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Biochar

pp 1–12 | Cite as

Biochar colloids and their use in contaminants removal

  • Salman SafariEmail author
  • Konstantin von Gunten
  • Md. Samrat Alam
  • Magdalena Hubmann
  • Tamzin A. Blewett
  • Ziyi Chi
  • Daniel S. Alessi
Original Article
  • 198 Downloads

Abstract

In this study, we report on the extraction, characterization, and potential applications of colloidal biochar derived from pyrolyzed wood—an untapped source of carbonaceous particles. A series of characterizations was performed on biochar colloids to unravel their colloidal properties and surface chemistry through which it was found that they have a net negative charge and are stable between pH 3 and 10. Moreover, our initial toxicity tests showed that biochar colloids themselves are not toxic and they can be used in remediation applications, which led us to investigate (1) their copper sorption, a model inorganic contaminant, in a scenario that biochar colloids are released into the environment and (2) their potential use in organic pollutants adsorption and degradation. Copper sorption studies showed that biochar colloids have a copper sorption capacity as high as 22 mg \(\hbox {g}^{-1}\) in sub-ppm copper solutions. This increased the acute 48 h lethal concentration (\(\hbox {LC}_{50}\)) of copper for Daphnia magna by 21 ppb, which is comparable to the previously reported effect by dissolved organic matter. Adsorption and degradation of methylene blue (MB), an often-used proxy for organic contaminants in water, were studied by coupling the biochar colloids to positively charged \(\hbox {TiO}_{2}\) nanoparticles and using it as a photocatalyst. The hybrid MB photodegradation efficiency was \(21\%\) higher than that of \(\hbox {TiO}_{2}\) nanoparticles alone. Enhancement of demethylation is proposed as the main degradation mechanism of MB, as confirmed by liquid chromatography–mass spectroscopy (LC/MS), and the positive impact of biochar colloids is ascribed to their abundant adsorption sites, which may facilitate MB adsorption and its photocatalytic degradation.

Keywords

Biochar Colloids Contaminants Photocatalysis Water treatment 

1 Introduction

Biochar is considered a new class of carbon-rich materials which can be produced by thermal treatment of biomass under limited oxygen (Ahmad et al. 2014). Due to the abundance of agricultural waste—a major resource for biochar production—and the tunability of biochar surface chemistry, biochar has received considerable attention for potential use in soil amendment, carbon dioxide sequestration, and contaminants removal (Ahmad et al. 2014; Manya 2012; Xiao et al. 2018). The carbonaceous nature of biochar and presence of functional groups on its surface have made biochar a versatile adsorbent to capture both organic and inorganic pollutants from water. While chemisorption and physiosorption are regarded as the primary removal mechanisms of the former, ion exchange, complexation with functional groups, and coordination of metal ions with \(\pi\) electrons of biochar are proposed as the governing removal mechanisms of the latter (Xie et al. 2015; Oliveira et al. 2017; Li et al. 2017b). Moreover, composites of biochar have also been investigated in remediation studies due to the synergistic effect of biochar and metal oxide particles in contaminants removal (Tan et al. 2016; Ghaffar et al. 2018; Milan and Liu 2019). More recently, biochar-supported \(\hbox {TiO}_{{2}}\) nanoparticle hybrids have been used in the photocatalytic degradation of model organic contaminants, since biochar is believed to promote organic adsorption and the generation of free radical species (Colmenares et al. 2016; Lisowski et al. 2017; Cai et al. 2017).

Recently, spherical carbon-rich colloids with a relatively high surface charge, so-called biochar colloids, have been extracted as a side product from pyrolyzed biomass via sonication (Wang et al. 2013a, b; Oleszczuk et al. 2016), acid/base (Li et al. 2017b), grinding (Li et al. 2017a), and ball milling (Naghdi et al. 2017; Lyu et al. 2018; Wang et al. 2018; Cao et al. 2019). It has been suggested that biochar colloids originate from the physical disintegration of amorphous regions of bulk biochar with higher polar content and less aromatic structure (Qu et al. 2016; Liu et al. 2018). From an environmental point of view, such characteristics may affect biochar colloids transport in soil and water, and have potential agronomic implications (Chen et al. 2017, 2018; Yue et al. 2019). From an engineering standpoint, such colloids can be used to bind organic molecules (Lyu et al. 2018; Tang et al. 2016; Dong et al. 2018) and inorganic species (Qian et al. 2016; Wang et al. 2018; Cao et al. 2019) or they can be employed to retard the colloidal mobility of engineered nanoparticles such as cesium oxide nanoparticles, which have demonstrated cytotoxicity and genotoxicity (Yi et al. 2015). More recently, the photochemical degradation of organic contaminants by colloids derived from biochar has been studied, and their contribution to the photogeneration of reactive species such as \(^{.}\)OH has been reported to be responsible for contaminants degradation (Fang et al. 2017; Zhou et al. 2018). Fu et al. (2016) have shown that the superoxide generation is promoted by phenolic structures in the biochar colloids, while carbonyl-bearing fractions, excluding aromatic ketones, enhance singlet oxygen formation.

Although, in recent years, biochar colloids have been characterized (Song et al. 2019; Yang et al. 2019) and investigated for the removal of organic and inorganic species (Wang et al. 2018; Dong et al. 2018; Cao et al. 2019), most of the studies deal with relatively high concentration of the studied contaminants, and there is no report on the effects of biochar colloids on the toxicity of such species to living organisms in the event of their environmental release. Moreover, biochar colloids possess a low photocatalytic activity, and they may undergo degradation, requiring the use of higher dosages of these colloids. In this work, the colloidal properties, surface chemistry, and toxicity of biochar colloids extracted from pyrolyzed wood chips are characterized. Their copper sorption and their effect on acute 48 h lethal concentration (\(\hbox {LC}_{{50}}\)) of copper in sub-ppm concentration to Daphnia magna are studied to mimic a realistic environment. To study their organic contaminants adsorption and degradation, the biochar colloids are coupled with \(\hbox {TiO}_{{2}}\) nanoparticles to prepare a photocatalyst and their performance is then evaluated using methylene blue (MB) (\(\le\) 10 ppm) as a model organic pollutant at different biochar colloids loadings, pH, and MB concentrations.

2 Materials and methods

2.1 Materials

Biochar from mixed wood chips pyrolyzed at 500 \(^{\circ }\hbox {C}\) was provided by the Alberta Biochar Initiative (ABI). Laboratory grade titanium (IV) dioxide nanopowder (Aeroxide® P25, average diameter 20 nm, 80% anatase and 20% rutile), and methylene blue were purchased from Sigma Aldrich and Fisher Scientific, Canada, respectively. A 1000 ppm copper nitrate standard was supplied by Fisher Scientific, Canada.

2.2 Methods

Biochar colloids extraction was performed by dispersing 3 g of ground and sieved (< 1 mm) biochar in 30 mL ultrapure water in a 50 mL polypropylene centrifuge tube. The suspension was placed in an ice bath and sonicated using a probe sonicator (Sonic Dismembrator Model 100, Fisher Scientific) at 20 W for 5 min (Oleszczuk et al. 2016). The sonicated suspensions were centrifuged at 3000g for 10 min, followed by filtration of the supernatant using a 450 nm nylon syringe filter.

