This study evaluated the dewatering of excess sludge and the removal of extracellular antibiotic-resistant genes (eARGs) from the treated filtrate by thermal–alkaline pretreatment (TAP) and thermal/persulfate (PS). The optimization of TAP and thermal/PS was investigated during excess sludge dewatering and removal of eARGs via response surface methodology (RSM). The results demonstrated that TAP could effectively decrease the water content of excess sludge (41%) at optimum operating conditions (such as temperature: 88 °C, operation time: 90 min, pH: 11.2). However, the increase in eARGs abundance in TAP-treated filtrate is probably due to the dissolved effluent of the intracellular matter during dewatering. Therefore, TAP-treated filtrate was subjected to thermal/PS, and the removal of eARGs after TAP was explored. The desirability function was used to optimize two kinds of removal efficiencies of eARGs, simultaneously. The optimal pH, persulfate concentration, and reaction temperature were 10.2, 0.039 M, and 75.12 °C, respectively. 6.28 log·copies/mL of tetA and 6.57 log·copies/mL of sulI were removed under the above-mentioned conditions. The process provided efficient dewatering of excess sludge and elimination of eARGs from the filtrate.
TAP significantly enhanced the sludge dewatering efficiency.
The abundance of eARGs increases significantly after TAP.
The desirability function was used to optimize multiple target parameters.
Thermal/PS can effectively reduce the abundance of eARGs, even below the detection limit.
At present, the main process of most wastewater treatment plants (WWTPs) is biological treatment, especially the activated sludge process or its modified processes. However, excess sludge is a by-product of biological treatment processes that take place in WWTPs (Mancuso et al. 2019). It was estimated that municipal sludge production in China reached 40 million tons in 2019 (Wei et al. 2020). Excess sludge contains high-risk pollutants that require proper and safe disposal. In general, sludge treatments can be summarized as disposal (land-fillings and incineration) and reuse (soil remediation). Among them, sludge dewatering is the essential step in excess sludge treatment. According to the landfill standard in China, the water content of sludge needed to be decreased to 60% (Zhang et al. 2020). After the untreated excess sludge was dewatered via a sludge dehydrator, the water content drops to 70–80%, which cannot meet the landfill standard. Therefore, it is necessary to further treat the excess sludge to achieve dewatering efficiency.
Thermal–alkaline pretreatment (TAP) is a common technique for excess sludge treatment, improving the rate of dewatering of excess sludge (Zhong et al. 2015). TAP could avoid operational risks effectively due to high-temperature conditions. Due to the synergistic effects of thermal and alkaline conditions, TAP (<100 °C) requires less energy demand than other high-temperature pretreatment technology (Guo et al. 2017). The TAP uses bases such as NaOH, Ca(OH)2, KOH, and NH3H2O, and NaOH is the most common base used in alkaline pretreatment. NaOH loadings are normally applied in the range of 1–10% g/g (Zheng et al. 2014). TAP could change the cellulosic crystal structure to destroy the ester bonds of lignin–carbohydrate complexes (Tsapekos et al. 2016). Moreover, the disintegration of extracellular polymeric substances (EPSs) and cell walls are recognized as the key limitations to efficient dewatering (Duan et al. 2020). TAP can also destroy cells wall and EPSs, resulting in the release of intracellular water and water combined with EPSs (Guo et al. 2017). However, one major constraint of this process is the significant increase of extracellular antibiotic-resistant genes (eARGs) in the effluent, which may cause a huge potential risk to receiving environment.
ARGs raise serious concern for public health as an important contaminant of emerging concern (CEC) (Pruden et al. 2006). The CECs are associated with an identified harmful health and environmental impact, even though they are present in trace amounts in the environment (Khan et al. 2022). Bacteria can acquire ARGs via horizontal gene transfer (HGT), which can be summarized by conjugation, transduction, and transformation (Lu et al. 2020a). A high abundance of eARGs remained in the sludge filtrate after the dewatering process, which could disseminate among the microbial community through the transformation of HGT frequently (Blokesch 2016). The excess sludge is not disposed of properly, which will bring huge pressure to the transfer of ARGs in the receiving environment.
Advanced chemical oxidation processes (AOPs) were used as a powerful source of reactive radicals to treat intracellular ARGs (Michael-Kordatou et al. 2018) and extracellular ARGs (Krzeminski et al. 2020). Among them, persulfate (PS) is the common oxidant, which has a high oxidizing ability (Ran & Li 2020). The oxidant is activated to produce highly reactive radical species, such as hydroxyl radical and sulfate radical (Hilles et al. 2016). Also, the high temperature is an effective way to activate reactive radical species (Su et al. 2019). The optimization of the TAP and thermal/PS was studied (Campo et al. 2018; Pourehie & Saien 2019). Compared with the conventional optimization method, response surface methodology (RSM) needs fewer experiments to optimize the process parameters (Xie et al. 2016).
