Statistical Study for Leaching of Covellite in a Chloride Media

Abstract

Covellite is a secondary copper sulfide, and it is not abundant. There are few investigations on this mineral in spite of it being formed during the leaching of chalcocite or digenite; the other investigations on covellite are with the use of mineraloids, copper concentrates, and synthetic covellite. The present investigation applied the surface optimization methodology using a central composite face design to evaluate the effect of leaching time, chloride concentration, and sulfuric acid concentration on the level of copper extraction from covellite (84.3% of purity). Copper is dissolved from a sample of pure covellite without the application of temperature or pressure; the importance of its purity is that the behavior of the parameters is analyzed, isolating the impurities that affect leaching. The chloride came from NaCl, and it was effectuated in a size range from –150 to +106 μm. An ANOVA indicated that the leaching time and chloride concentration have the most significant influence, while the copper extraction was independent of sulfuric acid concentration. The experimental data were described by a highly representative quadratic model obtained by linear regression (R² = 0.99).

Full text

metals
Article
Statistical Study for Leaching of Covellite in a
Chloride Media
Kevin Pérez 1, Norman Toro 2, 3, * , Manuel Saldaña 2,3 , Eleazar Salinas-Rodríguez 4,
Pedro Robles 5, David Torres 2,6 and Ricardo I. Jeldres 1, *
1Departamento de Ingeniería Química y Procesos de Minerales, Universidad de Antofagasta,
Antofagasta 1270300, Chile; kps003@alumnos.ucn.cl
2Faculty of Engineering and Architecture, Universidad Arturo Prat, Almirante Juan JoséLatorre 2901,
Antofagasta 1244260, Chile; manuel.saldana@ucn.cl (M.S.); david.Torres@sqm.com (D.T.)
3Departamento de Ingeniería Metalúrgica y Minas, Universidad Católica del Norte,
Antofagasta 1270709, Chile
4Área Académica de Ciencias de la Tierra y Materiales, Universidad Autónoma del Estado de Hidalgo,
Carretera Pachuca—Tulancingo km. 4.5, C.P. 42184, Mineral de la Reforma, Hidalgo C.P. 42184, Mexico;
salinasr@uaeh.edu.mx
5Escuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340000, Chile;
pedro.robles@pucv.cl
6Department of Mining, Geological and Cartographic Department, Universidad Politécnica de Cartagena,
30203 Murcia, Spain
*Correspondence: ntoro@ucn.cl (N.T.); ricardo.jeldres@uantof.cl (R.I.J.); Tel.: +56-55-2651-021 (N.T.)
Received: 23 March 2020; Accepted: 3 April 2020; Published: 4 April 2020


Abstract:
Covellite is a secondary copper sulfide, and it is not abundant. There are few investigations
on this mineral in spite of it being formed during the leaching of chalcocite or digenite; the other
investigations on covellite are with the use of mineraloids, copper concentrates, and synthetic covellite.
The present investigation applied the surface optimization methodology using a central composite face
design to evaluate the effect of leaching time, chloride concentration, and sulfuric acid concentration
on the level of copper extraction from covellite (84.3% of purity). Copper is dissolved from a sample of
pure covellite without the application of temperature or pressure; the importance of its purity is that
the behavior of the parameters is analyzed, isolating the impurities that affect leaching. The chloride
came from NaCl, and it was effectuated in a size range from –150 to +106
µ
m. An ANOVA indicated
that the leaching time and chloride concentration have the most significant influence, while the copper
extraction was independent of sulfuric acid concentration. The experimental data were described by
a highly representative quadratic model obtained by linear regression (R2=0.99).
Keywords: sulfide leaching; ANOVA; secondary sulfide; CuS
1. Introduction
Covellite is not an abundant, but it may be found in many copper deposits as a supergenic mineral,
usually as a coating in the sulfide enrichment zone. It is associated with the derivation due to alteration
from other minerals, such as chalcocite, chalcopyrite, bornite, and enargite [
1
]. Covellite appears in
attractive proportion in the oxidized minerals; it is an intermediate product for the conversion of
chalcopyrite [2] and participates in transforming digenite to covellite in oxygenated media [3,4].
Sulfurized copper ores are generally treated by flotation–smelting–refining [
5
–
7
]. Although they
have reported economic [
8
] and metallurgical viability, there are environmental problems associated
with the emission of sulfur dioxide and arsenic [
9
–
13
]. Arsenic, which has continuously increased in
recent decades with the increasing extraction of copper sulfide [
14
], presents a risk to human health
Metals 2020,10, 477; doi:10.3390/met10040477 www.mdpi.com/journal/metals