Background electrolyte for copper (Cu) solutions was prepared by dissolving sodium bicarbonate, potassium chloride, calcium chloride, and magnesium sulfate in deionized water to mimic Edmonton (Alberta, Canada) tap water (14.6 ppm Na, 2.5 ppm K, 15.3 ppm Ca, 15.3 ppm Mg). A 1000 ppm stock copper nitrate standard was diluted in the background electrolyte to prepare the desired Cu solutions, and its pH was adjusted by adding 1 M HCl or NaOH. Biochar colloids from a stock suspension of 400 ppm were added to each Cu solution, mixed on a rotary shaker, and samples were taken at predetermined times and centrifuged at 15000g for 5 min. Cu concentrations in the supernatants were analyzed using an Inductively Coupled Plasma-Triple Quadrupole Mass Spectrometer (ICP-MS/MS; Agilent 8800). To eliminate the potential contribution of Cu precipitation to its uptake by biochar colloids, control Cu solutions were conducted in parallel to treated samples for kinetics studies, and the sorption was determined by
$$\begin{aligned} {q_\mathrm{{removal}}}=\frac{C_\mathrm{{sample}}-C_\mathrm{{control}}}{C_\mathrm{{biochar}\,\mathrm {colloids}}} \end{aligned}$$
(1)
in which \(\hbox {q}_{\mathrm{{removal}}}\) is the Cu sorption of biochar colloids, \(\hbox {C}_{\mathrm{{sample}}}\) is the Cu concentration in the supernatant of the sample, \(\hbox {C}_{\mathrm{{control}}}\) is the Cu concentration in the supernatant of the control, and \(\hbox {C}_\mathrm{{biochar}\,\mathrm {colloids}}\) is the biochar colloids concentration in the treated sample.

For the photocatalysis experiments, a 10 g \(\hbox {L}^{-1}\) stock suspension of \(\hbox {TiO}_{{2}}\) nanopowder in ultrapure water was prepared by sonication for 1 min. The stock suspension was mixed with a biochar colloids suspension, sonicated for 1 min, and added to 20 mL of methylene blue solution with different concentrations, such that the final concentration of the photocatalyst was always 100 ppm. The final dispersion was stirred in the dark for an hour to ensure that MB adsorption reached equilibrium. Then, the dispersion was illuminated by a handheld UV lamp (365 nm, 6 W, 950 \(\upmu\)\(\hbox {cm}^{-2}\), Ultraviolet Laboratory Products, USA) at a distance of 10 cm from the mixture while being stirred continuously at room temperature. Samples of the dispersion were taken every 10 min and immediately centrifuged at 2000g for 5 min. The light absorption spectra of the supernatant were acquired with a Thermo \(\hbox {Scientific}^\mathrm{{TM}}\) Evolution 60S UV–visible spectrophotometer and the spectral intensity at 665 nm was used to determine the remaining MB concentration (Ursachi et al. 2012). To measure the intrinsic MB uptake capacity of biochar colloids, dispersions of MB and biochar colloids were mixed and agitated for an hour in the dark followed by centrifugation at 15000g for 5 min. Aliquots of the supernatants were analyzed by UV–Vis spectroscopy. The products from the photocatalytic degradation reaction were analyzed using liquid chromatography/mass spectrometry (LC/MS) equipped with electrospray ionization (Agilent 6130 LC/MS, USA).

2.2.1 Toxicity tests

Daphnia magna were obtained from Aquatic Research Organisms (Hampton, NH, USA) in November of 2018, and housed in the Department of Biological Sciences at the University of Alberta. The colony was maintained following the Organization for Economic Cooperation and Development (OECD) guidelines with some additional adjustments (OECD 2008). The Daphnia were held in 2 L glass aquaria with dechlorinated Edmonton City tap water (14.6 ppm Na, 15.3 ppm Ca, 15.3 ppm Mg, 2.5 ppm K, pH 7.6, hardness under 12 h/ 12 h light:dark photoperiod). The temperature was maintained at 20 ± 1 \(^{\circ }\hbox {C}\), and the water was changed every 3 days. Daphnia magna were fed with Roti-Rich invertebrate food (VWR, Edmonton Alberta, Canada) once daily to satiation. Acute 48 h lethal toxicity (\(\hbox {LC}_{{50}}\)) tests were preformed according to standard OECD guidelines (OECD 2008). Neonate Daphnia (< 24 h) were used for Cu, biochar colloids and \(\hbox {Cu}+\hbox {biochar}\) colloids exposures. Treatments and replicates were made from a copper nitrate stock solution (10 ppm), and biochar colloids treatments were diluted from 400 ppm, to a final concentration of 10 ppm of biochar colloids per Cu treatment. Eight concentrations of Cu were used for both treatment groups: Cu alone or \(\hbox {Cu}+\hbox {biochar}\) colloids (0, 10, 20, 40, 80, 160, 320, 640 ppm; 3 replicates per concentration). Acute toxicity tests were run for 48 h, at which time mortality was assessed. Neonates were not fed during the exposure, and each replicate housed 5 neonate Daphnia. Similarly, eight concentrations of biochar colloids were used for biochar colloids toxicity study (0, 1, 2, 5, 10, 20, 40, and 80 ppm; 3 replicates per concentration). The acute lethal concentrations and confidence intervals (CI) were calculated using the US EPA’s Toxicity Relationship Analysis Program (TRAP) version \(1.30\hbox {a}\) (EPA, Washington, DC, USA).

2.2.2 Characterization

To probe the surface reactivity of biochar colloids, 20 mg of colloids and 2 mL of 20 mM NaCl were added to 138 mL of ultrapure water in preparation for potentiometric titrations (Mettler Toledo T50). The solution with biochar colloids was purged with \(\hbox {N}_{{2}}\) for 30 min before the titration and during titration to remove the effect of \(\hbox {CO}_{{2}}\). The initial pH was set to 2.7 by adding 100 mM HCl and the samples were titrated with 100 mM NaOH from pH 2.7 to pH 11 followed by reverse titration with 100 mM HCl from pH 11 to 2.7 at a constant dispensing rate of 0.1 mL \(\hbox {min}^{-1}\). To determine the acidity constants and the site concentrations of proton-active functional groups on the biochar colloids surfaces, titration data were modeled using the least-squared optimization software FITEQL 4.0, and a nonelectrostatic surface complexation modeling (NEM) approach (Alam et al. 2018b).

To determine the metals concentrations in the biochar colloids, the surface sorbed metal ions were removed from the biochar colloids surface by acidifying 8 mL of a 0.6 g \(\hbox {L}^{-1}\) biochar colloids suspension with HCl to pH 1 followed by centrifuging at 15000g for 15 min to separate the colloids. The supernatant was discarded and the colloids were re-dispersed in ultrapure water. The acidification and centrifugation were repeated three times. The remaining solids were re-dispersed in 10 mL ultrapure water, mixed with 5 mL \(\hbox {HNO}_{{3}}\) (\(70\%\) w/w), and then heated to 130 \(^{\circ }\hbox {C}\). After the evaporation of the matrix, the residues were diluted in \(2\%\) nitric acid and \(0.5\%\) HCl and analyzed by the Inductively Coupled Plasma-Triple Quadrupole Mass Spectrometer (ICP-MS/MS; Agilent 8800), using reaction (\(\hbox {O}_{{2}}\)) and collision gases (\(\hbox {H}_{{2}}\), He) where necessary to minimize polyatomic interferences (von Gunten et al. 2017).

