This work aimed to determine activated carbon (AC) and hard wood derived biochar (BC) adsorption capacity for the uptake of four pesticides atrazine, chlorothalanil, α-endosulfan and β-endosulfan from aqueous solution by conducting batch experiments under different experimental conditions. Structural properties of AC and BC were determined through ‘SEM (Scanning Electron Microscope), FTIR (Fourier Transform Infrared Spectrometer) and XRD (X-ray Powder Diffraction Spectroscopy)’. The optimized pH, particle size, contact time, agitation speed and initial pesticides concentration for the maximum adsorption rates were found to be 7, 250 μm, 60 min, 180 rpm and 12 μgL¹ respectively. Pesticides adsorption were enhanced by increasing pH to 7 while slight decrease were noted when pH increases from 7 to 9. The adsorption equilibrium data were well described by the Langmuir isotherm model having a significant correlation coefficient value from 0.9999 to 1. Adsorption kinetic data were well fitted with the Lagergren's Pseudo-Second-Order kinetic model. The standard Gibb's free energy (ΔG) negative value at every temperature shows the practicability and spontaneity of the adsorption process. While the negative value for enthalpy change (ΔH) indicated the collective impact of exothermic adsorptions process with randomness intensifying due to positive entropy change.

  • The activated carbon (AC) and hard wood derived biochar were used as an adsorbent for pesticides remediation.

  • The external parameters were discussed in a very detail.

  • The adsorption capacity of both adsorbents were compared.

  • Detail characterization were carried out.

  • Adsorption mechanism was developed.

Water pollution consequent to pesticides addition is an essential environmental problem. The huge increase in world population during the 20th century would not have been possible without a simultaneous increase in food production. Almost one-third of agriculture production depends on pesticides utilization, otherwise an estimated 78% of fruit, 54% of vegetable and 32% of cereal crop production would be lost (Tudi et al. 2021). The increased use of pesticides in the agricultural sector and domestic applications, its prevalent mishandling (Thuy et al. 2012a, b), and its toxicity and carcinogenicity (Hussain et al. 2002) leads to production of toxic pollutants, contaminating the natural environment and causing human health risk (Hoai et al. 2011). Approximately, 2 million tonnes of pesticides are utilized annually worldwide (Sharma et al. 2019), however, it was only anticipated to be 5–7 metric tonnes with active substances annually throughout Europe (Kristoffersen et al. 2008). According to the United States Geological Survey (USGS), in US streams more than 90% of water samples were contaminated with a variety of pesticides. Similarly, Mazlan et al. (2017) reported 37,000–500,000 m2 of wetlands contamination in Canada by herbicides (Mazlan et al. 2017). Another illustration of the level of pesticide contamination in Turkey's West Mediterranean region is 53,349.5 g/ha, or an estimated 79% of the available pesticides (Yilmaz 2015). These pesticides percolate deep down in to the soil, contaminate the subsoil water, leaching into ground and surface water, and deteriorate water quality (Hussain et al. 2002). Since a few decades ago, remedial studies have gained attention in order to meet set drinking water requirements (Somashekar et al. 2015). Numerous research has been carried out to develop efficient techniques for the elimination of organic pollutants from water used for drinking purposes (Kubo et al. 2007; Ahmad et al. 2014) including precipitation, reverse osmosis, adsorption, ion exchange, incineration, air stripping, and chemical treatment. Amongst them, adsorption onto carbonaceous materials AC and BC as remedial strategy for pesticides' removal (Kyriakopoulos & Doulia 2006; Areerachakul et al. 2007; Mohan et al. 2014) has achieved environmental significance since it can efficiently remediate pollutants from both gaseous streams and aqueous environments (Aksu & Kabasakal 2004; Kah & Brown 2007). Adsorption as a surface phenomenon, its adsorption extent and rate for a specific adsorbent are influenced by the adsorbent physicochemical characteristics: pore size, elemental composition, surface chemistry and surface area (Liu et al. 2015; Khan et al. 2024a). During the adsorption process the pollutant adheres to the adsorbents surface due to electrostatic and hydrophobic interactions between the adsorbent and adsorbate (Al-Ghouti & Al-Absi 2020). For a long time, carbonaceous materials have been utilised as a good sorbent for remediation of organic and inorganic pollutants in water and soil medium (Ambaye et al. 2020).

Adsorption by AC has been the most effective remedial approach to treat contaminated wastewater and is therefore commonly used as a carbonaceous sorbent for organic pollutants' removal. Similar is the case with biochar, a carbon-rich material synthesized through pyrolysis with an intermediate to large surface area (Cao et al. 2011). Biochar has been in the attention of scientists due to its commendable role in the management of environmental problems (Sohi 2012). Biochar has certain unique properties: large surface area, porous structure, and increased surface functional groups, which make it the adsorbent of choice for the reduction of organic pollutants in water (Chen et al. 2007; Mohan et al. 2014). Moreover, biochar's production is also very low-cost; it is produced from solid waste and agricultural biomass, which is abundantly available in nature (Qian & Chen 2013). Atrazine, chlorothalanil, β-endosulfan, and α-endosulfan are the model pesticides used (Figure 1). Despite being prohibited due to their toxicity, the aforementioned pesticides are still in use in developing countries due to their low cost and versatility in the agriculture and industrial sector, ultimately contaminating water containing bodies (Sankararamakrishnan et al. 2005; Singh et al. 2012). In developing countries adsorption is considered as the most effective, promising, and commonly used water treatment technique (Foo & Hameed 2009; Khan et al. 2024b), while AC and BC were accepted as promising and very effective adsorbents for handling pesticide-contaminated water.
Figure 1

Chemical structure of atrazine (a), chlorothalanil (b), β-endosulfan (c) and α-endosulfan.

