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Article

Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks

by
Jiajia Liu
1,*,
Fei Wang
2 and
Wangqi Xu
2
1
Environmental Engineering College, Nanjing Polytechnic Institute, Nanjing 210044, China
2
Institute of Geotechnical Engineering, School of Transportation, Southeast University, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Water 2023, 15(21), 3789; https://doi.org/10.3390/w15213789
Submission received: 26 September 2023 / Revised: 26 October 2023 / Accepted: 26 October 2023 / Published: 29 October 2023
(This article belongs to the Special Issue Application of Smart Technologies in Integrated Water Quality Modeling)
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Abstract

:
Human activities such as the discharge of urban sewage, garbage, and industrial waste have seriously affected the quality of groundwater sources for human consumption. The potential for using biochar as a reactive medium in a permeable reactive barrier (PRB) was explored for Zn-contaminated groundwater treatment in this study. Four different types of biochar produced from wood, coconut shell, rice straw, and fruit shell were used. The production temperature of these biochars were 600 °C, 550 °C, 500 °C, and 500 °C, respectively. The samples were coded with the initials of the biochar source and the production temperature as WD600, CS550, RS500, and FS500. The results of various batch adsorption studies show that equilibrium solution pH has a great effect on the maximum adsorption capacity in the pH range of 2–7. The adsorption of Zn on biochars follows the Freundlich model and fits well with the pseudo-second-order model. The fixed-bed column test data were well fitted to the Dose–Response model. The adsorption capacities of WD600, CS550, RS500, and FS500 were 24.91, 15.87, 9.25, and 46.71 mg/g, respectively. The removal rate of FS500 can reach a maximum of 98.87%. FS500 is considered to be a potential reaction medium for treating Zn-contaminated groundwater in a PRB system. This work provides a new option for converting biomass waste into an adsorbent for zinc in wastewater. The results of this study are expected to provide a solid theoretical basis for the further application of biochar in groundwater pollution remediation.

