Industrial Wastewater Treatment Plant Research Articles

Biopolymeric Composite Columns for Improving Water Quality in a Freshwater Stream Receiving Wastewater Treatment Plant Effluents

AbstractInefficiently treated wastewater, which contains a high concentration of pollutants, is hazardous when it is mixed with the clean water of rivers and lakes. Nitrate in particular is a major global problem that leads to eutrophication and poses a threat to both aquatic ecosystems and human health. To address this issue, this work assessed the efficiency of polymeric cryogel (PC) and biopolymer (EPS)-blended composites (EPS@PC) in removing nitrates. Tests were also conducted to quantify the decrease in phosphate, chloride ions, and chemical oxygen demand (COD) in real water samples taken from the Ankara stream, which receives effluents from both urban (UWTP) and industrial (IWTP) wastewater treatment plants. Five different columns with varying adsorptive properties were prepared, some of which were combined with iron. The EPS-@PC-C5 column demonstrated the highest adsorption ratio for nitrate removal compared to the other tested columns. The EPS@PC-C5 achieved a high removal efficiency of 126.38 mg nitrate/g and showed COD reduction ranging from 60.2 to 94.1%. The removal ratio of chloride concentration varied between 56.0 and 75.7%, while the removal of phosphates ranged from 87 to 99%. Columns composed of EPS (EPS@PC) with both negatively and positively charged ligands are dependable and suitable options for water remediation. Graphical Abstract

Physics-informed and data-driven modeling of an industrial wastewater treatment plant with actual validation

Data-driven modeling is essential in chemical engineering, especially in complex systems like wastewater treatment plants. Recurrent neural networks are effective for modeling parameters in wastewater treatment process such as dissolved oxygen concentration and chemical oxygen demand due to their nonlinear adaptability. However, traditional models face challenges such as the requirement for larger datasets and more frequent sampling, noisy measurements, and overfitting. To address this, physics-informed neural networks integrate physical knowledge for improved performance. In our study, we apply both approaches to a wastewater treatment plant, enhancing prediction performance. Our results demonstrate that physics-informed models perform successfully in offline and online validation, especially when standard methods fail. They maintain effectiveness without frequent updates. Yet, integrating physics-informed knowledge can introduce noise when standard methods suffice. This result points out the need for careful consideration of model choice in different scenarios.

Complete long-term monitoring of greenhouse gas emissions from a full-scale industrial wastewater treatment plant with different cover configurations

The greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs), consisting mainly of methane (CH4) and nitrous oxide (N2O), have been constantly increasing and become a non-negligible contributor towards carbon neutrality. The precise evaluation of plant-specific GHG emissions, however, remains challenging. The current assessment approach is based on the product of influent load and emission factor (EF), of which the latter is quite often a single value with huge uncertainty. In particular, the latest default Tier 1 value of N2O EF, 0.016 ± 0.012 kgN2O–N kgTN−1, is estimated based on the measurement of 30 municipal WWTPs only, without involving any industrial wastewater. Therefore, to resolve the pattern of GHG emissions from industrial WWTPs, this work conducted a 14-month monitoring campaign covering all the process units at a full-scale industrial WWTP in Shanghai, China. The total CH4 and N2O emissions from the whole plant were, on average, 447.7 ± 224.5 kgCO2-eq d−1 and 1605.3 ± 2491.0 kgCO2-eq d−1, respectively, exhibiting a 5.2- or 3.9-times more significant deviation than the influent loads of chemical oxygen demand (COD) or total nitrogen (TN). The resulting EFs, 0.00072 kgCH4 kgCOD−1 and 0.00211 kgN2O–N kgTN−1, were just 0.36% of the IPCC recommended value for CH4, and 13.2% for N2O. Besides, the parallel anoxic-oxic (A/O) lines of this industrial WWTP were covered in two configurations, allowing the comparison of GHG emissions from different odor control setup. Unit-specific analysis showed that the replacement of enclosed A/open O with enclosed A/O reduced the CH4 EF by three times, from 0.00159 to 0.00051 kgCH4 kgCOD−1, and dramatically decreased the N2O EF by an order of magnitude, from 0.00376 to 0.00032 kgN2O–N kgTN−1, which was among the lowest of all full-scale WWTPs.

