Mining waste acting as a precursor of environmental stress in sediments

da Silva, Paulo Roberto Bairros; Parizotto, Denise; Silva, Leonardo Roggen; Parreira, Paulo Sergio; Melquiades, Fabio Luiz; Mauad, Frederico Fábio

doi:10.1590/S1413-415220220230

Paulo Roberto Bairros da Silva

Conceptualization

Data curation

Investigation

Methodology

Validation

Writing – original draft

Universidade Federal de Santa Maria, Departamento de Geociências – Santa Maria (RS), Brazil.

http://orcid.org/0000-0002-2052-4210

Denise Parizotto

Writing – original draft

Writing – review & editing

Universidade de São Paulo, Escola de Engenharia de São Carlos – São Carlos (SP), Brazil.

http://orcid.org/0000-0002-0290-7146

Leonardo Roggen Silva

Writing – review & editig

Universidade de São Paulo, Escola de Engenharia de São Carlos – São Carlos (SP), Brazil.

http://orcid.org/0000-0002-3560-6913

Paulo Sergio Parreira

Data curation

Formal analysis

Universidade Estadual de Londrina (UEL), Departamento de Física – Londrina (PR), Brazil.

http://orcid.org/0000-0001-8850-4913

Fabio Luiz Melquiades

Data curation

Formal analysis

Universidade Estadual de Londrina (UEL), Departamento de Física – Londrina (PR), Brazil.

http://orcid.org/0000-0003-1154-0339

Frederico Fábio Mauad

Project administration

Supervision

Universidade de São Paulo, Escola de Engenharia de São Carlos – São Carlos (SP), Brazil.

http://orcid.org/0000-0002-2477-2019

* Corresponding author: paulo.bairros-silva@ufsm.br

Conflicts of interest: the authors declare no conflicts of interest.

	Baggio et al. (2015)BAGGIO, S.B.; HARTMANN, L.A.; MASSONNE, H.J.; THEVE, T.; ANTUNES, L.M. Silica gossan as a prospective guide for amethyst geode deposits in the Ametista do Sul mining district, Paraná volcanic province, southern Brazil. Journal of Geochemical Exploration, v. 159, p. 213-226, 2015. https://doi.org/10.1016/j.gexplo.2015.09.011 https://doi.org/10.1016/j.gexplo.2015.09...	Hartmann et al. (2015)HERATH, D.; PITAWALA, A.; GUNATILAKE, J.; IQBAL, M.C.M. Using multiple methods to assess heavy metal pollution in an urban city. Environmental Monitoring AND Assessment, v. 190, p. 657-671, 2018. https://doi.org/10.1007/s10661-018-7016-5 https://doi.org/10.1007/s10661-018-7016-...	Korchagin; Caner; Bortoluzzi (2019)LONE, A.M.; ACHYUTHAN, H.; SHAH, R.A.; SANGODE, S.J. Environmental magnetism and heavy metal assemblages in lake bottom sediments, Anchar Lake, Srinagar, NW Himalaya, India. International Journal of Environmental Research, v. 12, p. 489-502, 2018. https://doi.org/10.1007/s41742-018-0108-9 https://doi.org/10.1007/s41742-018-0108-...
	Amethyst: Mina Museum	Amethyst: Mina Museum	Amethyst: Geodes
	( $\bar{X} \pm CI$ )	( $\bar{X} \pm CI$ )	( $\bar{X} \pm CI$ )
Oxides (%)
Na₂O	2.36 ± 0.04	2.21 ± 0.03	3.67 ± 0.18
MgO	5.56 ± 0.17	4.41 ± 0.36	5.55 ± 0.36
Al₂O₃	13.08 ± 0.18	14.99 ± 0.54	15.90 ± 0.52
SiO₂	49.42 ± 0.46	46.63 ± 1.28	47.42 ± 1.26
P₂O₅	0.28 ± 0.01	3.58 ± 0.06	0.87 ± 0.02
K₂O	1.13 ± 0.19	1.19 ± 0.23	1.47 ± 0.18
CaO	9.57 ± 0.07	8.10 ± 0.18	8.27 ± 0.28
TiO₂	2.28 ± 0.06	12.21 ± 0.27	3.54 ± 0.17
MnO	0.20 ± 0.02	0.56 ± 0.02	0.20 ± 0.02
Fe₂O₃	14.86 ± 0.61	0.20 ± 0.03	13.85 ± 0.87
ZnO	ND	ND	0.05 ± 0.00
SrO	ND	ND	0.06 ± 0.01

