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Ciência e Agrotecnologia

Print version ISSN 1413-7054On-line version ISSN 1981-1829

Ciênc. agrotec. vol.41 no.1 Lavras Jan./Feb. 2017

http://dx.doi.org/10.1590/1413-70542017411036916 

Agricultural Sciences

Zinc, copper and manganese availability in soils treated with alkaline sewage sludge from Paraná state (Brazil)

Disponibilidade de Zn, Cu e Mn em solos tratados com lodo de esgoto alcalinizado do estado do Paraná (Brasil)

Maristela Dalpisol1 

Beatriz Monte Serrat2 

Antonio Carlos Vargas Motta2  * 

Giovana Clarice Poggere3 

Simone Bittencourt4 

Julierme Zimmer Barbosa1 

1Universidade Federal do Paraná/UFPR, Programa de Pós-Graduação em Ciência do Solo, Curitiba, PR, Brasil

2Universidade Federal do Paraná/UFPR, Departamento de Solos e Engenharia Agrícola, Curitiba, PR, Brasil

3Universidade Federal de Lavras/UFLA, Programa de Pós-Graduação em Ciência do Solo, Lavras, MG, Brasil

4Companhia de Saneamento do Paraná/SANEPAR, Unidade de Serviço de Esgoto, Curitiba, PR, Brasil

ABSTRACT

In Paraná, most of the sludge generated in sewage treatment plants is subjected to the prolonged alkaline stabilization process. Although it is known that the alkaline sewage sludge contains micronutrients such as Zn, Cu and Mn, little is known about the availability of these elements in soils treated with this type of sewage sludge. Thus, the objective of the study was to evaluate the influence of alkaline sewage sludge from Paraná on Zn, Cu and Mn availability in soils. Twenty sewage treatment plants were selected throughout Paraná, where alkaline sewage sludge and the most representative agricultural soil of the each region were collected. Each soil was incubated for 60 days with alkaline sewage sludge rates (0, 10, 20, 40, and 80 Mg ha-1) from their region. Subsequently, Zn, Cu and Mn availability was determined using the Mehlich-1 extractant. The alkaline sewage sludge increased Zn availability and decreased Mn availability in most soils. Cu showed intermediate results, with increased availability, primarily in medium texture soils and decrease in most of the clayey soils. In soils with pH close to ideal for the plant growth, the alkaline sewage sludge rate should be carefully calculated so that there is no excessive increase in the pH and Zn, Cu and Mn imbalance.

Index terms: Acid soils; organic residues; recycling; micronutrients.

RESUMO

No Paraná, a maioria do lodo de esgoto gerado em estações de tratamento é submetida ao processo de estabilização alcalina prolongada. Embora seja conhecido que o lodo de esgoto alcalinizado contém micronutrientes como Zn, Cu e Mn, pouco se conhece sobre a disponibilidade desses elementos em solos tratados com esse tipo de lodo de esgoto. Assim, o objetivo do estudo foi avaliar a influência de lodos de esgoto alcalinizados do estado do Paraná sobre a disponibilidade de Zn, Cu e Mn no solo. Foram selecionadas vinte estações de tratamento de esgoto ao longo do Paraná, onde foram coletadas amostras de lodo de esgoto alcalinizado e amostras do solo agrícola mais representativo da região. Cada solo foi incubado por 60 dias com doses de lodo de esgoto (0, 10, 20, 40, e 80 Mg ha-1) da sua região. Posteriormente, foi determinada a disponibilidade de Zn, Cu e Mn no solo usando o extrator Mehlich-1. A aplicação de lodo de esgoto alcalinizado ao solo aumentou a disponibilidade de Zn e diminuiu a disponibilidade de Mn na maioria dos solos. Já o Cu apresentou resultados intermediários, com aumento de disponibilidade basicamente em solos de textura média e com diminuição para a maioria dos solos muito argilosos. Em solos com pH próximo ao ideal para o cultivo agrícola, a dose de lodo de esgoto alcalinizado deve ser cuidadosamente calculada para que não ocorra o aumento excessivo do pH e desbalanço nos teores de Zn, Cu e Mn.

Termos para indexação: Solos ácidos; resíduos orgânicos; reciclagem; micronutrientes.

INTRODUCTION

Among the micronutrients, Zn is the most deficient in the natural condition of Brazilian soils, requiring supplementation in new areas via fertilization to allow plant cultivation. Although less common, Cu deficiency occurs mainly in sandy or organic soils (Motta et al., 2007). The specific adsorption is one of the most important mechanisms for controlling Zn and Cu availability in soil. The Zn and Cu adsorption capacity varies depending on the texture, mineralogy, organic matter and pH (Arias et al., 2006; Casagrande; Soares; Mouta, 2008; Smolders et al., 2012), thus, the availability of these nutrients may vary from soil to soil. On the other hand, under natural acid soil condition the Mn usually has high availability, which may promote plants toxicity (Millaleo et al., 2010).

The use of organic residues on agricultural land has been increasingly common (Barcellos et al., 2015; Mondal et al., 2015). In Brazil, the states that most use sewage sludge for agricultural purposes are: Paraná, São Paulo and Rio Grande do Sul (Sampaio, 2010). Between 2007 and 2010 the sewage treatment plants in the Curitiba metropolitan region allocated 33,404 Mg (dry basis) of sanitized sewage sludge for use on 2,288 hectares of agricultural areas (Bittencourt et al., 2014). Studies have found that the sewage sludge have significant amounts of some elements essential to plants, such as Zn and Cu (Fia; Matos; Aguirre, 2005; Yada et al., 2015), and which can improve physical and biological soil properties (Bonini; Alves; Montanari, 2015; Mondal et al., 2015).