Metals 2020,10, 477 2 of 11
associated with a higher incidence of cancer and cardiovascular and respiratory diseases [
15
]. This has
led to increasingly stringent environmental controls. In contrast, the recovery of complex low-grade
copper minerals is based on the hydrometallurgical method, which is preferred due to its low cost of
treatment, short construction time, operational simplicity, and functional recovery performance [
16
].
Additionally, this strategy has environmental benefits by producing non-hazardous solid waste [
17
–
19
].
Sulfuric acid and an oxidizing agent are required to break down sulfurized copper ores and
release Cu
2+
in solution. All copper sulfides require the presence of Fe
3+
and O
2
as oxidizing agents
for leaching to occur. Copper sulfide is oxidized by the presence of Fe
3+
, and the resulting Fe
2+
is
reoxidized to Fe
3+
by O
2
. The redox pair Fe
2+
/Fe
3+
act as a catalyst in these reactions. The following
reactions occur with the main secondary copper mineral, chalcocite, when the temperature is high
(Equation (1)), and the sulfur is in the form of sulfate and not of elemental sulfur, as in natural conditions
(Equations (2) and (3)) [5]:
Cu2S(s) +Fe2(SO4)3(aq) =Cu2+(aq) +SO42−(aq) +CuS(s) +2FeSO4(aq) (1)
Cu2S(s) +2Fe3+(aq) =Cu2+(aq) +2Fe2+(aq) (2)
CuS(s) +2Fe3+(aq) =Cu2+(aq) +2Fe2+(aq) +S0(s). (3)
Research studies on covellite leaching have been varied, evaluating alternatives that contemplate
different dissolution media, such as ammonia [
16
,
20
], nitrates [
21
,
22
], and chlorides [
4
,
23
–
25
].
Bioleaching has also been considered, including bacteria such as thiobacillus ferrooxidans,
acidithiobacillus ferrooxidans, and acidithiobacillus thiooxidans, which can grow under anaerobic
conditions where ferric ions are used as electron receptors [26–29].
Several researchers [
23
,
24
,
30
–
32
] have reported two phases in which copper dissolves from
chalcocite in a sulfate or chloride media:
Cu2S(s) +2Fe3+(aq) =Cu2+(aq) +CuS(s) +2Fe2+(aq) (4)
CuS(s) +2Fe3+(aq) =Cu2+(aq) +S0(s) +2Fe2+(aq). (5)
According to Niu et al. [
30
], the leaching from chalcocite to covellite is fast (Equation (4)) because
of its low activation energy (4–25 kJ/mol); then, the reaction is controlled by the effect diffusive of an
oxidant on the mineral surface. Otherwise, the stage expressed in Equation (5), which corresponds
to the transformation of covelline to dissolved copper, is slower and requires an activation energy
close to 72 kJ/mol, suggesting electrochemical control [
24
,
33
]. Nicol and Basson [
25
] indicated that the
oxidation of covellite occurs as an intermediate stage in which it is transformed into polysulfide CuS
2
:
Cu2S2(s) =CuS2(s) +Cu2+(aq) +2e−(6)
CuS2(s) =Cu2+(aq) +2S0(s) +2e−. (7)
Covellite can be oxidized over a wide range of chloride concentrations and electrochemical
potential; however, the subsequent oxidation of CuS
2
is only achieved from media with high chloride
concentrations or high potentials [
25
]. Copper leaching processes in a chloride media are especially
adequate for leaching non-ferrous minerals such as chalcocite, djurleite, digenite, and covellite, since
in these cases, the leaching solutions contain low levels of dissolved iron [3].
The expected general reaction to predict copper dissolution under the conditions described is:
4CuS(s)+8Cl−
(aq)+4H+(aq)+O2(g)=4CuCl−
2(aq)+2H2O(l)+4S0(s). (8)
In previous research on covellite leaching carried out by other authors, the common factor is that
it was carried out with a synthetic covellite (a mineraloid), whereas the covellite used in this article is
pure, coming from a mine and manually separated from impurities. The creation of synthetic covellite

