Removal of heavy metals from industrial sludge with new plant–based washing agents

Journal Pre-proof Removal of heavy metals from industrial sludge with new plant–based washing agents Xiaoxun Xu, Yan Yang, Guiyin Wang, Shirong Zhang, Zhang Cheng, Ting Li, Zhanbiao Yang, Junren Xian, Yuanxiang Yang, Wei Zhou PII:

S0045-6535(20)30006-0

DOI:

https://doi.org/10.1016/j.chemosphere.2020.125816

Reference:

CHEM 125816

To appear in:

ECSN

Received Date: 14 September 2019 Revised Date:

7 December 2019

Accepted Date: 1 January 2020

Please cite this article as: Xu, X., Yang, Y., Wang, G., Zhang, S., Cheng, Z., Li, T., Yang, Z., Xian, J., Yang, Y., Zhou, W., Removal of heavy metals from industrial sludge with new plant–based washing agents, Chemosphere (2020), doi: https://doi.org/10.1016/j.chemosphere.2020.125816. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

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Removal of heavy metals from industrial sludge with new

2

plant–based washing agents

3

Xiaoxun Xu a,b,1, Yan Yang a,1, Guiyin Wang a,b, Shirong Zhang a,b,*, Zhang

4

Cheng a, Ting Li c, Zhanbiao Yang a, Junren Xian a, Yuanxiang Yang a and Wei

5

Zhou c

6 7

a. College of Environmental Sciences, Sichuan Agricultural University, Chengdu 611130, China;

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b. Key Laboratory of Soil Environment Protection of Sichuan Province, Chengdu 611130, China

9

c. College of Resources, Sichuan Agricultural University, Chengdu 611130, China

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1. These authors contributed equally to this work and should be considered co–first authors

11 12

* Correspondence: [email protected]; Tel.: +86–28–8629–0995

1

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Abstract: Washing is one of the techniques for permanent removal of heavy metals

14

from industrial sludge, for which washing agents are a key influence factor. However,

15

high–efficiency, eco–friendly, and inexpensive agents are still lacking. In this study, the

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solutions derived from the three plant materials including Fatsia japonica, Hovenia

17

acerbaand Pterocarya stenoptera were employed to remove Cd, Cu, Pb, and Ni from

18

industrial sludge. The effects of washing solution concentration, pH, washing time and

19

temperature on metal removal were investigated. The metal removal efficiencies were

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found to increase with increasing solution concentrations or washing temperatures,

21

decline with increasing pH, and presented various trends with increasing washing time.

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Among the three agents that derived from H. acerba showed relatively high removal

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for Cu (75.81%), Pb (63.42%), Ni (27.52%), and Cd (56.99%). After washing,

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environmental risks of residual metals were markedly diminished in sludge,

25

attributable to decrease in their exchangeable forms. Furthermore, the applications of

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the plant washing agents increased sludge organic carbon, alkali–hydrolysable

27

nitrogen, available phosphorus, and available potassium. Fourier transform infrared

28

spectroscopy analysis suggested that the hydroxyl, carboxyl, ether, and amide may be

29

the main functional groups in the three plant materials binding the heavy metals.

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Overall, the agent derived from H. acerba appears to be a feasible washing material

31

for heavy metals removal from sludge.

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Keywords: Plant washing agent; Industrial sludge; Heavy metals; Hovenia acerba

2

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1. Introduction

34

A large amount of sludge is inevitably produced in various industries, such as

35

electroplating, tanning, and mechanical manufacturing processing (Kulkarni et al.,

36

2019; Yadav and Garg, 2019). One of the most potential of handling sludge is the

37

application to land for improving soil fertility and structure (Suanon et al., 2016; Xu et

38

al., 2017; Tang et al., 2018; Li et al., 2019a). However, because potentially toxic

39

elements in sludge such as Cd, Pb, Ni, and Cu pose serious threats to plant, animal, and

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human health (Lee et al., 2017; Li et al., 2019b), it is crucial to develop effective

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strategies to reduce and remove these metals from sludge (Dai et al., 2019).