1. Introduction

As a precious water resource, groundwater not only provides a significant amount of drinking water for human beings but also supports agricultural planting and industrial production. However, the discharge of urban sewage, garbage, and industrial waste, as well as runoff from the intensive use of fertilizer and pesticides, have resulted in serious environmental problems. China’s ecological environment status bulletin (MEP, 2017) reported that the percentages of monitoring wells with poor water quality and extremely poor water quality were 45.4% and 14.7%, respectively [1]. With the release of the Law on the Prevention and Control of Soil Pollution of the People’s Republic of China (NPC, 2018) and the Water Pollution Control Action Plan (The State Council, 2015), there is a strong drive by the Chinese government for each department to integrate scientific and technological resources, to speed up the research of common key technologies, such as soil and groundwater pollution remediation and pollution control, treatment, and remediation through relevant, well-funded national science and technology projects and to develop advanced equipment and efficient and low-cost functional materials [2,3].
In recent years, the groundwater in China has been polluted by heavy metals to varying degrees. The zinc content of groundwater in some areas has seriously exceeded the national standard, which has posed a serious threat to the health of local residents. However, there are few studies on the treatment methods of groundwater with excess zinc contents. It is meaningful to study the treatment of zinc-contaminated groundwater since, in some areas, only the groundwater can be used for drinking [4]. The World Health Organization (WHO) and the United States Environmental Protection Agency (USEPA) set the permissible limit for zinc(II) in drinking water as 5 mg/L. The Department of Environment (DOE) in Malaysia set the permissible limit for zinc(II) in drinking water as 3 mg/L. In China, the limit is 1 mg/L according to the GB/T 14848-2017 Groundwater Quality Standard [5].
There are many methods to remove zinc in water. Chemical methods include coagulation, precipitation, sulfide, and precipitation. However, the disadvantages are also obvious, like cost, difficulties of large-scale application, and probability of secondary pollution [6,7]. Physical methods include the use of membranes, ion exchange, and adsorption (by activated carbon, minerals, or biochar). All of these methods have good prospects for removing heavy metals in groundwater, but relevant studies are limited [8,9]. The low-cost preparation and regeneration technology of activated carbon still needs continuous research and development and has better application prospects.
The adsorption properties of biochar for heavy metals are mainly affected by biomass type, pyrolysis temperature, solution pH, and heavy metal type and concentration. Chen studied the adsorption properties of Zn(II) in solution by biochar using hardwood (HW450) pyrolysis at 450 °C and corn stalk pyrolysis at 600 °C (CS600) [10]. It was found that the removal rate increased with the pH and reached a maximum value at 6.5. The adsorption effect of CS600 on Zn(II) in the solution was significantly better than that of HW450. Li used water hyacinth prepared at 200–500 °C to study its adsorption of zinc in aqueous solution [11]. The results showed that biochar prepared at 500 °C had the strongest adsorption capacity, and its adsorption mechanism was mainly the complexation between functional groups in biochar and metal ions. The adsorption process of zinc by biochar can be described by a quasi-second-order model (R2 > 0.95). The adsorption experiment results showed that wheat straw carbon prepared at low temperature has a strong adsorption capacity of Zn(II) under acidic conditions. The researchers have carried out a lot of research work on biomass types, preparation conditions, and the mechanism of biochar adsorption of heavy metals [12]. Due to the wide variety of biomass, the preparation conditions of biochar also have a great influence on its physicochemical properties, heavy metal adsorption mechanism, and kinetic process. Therefore, it is necessary to further study the physicochemical properties of biochar and its adsorption properties and kinetics of heavy metals.
The permeable reactive barrier (PRB) is a promising sustainable remediation technique invented in the early 1990s that has drawn great attention in recent years [13,14,15,16]. The use of sustainable reactive media is one of the key components of PRBs, the type of which depends on the target contaminants, their concentration, the mechanisms needed for their removal, and the hydro-geological site conditions [13,17,18,19]. Biochar, which has been studied extensively worldwide, is a sustainable sorbent for the heavy-metal remediation of water and soil [20]. The introduction of biochar enabled the use of inexpensive filling materials to enhance the effectiveness of PRBs. The application of biochar in PRB requires a good understanding of many factors, including the adsorption characteristics of contaminants onto biochar, the reaction speed of various contaminants with biochar, and the physical and chemical reactions involved in the complex wall system [21,22]. However, research on the application of biochar as the reactive material in PRBs is limited. Kumar et al. assessed the U(VI) removal rate of switchgrass biochar from groundwater. They claimed that the sorption capacity of switchgrass biochar was approximately 2.12 mg of U g−1 of biochar [23]. The pH of the system is a key factor in the adsorption process. Their results indicate that biochar could be used as an effective reactive barrier medium for U(VI)-contaminated groundwater. Gillham and O’Hannesin used zero-valent iron to degrade halogenated aliphatics and found that the adsorption rate constant is linked to the surface area-to-volume ratio, whereas the degradation rates are independent of velocity [24]. They also proposed in situ and aboveground applications for the remediation of contaminated groundwater. Beiyun et al. studied risk mitigation by waste-based (including wood-derived biochar) PRBs for groundwater pollution control at e-waste recycling sites [25]. The results show that waste-based PRBs are a technically feasible and economical way to mitigate human health risks through the proper selection of adsorbents. However, these limited studies did not focus on the most commonly used biochars in the Chinese market, and there is a lack of research on the related adsorption and desorption characteristics.
The properties of biochar, such as specific surface area, pH, and surface chemistry, are highly dependent on the feedstock of biochar and the pyrolysis conditions [26,27]. Hence, the effectiveness of different biochars in treating polluted groundwater is varied [28]. Shen et al. investigated the sorption of lead by biochar produced from British broadleaf hardwood; the results show that the biochar particle size and the initial solution pH have a significant impact on lead sorption [20]. Shen et al. used biochars produced from wheat straw pellets and rice husk at 550 and 700 °C to study the adsorption characteristics and mechanisms of Ni2+ on these biochars [29]. The results show that the adsorption capacities of Ni2+ for the wheat straw pellet biochar performed better than the rice husk biochar, and a higher production temperature at 700 °C contributed a better sorption compared to that at 550 °C. In addition, although the study of Tan et al. found that rice straw biochar was the most effective in decreasing Cd enrichment in rice plants compared to bran and husk biochars, limited studies have investigated the adsorption characteristics or mechanisms of Zn2+ on biochars [30].
Accordingly, this study compares the adsorption characteristics of zinc from groundwater onto biochars produced from wood at 600 °C, coconut shell at 550 °C, rice straw at 500 °C, and fruit shell at 500 °C and explores the potential application of biochar in the PRB system for groundwater remediation. The detailed objectives were (1) investigating the adsorption characteristics of Zn2+ on these four biochars; (2) estimating the influence of groundwater conditions such as the initial groundwater pH and the initial concentration of Zn2+ on the adsorption capacity of biochars; and (3) analyzing the adsorption kinetics of Zn2+ on these four kinds of biochars.

