Industrial Wastewater Treatment Plant Research Articles

Treatment of Endocrine Disrupting Chemicals from Organized Industrial Zone Wastewater Treatment Plant Effluents by Ozone-Based AOPs: Cost and Toxicity Assessments

Treatment of Endocrine Disrupting Chemicals from Organized Industrial Zone Wastewater Treatment Plant Effluents by Ozone-Based AOPs: Cost and Toxicity Assessments

Accurate identification of sludge contamination sources by classification-based PMF and machine learning with consideration of sewer network distribution differences

The application of source identification such as PMF for large-scale pollution source analysis frequently produces ambiguous outcomes. In this study, we utilized a classification-based method to accurately track key pollution sources in the sludge. In the study, we categorized the wastewater treatment plants into two groups: T1 and T2, according to the pipeline network. T1 sewage treatment plants are the main sewage plants in urban areas, covering a large area and connected to industrial wastewater treatment plants for secondary treatment. T2 sewage treatment plants are typically smaller in size and usually responsible for treating sewage in rural or township areas. The PMF analysis indicates that industrial pollution sources contribute 3.4 times more to T1 sludge than to T2 sludge, making industrial pollution the primary factor causing the disparity. The application of Random Forest and Adaboost based on pollutant concentrations for classification and fitting of sludge resulted in the identification of the main pollutants: Zn, Cu, Ni, and Cyanide, which align with characteristic pollutants from the electroplating industry. The GIS analysis shows a significant correlation between the distance of wastewater treatment plants with abnormal environmental risk and electroplating industrial parks, all within a 20 km radius. Indeed, when conducting large-scale pollution source identification studies, utilizing classification-based analysis can effectively improve the accuracy of pollution source identification, leading to more valuable analysis results.

Simultaneous production of polyhydroxybutyrate and biogas from paper mill sludge through sodium citrate-mediated disperser-induced phase separated pretreatment

Paper mill waste activated sludge is an excess sludge produced from the paper industry wastewater treatment plant. Because of the bulk nature, its disposal concerns both economic and environmental perspectives. However, it widely consists of organic components and is considered a major attraction for its valorization to produce bioenergy and valued products. During the bioenergy and valued product retrieval, the enzymatic hydrolysis got hampered due to the presence of exopolymeric substances and thus require proper pretreatment prior to the product recovery. The application of two different phases of pretreatment by removing the flocs in the first step and then followed by the cell disintegration by mechanical means helps in enhancing the organics efficiently in soluble phase. In this study, the upshot of sodium citrate mediated disperser disintegration on sludge from a paper mill was explored enhance enzymatic hydrolysis. Firstly, the floc deaggregation results at 0.05 g sodium citrate per g suspended solid with the maximum floc deaggregation degree of 89 %. Further, the consequence of disperser disintegration on the floc deaggregated sludge sample shows solid reduction and solubilization of 12.5 % and 17.5 %, respectively, higher than the disperser alone disintegration (9.57 % and 13.4 %). The anaerobic biodegradability assay shows the maximum biogas production of 174.3 mL/g of chemical oxygen demand while utilizing pretreated settled sludge as substrate. There was no accumulation of polyhydroxybutyrate using pretreated sludge supernatant. Thus, the phase-separated pretreatment by sodium citrate-induced disperser pretreatment is a suitable approach for enhancing hydrolysis during bioenergy recovery.

Detailed organic characterization of process water to evaluate reverse osmosis membrane fouling in industrial wastewater treatment

One of the major waste streams within the oil and gas (O&G) industry is produced and process water generated during hydrocarbon production and treatment, respectively. In gas production facilities, process water typically has lower salinity (i.e., <10,000 mg/L) which present opportunities for these wastewaters to be treated for beneficial reuse applications via advanced water treatment technologies, such as reverse osmosis (RO) membranes. One of the key challenges for RO membranes application to industrial wastewater treatment is fouling which is frequently attributed to the soluble organics present in the water and/or associated with field chemicals. In this study, a detailed organic characterization methodology, using liquid chromatography with organic carbon detector (LC-OCD) was applied to characterize the organics on a real process water collected from industrial wastewater treatment plant at a gas production facility. Additionally, a rigorous bench-scale testing procedure was implemented to assess the performance of a full-scale RO system with and without activated carbon filter (ACF) pretreatment, making this study the first one to apply LC-OCD methodology on real wastewater to evaluate the fouling of RO membranes deployed at an industrial treatment plant. Bench-scale RO results showed that in the absence of ACF pretreatment, a 12 % decline in membrane permeability (from 1.78 to 1.57 L/(m2-bar-h)) was observed, while no permeability decline was measured after ACF treatment. The organic fouling was confirmed by mass balance calculations on the bench scale experiments as well as Fourier Transform Infrared (FTIR) analysis on the membrane coupons. Moreover, LC-OCD analysis showed that the ACF inlet has a TOC concentration of approximately 3.06 mg/L; of those 1.29 mg/L (42 %) are hydrophobic, and 1.77 mg/L (58 %) are hydrophilic. After ACF treatment, the hydrophobic organics decreased to 0.65 mg/L, revealing that the ACF is removing >50 % of hydrophobic organics which are likely responsible for membrane fouling. Bench-scale operational and water quality results were comparable to the full-scale RO performance data validating the lab testing procedure implemented in this study.