42

The techniques of bioleaching, supercritical fluid extraction, electrokinetic

43

separation, and chemical washing have been developed for the removal of heavy

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metals in sludge ( Park et al., 2013; Xu et al., 2017; Marchenko et al., 2018; Tang et al.,

45

2018). Among these methods, chemical washing has been attracting more attention

46

owing to its unsophisticated operation, high efficiency, and relatively inexpensive cost

47

(Wu et al., 2015). Heavy metals removal with chemical washing is closely associated

48

with washing agents (WSA), pH, washing time, and contact temperature (Piccolo et

49

al., 2019). Recently, acids, chelates, and surfactants have been employed to extract

50

heavy metals from sludge (Gusiatin and Klimiuk, 2012; Suanon et al., 2016). However,

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they negatively affect sludge fertility and microbial properties (Ren et al., 2015). For

52

example, washing with N, N–bis (carboxymethyl) glutamic acid and citric acid

53

decreased the total nitrogen, total phosphorus, and total potassium of sludge (Ren et 3

54

al.,

2015;

Wang

et

al.,

2015).

Previous

study

have

reported

that

55

ethylenediaminetetraacetic acid may pose a high risk to microorganisms and plants due

56

to poor biodegradability and high persistence in soil, and result in secondary pollution

57

via leaching to groundwater (Wu et al., 2015; Suanon et al., 2016). Therefore,

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biodegradability and minimal damage to sludge fertility are consequential

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considerations when searching for highly efficient WSA.

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WSA derived from plant materials may be a promising alternative to these

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disadvantageous materials as they contain various functional groups that could bind

62

with metal cations (Sfaksi et al., 2014; Ali et al., 2016). Some studies had reported that

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water–soluble extracts of certain plant species, such as pineapple peel, soybean straw,

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Clematis brevicaudata and Coriaria nepalensis, can diminish soil nutrient loss and

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maintain soil organic matter (Cao et al., 2017; Feng et al., 2018). Furthermore, plant

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materials are biodegradable, widely sourced, and of low–cost. Therefore, it is

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essential to investigate more plant materials.

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Fatsia japonica (FJ) and Hovenia acerba (HA) contain various active constituents,

69

such as triterpenoid saponins, flavonoids, and fatty acids (Aoki et al., 1976; Zhang et

70

al., 2012; Ye et al., 2014), and the major ingredients of Pterocarya stenoptera (PS) are

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tannin, naphthoquinone, terpene, and steroid (Zhang et al., 2014; Xu et al., 2015).

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They have potential to bind with metal cations. Nevertheless, previous research on

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plant WSA mainly focused on soil heavy metals treatment (Cao et al., 2017; Feng et

74

al., 2018). It would thus be interesting to test the capacity of removing heavy metals 4

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from sludge using plant WSAs. Therefore, screening of plant WSAs for sludge

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washing is significant.

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The aims of our study are to explore the efficiencies of FJ, HA, and PS for heavy

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metals removal (Cd, Cu, Pb, and Ni), reveal changes in characteristic functional

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groups, identify the feasibility of sludge for land application, and provide evidence

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and reference to achieve land application of sludge.

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2. Materials and methods

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2.1. Samples preparation and characterization

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Metal–contaminated sludge samples were derived from an industrial sewage

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treatment plant (104.35°E, 31.07°N) in Sichuan, China. The sludge was air–dried,

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ground, and then sieved (200 mesh) prior to chemical analysis. Heavy metals in the

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sludge were digested with a 1:1:1 HNO3–HF–HClO4 mixture (Wang et al., 2016) and

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measured by a flame atomic absorption spectrophotometer (FAAS, Thermo Solaar M6,

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Thermo Fisher Scientific Ltd., USA). The concentrations of Cd, Pb, Ni, and Cu in the

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sludge were 6.22, 53.9, 139.95, and 104.30 mg kg–1.