Figure 1

Chemical structure of atrazine (a), chlorothalanil (b), β-endosulfan (c) and α-endosulfan.

Close modal

During the past few decades, a number of studies have been conducted on biochar and activated carbon as promising adsorbents for pesticides remediation from water (Binh & Nguyen 2020). However, research on the optimal adsorption conditions, isotherm, and kinetics of a mixture of pesticides by the adsorbents AC and BC in aqueous solution is rarely investigated. Therefore, the aim of the study was to investigate the adsorption efficiency of BC and AC for four pesticides in aqueous solution.

Chemicals and reagents

The pesticides atrazine (C8H14ClN5), chlorothalanil (C8Cl4N2), β-endosulfan (C9-H6-Cl6-O3-S) and α-endosulfan (C9 H6 Cl6 O3 S), were used as adsorbate and were purchased from the local market. Initially, 1,000 μg L¹ stock solution of all the four pesticides was prepared, from which a further 12 μg L¹ working solution was prepared and used in the experiment. For pH adjustment, diluted HCl and NaOH were used, and buffer solutions of pH 3, 5, 7, 9 and 11 were used to sustain the specific pH of the solution. BC was derived from a hard wood (Dalbergia sissoo) through the process of pyrolysis under a continuous flow of nitrogen (N2) for 6 h at 500 °C of static temperature (Khan et al. 2015), and AC applied in these experiments was purchased from Norit Nederland BV, Amersfoort. Analytical grade chemicals (N-Hexane, dichloromethane, NaOH, HCl, Na₂SO₄) were used in the study. Samples was prepared in deionized water. Prior to starting each experiment, the glass-wares utilized were washed with dichloromethane and frequently rinsed with distilled water. The physical and chemical properties are provided in Table 1.

Table 1

Physical properties of AC and BC

Sr. no.PropertiesACBCH
Bulk density 34.4 kg cm−3 0.42 g cm−3 
Particle size 250 μm 250 μm 
Solid density 2.0–2.1 g cm−3 1.66 g cm−3 
Pore volume 1.39 nm 0.03–0.02 nm 
Surface area 4.25 m² g−1 2,000 m² g−1 
Water holding capacity 67.3% 274.1% 
Sr. no.PropertiesACBCH
Bulk density 34.4 kg cm−3 0.42 g cm−3 
Particle size 250 μm 250 μm 
Solid density 2.0–2.1 g cm−3 1.66 g cm−3 
Pore volume 1.39 nm 0.03–0.02 nm 
Surface area 4.25 m² g−1 2,000 m² g−1 
Water holding capacity 67.3% 274.1% 

Equipment

For pH measurements, a pH meter (Mettler–Toledo) was used. Gas chromatographic mass spectrophotometer (GC-MS Shimadzu, 2010) was used for determination of pesticides. BC and AC spectral properties were assessed through Fourier Transform Infrared Spectroscopy (FTIR) (Shimadzu IR Prestige-21), and X-ray diffraction analysis (XRD) (JDX-3532) was used to examine spectral characteristics of AC and BC, while scanning electron microscopy (SEM) (JSM 5910 JEOL) was used to examine the morphology of the adsorbent surface in the selected materials.

Sorption experiments

A batch equilibrium method was used to determine the sorption of pesticides on adsorbents AC and BC. Briefly, 40 mL pesticides solution and 100 mg of adsorbent were placed in 250 mL conical flasks at varying concentration (25–100 μg L¹), maintained at the desired pH and temperature. The solution pH was maintained by adding 0.1M NaOH or 0.1M HCl. Sample flasks were sealed and were agitated for 1 h on a reciprocal shaker at a rate of 180 rpm at a fixed temperature of 25 °C. At a pre-determined time, the liquid samples were withdrawn from the shaker and were filtered through Wattman filter paper. The GC-MS method, as described later, was adopted to quantify the pesticides remaining concentrations in the medium of adsorption. The adsorption capacity for pesticides uptake, represented as qe (mg/g), was determined through the following equation:
(1)
where Ci = initial pesticides' concentration (μg L¹), Cf = final pesticides' concentration (μg L¹), V = volume of the solution, and W = weight of the adsorbent (g).

Experiments were repeated three times and the average value of the obtained data were recorded. The studied parameters were adsorbent dose, pH, adsorbate initial concentration, particle size, temperature, contact time and rotation per minute (rpm).

Analytical method

Extraction of pesticides residues from filtrate

For pesticides' extraction from the filtrate of the batch adsorption, liquid-liquid extraction method was employed as the best suited extraction method (AOAC 2000). Briefly, 40 mL of filtrate, 12 mL of the solvent N-hexane and 4 g NaCl was placed into a conical flask and shaken in a horizontal shaker for 1 hour at a rate of 80 rpm (Bremon, POB 105363, Germany). For pH adjustment a few drops of phosphate buffer and diluted HCl and NaOH were added when needed. A separating funnel was used to separate the mixture until formation of two distinct phases. The parted N-hexane layer (filtrate) was rinsed twice through the addition of 2.4 mL hexane solvent. A further small amount of sodium sulphate (Na2SO4) was added to the separated layer of N-hexane in order to remove water particles. Following separation by a separating funnel, the contents were evaporated at a temperature of 25 °C using a rotary evaporator to reduce the volume up to 1 mL. The extraction and the analysis process precision and accuracy were checked by implying sample blanks and reference materials.

