A biophysiological perspective on enhanced nitrate removal from decentralized domestic sewage using gravitational-flow multi-soil-layering systems

Song, Pei; Huang, Guohe; Hong, Yongyuan; An, Chunjiang; Xin, Xiaying; Zhang, Peng

doi:10.1016/j.chemosphere.2019.124868

Cited by 64 publications

(37 citation statements)

References 50 publications

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“…However, the preponderant classes in the S4 sample were Alphaproteobacteria (29.37%), Gammaproteobacteria (90.84%), Bacteroidia (1.87%), Deltaproteobacteria (4.17%), Bacilli (8.34%) and Clostridia (0.014%) [2,49,59]. It was evident that the distribution of the main classes in these seven samples was significantly different.…”

Section: Bacterial Diversity and Community Compositionmentioning

confidence: 92%

“…In recent years, several species belonging to the genera Thiobacillus, Bacillus and Thauera have been suggested to play an important role in antibiotic CIP and removal of nitrates [56]. Notably, Thiobacillus and Thauera can transfer electrons directly from the carbon electrode and promote nitrate reduction [16,49,59]. The richness and abundance of Pseudomonas (55.04%), Thiobacillus (28.88%) and Thauera (6.68%) [24,64] were enriched in the 3D-BER system.…”

Section: Bacterial Diversity and Community Compositionmentioning

confidence: 99%

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Effect of the C/N Ratio on Biodegradation of Ciprofloxacin and Denitrification from Low C/N Wastewater as Assessed by a Novel 3D-BER System

et al. 2020

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Emerging pollutants in the form of pharmaceuticals have drawn international attention during the past few decades. Ciprofloxacin (CIP) is a common drug widely found in effluents from hospitals, industrial and different wastewater treatment plants, as well as rivers. In this work, the lab-scale 3D-BER system was established, and more than 90% of the antibiotic CIP was removed from Low C/N wastewater. The best results were obtained with the current intensity being taken into account, and a different C/N ratio significantly improved the removal of CIP and nitrates when the ideal conditions were C/N = 1.5–3.5, pH = 7.0–7.5 and I = 60 mA. The highest removal efficiency occurred when CIP = 94.2%, NO3−-N = 95.5% and total nitrogen (TN) = 84.3%, respectively. In this novel system, the autotrophic-heterotrophic denitrifying bacteria played a vital role in the removal of CIP and an enhanced denitrification process. Thus, autotrophic denitrifying bacteria uses CO2 and H2 as carbon sources to reduce nitrates to N2. This system has the assortment and prosperous community revealed at the current intensity of 60 mA, and the analysis of bacterial community structure in effluent samples fluctuates under different conditions of C/N ratios. Based on the results of LC-MS/MS analysis, the intermediate products were proposed after efficient biodegradation of CIP. The microbial community on biodegrading was mostly found at phylum, and the class level was dominantly responsible for the NO3−-N and biodegradation of CIP. This work can provide some new insights towards the biodegradation of CIP and the efficient removal of nitrates from low C/N wastewater treatment through the novel 3D-BER system.

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Section: Bacterial Diversity and Community Compositionmentioning

confidence: 92%

Section: Bacterial Diversity and Community Compositionmentioning

confidence: 99%

Effect of the C/N Ratio on Biodegradation of Ciprofloxacin and Denitrification from Low C/N Wastewater as Assessed by a Novel 3D-BER System

et al. 2020

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“…Due to large differences of the water quality and quantity between rural and urban domestic wastewater, urban sewage treatment technology is not well applicable to the rural area in terms of both technology and economy [3]. The multi-soil-layering [4] system is a kind of soil purification sewage technology [5] emerging in Japan in the 20th century, which can be used as a good decentralized treatment type [6] of domestic sewage, due to its easy clogging, small space requirement, and low hydraulic loading rate. The MSL system is mainly composed of water-permeable layer and soil mixed layers [7], which mainly removes heavy metals in domestic sewage [8], chemical oxygen demand (COD), ammonia nitrogen (NH4 + -N), total nitrogen (TN), total phosphorus (TP) [9] and other pollutants through physical adsorption, exchange, and biological decomposition.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on the Treatment of Rural Domestic Wastewater Using the Multi-Soil-Layering System Filled with Sludge-Based Biochar