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HA, FJ, and PS were obtained from the fields in Chengdu, Sichuan. They were

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air–dried, ground, passed through the 50 mesh, and then added into plastic bottles with

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1000 mL distilled water. The bottles were continuously shaken on a shaker (150 rpm,

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24 h) at 25 °C. Subsequently, the suspensions were filtered to collect their extracts. By

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adding different weights of plant materials, a series of WSA from HA,FJ, and PS with

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different concentrations was prepared for the washing experiment (Feng et al., 2018). 5

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Their concentrations were expressed as the ratio of the initial mass of plant powder and

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the volume of the distilled water. The WSAs were then stored at 4 °C, and none of the

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heavy metals (Cd, Cu, Pb, and Ni) were detected in the WSAs by FAAS.

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2.2. Sludge washing experiments

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Acid–rinsed plastic bottles (100.00 mL) containing 2.00 g sludge were prepared

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for washing experiments, followed by the addition of WSA (40.00 mL). Control

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experiments were conducted by distilled water. The suspensions were filtrated after

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shaking. The concentrations of Cd, Cu, Pb, and Ni in the filtrate were measured by

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FAAS. The effects of WSA concentration, washing time, pH level and temperature

105

were investigated as follows:

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In order to investigate the effect of WSA concentration, the experiment was

107

conducted with the WSA concentration ranging from 20.00 g L–1 to 100.00 g L–1 for

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180 min at an initial pH of 4.0.

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The effect of washing time on the heavy metals removal of 50.00 g L–1 WSA was

110

investigated at an initial pH of 4.0. The experiment was conducted at different time

111

intervals (5, 30, 60, 120, 180, and 240 min).

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Five different pH levels (3.0–7.0) were applied to 50.00 g L–1 WSA for 180 min

113

to determine the effects of initial pH on heavy metals removal. The initial pH of the

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mixture was adjusted with dilute HNO3 or NaOH. The mixture was agitated at room

115

temperature (25 ± 2 °C).

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The effect of temperature on heavy metals removal was observed at 15, 25, 35, 6

–1

117

45, and 55 °C for 50.00 g L

with an initial pH of 4.0.

118

2.3. FTIR analysis for plant materials

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In order to identify the participant functional groups of water–soluble plant

120

extracts obtained from HA, FJ, and PS during the sludge washing process, the original

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plant powder and residual plant powder extracted by distilled water were analysed

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using a Fourier transform infrared spectroscopy (FTIR) spectrophotometer (Spectrum

123

Two; PerkinElmer Inc., Waltham, Massachusetts, USA). The materials were ground

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with KBr sufficiently in an agate mortar at a ratio of 1:100 and pressed into a disk under

125

high pressure (Feng et al., 2018). The spectra were recorded from 450 to 4000 cm–1 at a

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resolution of 4 cm–1. The samples of residual plant powder were collected after

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washing (50.00 g L−1 WSA, 180 min of reaction at 1:20 w/v, 25 °C and pH 4.00).

128

2.4. Sludge chemical analysis

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In this study, the chemical properties of the original and washed sludge (50.00 g

130

L−1 WSA, 180 min of reaction at 1:20 w/v, 25 °C and pH 4.00) were analysed. Sludge

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organic carbon (OC) concentration was measured via potassium dichromate oxidation

132

(Nelson et al., 1996), and total nitrogen (TN) was determined through the Kjeldahl

133

method (Bremner et al., 1996). Total phosphorus (TP) and total potassium (TK)

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concentrations were detected using the molybdenum antimony colorimetry method

135

and by flame photometry after calcination and extraction by NaOH, respectively

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(Sparks et al., 1996). Alkali–hydrolysable nitrogen (AN) available potassium (AK),

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and available phosphorus (AP) were determined through NaOH hydrolysis (Cornfield., 7

138

1960), ammonium acetate extraction and subsequent flame photometer analysis (Tan et

139

al., 1995), and sodium bicarbonate extraction and spectrophotometer analysis (Li et al.,

140

2019b), respectively.