GC-MS chromatography

The saturated organic solvent was collected in a 1 mL GCMS vial and placed in the GC-MS agilent's port for determination of the pesticides by gas chromatograph. A gas chromatograph mass spectrophotometer was used for the analysis, equipped with a split-less mode injector system, a flame photometric detector and a TRB 5 MS capillary column with 30 m length, 0.25 mm internal diameter and 0.25 μm stationary film thickness prepared from Phenomenex. Temperature of the oven was initially maintained at 50 and 25–125 °C for 1 min, 125–200 °C at a rate of 10 °C/min, and 200–270 °C at a rate of 5 °C /min; a 1 μL sample was then injected under split mode (split ratio 10:1). For one GC run the total time was 27.5 min. The ultra-pure helium was passed through a molecular sieve trap and used the trapped oxygen as the carrier gas. The velocity was kept constant at 40 cm/sec and the temperature of the injection port was maintained at 250 °C and used in a split-less mode injecting system. The detector temperature was held at 270 °C. A hydrogen generator instrument was applied for supplying hydrogen gas for the flame photometric detector (FPD) at a flow rate of 69.0 mL/min.

Quality control and statistical analysis

To ensure quality control, gauging accurateness and precision standards solution and reagent blanks was involved in every batch experiment. No contamination of the glassware was recorded per se. The results of the standard solution were also found to be satisfactory (97–99%). Experiments were performed in triplicate and the obtained results were expressed as mean of the corresponding triplicates. For statistical analysis, Origin Pro 2016 was applied to prepare graphs.

Characterization of adsorbent material

Fourier transform infrared (FTIR) spectroscopy

The FTIR spectra of AC and BC is shown in Figure 2(a) and 2(b). Various functional groups were observed on the surface of particular adsorbent material. According to Tansel & Nagarajan (2004), the existence of functional group on the surfaces of the adsorbents are responsible for the adsorption process. The FTIR spectra of AC (Figure 2(a)) showed very low functional groups peak intensity. Peaks at 3,436, 2,950, 1,563 and 1,120 cm¹ were observed on AC spectra. Existence of (C ≡ C) ambiences in alkynes group is indicated by the peaks recorded at 3,436 and 2,950 cm¹ (Kazemi et al. 2016; Wang et al. 2016). The features of ѵ(C = O) vibration are represented by the peaks 1,563 and 1,120 cm¹ (Jaouen & Salmain 2015; Wang et al. 2015). This may be due to the existence of coordinated carbonyls group on the surface of the AC (Boag et al. 2008). Similarly, FTIR spectra of BC (Figure 2(b)) indicate the broad band at 3,425.58 which shows the OH stretching vibrations (Paiva et al. 1996). The broad band at 3,163.26 and 1,620.21 attributed to COO asymmetric stretching while the peak at 1,404.18 attributed to COO stretching vibration. The peak at 1,026.12 indicates the C-O presence on the BC surface.
Figure 2

Fourier transform infra-red (FTIR) spectra of AC (a) and BC (b).

Figure 2

Fourier transform infra-red (FTIR) spectra of AC (a) and BC (b).

Close modal

Scanning electron microscopy (SEM)

Morphological and physical characteristics of the adsorbents were studied using SEM analysis. The SEM analysis was conducted for both under-reference adsorbents, i.e., AC and BC prior and later to the adsorption process, as shown in Figure 3. Images suggested that the BC have smaller cavities and pores as compared to the carbon procured commercially. These images also indicated the carbon flakes and size of the pores varies parallel to the variation in the washing step of BC synthesis. Morphological study of the BC surface confirms the larger surface area for pesticide adsorption. Multiple patterns of deposition can be seen when various SEM images are compared. This indicates pesticides' deposition on BC following adsorption experiments. Images also show coverage of the pores during the process of adsorption. The case for AC was also similar following the same pattern.
Figure 3

The surface of AC and BC using SEM of AC and BC: (a) AC before adsorption, (b) AC after adsorption, (c) BC before adsorption, (d) BC after adsorption.

Figure 3

The surface of AC and BC using SEM of AC and BC: (a) AC before adsorption, (b) AC after adsorption, (c) BC before adsorption, (d) BC after adsorption.

Close modal

X-ray diffraction (XRD)

The purpose of XRD diffractogram is to assess the material's crystallinity. Figure 4 displays the diffractogram of AC and BC. Carbon existence is indicated by the broad peak between 22 and 25°, while the sharp peak at 29.5° (100) and 38.8° (111) was attributed to the presence of C and CaO, respectively. Similarly the peaks at 45° (200) and 65° (220) represents CaO and MgO, respectively. Amorphous structure of AC was observed due to the broad peaks obtained in the region of 45–65°, respectively. Similarly, the XRD patterns observed for BC shows that the peak at 2θ = 20–30° refers to the graphite 2 aromatic layer stacking structure, while crystallites dimensions originate which are vertical to the aromatic layer. High prevalence and the greater contents of CaO and MgO were observed at peaks of (111), (200) and (220), respectively. The most piercing and sturdiest peaks at 2θ = 26° originates at crystal clear CaO. The X-ray diffraction peak confirms that BC surface is heterogeneous in nature.
Figure 4

X-ray diffraction curve BC and AC.

Figure 4

X-ray diffraction curve BC and AC.