Four objectives of this study were as follows: (a) to investigate the efficiency of TAP in dewatering from excess sludge, (b) to investigate the impact of TAP on eARGs, (c) to explore the degradation efficiency of eARGs by thermal/PS (AOP), and (d) to determine the optimal reaction condition of the TAP and thermal/PS via RSM. This study may contribute to understand the optimal dewatering process condition and the fate of eARGs during excess sludge dewatering, which also provides guidance for the application of TAP for dewatering rate and thermal/PS process for the removal of eARGs.
MATERIALS AND METHODS
Collection of samples
The sludge was obtained from the biological reaction tank of a reclaimed water reuse system (RWRS) (Supplementary material, Figure S1). The biological treatment process of the RWRS was an anoxic–membrane bioreactor (MBR). The capacity of the RWRS was 1,200 m3/day, and the hydraulic retention time of the anoxic tank and MBR tank was 3 and 7 h. The sludge had a solid concentration of 9,200–11,200 mg/L. The sludge samples were stored in pre-cleaned aluminum boxes, brought to the laboratory, and stored at −20 °C.
Optimization of TAP conditions and determination of moisture content
Excess sludge was heated in an electric heater in a 1-L tank until the desired temperature is reached. The sludge was added to the NaOH solution (20 g/L) until reaching the desired pH (10, 11, 12) and stirred by a blender. NaOH is widely used in chemical experiments, and has the commonness of alkali. Also, it can react with a variety of acids and organic matter. RSM was performed to optimize the experimental conditions.
Optimization of thermal/PS conditions
Excess sludge was treated by AOPs in a reactor of height 450 mm and diameter 400 mm (Supplementary material, Figure S2). The reaction temperature was maintained at specified temperatures (70, 80, and 90 °C). A 1,000 mL of the supernatant sample with different concentrations of PS (0.02, 0.03, and 0.04 M) under different conditions was injected into the reactor and mixed using a magnetic stirrer at 500 rpm. The important impact factors of the experiment were the initial solution pH, the concentration of PS, and reaction temperature (Furman et al. 2010; Asaithambi et al. 2017). Therefore, these three parameters were selected as independent variables and the removal efficiency of ARGs was selected as the dependent variable.
DNA extraction and quantitative polymerase chain reaction
All samples were placed in a refrigerator at 4 °C and the supernatant was collected. The residual solid and cells were removed from the supernatant by filtering through a 0.22 μm membrane. The extracted DNA in the filtrate was collected by precipitation (Zhang et al. 2018). Three hundred thirty millilitres (330 mL) of filtrate was added to a mixed solution containing 726 mL of absolute ethanol and 33 mL of 3 M sodium acetate solution, and the mixed solution was placed in a refrigerator at −20 °C for more than 12 h to precipitate the extracellular free DNA. The precipitates were obtained by centrifuging at 10,000 × g for 10 min and the supernatants were discarded, followed by air drying for 10 min. DNA extraction from dry precipitates was done according to the method followed by PowerSoil DNA Isolation Kit (Mo Bio, USA). The concentration of the extracted DNA was examined using NanoDrop 2000 (Thermo Fisher, USA).
Quantitative determination of target genes used the SYBR Green I method by a real-time PCR instrument (Bio-Rad CFX96 Touch, USA). The volume of the qPCR mixture was 20 μL, including 10 μL of SYBR Premix Ex Taq (Takara, Dalian, China), 2 μL of template DNA, 0.4 μL of each primer, and 7.2 μL of ddH2O. The primers for the ARGs quantification are listed in Supplementary material, Table S1. The reaction procedure was divided into pre-denaturation, denaturation, annealing, and extension. Standard curves were constructed based on the past research (Zhang et al. 2018). The standard plasmid was diluted in a 10-fold gradient. The correlation coefficients of the standard curves in this study were all >0.99 with the amplification efficiencies of 85–110% (Bai et al. 2012). All samples in the qPCR analysis were performed in triplicate.
Experiment design and data analysis
The treated supernatant was subjected to advanced oxidation to achieve the efficient removal of ARGs in the sludge. The experiment was optimized by the RSM in Box–Behnken Design (BBD), which was an effective technique to analyze experiments, and interpreted by the analysis of variance (ANOVA) (Xie et al. 2016). Due to the fitting error of the RSM experiment, data were evaluated by ANOVA to verify the significance of the particular model (Yusup et al. 2014).
