lower Horizon [HD]
(mg/kg )
I
II
III
IV
I
II
III
IV
Phosphorus
4151
634
981
2271
1310
638
572
838
Iron
3304
4780
6066
3244
3908
3567
3822
3345
Manganese
1186
1428
1709
1324
947
1806
691
2106
Copper
376
272
825
251
313
406
436
259
Zinc
1097
230
1572
445
250
504
1219
616
Cadmium
8.54
2.53
40.4
4.01
3.18
7.31
4.38
8.71
Arsenic
1607
3367
4612
2646
3682
3654
4869
1829
Lead
2222
649
660
566
629
190
628
312
Germanium
1.78
1.11
1.90
1.12
1.07
0.93
0.96
0.96
Lanthanium
22.8
13.1
22.6
15.9
13.7
9.94
9.62
16.5
Neodynium
20.6
12.3
23.3
15.5
13.9
13.5
10.1
15.7
Gadolinium
4.17
2.53
4.69
3.37
3.00
3.36
2.17
3.48
Erbium
2.32
1.70
2.79
2.00
1.89
2.07
1.49
2.02
From Table 7 and Table 8, it can be clearly seen that the concentration of the selected trace
elements (soil samples), exceeds the target values and in most cases the intervention values. The
high values of the soil samples owe to the fact that the soil of David-shaft are highly
contaminated by the past mine activities as well as the influence from the mine dump and
tailings. The intervention values and target values for toxic elements like As, Cd and Pb can be
clearly seen from table 7 and 8.
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 4: Differences in pH values in upper and lower horizon, throughout the investigation period time (from 158 to 214 doY), in David-shaft mine tailings [where Va= no vegetation, Vb= sparse vegetation and
Vc = dense vegetation]. The figures are plotted with average mean [n = 3] and its standard errors.
3.3
3.8
4.3
4.8
5.3
150 160 170 180 190 200 210 220
pH Values
Time (Days of the year)
Upper Horizon (HA)
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S3Vc
3.2
3.7
4.2
4.7
5.2
5.7
150 160 170 180 190 200 210 220
pH Values
Time (Days of the year)
Lower Horizon (HD)
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S4Va
RESULTS
27
RESULTS 28
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
4.2 pH in soil solution
Soil pH is a measure of acidity or alkalinity of a soil. A pH of 7 is neutral. A pH below 7 indicates
that the soil is acidic, further lowering of the values increases the acidity. A pH above 7 indicates
alkalinity, with higher values representing increase in alkalinity of the soil.
For the Upper Horizon (HA), it can be clearly seen, that at upper horizon, the lowest pH values
occurred at site 2, in non- vegetation (Va) throughout the measuring time period, with values ranging
from 3.3 to 3.5, whereas the highest pH values occurred in dense vegetation (Vc) at site 3 (ref site for
upper horizon). The pH range at upper horizon is between very acidic to acidic. In lower Horizon
(HD), the highest pH values occurred at site 4, in non-vegetation (Va) (i.e., ref site for lower
horizon), it was significantly high at T2-T5 (172-200 doY), it is within the range of acidic to slight
acidic, whereas at site 1 and site 2, the pH values were significantly low with values ranging from
3.3 to 4.5. The lowest pH values occurred at Site 2 in non-vegetation (Va). (See fig 4 above).
Vegetation types showing highest and lowest pH values: In non-vegetation (Va), the lowest pH
values occurred at S2/HA/T3 and S2/HD/T6 with a value of 3.34 while the highest value occurred at
S4/HD/T5 with a value of 6.1. In sparse vegetation (Vb), the lowest pH value occurred in S2/HA/T6
with a value of 3.74 while the highest value occurred at S1/HA/T6 with a 4.67, whereas in dense
vegetation type (Vc), the lowest pH value occurred in S2/HD/T6 with a value of 3.74 while the
highest value occurred at S3/HA/T6 with a value of 5.3. See fig 4 above. Using Multiple-sample
comparison from Statgraphics Centurion XVII, pH was analyzed for statistical significance at 95%
confidence level. Considering the effect of vegetation on the Upper Horizon (HA), throughout the
measuring time intervals for T1-T4 (158-186 doY), the p-values for the on-site parameters shows no
statistical difference (p ˃ 0.05). While at lower Horizon (HD), the p-values shows a statistically
significant difference (p ˂ 0.05) between the pH values. See tab 8 and 9. Furthermore, considering
the effects of vegetation on the on-site parameters through time interval T1-T4, it can be seen that the
p-values shows no statistical significance difference, whereas that of site 2, through time interval T1-
T5, shows that the statistical difference in the pH values was influenced by Vegetation "b" and
Vegetation "c" (see table 8, 9 and 10).
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 5: Electrical Conductivity (EC) of the measured soil solution chemistry in both upper and lower horizon, throughout the investigation period time (from 158 to 214 doY), in David-shaft mine tailings
[where Va= no vegetation, Vb= sparse vegetation and Vc = dense vegetation]. The figures are plotted with average mean [n = 3] and its standard errors.