Metals 2020,10, 477 3 of 11
is from a stoichiometric mixture of high-purity copper and elemental sulfur, with the application of
high temperature and vacuum sealing over long periods (approximately 3 days) for its formation.
Investigations such as those of Cheng and Lawson [
23
] and Miki et al. [
24
] feature examples of synthetic
covellite experiments (see Table 1). Meanwhile, other copper sulfide leaching investigations have been
carried out with concentrates high in chalcopyrite, enargite, digenite, and chalcocite, among others,
such as for example the investigations by Lundstrom [
2
], Ruiz [
34
], and Padilla [
35
]. The amount of
associated impurities within the concentrate, such as clay elements, pyrite, and silicas, among other
compounds, can affect the overall analysis of the tests, which makes the experiment very unique based
on its conditions. Finally, there are investigations carried out with white metal [
31
,
36
], which is an
intermediate species that is formed in copper smelting furnaces that is mineralogically similar to
chalcocite but does not have the same crystallographic behavior.
Table 1. Comparison with other investigations under similar conditions.
Research Title Dissolution
Agents Parameters Evaluated Ref. Maximum Cu
Extraction (%)
Type of
Covellite
The kinetics of leaching
covellite in acidic
oxygenated
sulfate—chloride solutions
HCl, HNO3,
NaCl, H2SO4
Temperature, oxygen
partial pressure, particle
size, stirring speed, and
sulfuric acid
concentration
[23] 85% Synthetic
covellite
The kinetics of dissolution
of synthetic covellite,
chalcocite, and digenite in
dilute chloride solutions at
ambient temperatures
HCl, Cu2+and
Fe3+
Potential effect, chloride
concentration, acid
concentration,
temperature, dissolved
oxygen, and pyrite effect
[24]>90% Synthetic
covellite
In this study, we leached pure covellite in a chloride medium with the incorporation of oxygen.
This was performed at ambient temperature and pressure to determine the relevance of the sulfuric
acid and sodium chloride concentration, followed by the dissolution time. The data were used to make
a statistical analysis through a representative quadratic model of copper extraction.
2. Materials and Methods
2.1. Covellite
The covellite sample was obtained from a Michilla mine. Using a porcelain mortar, the sample
(apparently pure) was reduced to a size between
−
150 and +106
µ
m, and then these were chemically
analyzed by atomic emission spectrometry via induction-coupled plasma (ICP-AES) in the geochemistry
lab of the Geological Sciences Department of the Universidad Cat
ó
lica del Norte (Antofagasta, Chile).
Table 2shows the chemical composition of the experimental samples.
Table 2. Chemical analysis of the covellite ore.
Element Cu S Ca O H
Mass (%) 56.14 31.08 3.66 8.76 0.36
The mineralogical analysis is presented in Table 2, where the chemical species were identified by
QEMSCAN (Bruker, Billerica, MA, USA). Covellite was the most abundant mineral (84.3%), followed
by a lower percentage of gypsum (15.7%).
2.2. Reagent and Leaching Tests
The sulfuric acid of analytical grade was acquired from Merck, with a purity of 95–97%, density
of 1.84 kg/L, and molecular weight of 98.08 g/mol.
The leaching tests were carried out in a 50-mL glass reactor with a 0.01 S/L ratio of the leaching
solution. A total of 200 mg of covellite ore was maintained in agitation and suspension at 600 rpm in a