Sampling points	Code	Coordinates		Campaigns	Date	Material
Barra Funda	BF	27º55’22’’ S	53º02’52’’ W	1º	02/07/2016	Sediments
Rodeio Bonito	RB	27º26’33’’ S	53º10’13’’ W	2º	17/09/2016	Sediments
Ametista do Sul	A	27º21’44’’ S	53º15’16’’ W	2º	17/09/2016	Sediments
Iraí — Ponte Velha	IPV	27º16’33’’ S	53º18’07’’ W	3º	01/11/2016	Sediments
Iraí — BR-386	IBR	27º13’25’’ S	53º19’31’’ W	3º	01/11/2016	Sediments

Value	Chemical Index of Alteration (CIA)	Value	Elementary ratio (ER1)	Value	Elementary ratio (ER2)
50 ≤	No chemical weathering	0.0 - 0.3	Clay minerals	3-8	Originated from mafic igneous rocks
50 - 60	Low chemical weathering			8-21	Intermmediate rocks
60 - 80	Moderate chemical weathering	0.3 - 0.9	Feldspars	21-70	Felsic igneous rocks
80 >	Extreme chemical weathering

	ANALYTE	BF		RB		A		IPV		IBR
	ANALYTE	( $\bar{X}$ ± CI)	VC (%)	( $\bar{X}$ ± CI)	VC (%)	( $\bar{X}$ ± CI)	VC (%)	( $\bar{X}$ ± CI)	VC (%)	( $\bar{X}$ ± CI)	VC (%)
1ª Sampling campaign	Na₂O	0.16 ± 0.01	4.5	0.29 ± 0.01	2.7	0.32 ± 0.01	1.9	0.30 ± 0.01	2.9	0.25 ± 0.06	20.6
	MgO	0.49 ± 0.02	3.3	0.67 ± 0.01	0.3	0.66 ± 0.01	1.3	0.60 ± 0.02	2.9	0.60 ± 0.02	2.9
	Al₂O₃	16.2 ± 0.2	1.3	13.9 ± 0.1	0.9	13.9 ± 0.2	1.3	12.5 ± 0.2	1.4	15.6 ± 0.3	1.5
	SiO₂	41.4 ± 0.6	1.3	44.9 ± 0.2	0.4	43.9 ± 0.3	0.5	44.5 ± 1.1	2.1	43.5 ± 0.5	1.1
	P₂O₅	0.27 ± 0.01	0.4	0.25 ± 0.01	1.8	0.23 ± 0.01	0.4	0.26 ± 0.01	1.9	0.30 ± 0.01	0.9
	K₂O	0.37 ± 0.02	0.6	0.55 ± 0.01	0.2	0.56 ± 0.01	0.5	0.56 ± 0.02	2.8	0.53 ± 0.01	0.5
	CaO	1.0 ± 0.01	0.9	1.4 ± 0.01	0.7	1.5± 0.00	0.3	1.3 ± 0.01	0.9	1.2 ± 0.02	1.9
	TiO₂	6.5 ± 0.1	0.8	9.1 ± 0.1	1.3	7.7 ± 0.1	1.1	9.7 ± 1.3	11.4	4.5 ± 0.2	3.3
	MnO	0.28 ± 0.01	0.7	0.30 ± 0.01	0.7	0.29 ± 0.01	0.5	0.33 ± 0.01	1.7	0.40 ± 0.02	4.3
	Fe₂O₃	17.7 ± 0.04	0.2	16.8 ± 0.04	0.2	17.0 ±0.01	0.3	17.8 ± 0.2	1.0	16.4 ± 0.8	4.5
	CuO	0.04 ± 0.01	1.2	0.03 ± 0.01	2.4	0.04 ± 0.01	1.8	0.04 ± 0.01	2.1	0.03 ± 0.01	4.8
	ZnO	0.02 ± 0.001	2.2	0.02 ± 0.001	1.8	0.02 ± 0.001	1.9	0.04 ± 0.001	5.0	0.02 ± 0.001	2.7
	SrO	0.0096 ± 0.0001	1.0	0.01 ± 0.001	1.9	0.01 ± 0.001	2.9	0.01 ± 0.001	5.2	0.01 ± 0.001	7.6
2ª Sampling campaign	Na₂O	0.19 ± 0.01	3.7	0.19 ± 0.01	5.8	0.20 ± 0.01	3.0	0.29 ± 0.01	1.9	0.20 ± 0.04	1.7