Close modal

Effect of contact time

The contact time effect on sorption of pesticides by AC and BC was investigated at 12 μgL¹ adsorbate initial concentration, 100 μg L¹ mass adsorbent, pH 7 and at fixed temperature of 30 °C. The removal percentage of a mixture of the four pesticides was measured at different contact times (30, 60, 360, 720, and 1,440 min). The pesticides uptake rates on the adsorbents (BC and AC) are evident from Figure 5. It shows that the pesticides sorption increases positively when the contact time increased. Initially adsorption showed a quite rapid pattern, followed by a gradual slowdown before achieving a final equilibrium position. An increase in the percentage of adsorption was recorded for atrazine from 88.2 to 95.7 and 87.4–94.9%, chlorothalanil 88.2–94.8 and 78.9–86.5%, β-endosulfan 81.5–87.8 and 75.7–84.9%, α-endosulfan 75.7–79.9 and 73.1–79.9% on AC and BC, respectively, with 12 μg L−1 initial concentration. Initially pesticides uptake by the sorbents was too quick because of the presence of abundant vacant positions for sorption, but as the contact time prolongs from 360 minutes, the adsorption rate was reduced. A similar trend was observed by Njoku & Hameed (2011) for the adsorption of pesticides. Finally, at the time interval of 1,440 minutes no more sorption of the pesticides was reported. This may be due to the reason that active binding sites were saturated by pesticides, also the concentration gradient between solid and liquid phases was decreased. Therefore, this point was selected as the equilibrium point. The adsorbent maximum adsorption capacity is represented by the mixture of pesticides adsorbed under operating conditions. Adsorbent adsorption capacity determine the rate of pesticides removal by transferring adsorbate particles from the outer to inner sites of the adsorbent. Similarly, at equilibrium a decrease in the rate of adsorption is observed and could be attributed to the pesticide molecules competition compared with the decreasing number of available adsorbents active sites (Alsherbeny et al. 2022). In addition, physicochemical properties of the compound were also involved in the sorption capacity, increasing with pesticides hydrophobicity and decreasing with their increased solubility in water, leading to a noticeable increase in contact time for polar pesticides (Rojas et al. 2014). The sorption capacity of the adsorbent and equilibrium time confirms the effectiveness of these materials for the elimination of pesticides from aqueous solution (Zheng et al. 2010).
Figure 5

The effect of contact time on the uptake of pesticides (temperature: 25 °C, pH: 7).

Figure 5

The effect of contact time on the uptake of pesticides (temperature: 25 °C, pH: 7).

Close modal

Effect of initial adsorbate (pesticides) concentration

The pesticide initial concentration is a vital parameter in the adsorption studies because a specific quantity of pesticide can be adsorbed by a defined quantity of adsorbent from water solutions. The effect of adsorbate's initial concertation is given in Figure 6, showing that the adsorption efficacy of the adsorbent decreased with the increase in initial concentration of the adsorbate. At various initial concentrations of 10, 25, 50, 75 and 100 μg L¹, the decrease in the percent removal of pesticides was observed in the range of 99.8–99.7 and 99.9–99.1% for atrazine, 98.8–93.8 and 99.1–97.1% for chlorothalanil, 95–89.8 and 96.9–93.8% for β-endosulfan, 90.9–86.5 and 95.7–90.6% for α-endosulfan on AC and BC, respectively. The results obtained are in line with the research performed by Memon et al. (2007) and Thuy et al. (2012a, b). It may be concluded that sorbate ion sorption involves larger active sites at lower sorbate ion/sorbent ratios. Along with an increase in the sorbate ions vs sorbent ions, saturation at the greater energy positions occurs, and adsorption starts at lower energies sites leading to a decrease in the adsorption percentage (Okoya et al. 2020). Previously conducted studies showed a progressive decline in the ion concentration ratio at higher concentrations to the active sites. Similar results were also obtained by Alsherbeny et al. (2022) who found that the adsorption sites were rapidly saturated by increasing adsorbate initial concentration. On the contrary, with the decrease in adsorbate initial concentration a progressive development was found in the adsorption of adsorbate on the adsorbent surface due to the availability of enough surface active sites.
Figure 6

Initial concentration effects on the uptake of pesticides.

Figure 6

Initial concentration effects on the uptake of pesticides.

Close modal

Effect of adsorbent dose

Adsorbent dosage is an important parameter in the adsorption process. This experiment was performed at 12 μg L¹ of stable initial concentrations, contact time of 1 h, temperature of 25 °C and at stable pH of 07. Table 2 makes it evident that the quantity of adsorbed pesticides is significantly influenced by the dose of the adsorbent. The results show that the adsorption rate increased positively with the increases in mass of the adsorbent from 20 to 200 μg L¹. The percentage removal of pesticides was observed for atrazine from 91.75 to 99.9 and 75.8–98.3%, chlorothalanil from 81.6 to 90 and 72.4–96.6%, β-endosulfan from 75.8 to 85.8 and 71.6–94.1%, α-endosulfan from 73.3 to 82.5 and 69.1–92.5% for AC and BC, respectively. One possible explanation could be the increase in the number of existing sorption positions along with the intensification in the amount of solid mass in the solution (Gupta et al. 2011b). The results may also be attributed to the competition among water molecules and pesticides towards the adsorbent surface. As the adsorbent dose increases the active sites and surface area are abundantly exposed to the pesticides, leading towards reduction in competition between water molecules and pesticides, enhancing the capacity of adsorption. On the other hand with the reduction of adsorbent dose, competition was boosted up among water molecules and pesticides for the surface functional group of the adsorbent, resulting in a reduction in capacity of pesticides' adsorption (Ahmad et al. 2014). Other adsorption studies which employed biochar and various other adsorbents for the removal of pesticides report equivalent effects (Okoya et al. 2020). Suo et al. (2018) reported that an increase in the dosage of adsorbent enhances the capacity of adsorption because the available surface area for adsorption increases positively.