In the designed experiment, three parameters were selected as the independent variables in the TAP-thermal/PS and the dewatering rate of sludge and removal efficiency of tetA and sulI were selected as their responses. The range and levels of the independent variables determined in the experiments are given in Supplementary material, Table S2.
In general, there were three types of methods to evaluate the significance and reliability of the model. Firstly, the P and F values indicate the influencing items on the response (Inayat et al. 2020). Secondly, the regression coefficients (R2) imply the reliability of predicted values (Shahbaz et al. 2017). Thirdly, the lack of fit shows the systematic error (Raheem et al. 2018).
Establishment of desirability function
RESULTS AND DISCUSSION
Analysis of variance
Supplementary material, Table S3 shows the BBD with three factors in three levels, the experimental and predicted results of TAP and thermal/PS. Three important process variables were evaluated for the dewatering rate (pH, temperature, and time) and removal efficiency of eARGs (pH, concentration, and temperature) in TAP and thermal/PS. The data show that the predicted value is in good agreement with the experimental value.
The regression analysis of two process variables was carried out. The values of coefficients and the significance levels are shown in Supplementary material, Table S4. It could be seen that, for the TAP, the linear coefficients of reaction time (), temperature (), and the interaction coefficient of pH with reaction time () as well as the quadratic coefficients were significant for the dewatering rate at a level of less than 5%. For the thermal/PS to remove tetA, the linear coefficients ,the interaction coefficient , and the quadratic coefficients , were the significant variables. For the thermal/PS to remove sulI, the linear coefficients ,the interaction coefficient , and the quadratic coefficients were the significant variables. The result indicated that significant parameters affect the removal efficiency of ARGs.
On the basis of the coefficients in Supplementary material, Table S4, the dewatering rate and the removal efficiencies of eARGs could be explained by independent variables. Also, the models are as follows:
The data show that the predicted value is in good agreement with the experimental value.
To certify that the model will be suitable for the experimental data, it was necessary to test whether the model shows significant regression or a non-significant lack of fits (Bezerra et al. 2008). There were three types of methods to evaluate the significance of the models. The ‘P-value’ of 0.0001, 0.0039, and 0.0058 imply a good correlation between the models. The three models have high regression coefficients (R2 = 0.9823, 0.9227, and 0.9122, respectively) as shown in Supplementary material, Table S5, which implies that up to 91.22% of the variations for dewatering rate and removal efficiency of eARGs could be explained by the independent variables. The ‘Lack of Fit’ P-value of 9.73–36.66% suggests that there was only 9.73–36.66% chance that a ‘Lack of Fit’ of this large could occur due to noise. All those data indicated that those three models were of great significance and were suitable for fitting the relationship between the dewatering rate or removal efficiencies of eARGs and the three independent variables.
Application of TAP for dewatering
Determination of the TAP optimal conditions
The water of the sludge included intracellular water and water with combined polymeric substances (EPSs). From these results, the cell wall structure of the bacteria was destroyed by TAP and it increased the release of intracellular water and organic matter. TAP technology can destruct the structure of EPSs to release cell-associated water. Moreover, the cell wall can be destroyed more easily with high temperatures (Li et al. 2017). The addition of alkali caused accelerated decomposition of the cell walls. At high pH values, solubilization of EPSs leads to several reactions in the cell wall to release intracellular water (Toutian et al. 2020a). The orthophosphate bonds of phospholipids in the cell wall were easily destroyed at the combined conditions of thermal and alkali (Toutian et al. 2020b). The dewatering rate by combined thermal–alkaline was higher than the simple thermal treatment (Li et al. 2012).
The relationship between the dewatering rate and the degree of sludge cracking
TAP could rupture the cell and convert some matter from the intracellular state to the extracellular state, and the content of organic matter in the filtrate increases accordingly. It could be seen from Supplementary material, Figure S3(a) that the soluble chemical oxygen demand (SCOD) in the untreated sludge is 120 mg/L. Under TAP optimum conditions, SCOD increases from 120 mg/L in the initial state to 3,320 mg/L at 100 min.
The previous study showed that the dewatering rate was significantly related to the degree of sludge cracking. The SCOD could reflect the degree of sludge cracking, and the degree of sludge cracking can be calculated by Equation (2). As was shown in Supplementary material, Figure S3(b), the sludge dewatering increases with the degree of sludge cracking from 20 to 80 min under optimum conditions of TAP. But the trend of sludge dewatering was opposite to the degree of sludge cracking from 80 to 100 min. The dewatering rate reached 40.14% at 80 min. These results suggest that sludge cracking played a crucial role in dewatering. Guo et al. (2017) reported that TAP was helpful for sludge cracking, and it was an effective method for dewatering of sludge. With the cell wall being ruptured, EPS accumulated in the sludge, which leads to a dewatering capacity decrease. It was found that the degree of sludge cracking was useful for sludge dewatering (Ruiz-Hernando et al. 2014), but massive sludge cracking also had negative effects on sludge dewatering (Lu et al. 2019).