Metals 2020,10, 477 4 of 11
five-position magnetic stirrer (IKA ROS, CEP 13087-534, Campinas, Brazil) with an oxygen addition
of 6 mL/min connecting a hose to the reactor. The tests were realized at an ambient temperature (25
◦
C), with variations of sulfuric acid and chloride concentrations and leaching time. The tests were
performed in duplicate; chemical analyses were carried on 5 mL undiluted samples using atomic
absorption spectrometry with a coefficient of variation
≤
5% and a relative error between 5% and 10%.
Measurements of pH and oxidation-reduction potential (ORP) of PLS (pregnant leaching solution)
were made using a pH-ORP meter (HANNA HI-4222, St. Louis, MO, USA). The solution ORP was
measured in a combination ORP electrode cell composed of a platinum working electrode and a
saturated Ag/AgCl reference electrode.
2.3. Experimental Design
The Cu extraction rates was studied through the effects of time and chloride and H
2
SO
4
concentrations variables on leaching covellite [
37
–
40
]. An experimental design was carried out
considering three levels per factor, resulting in a total of 27 samples [
41
]. The fit of the multiple linear
regression model was generated in the statistical software Minitab 18 (version 18, Pennsylvania State
University, State College, PA, USA), studying the linear and quadratic effects and the interactions of
the factors considered in the study [42], as shown in Equation (9).
The general form of the experimental model is represented by (Equation (9)):
Y=(overall constant)+(linear effects)+(interaction effects)+(curvature effects)
Y=b0+b1x1+b2x2+b3x3+b12x1x2+b13x1x3+b23x2x3+b11x2
1+b22x2
2+b33x2
3
(9)
where brepresents the variables coefficients and x
1
,x
2
, and x
3
are time, chloride, and H
2
SO
4
concentration variables, respectively. Table 3shows the parameters used in the experimental model,
and Equation (10) shows the transformation between the real values (Z
i
) and coded values (X
i
) of the
experimental design.
Xi=Zi−Zhigh+Zlow
2
Zhigh −Zlow
2
(10)
where Zhigh and Zlow are respectively the highest and lowest levels of each variable [43].
Table 3. Experimental parameters and codifications level.
Experimental Variable Low Medium High
Time (h) 48 72 144
Chloride Concentration (g/L) 20 50 100
H2SO4Concentration (M) 0.5 1 2
Codifications −1 0 1
The levels of selected parameters (Table 3) are justified by the following, starting with the level
of chloride: at an industrial level, concentrations of up to 100 g/L of chloride are being used to leach
copper sulfides, while other researchers have indicated that the concentration of chloride does not
have much relevance after 0.5 M [
23
], which is equivalent to 18 g/L. That is why 20 to 100 g/L was
selected to evaluate its effect as a function of concentration. Meanwhile, something similar occurs with
choice of the concentration of sulfuric acid. Some researchers have mentioned that its effect is minimal
in the dissolution of copper from covellite; it is only necessary in small amounts. In the research of
Cheng and Lawson [
23
], a significant change is not highlighted when the concentration of sulfuric acid
was 0.5 or 2 M; therefore, these two values are chosen as limits to analyze their effect.
The R
2
,R
2adj
, and p-values statistics were used to indicate whether the model obtained is adequate
to describe the dependent variable under the sampled domain. The R
2
statistics measures the proportion
of total variability that is explained by the model, the predicted R
2
statistic determines the performance

Metals 2020,10, 477 5 of 11
of the model predicting the response, and finally, the p-values indicate whether there is a statistically
significant association between the dependent variable and a determined independent variable [43].
3. Results
3.1. ANOVA
Based on the results obtained (Table 4). An ANOVA test (Table 5) showed no significant effect of
the interaction {time, Cl} and the effects of the curvature of chloride variable on the dependent variable
(copper extraction). Meanwhile, the interactions between the effects {Time, H
2
SO
4
} and {Chloride,
H2SO4} and the curvature of time variable contribute to explain the variability of the model.
Table 4.
Experimental configuration and Cu extraction data (at T=25
◦
C, Stirring rate =600 rpm, P =1 atm).
Exp. No. Time (h) Cl (g/L) H2SO4(M) Cu Extraction Rate (%)
1 48 20 0.5 2.50
2 48 50 0.5 3.50
3 48 100 0.5 6.00
4 48 20 1 3.00
5 48 50 1 3.63
6 48 100 1 9.13
7 48 20 2 3.25
8 48 50 2 5.50
9 48 100 2 11.38
10 72 20 0.5 5.13
11 72 50 0.5 8.75
12 72 100 0.5 11.25
13 72 20 1 5.88
14 72 50 1 9.25
15 72 100 1 13.88
16 72 20 2 6.38
17 72 50 2 11.63
18 72 100 2 18.75
19 144 20 0.5 24.63
20 144 50 0.5 24.88
21 144 100 0.5 28.75
22 144 20 1 26.25
23 144 50 1 29.75
24 144 100 1 35.00
25 144 20 2 28.75
26 144 50 2 31.25
27 144 100 2 38.75
Table 5. ANOVA Cu extraction.
Source F-Value p-Value
Regression 371.42 0.000
Time 2624.36 0.000
Cl 257.04 0.000
H2SO4105.5 0.000
Time ×Time 9.7 0.006
Cl ×Cl 0.56 0.466
H2SO4×H2SO43.39 0.083
Time ×Cl 0.81 0.379
Time ×H2SO411.22 0.004
Cl ×H2SO422.6 0.000