The surface chemistry of the biochar colloids was further characterized by X-ray photoelectron spectroscopy (XPS) and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. XPS analysis was performed using a Kratos Axis 165 instrument with a monochromatized Al X-ray source at 12 mA and 14 kV. Survey scans spanned from binding energies of 1100 to 0 eV were collected with an analyzer pass energy of 160 eV and a step of 0.3 eV. FTIR spectra of a sample of ground parent biochar and a sample of dried biochar colloids were acquired with a platinum ATR-FTIR, Bruker, from wavenumbers of 4000 to 400 \(\hbox {cm}^{-1}\) at spectral resolution of 4 \(\hbox {cm}^{-1}\) (von Gunten et al. 2017). Furthermore, the carbon structure of the surface of biochar colloids was studied using a Thermo Scientific \(^\mathrm{{TM}}\) DXR \(^\mathrm{{TM}}\) Raman microscope equipped with a 532 nm laser with a power of 1 mW. The size and zeta potential of colloids were obtained using a Malvern Instrument Zetasizer Nano ZS equipped with a 633 nm laser (Westborough, Massachusetts, USA) and measured in \(173^{\circ }\) backscatter mode in pH range 2–10, after which the Smoluchowski equation was used to determine zeta potential (Hunter 1981). Biochar colloids were imaged using a Morgagni 268 Transmission Electron Microscope (TEM) from the Field Electron and Ion company (FEI), USA.

3 Results and discussion

3.1 Characterization

The ICP-MS/MS analyses showed that the metals constitute less than \(1\%\) of the biochar colloids, similar to their parent biochar (von Gunten et al. 2017), suggesting a relatively high carbon content of the extracted colloids (see the Supporting Information for details). From a surface chemistry perspective, the 2-site protonation model provides the best fit of the acid/base titration data yielding \(\hbox {pK}_{{a}}\) values of 2.1 and 8 and corresponding site concentrations of 2.1 and 1.7 mmol \(\hbox {g}^{-1}\), respectively (see Table 1). While the site concentrations of biochar colloids are considerably higher than those of parent biochar, the chemical groups on the first and second sites can be attributed to carboxyl and phenolic groups, respectively (Li et al. 2014). These results are further corroborated by FTIR analysis (Fig. 1). In addition to the ether and phenolic functional groups of the parent biochar (von Gunten et al. 2017), the biochar colloids have absorption bands characteristic for carbonyl (1738 \(\hbox {cm}^{-1}\)), alkoxy \(\hbox {C}\)\(\hbox {O}\) (\({\textit{sp}}^{3}\)) (\(1229\,\hbox {cm}^{-1}\)), and broadened OH stretching (\(3000\,\hbox {cm}^{-1}\)) are present, superimposed on CH stretching bands (2800–\(3100\,\hbox {cm}^{-1}\)), the latter of which confirms the existence of carboxyl groups on the biochar colloids surface (Colthup et al. 1990). These results are further supported by XPS findings in which the C \(1\hbox {s}\) binding energy spectrum of biochar colloids can be divided into four bands 284.8, 285.4, 286.5, and 289 eV corresponding to \(\hbox {C}\)\(\hbox {C}\), \(\hbox {C}\)\(\hbox {O}\), \(\hbox {C}\)\(\hbox {O}\)\(\hbox {C}\), and C(O)O groups, respectively (Fig. 2) (Mattevi et al. 2009; Sun et al. 2016). A similar binding energy spectrum was observed for the parent biochar; however, \(\hbox {C}\)\(\hbox {O}\) and C(O)O bands at 286.2 and 289 eV, respectively, are not as pronounced as those in the biochar colloids spectrum. It has been argued that less carbonized parts of bulk biochar are more susceptible to physical disintegration during sonication and release more colloidal biochar. Thereby, the resulting colloidal particles contain more oxygen-bearing groups, such as carboxyl and phenols, and less carbon as compared to the bulk biochar (Liu et al. 2018).

The presence of graphitic regions of biochar colloids and biochar itself was evidenced by Raman spectroscopy, with D and G bands appearing at 1340 and 1590 \(\hbox {cm}^{-1}\), respectively (Fig. \(\hbox {S}2\)). The former is the Raman signature of disorder and defects in the carbon structure and the latter corresponds to first-order in-plane vibration of pairs of C \(\hbox {sp}^{2}\) atoms (Lucchese et al. 2010). The higher \(\hbox {I}_{{D}}/\hbox {I}_{{G}}\) in biochar colloids, as compared to the parent biochar, reflects the presence of ring-breathing vibrations of C \(\hbox {sp}^{2}\) atoms in benzene, and a more amorphous structure (Ferrari and Robertson 2000; Sevilla and Fuertes 2009; Yang et al. 2011).
Table 1

Acid dissociation constants and charge density of their corresponding functional groups for the parent biochar and extracted biochar colloids

Material

\(\hbox {pKa}_{{1}}\)

\(\hbox {pKa}_{{2}}\)

Site 1 (mmol \(\hbox {g}^{-1}\))

Site 2 (mmol \(\hbox {g}^{-1}\))

Parent biochar

4.3

7.5

1.0

0.2

Biochar colloids

2.1

8.0

2.5

1.7

Fig. 1

Fourier Transform Infrared (FTIR) spectra of the parent biochar and extracted biochar colloids

Fig. 2

X-ray Photoelectron Spectroscopy (XPS) analysis of the parent biochar and extracted biochar colloids (BC)

TEM micrographs of biochar colloids show that they are mostly spherical with a diameter of 50–100 nm, as reported previously (Wang et al. 2013a) (see Fig. \(\hbox {S}3\)). Following TEM imaging, the particles were further characterized by DLS, and the hydrodynamic diameter and zeta potential of biochar colloids were determined to be 140 nm and \(-30\) to \(-40\) mV, respectively, at pH > 2 with a low polydispersity index (\(<0.15\)) (Figs. 3 and \(\hbox {S}4\)). Aggregation of the biochar colloids at pH 2, manifested in a higher polydispersity index and broader particle size distribution, is primarily because of the protonation of carboxyl and phenolic groups, as observed in the titration results, and subsequent diminishment of interparticle electrostatic repulsion. On the other hand, most of \(\hbox {TiO}_{{2}}\) nanoparticles have dimensions less than 30 nm (see Fig. \(\hbox {S}3\)) and are positively charged at pH < 8, with a \(\hbox {pH}_\mathrm{{pzc}}\) of 8 (Zhang et al. 2017) (Fig. 4).
Fig. 3

Size distributions of biochar colloids at different pH (top) and \(\zeta\)-potential of biochar colloids and \(\hbox {TiO}_{{2}}\) nanoparticles at different pH (bottom) acquired by Dynamic Light Scattering (DLS)

Fig. 4

Kinetics of Cu sorption to biochar colloids (10 ppm) at different pH. Initial Cu concentration was 0.5 ppm