	MgO	0.51 ± 0.02	3.5	0.45 ± 0.01	0.9	0.49 ± 0.02	3.0	0.58 ± 0.01	0.4	0.47 ± 0.01	2.8
	Al₂O₃	16.1 ± 0.2	1.2	13.5 ± 0.1	0.7	13.6 ± 0.2	1.2	12.3 ± 0.1	0.8	14.5 ± 0.2	0.9
	SiO₂	41.8 ± 0.3	0.6	45.3 ± 0.2	0.4	44.1 ± 0.3	0.7	43.3 ± 0.2	0.5	40.8 ± 0.4	1.0
	P₂O₅	0.26 ± 0.01	1.2	0.30 ± 0.01	0.4	0.27 ± 0.01	0.4	0.24 ± 0.01	1.5	0.29 ± 0.01	0.4
	K₂O	0.39 ± 0.01	0.2	0.45 ± 0.01	0.6	0.48 ± 0.01	0.5	0.50 ± 0.01	0.8	0.47 ± 0.01	0.8
	CaO	1.07 ± 0.02	1.4	1.02 ± 0.01	0.5	1.06 ± 0.02	1.7	1.18 ± 0.00	0.3	1.00 ± 0.01	1.1
	TiO₂	6.6 ± 0.1	1.0	6.4 ± 0.1	0.4	6.7 ± 0.2	2.5	12.1 ± 0.5	3.7	5.0 ± 0.1	1.8
	MnO	0.25 ± 0.01	0.9	0.37 ± 0.01	0.9	0.35 ± 0.01	0.6	0.32 ± 0.01	0.4	0.38 ± 0.01	0.2
	Fe₂O₃	18.0 ± 0.1	0.4	17.0 ± 0.2	1.2	17.1 ± 0.1	0.5	17.7 ± 0.1	0.4	17.6 ± 0.1	0.4
	CuO	0.04 ± 0.01	1.2	0.03 ± 0.01	3.7	0.03 ± 0.01	1.8	0.03 ± 0.01	2.6	0.04 ± 0.01	1.4
	ZnO	0.02 ± 0.01	4.5	0.02 ± 0.01	1.5	0.02 ± 0.01	3.2	0.02 ± 0.01	4.3	0.03 ± 0.01	0.8
	SrO	0.01 ± 0.0001	3.2	0.01 ± 0.00001	1.5	0.01 ± 0.0001	0.9	0.00 ± 0.0001	11.4	0.01 ± 0.0001	2.9
3ª Sampling campaign	Na₂O	0.16 ± 0.01	3.3	0.30 ± 0.05	12.8	0.20 ± 0.01	6.1	0.27 ± 0.01	3.9	0.20 ± 0.01	6.3
	MgO	0.46 ± 0.01	0.6	0.70 ± 0.02	2.7	0.49 ± 0.03	6.0	0.53 ± 0.01	2.1	0.50 ± 0.01	0.5
	Al₂O₃	14.0 ± 0.1	0.9	13.9 ± 0.20	1.1	14.0 ± 0.5	1.9	12.2 ± 0.1	1.0	14.6 ± 0.1	0.2
	SiO₂	42.7 ± 0.2	0.4	44.6 ± 0.5	1.1	41.6 ± 0.8	1.6	44.4 ± 0.5	1.0	43.1 ± 0.1	0.1
	P₂O₅	0.24 ± 0.01	0.4	0.25 ± 0.01	1.3	0.27 ± 0.01	2.4	0.25 ± 0.01	0.8	0.29 ± 0.01	1.3
	K₂O	0.37 ± 0.01	0.8	0.60 ± 0.01	0.3	0.47 ± 0.01	0.5	0.55 ± 0.02	3.1	0.49 ± 0.01	0.4
	CaO	1.07 ± 0.01	0.3	1.55 ± 0.02	0.9	1.13 ± 0.02	1.2	1.25 ± 0.01	1.0	1.06 ± 0.01	0.4
	TiO₂	7.00 ± 0.3	3.4	7.85 ± 0.03	0.6	6.50 ± 0.03	0.8	8.50 ± 0.6	11.2	7.00 ± 0.02	0.6
	MnO	0.28 ± 0.01	1.0	0.30 ± 0.01	0.1	0.31 ± 0.01	0.4	0.32 ± 0.01	1.4	0.34 ± 0.01	0.7
	Fe₂O₃	16.6 ± 0.1	0.5	17.0 ± 0.1	0.3	17.0 ± 0.1	0.4	16.9 ± 0.1	0.5	17.4 ± 0.2	0.9
	CuO	0.04 ± 0.01	1.2	0.03 ± 0.01	1.2	0.03 ± 0.01	1.8	0.03 ± 0.01	1.0	0.03 ± 0.01	4.0
	ZnO	0.02 ± 0.01	3.0	0.02 ± 0.01	1.8	0.02 ± 0.01	2.4	0.02 ± 0.01	2.4	0.02 ± 0.01	5.2
	SrO	0.01 ± 0.001	3.3	0.01 ± 0.001	2.0	0.01 ± 0.001	2.9	0.01 ± 0.001	10.3	0.01 ± 0.001	5.2