Metals 2020,10, 477 6 of 11
The contour plot in Figure 1shows that the Cu extraction rate increases with more time and higher
concentrations of chloride and H2SO4.
Figure 1.
Experimental contour plot of Cu extraction versus time and chloride (
a
), time and H
2
SO
4
concentration (b), and chloride concentration and H2SO4concentration (c).
Figures 2and 3show that the linear effect of time, chloride, and H
2
SO
4
concentration and the
interactions of time–H
2
SO
4
concentration and of chloride–H
2
SO
4
concentrations affected the Cu
extraction rate.
Figure 2. Linear effect plot for Cu extraction.

Metals 2020,10, 477 7 of 11
Figure 3.
Interactions of time–chloride (
a
), time–H
2
SO
4
concentration (
b
), and chloride–H
2
SO
4
(
c
) on
Cu extraction.
Then, the Cu extraction rate model over the range of sampled conditions is presented in Equation (11).
Cu Extraction (%)=0.16969+0.12332x1+0.03904x2+0.02502x3+0.01782x2
1
−0.00870x2
3+0.00921x1x3+0.01347x2x3(11)
The ANOVA test indicated that the model presented in Equation (11) represents adequately the
Cu extraction under the experimental domain, which is validated by the R
2
(0.9945) and R
2adj
values
(0.9925). The ANOVA indicates that all the factors influence the Cu extraction from CuS, as indicated in
the Fstatistic, where F
reg
(371.42) >F
T,95%
confidence level F
7,19
(2.543). Additionally, the p-value was
lower than the significance level, which indicates that the multiple regression is statistically significant.
The normality test applied to the standardized residuals of the regression model (Equation (11))
indicates that the residuals are relatively close to the fitted normal distribution line (Figure 4), and
the p-value of the test is greater than the significance level (0.05), so it is not possible to reject the
assumption that the model residuals are normally distributed.
Finally, the ANOVA analysis indicated that the independent variables considered can explain
the variations in the copper extraction, the minimal difference between R
2
and R
2pred
reduces the
possibility that the model is over-adjusted, and the leaching, chloride, and H
2
SO
4
concentrations,
and the interactions of time–H
2
SO
4
and chloride–H
2
SO
4
are the most critical factors in explaining
the process.

Metals 2020,10, 477 8 of 11
Figure 4. Probability plot of residual values.
3.2. Effect of Chloride Concentration
Figure 5shows that the highest rate of copper extraction (71.2%) was obtained with high
concentrations of chloride ions (100 g/L), demonstrating the importance of this variable [
4
,
24
]. However,
Cheng and Lawson [
23
] stated that over a critical chloride concentration at 0.25 M, there is no more
significant influence of the electrolyte. In the range of 20 to 50 (g/L), chloride has no positive effects
based on the leaching time, obtaining maximum copper extractions of 44.9% and 56.3%, respectively.
This agrees with the results of other research [
24
], which indicates that CuS oxidation to CuS
2
is
possible with any chloride concentration, but the oxidation of CuS
2
is only possible with very high
potential or high chloride concentrations [25].
Figure 5. Extraction of Cu (%) vs. time (h), depending on the addition of chloride.
4. Conclusions
The present research shows the laboratory results of dissolving copper from covellite in chloride
media provided by NaCl. The highest copper extraction rate was obtained with the highest
concentrations of chloride, and the main findings of this investigation were:
1.
The linear variables of time and chloride concentration have the greatest influence on the model.
2.
Under ambient conditions of pressure and temperature, H
2
SO
4
concentration–time and chloride
concentration–time have significant effects on copper extraction kinetics from covellite.