Table 2

Effect of the adsorbent's dosage on the uptake of pesticides on to AC and BC (temperature 25 °C, contact time 1 h, pH 7, initial concentration 12 μg L¹)

% RemovalAC
BC
adsorbent dose (μg L¹)AtrazineChlorothalanilβ-endosulfanα-endosulfanAtrazineChlorothalanilβ-endosulfanα-endosulfan
20 91.75 81.66 75.83 73.33 75.83 72.41 71.66 69.16 
60 92.33 83.33 78.33 74.91 80.83 74.91 72.5 70 
120 99.75 88.33 82.5 75.83 91.5 89.08 82.91 80 
160 99.83 89.166 84.16 78.33 95.83 94.91 92.5 90.83 
200 99.91 90.00 85.83 82.50 98.33 96.66 94.16 92.5 
% RemovalAC
BC
adsorbent dose (μg L¹)AtrazineChlorothalanilβ-endosulfanα-endosulfanAtrazineChlorothalanilβ-endosulfanα-endosulfan
20 91.75 81.66 75.83 73.33 75.83 72.41 71.66 69.16 
60 92.33 83.33 78.33 74.91 80.83 74.91 72.5 70 
120 99.75 88.33 82.5 75.83 91.5 89.08 82.91 80 
160 99.83 89.166 84.16 78.33 95.83 94.91 92.5 90.83 
200 99.91 90.00 85.83 82.50 98.33 96.66 94.16 92.5 

Effect of pH

Adsorption highly depends on pH of the solution, having an influence on both ionization degree of adsorbate and surface charge of adsorbent during the process of adsorption (N'diaye et al. 2019). The initial pH of solution acts as a vital factor which influences the process of adsorption. In order to assess the effects of pH, pesticides' adsorptions were studied at a wide range of pH from 3 to 11. The model pesticides selected for this study were unstable and easily decomposed in alkaline conditions. Figure 7 shows that increases in the pH from 3 to 7 resulted in increases in adsorption of atrazine from 91 to 99 and 82–94%, chlorothalanil 90–95 and 82–93%, β-endosulfan 89–93 and 74–91%, α-endosulfan 88–92 and 72–82% for AC and BC, respectively. Further increase in solution's pH led towards a slight decrease in the adsorption process, hence the maximum adsorption rate for all the four pesticides was observed at pH 7 for both AC and BC, respectively. This indicates that at high pH the adsorbent surface was charged negatively, while at low pH the adsorbents surface was charged positively. Therefore, at neutral pH of the solution, the adsorbents' surface was charged negatively. This was helpful in the pesticides' removal because of the electrostatic interaction between the adsorbents and the adsorbate. Therefore, neutral pH 7 was proposed as the optimal pH and was maintained throughout the whole experimental study. The results obtained were closely related to the investigations conducted by Suo et al. (2018). Atrazine is a weak basic pesticide (Zheng et al. 2010). In an acidic medium, a carbonaceous adsorbent was generally found in protonated form while in an alkaline medium, it was found in deprotonated form. The adsorbent positively charged surface at neutral pH attracts superfluous H+ ions enhancing the process of adsorption. At higher pH of 9 both the adsorbent and atrazine surfaces in aqueous solution carries a negative charge resulting in electrostatic repulsive interaction, leading towards a reduction in adsorption efficiency (Tan et al. 2016). The positive charged pesticide and negative charged adsorbent surface result in an electrostatic attraction between adsorbent and adsorbate (Gupta et al. 2011a). Similarly, for endosulfan, negatively charged surface attracted electrostatically towards the positively charged adsorbent surface, while when the pH increases from 7 to 9, the polysaccharide OH group receives negative charge leading to repulsive forces formation between adsorbate molecules and adsorbent surface (Memon et al. 2007).
Figure 7

Effect of solution pH on the uptake of pesticides.

Figure 7

Effect of solution pH on the uptake of pesticides.

Close modal

Effect of adsorbent particle size

To assess the effect of particle size on the adsorption process, experiments were carried out on various particle sizes of the adsorbents, ranging from 2 mm to 20 μm, as shown in Figure 8. The results show that the decreases in adsorbent size according to mesh size were from 2 mm to 20 μm, atrazine adsorption capacity was increased from 94 to 99 and 82–90% for AC and BC, respectively. Similar results were also observed for chlorothalanil (82–90 and 81–88%), β-endosulfan (75–83 and 79–86%) and α-endosulfan (74–82 and 75–84%) for AC and BC, respectively. This concludes that the adsorbed amount of pesticides increases positively with a decrease in the mesh size and hence the particle size, which is indeed true as decreasing mesh size has decreasing particle size, which in turn has a higher surface area. The potential reason for this phenomenon is that the surface area enhances when mesh size decreases due to the decrease in particle size. Additionally, the smaller particles of the adsorbents shortens the diffusion paths therefore maximizing the adsorbate's penetration ability into the innermost pores of the adsorbents (Gupta & Ali 2001). Therefore, high adsorption of the pesticides were observed and particle size of 250 mm was preferred for advanced experimental study.
Figure 8

Adsorbent particle size effect on the adsorption of pesticides.

Figure 8

Adsorbent particle size effect on the adsorption of pesticides.

Close modal

Effect of agitation speed

The speed of agitation is an essential parameter and significantly affects the process of adsorption. It ensures the necessary contact of the adsorbate with the adsorbent surfaces during the adsorption process. It also facilitates the adsorbate distribution inside the solution and helps to form the boundary film (Akech et al. 2018). Agitation speed used in this study was 25–200 rpm. The obtained results show a positive correlation among the sorption capability and speed of agitation speed. With the increase in the speed of agitation the pesticides' adsorption capacity onto adsorbent increases as presented in Figure 9. The rate of percent adsorption for atrazine was 87.5–95.9 and 79.1–90.2%, chlorothalanil 79.1–90.2 and 73.3–78.3%, β-endosulfan 75.8–82.5 and 70.0–75.8%, α-endo 74.1–79.1 and 65.8–71.6% for AC and BC, respectively. Most probably the agitation speed has as impact on the boundary layer resistance and mobility of the adsorbate inside the system (McKay 1982; Low & Lee 1997), which ultimately effects the adsorption efficiency of the adsorbent. The results obtained were in good agreement with Akech et al. (2018).
Figure 9

Effect of agitation speed on pesticides' adsorption (25–200 rpm).