The chemical composition of sewage sludge varies with origin, collection time and type of treatment to which it was submitted (Healy et al., 2016). In Paraná, most of the sewage sludge is subjected to sanitization by a prolonged alkaline stabilization process (addition of lime aimed at raising the pH of the mixture to 12 and a curing period of 30 days) (Paraná, 2009). Thus, when applied to agricultural land, the alkaline sewage sludge has double action, it increases the soil pH (Berton; Nogueira, 2010; Poggere et al., 2012) and can be a micronutrients source (Smolders et al., 2012; Bittencourt et al., 2014). However, unlike mineral fertilizer, the chemical composition of sewage sludge is quite variable, which results in a high degree of uncertainty regarding the micronutrient supply. Thus, the objective of this study was to evaluate the influence of alkaline sewage sludge from Paraná as to Zn, Cu and Mn availability in soils.

MATERIAL AND METHODS

The Sanitation Company of Paraná (SANEPAR) is divided into twenty sectors throughout the Paraná State (Brazil); and in each sector there are several sewage treatment plants (STPs). In this study, for each of the twenty SANEPAR sectors, the STP from sector municipal headquarters was selected, where the sludge was generated by anaerobic treatment. The samples of sewage sludge were collected between March 2009 and August 2010, and consisted of raw sludge recently dewatered in a drying bed. The sludge was sanitized by prolonged the alkaline stabilization process with the addition of lime (calcium oxide; total neutralizing power [TNP] 105.1) at 50% total solids and 30 days of curing. The total content of Zn, Cu and Mn present in the alkaline sewage sludge were determined according to the methodology described in Martins and Reissmann (2007).

For each municipality where the sewage sludge was collected, we also selected the type of agricultural soil most representative of the region. For each soil samples were taken from the 0-20 cm layer [point known by the use of global position system (GPS)] in area without having added lime for at least five years. The samples were air dried, ground, homogenized, passed through a 2 mm sieve, and analyzed as to physical and chemical attributes. With the help of location points provided by GPS, soil classes were allocated according to Bhering and Santos (2008). The results of the soil and soil class analyses are shown in Table 1. Detailed information concerning these soils and sludges has been previously reported (Poggere et al., 2012).

Table 1: Class and physical and chemical properties of the soil used in the incubation process with alkalized sewage sludge in Paraná, Brazil. 

Sector Soil class 1 Sand 3 Silt Clay Al3+ H+Al3+ Ca2+ Mg2+ K+ P OC
----- g kg-1 ----- ----------- cmolc dm-3 ----------- mg dm-3 g dm-3
Apucarana NVef 58 191 750 0.1 5.4 4.2 2.3 0.5 2.2 24.3
Cascavel LVdf 45 103 850 1.3 10.5 3.6 1.2 0.3 3.6 30.7
Campo Mourão LVdf 70 129 800 0.9 7.2 1.5 0.8 0.2 3.4 35.1
Francisco Beltrão LVdf 31 268 700 5.3 17.6 2.5 1.4 0.4 3.6 19.2
Foz do Iguaçu NVef 24 326 650 0.1 4.3 4.5 2.1 0.3 2.5 31.8
Guarapuava LBd 35 215 750 1.3 12.1 1.9 1.2 0.3 2.7 38.6
Londrina LVdf 40 234 725 0.0 4.0 2.6 1.1 0.1 2.7 15.3
Maringá NVef 51 198 750 0.3 6.7 4.8 1.8 0.3 3.6 45.7
Pato Branco LVdf 19 131 850 2.9 14.1 0.5 0.1 0.1 1.3 46.9
Pinhais LBw 221 129 650 3.7 15.8 3.1 1.6 0.1 1.3 65.4
Toledo LVdf 67 132 800 1.5 7.8 2.0 0.9 0.5 3.7 31.8
Cornélio Procópio NVef 110 439 450 0.2 7.9 4.0 1.4 0.6 3.8 25.3
Santo Antônio da Platina LVef 300 274 425 0.3 6.3 3.2 1.5 0.2 3.8 17.2
Arapongas 2 LVd 701 49 250 1.2 7.2 1.3 0.5 0.3 4.2 23.2
Matinhos CXbd 488 211 300 2.3 7.8 0.1 0.2 0.1 3.2 28.5
Ponta Grossa LV 646 78 275 0.3 4.3 1.2 0.6 0.1 2.4 13.3
Rio Negro RRdh 446 328 225 2.7 9.0 0.2 0.2 0.1 5.9 30.7
Telêmaco Borba PVAd 391 384 225 2.4 9.7 0.5 0.1 0.1 2.2 18.2
Paranavaí PVd 803 47 150 0.2 2.5 0.7 0.4 0.1 1.4 5.1
Umuarama LVd 767 33 200 0.7 5.8 1.2 0.4 0.1 3.1 13.3

1Predominant soil type in the mapping unit corresponding to the soil sample collection local, according to Brazilian classification (Bhering; Santos, 2008); LVdf: LATOSSOLO VERMELHO Distroférrico; LBw: LATOSSOLO BRUNO Ácrico; LBd: LATOSSOLO BRUNO Distrófico; Nvef: NITOSSOLO VERMELHO Eutroférrico; RRdh: NEOSSOLO REGOLÍTICO Distro-húmbrico; CXbd = CAMBISSOLO HÁPLICO tb Distrófico; PVAd: ARGISSOLO VERMELHO-AMARELO Distrófico; LVd: LATOSSOLO VERMELHO Distrófico; LV: LATOSSOLO VERMELHO; 2Soil collected in the municipality of Maringá, representative of Arapongas sector. 3Soil analysis: granulometry by hidrometer method; Ca2+, Mg2+, Al3+ (extracted with KCl 1mol L-1); H+Al3+ (Estimated by pH-SMP); organic carbon (OC) (volumetric method by potassium dichromate); K+ and P (Mehlich-1 extraction).