2. Material and Methods

2.1. Biochar

Biochar powders derived from wood, coconut shell, rice straw, and fruit shell were purchased from the Liyang Desheng activated carbon plant. The production temperatures of these biochars were 600 °C, 550 °C, 500 °C, and 500 °C, respectively. The samples were coded with the initials of the biochar source and the production temperature as WD600, CS550, RS500, and FS500. The physicochemical properties of the biochars are shown in Table 1. The properties, such as surface area, particle size, ferric salts, mass density, and moisture content, were obtained from the supplier. The particle sizes of WD600, CS550, RS500, and FS500 are >0.075 mm, >0.075 mm, 0.075–0.15 mm, and 0.09–0.18 mm, respectively. The pH values of the biochars were determined in the laboratory according to the GBT 12496.7 [31]. The cation exchange capacity (CEC) of biochar was tested through a compulsive exchange method, which can be found in Gillman and Sumpter [32]. Zinc nitrate hexahydrate, sodium nitrate, nitric acid, sodium hydroxide, and barium chloride dihydrate were obtained from the Chengdu Kelon chemical reagent plant. The chemicals of Zn(NO3)2·6H2O, NaNO3, HNO3, NaOH, and BaCl2·2H2O used in this study were AR-grade.

2.2. Batch Adsorption Studies

2.2.1. Kinetic Study

Batch kinetic experiments were performed at pH 7, and an initial Zn2+ concentration of 50 mg/L was used to estimate the equilibrium time for the adsorption reaction. A solution of 50 mg/L Zn2+ in 0.01 M NaNO3 was prepared, after which 0.1 g of biochar (WD600, CS550, RS500, or FS500) was added to 20 mL of the Zn(NO3)2 solution. The mixture was shaken at 200 rpm and 25 °C. The reaction time was set at 5 min, 10 min, 20 min, 30 min, 1 h, 2 h, 3 h, 6 h, 12 h, or 24 h. At the end of the experiment, aqueous samples were filtered through 0.22 μm filters, acidified, and analyzed by a Thermo Scientific spectrometer (ICE3300).

2.2.2. Equilibrium Study

The initial concentrations of the Zn2+ solutions used in these experiments were varied at 10, 30, 60, 80, 100, 200, and 300 mg/L, and the experiment was conducted in a 0.1 M NaNO3 solution. The pH of these Zn2+ solutions was adjusted to 5. After this preparation, 0.1 g of biochar (WD600, CS550, RS500, or FS500) was then added to 20 mL of the Zn(NO3)2 solution. The mixtures were shaken for about 24 h at 25 °C. At the end of the specified time, the aqueous samples were filtered, acidified, and analyzed as described above.

2.2.3. Effect of pH

The pH-related adsorption study was observed by studying the Zn2+ adsorption in a solution of 50 mg/L Zn2+ in 0.01 M NaNO3 over a pH range of 2–7. The pH of each initial solution was adjusted to 2, 3, 4, 5, 6, and 7 by solutions of 0.01–1 M NaOH or HNO3. Then, 0.1 g of biochar (WD600, CS550, RS500, or FS500) was added to 20 mL of 50 mg/L Zn(NO3)2 solutions in 0.1 M NaNO3. The mixtures were placed in a constant-temperature incubator shaker (25 °C) and were shaken at 200 rpm for 24 h to reach equilibrium. After filtration of the samples through a 0.22 μm filter, the equilibrium pH of each solution was measured by a pH meter. The concentration remaining in the solution was then measured by atomic absorption spectrometry after dilution and acidification. The concentration of Zn2+ was measured by a Thermo Scientific spectrometer (ICE3300). All tests in this study were performed in triplicate. The procedural blanks were run in parallel to eliminate possible adsorption of Zn2+ on tubes and filters.