Fig. 5

Kinetics of Cu sorption to biochar colloids (10 ppm) at different pH. Initial Cu concentration was 1 ppm

3.2 Sorption of Cu as a model inorganic contaminant

Acute 48 h lethal toxicity (\(\hbox {LC}_{{50}}\)) of biochar colloids was studied in the concentration range of 0–80 ppm, and no toxicity was observed within this concentration range, as previously observed for natural dissolved organic matter (Albanese et al. 2017). Knowing these biochar colloids pose no toxicity themselves, we proceeded to study the kinetics of Cu sorption to biochar colloids which show relatively fast Cu sorption across the studied pH range, except at pH 8 with an initial Cu concentration of 1 ppm. In addition, Cu binding is nearly instantaneous which was determined by centrifuging the dispersion immediately after mixing the biochar colloids and Cu solution (Fig. 5). This is in agreement with the surface chemistry and colloidal stability of biochar colloids in which the high presence of carboxyl and hydroxyl groups can scavenge Cu ions, as shown by titration and zeta-measurements. Reduced Cu sorption at pH 3 and 5 can be related to the partial protonation of biochar colloids carboxyl and hydroxyl groups, while at pH 8, most of these groups are deprotonated and can sorb more than 22 mg \(\hbox {g}^{-1}\) of Cu, as it has been well-reported in the literature for bulk biochar (Wang et al. 2018; Chen et al. 2011; He et al. 2018; Alam et al. 2018a). To shed more light on the mechanisms of Cu sorption, a pseudo-second-order kinetics model was used to fit the sorption data (Chen et al. 2011; Ho and McKay 1999), according to Eq. 1 in supporting information. The results of modeling have been summarized in Table 2, which indicate high correlation coefficients (\(>0.9\)) for all conditions. Moreover, Cu sorption and sorption rate constants of biochar colloids are significantly higher than those reported for bulk biochar in the literature owing to the colloidal properties and high charge density of biochar colloids (Chen et al. 2011).
Table 2

Pseudo-second-order kinetics modeling of Cu sorption by biochar colloids

Cu concentration (ppm)

pH

\(q_\mathrm{{e}}\) (mg \(\hbox {g}^{-1}\))

K (g mg \(^{-1}\)\(\hbox {h}^{-1}\))

R \(^{2}\)

0.5

3

4.3

0.2

0.91

0.5

5

3.7

2.7

0.92

0.5

8

11.7

4.9

0.99

1

3

3.1

0.58

0.92

1

5

10.8

0.65

0.99

1

8

23.6

10.0

0.98

Cu sorption to biochar colloids was modeled using isotherm approaches, and was studied at the same Cu concentration range as the toxicity tests (Fig. 6). Fitting of these results with the Langmuir and Freundlich models, as summarized in Table 3, reveals a relatively poor correlation coefficient (0.5) for the Langmuir model but a significantly higher one for the Freundlich model (0.86) (see supporting information for relevant equations). The Freundlich model is empirical and can be used to model nonideal sorption on heterogeneous surfaces and multilayer sorption (Ho et al. 2002). A high correlation coefficient for the Freundlich model might indicate that the surface of biochar colloids is heterogeneous, perhaps due to their different formation pathways. Liu et al. (2018) identified two pathways including pore collapse during pyrolysis and physical weathering, and they observed a noticeably higher oxygen content in biochar colloids from physical degradation pathway. In our study, biochar colloids were extracted by sonication and the final biochar colloids suspension include a mixture of biochar colloids resulting from both pore collapse and physical degradation.
Fig. 6

Cu sorption of biochar colloids (10 ppm) at room temperature

Table 3

Langmuir and Freundlich model fitting results for the experimental data in which n, \({K}_\mathrm{{f}}\), \({Q}_{{\max }}\) (mg \(\hbox {g}^{-1}\)), and b are the adsorption capacity index, adsorption intensity index, maximum adsorption capacity, and the affinity constant, respectively

Freundlich model

Langmuir model

\({n}=2.04\)

\({Q}_{\max }=15.8\)

\({K}_\mathrm{{f}}=12.1\)

\({b}=3.5\)

\({R}^{2}=0.86\)

\({R}^{2}=0.5\)

Due to their high charge content and, subsequently, their Cu-binding capacity, biochar colloids can alter the toxicity of Cu to Daphnia magna (Fig. 7) which may have significant environmental implications. The acute lethal concentration of Cu in the absence of biochar colloids was found to be 43 ± 19 ppb with a confidence interval of 2–85 ppb, whereas in the presence of biochar colloids, the values are 64 ± 22 ppb and 15–113 ppm, respectively. The 21 ppb increase in \(\hbox {LC}_{{50}}\) of Cu is in good agreement with Cu sorption capacity of 2 mg \(\hbox {g}^{-1}\) for biochar colloids at Cu concentration of \(\hbox {C}_\mathrm{{eq}}=45\) ppb, as shown in Fig. 6. Similar results have been reported for natural dissolved organic matter in the past, which implies that the release of biochar colloids from bulk biochar in the environment can mitigate sub-ppm transition metal toxicity to aquatic organisms (Schamphelaere et al. 2004; Blewett et al. 2018).
Fig. 7

Mortality of Daphnia magna in the presence of Cu and biochar colloids (10 ppm) at room temperature

3.3 Adsorption and degradation of methylene blue as a model organic contaminant

As explained earlier, biochar colloids have a carbonaceous nature and posses oxygen-containing functional groups (Lyu et al. 2018) making them an ideal candidate for adsorption of both inorganic and organic contaminants. Moreover, carbonaceous materials such as biochar can be coupled with photocatalysts such as \(\hbox {TiO}_{{2}}\) to adsorb and degrade the sorbed organic contaminants (Colmenares et al. 2016; Lisowski et al. 2017; Cai et al. 2017). Therefore, following our Cu sorption and toxicity studies, we explored the possibility of biochar colloids application in adsorption and degradation of organic contaminants (\(\le\) 10 ppm) using methylene blue (MB) as a model organic pollutant. Because both biochar colloids and \(\hbox {TiO}_{{2}}\) nanoparticles are highly charged, it is possible to prepare a new photocatalyst by coupling them through electrostatic attraction. Successful coupling was confirmed by the increase in hydrodynamic size of the resulting composite particles (Fig. 8).
Fig. 8

Particle size distribution of biochar colloids (BC) and their composite with titanium dioxide (\(\hbox {TiO}_{{2}}/5\%\) biochar colloids)

Our preliminary MB adsorption tests (data not shown) showed that the adsorption equilibrium between MB and biochar colloids can be achieved within an hour, and MB uptake capacity of biochar colloids can reach as high as 80 mg \(\hbox {g}^{-1}\) (see Fig. S7), as reported previously (Lyu et al. 2018). While the MB adsorption capacity of \(\hbox {TiO}_{{2}}\) nanoparticles is about 1 mg \(\hbox {g}^{-1}\), their composites with biochar colloids exhibited a higher MB uptake capacity, ranging from 1.8 to 9 mg \(\hbox {g}^{-1}\) as biochar colloids dosage increases from 1 to \(10\%\) (Fig. \(\hbox {S}7\)).