Each soil was incubated with increasing rates of alkaline sewage sludge from their respective sector. The incubation assay was employed according to the official methodology described in Brasil (2006). Each soil was incubated with five rates of alkaline sewage sludge (0, 10, 20, 40, and 80 Mg ha-1 of total solids), with three replications. After 60 days of incubation, soil samples were: collected; air dried; ground; homogenized; passed through a 2 mm sieve. The pH of the samples was determined (CaCl2 0.01 mol L-1; soil:solution 1:2.5) (Table 2). To analyze the Zn, Cu and Mn availability, 10 cm3 of soil sample were transferred into glass flasks (150 ml) and then added to 100 mL of Mehlich-1 (0.05 mol L-1 HCl + 0.0125 mol L-1 H2SO4). The flasks remained in a horizontal shaker for 5 minutes and then at rest for one night. The Zn, Cu and Mn concentrations were then determined in the equilibrium solution by atomic absorption spectrometry (Varian, AA240FS).

Table 2: pH-CaCl2 values obtained in soil corresponding to each sector after incubation with increasing rates of the respective alkaline sewage sludge of Paraná State, Brazil. 

Sector Sewage sludge (Mg ha-1)
0 10 20 40 80
Apucarana 5.1 5.8 6.2 6.8 7.6
Cascavel 4.0 4.5 4.9 5.7 6.6
Campo Mourão 4.0 5.0 5.7 6.5 7.5
Francisco Beltrão 4.0 4.3 4.5 5.1 6.3
Foz do Iguaçu 5.1 6.0 6.7 7.6 8.1
Guarapuava 4.4 4.5 5.2 6.2 7.3
Londrina 5.0 5.9 6.5 7.2 7.9
Maringá 4.3 5.4 6.4 7.2 7.6
Pato Branco 3.8 4.2 4.6 5.4 6.4
Pinhais 4.2 4.6 4.9 5.5 6.5
Toledo 3.9 4.7 5.5 6.5 7.3
Cornélio Procópio 4.9 6.3 7.2 7.7 8.2
Santo Antônio da Platina 5.3 5.9 7.1 7.8 8.2
Arapongas 1 3.8 5.1 6.6 7.6 8.2
Matinhos 5.6 6.3 6.8 7.2 7.7
Ponta Grossa 4.5 6.7 7.8 8.2 8.6
Rio Negro 5.7 6.2 6.6 7.4 8.2
Telêmaco Borba 3.8 4.9 5.7 7.2 7.8
Paranavaí 4.5 7.0 7.1 8.2 8.5
Umuarama 4.2 6.0 7.3 7.8 8.4
Mean 4.5 5.5 6. 2 6.9 7.6

1Soil collected in the municipality of Maringá, representative of Arapongas sector.

For each soil, data on Zn, Cu and Mn availability were subjected to analysis of variance (ANOVA), following a completely randomized design with three replications. When ANOVA was significant (p <0.05), the data were subjected to regression analysis, choosing the model with the highest coefficient of determination (R2) and significance (p <0.05 or p <0.01). To determine the Zn, Cu and Mn recovery efficiency (by Mehlich-1 extraction) as a function of the amount of these elements added to the alkaline sewage sludge application, the following formula was used:

where: ER, element recovery (%); Czero, element content in soil without alkaline sewage sludge aplication (mg kg-1); Css, element content in soil with alkaline sewage sludge application (mg kg-1); EASS, element addition with sewage sludge (kg ha-1).

RESULTS AND DISCUSSION

The total Zn, Cu and Mn contents in the alkaline sewage sludge were varied greatly (Table 3). All Zn values observed are below the average value of 369 mg kg-1, observed by Bittencourt et al. (2014) for 99 batches of alkaline sewage sludge, intended for agricultural use, from 2007 to 2010 in the metropolitan region of Curitiba. For Cu values, nine alkaline sewages sludges were higher than the average 96.8 mg kg-1 obtained by Bittencourt et al. (2014). However, both elements were below the total values of 3,176 mg kg-1 for Zn and 1,019 mg kg-1 for Cu, obtained by Rangel et al. (2006), who studied sludge coming from the wastewater treatment plant of Barueri, São Paulo, which deals with domestic and industrial sewage.

Table 3: Total content and added amounts of Zn, Cu and Mn in 20 alkaline sewage sludges from Paraná state (Brazil) and maximum values established by Sema and Conama regulations. 