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2.5. Fraction distribution of heavy metals in sludge

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The fractions of Cd, Cu, Pb, and Ni were performed using sequential extraction

143

based on Tessier et al. (1979). The metal fractions include exchangeable, carbonate

144

bound, iron and manganese oxide bound (Fe–Mn oxide bound), organic matters bound,

145

and residual fractions.

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2.6. Quality control and statistical analysis

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All chemical reagents used were analytically pure. A sludge sample (RTC–

148

CRM031) with certified concentrations of Cd, Cu, Pb, and Ni was used as a reference.

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Each treatment was performed in triplicate and reagent blanks were also used to ensure

150

the accuracy and precision of the analysis. The total metal recovery rates ranged from

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86.1% to 109.3% (Cd, Cu, Pb, and Ni). All data statistical analyses were performed in

152

SPSS version 20.0 (SPSS Inc., USA). One–way analysis of variance (ANOVA) was

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tested to compare whether the metal removal under different experimental conditions

154

was significantly different. Statistical significance (p < 0.05) was determined by

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Fisher’s least significant difference test.

8

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3. Results and discussion

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3.1. Removal of heavy metals with WSA

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3.1.1. Effect of WSA concentration

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The concentrations of WSA significantly affect heavy metals removal (Zhang et

160

al., 2019). As shown in Fig. 1, heavy metals removal considerably increased with

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concentrations up to 65.00 or 80.00 g L–1 (p < 0.05). The concentration of plant WSA

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determines the amount of functional groups in the reaction, and a higher concentration

163

could supply more complexing sites to heavy metals (Zhang et al., 2019). However,

164

removal efficiencies generally reached a plateau at concentrations > 80.00 g L–1,

165

which is attributed to the low concentration of exchangeable and carbonate bound

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fractions of Cd, Cu, Pb, and Ni in sludge (Ren et al., 2015).

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Among the three materials, the HA derived WSA exhibited the highest

168

efficiencies of heavy metals removal, reaching 75.81% for Cu, 25.44% for Ni, and

169

63.42% for Pb at the concentration of 100.00 g L–1. Nevertheless, the FJ derived WSA

170

(100 g L–1) provided the highest removal efficiency of Cd (71.36%). In contrast, the

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metal removal efficiencies in the control experiment were less than 5%. This

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phenomenon may related to available functional groups in plant WSA such as carboxyl,

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amino, and amide groups, which can exchange hydrogen ions for metal cations or

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increase the electronic donating ability, thus promoting heavy metals removal from

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sludge (Sahmoune, 2018; Chen et al., 2019).

9

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3.1.2. Effect of pH

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The pH of WSA could affect the adsorption–desorption behaviour of heavy metals

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and the ionisation degree of functional groups in the extracts, and result in the change

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of the removal efficiency of heavy metals in sludge (Pérez–Esteban et al., 2013; Feng et

180

al., 2018). In this study, Cd, Cu, Pb, and Ni removal efficiencies in sludge were highly

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pH–dependent (Fig. 2). Regardless of the types of plant materials, the maximum

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metal removal of Cd (72.04%), Pb (47.80%), Cu (56.41%) and Ni (26.46%) were

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observed at pH 3.00, after which it declined. At a low pH, the WSAs could reduce the

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negative surface charge of the sludge particles and organic matter, and facilitate the

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dissolution of Fe–Mn oxides and the formation of soluble metal–organic chelates,

186

resulting in the removal of associated metals (Pérez–Esteban et al., 2013; Feng et al.,

187

2018).