As shown in Fig. \(\hbox {S}8\), coupling \(\hbox {TiO}_{{2}}\) with biochar colloids has a positive effect on the photodegradation of methylene blue up to \(5\%\) loading of biochar colloids after which the carbon nanomaterials block light irradiation of \(\hbox {TiO}_{{2}}\) and reduce the overall photoconversion efficiency, as reported previously for graphene and carbon nanotubes (Zhang et al. 2010). Moreover, the kinetics of the photoconversion at a \(5\%\) biochar colloids loading is considerably faster than that of bare \(\hbox {TiO}_{{2}}\) (Fig. 9), and its final removal efficiency is \(21\%\) higher after 1 h, only slightly lower than that of previously reported carbon doped \(\hbox {TiO}_{{2}}\), perhaps because of less intimate contact between biochar colloids and \(\hbox {TiO}_{{2}}\) (Lin et al. 2013). In addition, under UV illumination and in the absence of \(\hbox {TiO}_{{2}}\), MB shows no indication of photodegradation, even in the presence of biochar colloids, which highlights the role of \(\hbox {TiO}_{{2}}\) in generating radical species.

The role of biochar colloids can be explained by their high density of negative charge which may provide more adsorption sites for methylene blue and may accelerate photodegradation (Lisowski et al. 2017; Cai et al. 2017; Leary and Westwood 2011; Zhang et al. 2012; Li et al. 2016). Such improvement has been reported for carbon black, a carbonaceous material with similar properties to biochar colloids (Mao and Weng 2009). Moreover, it has been argued in literature that a complementary component such as nanocarbon cannot only accommodate more reaction sites but also act as an electron sink to enhance the interfacial charge separation in \(\hbox {TiO}_{{2}}\) nanoparticles and elevate radical hydroxyl and oxygen formation (Leary and Westwood 2011; Zhang et al. 2012; Li et al. 2016; Colmenares et al. 2016). We conducted a series of photoluminescence spectroscopy experiments to study the effect of biochar colloids on electron/hole recombination (Lin et al. 2013). However, no significant impact of biochar colloids on interfacial charge separation in \(\hbox {TiO}_{{2}}\) was observed. Moreover, because biochar colloids themselves did not degrade MB in the absence of \(\hbox {TiO}_{{2}}\) and the presence of UV illumination (Fig. 9) it can be concluded that their contribution to the photocatalytic activity of the \(\hbox {TiO}_{{2}}\)/biochar colloids composite is mainly governed by MB adsorption.

To better understand the kinetics of MB degradation, the Langmuir–Hinshelwood model was used to fit the experimental data (Boudart 1956). Nonlinear regression fitting was utilized to obtain \(K_{1}\) and \(K_{2}\) in Eq. 5 in the supporting information file and the results are presented in Table 4. While the adsorption equilibrium constant increases with increasing biochar colloids dosage, due to a higher methylene blue uptake, the reaction rate peaks at \(5\%\) after which it decreases, likely because of the decrease in \(\hbox {TiO}_{{2}}\) illumination efficiency as explained earlier. While the experimental data and theoretical predictions agree well in the case of \(\hbox {TiO}_{{2}}\) alone, the model overestimates the hybrid photodegradation efficiency. The adsorption of degraded methylene blue to biochar colloids surface underpins the latter deviation, given that the biochar colloids surface is comprised of hydrophobic moieties, as evidenced by the XPS and FTIR analyses. The adsorption of these degraded MB molecules generated by photodegradation to biochar colloids inhibits further adsorption of MB itself, resulting in slower degradation as time elapses (Fig. 9). Increasing the initial MB concentration promotes its adsorption to biochar colloids (Fig. \(\hbox {S}9\)). On the other hand, it decelerates MB photodegradation by both \(\hbox {TiO}_{{2}}\) nanoparticles and the composite photocatalysts, as shown in Fig. 10 and reflected in reaction rates in Table 5. Since MB themselves are prone to absorb UV light; thereby, less UV radiation is received by the photocatalysts (Li et al. 2008; Xu et al. 2014). For the reasons mentioned earlier, the calculated reaction rate and adsorption constants from nonlinear fitting are markedly higher for the composite photocatalyst as compared to \(\hbox {TiO}_{{2}}\) itself across the studied MB concentration range (Table 5). Similarly, the effect of initial MB pH on its photodegradation by \(\hbox {TiO}_{{2}}\)/biochar colloids (\(5\%\)) was investigated, and the results suggest a slower photodegradation rate under acidic conditions (Fig. 11), whereas at neutral and alkaline pH, the photodegradation kinetics are similar. At lower pH, protonation of the biochar colloids results in a lower \(\zeta\)-potential (Fig. 3) weakening the electrostatic attraction of positively charged MB, as reflected in their lower uptake capacity (Fig. \(\hbox {S}10\)). It is noteworthy that a modestly higher MB uptake at pH 8, due to a stronger electrostatic attraction, did not lead to faster degradation. The reason lies in the isoelectric point of \(\hbox {TiO}_{{2}}\) particles (pH 8), at which they lose their affinity with biochar colloids.
Table 4

Removal efficiency, the reaction rate, and the adsorption equilibrium constants of 100 ppm photocatalyst with different biochar colloids dosage at 100 ppm methylene blue, pH 5 and room temperature

Biochar dosage (\(\%\))

Removal efficiency (\(\%\))

\(K_{1}\) (min \(^{-1}\))

\(K_{2}\) (L mg \(^{-1}\))

0

\(50\pm 0.3\)

0.0128

0

1

\(55\pm 0.5\)

0.0147

0

5

\(71\pm 4\)

0.03

0.033

10

\(61\pm 3\)

0.028

0.048

The reported data and error bars are the average and standard deviation of 3 replicates, respectively

Table 5

Effect of methylene blue concentration on the reaction rate and adsorption equilibrium constants of 100 ppm photocatalyst at pH 5, and room temperature

Photocatalyst

MB concentration

\(K_{1}\) (min \(^{-1}\))

\(K_{2}\) (L mg \(^{-1}\))

\(\hbox {TiO}_{{2}}\)

2

0.082

0.118

5

0.03

0

10

0.0128

0

\(\hbox {TiO}_{{2}}/5\%\) biochar colloids

2

0.2

2.2

5

0.06

0.1

10

0.03

0.033

The reported data and error bars are the average and standard deviation of 3 replicates, respectively

The relative abundance of degradation products was determined by liquid chromatography (Fig. 12), and using their mass to charge peaks in mass spectroscopy study, demethylation is proposed as the degradation pathway as photocatalysis proceeds (Fig. 13). While initial methylene blue shows a single peak in the chromatograph, under UV irradiation in the presence of \(\hbox {TiO}_{{2}}\) degradation products, which have lost one and two methyl groups (products b and c in Fig. 13, respectively), start to appear. The relative abundance of these products increased with the use of biochar colloids, and trace of a new degradation product, d, was observed, which are in agreement with diminished blue color intensity of the initial MB (Rauf et al. 2010; Zhang et al. 2001). It has been proposed that because of their weak electron donor characteristic, methyl groups on MB are prone to cleaving by electrophilic species (Zhang et al. 2001). Biochar colloids have a higher MB binding capacity bringing more MB molecules to the vicinity of the \(\hbox {TiO}_{{2}}\) surface, where the concentration of such radical species is higher.