Sector Total content (mg kg-1) Zn ------ (kg ha-1) ------ Cu ------ (kg ha-1) ------ Mn ------ (kg ha-1) ------
Zn Cu Mn 10 20 40 80 10 20 40 80 10 20 40 80
Apucarana 212 36 88 2.1 4.2 8.4 16.9 0.3 0.7 1.4 2.8 0.8 1.7 3.5 7.0
Cascavel 307 163 105 3.0 6.1 12.2 24.5 1.6 3.2 6.5 13.0 1.0 2.1 4.2 8.4
Campo Mourão 258 79 135 2.5 5.1 10.3 20.6 0.7 1.5 3.1 6.3 1.3 2.7 5.4 10.8
Francisco Beltrão 265 70 107 2.6 5.3 10.6 21.2 0.7 1.4 2.8 5.6 1.0 2.1 4.2 8.5
Foz do Iguaçu 51 42 63 0.5 1.0 2.0 4.0 0.4 0.8 1.6 3.3 0.6 1.2 2.5 5.0
Guarapuava 226 49 190 2.2 4.5 9.0 18.0 0.4 0.9 1.9 3.9 1.9 3.8 7.6 15.2
Londrina 304 635 148 3.0 6.0 12.1 24.3 6.3 12.7 25.4 50.8 1.4 2.9 5.9 11.8
Maringá 260 189 68 2.6 5.2 10.4 20.8 1.8 3.7 7.5 15.1 0.6 1.3 2.7 5.4
Pato Branco 254 101 87 2.5 5.0 10.1 20.3 1.0 2.0 4.0 8.0 0.8 1.7 3.4 6.9
Pinhais (CMR) 1 319 81 117 3.1 6.3 12.7 25.5 0.8 1.6 3.2 6.4 1.1 2.3 4.6 9.3
Toledo 302 126 94 3.0 6.0 12.0 24.1 1.2 2.5 5.0 10.0 0.9 1.8 3.7 7.5
Cornélio Procópio 96 108 77 0.9 1.9 3.8 7.6 1.0 2.1 4.3 8.6 0.7 1.5 3.0 6.1
Santo Antônio da Platina 271 78 127 2.7 5.4 10.8 21.6 0.7 1.5 3.1 6.2 1.2 2.5 5.0 10.1
Arapongas 2 289 104 107 2.8 5.7 11.5 23.1 1.0 2.0 4.1 8.3 1.0 2.1 4.2 8.5
Matinhos 288 81 126 2.8 5.7 11.5 23.0 0.8 1.6 3.2 6.4 1.2 2.5 5.0 10.0
Ponta Grossa 249 48 147 2.4 4.9 9.9 19.9 0.4 0.9 1.9 3.8 1.4 2.9 5.8 11.7
Rio Negro 256 53 158 2.5 5.1 10.2 20.4 0.5 1.0 2.1 4.2 1.5 3.1 6.3 12.6
Telêmaco Borba 284 68 112 2.8 5.6 11.3 22.7 0.6 1.3 2.7 5.4 1.1 2.2 4.4 8.9
Paranavaí 295 238 120 2.9 5.9 11.8 23.6 2.3 4.7 9.5 19.0 1.2 2.4 4.8 9.6
Umuarama 298 137 103 2.9 5.9 11.9 23.8 1.3 2.7 5.4 10.9 1.0 2.0 4.1 8.2
Sema 021/09 2 2,500 1,000 nd
Conama 375/06 3 2,800 1,500 nd

1CMR: Curitiba metropolitan region; 2Paraná (2009); 3Brasil (2006). nd: not available.

The values comply with the current legislation for maximum state (Sema 021/09) (Paraná, 2009) and federal levels permitted (Conama 375/06) (Brazil, 2006), with no limitation as to use. These low values are due mainly to low or no presence of industrial dumping in the sewage disposal system, since the policy is to treat industrial sludge before its release into the collection network and Sanepar has restrictive policies regarding reception of industrial wastewater in the sewage system (Paraná, 2013).

The results presented in Table 4 indicate a linear increase of Zn in 17 of the 20 analyzed soils after application of alkaline sewage sludge. The increase occurred despite an increase in pH, that at a rate of 80 Mg ha-1, promoted pH-CaCl2 increases to values ​​above 7 in most soils, with an average of 7.6 (Table 2). As a result, the availability of the elements can be affected, with their liberation into the soil solution or with retention/precipitation (Berton & Nogueira, 2010). Decreased Zn availability with increasing pH is well known and, according to Nachtigall, Nogueirol and Alleoni (2009), this fact is related to the transition of exchangeable Zn to no-exchangeble forms, resulting in precipitation of insoluble forms, such as oxides and organic complex.

Table 4: Available Zn in soils of Paraná state (Brazil) as a function of increasing sludge rates from their respective sector and the best regression equations. 

TC1 Sector Alkaline sewage sludge (Mg ha-1) Sig Equation R2 CV
0 10 20 40 80
-------- Available Zn (mg dm-3) -------- %
Apucarana 4.7 § 6.4 7.7 9.6 15.5 § ** y = 4.869 + 0.131x 0.99 3.2
Cascavel 3.5 § 5.2 7.2 11.3 17.3 § ** y = 3.673 + 0.174x 0.99 4.8
Campo Mourão 1.6 / 1.4 1.6 2.3 4.3 § ** y = 1.106 + 0.038x 0.94 10.3
Francisco Beltrão 1.2 † 1.4 1.9 2.9 5.1 § ** y = 0.976 + 0.051x 0.99 11.3
Very clayey Foz do Iguaçu 3.0 § 2.6 2.9 3.2 2.9 § ns --- --- 14.1
Guarapuava 2.9 § 4.0 3.0 3.1 5.1 § ns --- --- 3.1
Londrina 1.6 / 3.2 6.0 10.1 15.6 § ** y = 1.960 + 0.178x 0.98 4.5
Maringá 4.1 § 4.2 5.8 8.8 10.3 § ** y = 4.094 + 0.085x 0.91 5.8
Pato Branco 1.2 † 3.4 2.3 3.1 5.9 § ** y = 1.687 + 0.050x 0.81 33.6
Pinhais (CMR)2 3.6 § 4.6 6.0 4.8 6.8 § * y = 4.179 + 0.032x 0.67 27.9
Toledo 1.7 / 3.5 5.6 8.8 14.5 § ** y = 2.035 + 0.159x 0.99 5.5
Clayey Cornélio Procópio 3.5 § 3.8 4.2 5.4 6.9 § ** 0.0435x + 3.455 0.99 8.3
St Ant da Platina 2.5 / 3.0 8.5 5.5 3.5 § ns --- --- 6.4
Arapongas 3.6 § 3.4 5.6 11.0 18.3 § ** y = 2.447 + 0.197x 0.97 10.8
Matinhos 1.7 / 2.3 3.7 5.0 6.4 § ** y = 2.080 + 0.058x 0.93 14.5
Ponta Grossa 2.4 § 2.8 3.5 5.8 7.6 § ** y = 2.381 + 0.068x 0.97 4.1
Medium texture Rio Negro 1.5 † 2.4 2.5 2.7 6.2 § ** y = 1.400 + 0.055x 0.91 23.7
Telêmaco Borba 1.2 † 3.3 2.9 6.3 10.4 § ** y = 1.440 + 0.113x 0.97 17.8
Paranavaí 0.7 ‡ 6.6 9.5 12.5 17.8 § ** y = 3.676 + 0.191x 0.89 9.9
Umuarama 1.8 / 3.3 5.5 8.0 12.3 § ** y = 2.276 + 0.130x 0.98 5.3