Nanoparticle-assisted biohydrogen production from pretreated food industry wastewater sludge: Microbial community shifts in batch and continuous processes

Biohydrogen production from industrial waste has gained a significant attention as a sustainable energy source. In this study, the enrichment of biohydrogen production from pretreated dissolved air flotation (DAF) sludge, generated from food industry wastewater treatment plants, was investigated using SiO2@Cu-Ag dendrites core–shell nanostructure (NS). The effect of NS on the changes of the microbial community and biohydrogen yield was evaluated through batch and continuous tests. In batch mode, various nanomaterial doses were investigated with several concentrations ranging from 20 to 50 mg/L for hydrogen production using glucose as a substrate. The optimum core–shell NS amount was 40 mg/L, achieving a maximum H2 yield of 163 mL/g volatile solids (VS) compared to the control's 79 mL/g VS. However, 50 mg/L NS inhibited most bacteria in the sludge. The continuous experiment used a continuous stirring tank reactor (CSTR) with 40 mg/L SiO2@Cu-Ag core–shell NS and pretreated industrial sludge as substrate. The H2 yield increased to 115 L/kg VS compared to the control reactor's 89 L/kg VS. The gas analysis showed compositional proportions of 83 % H2, 7 % CO2, and 4.5 % methane, while the microbial community analysis indicated the development of hydrogen-producing species such as Clostridium. In conclusion, SiO2@Cu-Ag core–shell NS addition enhanced anaerobic degradation of organic matter and its conversion to biohydrogen. The selected nanomaterial can be used for an effective continuous treatment system for industrial sludge while promoting dark fermentation.

Towards the implementation of Positive Energy Districts in industrial districts: an Italian case study

Owing to the opportunity to provide an annual positive energy balance and net-zero carbon emissions, Positive Energy Districts aim at fostering the energy transition of urban city centres. To fully support the decarbonization of cities, it may be interesting to extend their implementation to other energy intensive districts, such as cities’ industrial areas. In this regard, this paper addresses the opportunity to apply the Positive Energy District concept within the industrial area of a city in the South of Italy. A mixed-use building, the industrial wastewater treatment plant and an office building have been involved as users and equipped with a 250 kW wind turbine and multiple photovoltaic plants installed on the roof of the buildings, in parking areas and in an unused land, for a total peak power equal to 466 kW. The renewable-based plants’ generation has been simulated in HOMER Pro® software, on a quarter-hour basis, and an energy and environmental analysis have been performed using users’ real electric load profiles. The proposed configuration allows to save 55% of primary energy and carbon dioxide emissions compared to the baseline case where users’ electric energy demand is fully met by the power grid. In particular, the primary energy saving is equal to 1 GWh/y and the carbon dioxide emissions reduction is equal to 150 tCO2/y.

Metagenomic analysis reveals the distribution, function, and bacterial hosts of degradation genes in activated sludge from industrial wastewater treatment plants