Evaluating the Influence of Reverse Osmosis on Lakes Using Water Quality Indices: A Case Study in Saudi Arabia

A drastic level of resource degradation was revealed through a preliminary evaluation (completed in 2016) of water quality in a recreational lake in the second industrial city in Dammam, Saudi Arabia. The primary signs were a foul smell, algal bloom, high turbidity, and lack of aquatic life. This study aims to evaluate the influence of reverse osmosis (RO) on lake water quality. The recreational lake consists of two connected lakes (Lakes 1 and 2), which receive treated effluent from an industrial wastewater treatment plant. Composite samples were collected from the lakes to analyze their physiochemical parameters. Descriptive analyses were performed, and two water quality indices were developed to observe the variations in water quality conditions between the two periods (2016 and 2021). The results indicated that the water parameters of total dissolved solids (TDS), sulphate (SO42−), biological oxygen demand (BOD), and dissolved oxygen (DO) in 2016 (3356, 4100, 516, and 1.32 mg/L, respectively) were significantly improved in 2021 (2502, 1.28, 9.39, and 7.79 mg/L, respectively). The results of the water quality index (WQI) and comprehensive pollution index (CPI) indicated that the water quality in Lake 1 was significantly enhanced in 2021 (WQI = 85, CPI = 1) in comparison with assessment data from 2016 (WQI = 962, CPI = 8). However, the data from Lake 2 revealed higher pollution levels in 2021 (WQI = 1722, CPI = 18) than those recorded in 2016 (WQI = 1508, CPI = 13). As indicated by the absence of bad smells, algal blooms, and restoration of aquatic life, the RO intervention successfully improved the water quality in Lake 1. The WQI and CPI were helpful tools for evaluating lake water quality.

An outbreak of Legionnaires' disease linked to a municipal and industrial wastewater treatment plant, The Netherlands, September-October 2022.

Wastewater treatment plants (WWTPs) are increasingly identified as Legionnaires' disease (LD) sources. An outbreak investigation was initiated following five LD cases reported in September 2022 in Houten, the Netherlands. Case identification was based on the European LD case definition, with symptom onset from 1 September 2022, residence in or within 5 km of Houten, or visit to Houten within the incubation period, without other likely sources. We sampled potential sources and genotyped environmental and clinical isolates. We identified 15 LD cases with onset between 13 September and 23 October 2022. A spatial source identification and wind direction model suggested an industrial (iWWTP) and a municipal WWTP (mWWTP) as potential sources, with the first discharging water into the latter. Both tested positive for Legionella pneumophila serogroups 1 and 6 with multiple sequence types (ST). We detected L. pneumophila sg1 ST42 in the mWWTP, matching with one of three available clinical isolates. Following control measures at the WWTPs, no further cases were observed. This outbreak underlines that municipal and industrial WWTPs can play an important role in community LD cases and outbreaks, especially those with favourable conditions for Legionella growth and dissemination, or even non-favourable conditions for growth but with the influx of contaminated water.

Microbial community structure and diversity attached to the periphyton in different urban aquatic habitats.

Periphyton is a complex community composed of diverse prokaryotes and eukaryotes; understanding the characteristics of microbial communities within periphyton becomes crucial for biogeochemical cycles and energy dynamics of aquatic ecosystems. To further elucidate the community characteristics of periphyton across varied aquatic habitats, including unpolluted ecologically restored lakes, aquaculture ponds, and areas adjacent to domestic and industrial wastewater treatment plant outfalls, we explored the composition and diversity of prokaryotic and eukaryotic communities in periphyton by employing Illumina MiSeq sequencing. Our findings indicated that the prokaryotic communities were predominantly composed of Proteobacteria (40.92%), Bacteroidota (21.01%), and Cyanobacteria (10.12%), whereas the eukaryotic communities were primarily characterized by the dominance of Bacillariophyta (24.09%), Chlorophyta (20.83%), and Annelida (15.31%). Notably, Flavobacterium emerged as a widely distributed genus among the prokaryotic community. Unclassified_Tobrilidae exhibited higher abundance in unpolluted ecologically restored lakes. Chaetogaster and Nais were enriched in aquaculture ponds and domestic wastewater treatment plant outfall area, respectively, while Surirella and Gomphonema dominated industrial sewage treatment plant outfall area. The alpha diversity of eukaryotes was higher in unpolluted ecologically restored lakes. pH and nitrogen content ( , , and TN) significantly explained the variations for prokaryotic and eukaryotic community structures, respectively. Eukaryotic communities exhibited a more pronounced response to habitat variations compared to prokaryotic communities. Moreover, the association networks revealed an intensive positive correlation between dominant Bacillariophyta and Bacteroidota. This study provided useful data for identifying keystone species and understanding their ecological functions.