1TC = textural class; 2CMR = Curitiba metropolitan region; Costa and Oliveira (1998), § = high available Zn in soil; / = good available Zn in soil; † = mean available Zn in soil; ‡ = low available Zn in soil; ns = not significant; * and **significant at 5 and 1%, respectively; cv = coeficient of variation.

However, the acid solution of Mehlich-1 can extract insoluble soil Zn forms, not satisfactorily discriminating the pH effect on Zn availability for plants (Abreu; Lopes; Santos, 2007). This is due to a greater extraction ability of Mehlich-1 compared to other extractors (such as DTPA, for example), a capacity assigned to less weakening of the acid solution in more buffered conditions (Oliveira et al., 1999). This fact indicates an increase in critical Zn level in soils with high pH for plant growth. In this direction, Reszel, Reszel and Glowacka (2007) evaluated the influence of sewage sludge and a mixture (sewage sludge, sugar beet residue and ash) on available soil Zn and Cu content (1 mol L-1 HCl extractant) and in corn plants and observed that: in soil, the application of sewage sludge or sludge + waste, increased the levels of these micronutrients; in plants, the two micronutrients decreased. However, it is important to note that the Zn availability in soil, evaluated by Mehlich-1, shows good correlation with the amount of this nutrient in the plant shoots (Borges; Coutinho, 2004; Sobral et al., 2013). However, Pontoni (2012) found an increase or maintenance of Zn content in plants in soil amended with alkaline sewage sludge, contrasting with a decrease of Zn with the isolated application of lime.

Of the three soils that showed no increase in Zn content after the addition of alkaline sewage sludge (Table 4), the only soil in which this result may have a plausible explanation is that from Foz do Iguaçu, as it received sludge with the lowest Zn level (51 mg kg-1) (Table 3). The sludges from Guarapuava and Santo Antonio da Platina showed levels of 226 and 271 mg kg-1. The lack of change in Zn availability with the addition of alkaline sewage sludge may be due to the Zn release (which may have been low) from the sludge itself and/or transformation of Zn into forms that the extractant was unable to extract in solid phase. Thus, for a minority of cases, the alkaline sewage sludge will bring no Zn availability benefits, and more studies are needed to identify the factors related to the Zn increase absence.

The magnitude of Zn increase due to alkaline sewage sludge varied between soil and sludge. Alkaline sewage sludge from Pinhais was that with the highest total Zn content (319 mg kg-1), but the increase in available Zn in the soil was 0.032 mg Mg-1 of sludge, reaching values of 1.8 times higher at the maximum rate (80 Mg ha-1) in comparison to soil without sludge application. For Cascavel, Toledo and Londrina, which showed total Zn content in sludge similar to Pinhais, increases in the Zn availability were 4.9; 8.5 and 9.7 fold, following the additions of 0.174; 0.154 and 0.178 mg Mg-1 of sludge, respectively. This result was probably due to higher organic carbon (65 g dm-3) present in Pinhais soil. According to Alloway (1995), the humic substances present a high degree of selectivity for micronutrients; in this case, greater affinity for Cu and lower for Zn, but forming the inner sphere complexes with both elements. Studies with Zn fractionation in soil have reported that with increasing pH, exchangeable Zn decreases, but Zn associated with organic fraction and mineral fraction of the soil present increases (Melo et al., 2008; Torri; Lavado, 2008).

In all soils, Zn available content reached appropriate or high levels from the second rate applied (Table 4), but did not reach levels above 30 mg dm-3, considered excessive (Costa; Oliveira, 1998). However, the total amount of Zn applied to the maximum sludge rate (80 Mg ha-1 x Zn content in the sludge), ranged from 4.1 kg ha-1 (Foz do Iguaçu) to 25.5 kg ha-1 (Pinhais), being higher than those usually recommended. According to Raij et al. (1996), for São Paulo state, the recommended Zn rates range from 1 to 6 kg ha-1 for different crops. The Commission of Chemistry and Soil Fertility (CQFS-RS/SC, 2004), cites that micronutrient deficiency is unlikely in Rio Grande do Sul and Santa Catarina states. However, Motta et al. (2007) report that the Zn appears frequently at critical levels in Paraná soils.

In general, the Zn recovery by the Mehlich-1 extractor ranged from -154% to 399% (Figure 1), and in only three soils were negative recovery values observed (Campo Mourão, Foz do Iguaçu and Arapongas). Negative values indicate a decrease in soil native Zn with alkaline sewage sludge, overlaps the Zn applied. On the other hand, values above 100% suggest that the alkaline sewage sludge, besides making Zn available, intensified the release Zn from low availability forms to available forms.

Figure 1: Zinc recovery (%) (Mehlich-1 extractor) from soils treated with alkaline sewage sludge from Paraná, Brazil. Sector: 1 - Apucarana; 2 - Cascavel; 3 - Campo Mourão; 4 - Francisco Beltrão; 5 - Foz do Iguaçu; 6 - Guarapuava; 7 - Londrina; 8 - Maringá; 9 - Pato Branco; 10 - Pinhais; 11 - Toledo; 12 - Cornélio Procópio; 13 - Santo Antônio da Platina; 14 - Arapongas; 15 - Matinhos; 16 - Ponta Grossa; 17 - Rio Negro; 18 - Telêmaco Borba; 19 - Paranavaí; 20 - Umuarama.  