For comprehensive insights into the bacterial community and its functions during industrial wastewater treatment, with a particular emphasis on its pivotal role in the bioremediation of organic pollutants, this study utilized municipal samples as a control group for metagenomic analysis. This approach allowed us to investigate the distribution, function, and bacterial hosts of biodegradation genes (BDGs) and organic degradation genes (ODGs), as well as the dynamics of bacterial communities during the industrial wastewater bioprocess. The results revealed that BDGs and ODGs associated with the degradation of benzoates, biphenyls, triazines, nitrotoluenes, and chlorinated aromatics were notably more abundant in the industrial samples. Specially, genes like clcD, linC, catE, pcaD, hbaB, hcrC, and badK, involved in the peripheral pathways for the catabolism of aromatic compounds, benzoate transport, and central aromatic intermediates, showed a significantly higher abundance of industrial activated sludge (AS) than municipal AS. Additionally, the BDG/ODG co-occurrence contigs in industrial samples exhibited a higher diversity in terms of degradation gene carrying capacity. Functional analysis of Clusters of Orthologous Groups (COGs) indicated that the primary function of bacterial communities in industrial AS was associated with the category of “metabolism”. Furthermore, the presence of organic pollutants in industrial wastewater induced alterations in the bacterial community, particularly impacting the abundance of key hosts harboring BDGs and ODGs (e.g. Bradyrhizobium, Hydrogenophaga, and Mesorhizobium). The specific hosts of BDG/ODG could explain the distribution characteristics of degradation genes. For example, the prevalence of the Adh1 gene, primarily associated with Mesorhizobium, was notably more prevalent in the industrial AS. Overall, this study provides valuable insights into the development of more effective strategies for the industrial wastewater treatment and the mitigation of organic pollutant contamination.

Investigation of reusability of effluents from an organized industrial zone wastewater treatment plant using a pressure-driven membrane process

Abstract The quantity of wastewater being discharged into the environment due to the rise in industrial activities is progressively growing over time. Aside from large environmental risk posed by untreated wastewater discharge, the reuse of treated water prevents wastage of large amounts of water. For this reason, in this study, the reuse potential of an organized industrial zone wastewater was investigated by membrane processes. The appropriate membrane type and rejection performance were determined for various pollutant parameters including conductivity, chemical oxygen demand (COD), total nitrogen (TN), chloride, and sulfate. Laboratory-scale batch membrane filtration experiments were performed by using three different membrane types (BW30, XLE, and X20). The experiments were conducted at 15 and 20 bar pressures and flux data were collected during the operations. The results showed that BW30 and X20 membranes could be operated comfortably with 80% recovery for the wastewater containing low and high sulfate concentrations. For the wastewater with low sulfate concentration, the fluxes of BW30 and X20 at 20 bar were 19.7 and 16.4 L/m2/h, respectively, at 80% recovery. On the other hand, for the wastewater with higher sulfate concentration, the fluxes of BW30 and X20 at 20 bar were 8.6 and 11.5 L/m2/h, respectively.

Recent Advances in the Treatment of Industrial Wastewater from Different Celluloses in Continuous Systems.

There are numerous studies on water care methods featured in various academic and research journals around the world. One research area is cellulose residue coupled with continuous systems to identify which are more efficient and easier to install. Investigations have included mathematical design models that provide methods for developing and commissioning industrial wastewater treatment plants, but nothing is provided on how to size and start these treatment systems. Therefore, the objective is to determine recent advances in the treatment of industrial wastewater from different celluloses in continuous systems. The dynamic behavior of the research results with cellulose biomasses was analyzed with the mass balance model and extra-particle and intraparticle dispersion, evaluating adsorption capacities, design variables, and removal constants, and making a size contribution for each cellulose analyzed using adsorption capacities. A mathematical model was also developed that feeds on cellulose reuse, determining new adsorption capacities and concluding that the implementation of cellulose waste treatment systems has a high feasibility due to low costs and high adsorption capacities. Furthermore, with the design equations, the companies themselves could design their systems for the treatment of water contaminated with heavy metals with cellulose.

The role of corporate social responsibility and government incentives in installing industrial wastewater treatment plants: SEM-ANN deep learning approach

Contaminated industrial wastewater is one of the severe causes of health diseases. The wastewater treatment trend in developing countries is less, and governments are not strictly pursuing the wastewater management protocols adopted by firms. To study the intention to install wastewater treatment plants at the firm level and provide policy suggestions to the developing countries’ governments, we have collected a cross-sectional dataset from manufacturing firms. We have presented an integrated model based on the theory of planned behaviour and tested our proposed model by implying SEM-ANN deep learning techniques. Results revealed that Environmental knowledge, installation cost, firm reputation, and corporate social responsibility positively influence firm management’s intention to install wastewater treatment plants, but awareness of the risk associated with contaminated wastewater has a negative influence. On the other hand, Government incentives do not influence the process. In addition, our study has found that firm size moderates the relationship between explained and exploratory variables. Our study provided valuable insight into the available literature and provided some policy suggestions to developing countries' governments to cope with water scarcity and health issues caused by contaminated industrial wastewater.