Analyte	Variation source	SQ	DF	MQ	F	p value
Na₂O	Between groups	0.1	4	0.0	8.9	3.09 x 10-5
	Within groups	0.1	40	0.0
	Total	0.1	44	0.0
MgO	Between groups	0.1	4	0.0	3.3	0.02
	Within groups	0.2	40	0.0
	Total	0.3	44	0.0
Al₂O₃	Between groups	53.8	4	13.4	43.6	4.5 x 10^-14
	Within groups	12.3	40	0.3
	Total	66.2	44	0.0
SiO₂	Between groups	52.3	4	13.1	15.0	1.45 x 10^-7
	Within groups	34.9	40	0.9
	Total	87.2	44	0.0
P₂O₅	Between groups	0.0	4	0.0	9.7	1.40 x 10^-5
	Within groups	0.0	40	0.0
	Total	0.0	44	0.0
K₂O	Between groups	0.1	4	0.0	23.7	4.12 x 10_-10
	Within groups	0.1	40	0.0
	Total	0.2	44	0.0
CaO	Between groups	0.5	4	0.1	6.2	0.00
	Within groups	0.8	40	0.0
	Total	1.3	44	0.0
TiO₂	Between groups	101.9	4	25.5	20.1	3.75 x 10^-9
	Within groups	50.6	40	1.3
	Total	152.5	44	0.0
MnO	Between groups	0.0	4	0.0	23.1	6.09 x 10^-10
	Within groups	0.0	40	0.0
	Total	0.1	44	0.0
Fe₂O₃	Between groups	2.15	4	0.5	2.5	0.05
	Within groups	8.5	40	0.2
	Total	10.7	44	0.6

Na₂O	BF	RB	A	IPV	IBR	P₂O₅	BF	RB	A	IPV	IBR
BF		0.0	0.01	0.0	0.1	BF		0.5	1.0	1.0	0.0
RB	6.5		0.7	0.9	0.3	RB	2.3		0.8	0.2	0.0
A	4.8	1.7		0.2	0.9	A	0.8	1.4		0.8	0.0
IPV	7.7	1.2	2.9		0.0	IPV	0.8	3.1	1.6		0.0
IBR	3.7	2.8	1.1	4.0		IBR	7.0	4.8	6.2	7.9
MgO	BF	RB	A	IPV	IBR	K₂O	BF	RB	A	IPV	IBR
BF		0.0	0.5	0.1	0.7	BF		0.0	0.0	0.0	0.0
RB	4.8		0.4	0.8	0.2	RB	11.7		0.5	1.0	0.3
A	2.3	2.5		0.9	1.0	A	9.4	2.3		0.4	1.0
IPV	3.4	1.4	1.0		0.8	IPV	11.8	0.1	2.4		0.3
IBR	1.7	3.1	0.6	1.7		IBR	8.9	2.8	0.5	2.9
Al₂O₃	BF	RB	A	IPV	IBR	CaO	BF	RB	A	IPV	IBR
BF		0.0	0.0	0.0	0.2	BF		0.0	0.1	0.1	1.0
RB	9.1		1.0	0.0	0.0	RB	5.9		0.4	0.6	0.0
A	9.1	0		0.0	0.0	A	3.5	2.5		1.0	0.2
IPV	17.2	8.0	8.0		0.0	IPV	3.8	2.1	0.4		0.1
IBR	3.1	6.0	6.0	14.1		IBR	0.4	5.5	3.1	3.5
SiO₂	BF	RB	A	IPV	IBR	TiO₂	BF	RB	A	IPV	IBR
BF		0.0	0.0	0.0	0.8	BF		0.3	1.00	0.0	0.2
RB	9.6		0.0	0.3	0.0	RB	2.9		0.5	0.0	0.0
A	4.0	5.5		0.3	0.4	A	0.7	2.2		0.0	0.1
IPV	6.8	2.7	2.8		0.0	IPV	8.9	6.0	8.2		0.0
IBR	1.6	8.0	2.5	5.2		IBR	3.2	6.1	3.9	12.1
MnO	BF	RB	A	IPV	IBR	Fe₂O₃	BF	RB	A	IPV	IBR
BF		0.0	0.0	0.0	0.0	BF		0.1	0.3	1.0	0.7
RB	605		1.0	1.0	0.0	RB	3.3		1.0	0.1	0.8
A	5.6	0.8		0.8	0.0	A	2.8	0.5		0.2	0.9
IPV	7.2	0.7	1.5		0.0	IPV	0.2	3.5	3.0		0.6
IBR	13.5	7.0	7.9	6.3		IBR	1.8	1.5	1.0	1.9