The proliferation of antibiotic resistance genes (ARGs) and microbial communities in industrial wastewater treatment plant treating N,N-dimethylformamide (DMF) by AAO process.

The excessive use of antibiotics has resulted in the contamination of the environment with antibiotic resistance genes (ARGs), posing a significant threat to public health. Wastewater treatment plants (WWTPs) are known to be reservoirs of ARGs and considered to be hotspots for horizontal gene transfer (HGT) between bacterial communities. However, most studies focused on the distribution and dissemination of ARGs in hospital and urban WWTPs, and little is known about their fate in industrial WWTPs. In this study, collected the 15 wastewater samples containing N,N-dimethylformamide (DMF) from five stages of the anaerobic anoxic aerobic (AAO) process in an industrial WWTPs. The findings revealed a stepwise decrease in DMF and chemical oxygen demand (COD) content with the progression of treatment. However, the number and abundances of ARGs increase in the effluents of biological treatments. Furthermore, the residues of DMF and the treatment process altered the structure of the bacterial community. The correlation analysis indicated that the shift in bacterial community structures might be the main driver for the dynamics change of ARGs. Interestingly, observed that the AAO process may acted as a microbial source and increased the total abundance of ARGs instead of attenuating it. Additionally, found that non-pathogenic bacteria had higher ARGs abundance than pathogenic bacteria in effluents. The study provides insights into the microbial community structure and the mechanisms that drive the variation in ARGs abundance in industrial WWTPs.

Temporal and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in the Danube River in Hungary

The Danube is a significant transboundary river on a global scale, with several tributaries. The effluents from industrial operations and wastewater treatment plants have an impact on the river's aquatic ecosystem. These discharges provide a significant threat to aquatic life by deteriorating the quality of water and sediment. Hence, a total of 16 Polycyclic Aromatic Hydrocarbons (PAHs) compounds were analyzed at six locations along the river, covering a period of 12 months. The objective was to explore the temporal and spatial fluctuations of these chemicals in both water and sediment. The study revealed a significant fluctuation in the concentration of PAHs in water throughout the year, with levels ranging from 224.8 ng/L during the summer to 365.8 ng/L during the winter. Similarly, the concentration of PAHs in sediment samples varied from 316.7 ng/g in dry weight during the summer to 422.9 ng/g in dry weight during the winter. According to the Europe Drinking Water Directive, the levels of PAHs exceeded the permitted limit of 100 ng/L, resulting in a 124.8% rise in summer and a 265.8% increase in winter. The results suggest that the potential human-caused sources of PAHs were mostly derived from pyrolytic and pyrogenic processes, with pyrogenic sources being more dominant. Assessment of sediment quality standards (SQGs) showed that the levels of PAHs in sediments were below the Effect Range Low (ERL), except for acenaphthylene (Acy) and fluorene (Fl) concentrations. This suggests that there could be occasional biological consequences. The cumulative Individual Lifetime Cancer Risk (ILCR) exceeds 1/104 for both adults and children in all sites.

Linking metabolomics to machine learning reveals the metabolic fates of the refractory industrial pollutant 1-Hexadecene

In order to solve the low removal efficiency of 1-Hexadecene in industrial wastewater treatment plants and fill the knowledge gap of its microbial metabolic mechanisms, this work studied the 1-Hexadecene degrading microorganisms enrichment and its metabolic pathway using continuous bioreactors and batch incubation tests. With the successful enrichment of hexadecene-degrading microorganisms, the biodegradation rates of 1-Hexadecene at 50–200 mg/L could range from 58.6 % to 72.5 %. The 16S rRNA fragment and microbial community analysis identified Flavihumibacter, Gemmatimonas, and Caulobacter as putative 1-Hexadecene degraders. Through mass spectrum qualification analysis, Principal component analysis and orthogonal partial least squares discriminant analysis, totally 81 featured metabolites associated with 1-Hexadecene biogradation were screened out. The machine learning based support vector machines and random forests further identified 18 biomarkers during those featured metabolites. Based on the coupling metabolomics analysis with machine learning, three potential metabolic pathways with Heptane, 2,5-dimethyl hexane, 3-ethyl-3-methyl-heptane as the respective end products were proposed through biomarkers. These results provide new insights for the analysis of metabolic pathway of 1-Hexadecene, and theoretical support for the bioaugmentation of its treatment processes.