Metals 2020,10, 477 9 of 11
3.
The ANOVA analysis indicates that the quadratic model adequately represents copper extraction,
which was validated by the R2value (0.9945).
4.
The highest copper extraction rate at ambient temperature of 71.2% was obtained with a low
sulfuric acid concentration (0.5 M), high level of chloride (100 g/L), and extended leaching time
(600 h).
Author Contributions:
K.P., N.T., R.I.J. contributed in project administration, investigation and wrote paper, M.S.
and D.T. contributed in the data curation, E.S.-R. and P.R. contributed in validation and supervision. All authors
have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Acknowledgments:
The authors are grateful for the contribution of the Scientific Equipment Unit-MAINI of
the Universidad Cat
ó
lica del Norte for facilitating the chemical analysis of the solutions. Pedro Robles thanks
the Pontificia Universidad Cat
ó
lica de Valpara
í
so for the support provided. Also, we thank Conicyt Fondecyt
11171036 and Centro CRHIAM Project Conicyt/Fondap/15130015.
Conflicts of Interest: The authors declare they have no conflict of interest.
References
1. Klein, C.; Hurlbut, C.S. Manual de Mineralogía; Reverté: Madrid, Spain, 1996; ISBN 8429146067.
2.
Lundström, M.; Liipo, J.; Taskinen, P.; Aromaa, J. Copper precipitation during leaching of various copper
sulfide concentrates with cupric chloride in acidic solutions. Hydrometallurgy
2016
,166, 136–142. [CrossRef]
3.
Ruiz, M.C.; Honores, S.; Padilla, R. Leaching kinetics of digenite concentrate in oxygenated chloride media
at ambient pressure. Metall. Mater. Trans. B 1998,29, 961–969. [CrossRef]
4.
Senanayake, G. Chloride assisted leaching of chalcocite by oxygenated sulphuric acid via Cu(II)-OH-Cl.
Miner. Eng. 2007,20, 1075–1088. [CrossRef]
5.
Schlesinger, M.E.; King, M.J.; Sole, K.C.; Davenport, W.G. Extractive Metallurgy of Copper, 5th ed.; Elsevier:
Oxford, UK, 2011; ISBN 9780080967899.
6.
Shuva, M.A.H.; Rhamdhani, M.A.; Brooks, G.A.; Masood, S.; Reuter, M.A. Thermodynamics data of valuable
elements relevant to e-waste processing through primary and secondary copper production: A review. J.
Clean. Prod. 2016,131, 795–809. [CrossRef]
7.
Turan, M.D.; Sari, Z.A.; Miller, J.D. Leaching of blended copper slag in microwave oven. Trans. Nonferrous
Met. Soc. China 2017,27, 1404–1410. [CrossRef]
8.
Kelm, U.; Avendaño, M.; Balladares, E.; Helle, S.; Karlsson, T.; Pincheira, M. The use of water-extractable
Cu, Mo, Zn, As, Pb concentrations and automated mineral analysis of flue dust particles as tools for impact
studies in topsoils exposed to past emissions of a Cu-smelter. Chemie der Erde 2014,74, 365–373. [CrossRef]
9.
Afif, C.; Ch
é
lala, C.; Borbon, A.; Abboud, M.; Adjizian-G
é
rard, J.; Farah, W.; Jambert, C.; Zaarour, R.;
Saliba, N.B.; Perros, P.E.; et al. SO
2
in Beirut: Air quality implication and effects of local emissions and
long-range transport. Air Qual. Atmos. Heal. 2008,1, 167–178. [CrossRef]
10.
Dijksira, R.; Senyard, B.; Shah, U.; Lee, H. Economical abatement of high-strength SO
2
off-gas from a smelter.
J. South. African Inst. Min. Metall. 2017,117, 1003–1007. [CrossRef]
11.
Dimitrijevi´c, M.; Kostov, A.; Tasi´c, V.; Milosevi´c, N. Influence of pyrometallurgical copper production on the
environment. J. Hazard. Mater. 2009,164, 892–899. [CrossRef]
12.
S
á
nchez de la Campa, A.M.; de la Rosa, J.D.; S
á
nchez-Rodas, D.; Oliveira, V.; Alastuey, A.; Querol, X.; G
ó
mez
Ariza, J.L. Arsenic speciation study of PM2.5 in an urban area near a copper smelter. Atmos. Environ.
2008
,
42, 6487–6495. [CrossRef]
13.
Serbula, S.M.; Milosavljevic, J.S.; Radojevic, A.A.; Kalinovic, J.V.; Kalinovic, T.S. Extreme air pollution with
contaminants originating from the mining—Metallurgical processes. Sci. Total Environ.
2017
,586, 1066–1075.
[CrossRef] [PubMed]
14.
Balladares, E.; Jerez, O.; Parada, F.; Baltierra, L.; Hern
á
ndez, C.; Araneda, E.; Parra, V. Neutralization and
co-precipitation of heavy metals by lime addition to effluent from acid plant in a copper smelter. Miner. Eng.
2018,122, 122–129. [CrossRef]
15.
World Health Organization. World Health Statistics 2018: Monitoring Health for the SDGs, Sustainable
Development Goals; WHO: Geneva, Switzerland, 2018; ISBN 9789241565585.