2.3. Fixed-Bed Column Study

To simulate the application of biochars in removing Zn2+ from aqueous solutions, fixed-bed column experiments were conducted in an acrylic cylinder with a height of 200 mm and an internal diameter of 26 mm. The biochars WD600 and RS500 were mixed uniformly with sand and packed in the column to yield the desired 100 mm bed length. The ratios of biochars to the sand applied in the column were 1:9 and 2:8, respectively. The Zn(NO3)2 solution, with an initial concentration of 50 mg/L, was pumped downwards at a constant flow rate of 1 mL/min through a peristaltic pump (BT 100S). The liquid was collected from the bottom outlet every 10 min and then filtered with 0.45 μm filters before the measurement of Zn2+ concentration.

3. Results and Discussion

3.1. Kinetics

Because the adsorption of Zn2+ by RS500 and FS500 was rapid, the initial phase, in which the equilibrium constant Qe usually increases with time, was not observed. Hence, the kinetic data were not considered to be suitable for further analysis using the kinetic model. Therefore, the results of only the WD600 and CS550 kinetics studies were fitted in this paper using the pseudo-first-order model and pseudo-second-order model to study their adsorption mechanism (Figure 1 and Figure 2). Correlation coefficient (R2) and Akaike information criterion (AIC) values were used to find a better-fitting model. The AIC is based on the concept of entropy and can evaluate the complexity of the estimated model and the goodness of the fit. A model with a higher correlation coefficient and a lower AIC value is preferred. The pseudo-second-order equation fitted the data better, with higher regression coefficients of WD600 and CS500 at 0.83 and 0.73 and lower AIC values than the counterparts obtained from the pseudo-first-order model (Table 2). The calculated qe of WD600 and CS500 were 8.19 mg/g and 6.44 mg/g, whereas the experimental qe were 9.656 mg/g and 6.885 mg/g, respectively. The well-fitted data indicate that the dominant adsorption mechanism of Zn on WD600 and CS500 is chemisorption [20,33] All these data indicate that the pseudo-second-order model is preferred for the adsorption kinetics of Zn on biochars; this agrees well with the studies of Shen et al. [20,29].
The adsorption of Zn2+ onto FS500, CS550, and RS500 reached equilibrium within 5 min. However, it took more than 30 min for WD600 to reach equilibrium. Although the adsorption amount was accumulated over time, the adsorption speed was reduced over the same time period. This may be due to the distribution of the initial abundance of unsaturated positions on the surface of biochars. The highest adsorption capacities of WD600, CS550, RS500, and FS500 tested in this kinetic study were 9.656 mg/g, 6.885 mg/g, 2.615 mg/g, and 15.390 mg/g, respectively. The equilibrium times of RS500 and FS500 were consistent with the results of Shen et al. [19], in which an equilibrium was reached in 5 min using biochars derived from mixed softwood and Miscanthus straw to adsorb Ni. Smaller particle sizes of biochar were found to aid the mass transport of adsorbate inside the adsorbent [34].

3.2. Adsorption Isotherms

Figure 3 shows the influence of initial Zn2+ concentrations (10–300 mg/L) on the adsorption amount of 0.1 g biochar. The adsorption amount of each biochar clearly increases with the increase in initial Zn2+ concentrations from 10 mg/L to 200 mg/L. The Zn2+ adsorption amount of biochar in a 300 mg/L initial Zn2+ solution was found to be lower than that of a 200 mg/L initial Zn2+ solution. This decrease in Zn adsorption follows the decrease in net negative surface charge density, although this decrease could also be partially due to a limited number of adsorption sites [35]. Indeed, at low Zn levels, the biochars were unsaturated with respect to Zn. However, with the increase in Zn2+ concentration, competition between cations for adsorption sites and electrostatic repulsion have a marked effect on the adsorption of Zn.
Among the four biochars, the adsorption and removal of Zn in FS500 was 2–5 times higher under various initial Zn2+ concentrations than in the other three biochars. The highest Zn adsorption by FS500 was 46.71 mg/g. Meanwhile, the highest Zn adsorption amount by RS500 was only 9.25 mg/g. At adsorption equilibrium, the order of the amount of Zn adsorption of the four biochars was FS500 > WD600 > CS550 > RS500. This agrees well with the order of the percentage of Zn removal of biochars under a pH range of 2–7.
Based on the equilibrium adsorption of Zn on biochars, the experimental data were fitted using isotherm models, including the Langmuir, Freundlich, Sips, and BET models. Except for the Freundlich model, the other models did not match the experimental data, so they were not provided in Figure 3. For the Freundlich model, KF is the adsorption capacity of the adsorbent (mg/g); 1/n ranges between 0 and 1 and is a measure of the adsorption intensity or surface heterogeneity, and the surface of the adsorbent is more heterogeneous if its value is closer to zero. As can be found from Table 3, R2 values of WD600, CS550, RS500, and FS500 for the Freundlich model were 0.868, 0.642, 0.719, and 0.516, respectively. The R2 values of FS500 were extremely low. In the Freundlich model, as KF is the adsorption capacity of the adsorbent, the larger the KF value, the stronger the adsorption capacity of that biochar. The results show that the order of KF of the four biochars is FS500 > WD600 > CS550 > RS500. The 1/n values of WD600, CS550, RS500, and FS500 were 0.56, 0.50, 1.15, and 0.17, respectively, which indicates that the surface of FS500 is more heterogeneous compared to the other biochars used in this study.