In very clayey and clayey soils Zn recovery for the highest rate (80 Mg ha-1) ranged from -5 to 127% (Figure 1). The highest values were observed in Apucarana (127%), Londrina (115%), Cascavel (112%) and Toledo (106%) soils, that received sludge with Zn levels above 212 mg kg-1 (Table 3). Despite the high clay content and probably higher oxide contents, which could promote high adsorption specific Zn (Birth; Supplies, 2004; Motta et al., 2007), the results for the four above-mentioned soils (higher recovery Zn) indicate that the Zn availability varied with the soil attributes and nutrient content of each sludge. These results emphasize that in this study, the effect of soil pH, after alkaline sewage sludge application, had little influence on the availability of Zn by the Mehlich-1 extractor.

The medium texture soils presented Zn recovery varying between 41 and 144% in application of 80 Mg ha-1 (Figure 1), and the Paranavaí soil presented the higher rate (144%) of Zn recovery. However, it is noteworthy that this soil has a clay content of 150 g kg-1, near the lower limit for sandy soils, and in soils like this, the maximum application rate of alkaline sewage sludge (Poggere et al., 2012) is much less than the highest rate (80 Mg ha-1) used in this study. Similar results was observed in Arapongas and Umuarama soils, with clay contents of 250 and 200 g kg-1, and 127 and 88% recovery rates, respectively, for the rate of 80 Mg ha-1. In this condition, due to the smaller amount of clay, Zn released from sludge probably had low adsorption on the soil solid phase (Abreu; Lopes; Santos, 2007), allowing high recovery values.

Similar to that observed for Zn, Cu availability after addition of alkaline sewage sludge varied depending on the soil (Table 5). But unlike Zn, responses ranged from a Cu decrease to increase. This can be explained by the lower Cu content in the sludge, compared to Zn, except for Londrina sludge. A direct relationship between sludge rate and available Cu was observed; with linear and quadratic equations for 9 soils and 1 soil. However, an inverse relationship was observed with linear and quadratic equations for 8 soils and 1 soil. That is, only one soil did not present a change resulting from the alkaline sewage sludge application.

Table 5: Available Cu in soils of Paraná state (Brazil) as a function of increasing sludge rates from their respective sector and the best regression equations. 

TC1 Sector Alkaline sewage sludge (Mg ha-1) Sig Equation R2 CV
0 10 20 40 80
------- Available Cu (mg dm-3) ------ %
Apucarana 10.6 ¥ 8.9 8.9 8.7 6.6 § * y = 10.002 - 0.041x 0.86 5.2
Cascavel 7.6 § 8.2 8.4 8.5 9.1 ¥ ** y = 7.890 + 0.016x 0.85 3.5
Campo Mourão 5.9 § 5.3 4.9 4.5 4.4 § ** y = 5.512 - 0.017x 0.76 4.2
Francisco Beltrão 12.4 ¥ 11.0 10.1 9.9 11.3 ¥ ** y = 12.2 - 0.116x + 0.001x2 0.94 5.3
Very clayey Foz do Iguaçu 10.5 ¥ 8.6 8.5 8.3 7.5 § ** y = 9.536 - 0.029x 0.67 5.1
Guarapuava 2.8 § 2.8 2.6 2.2 2.1 § ** y = 2.800 - 0.010x 0.89 22.8
Londrina 13.0 ¥ 16.1 18.6 21.1 20.7 ¥ ** y = 15.317 + 0.086x 0.65 5.6
Maringá 3.5 § 2.9 3.2 3.0 1.8 / ** y = 3.437 - 0.018x 0.83 6.1
Pato Branco 3.8 § 3.6 3.7 3.3 3.1 / ** y = 3.747 - 0.008x 0.81 33.6
Pinhais (RMC)2 2.9 § 2.7 2.5 2.5 1.4 † ** y = 2.905 - 0.017x 0.91 17.9
Toledo 8.0 ¥ 8.3 8.4 8.7 8.1 ¥ ns --- --- 5.6
Clayey Cornélio Procópio 9.3 ¥ 9.6 8.9 8.4 6.8 § ** y = 9.631 - 0.034x 0.96 3.7
St. Ant. da Platina 8.9 ¥ 9.5 11.8 11.2 9.9 ¥ ** y = 8.9 + 0.125x - 0.001x2 0.75 5.8
Arapongas 1.0 † 1.2 1.3 1.6 1.6 / ** y = 1.089 + 0.007x 0.77 13.4
Matinhos 2.2 § 2.1 2.3 2.6 2.7 § ** y = 2.158 + 0.007x 0.84 8.1
Ponta Grossa 1.9 / 1.9 2.1 2.2 2.2 § ** y = 1.931 + 0.004x 0.72 11.2
Medium texture Rio Negro 1.7 / 1.8 2.0 1.9 2.1 § ** y = 1.775 + 0.004x 0.86 3.6
Telêmaco Borba 0.9 † 1.4 1.3 1.5 1.8 / ** y = 1.084 + 0.010x 0.82 6.2
Paranavaí 1.2 † 2.0 2.9 4.7 7.4 § ** y = 1.289 + 0.077x 0.99 14.7
Umuarama 2.1 § 2.3 2.7 2.9 3.1 § ** y = 2.295 + 0.011x 0.81 4.9

1 TC = textural class; 2 CMR = Curitiba metropolitan region; Costa and Oliveira (1998), ¥ = very high available Cu in soil; § = high available Cu in soil; / = good available Cu in soil; † = mean available Cu in soil; ‡ = low available Cu in soil; ns = not significant; * and **significant at 5 e 1%, respectively; cv = coeficient of variation.

