Effective Removal of Acid Dye in Synthetic and Silk Dyeing Effluent: Isotherm and Kinetic Studies

Here, we propose a low-cost, sustainable, and viable adsorbent (pine tree-derived biochar) to remove acid dyes such as acid violet 17 (AV), which is used in the silk dyeing industry. As a case study, the AV removal process was demonstrated using synthetic effluent and further as a proof of concept using real dye effluent produced from the Sirumugai textile unit in India. The pine tree-derived biochar was selected for removal of aqueous AV dye in batch and fixed-bed column studies. The adsorbent material was characterized for crystallinity (XRD), surface area (BET), surface morphology and elemental compositions (SEM–EDX), thermal stability (TGA), weight loss (DGA), and functional groups (FTIR). Batch sorption studies were performed to evaluate (i) adsorption at various pH values (at pH 2 to 7), (ii) isotherms (at 10, 25, and 35 °C) to assess the temperature effect on the sorption efficiency, and (iii) kinetics to reveal the effect of time, adsorbent dose, and initial concentration on the reaction rate. After systematic evaluation, 2 g/L biochar, 25 mg/L AV, pH 3, 40 °C, and 40 and 360 min in a completely mixed batch study resulted in 50 and 90% dye removal, respectively. The isoelectric point at pH 3.7 ± 0.2 results in maximum dye removal, therefore suggesting that monitoring the ratio of different effluent (acid/wash/dye) can improve the colorant removal efficiency. The Langmuir isotherm best fits with the sorption of AV to biochar, provided a maximal dye uptake of 29 mg/g at 40 °C, showing that adsorption was endothermic. Fixed-bed studies were conducted at room temperature with an initial dye concentration of 25 and 50 mg/L. The glass columns were packed with biochar (bed depth 20 cm, pore volume = 14 mL) at an initial pH of 5.0 and a 10 mL/min flow rate for 120 min. Finally, the regeneration of the adsorbent was achieved using desorption studies conducted under the proposed experimental conditions resulted in 90–93% removal of AV even after five cycles of regeneration.


Dyeing process of soft silk and Kovai Kora Sarees
For the dying of silk filaments, acid dyes solutions are used in big vessels. The acid dyes contain sodium salt from sulfonic acid what makes them highly soluble in water 1 . In a mixture of water and acetic acid 2 , the NH 2 groups of the silk fibers are protonated to give a positive charge of NH 3 + , allowing the formation of ionic interactions between the fibers the negative dye charge. Van-der-Waals bonds, dipolar bonds, and hydrogen bonds are also formed between the dye and the fiber 3 . For the dyeing, acid dye powder is dissolved in water, followed by soap and washing soda to remove the sericin 4 better. Sericin is a protein present on the surface of the filament of the silk and is responsible for its stiffness/ harshness. Thus, removing it makes the silk softer 5 .

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Then the dye bath temperature is raised to boil. At boiling, the fiber dyeing is continued for 5 to 10 minutes until the required shade is attained. However, to fix the dye on the surface of the silk fiber, the dyed silk skein is immersed in an acid bath with water: acetic acid ratio of 2:1.
In acidic solution, fixation of the dye molecules onto the silk by ionic bonds is enhanced due to the electrostatic attractions 6 . After the dye fixation with an acetic acid solution, the fibers are washed with plain water to remove all the dye and acid excess and hung to dry 7 ; then, the dried material will be transferred to weaving on the handloom. One of the house dyers' main challenges is the lack of a proper textile wastewater effluent collection and treatment system.
The used dye solution is discharged to the drainage or environment to groundwater or the river and may cause severe environmental damage and health problems.

Real Effluent Characterization
Batch experiments were conducted with actual effluent samples from house dyers. The dye effluent can be divided into three categories: 1. Dyeing effluent: Water remains after the dyeing process and contains dissolved acid dye powder, soap, washing soda, and sericin from the silk fibers that make it a bit viscous.
2. Acid wash effluent: Water that remains after the fixation process. It contains acetic acid, a small amount of acid dye that is released from the dyed silk and sericin.
3. Wash water effluent: After the acid wash, the silk was washed with plain water. Hence everything that was in the acid wash can also be in this effluent. Table S1 shows the real dye effluent properties consist of TDS and TSS (25,660 and 22,460 mg/L), respectively. However, increased TDS is due to high dye molecules and inorganic salts, and high TSS is probably due to sericin protein from the silk and small fibers that are released into the water during the dyeing. The UV absorbance at 254 nm is the highest (0.56 OD) for dyeing effluent because of the high presence of dye molecules which are organic molecules.