Wang¹,

Zhang²,

Guo³

et al. 2021

ACSM

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This paper aims to improve the treatment effect of the multi-soil-layering system (MSL) on rural domestic wastewater. For this, sludge-based biochar materials were selected in the experiments to study its impacts on the treatment of rural domestic wastewater using the MSL. The comparative experiments were conducted for the three MSL systems filled with different materials: the sludge-based biochar (a), wood chips (b), and charcoal (c). The results showed that when the sludge-based biochar material was used as a filler, the removal effect of COD, NH4+-N, TN, TP is better than that of wood chips and charcoal, and the removal rates were 80%, 90%, 65% and 92%, respectively, meeting the Grade A standard specified in the Hebei Province Rural Domestic wastewater Discharge Standard (DB13/2171-2015); hydraulic loading rates (HLRs) have a great impact on the removal of pollutants, and the pollutant indicators in the system (a)re affected by the HLRs in different degrees, i.e., NH4+-N>TP>COD>TN from high to low; considering the treatment efficiency and pollutant removal effect, the HLRs should be selected between 800L/(m2·d) and 1200L/(m2·d). It’s concluded finally that the sludge-based biochar material can strengthen the removal effect of the MSL system. This study is of theoretical value for the further research on MSL system and resource utilization of the sludge.

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“…For example, Zhang et al (2019) used hierarchical cluster analysis to evaluate the performance of the MSL system. Song et al (2020) combined factorial analysis and multiple linear regression (MLR) to study the effects of operating factors on microbial characteristics and the microscopic mechanism. Other studies have developed a stepwise cluster inference model to estimate pollutant removal in MSL systems (Song et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…For these reasons, we have investigated the removal efficiency of FCs from domestic wastewater by a two-stage MSL (MSL-TS) system and predicted their concentrations in the treated water. As documented in recent studies (Song et al, 2018(Song et al, , 2020, computer-based simulation is a practical method for predicting the performance of the MSL system. Computer-based simulations help to model natural systems and have become a useful tool to understand the behavior of the wastewater treatment systems.…”

Section: Introductionmentioning

confidence: 99%

Neural network and cubist algorithms to predict fecal coliform content in treated wastewater by multi‐soil‐layering system for potential reuse

et al. 2020

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This study aims to find the most accurate machine learning algorithms as compared to linear regression for prediction of fecal coliform (FC) concentration in the effluent of a multi‐soil‐layering (MSL) system and to identify the input variables affecting FC removal from domestic wastewater. The effluent quality of two different designs of the MSL system was evaluated and compared for several parameters for potential reuse in agriculture. The first system consisted of a single‐stage MSL (MSL‐SS), and the second system consisted of a two‐stage MSL (MSL‐TS). The concentration of FC in the effluent of the MSL‐TS system was estimated by three machine learning algorithms: artificial neural network (ANN), Cubist, and multiple linear regression (MLR). The accuracy of the models was measured by comparing the real and predicted values. Significant (p < .001) improvements were noted for the removal of pollutants by the MSL‐TS system compared with the MSL‐SS system. Overall, the water quality parameters investigated complied with FAO irrigation standards. The predictive performance of the models has been compared and evaluated using several metrics. The results revealed that the ANN model yielded a superior predictive performance (R2 = .953), followed by the Cubist model (R2 = .946) and the MLR technique (R2 = .481). Based on the accurate model (ANN), the degree of influence of each predictor was investigated, and the results show that total suspended solids and pH have proved to be more useful for predicting FC concentrations.

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A biophysiological perspective on enhanced nitrate removal from decentralized domestic sewage using gravitational-flow multi-soil-layering systems

Cited by 64 publications

References 50 publications

Effect of the C/N Ratio on Biodegradation of Ciprofloxacin and Denitrification from Low C/N Wastewater as Assessed by a Novel 3D-BER System

Effect of the C/N Ratio on Biodegradation of Ciprofloxacin and Denitrification from Low C/N Wastewater as Assessed by a Novel 3D-BER System

Experimental Study on the Treatment of Rural Domestic Wastewater Using the Multi-Soil-Layering System Filled with Sludge-Based Biochar

Neural network and cubist algorithms to predict fecal coliform content in treated wastewater by multi‐soil‐layering system for potential reuse

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