3.3. Influence of Initial Solution pH on Zn2+ Adsorption

The significant effect of the initial and equilibrium solution pH’s on the sorption of Zn2+ on biochars is shown in Figure 4, which shows that Zn2+ will precipitate to form Zn(OH)2 when the solution pH is at 7.94 [36]. When the solution pH is higher than 8, zinc complex compounds are produced [36,37,38]. At pH 9–12, Zn(OH)2 was considered to be the controlling phase [36]. Hence, a pH range of 2–7 was selected in this study.
As can be seen in Table 1, the pH values of WD600, CS550, RS500, and FS500 are 8.98, 6.89, 3.49, and 10.84, respectively. The high pH of FS500 at 10.84 did not significantly increase the equilibrium solution pH of 3.07 when the initial solution pH was 2 (Figure 4). However, when the initial solution pH was 3, the equilibrium solution pH values of WD600, CS550, and FS500 were increased significantly to 6.87, 5.65, and 10.28, respectively. In other words, despite the low pH of RS500 at 3.49, the equilibrium solution pH values of WD600, CS550, and FS500 were increased in various degrees with the addition of biochars. A similar increase in the equilibrium solution pH after adding biochars was found at initial solution pHs of 4–7. The equilibrium solution pH was found to be the highest (7.71%, 6.69%, 4.32%, and 10.7% for WD600, CS550, RS500, and FS500, respectively) when the initial pH was 7. However, no matter what type of biochar (except RS500) was used in this study, an insignificant increase in equilibrium solution pH values at initial pHs of 3–7 was noticed in Figure 4. This resistance to pH change may be because of the buffering capacity of biochar. Because the pH of RS500 is 3.49, the equilibrium solution pH was raised to 3.2 when the initial pH was 3, and the equilibrium solution pH was lowered to 4.32 when the initial pH was 7.
The adsorbent surface charge and the dissociation or protonation of organic weak electrolytes are determined by their equilibrium solution pH values [36,39]. At pH 2, the surface of the biochars was dominated by positively charged points. As a result of this electrostatic repulsion between positively charged ions on the biochar surface and Zn2+ in solution, the Zn2+ removal percentages using the four biochars were the lowest at the lowest pH (9.34%, 7.23%, 7.42%, and 15.65% for WD600, CS550, RS500, and FS500, respectively). This observation agrees well with the proposal of Wang and Al-Tabbaa that due to the physical adsorption of Zn on particle surfaces or its chemical fixation as a Zn complex, an extensive portion of Zn is dissolved when the solution pH is 2. At pH 3, these values were increased to 24.33%, 17.09%, and 13.24% for WD600, CS550, and RS500, respectively [37]. The increase in the Zn2+ removal rate of FS500 was even more significant, from 15.64% to 98.87%. The Zn2+ removal percentages of FS500 remained nearly constant within initial pH values of 3–7 because of the buffing capacity of the biochar [19]. One reason for the slow growth of Zn2+ removal percentages at initial pH 2–7 for RS500 was likely due to electrostatic repulsion with Zn2+ under an acidic environment. The Zn2+ removal rates of WD600 and CS550 at initial pH 6 were decreased. This observation agrees well with the proposal of Feng [40]. The solution’s initial pH value significantly influenced the adsorption, and the optimum pH value for Zn(II) was 6.0. Each heavy metal ion has a limiting pH, and when the solution pH exceeds its limiting pH, the metal ion will exist in other forms and produce precipitation. Masoumeh et al. studied biochars from apple wood (WB) and rice straw (RB) and found that Zn adsorption increasing the initial pH of solutions from 4 to 6 increased the Zn adsorption in RB600, RB300, and WB600 [41]. These results indicate the high efficiency of FS500 in treating Zn-contaminated liquids when the pH is higher than 3 and the potential application of FS500 in PRB systems.