4 Conclusions

In this work, biochar colloids were extracted as a byproduct from pyrolyzed biomass, and their colloidal properties, surface chemistry, and toxicity were studied. Biochar colloids showed a high colloidal stability, zeta potential of -30 to -40 mV at pH > 2, and a significantly higher charge content as compared to the bulk biochar. Moreover, biochar colloids did not pose any toxicity in the studied concentration range of 0-80 ppm which, together with their colloidal properties and surface chemistry, make them an ideal candidate for contaminants removal. Sorption of sub-ppm Cu, as a model inorganic contaminant, to biochar colloids was studied under different physiochemical conditions and a high Cu sorption, 22 mg \(\hbox {g}^{-1}\), was observed which was attributed to the presence of carboxyl groups on biochar colloids surface. Pseudo-second-order kinetics and Freundlich models were found to fit the Cu sorption kinetics and isotherms with a high correlation coefficient, respectively, indicating heterogeneity of the biochar colloids surface chemistry. Moreover, it was found that they can increase acute 48 h lethal (\(\hbox {LC}_{{50}}\)) of Cu to Daphnia magna by 21 ppb, which has significant environmental implications in the case of biochar colloids release. To study organic contaminants adsorption and degradation, a new photocatalyst was prepared by hybridizing \(\hbox {TiO}_{{2}}\) nanoparticles with biochar colloids via electrostatic coupling. The photoconversion efficiency of the hybrid was evaluated at different dosages, solution pH, and organic contaminant (methylene blue) concentrations. Our findings show that by replacing only \(5\%\) of the \(\hbox {TiO}_{{2}}\) photocatalyst with biochar colloids, the photodegradation efficiency was improved by \(21\%\). Moreover, at \(5\%\) dosage of biochar colloids, the calculated reaction constant was more than twice of that of \(\hbox {TiO}_{{2}}\) nanoparticles alone, regardless of methylene blue concentration. This considerable positive influence of incorporating biochar colloids into the hybrid material may be related to its high density of negative charge and methylene blue uptake which endow \(\hbox {TiO}_{{2}}\)/biochar colloids composites with a higher reactive surface area. For these reasons, we suggest that biochar colloids, extracted as side product from pyrolyzed biomass, may be a viable sorbent in removal of dilute contaminants in water treatment applications.
Fig. 9

Kinetics of methylene blue (MB) photodegradation in the absence of photocatalyst (\(\times\)) and the presence of \(\hbox {TiO}_{{2}}\) nanoparticles and varying dosage of biochar colloids (BC) at room temperature (symbols) and their respective fitting (lines). The initial concentrations of MB and photocatalyst are 10 and 100 ppm, respectively. The reported data and error bars are the average and standard deviation of 3 replicates, respectively

Fig. 10

Effect of initial methylene blue (MB) concentration on its photodegradation by \(\hbox {TiO}_{{2}}\) nanoparticles and \(\hbox {TiO}_{{2}}\) nanoparticles/biochar colloids (BC) (\(5\%\)) at pH 5 and room temperature (symbols) and their respective fitting (lines). The total concentration of the photocatalyst is 100. The reported data and error bars are the average and standard deviation of 3 replicates, respectively

Fig. 11

Effect of initial methylene blue (MB) pH on its photodegradation in the presence of \(\hbox {TiO}_{{2}}\) nanoparticles/biochar colloids (BC) (\(5\%\)) at room temperature. The initial concentrations of MB and photocatalyst are 10 and 100 ppm, respectively. The reported data and error bars are the average and standard deviation of 3 replicates, respectively

Fig. 12

Liquid chromatography patterns of methylene blue, degradation products of methylene blue in the presence of \(\hbox {TiO}_{{2}}\), and degradation products of methylene blue in the presence of \(\hbox {TiO}_{{2}}\)/biochar colloids(\(5\%\)) at pH 5

Fig. 13

Proposed structure of main degradation products based on liquid chromatography–mass spectroscopy results (LC/MS). See supporting information on details of mass to charge peaks

Notes

Acknowledgements

This work was supported by a Natural Sciences and Engineering Research Council (NSERC) Discovery grant (RGPIN-04134) to D.S.A. The authors would like to thank Prof. Jonathan Curtis in department of Agricultural, Food, and Nutritional Science and Prof. Al Meldrum in the Department of Physics at the University of Alberta for the use of FTIR and photoluminescence spectroscopy, respectively. Furthermore, the authors are grateful to Prof. Jonathan G. C. Veinot and Maryam Aghajamali in the Department of Chemistry at the University of Alberta for the use of a Zetasizer.

Supplementary material

42773_2019_14_MOESM1_ESM.docx (943 kb)
Supplementary material 1 (docx 942 KB)