Figure 9

Effect of agitation speed on pesticides' adsorption (25–200 rpm).

Close modal

Modeling of the adsorption isotherms

Adsorptions isotherm of the pesticides on the adsorbents (AC and BC) are plotted in Figure 10, which shows that the adsorbents' affinity declines progressively with an increase in the pesticides' concentration. Holistically, both the adsorbents show significant capacity of adsorption for the pesticides. Therefore, it is concluded that the adsorbents textual features were favorable to good capacities of adsorption (Gupta et al. 2002). This proves that the adsorption procedure is completely a surface phenomenon while the nature of interconnection amongst the adsorbate with the adsorbent is somehow physical. The Freundlich and Langmuir models were used to analyze isotherms data and an appropriate model was found by using their linear regression results. Table 3 presents the pesticides Langmuir constant values (qmax and b), Freundlich constant values (Kf and n), and the regression coefficients (R²). The Langmuir model was considered the most suitable because it has correlation coefficients for both AC and BC pesticides' system. Both the adsorbents have high affinity for atrazine as indicated by the b values. Figure 10 represents cf/qe vs cf linear plots for atrazine sorption. This shows that the Langmuir equation is applicable (Figure 11). The order of the pesticides' adsorption onto adsorbents is as follows: atrazine > chlorothalanil > β-endosulfan > α-endosulfan (Table 3). The obtained results were closely related to the study conducted by Suo et al. (2018).
Table 3

Adsorption isotherm model parameters for the pesticides

AC
Langmuir isotherm
Freundlich isotherm
PesticidesTempQmaxbR²KfnR²
Atrazine 30 °C 9.98004 2 × 1016 8.843008 1.183852 0.9466 
Chlorothalanil 30 °C 9.881423 9.88 × 1016 13.23427 1.747335 0.99999 
β-endosulfan 30 °C 9.852217 2.54 × 1014 1.538155 1.337077 0.9972 
α-endosulfan 30 °C 9.090909 2.75 × 1014 3.805397 1.185677 0.9983 
BC
Langmuir Isotherm
Freundlich Isotherm
PesticidesTempQmaxbR²KfNR²
Atrazine 30 °C 10.1833 1.006468 0.9832 34.64176 2.002002 0.9319 
Chlorothalanil 30 °C 9.910803 1.44 × 1015 19.00203 1.515152 0.9934 
β-endosulfan 30 °C 9.689922 3.44 × 1014 8.935112 1.311647 0.9938 
α-endosulfan 30 °C 9.569378 5.23 × 1014 6.6115 1.35318 0.9899 
AC
Langmuir isotherm
Freundlich isotherm
PesticidesTempQmaxbR²KfnR²
Atrazine 30 °C 9.98004 2 × 1016 8.843008 1.183852 0.9466 
Chlorothalanil 30 °C 9.881423 9.88 × 1016 13.23427 1.747335 0.99999 
β-endosulfan 30 °C 9.852217 2.54 × 1014 1.538155 1.337077 0.9972 
α-endosulfan 30 °C 9.090909 2.75 × 1014 3.805397 1.185677 0.9983 
BC
Langmuir Isotherm
Freundlich Isotherm
PesticidesTempQmaxbR²KfNR²
Atrazine 30 °C 10.1833 1.006468 0.9832 34.64176 2.002002 0.9319 
Chlorothalanil 30 °C 9.910803 1.44 × 1015 19.00203 1.515152 0.9934 
β-endosulfan 30 °C 9.689922 3.44 × 1014 8.935112 1.311647 0.9938 
α-endosulfan 30 °C 9.569378 5.23 × 1014 6.6115 1.35318 0.9899 
Figure 10

Adsorption isotherm of pesticides on AC and BC at 25 °C.

Figure 10

Adsorption isotherm of pesticides on AC and BC at 25 °C.

Close modal
Figure 11

Langmuir adsorption isotherm of atrazine on AC and BC at a fixed temperature of 25 °C.

Figure 11

Langmuir adsorption isotherm of atrazine on AC and BC at a fixed temperature of 25 °C.

Close modal

Thermodynamic study

Thermodynamics study is very helpful in the assessment of deviations in the internal energy during the process of adsorption. The parameters of thermodynamics that is Gibbs free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were calculated by the following equations:
(2)
(3)
where R = gas constant (8.314 J/mol K), and T = temperature (Kelvin).

Table 4 summarizes the thermodynamic parameters values at different temperature which signify the adsorption process sensitivity towards temperature. The free energy (ΔG) negative value at every temperature shows the practicability and spontaneity of the adsorption process. It is also identified that the variation in free energy decreases as the temperature increases, exhibiting an enhancement in adsorption with the increase in temperature (Gupta & Ali 2008). The extra release in energy resulted in negative values during the pesticides and the adsorbent surface interaction. Without any doubt, the ΔH value indicated the collective impact of exothermic adsorptions process and endothermic collapse of hydrogen bonds. Endothermic adsorption processes were prevailed by exothermic processing, resulting in negative values of ΔH, supporting the exothermic nature of the process. The obtained entropy positive values (ΔS) indicate amplified randomness at the interface of the solid solution throughout pesticides fixation on the adsorbents active sites and imitates the adsorbent materials affinity towards pesticides (Gupta et al. 2011a).