100
300
500
700
900
1100
1300
150 160 170 180 190 200 210 220
Ec. (µs/cm)
Time (Days of the year)
Upper Horizon (HA)
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S3Vc
300
500
700
900
1100
1300
1500
150 160 170 180 190 200 210 220
Ec. (µs/cm)
Time (Days of the year)
Lower Horizon (HD)
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S4Va
29
RESULTS
RESULTS 30
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
4.3 Electrical conductivity in soil solution
For the Upper Horizon (HA), Ec values in site 1 were higher in non- vegetation type (Va), followed
by sparse vegetation type “Vb” (except for T3 and T4), whereas the lowest EC values occurred at
occurred in dense vegetation type (Vc). At site 2, the EC values, were significantly higher in dense
vegetation type (Vc), followed by non- vegetation type (Va), whereas the lowest EC values occurred
in sparse vegetation (Vb), throughout the investigation time period. For site 3 (ref site), there was a
decreasing trend in the EC values, generally, the lowest values of EC occurred at upper horizon, in
site 3 (ref. site). For the Lower Horizon (HD), the EC values in site 1 were higher in sparse vegetation
(Vb), followed by dense vegetation (Vc), whereas the lowest EC values occurred in non-vegetation
(Va). At site 2, the Ec values, were significantly higher in non-vegetation (Va), followed by dense
vegetation (Vc), whereas the lowest values occurred in sparse vegetation (Vb). For site 4 (ref site),
there was an increasing trend in the Ec. (see fig 5, Page 29).
Vegetation types showing highest and lowest Ec values: In non-vegetation (Va), the lowest EC
occurred in S4/HD/T1 with a value of 585µS/cm while the highest value occurred at S2/HD/T1 with a
value of 1455.3µS/cm. In sparse vegetation (Vb), the lowest EC occurred in S2/HA/T4 with a value of
201µS/cm while the highest value occurred at S1/HA/T4 with a value of 1214µS/cm, whereas in
dense vegetation (Vc), the lowest EC occurred in S3/HA/T6 with a value of 122.9µS/cm while the
highest value occurred at S3/HA/T1 with a value of 1286.2µS/cm. see fig 5.
Using Multiple-sample comparison from Statigraphics Centurion XVII, electrical conductivity was
analyzed for statistical significance at 95% confidence level. Considering the effect of Upper
Horizon (HA), throughout the measuring time intervals for T1-T5 (158-186 doY), the p-values for
the electrical conductivity shows no statistical difference (p = ˃ 0.05) for both Site 1 and Site 2
throughout the selected time intervals. (See tab 8; Page 55).
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
0
100
200
300
400
500
600
150 160 170 180 190 200 210 220
P (µg/l)
Time (days of the year)
P in Upper Horizon [HA]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S3Vc
0
50
100
150
200
250
150 160 170 180 190 200 210 220
P (µg/l)
Time (days of the year)
P in Lower Horizon [HD]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S4Va
0
1000
2000
3000
4000
5000
6000
150 160 170 180 190 200 210 220
Mn (µg/l)
Time (days of the year)
Mn in Upper Horizon [HA]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S3Vc
500
1500
2500
3500
4500
5500
6500
7500
150 160 170 180 190 200 210 220
Mn (µg/l)
Time (days of the year)
Mn in Lower Horizon [HD]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S4Va
RESULTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 6: Soil solution chemistry at the investigated site (1-4), showing differences and distributions in the concentrations of soil nutrients (P, Mn), within upper and lower horizon, throughout the
investigation period time (from 158 to 214 doY), in David-shaft mine tailings [where Va= no vegetation, Vb= sparse vegetation and Vc = dense vegetation]. The figures are plotted with
average mean [n=3] and its standard errors.
0
500
1000
1500
2000
2500
150 160 170 180 190 200 210 220
Cu (µg/l)
Time (days of the year)
Cu in Upper Horizon [HA]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S3Vc
0
500
1000
1500
2000
2500
3000
150 160 170 180 190 200 210 220
Cu (µg/l)
Time (days of the year)
Cu in Lower Horizon [HD]
S1Va
S1Vb
S1Vc
S2Va
S2Vb
S2Vc
S4Va
5000
15000
25000
35000
45000
55000
65000
150 160 170 180 190 200 210 220
Zn (µg/l)
Time (days of the year)
Zn in Upper Horizon [HA]
S1Va
S1Vb
S1Vc
2000
22000
42000
62000
82000
102000
150 160 170 180 190 200 210 220
Zn (µg/l)
Time (days of the year)
Zn in Lower Horizon [HD]
S1Va
S1Vb
S1Vc
31
RESULTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 7: Soil solution chemistry at the investigated site (1-4), showing differences and distributions in the concentrations of soil nutrients (Cu, Zn), within upper and lower horizon, throughout the
investigation period time (from 158 to 214 doY), in David-shaft mine tailings [where Va= no vegetation, Vb= sparse vegetation and Vc = dense vegetation]. The figures are plotted with
average mean [n=3] and its standard errors.