Metals 2020,10, 477 10 of 11
16.
Baba, A.A.; Balogun, A.F.; Olaoluwa, D.T.; Bale, R.B.; Adekola, F.A.; Alabi, A.G.F. Leaching kinetics of a
Nigerian complex covellite ore by the ammonia-ammonium sulfate solution. Korean J. Chem. Eng. 2017,34,
1133–1140. [CrossRef]
17.
Gonz
á
lez, C.; Parra, R.; Klenovcanova, A.; Imris, I.; S
á
nchez, M. Reduction of Chilean copper slags: A case of
waste management project. Scand. J. Metall. 2005,34, 143–149. [CrossRef]
18.
Lü, C.; Wang, Y.; Qian, P.; Liu, Y.; Fu, G.; Ding, J.; Ye, S.; Chen, Y. Separation of chalcopyrite and pyrite from a
copper tailing by ammonium humate. Chinese J. Chem. Eng. 2018,26, 1814–1821. [CrossRef]
19.
Rabadjieva, D.; Tepavitcharova, S.; Todorov, T.; Dassenakis, M.; Paraskevopoulou, V.; Petrov, M. Chemical
speciation in mining affected waters: The case study of Asarel-Medet mine. Environ. Monit. Assess.
2009
,
159, 353–366. [CrossRef]
20.
Reilly, I.G.; Scott, D.S. The leaching of cupric sulfide in ammonia. Ind. Eng. Chem. Process Des. Dev.
1976
,15,
60–67. [CrossRef]
21.
Fisher, W.W. Comparison of chalcocite dissolution in the sulfate, perchlorate, nitrate, chloride, ammonia, and
cyanide systems. Miner. Eng. 1994,7, 99–103. [CrossRef]
22.
Vraˇcar, R.Ž.; Vuˇckovi´c, N.; Kamberovi´c, Ž. Leaching of copper(I) sulphide by sulphuric acid solution with
addition of sodium nitrate. Hydrometallurgy 2003,70, 143–151. [CrossRef]
23.
Cheng, C.Y.; Lawson, F. The kinetics of leaching covellite in acidic oxygenated sulphate-chloride solutions.
Hydrometallurgy 1991,27, 249–268. [CrossRef]
24.
Miki, H.; Nicol, M.; Vel
á
squez-Y
é
venes, L. The kinetics of dissolution of synthetic covellite, chalcocite and
digenite in dilute chloride solutions at ambient temperatures. Hydrometallurgy
2011
,105, 321–327. [CrossRef]
25.
Nicol, M.; Basson, P. The anodic behaviour of covellite in chloride solutions. Hydrometallurgy
2017
,172, 60–68.
[CrossRef]
26.
Donati, E.; Pogliani, C.; Boiardi, J.L. Anaerobic leaching of covellite by Thiobacillus ferrooxidans. Appl.
Microbiol. Biotechnol. 1997,47, 636–639. [CrossRef]
27.
Monteiro, F.V.; Garcia, O.; Tuovinen, O. Oxidative dissolution of covellite by Thiobacillus ferrooxidans.
Process Metall. 1999,9, 283–290.
28.
Falco, L.; Pogliani, C.; Curutchet, G.; Donati, E. A comparison of bioleaching of covellite using pure cultures
of Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans or a mixed culture of Leptospirillum
ferrooxidans and Acidithiobacillus thiooxidans. Hydrometallurgy 2003,71, 31–36. [CrossRef]
29.
Lee, J.; Acar, S.; Doerr, D.L.; Brierley, J.A. Comparative bioleaching and mineralogy of composited sulfide ores
containing enargite, covellite and chalcocite by mesophilic and thermophilic microorganisms. Hydrometallurgy