Table 4

Thermodynamic parameters for pesticides' adsorption

PesticidesΔGΔHΔSR²
AC 288 298 318 328 338    
Atrazine –9813.32 –9813.32 –10686.8 –10977.9 –11269.1 –1428.26 29.1148 0.8723 
Chlorothalanil –10604.5 –10899 –11488.1 –11782.6 –12077.2 –2121.98 29.45318 0.9168 
β–endosulfan –12670.5 –12985.4 –13615.3 –13930.3 –14245.2 –3599.88 31.49509 0.9665 
α–endosulfan –9977.66 –10212.7 –10682.8 –10917.9 –11152.9 –3208.12 23.50534 0.8272 
BC 288 298 318 328 338    
Atrazine –10935.5 –11242.8 –11857.2 –12164.4 –12471.7 –2087.4 30.72272 0.9403 
Clorothalanil –9627.69 –9870.81 –9870.81 –10600.2 –10843.3 –2625.89 24.3118 0.8605 
β–endosulfan –9359.35 –9586.64 –10041 –10268.5 –10495.8 –2813.21 22.72964 0.9449 
α–endosulfan –8015.21 –8208.36 –8594.66 –8787.81 –8980.96 –2452.46 19.31508 0.9522 
PesticidesΔGΔHΔSR²
AC 288 298 318 328 338    
Atrazine –9813.32 –9813.32 –10686.8 –10977.9 –11269.1 –1428.26 29.1148 0.8723 
Chlorothalanil –10604.5 –10899 –11488.1 –11782.6 –12077.2 –2121.98 29.45318 0.9168 
β–endosulfan –12670.5 –12985.4 –13615.3 –13930.3 –14245.2 –3599.88 31.49509 0.9665 
α–endosulfan –9977.66 –10212.7 –10682.8 –10917.9 –11152.9 –3208.12 23.50534 0.8272 
BC 288 298 318 328 338    
Atrazine –10935.5 –11242.8 –11857.2 –12164.4 –12471.7 –2087.4 30.72272 0.9403 
Clorothalanil –9627.69 –9870.81 –9870.81 –10600.2 –10843.3 –2625.89 24.3118 0.8605 
β–endosulfan –9359.35 –9586.64 –10041 –10268.5 –10495.8 –2813.21 22.72964 0.9449 
α–endosulfan –8015.21 –8208.36 –8594.66 –8787.81 –8980.96 –2452.46 19.31508 0.9522 

Effect of temperature

Temperature is the most influential parameter in the field of adsorption. The study of adsorption was performed at 12 μg L¹ of pesticides fixed concentration, neutral pH 7 and at different temperatures of 288, 298, 318, 328 and 338 K, to observe the effect of temperature. Figure 12 expresses the adsorbent sorption capability at various temperatures. It was observed that the percent ratio of sorption enhances positively by a rise in the temperature. The observed values for atrazine were 91.8–99.9 and 79.1–90%, for chlorothalnil 83.3–94.9 and 79.1–92.5%, β-endosulfan 75.7–92.4 and 75.8–90%, α-endosulfan 74.1–90.7 and 73.3–86.6% for AC and BC, respectively. The possible reason for improved capacity of adsorption is the augmented rate of peripheral and intra-particle penetration on to the surface of the adsorbate molecules, due to the small size of the adsorbate making it possible to move easily towards the surface at high temperature (Khan et al. 2020). These results indicate the exothermic nature of the adsorption reaction.
Figure 12

Effect of temperature on the uptake of pesticides (initial concentration: 12 μg L¹ contact time: 1 h, pH 7).

Figure 12

Effect of temperature on the uptake of pesticides (initial concentration: 12 μg L¹ contact time: 1 h, pH 7).

Close modal

Adsorption kinetics

Adsorption kinetics of pesticides on both the activated carbon and biochar were investigated by the two most significant models which are the pseudo-first-order and pseudo-second-order models. Adsorption kinetics were assessed to examine the mechanism of adsorption and are presented by using the below formulas:
(4)
(5)
where Qe = amount of pesticides' adsorption at equilibrium, K1 = constant rate for the pseudo-first-order kinetic model, and K2 = constant rate for the pseudo-second-order kinetic model.
Both the kinetics models, K1 and K2 explain the kinetic of a solid solution systems which is dependent on bi-nuclear as well as mono-nuclear mechanisms respectively, due to the adsorption capacity of adsorbent (Zhao et al. 2018). Table 5 shows the value of kinetics parameter, and regressions coefficient (R²) for pesticides at 12 μg L¹ of fixed initial concentrations. The data of sorption kinetics for pesticides was better simulated for both the kinetic models, suggesting that both the models provided good fit to the kinetics of all the four model pesticides. It was also observed that the value of correlation coefficients (R²) is higher for the pseudo-second-order adsorptions model K2 (>0.999). Similarly, capabilities of adsorption measured by K2 are found proximate to the experimentally observed values. Therefore, the model of Lagergren's pseudo-second-order adsorption is concluded as the utmost appropriate model to explain the pesticides' adsorption kinetics over AC and BC. Figure 13 signifies t/qt linear plot versus time (t) for the adsorptions of pesticides on to AC and BC (time x-axis, t/qt for all pesticides for AC and BC on y-axis) showing that the model of Lagergren's pseudo-second-order is suitably applicable here. The obtained results for the pseudo-second-order model and its significance for removal of pesticides by the adsorbents (AC and BC) is also justified by the previous studies conducted by Suo et al. (2018).
Table 5