New findings on the occurrence, removal, and risk assessment of nonylphenol and octylphenol in industrial wastewater treatment plants in Korea

Nonylphenol (NP) and octylphenol (OP), extensively used in industries, can disrupt the human endocrine system and cause significant ecological toxicity. Therefore, in this study, we aimed to reveal the occurrence and removal characteristics of NP and OP in 30 industrial wastewater treatment plants (IWWTPs). Specifically, this study focused on 13 NP isomers that have not been previously reported. Additionally, the potential environmental risk of NP and OP discharged from IWWTPs was assessed using a minimum dilution factor (MDF), proposed for the first time in this study. We showed that the concentration and proportion of the isomer NP11 were higher than those of the other isomers in the IWWTP influents and effluents. We also identified an activated sludge-activated carbon adsorption process suitable for removing NP and OP. Finally, we proposed the MDF value of 11 for the potential environmental risk assessment of NP and OP, revealing that OP poses a higher risk than NP when discharged into surface water. These findings underscore the importance of focusing on the isomer NP11 and OP in IWWTPs.

Phylogenomics analysis of multidrug-resistant Elizabethkingia anophelis in industrial wastewater treatment plant.

This study investigated the phylogenetic relatedness of multidrug-resistant Elizabethkingia anophelis recovered from an industrial wastewater treatment plant (WWTPi). The wastewater samples were plated in brain heart infusion agar (4mg/L ceftazidime, 8mg/L meropenem, and 2mg/L polimixin). Four isolates recovered from four stages of WWTPi (influent, aeration, decantation, and treated effluent) were identified and evaluated of susceptibility profiles in the VITEK 2 system. These strains identified as E. meningoseptica were confirmed to be E. anophelis by whole genomic sequencing (Miseq-Illumina) and showed antimicrobial resistance genes of β-lactams, aminoglycosides, and tetracycline's classes. The ribosomal multilocus sequence typing showed that they belong to the rST 65620 together with clinical strains. The phylogenomic tree revealed the similarity of our strains to those belonging to sublineage 11 and the single nucleotide polymorphism analysis confirmed that they belong to a single clade. To the best of our knowledge, this is the first study reporting the persistence of multidrug-resistant E. anophelis sublineage 11 along the wastewater treatment.

Greenhouse Gas Emissions of an Urban Water System in Korea: A case study of Paju city

Objectives : This study assessed the greenhouse gas emissions (GHG) in the urban water system from a life cycle perspective in the city of Paju. It serves as a case study to provide a quantitative basis for the net-zero water management.Methods : The scope of the study included the centralized local water supply and inter-basin water import system (water abstraction facilities, water treatment plants, pump stations, and water pipelines), wastewater system (wastewater pipelines, pump stations, and wastewater treatment plants, public industrial wastewater treatment plants, on-site wastewater treatment facilities), and circular water use (rainwater harvesting, greywater reuse, and wastewater recycling). This study considered scope 1 emissions, specifically CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O emissions generated from wastewater treatment plants, scope 2 emissions from the electricity use during the operation of water infrastructure, and scope 3 emissions associated with the production of water and wastewater pipelines and chemicals. Scope 1 emissions were quantified using both the national guidelines and the 2019 IPCC guideline, and the estimates based on the two methods were compared. Scope 2 and scope 3 emissions were evaluated using life cycle assessment. To quantify GHG emissions for the year 2018, data were collected or estimated from various sources, including public statistics, field interviews, and the literature.Results and Discussion : In 2018, the total GHG emissions from Paju’s water system were 197.4 thousand tons of CO&lt;sub&gt;2&lt;/sub&gt; eq. Among these emissions, the scope 2 emissions accounted for the largest share, comprising 66.3% of the total. Notably, circular water use, which included wastewater recycling for high-quality industrial uses, accounted for 41.0% of the scope 2 emissions. Scope 1 emissions accounted for 25.5% and scope 3 emissions accounted for 8.2% of the total emissions. However, in the case of scope 1 emissions, the estimates varied significantly by 2.9 to 6.5 times, depending on the calculation methods and emission factors provided by two different guidelines.Conclusion : To achieve carbon neutrality in the water sector of the city of Paju, two approaches are required: enhancing energy efficiency to reduce scope 2 emissions and implementing measures to reduce scope 1 emissions. However, to obtain accurate and reliable estimates of the GHG emissions, it is crucial to develop applicable scope 1 emission factors based on field data. Furthermore, to gain a comprehensive understanding of GHG emissions in the water sector, further studies are necessary to analyze embodied GHG emissions in water infrastructure and GHG emissions associated with the end use of water.