The Cu availability decreases with the use of alkaline sewage sludge were observed in 9 of 13 clayey and very clayey soils (Table 5). In addition to the higher clay content, this group of soils showed high organic carbon content. Thus, smaller increases in Cu compared to Zn are evident, as well as the importance of the texture in the Cu response due to sludge.

The lowest Mehlich-1 Cu extraction ability, compared to Zn was observed; and is possibly related to at least three reasons: 1) Cu has a lower hydrolysis constant than Zn, which is related to the formation of complexes with higher binding energy (Sparks, 2003); 2) Cu has a higher electronegativity than Zn, being more strongly bound by the mineral constituents of the soil (Arias et al, 2006); 3) Cu has a higher affinity for organic matter in comparison to Zn (Souza et al., 2012).

Corroborating the Cu availability decrease results, Fan et al. (2011) observed reduction in exchangeable content (readily available) and increase in content in the oxides and the residual fraction after application of alkaline sludge. The authors explain the reduction of Cu exchangeable by its precipitation in the form of carbonates. On the other hand, the increase in Cu availability in soil with very clayey texture (Table 5) can be justified by the high Cu content in Londrina sludge (635 mg kg-1), well above the levels the other sludges (mean 97 mg kg-1, range: 36-238 mg kg-1) (Table 3). For Cascavel soil this result was not expected, which has a quarter of Londrina sludge content and high carbon (30.7 g dm-3) and clay content (850 g kg-1), which would provide a high adsorption capacity to the soil.

Of the other soils that showed an increase in the Cu availability in response to the sludge addition, all have a medium texture (300-150 g kg-1). As a result, buffering capacity of these soils is low, which reduces the capacity of the solid phase to adsorb Cu added via sludge. Another consequence of the low buffering capacity of medium texture soils is that there was no effect on the extraction capacity of the Mehlich-1, even with increasing pH values above 7 in the higher sludge rate. This effect is evident when one carefully examines the soil characteristics. The increase in the available Cu in Paranavaí soil at a high sludge rate (80 Mg ha-1) was 6.1 fold, in comparison to the soil that did not received sludge, while in the remaining medium texture soils, increases were between 1.1 and 2.0 fold. This result is a consequence of the low clay (150 g kg-1) and organic carbon content (5.1 g dm-3) of Paranavaí soil and higher Cu content in the sludge (137 mg kg-1), compared to sludge applied to medium texture soils.

In general, the Cu recovery by Mehlich-1 extractor was negative for seven very clayey soils (Figure 2). There was Cu retention in these soils and the addition of sludge acts more like a drain than as a source, due to the influence of the pH increase on the increase of the Cu adsorption capacity for the mineral or organic soil fraction (Arias et al., 2006; Souza et al., 2012). But, the Cu recovery was positive for two very clayey, one clayey and six medium texture soils (Figure 2). Thus, besides the soil ability to adsorb Cu, other factors affect the recovery (e.g., amount of Cu added via sludge, sludge decomposition and mineralization of Cu).

Figure 2: Copper recovery (%) (Mehlich-1 extractor) from soils treated with alkaline sewage sludge from Paraná, Brazil. Sector: 1 - Apucarana; 2 - Cascavel; 3 - Campo Mourão; 4 - Francisco Beltrão; 5 - Foz do Iguaçu; 6 - Guarapuava; 7 - Londrina; 8 - Maringá; 9 - Pato Branco; 10 - Pinhais; 11 - Toledo; 12 - Cornélio Procópio; 13 - Santo Antônio da Platina; 14 - Arapongas; 15 - Matinhos; 16 - Ponta Grossa; 17 - Rio Negro; 18 - Telêmaco Borba; 19 - Paranavaí; 20 - Umuarama. 

The amount of total Cu applied per hectare to the soil with the sludge at the largest sludge rate (80 Mg ha-1 x Cu content in the sludge), ranged from 3 to 51 kg ha-1. These Cu values are higher than generally recommended. According to Raij et al. (1996), for São Paulo state, the recommended Cu rates range from 1 to 5 kg ha-1 for different cultures. But, Cu and Zn have long residual effect in the soil, according to Fan et al. (2011), this residual effect is due to the prevalence of specific adsorption to soil mineral and organic colloids. Thus, monitoring Cu content in the soil is necessary to avoid high sludge applications rates causing Cu toxicity in plants, especially in soils with low buffering capacity.

Unlike Zn, the Mn availability after the addition of alkaline sewage sludge decreased in 15 soils, increased in two soils and did not change in three (Table 6). The amount of Mn applied, generally, is near that applied to Cu, which indicates that not only the amount should be considered. Thus, decreasing levels of available Mn in these soils is directly linked to increased sensitivity of the element to the pH change (Abreu; Lopes; Santos, 2007). With the increase of the soil pH, the Mn2+ cationic form is converted into manganic oxides (Hue; May, 2002) or strongly bound to organic matter (Moreira et al., 2016; Nachtigall; Nogueirol; Alleonni, 2009).

Table 6: Available Mn in soils of Paraná state (Brazil) as a function of increasing sludge rates from their respective sector and the best regression equations. 