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3.1.3. Effect of washing time

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In addition to the pH of the washing solution, washing time also influences the

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adsorption–desorption behaviour of heavy metals in sludge (Zhang et al., 2019). As

191

shown in Fig. 3, the removal efficiencies of heavy metals generally increased with

192

washing time up to 60 min, which can be attributed to the extraction of more heavy

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metals from sludge. Moreover, electrostatic repulsion between the metal cations on the

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adsorbent prevented the adsorption of subsequent metal cations (Zou et al., 2009; Chen

195

et al., 2019). The kinetic models (pseudo–first order, pseudo–second order and

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Elovich) were fitted at a range of 5–120 min to understand possible adsorption 10

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mechanism (Bhatnagar et al., 2010; Al–Qahtani, 2016). As shown in Table S1, the

198

pseudo–second order has a higher correlation coefficient (R2), which means that

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chemisorptive interactions are dominant in the experiments (Jang and Kan, 2019).

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The high R2 value of the Elovich model indicated that chemisorption was the

201

controlling step, similar to other studies using this model for the adsorption kinetics of

202

metal ions (Ali et al., 2016; Lasheen et al., 2012). However, the removal of some

203

heavy metals decrease

204

stability of soluble metal–organic polymers (Ho et al., 2012). In addition, the metal

205

removal may be affected by re–sorption and re–precipitation and decreased with

206

increasing washing time.

207

3.1.4. Effect of contact temperature

with washing time at 120 min, which may be attributed to the

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As shown in Fig. 4, the metal removal efficiencies increased significantly with the

209

increasing washing temperature, and reached the maximum level at 55 °C (58.19% for

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Cu, 74.19% for Cd, 45.97% for Pb, and 25.72% for Ni). The enhancement in removal

211

efficiencies with temperature may be attributed to the decrease in the thickness of the

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boundary layer surrounding the fine particles of sludge with temperature, decreasing

213

the mass transfer resistance of sludge particles in the boundary layer (Kołodyńska,

214

2011). In addition, increasing washing temperature, which could also enhance the

215

dissolution and diffusion rate of heavy metals, is effective for improving removal

216

efficiencies (Shaker and Hassan, 2014). Cd removal did not increase significantly with

217

washing temperature over 45 °C (p > 0.05). As washing temperature was increased, the 11

218

restricting factor of Cd removal changed from washing temperature to washing

219

concentration, and pH (Prakash et al., 2013). However, more energy need to be used to

220

get a high washing temperature, washing sludge at room temperature is more

221

substantial.

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3.2. FTIR analysis of plant materials

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FTIR analysis is essential for identifying some characteristic functional groups

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present in these sorbents (Abdolali et al., 2016). Several peaks in the spectra of the

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plant powder were observed, with different peaks corresponding to different

226

functional groups. As shown in Fig. 5, the strong broad band observed at 3425 cm–1

227

corresponds to stretching of the O–H bond of the hydroxyl groups from the alcohols,

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phenols and carboxylic acids (Jiménez–cedillo et al., 2013). The bands at 2922, 2847,

229

1057 and 596 cm–1 are assigned to stretches of C–H, C–H, C–O–C and S–O (Lammers

230

et al., 2009; Farooq et al., 2010; Siengchum et al., 2013). The absorption peaks at 1637,

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1443 and 1249 cm–1 could all be attributed to C=O stretching vibration of the carboxyl

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group (Stewart, 1996; Lammers et al., 2009; Barka et al., 2013; Calero et al., 2013).

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Comparing the peaks of different plant powders, some peaks of plant powder extracted

234

by distilled water changed in intensity, shifted in position, and increased or decreased

235

in number, indicating that some phytochemical components were extracted to WSA.

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Functional groups of the phytochemical components could combine and exchange

237

heavy metals ions in sludge colloids (Alikhani and Manceron, 2015). Consequently, the

238

hydroxyl, carboxyl, ether, and amide groups may be the main functional groups in the 12

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three plant materials, and they have been identified as potential sites responsible for

240

binding heavy metals ions to the biomass (Feng et al., 2018).