A study of continuous-flow electrocoagulation process to minimize chemicals dosing in the full-scale treatment of plastic plating industry wastewater

A continuous-flow electrocoagulation unit was used to replace the existing chemical coagulation in plastic plating industry wastewater treatment plants, aiming to enhance pollutant removal and cost efficiency. This study was conducted at an on-site wastewater treatment plant, with the electrocoagulation process monitored for nine consecutive months. A novel electrocoagulation unit equipped with multi-rod helical systems (i.e., made of an iron anode and a stainless-steel cathode) was used in this study, with the treatment flow adjusted to optimize the operational costs. The results indicate that energy consumption can be maintained at 7200 kWh/month while achieving >99 % removal of heavy metals (Cr, Ni, and Cu), with removal rates of 78.64 ± 0.13 mg/L.day (Cr), 105.47 ± 0.07 mg/L.day (Ni), and 38.30 ± 0.09 mg/L.day (Cu). The chemical cost was reduced by approximately 50 %. Furthermore, an over 50 % reduction in sludge production was achieved, with the acid and alkaline by-products entirely recycled. Compared to the previously applied chemical coagulation, electrocoagulation can reduce operational costs from US$ 6.11 to US$ 2.87 per m3 of wastewater treated. These results confirm that electrocoagulation can be optimized and implemented to replace conventional chemical coagulation.

N-nitrosamines in electroplating and printing/dyeing industrial wastewater treatment plants: Removal efficiency, environmental emission, and the influence on drinking water

The discharge of industrial wastewater containing high concentrations of N-nitrosamines to the aquatic environment can impair downstream source waters and pose potential risks to human health. However, the transport and fate of N-nitrosamines in typical industrial wastewater treatment plants (IWWTPs) and the influence of these effluents on source water and drinking water are still unclear. This study investigated nine N-nitrosamines in four full-scale electroplating (E-) and printing/dyeing (PD-) IWWTPs, two drinking water treatment plants (DWTPs) in the lower reaches of these IWWTPs, and the corresponding tap water in South China. The total concentrations of N-nitrosamines (∑NAs) were 382–10,600, 480–1920, 494–789, and 27.9–427 ng/L in influents, effluents, source water, and tap water, respectively. The compositions of N-nitrosamine species in different influents varied a lot, while N-nitrosodi-n-butylamine (NDBA) and N-nitrosodimethylamine (NDMA) dominated in most of the effluents, source water, and tap water. More than 70 % N-nitrosamines were removed by wastewater treatment processes used in E-IWWTPs such as ferric-carbon micro-electrolysis (Fe/C-ME), while only about 50 % of N-nitrosamines were removed in PD-IWWTPs due to the use of chlorine reagent or other inefficient conventional processes such as flocculation by cationic amine-based polymers or bio-contact oxidation. Therefore, the mass fluxes of N-nitrosamines discharged from these industrial wastewaters to the environment in the selected two industrial towns were up to 14,700 mg/day. The results based on correlation and principal component analysis significantly demonstrated correlations between E-and PD-effluents and source water and tap water, suggesting that these effluents can serve as sources of N-nitrosamines to local drinking water systems. This study suggests that N-nitrosamines are prevalent in typical IWWTPs, which may infect drinking water systems. The findings of this study provide a basis data for the scientific evaluation of environmental processes of N-nitrosamines.

SOURCES OF POLLUTION OF SURFACE WATERS, DEVELOPMENT OF RECOMMENDATIONS FOR THEIR DETECTION AND DEVELOPMENT OF PREVENTION METHODS

The problem of water pollution is becoming more and more urgent for the whole world. Unfortunately, Georgia is not an exception, where water sources, despite their number, are small and a significant part of them is polluted. Unlike contamination of industrial wastewater treatment plants, which comes from multiple diffuse sources, biological contamination results from the movement of precipitation or snowmelt onto and into the soil. As runoff moves, it collects and transports natural and anthropogenic pollutants and deposits them in rivers, groundwater, or lakes. Special attention should be paid to the biological pollution of water sources, which occurs as a result of washing or flushing of sources of anthropogenic biological pollution with rain and melt water. After entering the water environment, under favorable conditions, pathogenic organisms can multiply rapidly, which poses a threat to the environment. Contamination of water sources is a major cause of water quality problems. The impact of source water contaminants on specific waters varies and cannot always be fully assessed. However, we know that these pollutants have harmful effects on drinking water supplies and wildlife. That is why it is necessary to find the source of biological pollution of water in order to develop an effective method of its elimination.

PHA and EPS production from industrial wastewater by conventional activated sludge, membrane bioreactor and aerobic granular sludge technologies: A comprehensive comparison

The present study has focused on the mainstream integration of polyhydroxyalkanoate (PHA) production with industrial wastewater treatment by exploiting three different technologies all operating in sequencing batch reactors (SBR): conventional activated sludge (AS-SBR), membrane bioreactor (AS-MBR) and aerobic granular sludge (AGS). A full aerobic feast/famine strategy was adopted to obtain enrichment of biomass with PHA-storing bacteria. All the systems were operated at different organic loading (OLR) rate equal to 1-2-3 kgCOD/m3∙d in three respective experimental periods. The AS-MBR showed the better and stable carbon removal performance, whereas the effluent quality of the AS-SBR and AGS deteriorated at high OLR. Biomass enrichment with PHA-storing bacteria was successfully obtained in all the systems. The AS-MBR improved the PHA productivity with increasing OLR (max 35% w/w), whereas the AS-SBR reduced the PHA content (max 20% w/w) above an OLR threshold of 2 kgCOD/m3∙d. In contrast, in the AGS the increase of OLR resulted in a significant decrease in PHA productivity (max 14% w/w) and a concomitant increase of extracellular polymers (EPS) production (max 75% w/w). Results demonstrated that organic carbon was mainly driven towards the intracellular storage pathway in the AS-SBR (max yield 51%) and MBR (max yield 61%), whereas additional stressors in AGS (e.g., hydraulic selection pressure, shear forces) induced bacteria to channel the COD into extracellular storage compounds (max yield 50%) necessary to maintain the granule's structure. The results of the present study indicated that full-aerobic feast/famine strategy was more suitable for flocculent sludge-based technologies, although biofilm-like systems could open new scenarios for other biopolymers recovery (e.g., EPS). Moreover, the AS-MBR resulted the most suitable technology for the integration of PHA production in a mainstream industrial wastewater treatment plant, considering the greater process stability and the potential reclamation of the treated wastewater.

Regulatory of salinity on assembly of activated sludge microbial communities and nitrogen transformation potential in industrial plants of the lower Yangtze River basin

This study aims to thoroughly investigate the impact mode of salinity carried by industrial wastewater on the anaerobic-anoxic-oxic (A2O) sludge in wastewater treatment plants (WWTPs). Through comprehensive investigation of the A2O stage activated sludge (AS) from 19 industrial WWTPs in the downstream area of the Yangtze River, China, A total of 38 samples of anaerobic sludge and oxic sludge were collected and analyzed. We found that salinity stress significantly inhibits the growth of the AS community, particularly evident in the anaerobic sludge community. Furthermore, the high-saline environment induces changes in the structure and functional patterns of the AS community, leading to intensive interactions and resource exchanges among microorganisms. Halophilic microorganisms may play a crucial role in this process, significantly impacting the overall community structure, especially in the oxic sludge community. Additionally, salinity stress not only suppresses the nitrogen transformation potential of the AS but also leads to the accumulation of nitrite, thereby increasing the emission potential of both NO and N2O, exacerbating the greenhouse effect of the A2O process in industrial WWTPs. The findings of this study provide necessary theoretical support for maintaining the long-term stable operation of the A2O sludge system in industrial WWTPs, reducing carbon footprint, and improving nitrogen removal efficiency.

Energy and resource recovery from a future aerobic granular sludge wastewater treatment plant and benefit analysis

The sustainable approach to energy and resource recovery from excess sludge is gaining traction. This study compared the benefits of methane production through anaerobic digestion (AD) and the recovery of alginate-like exopolymers (ALE)/phosphorus (P) from two types of aerobic granular sludge (AGS). Bacterial and algal-bacterial AGS produced similar methane amounts, around 292 and 287 mL/g-VSadded, respectively, over 30 days, with 72% and 80% biodegradability. After ALE extraction, the remaining AGS showed a 48–56% decrease in methane production without pH adjustment. However, a conceptual wastewater treatment plant (WWTP) processing 10,000 m3/d of wastewater with ALE/P and methane recovery yielded the highest net profits, approximately 66.3 thousand USD annually, when algal-bacterial AGS was used, compared to 59.2 thousand USD for the bacterial AGS-based WWTP. These findings provide valuable insights for developing a sustainable wastewater industry and future WWTP design.

Phytotoxicity and genotoxicity assessment of organic and inorganic contaminants detected in pharmaceutical industrial wastewaters using Vigna radiata and Allium cepa

The discharged effluent of pharmaceutical industrial wastewater treatment plants (PIWWTPs) exhibits substantial environmental toxicity due to the intricate combination of organic and inorganic pollutants. This study assessed the phytotoxicity, genotoxicity, and cytotoxicity of untreated and treated pharmaceutical industrial wastewater (PIWW). Most of the physicochemical parameters viz. COD, BOD, EC, sulfide, sulfate, nitrate, phosphate, grease, phenols, and metal concentrations viz. B, Cr, Ca, Cd, Cu, Zn, Pb, Hg, and As in untreated wastewater (UTW) were noted beyond the permissible limit and remained higher in treated wastewater (TW). The findings revealed that the performance of PIWWTP was woefully inadequate. The GC-MS spectra of UTW and TW revealed the presence of various organic contaminants. The toxicological studies showed that the UTW had a high degree of phytotoxicity, which persisted even after the treatment as it inhibited the seed germination in Vigna radiata. The seed germination was inhibited up to 70% and 50% tested at 50% concentration of UTW and TW respectively. Genotoxicity was measured by determining mitotic index and chromosomal aberrations in Allium cepa root apex grown in untreated and treated PIWW. Compared to the negative control, the mitotic index dropped to 85% and 75% at the 50% concentrations of UTW and TW, respectively. Chromosomal aberrations were also found in the cellular mass of root apex growing in both UTW and TW. According to the findings, it is unsafe for the environment to release PIWW that has not been properly treated, as this could pose serious risks to environmental health.

Olive mill wastewater co-treatment: Effect of (electro)Fenton processes and dilution ratio on moving bed biofilm reactor performance

The treatment of olive mill wastewater (OMW) represents still an open challenge because of its highly polluting load. One of the most affordable methods for small-medium mills is to send OMW to industrial wastewater treatment plants (IWTP). Accordingly, this work explored a strategy consisting of the biological co-treatment of real OMW and simulated urban wastewater by a moving bed biofilm reactor (MBBR), with and without (electro)Fenton pre-treatment, to simulate OMW treatment through a multi-barrier approach in an IWTP. The effluent of the MBBR without pre-treatment, despite the long period of operation of 18 months, was in compliance with the limit for total phenols (TPHs) of 0.5 mg/L only at a really low OMW's dilution ratio (DR) (1/4000 (v/v)). The Fenton oxidation (FO) and the electro-assisted Fenton (EAF) processes were investigated as pre-treatment of diluted OMW. FO resulted in good performances in terms of TPHs removal (81%) and improved biodegradability (final BOD5/COD ratio = 0.35) but in poor COD removal (24%). EAF was more effective (COD removal = 41%, TPHs removal = 85%, and final BOD5/COD ratio = 0.40) than FO. Therefore, EAF was finally investigated on undiluted OMW (COD removal = 56%, TPHs removal = 84%, and final BOD5/COD ratio = 0.62) and subsequently co-treated with simulated urban wastewater by MBBR, identifying 1/1000 as the optimal DR. The investigated multi-barrier approach is an interesting option for OMW co-treatment in IWTPs to successfully address the challenge of TPHs degradation and drastically reduce the volume of the biological process unit (4 times lower than MBBR treatment alone).

Microbiome comparisons reveal the core microorganisms and key nitrogen metabolic pathway involved in industrial nitrogen fertilizer wastewater treatment plants

Microbiomes from municipal wastewater treatment plants (WWTPs) have been widely investigated, but less attention has been paid to those in the industrial WWTPs. To compare the microbiomes involved in nitrogen fertilizer wastewater treatment, four WWTPs with different concentrations and types of pollutants, processes, and geographic locations were chosen. Diversity results revealed that microbial community was similar within the same WWTP, but different among the four WWTPs. CPCoA further demonstrated these differences (P = 0.022), implying that the diverse manufactured products acted as electron donors to create distinct ecological niches for denitrification. However, bacterial composition and functional profile were similar among four WWTPs (P > 0.05), and their abundance differed and fluctuated. More than 80 % of the dominant genera detected were present in all four WWTPs. And the core bacteria identified were Hyphomicrobium, Acinetobacter, Pedomicrobium, Methyloversatilis, Gp16, Thauera, and Moorella respectively, accounting for 19.524 % of total bacterial abundance. Forty-five nitrogen metabolism genes were active in four nitrogen cycle pathways (nitrification, assimilatory nitrate reduction, dissimilatory nitrate reduction, denitrification). The key genes were amoC (0.30 %), nasA (5.35 %), nirA (2.17 %), nirB (6.04 %), nirD (5.82 %), narG (3.87 %), narH (4.65 %), nirK (3.90 %), norB (3.32 %), nosZ (2.80 %). Hyphomicrobium, Thauera, Afipia, and Paracocccus were the hosts of denitrification genes, synergistically treating the nitrogen fertilizer wastewater to meet the discharge standard. These results suggested that microbial community structure in the nitrogen fertilizer industry is similar, helping further the understanding of the microbiota at an industry level though more samples are required to verify this.

Viral community distribution, assembly mechanism, and associated hosts in an industrial park wastewater treatment plant

Viruses manipulate bacterial community composition and impact wastewater treatment efficiency. Some viruses pose threats to the environment and human populations through infection. Improving the efficiency of wastewater treatment and ensuring the health of the effluent and receptor pools requires an understanding of how viral communities assemble and interact with hosts in wastewater treatment plants (WWTPs). We used metagenomic analysis to study the distribution, assembly mechanism, and sensitive hosts for the viral communities in raw water, anaerobic tanks, and returned activated sludge units of a large-scale industrial park WWTP. Uroviricota (53.42% ± 0.14%) and Nucleocytoviricota (26.1% ± 0.19%) were dominant in all units. Viral community composition significantly differed between units, as measured by β diversity (P = 0.005). Compared to raw water, the relative viral abundance decreased by 29.8% in the anaerobic tank but increased by 9.9% in the activated sludge. Viral community assembly in raw water and anaerobic tanks was predominantly driven by deterministic processes (MST <0.5) versus stochastic processes (MST >0.5) in the activated sludge, indicating that differences in diffusion limits may fundamentally alter the assembly mechanisms of viral communities between the solid and liquid-phase environments. Acidobacteria was identified as the sensitive host contributing to viral abundance, exhibiting strong interactions and a mutual dependence (degree = 59). These results demonstrate the occurrence and prevalence of viruses in WWTPs, their different assembly mechanism, and sensitive hosts. These observations require further study of the mechanisms of viral community succession, ecological function, and roles in the successive wastewater treatment units.

Niche differentiation in microbial communities with stable genomic traits over time in engineered systems.

Microbial communities in full-scale engineered systems undergo dynamic compositional changes. However, mechanisms governing assembly of such microbes and succession of their functioning and genomic traits under various environmental conditions are unclear. In this study, we used the activated sludge and anaerobic treatment systems of four full-scale industrial wastewater treatment plants as models to investigate the niches of microbes in communities and the temporal succession patterns of community compositions. High-quality representative metagenome-assembled genomes revealed that taxonomic, functional, and trait-based compositions were strongly shaped by environmental selection, with replacement processes primarily driving variations in taxonomic and functional compositions. Plant-specific indicators were associated with system environmental conditions and exhibited strong determinism and trajectory directionality over time. The partitioning of microbes in a co-abundance network according to groups of plant-specific indicators, together with significant between-group differences in genomic traits, indicated the occurrence of niche differentiation. The indicators of the treatment plant with rich nutrient input and high substrate removal efficiency exhibited a faster predicted growth rate, lower guanine-cytosine content, smaller genome size, and higher codon usage bias than the indicators of the other plants. In individual plants, taxonomic composition displayed a more rapid temporal succession than functional and trait-based compositions. The succession of taxonomic, functional, and trait-based compositions was correlated with the kinetics of treatment processes in the activated sludge systems. This study provides insights into ecological niches of microbes in engineered systems and succession patterns of their functions and traits, which will aid microbial community management to improve treatment performance.