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Also, the absorbance at 280 nm is the highest for this effluent, indicating a high sericin protein 8 . The dyeing process is done at water boiling temperature in soap and sodium carbonate (alkaline hot water). These conditions cause a degumming process, which means the sericin is separated from the silk fibers and dissolves in the water; the released sericin can also contribute to high COD in the dyeing effluent.  Table S1 also presents the amount of effluent generated on an average per day from each household. The exact amount will vary depending on the quantity of dyed material per day, but approximately 500 to 600 L will be discharged to the environment /day/ household (personal communication). In the sirumugai, 80 to 100 households practice dyeing, resulting in 40,000 to 60,000 L of contaminated effluent discharged to rivers and lakes daily (personal communication). Figure S shows the dyeing process, the different dye effluents, and the discharge to the environment.  The electric conductivity of the bulk aqueous solution, B, is insufficient to represent the conductivity within the porous plug of the biochar sample. Material conductance, e, but also the ionic conductance within the porous biochar particles, p 10 , contribute to the overall conductance such that B in Eq. 1 needs to be replaced by (2) Unfortunately, the contributions e and p remain unknown.
( Figure S4) also shows a significant difference between the isoelectric points of straw-based biochar and our biochar sample derived from a pine tree. Again the different types of biochar samples may account for the discrepancy in the IEP. Furthermore, grinding the biochar sample created a new surface area, which is likely more reactive than granular biochar's aged surface.
The lower IEP and thus the higher acidity of straw-based biochar would account for the enhanced reactivity. Note that the surface area increases enormously due to the small particle size required for ELS ( 1 μm). We have also ground a sample of the pine tree-based biochar to prepare a dispersion in deionized water for a comparative ELS measurement (Litesizer 500).
As shown in Figure S.4 the result compares well with the zeta potential of straw-based biochar and confirms the streaming potential method's restrictions. Figure S4: Comparison of apparent zeta potential for biochar derived from pine tree based on streaming potential measurement (SP) with the zeta potential for straw-based biochar determined by electrophoretic mobility measurement (ELS).

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The effect is higher at high streaming potential, which occurs at higher pressure difference, and decreases as the streaming potential reduces. Ideally, the streaming potential coupling coefficient dUstr/dp should determine at the no-flow condition. However, this is impossible since the streaming potential is inhibited in the absence of liquid flow.
The non-linear dependence of the streaming potential on the pressure gradient represented by a parabolic polynomial fit (power 2 or power 4 depending on the pressure range considered for the analysis of the pressure ramp) and determined the streaming potential coupling coefficient as the slope of this parabolic curve at the extrapolated p = 0 mbar. In the example shown in Figure S.3, this approach gives a zeta potential of  = -16.6 mV, which is 88% higher than the zeta potential obtained from the erroneous linear fit of the measured data.

Responsive Surface Methodology (RSM) for dye removal by biochar:
Response surface methodology (RSM) is an effective tool for optimizing the process when a combination of several independent variables and their interactions affect desired responses 1,2 .
In using the RSM approach, batch runs were conducted in CCD model designed experiments S11 to visualize the effects of independent factors on the response and the results along with the experimental conditions. A five-level CCD was performed to evaluate the influence of the 4 variables on the dye removal efficiency. Table S3 lists the process control variables and their limits. The center points are used to determine the experimental error and the reproducibility of the data. The independent variables are coded based on (−1, +1) interval where the low and high levels are coded as−1 and +1, respectively. Table S4 shows the experimental design points consisting of 2n factorial points with 2n axial points and Nc central points and the test results for the response variables. The axial points are located at a distance ofαfrom the center and make the design rotatable. In this study,α value was fixed at 2 (rotatable). This method is suitable for fitting a quadratic sur-face, and it helps to optimize the effective parameters with a minimum number of experiments and analyze the interaction between the parameters. Efficiency in order to evaluate the influence of operating parameters on the removal efficiency of AV, four main factors were chosen: Initial dye concentration (g/L) (X 1 ), pH (X 2 ), a dose of adsorbent (g/L)(X 3 ) and sorption time (min)(X 4 ). The  implying that model is relevant and significant. In this case, X 1 , X 2 , X 3 , X 4 , X 1 2 , X 2 2 , X 3 2 , X 4 2 , S14 X 3 X 4 are significant model terms.

Regeneration cycle
Biochar mass (g) Figure S12: Biochar mass after each regeneration. Comparison between biochar and GAC after 30 min and 60 min of treatment.
Recovery of sericin and filtration of TSS particles from the textile wastewater effluent Reuse of the recovered sericin for cosmetics/pharmaceuticals products pH reduction for the biochar adsorption Dye removal by biochar in column or batch-adsorption design pH adjustment of the effluent if the pH is too low Biochar regeneration with ethanol and sonication followed by water rinsing Figure S15: Schematic chart of the suggested textile dye wastewater adsorption system.