0
1000
2000
3000
4000
5000
6000
7000
150 160 170 180 190 200 210 220
Zn (µg/l)
Time (days of the year)
Zn in Upper Horizon [HA]
S2Va
S2Vb
S2Vc
S3Vc
0
1000
2000
3000
4000
5000
6000
7000
150 160 170 180 190 200 210 220
Zn (µg/l)
Time (days of the year)
Zn in Lower Horizon [HD]
S2Va
S2Vb
S2Vc
S4Va
32
RESULTS
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 8: Soil solution chemistry at the investigated site (2-4), showing differences and distributions in the concentrations of soil nutrients (Zn, Fe), within upper and lower horizon, throughout the
investigation period time (from 158 to 214 doY), in David-shaft mine tailings [where Va= no vegetation, Vb= sparse vegetation and Vc = dense vegetation]. The figures are plotted with
average mean [n=3] and its standard errors.
0
200
400
600
800
1000
1200
1400
1600
150 160 170 180 190 200 210 220
Fe (µg/l)
Time (days of the year)
Fe in Upper Horizon [HA]
S2Va
S2Vb
S2Vc
S3Vc
0
500
1000
1500
2000
150 160 170 180 190 200 210 220
Fe (µg/l)
Time (days of the year)
Fe in Lower Horizon [HD]
S2Va
S2Vb
S2Vc
S4Va
33
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
Figure 9: Soil solution chemistry at the investigated site 1, showing differences and distributions in the concentrations of soil nutrients (Fe), within upper and lower horizon, throughout the
investigation period time (from 158 to 214 doY), in David-shaft mine tailings [where Va= no vegetation, Vb= sparse vegetation and Vc = dense vegetation]. The figures are plotted with
average mean [n=3] and its standard errors.
100
150
200
250
300
150 160 170 180 190 200 210 220
Fe (µg/l)
Time (days of the year)
Fe in Upper Horizon [HA]
S1Va
S1Vb
S1Vc
100
150
200
250
300
350
400
150 160 170 180 190 200 210 220
Fe (µg/l)
Time (days of the year)
Fe in Lower Horizon [HD]
S1Va
S1Vb
S1Vc
RESULTS
34
RESULTS 36
Callistus Obunadike MSc Thesis Jan. 2017 DOI: https://doie.org/10.0201/Thesis.2023370220
4.4 Nutrients in soil solution (P, Mn, Fe, Cu, Zn)
4.4.1 Phosphorus in soil solution
Phosphorus at upper horizon (HA): At site 1, the concentration of P, were significantly higher in
non-vegetation (Va) (except for T5/200doY) compared to sparse vegetation (Vb) (Fig. 6).
Phosphorus concentration in site 1, was significantly higher at T3 (186 doY) in sparse vegetation
(Vb), compared to other vegetation at the other sites (see Appendix Table B10). In sparse vegetation
(Vb), the concentrations of P, were significantly higher at site 1 compared to site 2 throughout the
six-time period (T1-T6). At site 2, dense vegetation (Vc), has the highest P, followed by site 1 and
the least P, occurred in site 3 (ref. site). Generally, from the multiple-sample comparison, phosphorus
shows a statistically significant difference with (p-value ˂ 0.05) at site 1 whereas there was no
statistical difference for p-values at site 2 (p-value ˃ 0.05). Considering the effects of vegetation on
the P concentrations, the p-values shows nSSD (except for non-vegetation “Va”), this was due to the
artificial creation of the non-vegetation (Va) in site 1 compared to the natural occurring non-
vegetation, at the other sites. (See fig 6 and Table 8).
Phosphorus at lower horizon (HD): At lower horizon, the P concentration in site 2 was significantly
higher at T4 and T5, with an increasing trend in sparse vegetation (Vb). The concentration of P in
sparse vegetation (Vb) for site 2, were significantly higher compared to other sites. Similar
concentrations were measured in dense vegetation (Vc) for both site 1 and site 2. The least P
occurred mainly in non-vegetation (Va), during T1 to T3, whereas the lowest concentration of P in
non-vegetation (Va), occurred at site 4 (ref. site). From the multiple-sample comparison, the p-values
shows no statistically significant difference with p-value ˃ 0.05. See fig 6 and Table 9.
Vegetation types showing highest and lowest phosphorus values: In non-vegetation (Va), the lowest
concentration of P occurred in S1/HD/T3 with a value below detection limit while the highest value
occurred at S2/HA/T5 with a value of 348.9 µg/l. In sparse vegetation (Vb), the lowest concentration
of P occurred in S2/HA/T2 with a value of 9.51µg/l while the highest value occurred at S1/HA/T3 with
a value of 581µg/l, whereas in dense vegetation (Vc), the lowest concentration of P occurred in
S3/HA/T6 with a value of 3.42µg/l while the highest value occurred at S1/HD/T2 with a value of
526.7µg/l. see fig 6.
4.4.2 Manganese in soil solution
Manganese at upper horizon (HA):