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3.3. Changes of heavy metals fractions in sludge

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The fractional distribution of the heavy metals has significant effects on heavy

243

metals removal from sludge (Wang et al., 2015). It can be noticed in Fig. 6 that metal

244

fraction distribution in the sludge changed depending on the washing process. Before

245

sludge washing, the Fe–Mn oxide bound fraction was the main fraction of Cd, Cu, Pb,

246

and Ni (62.32, 48.34, 38.13 and 46.93%). However, the ratio of heavy metals in

247

exchangeable and carbonate bound fractions is related to solubility and mobility of

248

heavy metals (Ren et al., 2015; Wang et al., 2018b). The ratios of Cd, Cu, and Pb in

249

exchangeable and carbonate bound fractions were higher than that of Ni, which may

250

result in relatively higher removal efficiencies of Cd, Cu and Pb than Ni ( Guo et al.,

251

2018).

252

After washing, the exchangeable, carbonate bound, and Fe–Mn oxides bounds

253

fractions of heavy metals significantly declined (Fig. 6). Nevertheless, the content of

254

Cd in the exchangeable fraction remained high. We speculated that the newly formed

255

metal–ligand complex might have been re–adsorbed by the sludge surface, where the

256

ligand formed a bridge between the sludge surface and the metal cations (Chen et al.,

257

2016). The fraction distribution of heavy metals determines ecological risk. After

258

washing with the three WSAs, the potential ecological risk of sludge from Cd, Cu, Pb,

259

and Ni was appreciably reduced (Suanon et al., 2016; Asgari Lajayer et al., 2019). 13

260

3.4. Changes of chemical properties in sludge

261

Decreasing nutrient loss is essential for achieving the reuse of sludge. In this

262

regard, the washing technology may change the chemical properties (Ren et al., 2015;

263

Wang et al., 2015). Compared with the untreated sludge, significant increases of OC,

264

AN, AP, and AK in sludge were observed after washing (Table 1, p < 0.05). The

265

increase of organic matter was also observed in previous studies using citric acid to

266

treat sludge (Ren et al., 2015; Wang et al., 2015). This enhancement may be related to

267

these washing solution residues with rich organic carbon and nutrients (Feng et al,

268

2018).

269

Comparatively, more efficient improvement was observed for AP and AK after

270

washing with the three WSAs (Table 1). This improvement might be related to the

271

transformation and dissolving of unavailable P and K to the AP andAK under acidic

272

washing conditions (Liu and Lin, 2013; Ren et al., 2015). N, N–bis (carboxymethyl)

273

glutamic acid, and citric acid have been reported to decrease TN, TP, and TK during

274

the washing process (Ren et al., 2015; Wang et al., 2015). These results revealed that

275

three WSAs can effectively moderate the effects of washing on sludge chemical

276

properties. In China, the mean TN, TP, and TK contents of soil are 1.0–2.0, 0.44–0.85

277

and about 16 g kg–1, respectively (Wang et al., 2015). Considering this, the treated

278

sludge has potential for application to soil amendment and manure.

279

4. Conclusions

280

Three WSAs derived from HA, FJ, and PS, effectively removed Cd, Pb, Ni, and 14

281

Cu from sludge. The concentrations, pH, washing time, and washing temperature of

282

the WSAs were closely related to heavy metals removal efficiencies, and the washing

283

process of WSA may be dominated by chemisorptive interactions. The optimal Cd,

284

Cu, Pb, and Ni removal efficiencies were 56.99, 75.81, 63.42, and 27.52%

285

respectively for HA, 74.19, 26.99, 42.02, and 21.53% respectively for FJ, and 23.88,

286

26.09, 48.55, and 26.46% respectively for PS. After washing, the WSAs mainly

287

removed easily extractable fractions of the metals, such as the exchangeable and

288

carbonate–bond fractions. In addition, the potential ecological risk of sludge was

289

reduced and the organic carbon and nutrient in sludge was supplemented. Therefore,

290

the WSAs derived from HA, FJ, and PS proved to be novel washing agents for the

291

removal of heavy metals from sludge, and they can be beneficial to the further

292

application of sludge to land. The impact of agricultural use of sludge washed by

293

WSAs on soil fertility, microorganisms and plant productivity are also worth

294

exploring.