The fate of eARGs and iARGs during TAP
|.||tetA .||tetC .||sulI .||sulII .||ermB .||dfrA1 .||dfrA13 .|
|.||tetA .||tetC .||sulI .||sulII .||ermB .||dfrA1 .||dfrA13 .|
*P < 0.05.
**P < 0.01.
***P < 0.001.
Supplementary material, Figure S4 shows that iARGs are transformed into eARGs as the degree of sludge cracking. The abundance of eARGs was the highest when TAP was conducted for 40 min, and the abundance of eARGs remained stable after 40 min of the TAP. TAP has a significant effect on bacterial disintegration (Zhong et al. 2015), and a large amount of eARGs and EPSs was produced after the TAP (Wei et al. 2020). The removal efficiency of eARGs was ineffective during the TAP because of the recovery of bacterial DNA (Suss et al. 2009). The study shows that the total removal efficiency of ARGs could be improved to 52.50% using alkaline and thermal pretreatment (Wang et al. 2019).
Application of thermal/PS to reduce eARGs
The fate of eARGs, intI1, and 16S rDNA during thermal/PS
Respective roles of pH, PS concentration, and reaction temperature in degrading intI1 during thermal/PS treatment
Table 2 summarizes the rmax, ks, and c0 parameters derived from experimental data, and Figure 4 plots the fitting curve using Equation (6). The fitting curves were excellent and with Pearson's R2 value of 0.999 for pH 3, 0.997 for pH 7, and 0.993 for pH 11.
|.||rmax .||ks .||c0 .|
|.||rmax .||ks .||c0 .|
When pH and reaction temperature were stable, intI1 removal efficiency increased with PS concentration. It was caused by the increasing oxidizing radical concentration by increasing PS concentration, and oxidizing radicals were directly related to the degradation of intI1. A significance relationship was observed between the intI1 removal efficiency and the initial PS concentration (Hu et al. 2020). When the concentration of PS was higher than 0.01 M, the removal rate of intI1 remained stable with the concentration increases.
Determination of the optimal conditions
Figure 5 indicates that the effect of PS concentration changes on removal was more critical than others. The optimum process parameters for the removal efficiency of sulI and tetA (pH = 10.24 and 10.22, the temperature was 75.56 and 78.94 °C, PS concentration was 0.038 and 0.040 mg/L) were obtained and their removal efficiency were 6.30 and 6.48 log·copies/mL, respectively.
It was notable that the removal efficiency of eARGs in this study was much more significant than in previous studies. For example, Ahmed et al. (2020) reported that the photo-Fenton process with conditions of 0.5 mM of (2.8 mg/L) and 10 mM of H2O2 (170.7 mg/L) would decrease in 6.0 log of eARGs. Yoon et al. (2017) used a thermal/H2O2 process under the conditions of 60–90 mJ/cm2 of thermal fluence with 10 mg/L of H2O2 that could degrade 4.5 logs of eARGs at pH 7. Compared with previous studies, thermal/PS in this study was more promising than the photo-Fenton process and thermal/H2O2 for the removal of eARGs. The higher degradation efficiency of eARGs might be due to the strong oxidation of PS.
The present study focused on the optimization of the dewatering process, while the fate of eARGs during the TAP and thermal/PS process was also examined. TAP and thermal/PS were proved to be effective for the dewatering of sludge and removal of eARGs in the filtrate, respectively. The main conclusions are given as follows.
The TAP was found to be efficient in dewatering and resulted in the increase in eARGs in the filtrate. The optimal TAP condition for the dewatering rate was obtained by the RSM. The dewatering rate under optimized conditions (pH: 11.2, T: 88 °C, time: 90 min) was 41%. The absolute abundances of eARGs in sludge using TAP increased by 1.06–1.90 log·copies.
The application of thermal/PS as a post-treatment of the TAP was found to be capable of eliminating eARGs in the filtrate. The removal efficiencies of tetA and sulI under optimized conditions (pH: 10.2, conc.: 0.039 M, temp.: 75.12 °C) were 6.28 and 6.57 log·copies/mL, respectively.
This study was supported by the project (No. 51678003) granted by the National Natural Science Foundation of China, project (No. 2022C02038) granted by the Science and Technology Project of Zhejiang Province, and project (No. RC2224) granted by the Science and Technology Planning Project of Zhejiang Water Resources Department.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.