Kinetic parameters for pesticides on AC and BC

ACPseudo-second-order
Pseudo-first-order
Adsorbateqe (exp)ciqe (theo)K2R²qe (theo)K1R²
Atrazine 0.51 12 0.574746 0.40583 0.9913 0.554908 –19.5056 0.7661 
Chlorothalanil 0.62 12 0.695265 0.308275 0.9938 0.671456 –16.7911 0.7714 
β-endosulfan 1.46 12 1.539409 1.388093 0.9981 1.519757 –10.055 0.7735 
α-endosufan 2.41 12 2.467917 0.457473 0.9997 2.43546 –5.03434 0.9132 
BC AdsorbatePseudo-second order
Pseudo-first-order
qe (exp)ciqe (theo)K2R²qe (theo)K1R²
Atrazine 0.61 12 0.641437 0.988845 0.9981 0.605144 –17.8772 0.9788 
Chlorothalanil 1.61 12 1.666111 2.078708 0.9993 1.615509 –417.206 0.9727 
β-endosulfan 1.81 12 1.897893 0.591822 0.9985 1.849797 –112891 0.9097 
α-endosufan 2.41 12 2.520797 0.620792 0.9998 2.452784 –7.09002 0.949 
ACPseudo-second-order
Pseudo-first-order
Adsorbateqe (exp)ciqe (theo)K2R²qe (theo)K1R²
Atrazine 0.51 12 0.574746 0.40583 0.9913 0.554908 –19.5056 0.7661 
Chlorothalanil 0.62 12 0.695265 0.308275 0.9938 0.671456 –16.7911 0.7714 
β-endosulfan 1.46 12 1.539409 1.388093 0.9981 1.519757 –10.055 0.7735 
α-endosufan 2.41 12 2.467917 0.457473 0.9997 2.43546 –5.03434 0.9132 
BC AdsorbatePseudo-second order
Pseudo-first-order
qe (exp)ciqe (theo)K2R²qe (theo)K1R²
Atrazine 0.61 12 0.641437 0.988845 0.9981 0.605144 –17.8772 0.9788 
Chlorothalanil 1.61 12 1.666111 2.078708 0.9993 1.615509 –417.206 0.9727 
β-endosulfan 1.81 12 1.897893 0.591822 0.9985 1.849797 –112891 0.9097 
α-endosufan 2.41 12 2.520797 0.620792 0.9998 2.452784 –7.09002 0.949 
Figure 13

Lagergren's pseudo-second-order plot of pesticides on AC and BC at 12 μg L¹ initial concentration.

Figure 13

Lagergren's pseudo-second-order plot of pesticides on AC and BC at 12 μg L¹ initial concentration.

Close modal

Possible adsorption reaction mechanism

The adsorbate diameter is smaller than adsorbents (AC and BC) pore size. Therefore, adsorbate ion can be easily caught on the adsorbent surface in the microspores and mesoporous (Ma et al. 2019). However, simply the surface area of adsorbents cannot determine adsorbate adsorption rate during the process of adsorption, indicating that filling of pores is not the only significant factor in pesticides' adsorption (Zheng et al. 2019) . SEM analysis of the adsorbents before and after adsorption (Figure 3) also better explains the adsorption mechanism. Minor changes were observed in the surface morphology of the adsorbents after adsorption of pesticides as shown in Figure 14, which indicates that molecules of the pesticides partially adsorbed on the adsorbents outside surfaces through the process of diffusion. Then the major portion of pesticides molecules diffuse into the adsorbents pores and adsorb onto the active sites, like carboxylic groups and metaphosphate groups which is also verified from kinetic study.
Figure 14

Proposed adsorption reaction mechanism of atrazine, chlorothalanil, β-endosulfan, and α-endosulfan adsorption by AC and BC.

Figure 14

Proposed adsorption reaction mechanism of atrazine, chlorothalanil, β-endosulfan, and α-endosulfan adsorption by AC and BC.

Close modal

The current study investigated pesticides' adsorption onto AC and BC derived from hardwood by conducting batch experiments. Adsorption of pesticides is strongly dependent upon adsorbent initial concentration, contact time, temperature and solution pH. Under the optimal condition of pH 7, contact time 60 min, agitation speed 180 rpm and 12 μg L¹ of initial pesticides concentration the adsorbents offered commendable capacities of adsorption for removal of model pesticides used. pH was considered as a key factor for removal of pesticides from aqueous solution and therefore it was observed that pesticides were easily decomposed at neutral pH. Adsorption of pesticides on adsorbents includes diffusion and surface adsorption phenomenon, which become more effective with the increase in temperature. Both the textural and surface chemistry of the adsorbents were favorable for the bulky adsorbates greater adsorption capacity. Reducing tendency in the adsorption proficiency of the adsorbents is due to the pesticide solubility. Adsorption equilibrium data follow the Langmuir adsorption isotherm model, while the kinetics data were better described by the pseudo-second-order model. The thermodynamics studies confirm the exothermic, spontaneous and random nature of the experimental process. This study successfully ascertained that both the adsorbents are eco-friendly and economical for the remediation of pesticides in aqueous solution and water containing bodies.

No funding was available for this work

The authors declare that they have no known competing interests that could have appeared to influence the work reported in this paper.

Dr Sardar Khan designed the study. Dr Kalsoom performed laboratory experiments. The first draft of the manuscript was written by Dr Kalsoom. Statistical techniques were applied by Dr Afsar Khan. Figure and graphs were prepared by Mr Zar Ali Khan. Dr Nisar Muhammad was involved in graphing of the manuscript, Dr Fariha Jabeen, Muhammad Ziad contributed in the revision of this manuscript.

All relevant data are available upon request.

The authors declare there is no conflict.

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