References

  1. Ahmad M, Rajapaksha AU, Lim JE, Zhang M, Bolan N, Mohan D, Vithanage M, Lee SS, Ok YS (2014) Biochar as a sorbent for contaminant management in soil and water: a review. Chemosphere 99:19–33Google Scholar
  2. Alam MS, Gorman-Lewis D, Chen N, Flynn SL, Ok YS, Konhauser KO, Alessi DS (2018a) Thermodynamic analysis of nickel(ii) and zinc(ii) adsorption to biochar. Environ Sci Technol 52(11):6246–6255Google Scholar
  3. Alam MS, Swaren L, von Gunten K, Cossio M, Bishop B, Robbins LJ, Hou D, Flynn SL, Ok YS, Konhauser KO, Alessi DS (2018b) Application of surface complexation modeling to trace metals uptake by biochar-amended agricultural soils. Appl Geochem 88(Part A):103–112Google Scholar
  4. Albanese KA, Lanno RP, Hadad CM, Chin Y-P (2017) Photolysis- and dissolved organic matter-induced toxicity of triclocarban to daphnia magna. Environ Sci Technol Lett 4:457–462Google Scholar
  5. Blewett TA, Dow EM, Wood CM, McGeer JC, Smith DS (2018) The role of dissolved organic carbon concentration and composition on nickel toxicity to early life-stages of the blue mussel mytilus edulis and purple sea urchin strongylocentrotus purpuratus. Ecotoxico. Environ Saf 160:162–170Google Scholar
  6. Boudart M (1956) Kinetics on ideal and real surfaces. A I Ch E J 1:62–64Google Scholar
  7. Cai X, Li J, Liu Y, Yan Z, Tan X, Liu S, Zeng G, Gu Y, Hu X, Jiang L (2017) Titanium dioxide-coated biochar composites as adsorptive and photocatalytic degradation materials for the removal of aqueous organic pollutants. ACS Sustain Chem Eng 93(3):783–791Google Scholar
  8. Cao Y, Xiao W, Shen G, Ji G, Zhang Y, Gao C, Han L (2019) Carbonization and ball milling on the enhancement of pb(ii) adsorption by wheat straw: Competitive effects of ion exchange and precipitation. Bioresour Technol 273:70–76Google Scholar
  9. Chen M, Wang D, Yang F, Xu X, Xu N, Cao X (2017) Transport and retention of biochar nanoparticles in a paddy soil under environmentally-relevant solution chemistry conditions. Environ Pollut 230:540–549Google Scholar
  10. Chen M, Wang D, Yang F, Xu X, Xu N, Cao X (2018) Contrasting effects of biochar nanoparticles on the retention and transport of phosphorus in acidic and alkaline soils. Environ Pollut 239:562–570Google Scholar
  11. Chen X, Chen G, Chen L, Chen Y, Lehmann J, McBride MB, Hay AG (2011) Adsorption of copper and zinc by biochars produced from pyrolysis of hardwood and corn straw in aqueous solution. Bioresour Technol 102(19):8877–8884Google Scholar
  12. Colmenares JC, Varma RS, Lisowski P (2016) Sustainable hybrid photocatalysts: titania immobilized on carbon materials derived from renewable and biodegradable resources. Green Chem 18:5736–5750Google Scholar
  13. Colthup NB, Daly LH, Wiberley SE (1990) Introduction to infrared and raman spectroscopy (third edition). Academic Press, CambridgeGoogle Scholar
  14. Dong X, He L, Hu H, Liu N, Gao S, Piao Y (2018) Removal of \(17\beta\)-estradiol by using highly adsorptive magnetic biochar nanoparticles from aqueous solution. Chem Eng J 352:371–379Google Scholar
  15. Fang G, Liu C, Wang Y, Dionysiou DD, Zhou D (2017) Photogeneration of reactive oxygen species from biochar suspension for diethyl phthalate degradation. Appl Catal B 214:34–45Google Scholar
  16. Ferrari AC, Robertson J (2000) Interpretation of raman spectra of disordered and amorphous carbon. Phys Rev B 61(20):14095–14107Google Scholar
  17. Fu H, Liu H, Mao J, Chu W, Li Q, Alvarez PJJ, Qu X, Zhu D (2016) Photochemistry of dissolved black carbon released from biochar: Reactive oxygen species generation and phototransformation. Environ Sci Technol 50:1218–1226Google Scholar
  18. Ghaffar A, Zhu X, Chen B (2018) Biochar composite membrane for high performance pollutant management: Fabrication, structural characteristics and synergistic mechanisms. Environ Pollut 233:1013–1023Google Scholar
  19. He P, Yu Q, Zhang H, Shao L, Lu F (2018) Removal of copper (ii) by biochar mediated by dissolved organic matter. Sci Rep 7:7091Google Scholar
  20. Ho Y-S, McKay G (1999) Pseudo-second order model for sorption processes. Process Biochem 34(5):451–465Google Scholar
  21. Ho Y-S, Porter JF, McKay G (2002) Equilibrium isotherm studies for the sorption of divalent metal ions onto peat: copper, nickel and lead single component systems. Water Air Soil Pollut 141(1):1–33Google Scholar
  22. Hunter RJ (1981) Zeta potential in colloid science. Academic Press, CambridgeGoogle Scholar
  23. Leary R, Westwood A (2011) Carbonaceous nanomaterials for the enhancement of \(\text{TiO}_{2}\) photocatalyis. Carbon 49(3):741–772Google Scholar
  24. Li L, Zhang K, Chen L, Huang Z, Liu G, Li M, Wen Y (2017a) Mass preparation of micro/nano-powders of biochar with water-dispersibility and their potential application. New J Chem 41:9649–9657Google Scholar
  25. Li M, Liu Q, Lou Z, Wang Y, Zhang Y, Qian G (2014) Method to characterize acid-base behavior of biochar: site modeling and theoretical simulation. ACS Sustain Chem Eng 2(11):2501–2509Google Scholar
  26. Li M, Zhang A, Wua H, Liu H, Lv J (2017b) Predicting potential release of dissolved organic matter from biocharsderived from agricultural residues using fluorescence and ultravioletabsorbance. J Hazard Mater 334:86–92Google Scholar
  27. Li X, Yu J, Wageh S, Al-Ghamdi AA, Xie J (2016) Graphene in photocatalysis: a review. Small 12(48):6640–6696Google Scholar
  28. Li Y, Sun S, Ma M, Ouyang Y, WenbinYan (2008) Kinetic study and model of the photocatalytic degradation of rhodamine b (rhb) by a \(\text{TiO}_{2}\)-coated activated carbon catalyst: effects of initial rhb content, light intensity and \(\text{TiO}_{2}\) content in the catalyst. Chem Eng J 142(2):147–155Google Scholar
  29. Lin C, Song Y, Cao L, Chen S (2013) Effective photocatalysis of functional nanocomposites based on carbon and \(\text{TiO}_2\) nanoparticles. Nanoscale 5(11):4986–4992Google Scholar
  30. Lisowski P, Colmenares JC, Masek O, Lisowski W, Lisovytskiy D, Kaminska A, Lomot D (2017) Dual functionality of \(\text{TiO}_{2}\)/biochar hybrid materials: photocatalytic phenol degradation in the liquid phase and selective oxidation of methanol in the gas phase. ACS Sustain Chem Eng 5(7):6274–6287Google Scholar
  31. Liu G, Zheng H, Jiang Z, Zhao J, Wang Z, Pan B, Xing B (2018) Formation and physicochemical characteristics of nano biochar: Insight into chemical and colloidal stability. Environ Sci Technol 52:10369–10379Google Scholar
  32. Lucchese MM, Stavale F, Ferreira EHM, Vilani C, Moutinho MVO, B.Capaz R, Achete CA, Jorio A (2010) Quantifying ion-induced defects and raman relaxation length in graphene. Carbon 48(5):1592–1597Google Scholar
  33. Lyu H, Gao B, Hed F, Zimmerman AR, Ding C, Tang J, Crittenden CJ (2018) Experimental and modeling investigations of ball-milled biochar for the removal of aqueous methylene blue. Chem Eng J 335:110–119Google Scholar
  34. Manya JJ (2012) Pyrolysis for biochar purposes: a review to establish current knowledge gaps and research needs. Environ Sci Technol 46(15):7939–7954Google Scholar
  35. Mao C-C, Weng H-S (2009) Promoting effect of adding carbon black to tio2 for aqueous photocatalytic degradation of methyl orange. Chem Eng J 155(3):744–749Google Scholar