Microbial community structure and functional prediction in five full-scale industrial park wastewater treatment plants

The development of industrial parks has become an important global trend contributing significantly to economic and industrial growth. However, this growth comes at a cost, as the treatment of multisource industrial wastewater generated in these parks can be difficult owing to its complex composition. Microorganisms play a critical role in pollutant removal during industrial park wastewater treatment. Therefore, our study focused on the microbial communities in five full-scale industrial park wastewater treatment plants (WWTPs) with similar treatment processes and capacities. The results showed that denitrifying bacteria were dominant in almost every process section of all the plants, with heterotrophic denitrification being the main pathway. Moreover, autotrophic sulfur denitrification and methane oxidation denitrification may contribute to total nitrogen (TN) removal. In plants where the influent had low levels of COD and TN, dominant bacteria included oligotrophic microorganisms like Prosthecobacter (2.88 % ~ 10.02 %) and hgcI_clade (2.05 % ~ 9.49 %). Heavy metal metabolizing microorganisms, such as Norank_f__PHOS-HE36 (3.96 % ~ 5.36 %) and Sediminibacterium (1.86 % ~ 5.34 %), were prevalent in oxidation ditch and secondary settling tanks in certain plants. Functional Annotation of Prokaryotic Taxa (FAPROTAX) revealed that microbial communities in the regulation and hydrolysis tanks exhibited higher potential activity in the nitrogen (N) and sulfur (S) cycles than those in the oxidation ditch. Sulfate/sulfite reduction was common in most plants, whereas the potential occurrence of sulfide compounds and thiosulfate oxidation tended to be higher in plants with a relatively high sulfate concentration and low COD content in their influent. Our study provides a new understanding of the microbial community in full-scale industrial park WWTPs and highlights the critical role of microorganisms in the treatment of industrial wastewater.

Sludge bulking monitoring in industrial wastewater treatment plants through graphical methods: A dynamic graph embedding and Bayesian networks approach

Sludge bulking is a prevalent issue in wastewater treatment plants (WWTPs) that negatively impacts effluent quality by hindering the normal functioning of treatment processes. To tackle this problem, we propose a novel graph-based monitoring framework that employs advanced graph-based techniques to detect and diagnose sludge bulking events. The proposed framework utilizes historical datasets under normal operating conditions to extract pertinent features and causal relationships between process variables. This enables operators to trigger alarms and diagnose the root cause of the bulking event. Sludge bulking detection is carried out using the dynamic graph embedding (DGE) method, which identifies similarities among process variables in both temporal and neighborhood dependencies. Consequently, the dynamic Bayesian network (DBN) computes the prior and posterior probabilities of a belief, updated at each time step. Variations in these probabilities indicate the potential root cause of the sludge bulking event. The results demonstrate that the DGE outperforms other linear and non-linear feature extraction methods, achieving a detection rate of 99%, zero false alarms, and less than one percent incorrect detections. Additionally, the DBN-based diagnostic method accurately identified the majority of sludge bulking root causes, primarily those resulting from sudden drops in COD concentration, with an accuracy of 98% an improvement of 11% over state-of-the-art techniques.

Experimental and statistical modeling of the effect of process modification and wastewater characterization on greenhouse gas emissions for a dairy industry wastewater treatment plant: A minimization approach

Abstract This study aimed to determine the effect of design conditions and wastewater characterization on greenhouse gas (GHG) emissions from an industrial wastewater treatment plant. Analysis of variance, correlation analyses, heat-mapping, and principal component analyses (PCA) were performed to determine the correspondence between GHG emissions and wastewater characterization. Then, a new empirical model based on the correlation of wastewater characterization has been developed. This study has concentrated on using process modification to mitigate GHG emissions. If an aeration tank is operated at 36 h of hydraulic retention time and 20 days of solid retention time at design conditions, an average reduction of 45.4, 45.3, and 45.2% in carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions, respectively, have been ensured. According to correlation analysis, a moderately significant positive correlation was found between effluent chemical oxygen demand values and CO2 and CH4 values (r = 0.909, r = 0.937). N2O emissions were closely related to Total Kjeldahl Nitrogen input values (r = 0.876). GHG emissions have been calculated using this correlation, and the results overlapped with the monitoring values. The estimated results of GHG emissions based on wastewater characterization have converged to in situ monitoring results, by an average of 82%.