3.4. Column Test

Fixed-bed column studies were significant in simulating the practical application of adsorbents in treating contaminated water and in assessing their viability and feasibility. The Dose–Response model, the Thomas model, and the Yoon–Nelson model were applied to fit the experimental data and to predict breakthrough curves in Figure 5 and Figure 6. The mass of adsorbents was determined, and the column kinetic parameters obtained from the models are presented in Table 4, in which a, KTh, KYN are the constants of the corresponding models, q0 is the maximum concentration of solute in the solid phase, R2 is the correlation coefficient, and Tb is the breakthrough time (C/C0 = 0.5) predicted by the Yoon–Nelson model. Due to the higher values of R2, the Dose–Response model is better fitted to the data than the other models are.

4. Conclusions

In this study, the basic physical and chemical properties of biochars produced from wood, coconut shell, rice straw, and fruit shell were introduced, and the detailed adsorption characteristics of Zn on these four biochars were discussed in this study. The different types of materials led to the difference in biochar adsorption capacity, which affected the alkaline mineral content of biochar and the related pH and CEC values. The results of various batch adsorption studies showed that the equilibrium solution pH had a great effect on the maximum adsorption capacity in the pH range of 2–7. FS500, with a pH of 10.84, was considered to be the most efficient biochar in the adsorption of Zn in aqueous solution. At adsorption equilibrium, the order of Zn adsorption amount of the four biochars is FS500 > WD600 > CS550 > RS500. All these data indicated that the pseudo-second-order model is preferred for the adsorption kinetics of Zn on biochars. The fixed-bed column test data were well fitted with the Dose–Response model. The adsorption capacities of WD600, CS550, RS500, and FS500 were 24.91, 15.87, 9.25, and 46.71 mg/g, respectively. The adsorption of Zn onto FS500 and RS500 reached equilibrium within 5 min. However, it took longer for WD600 and CS550 to complete a 70% adsorption. FS500 has the potential to be applied in a PRB system for treating contaminated groundwater.
The adsorption capacity and mechanism of different biochars can provide scientific data for the application of biochars. The FT-IR spectra and SEM images of the biochars can find the functional groups and morphology of biochars. In order to further study the adsorption mechanism, the FT-IR spectra and SEM images of the biochars can be used in the later stage. It is recommended that biochar be produced from a variety of feedstocks in accordance with UKBRC’s standard procedures. Therefore, relevant comparisons can be made to identify biochar suitable for contaminated groundwater and to explore its mechanism of adsorption of heavy metals.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15213789/s1, Figure S1. Speciation diagram and effect of initial solution pH on the Zn adsorption; Figure S2. The fitting of pseudo-first-order model for Zn adsorption onto CS500.

Author Contributions

Formal analysis, W.X.; funding acquisition, J.L.; writing—original draft, W.X. and J.L.; writing—review, F.W.; editing the English text of a draft, Alicia Glatfelter, from Liwen Bianji (Edanz) (http://www.liwenbianji.cn, accessed on 1 February 2023). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Basic Science (Natural Science) Project of Higher Education Institutions of Jiangsu Province (21KJB610012), Talent Introduction Program of Nanjing Polytechnic Institute (NJPI-2021-03), and the National Natural Science Foundation of China (51978157).

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article [and/or its Supplementary Materials].