  36. Mattevi C, Eda G, Agnoli S, Miller S, Mkhoyan KA, Celik O, Mastrogiovanni D, Granozzi G, Garfunkel E, Chhowa M (2009) Evolution of electrical, chemical, and structural properties of transparent and conducting chemically derived graphene thin films. Adv Funct Mater 19:2577–2583Google Scholar
  37. Milan MM, Liu G (2019) Sewage sludge-derived \(\text{TiO}_{2}/\text{Fe}/\text{Fe}_{3}\text{C}\)-biochar composite as an efficient heterogeneous catalyst for degradation of methylene blue. Chemosphere 215:101–114Google Scholar
  38. Naghdi M, Taheran M, Brar SK, Rouissia T, Verma M, Surampalli RY, Valero JR (2017) A green method for production of nanobiochar by ball milling-optimization and characterization. J Clean Prod 164:1394–1405Google Scholar
  39. OECD (2008) OECD. Guideline for testing of chemicals; No. 211, Daphnia magna reproduction test. OECDGoogle Scholar
  40. Oleszczuk P, Cwikla-Bundyra W, Bogusz A, Skwarek E, Ok YS (2016) Characterization of nanoparticles of biochars from different biomass. J Anal Appl Pyrolysis 121:165–172Google Scholar
  41. Oliveira FR, Patel AK, Jaisi PD, Adhikari S, Lud H, Khanal SK (2017) Environmental application of biochar: current status and perspectives. Bioresour Technol 246:110–122Google Scholar
  42. Qian L, Zhang W, Yan J, Han L, Gao W, Liu R, Chen M (2016) Effective removal of heavy metal by biochar colloids under different pyrolysis temperatures. Bioresour Technol 206:217–224Google Scholar
  43. Qu X, Fu H, Mao J, Ran Y, Zhang D, Zhu D (2016) Chemical and structural properties of dissolved black carbon released from biochars. Carbon 96:759–767Google Scholar
  44. Rauf MA, Meetani MA, Khaleel A, Ahmed A (2010) Photocatalytic degradation of methylene blue using a mixed catalyst and product analysis by lc/ms. Chem Eng J 157:373–378Google Scholar
  45. Schamphelaere KACD, Vasconcelos FM, Tack FMG, Allen HE, Janssen CR (2004) Effect of dissolved organic matter source on acute copper toxicity to daphnia magna. Environ Toxicol Chem 23(5):1248–1255Google Scholar
  46. Sevilla M, Fuertes AB (2009) The production of carbon materials by hydrothermal carbonization of cellulose. Carbon 47(9):2281–2289Google Scholar
  47. Song B, Chen M, Zhao L, Qiu H, Cao X (2019) Physicochemical property and colloidal stability of micron- and nano-particle biochar derived from a variety of feedstock sources. Sci Total Environ 661:685–695Google Scholar
  48. Sun Y, Wu Z-Y, Wang X, Ding C, Cheng W, Yu S-H, Wang X (2016) Macroscopic and microscopic investigation of u(vi) and eu(iii) adsorption on carbonaceous nanofibers. Environ Sci Technol 50(8):4459–4467Google Scholar
  49. Tan X, Guo LY, Ling GY, Xu Y, Ming ZG, Jiang HX, Bo LS, Wang X, Mian LS, Li J (2016) Biochar-based nano-composites for the decontamination of wastewater: a review. Bioresour Technol 212:318–333Google Scholar
  50. Tang J, Li X, Luo Y, Li G, Khan S (2016) Spectroscopic characterization of dissolved organic matter derived from different biochars and their polycylic aromatic hydrocarbons (pahs) binding affinity. Chemosphere 152:399–406Google Scholar
  51. Ursachi I, Stancu A, Vasile A (2012) Magnetic \(\alpha\)-\(\text{Fe}_{2}\text{O}_{3}/\text{mcm}\)-\(41\) nanocomposites: preparation, characterization, and catalytic activity for methylene blue degradation. J Colloid Interface Sci 377(1):184–190Google Scholar
  52. von Gunten K, Alam MS, Hubmann M, Ok YS, Konhauser KO, Alessi DS (2017) Modified sequential extraction for biochar and petroleum coke: metal release potential and its environmental implications. Bioresour Technol 236:106–110Google Scholar
  53. Wang B, Gao B, Wan Y (2018) Entrapment of ball-milled biochar in ca-alginate beads for the removal of aqueous cd(ii). J Ind Eng Chem 61:161–168Google Scholar
  54. Wang D, Zhang W, Hao X, Zhou D (2013a) Transport of biochar particles in saturated granular media: Effects of pyrolysis temperature and particle size. Environ Sci Technol 47:821–828Google Scholar
  55. Wang D, Zhang W, Zhou D (2013b) Antagonistic effects of humic acid and iron oxyhydroxide grain coating on biochar nanoparticle transport in saturated sand. Environ Sci Technol 47(10):5154–5161Google Scholar
  56. Xiao X, Chen B, Chen Z, Zhu L, Schnoor JL (2018) Insight into multiple and multilevel structures of biochars and their potential environmental applications: A critical review. Environ Sci Technol 52(9):5027–5047Google Scholar
  57. Xie T, Reddy KR, Wang C, Yargicoglu E, Spokas K (2015) Characteristics and applications of biochar for environmental remediation: a review. Crit Rev Env Sci Tech 45:939–969Google Scholar
  58. Xu C, Rangaiah GP, Zhao XS (2014) Photocatalytic degradation of methylene blue by titanium dioxide: experimental and modeling study. Ind Eng Chem Res 53(38):14641–14649Google Scholar
  59. Yang W, Shang J, Sharma P, Li B, Liu K, Flury M (2019) Colloidal stability and aggregation kinetics of biochar colloids: effects of pyrolysis temperature, cation type, and humic acid concentrations. Sci Total Environ 658:1306–1315Google Scholar
  60. Yang Z-C, Li X, Wang J (2011) Intrinsically fluorescent nitrogen-containing carbon nanoparticles synthesized by a hydrothermal process. Carbon 49(49):5207–5212Google Scholar
  61. Yi P, Pignatello JJ, Uchimiya M, White JC (2015) Heteroaggregation of cerium oxide nanoparticles and nanoparticles of pyrolyzed biomass. Environ Sci Technol 49(22):13294–13303Google Scholar
  62. Yue L, Liana F, Han Y, Bao Q, Wang Z, Xing B (2019) The effect of biochar nanoparticles on rice plant growth and the uptake of heavy metals: implications for agronomic benefits and potential risk. Sci Total Environ 656:9–18Google Scholar
  63. Zhang C, Lohwacharin J, Takizawa S (2017) Properties of residual titanium dioxide nanoparticles after extended periods of mixing and settling in synthetic and natural waters. Sci Rep 7:9943Google Scholar
  64. Zhang N, Zhang Y, Xu Y-J (2012) Recent progress on graphene-based photocatalysts: current status and future perspectives. Nanoscale 4:5792–5813Google Scholar
  65. Zhang T, Oyama T, Aoshima A, Hidaka H, Zhao J, Serpone N (2001) Photooxidative n-demethylation of methylene blue in aqueous \(\text{TiO}_{2}\) dispersions under uv irradiation. J Photochem Photobiol A 140(2):163–172Google Scholar
  66. Zhang Y, Tang Z-R, Fu X, Xu Y-J (2010) \(\text{TiO}_{2}\)-graphene nanocomposites for gas-phase photocatalytic degradation of volatile aromatic pollutant: Is \(\text{TiO}_{2}\)-graphene truly different from other \(\text{TiO}_{2}\)-carbon composite materials? ACS Nano 4(12):7303–7314Google Scholar
  67. Zhou Z, Chen B, Qu X, Fu H, Zhu D (2018) Dissolved black carbon as an efficient sensitizer in the photochemical transformation of \(17\alpha\)-estradiol in aqueous solution. Environ Sci Technol 52:10391–10399Google Scholar

Copyright information

© Shenyang Agricultural University 2019

Authors and Affiliations

  1. 1.Department of Earth and Atmospheric SciencesUniversity of AlbertaEdmontonCanada
  2. 2.Department of Agricultural, Food, and Nutritional ScienceUniversity of AlbertaEdmontonCanada
  3. 3.Department of Biological SciencesUniversity of AlbertaEdmontonCanada
  4. 4.School of Chemistry and Chemical EngineeringShanghai Jiao Tong UniversityShanghaiChina

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