2011,105, 213–221. [CrossRef]
30.
Niu, X.; Ruan, R.; Tan, Q.; Jia, Y.; Sun, H. Study on the second stage of chalcocite leaching in column with
redox potential control and its implications. Hydrometallurgy 2015,155, 141–152. [CrossRef]
31.
Ruiz, M.C.; Abarz
ú
a, E.; Padilla, R. Oxygen pressure leaching of white metal. Hydrometallurgy
2007
,86,
131–139. [CrossRef]
32.
Senanayake, G. A review of chloride assisted copper sulfide leaching by oxygenated sulfuric acid and
mechanistic considerations. Hydrometallurgy 2009,98, 21–32. [CrossRef]
33.
Ruan, R.; Zou, G.; Zhong, S.; Wu, Z.; Chan, B.; Wang, D. Why Zijinshan copper bioheapleaching plant works
efficiently at low microbial activity-Study on leaching kinetics of copper sulfides and its implications. Miner.
Eng. 2013,48, 36–43. [CrossRef]
34.
Ruiz, M.C.; Montes, K.S.; Padilla, R. Chalcopyrite leaching in sulfate-chloride media at ambient pressure.
Hydrometallurgy 2011,109, 37–42. [CrossRef]
35.
Padilla, R.; Jerez, O.; Ruiz, M.C. Hydrometallurgy Kinetics of the pressure leaching of enargite in
FeSO4–H2SO4–O2media. Hydrometallurgy 2015,158, 49–55. [CrossRef]
36.
Ruiz, M.C.; Gallardo, E.; Padilla, R. Copper extraction from white metal by pressure leaching in
H2SO4-FeSO4-O2. Hydrometallurgy 2009,100, 50–55. [CrossRef]
37.
Aguirre, C.L.; Toro, N.; Carvajal, N.; Watling, H.; Aguirre, C. Leaching of chalcopyrite (CuFeS
2
) with an
imidazolium-based ionic liquid in the presence of chloride. Miner. Eng. 2016,99, 60–66. [CrossRef]
38.
Bezerra, M.A.; Santelli, R.E.; Oliveira, E.P.; Villar, L.S.; Escaleira, L.A. Response surface methodology (RSM)
as a tool for optimization in analytical chemistry. Talanta 2008,76, 965–977. [CrossRef]
39.
Dean, A.; Voss, D.; Draguljic, D. Response Surface Methodology. In Design and Analysis of Experiments;
Springer Nature: Cham, Switzerland, 2017; pp. 565–614.

Metals 2020,10, 477 11 of 11
40.
Toro, N.; Herrera, N.; Castillo, J.; Torres, C.; Sep
ú
lveda, R. Initial investigation into the leaching of manganese
from nodules at room temperature with the use of sulfuric acid and the addition of foundry slag—Part I.
Minerals 2018,8, 565. [CrossRef]
41.
Toro, N.; Saldaña, M.; G
á
lvez, E.; C
á
novas, M.; Trigueros, E.; Castillo, J.; Hern
á
ndez, P.C. Optimization of
parameters for the dissolution of mn from manganese nodules with the use of tailings in an acid medium.
Minerals 2019,9, 387. [CrossRef]
42.
Saldaña, M.; Toro, N.; Castillo, J.; Hern
á
ndez, P.; Trigueros, E.; Navarra, A. Development of an analytical
model for the extraction of manganese from marine nodules. Metals 2019,9, 903. [CrossRef]
43. Montgomery, D.C. Design and Analysis of Experiments; John Wiley & Sons: New York, NY, USA, 2012.
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