Conflicts of Interest

The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

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Water 15 03789 g001
Figure 1. The fitting of pseudo-first-order and pseudo-second-order models for Zn adsorption onto WD600.
Figure 1. The fitting of pseudo-first-order and pseudo-second-order models for Zn adsorption onto WD600.
Water 15 03789 g001
Water 15 03789 g002
Figure 2. The fitting of pseudo-first-order and pseudo-second-order models for Zn adsorption onto CS500.
Figure 2. The fitting of pseudo-first-order and pseudo-second-order models for Zn adsorption onto CS500.
Water 15 03789 g002
Water 15 03789 g003
Figure 3. Isotherm plots for Zn2+ adsorption onto biochars.
Figure 3. Isotherm plots for Zn2+ adsorption onto biochars.
Water 15 03789 g003
Water 15 03789 g004
Figure 4. The influence of initial solution pH on the Zn2+ removal percentage of (a) WD600, (b) CS550, (c) RS500, and (d) FS500.
Figure 4. The influence of initial solution pH on the Zn2+ removal percentage of (a) WD600, (b) CS550, (c) RS500, and (d) FS500.
Water 15 03789 g004
Water 15 03789 g005
Figure 5. Experimental data and mathematical model fitting of the adsorption of Zn2+ to WD600.
Figure 5. Experimental data and mathematical model fitting of the adsorption of Zn2+ to WD600.
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Water 15 03789 g006
Figure 6. Experimental data and mathematical model fitting of the adsorption of Zn2+ to RS500.
Figure 6. Experimental data and mathematical model fitting of the adsorption of Zn2+ to RS500.
Water 15 03789 g006
Table 1. The physicochemical properties of the biochars.
Table 1. The physicochemical properties of the biochars.
WD600CS550RS500FS500
Surface area (m2/g)>700>900>300>500
pH8.986.893.4910.84
CEC (cmol/kg)6.865.544.307.31
Particle size (mm)>0.075>0.0750.075–0.150.09–0.18
Ferric salts (%)<0.1<0.05<0.1<0.1
Mass density (mg/L)<450<450<450<500
Moisture content (%)<10<10<10<10
Table 2. Adsorption kinetics fitting results of WD600 and CS550.
Table 2. Adsorption kinetics fitting results of WD600 and CS550.
BiocharPseudo-First-Order ModelPseudo-Second-Order Model
k1
(1/h)		qe
(mg/g)		R2AICK2
(g/mg/h)		qe
(mg/g)		R2AIC
WD6004.94 ± 1.247.71 ± 0.410.668.010.89 ± 0.248.19 ± 0.330.830.61
CS55010.30 ± 2.196.20 ± 0.220.60−2.812.92 ± 0.866.44 ± 0.210.73−6.63
Table 3. Precipitation isothermal parameters of Zn2+ adsorption in WD600, CS550, RS500, and FS500.
Table 3. Precipitation isothermal parameters of Zn2+ adsorption in WD600, CS550, RS500, and FS500.
Freundlich Isotherm Mode
KF
(L/mg)		1/nR2
WD6001.32 ± 0.760.56 ± 0.120.868
CS5501.11 ± 0.960.50 ± 0.180.642
RS5000.01 ± 0.031.15 ± 0.380.719
FS50021.5 ± 5.070.17 ± 0.060.516
Table 4. Mathematical model parameters for the adsorption of Zn2+ to the biochars.
Table 4. Mathematical model parameters for the adsorption of Zn2+ to the biochars.
10% WD60020% WD60010% RS50020% RS500
Mass of Adsorbents (g)2.134.363.807.22
ModelParameters
Dose–Responsea2.27 ± 0.221.14 ± 0.141.04 ± 0.141.42 ± 0.23
q0 (mg/g)13.42 ± 0.667.57 ± 0.594.56 ± 0.554.22 ± 0.42
R20.8730.7210.6750.638
ThomasKTh (mL−1 mg−1 min−1)0.07 ± 0.010.04 ± 0.0040.04 ± 0.0050.04 ± 0.006
q0 (mg/g)15.16 ± 0.849.35 ± 0.586.13 ± 0.885.21 ± 0.43
R20.8270.6810.5770.619
Yoon–NelsonKYN (min−1)0.003 ± 3.5 × 10−40.002 ± 2.1 × 10−40.002 ± 2.7 × 10−40.002 ± 3.2 × 10−4
Tb (min)645.9 ± 35.8814.9 ± 50.9466.3 ± 66.7752.9 ± 62.4
R20.8270.6810.5770.619
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Liu, J.; Wang, F.; Xu, W. Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks. Water 2023, 15, 3789. https://doi.org/10.3390/w15213789

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Liu J, Wang F, Xu W. Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks. Water. 2023; 15(21):3789. https://doi.org/10.3390/w15213789

Chicago/Turabian Style

Liu, Jiajia, Fei Wang, and Wangqi Xu. 2023. "Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks" Water 15, no. 21: 3789. https://doi.org/10.3390/w15213789

APA Style

Liu, J., Wang, F., & Xu, W. (2023). Characteristics of Zinc Adsorption onto Biochars Derived from Different Feedstocks. Water, 15(21), 3789. https://doi.org/10.3390/w15213789

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