	Chemical Index of Alteration (CIA)	Elementary Ratio (ER1)	Elementary Ratio (ER2)
Sediments
Barra Funda (BF)	90.6	0.03	2.3
Rodeio Bonito (RB)	86.6	0.04	1.8
A (Ametista)	87.5	0.04	2.0
IPV (Iraí — Ponte Velha)	85.6	0.04	1.2
IBR (Iraí — BR-386)	89.2	0.03	2.7
Mining tailings
Baggio et al. (2015)BAGGIO, S.B.; HARTMANN, L.A.; MASSONNE, H.J.; THEVE, T.; ANTUNES, L.M. Silica gossan as a prospective guide for amethyst geode deposits in the Ametista do Sul mining district, Paraná volcanic province, southern Brazil. Journal of Geochemical Exploration, v. 159, p. 213-226, 2015. https://doi.org/10.1016/j.gexplo.2015.09.011 https://doi.org/10.1016/j.gexplo.2015.09...	50.0	0.09	5.7
Hartmann et al. (2015)HERATH, D.; PITAWALA, A.; GUNATILAKE, J.; IQBAL, M.C.M. Using multiple methods to assess heavy metal pollution in an urban city. Environmental Monitoring AND Assessment, v. 190, p. 657-671, 2018. https://doi.org/10.1007/s10661-018-7016-5 https://doi.org/10.1007/s10661-018-7016-...	56.6	0.01	1.2
Korchagin; Caner; Bortoluzzi (2019)LONE, A.M.; ACHYUTHAN, H.; SHAH, R.A.; SANGODE, S.J. Environmental magnetism and heavy metal assemblages in lake bottom sediments, Anchar Lake, Srinagar, NW Himalaya, India. International Journal of Environmental Research, v. 12, p. 489-502, 2018. https://doi.org/10.1007/s41742-018-0108-9 https://doi.org/10.1007/s41742-018-0108-...	54.2	0.03	4.5

	Elementary ratio (ER₃)	Elementary ratio (ER₄)	CaO
Sediments
Barra Funda (BF)	2.7	46.3	1.0
Rodeio Bonito (RB)	3.3	31.8	1.3
A (Ametista)	3.1	33.8	1.5
IPV (Iraí — Ponte Velha)	3.6	32.5	1.2
IBR (Iraí — BR-386)	2.8	34.5	1.1

Major oxides	Nemerow Pollution Index
Major oxides	BF	RB	A	IPV	IBR
Al₂O₃	1.2	1.0	1.0	0.9	1.0
SiO₂	1.5	1.6	1.6	1.6	1.2
P₂O₅	0.9	1.0	0.9	0.9	1.0
K₂O	1.2	1.7	1.6	1.7	1.2
CaO	1.1	1.5	1.3	1.3	1.1
MnO	0.8	1.0	1.0	1.0	1.1
Fe₂O₃	1.1	1.0	1.0	1.1	1.0
CuO	3.0	2.5	2.7	2.9	1.5
ZnO	2.5	2.5	2.4	2.5	1.3

[1] * Corresponding author: paulo.bairros-silva@ufsm.br

Brasil

Brasil

Mining waste acting as a precursor of environmental stress in sediments

Rejeitos de mineração atuando como precursores de estresse ambiental em sedimentos

Abstract