TC1 Sector Alkaline sewage sludge (Mg ha-1) Sig Equation R2 CV
0 10 20 40 80
------ Available Mn (mg dm-3) ------ %
Apucarana 195 ¥ 179 174 153 160 ¥ ** y = 89.434 - 0.182x 0.65 7.8
Cascavel 149 § 142 136 134 137 § ns --- --- 6.3
Campo Mourão 42 § 36 31 27 26 § ** y = 38.308 - 0.185x 0.72 10.9
Francisco Beltrão 104 § 93 90 79 78 § ** y = 98.439 - 0.303x 0.76 8.1
Very clayey Foz do Iguaçu 192 ¥ 165 148 133 135 § ** y = 173.530 - 0.609x 0.62 4.5
Guarapuava 67 § 59 52 43 44 § ** y = 61.468 - 0.264x 0.69 8.1
Londrina 221 ¥ 208 200 192 165 ¥ ** y = 217.200 - 0.658x 0.98 3.8
Maringá 186 ¥ 160 155 123 83 § ** y = 178.820 - 1.228x 0.98 6.2
Pato Branco 43 § 32 31 32 28 § ** y = 37.593 - 0.133x 0.53 10.6
Pinhais (RMC)2 35 § 23 13 11 9 / ** Y = 26.573 - 0.267x 0.60 12.0
Toledo 95 § 83 83 81 76 § ** y = 89.434 - 0.182x 0.65 7.9
Clayey Cornélio Procópio 188 ¥ 176 159 147 167 ¥ ** y = 175.030 - 0.239x 0.23 4.7
St Ant da Platina 182 ¥ 180 160 169 166 ¥ * y = 176.530 - 0.158x 0.31 5.5
Arapongas 47 § 39 41 36 39 § * y = 43.158 - 0.073x 0.34 9.7
Matinhos 1.7 ‡ 2.0 3.2 3.4 3.5 ‡ ** y = 2.145 + 0.021x 0.64 19.5
Ponta Grossa 12 / 10 10 10 11 / ** y = 11.6 - 0.079x + 0.001x2 0.68 7.8
Medium texture Rio Negro 11 / 10 10 9.9 11 / * y = 11.5 - 0.081x + 0.001x2 0.40 8.7
Telêmaco Borba 11 / 13 14 17 17 § ** y = 12.361 + 0.082x 0.82 9.3
Paranavaí 66 § 48 54 62 67 § * y = 59.6 - 0.249x + 0.004x2 0.38 12.3
Umuarama 87 § 65 74 54 50 § * y = 78.721 - 0.408x 0.70 27.0

1 TC = textural class; 2CMR = Curitiba metropolitan region; Costa and Oliveira (1998), ¥ = very high available Mn in soil; § = high available Mn in soil; / = good available Mn in soil; † = mean available Mn in soil; ‡ = low available Mn in soil; ns = not significant; * and **significant at 5 e 1%, respectively; cv = coeficient of variation.

On the other hand, Matinhos and Telêmaco Borba, who obtained an increase in Mn availability, showed behavior contrary to other soils with similar clay and organic matter content. Borges and Coutinho (2004) applied sewage sludge with and without lime in two soils, and observed an increase in available Mn extracted by Mehlich-1. Abreu et al. (2004) point out that higher values of Mn extracted by Mehlich-1 solution (acidic solution) and Mehlich-3 (mixed solution) may be due to greater capacity for solubilizing Mn in some soils, particularly when linked to iron oxides.

The Mn recovery by Mehlich-1 extractor was negative in 18 soils, with very low levels, reaching -8571% (Foz do Iguaçu soil, at a rate of 10 Mg ha-1) (Figure 3). The extremely low recovery values demonstrate how Mn is influenced by pH values and Mn content in sewage sludge. In practical terms, the decrease in Mn may be a positive aspect, since it is the second most likely element to cause toxicity in acid soils (Millaleo et al., 2010). Therefore, the pH increase and decrease in Mn availability can mean its toxicity decrease and a benefit to plants. Corroborating the results of this study, Pontoni (2012) found a large decrease in Mn content in leaf tissue as a result of the alkaline sewage sludge application in soil. However, we found that despite the decrease in the Mn availability in most soils, there was virtually no change in the interpretation of Mn level in the soil (Table 6).

Figure 3: Manganese recovery (%) (Mehlich-1 extractor) from soils treated with alkaline sewage sludge from Paraná, Brazil. Sector: 1 - Apucarana; 2 - Cascavel; 3 - Campo Mourão; 4 - Francisco Beltrão; 5 - Foz do Iguaçu; 6 - Guarapuava; 7 - Londrina; 8 - Maringá; 9 - Pato Branco; 10 - Pinhais; 11 - Toledo; 12 - Cornélio Procópio; 13 - Santo Antônio da Platina; 14 - Arapongas; 15 - Matinhos; 16 - Ponta Grossa; 17 - Rio Negro; 18 - Telêmaco Borba; 19 - Paranavaí; 20 - Umuarama. 

The positive Mn recovery occurred in two soils (Matinhos and Telêmaco Borba) (Figure 3), and these soils showed good Mn content and low availability, respectively (Table 6). However, the level of interpretation changed (high) only for Telêmaco Borba soil. Thus, in these two soils, applications of alkaline sewage sludge had no significant impact as a Mn source. It is worth noting that the Mn deficiency has been observed especially in soils receiving excessive liming (Tanaka; Mascarenhas; Bulisani, 1993) or in systems that favor the accumulation of organic matter, such as the no-tillage system (Moreira et al., 2016).

CONCLUSIONS

The alkaline sewage sludge from Paraná state had a distinct effect on the three micronutrients. There was an increase in Zn availability for most soils, especially sandy soils. Available Cu presented a decrease with alkaline sewage sludge application in very clayey soil, suggesting that the increase in the adsorption/precipitation overlaps via the sludge addition. However, in soils with lower adsorption capacity, the opposite occurs. Therefore, two attributes were keys in the effect of the alkaline sewage sludge Cu availability, texture and Cu content in the sludge. The high sensitivity of Mn to pH elevation resulted in a decrease in availability. Thus, regardless of the Mn content in the sludge, raising the pH decreased the Mn availability.

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Received: September 18, 2016; Accepted: October 31, 2016

*Corresponding author: mottaufpr@gmail.com

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