Assessment of Heavy Metal Accumulation Using Soil Pollution Indices in an Industrial Town, Landfill, and Wastewater Treatment Plant of Ilam City, Iran

Assessment of Heavy Metal Accumulation Using Soil Pollution Indices in an Industrial Town, Landfill, and Wastewater Treatment Plant of Ilam City, Iran

Full-scale partial nitritation and anammox (PN/A) application in removing nitrogen from industrial wastewater: Performance and life cycle assessment

Anaerobic ammonium oxidation (anammox) is an innovative nitrogen removal process that is widely used in wastewater treatment due to its energy-saving potential and ability to reduce carbon emissions. However, research on the application of anammox in full-scale industrial wastewater treatment plants (WWTPs) is limited, and its environmental impacts are yet to be fully understood. This study evaluates the performance and environmental burdens of one-stage partial nitritation and anammox (PN/A) in a full-scale WWTP treating coal chemical wastewater, with different demonstration periods. Compared with conventional nitrification–denitrification, the energy footprint and carbon footprint of the PN/A process were significantly lower and effluent quality was improved. Based on the four-quadrant clustering method, the overall performance of the studied WWTP achieved the greatest synergy during the stable operation period. Life cycle assessment has shown that the PN/A process significantly reduces the system’s contribution to environmental indicators. According to the sensitivity analysis, the fluctuations in energy consumption and chemical usage have significant environmental impacts, with differential sensitivity in the environmental impacts of two demonstration periods. Therefore, considering the specific situation of the WWTPs, optimizing the parameters/indicators most sensitive to environmental impact is essential to reducing environmental loads. Importantly, this work demonstrated that PN/A can improve the operational performance of full-scale industrial WWTPs with lower environmental burdens, providing valuable guidance for the development of sustainable wastewater treatment processes.

Engineered Fe-doped activated carbon from industry waste for peroxymonosulfate activation: Performance and mechanism

Efficient and low-cost catalysts are important for contaminant remediation in peroxymonosulfate (PMS)-based advanced oxidation processes (AOPs). In this study, a solid waste, generated by the polyferric chloride coagulation of the phenol-saturated powder activated carbon from an industrial wastewater treatment plant, was used to prepare metal/carbon composites under different pyrolysis temperatures (650–950 °C). The catalyst pyrolyzed at 950 °C (FeAC-950) exhibited the highest reactive activity for PMS activation as demonstrated by a series of electrochemical techniques. Nearly complete BPA elimination can be achieved within 60 min by 0.1 g L–1 FeAC-950 and 0.5 mM PMS. The results of electron paramagnetic resonance (EPR), chemical quenching and open circuit potential (OCPT) experiments demonstrate a combined radical and non-radical oxidation mechanism in the FeAC-950/PMS process and BPA was removed dominantly through radical pathway. Various persistent organic pollutants can be efficiently eliminated in the FeAC-950/PMS system. In addition, the present system showed good tolerance to natural organic matter as well as some common anions such as chloride and nitrate. This study dedicated a simple method to prepare an efficient solid waste-based catalyst in environmental catalysis. The outcomes will not only provide a value-added reuse approach for waste management but also facilitate the FeAC-950 applications in wastewater remediation technologies.

Abundance, characteristics, and removal of microplastics in different wastewater treatment plants in a Yangtze River Delta city of China

Microplastics (MPs) have become emerging environmental pollutants worldwide. Wastewater treatment plants (WWTPs) are considered to be the major source and sink of MPs in the terrestrial and aquatic environment. The present study has been carried out for Nanjing, a typical Yangtze River Delta city in China. In this work, the abundance and characteristics of MPs were investigated in the influent of four WWTPs, and the removal effect of different treatment processes was studied in the two advanced tertiary treatment WWTPs. In the influent, the abundance of MPs of industrial WWTPs (IWWTPs) was higher than that of municipal WWTPs (MWWTPs), with a dominant size of 38–63 μm. MP shapes were mainly distributed in fragments and fibers, with polymer species of polypropylene (PP) and polyethylene (PE). In the final effluent, MPs were removed by 93.81 % in IWWTPs versus 88.10 % in MWWTPs, which were mainly influenced by the tertiary treatment technology. The tertiary treatment showed significant differences with the removal efficiency of 61.58 % in IWWTPs, equipped with a high-density sediment tank, and 30.40 % in MWWTPs, equipped with a denitrification filter. This study provides comprehensive information about the MPs' characteristics and fate contained in different sewage of WWTPs and analyzes the tertiary treatment effect of MPs, expecting to provide constructive support for the improvement of management strategies in WWTPs technologies.