295

5. Acknowledgments

296

The authors are grateful for the support of Key Research and Development

297

Projects of Sichuan Province, China, Grant No. 2019YFN0020, Environmental

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Protection Science and Technology Projects of Sichuan Province, China, Grant No.

299

2018HB30.

300

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Table 1. Sludge chemical properties before and after washing. OC

(g kg-1)

TN (g

kg-1)

-1

TP (g kg

)

TK (g

kg-1)

AN (g

kg-1)

-1

AP (g kg

)

AK (g

kg-1)

Original sludge

245.01 ± 4.71d

18.45 ± 1.07a

15.02 ± 0.35ab

7.23 ± 0.26a

2.35 ± 0.18b

4.13 ± 0.34b

1.03 ± 0.13c

HA

258.63 ± 9.16c

17.89 ± 0.48a

14.59 ± 0.66b

6.50 ± 0.58b

2.45 ± 0.24b

4.74 ± 0.67a

1.18 ± 0.19bc

FJ

284.54 ± 11.71b

18.23 ± 0.56a

14.32 ± 0.48b

7.01 ± 0.31a

2.70 ± 0.13a

4.51 ± 0.92ab

1.34 ± 0.11a

PS

307.72 ± 8.53a

18.35 ± 1.03a

15.12 ± 0.33a

6.50 ± 0.14b

2.17 ± 0.16c

4.41 ± 0.41ab

1.23 ± 0.17ab

HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera; OC, organic carbon; TN, total nitrogen; TP, total phosphorus; TK, total potassium; AN, alkali-hydrolyzable nitrogen; AP, available phosphorus; AK, available potassiu

Fig. 1 Effects of the concentrations on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Fig. 2 Effects of the pH on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Fig. 3 Effects of the washing time on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Fig. 4 Effects of the washing temperature on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Fig. 5 FTIR spectra of HA, FJ and PS before and after washing. Fig. 6 Comparative distribution of Cd, Cu, Pb and Ni in the sludge before and after washing with three plant water-soluble extracts.

Fig. 1 Effects of the concentrations on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Note: HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. Error bars represent the standard deviations (n = 3).

Fig. 2 Effects of the pH on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Note: HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. Error bars represent the standard deviations (n = 3).

Fig. 3 Effects of the washing time on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Note: HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. Error bars represent the standard deviations (n = 3).

Fig. 4 Effects of the washing temperature on the removals of Cd, Cu, Pb, and Ni with plant water-soluble extracts from sludge. Note: HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. Error bars represent the standard deviations (n = 3).

Fig. 5 FTIR spectra of HA, FJ and PS before and after washing. Note: HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. W-FJ, FJ powder extracted by distilled water. W-HA, HA powder extracted by distilled water. W-PS, PS powder extracted by distilled water

Fig. 6 Comparative distribution of Cd, Cu, Pb and Ni in the sludge before and after washing with three plant water-soluble extracts. Note: Before, original sludge; HA, Hovenia acerba; FJ, Fatsia japonica; PS, Pterocarya stenoptera. EXC, exchangeable fraction, CAR, carbonates bound fraction, FeMn, Fe-Mn oxides bound fraction, ORG, organic matter bound fraction, RES, residual fraction

Highlights: •Heavy-metal removal from sludge using plant washing agents was evaluated. •The agent from Hovenia acerba effectively removed heavy metals from sludge. •The washing agents tended to moderate changes in the chemical properties of sludge. •The sludge is suitable as manure and can be used for soil amendment after washing.

The author Xiaoxun Xu, Yan Yang and Shirong Zhang did the experimental work and wrote the manuscript. Guiyin Wang, Zhang Cheng, Ting Li and Zhanbiao Yang contributed to the data analysis and prepared Figures and Tables. Junren Xian Yuanxiang Yang, and Wei Zhou contributed to experimental design and the experiment operation. All authors reviewed the manuscript and contributed to the scientific discussion.

Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: