Next Article in Journal
Spatio-Temporal Morphodynamics of a Nourished Sandy Shore Based on LiDAR Measurements
Previous Article in Journal
Morphometric Analysis Using Geographical Information System and the Relationship with Precipitation Quantiles of Major Dam Basins in South Korea
Previous Article in Special Issue
Composition, Dynamic Changes, and Carbon Sequestration Effects of Organic Carbon in the Water of a Penaeus vannamei Culture Pond
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 16
Issue 7
10.3390/w16071054
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Treatment Effect of Long-Term Subsurface-Flow Constructed Wetland on Mariculture Water and Analysis of Wetland Bacterial Community

by
Chen Chen
1,
Guijun Yang
2,*,
Xuechu Chen
3,*,
Pengquan Li
1,
Jingfei Chen
1,
Maocang Yan
1 and
Chong Guo
2
1
Zhejiang Key Laboratory of Exploitation and Preservation of Costal Bio-Resource, Zhejiang Mariculture Research Institute, Wenzhou 325000, China
2
School of Environment and Ecology, Jiangnan University, Wuxi 214122, China
3
School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
*
Authors to whom correspondence should be addressed.
Water 2024, 16(7), 1054; https://doi.org/10.3390/w16071054
Submission received: 6 February 2024 / Revised: 21 March 2024 / Accepted: 27 March 2024 / Published: 6 April 2024
(This article belongs to the Special Issue Water Quality in Aquaculture Production)
Browse Figures
Versions Notes

Abstract

:
To improve the quality of natural seawater to meet the needs of aquaculture production, a large-scale subsurface-flow constructed wetland (HSFCW) was constructed and operated stably for 2 years to understand the reasons for its purification effect on natural seawater. The results of the study showed that the system could maintain a high purification effect on natural seawater during aquaculture; the average removal rates of COD, TSS, TN, NH4+-N, and DON (organic nitrogen) were 22.29%, 49.33%, 36.94%, 10.88%, and 44.08%, respectively. Additionally, the HSFCW could effectively remove harmful algae such as Cyanobacteria; the removal rate of dominant algae species in Cyanobacteria was 90.33–97.93%. The pyrosequencing of 16S ribosomal DNA revealed that Proteobacteria, Nitrospirae, and Chloroflexi were the main and key bacterial phyla in the system. Members of these key gates are regarded as playing important roles in resisting water purification. The study results suggest that the subsurface-flow wetland system can effectively improve seawater quality and reduce the density of harmful algae cells.

1. Introduction

The global aquaculture industry produced around 82 million tons in 2018, with 30.8 million tons from marine aquaculture, which accounted for 37.5% of global aquaculture production [1]. Experts have predicted significant future growth in the percentage of aquaculture coming from marine areas [2]. Meanwhile, land-based and nearshore aquaculture systems have widely been accepted and promoted [3]. Seawater is usually extracted from offshore areas for aquaculture. However, in recent decades, offshore seawater quality has deteriorated, such as from eutrophication, and influent water from offshore areas needs to be properly treated before entering the aquaculture system [4].
As an ecofriendly technology, constructed wetlands (CWs) have the advantages of less secondary pollution, low construction cost, and simple management and operation [5,6,7]. Therefore, CWs are widely used in treating water pollution from agricultural nonpoint sources. CWs rely on the simultaneous occurrence of several complicated physical, chemical, and biological processes for removing pollutants, including sorption and sedimentation, photolysis, hydrolysis, volatilization, plant uptake and accumulation, plant exudation, and microbial degradation [6,8,9]. Wu, et al. [10] conducted long-term monitoring of secondary effluent treatment from wastewater treatment plants by a continuous large-scale constructed wetland system. The average removal efficiency of COD and NH4+-N reached 53% and 72%, respectively. At that time, most of the existing research was based on freshwater constructed wetlands, and there was a lack of long-term tracking analysis of large-scale seawater constructed wetland systems.
Microorganisms play a crucial role in constructed wetland systems inorganic pollutant degradation, nutrient fixation, and transformation [11]. In the past, the research on microbial community structure in different functional blocks of CWs mainly focused on the short-term operation of CWs, which lacked study of the long-term operation of CWs, especially seawater CWs [12].
Therefore, a large-scale seawater constructed wetland system that had been operating stably for 2 years was monitored in this study. The specific objectives were to (1) evaluate the removal efficiency of conventional pollutants and algae in low-polluted seawater by long-term operation of large-scale wetland systems; (2) explore the spatial distribution of bacterial communities in various areas of the wetland system; and (3) analyze the relationship between bacterial community and pollutant removal.

2. Materials and Methods

2.1. Subsurface-Flow Wetland System

The wetland was built to meet the demand for aquaculture water in the Yongxing Base of Zhejiang Marine Aquaculture Research Institute (Wenzhou, China). The total land area of this base is approximately 18.5 hectares. The Base mainly conducts Litopenaeus vannamei breeding and shellfish nursery work.
A large horizontal subsurface-flow constructed wetland (HSFCW) was built in August 2017 with an area of 1224 m2. The wetland mainly treated natural seawater from Wenzhou Bay, with a daily treatment capacity of 1800 m3. The hydraulic retention time (HRT) was around 12 h, and the hydraulic load (HL) was 1.47 t/m2·d−1. The system was divided into two functional zones: an influent sedimentation area and a filler treatment area (Figure 1). The UPVC pipe with a diameter of 20 mm was laid at the bottom of the filler treatment area for aeration, and the aeration area accounted for one-third of the total filler treatment area. The aeration zone was aerated throughout the day, and the aeration intensity was 12.5 m3/min. The filling area was filled with gravel (particle size 3–5 cm, filling height 0.6 m) and gravel (particle size 6–8 cm, filling height 0.6 m) from bottom to top, and the inlet water passed through 20–30 cm of surface layer substrate. In this constructed wetland, mangrove Kandelia obovata was the main plant with a planting density of 30 plants/m2 (Figure 1).
The experiment was operated from April to December 2020 (production and breeding activities were not carried out from January to March due to low temperature), and the system had been operating stably for 2 years. During the operation of the system, the water temperature was 11.5–32.5 °C, pH was 8.14 ± 0.17, salinity was 19.4 ± 0.3‰, and dissolved oxygen (DO) was 4.89–7.59 mg /L.

2.2. Water Sampling and Analytical Methods

The effect of the constructed wetland on purifying natural seawater was evaluated by monitoring influent (S-1) and effluent (S-2) water quality. Chemical indexes of water quality included total nitrogen (TN), ammonia nitrogen (NH4+-N), nitrite-nitrogen (NO2−-N), nitrate-nitrogen (NO3−-N), and chemical oxygen demand (COD). All chemical indicator tests were based on standard methods [13]. Total suspended solid (TSS) was tested by the gravimetric method. The species and density of phytoplankton were determined according to Hu‘s method [14]. Water quality was tested bimonthly, and four groups of parallel sampling were used for water quality analysis at each sampling point.
To study the microbial community status of the subsurface wetland system, intermediate water was collected from the water inlet (S-1) and outlet (S-2); additionally, substrates were collected from the aerobic (J-O) and anaerobic (J-H) zones in the packed bed during August 2020. Three samples were randomly selected in each designated area and mixed for microbial analysis. The biofilms on the samples were separated by an ultrasonic cleaner, and then the suspensions were filtered with 0.22 μm filter membranes. After filtration, the sample material remaining on the filter membrane was the biofilm. Finally, the filter papers were stored in an ultralow temperature refrigerator at −80 °C for subsequent DNA extraction experiments.

2.3. DNA Extraction and PCR Amplification

The extraction of biofilm DNA was performed using a water sample genomic DNA rapid extraction kit, and then the extracted genomic DNA was detected by 1% Agarose gel electrophoresis. The V4–V5 region of the 16S rRNA gene was amplified by PCR using the primers 515F: 5′-GTGCCAGCMGCCGCGG-3′ and 907R: 5′-CCGTCAATTCMTTRAGTTT-3′. Then, the amplified PCR fragments were detected by 2% Agarose gel electrophoresis. Finally, the PCR products were quantified by the QuantiFluorTM-ST blue fluorescence quantitative system (Promega Company, Beijing, China). According to the sequencing requirements for each sample, the corresponding proportion was mixed to construct the Miseq gene library.
The high-throughput sequencing platform was Illumina Miseq PE250. The PE reads obtained by Miseq sequencing were spliced according to the overlap relationship, and the sequence quality was controlled and filtered. After distinguishing the samples, OTU clustering analysis and species taxonomy analysis were performed. When analyzing the composition of species structure, in order to prevent chlorophyll interference, the OTUs were counted after removing cyanobacteria and rare species.

2.4. Data Analysis

Origin 11.0 and SPSS18.0 were used for water quality data analysis. QIIME PE250 software was used to analyze α-biodiversity.

Average Removal Amount

Average removal amount (ARA) = [ (Cin × Qin) − (Cout − Qout)/Warea]
where the ARA is in a unit of g/m2·d−1, where Warea is the area of the subsurface-flow wetland system (m2); Cin and Cout are the average mass concentration of influent and effluent (mg/L); and Qin and Qout are the average flow rate of influent and effluent (m3·d−1).

3. Results and Discussion

3.1. Variation in Water Quality

The purification effect of organic matter and suspended particulate matter in the subsurface-flow wetland is shown in Figure 2. The average concentration of COD in the influent was 3.25 (±0.51) mg/L. According to China’s water standard GB 3097-1997 as a reference [15], the seawater belonged to the third category of water quality, which was not suitable for aquaculture without treatment (Table 1). The average concentration of COD in the effluent treated by the subsurface-flow wetland was 2.60 (±0.50) mg/L, and the water quality was upgraded to the second category. The average removal amount was 0.96 (±0.11) g/m2·d−1, and the average removal rate was 20.29 (±2.88) %. In the subsurface-flow wetland system, the physical processes of precipitation, matrix adsorption, filtration, and microbial biodegradation were the main ways organic matter in seawater was removed [16]. As an important evaluation index of water quality monitoring, COD could reflect the organic pollutants in water. Because the influent COD content was low, the system treatment effect was not obvious.
The clogging problem has always been an important factor affecting the long-term stable operation of wetland systems [17]. Therefore, to prevent the reduction in its water conductivity and removal effect, the system had been cleaned and maintained regularly every year since its establishment and operation. Previous studies have suggested that the maximum TSS load of a wetland system should be 15 g/m2·d−1 [18]. The removal amount of TSS was 12.27 (±2.74) g/m2·d−1, the average removal rate was 49.33 (±12.75) %, and the average concentration of effluent was less than 10 mg/L. The removal amount was 14.91 and 15.21 g/m2·d−1 in June and October, respectively.
Excessive nitrogen may affect the normal physiology and behavior of aquatic organisms [19]. It can be seen from Table 2 that the concentration of TN in the influent and effluent was 0.92–2.06 mg/L and 0.72–1.15 mg/L, respectively. The average removal amount was 0.78 (±0.43) g/m2·d−1, and the average removal rate was 36.94%. The concentration of DIN (dissolved inorganic nitrogen) in the influent was 0.19–0.29 mg/L, and the effluent was 0.17–0.24 mg/L. The average removal amount and removal rate of DIN was 0.04 g/m2·d−1 and 10.88%. The concentration of DON (dissolved organic nitrogen) in the influent and the effluent was 0.69–1.77 mg/L and 0.51–0.93 mg/L. The average removal amount was 0.74 g/m2·d−1, and the average removal rate was 41.82%. The removal rate of DON in the subsurface-flow wetland characterizes the mineralization intensity of organic nitrogen, and the removal rate was positively correlated with temperature [20]. In April, the total nitrogen concentration of the influent and effluent of the system was 0.92 (±0.02) mg/L and 0.75 (±0.05) mg/L, respectively, and the removal rate was only 17.8%. Due to higher temperatures and more active microbial activity from June to October, the TN removal rate remained at a high level, with the highest removal rate at 44.08%. The main ways of nitrogen removal in the subsurface-flow wetland system were ammonia volatilization, denitrification, deposition, and adsorption [21,22]. Related studies have shown that subsurface-flow wetland systems are suitable for the removal of nitrogen pollutants in rivers and lakes, and could maintain a high TN removal rate even under long-term operation [23].
The form of nitrogen in the influent was mainly DON, which accounted for 75.68–89.26%, while DIN accounted for 10.74–24.32% (Figure 3). After subsurface-flow wetland treatment, the proportion of organic nitrogen decreased, the proportion of inorganic nitrogen increased, and DIN in the effluent was mainly NO3−-N. The subsurface-flow wetland system had the most significant effect on the removal of DON, while for DIN, NH4+-N decreased from 0.11 (±0.03) mg/L to 0.06 (±0.02) mg/L and NO3−-N increased from 0.09 (±0.03) mg/L to 0.14 (±0.02) mg/L. It is generally believed that NO2−-N has high biological toxicity to aquatic organisms. Elevated NO2−-N can hinder biological growth and even induce death in aquatic organisms [24]. NO2−-N decreased from 0.028 (±0.021) mg/L to 0.006 (±0.003) mg/L during the monitoring period, and the average removal rate reached 78.54% (Figure 4).
Statistical analyses showed that the wetland system significantly reduced the concentrations of TSS, COD, TN, DON, NH4+-N, and NO2−-N in seawater (p < 0.05).

3.2. Variation in Phytoplankton Community Structure

Because various cyanobacteria and dinoflagellates released some toxic secondary metabolites (e.g., microcystins, nodularins), this process affected the taste and odor of the cultured organisms.
The subsurface-flow wetland system mainly achieved the removal of phytoplankton through precipitation, matrix adsorption, physical interception, flocculation precipitation, and microbial degradation [25]. The dominant species in influent and effluent were Microcystis (30,577.29 × 103 ind./L), Synechocystis (2673.70 × 103 ind./L); Phaeodactylum (24,030 × 103 ind./L), Melosira (135.30 × 103 ind./L), and Chlorophyta Dunaliella (148.69 × 103 ind./L) (Table 3).
The effect of the subsurface-flow wetland system on algae removal is shown in Figure 5. The wetland system had a significant removal effect on Cyanophyta and Pyrrophyta, and the average removal rates were 92.90% and 97.85%, respectively. The density of Cyanophyta in the influent increased first and then decreased with the seasons, while the removal rate of Cyanophyta in the subsurface-flow wetland system was stable. The density of Cyanophyta in the influent reached its highest value in June, 129.60 × 106 ind./L, and decreased to 3.64 × 106 ind./L after treatment by the subsurface-flow wetland (Figure 5a). The density of Pyrrophyta in the influent was low. In October and December, during the treatment by the subsurface-flow wetland system, the densities of Pyrrophyta were 0.41 × 106 ind./L and 0.66 × 106 ind./L, which were reduced to 0.02×106 ind./L and 0.003 × 106 ind./L, respectively (Figure 5b). The density of Bacillariophyta in the influent increased first and then decreased with the change in seasons. The density of algae was the highest in June, with an average of 105.61 × 106 ind./L. The density of Bacillariophyta decreased to 0.26 × 106 ind./L after subsurface-flow wetland treatment. When the Bacillariophyta density in the influent was low, the Bacillariophyta density in the effluent increased. When the density of Bacillariophyta in the influent was high, the removal efficiency of Bacillariophyta in the subsurface-flow wetland system was stable, and the average removal rate was 97.24% from June to December (Figure 5c). The density of Chlorophyta in the influent was low. From April to June, the density of Chlorophyta in the influent was less than 0.10 × 106 ind./L. After treatment in the subsurface-flow wetland, the density of Chlorophyta increased. After subsurface-flow wetland treatment, the density of Chlorophyta clearly decreased, and the average removal rate was 84.17% (Figure 5d).
Currently, chemical measures are usually used to regulate the planktonic state of the water, such as the addition of copper sulfate [26,27]. Although the treatment effect is good, there are chemical residues and cost problems. From the point of view of treatment effect, a constructed wetland is a better alternative scheme, which has a better removal effect on cyanobacteria and greatly reduces the operation cost. However, since the removal of harmful algae involved a series of biological and physicochemical processes, it is difficult to determine which pathway plays a major role in the system.

3.3. Characteristics of Microbial Communities

3.3.1. Richness and Diversity of Microbial Communities

Table 4 shows the different indices of microbial communities among different sampling points in the constructed wetland. The Coverage index of all samples reached more than 0.98, indicating that the measured OTUs (operational taxonomic units) represented the actual situation of the microorganisms in each sample, and the data were comparable. The Shannon index reflected the microbial diversity of samples. Chao 1 and Ace reflected the microbial richness of the samples [28]. The significance of the sample Shannon index was J-H > J-O > S-2 > S-1, and a similar value tendency was found for the Chao 1 and Ace indices. The results showed that the microbial diversity and richness of the substrate were significantly greater than those measured for the water sample. Under anaerobic conditions, the species diversity and richness of the epiphytic bacteria were higher. After the aquaculture water was treated by the subsurface-flow wetland, the species diversity and richness increased.

3.3.2. Composition and Distribution of Microbial Communities

To further analyze the bacterial community structure of the system matrix and water samples, the sample differences were compared based on phylum, family, and genus classification. Figure 6 shows that the microbial community in the subsurface-flow wetland had a high diversity at the phylum level, while the bacterial community in the aquaculture water had a low diversity at the phylum level. The matrix aerobic zone and anaerobic zone in the subsurface-flow wetland had similar microbial community composition. Proteobacteria, Chloroflexi, Firmicutes, and Nitrospira were the main bacterial phyla. Among them, Proteobacteria had the greatest abundance, accounting for 33.82% and 36.22% of the bacterial communities in the aerobic and anaerobic zones, respectively. Proteobacteria were mostly obligate or facultative anaerobic metabolic bacteria, which were the dominant phylum in the subsurface-flow wetland system. Nitrifying bacteria and most denitrifying bacteria play an important role in wetland nitrogen removal [29,30]. Studies have shown that Proteobacteria is the dominant phylum in wetlands, usually accounting for 30–40% of all flora [31]. In the matrix microbial community composition in this study, Proteobacteria accounted for more than 30%, which is consistent with previous studies [32]. The microorganisms from the phylum Chloroflexi accounted for a large proportion of the system flora, but its value in the system is not yet clear.
Firmicutes are common in anaerobic nitrification reactors similar to constructed wetlands, where functional bacteria capable of degrading macromolecular organic matter exist [33]. Nitrospira, comprising aerobic autotrophic nitrite-oxidizing bacteria, plays an important role in the nitrification process. The richness in the distribution of Nitrospira is the main reason for the removal of nitrogen nutrients [34]. In the microbial community structure of water samples S-1 and S-2, the microbial communities in natural seawater were mainly composed of Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, and Planctomycetes. The subsurface-flow wetland might promote the growth of Actinobacteria, Bacteroidetes, and Planctomycetes, but inhibit the growth of Proteobacteria and Firmicutes.
A total of 305 families were identified from the database, including 21 dominant families with relative abundance greater than 2%, as shown in Figure 7. The dominant bacteria filling the matrix were Nitrospiraceae, Saprospiraceae, Anaerolineaceae, and Flavobacteriaceae. Nitrospiraceae was the only established family in Nitrospirae, including Nitrospira, Leptospirillum, and Thermodesulfovibrio. Only Nitrospira was detected in the subsurface system. Nitrospira is widely distributed in aerobic wetland systems. It is the main bacteria known in nature that catalyzes nitrite oxidation and is crucial to the biogeochemical nitrogen cycle [35]. Saprospiraceae is often detected in the activated sludge of wastewater treatment systems. Its isolated and in situ strains have the ability to hydrolyze and utilize carbon sources. The bacteria of this family play an important role in the decomposition of complex organic matter in the environment [36]. Saprospiraceae is the dominant family of bacteria on biofilms in the presence of AOM (algal organic matter), capable of hydrolyzing proteins [37] and usually coexisting with Flavobacteria [38]. In this system, Saprospiraceae and Flavobacteriaceae were the dominant families. Anaerolineaceae is widely found in natural ecosystems and is an important organic degradation bacteria under anaerobic conditions [39]. Rhodobacteraceae is often detected in marine aquaculture biofilters and macroalgae-associated microorganisms. Related studies have reported that Rhodobacteraceae and Flavobacteriaceae are key groups in biological flocculation systems [40]. Rhodospirillaceae is a large family of α-proteobacteria, and 12 genera were identified in the subsurface-flow wetland system. This family of bacteria is widely reported to have biohydrogen production capacity [41,42]. Dominant bacteria basically have an important pollutant degradation function, and may play a synergistic purification effect.
The top 10 genera in the matrix were analyzed for differences among groups, and the results are shown in Figure 8. The dominant genera in the microbial community of the subsurface-flow wetland were Nitrospira, norank _ o _ _ Ardenticatenales, Mycobacterium, etc. Among them, the relative abundance of Nitrospira, norank _ o _ _ Ardenticatenales, TB255 _ marine _ benthic _ group, and unclassified _ c _ _ Gammaproteobacteria were significantly different (p < 0.05). The relative abundance of Nitrospira in the anaerobic zone (8.23%) was significantly higher than that in the aerobic zone (4.25%) (p < 0.05). The relative abundance of norank _ o _ _ Ardenticatenales in the anaerobic zone (3.6%) was significantly lower than that in the aerobic zone (7.5%) (p < 0.05). Previous studies suggested that nitrification is catalyzed by AOB (ammonia-oxidizing bacteria) or AOA (ammonia-oxidizing archaea) and NOB (nitrite-oxidizing bacteria), and recent studies have found that Nitrospira is also a key component in the nitrogen cycling microbial community, with the global distribution of Nitrospira representing the most diverse known NOB group [43].

4. Conclusions

In this study, the pollutant removal capacity and bacterial community status of the seawater subsurface-flow constructed wetland with stable operation for 2 years were investigated. It was found that the system had a good removal effect on conventional pollutants (TSS, COD, TN, DON, NH4+-N and NO2−-N) and potentially harmful algae such as cyanobacteria during the stable operation of the subsurface-flow wetland system. Studies found that Nitrospiraceae, Saprospiraceae, Anaerolineaceae, Rhodobacteraceae, Flavobacteriaceae played synergistic roles in degradation in the removal of pollutants. In general, the seawater subsurface-flow wetland could significantly improve the water quality and met the demand of aquaculture water.
The abuse of antibiotics has always been a pain point in the aquaculture industry. If the large-scale constructed wetland system is used for the treatment of mariculture wastewater, the removal of antibiotics may be a good evaluation standard.

Author Contributions

Conceptualization, C.C.; Methodology, G.Y.; Data curation, J.C.; Writing—original draft, P.L. and C.G.; Writing—review & editing, G.Y.; Visualization, X.C.; Supervision, X.C.; Project administration, M.Y.; Funding acquisition, C.C. and M.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Wenzhou Major Scientific and Technological Innovation Research Project (Grant No. ZN2021001), Zhejiang Province Key R & D Program (2021C02025).

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ahmad, A.; Abdullah, S.R.S.; Abu Hasan, H.; Othman, A.R.; Ismail, N.I. Aquaculture industry: Supply and demand, best practices, effluent and its current issues and treatment technology. J. Environ. Manag. 2021, 287, 112271. [Google Scholar] [CrossRef] [PubMed]
  2. Hai, A.T.N.; Speelman, S. Economic-environmental trade-offs in marine aquaculture: The case of lobster farming in Vietnam. Aquaculture 2020, 516, 734593. [Google Scholar] [CrossRef]
  3. Troell, M.; Joyce, A.; Chopin, T.; Neori, A.; Buschmann, A.H.; Fang, J.-G. Ecological engineering in aquaculture—Potential for integrated multi-trophic aquaculture (IMTA) in marine offshore systems. Aquaculture 2009, 297, 1–9. [Google Scholar] [CrossRef]
  4. Luo, Y.; Liu, J.-W.; Wu, J.-W.; Yuan, Z.; Zhang, J.-W.; Gao, C.; Lin, Z.-Y. Comprehensive Assessment of Eutrophication in Xiamen Bay and Its Implications for Management Strategy in Southeast China. Int. J. Environ. Res. Public Health 2022, 19, 3055. [Google Scholar] [CrossRef]
  5. Kataki, S.; Chatterjee, S.; Vairale, M.G.; Dwivedi, S.K.; Gupta, D.K. Constructed wetland, an eco-technology for wastewater treatment: A review on types of wastewater treated and components of the technology (macrophyte, biolfilm and substrate). J. Environ. Manag. 2021, 283, 111986. [Google Scholar] [CrossRef] [PubMed]
  6. Wu, H.; Zhang, J.; Ngo, H.H.; Guo, W.; Hu, Z.; Liang, S.; Fan, J.; Liu, H. A review on the sustainability of constructed wetlands for wastewater treatment: Design and operation. Bioresour. Technol. 2015, 175, 594–601. [Google Scholar] [CrossRef] [PubMed]
  7. Wu, S.; Kuschk, P.; Brix, H.; Vymazal, J.; Dong, R. Development of constructed wetlands in performance intensifications for wastewater treatment: A nitrogen and organic matter targeted review. Water Res. 2014, 57, 40–55. [Google Scholar] [CrossRef]
  8. Parde, D.; Patwa, A.; Shukla, A.; Vijay, R.; Killedar, D.J.; Kumar, R. A review of constructed wetland on type, treatment and technology of wastewater. Environ. Technol. Innov. 2021, 21, 101261. [Google Scholar] [CrossRef]
  9. Vymazal, J.; Zhao, Y.; Mander, U. Recent research challenges in constructed wetlands for wastewater treatment: A review. Ecol. Eng. 2021, 169, 106318. [Google Scholar] [CrossRef]
  10. Wu, H.; Zhang, J.; Guo, W.; Liang, S.; Fan, J. Secondary effluent purification by a large-scale multi-stage surface-flow constructed wetland: A case study in northern China. Bioresour. Technol. 2018, 249, 1092–1096. [Google Scholar] [CrossRef]
  11. Zhang, Q.-Q.; Ying, G.-G.; Pan, C.-G.; Liu, Y.-S.; Zhao, J.-L. Comprehensive Evaluation of Antibiotics Emission and Fate in the River Basins of China: Source Analysis, Multimedia Modeling, and Linkage to Bacterial Resistance. Environ. Sci. Technol. 2015, 49, 6772–6782. [Google Scholar] [CrossRef]
  12. Shan, A.; Wang, W.; Kang, K.J.; Hou, D.; Luo, J.; Wang, G.; Pan, M.; Feng, Y.; He, Z.; Yang, X. The Removal of Antibiotics in Relation to a Microbial Community in an Integrated Constructed Wetland for Tail Water Decontamination. Wetlands 2020, 40, 993–1004. [Google Scholar] [CrossRef]
  13. Jia, L.; Gou, E.; Liu, H.; Lu, S.; Wu, S.; Wu, H. Exploring Utilization of Recycled Agricultural Biomass in Constructed Wetlands: Characterization of the Driving Force for High-Rate Nitrogen Removal. Environ. Sci. Technol. 2019, 53, 1258–1268. [Google Scholar] [CrossRef]
  14. Hu, H. The Freshwater Algae of China: Systematics, Taxonomy and Ecology; Science Press: Beijing, China, 2006. [Google Scholar]
  15. GB 3097-1997; General Administration of Quality Supervision, Inspection and Quarantine of People’s Republic of China. Sea Water Quality Standard: Beijing, China, 1997.
  16. Wang, X.; Tian, Y.; Zhao, X.; Peng, S.; Wu, Q.; Yan, L. Effects of aeration position on organics, nitrogen and phosphorus removal in combined oxidation pond-constructed wetland systems. Bioresour. Technol. 2015, 198, 7–15. [Google Scholar] [CrossRef]
  17. Shi, Y.; Zhang, G.; Liu, J.; Zhu, Y.; Xu, J. Performance of a constructed wetland in treating brackish wastewater from commercial recirculating and super-intensive shrimp growout systems. Bioresour. Technol. 2011, 102, 9416–9424. [Google Scholar] [CrossRef]
  18. Muller, V. Betriebssicherheit von Pflanzenklaranlagen. Wasserwirtsch. Wassertech. 2000, 32–34. [Google Scholar]
  19. Banerjee, S.; Maity, S.; Guchhait, R.; Chatterjee, A.; Biswas, C.; Adhikari, M.; Pramanick, K. Toxic effects of cyanotoxins in teleost fish: A comprehensive review. Aquat. Toxicol. 2021, 240, 105971. [Google Scholar] [CrossRef]
  20. Huang, J.; Cai, W.; Zhong, Q.; Wang, S. Influence of temperature on micro-environment, plant eco-physiology and nitrogen removal effect in subsurface flow constructed wetland. Ecol. Eng. 2013, 60, 242–248. [Google Scholar] [CrossRef]
  21. Wang, T.; Xiao, L.; Lu, H.; Lu, S.; Li, J.; Guo, X.; Zhao, X. Nitrogen removal from summer to winter in a field pilot-scale multistage constructed wetland-pond system. J. Environ. Sci. 2022, 111, 249–262. [Google Scholar] [CrossRef]
  22. Wang, Y.; Li, Q.; Zhang, W.; Wang, S.; Peng, H. Pollutants removal efficiency assessment of constructed subsurface flow wetlands in lakes with numerical models. J. Hydrol. 2021, 598, 126289. [Google Scholar] [CrossRef]
  23. Jozwiakowski, K.; Bugajski, P.; Kurek, K.; Caceres, R.; Siwiec, T.; Jucherski, A.; Czekala, W.; Kozlowski, K. Technological reliability of pollutant removal in different seasons in one-stage constructed wetland system with horizontal flow operating in the moderate climate. Sep. Purif. Technol. 2020, 238, 116439. [Google Scholar] [CrossRef]
  24. Kroupova, H.K.; Valentova, O.; Svobodova, Z.; Sauer, P.; Machova, J. Toxic effects of nitrite on freshwater organisms: A review. Rev. Aquac. 2018, 10, 525–542. [Google Scholar] [CrossRef]
  25. Hernandez-Crespo, C.; Gargallo, S.; Benedito-Dura, V.; Nacher-Rodriguez, B.; Rodrigo-Alacreu, M.A.; Martin, M. Performance of surface and subsurface flow constructed wetlands treating eutrophic waters. Sci. Total Environ. 2017, 595, 584–593. [Google Scholar] [CrossRef]
  26. Buley, R.P.; Gladfelter, M.F.; Fernandez-Figueroa, E.G.; Wilson, A.E. Complex effects of dissolved organic matter, temperature, and initial bloom density on the efficacy of hydrogen peroxide to control cyanobacteria. Environ. Sci. Pollut. Res. 2023, 30, 43991–44005. [Google Scholar] [CrossRef]
  27. Kinley-Baird, C.; Calomeni, A.; Berthold, D.E.; Lefler, F.W.; Barbosa, M.; Rodgers, J.H.; Laughinghouse, H.D. Laboratory-scale evaluation of algaecide effectiveness for control of microcystin-producing cyanobacteria from Lake Okeechobee, Florida (USA). Ecotoxicol. Environ. Saf. 2021, 207, 111233. [Google Scholar] [CrossRef]
  28. Zhang, T.; Shao, M.-F.; Ye, L. 454 Pyrosequencing reveals bacterial diversity of activated sludge from 14 sewage treatment plants. ISME J. 2012, 6, 1137–1147. [Google Scholar] [CrossRef]
  29. Guan, W.; Yin, M.; He, T.; Xie, S. Influence of substrate type on microbial community structure in vertical-flow constructed wetland treating polluted river water. Environ. Sci. Pollut. Res. 2015, 22, 16202–16209. [Google Scholar] [CrossRef]
  30. Liao, X.; Chen, C.; Zhang, J.; Dai, Y.; Zhang, X.; Xie, S. Operational performance, biomass and microbial community structure: Impacts of backwashing on drinking water biofilter. Environ. Sci. Pollut. Res. 2015, 22, 546–554. [Google Scholar] [CrossRef]
  31. Santos, F.; Ribeiro de Almeida, C.M.; Ribeiro, I.; Ferreira, A.C.; Mucha, A.P. Removal of veterinary antibiotics in constructed wetland microcosms Response of bacterial communities. Ecotoxicol. Environ. Saf. 2019, 169, 894–901. [Google Scholar] [CrossRef]
  32. Ansola, G.; Arroyo, P.; Saenz de Miera, L.E. Characterisation of the soil bacterial community structure and composition of natural and constructed wetlands. Sci. Total Environ. 2014, 473, 63–71. [Google Scholar] [CrossRef]
  33. Liu, Y.; Zhang, J.; Zhao, L.; Li, Y.; Dai, Y.; Xie, S. Distribution of sediment ammonia-oxidizing microorganisms in plateau freshwater lakes. Appl. Microbiol. Biotechnol. 2015, 99, 4435–4444. [Google Scholar] [CrossRef]
  34. Dong, W.; Lu, G.; Yan, L.; Zhang, Z.; Zhang, Y. Characteristics of pellets with immobilized activated sludge and its performance in increasing nitrification in sequencing batch reactors at low temperatures. J. Environ. Sci. 2016, 42, 202–209. [Google Scholar] [CrossRef]
  35. Zhang, Q.; Yang, Y.Q.; Chen, F.R.; Zhang, L.L.; Ruan, J.J.; Wu, S.J.; Zhu, R.L. Effects of hydraulic loading rate and substrate on ammonium removal in tidal flow constructed wetlands treating black and odorous water bodies. Bioresour. Technol. 2021, 321, 124468. [Google Scholar] [CrossRef]
  36. Xia, Y.; Kong, Y.; Thomsen, T.R.; Nielsen, P.H. Identification and ecophysiological characterization of epiphytic protein-hydrolyzing Saprospiraceae (“Candidatus epiflobacter” spp.) in activated sludge. Appl. Environ. Microbiol. 2008, 74, 2229–2238. [Google Scholar] [CrossRef]
  37. Jeon, Y.; Li, L.; Calvillo, J.; Ryu, H.; Domingo, J.W.S.; Choi, O.; Brown, J.; Seo, Y. Impact of algal organic matter on the performance, cyanotoxin removal, and bio fi lms of biologically-active fi ltration systems. Water Res. 2020, 184, 116120. [Google Scholar] [CrossRef]
  38. Kim, N.-K.; Oh, S.; Liu, W.-T. Enrichment and characterization of microbial consortia degrading soluble microbial products discharged from anaerobic methanogenic bioreactors. Water Res. 2016, 90, 395–404. [Google Scholar] [CrossRef]
  39. Wang, Q.; Liu, W.; Yuan, X.; Wang, R.; Liu, L.; Li, H.; Zhao, C.; Kong, Q. Characteristics of Bacterial and Archaeal Communities in Microbial-Enhanced Constructed Wetlands under NaCl Stress. Clean-Soil Air Water 2022, 50, 2100152. [Google Scholar] [CrossRef]
  40. Wei, G.; Shan, D.; Li, G.; Li, X.; Tian, R.; He, J.; Shao, Z. Prokaryotic communities vary with floc size in a biofloc-technology based aquaculture system. Aquaculture 2020, 529, 735632. [Google Scholar] [CrossRef]
  41. Mishra, P.; Krishnan, S.; Rana, S.; Singh, L.; Sakinah, M.; Ab Wahid, Z. Outlook of fermentative hydrogen production techniques: An overview of dark, photo and integrated dark-photo fermentative approach to biomass. Energy Strategy Rev. 2019, 24, 27–37. [Google Scholar] [CrossRef]
  42. Meky, N.; Elreedy, A.; Ibrahim, M.G.; Fujii, M.; Tawfik, A. Intermittent versus sequential dark-photo fermentative hydrogen production as an alternative for bioenergy recovery from protein-rich effluents. Energy 2021, 217, 119326. [Google Scholar] [CrossRef]
  43. Daims, H.; Lebedeva, E.V.; Pjevac, P.; Han, P.; Herbold, C.; Albertsen, M.; Jehmlich, N.; Palatinszky, M.; Vierheilig, J.; Bulaev, A.; et al. Complete nitrification by Nitrospira bacteria. Nature 2015, 528, 504–509. [Google Scholar] [CrossRef]
Water 16 01054 g001
Figure 1. The plane structure of the subsurface-flow wetland: (a) inlet sedimentation area; (b) filler treatment area.
Figure 1. The plane structure of the subsurface-flow wetland: (a) inlet sedimentation area; (b) filler treatment area.
Water 16 01054 g001
Water 16 01054 g002
Figure 2. Removal effect on COD (a) and TSS (b) in the HSFCW (S-1: inlet, S-2: outlet).
Figure 2. Removal effect on COD (a) and TSS (b) in the HSFCW (S-1: inlet, S-2: outlet).
Water 16 01054 g002
Water 16 01054 g003
Figure 3. Changes in DON (a) and DIN (b) in the HSFCW (S-1: inlet, S-2: outlet).
Figure 3. Changes in DON (a) and DIN (b) in the HSFCW (S-1: inlet, S-2: outlet).
Water 16 01054 g003
Water 16 01054 g004
Figure 4. Removal effect on TN (a); NO3−-N (b); NO2−-N (c); and NH4+-N (d) in the HSFCW (S-1: inlet, S-2: outlet).
Figure 4. Removal effect on TN (a); NO3−-N (b); NO2−-N (c); and NH4+-N (d) in the HSFCW (S-1: inlet, S-2: outlet).
Water 16 01054 g004
Water 16 01054 g005
Figure 5. Removal effect on main algae: (a) Cyanophyta; (b) Bacillariophyta; (c) Chlorophyta; and (d) Pyrrophyta in the HSFCW (S-1: inlet, S-2: outlet).
Figure 5. Removal effect on main algae: (a) Cyanophyta; (b) Bacillariophyta; (c) Chlorophyta; and (d) Pyrrophyta in the HSFCW (S-1: inlet, S-2: outlet).
Water 16 01054 g005
Water 16 01054 g006
Figure 6. Community structure composition of different samples (phylum level) (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
Figure 6. Community structure composition of different samples (phylum level) (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
Water 16 01054 g006
Water 16 01054 g007
Figure 7. Community structure composition of different samples (Class level) (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
Figure 7. Community structure composition of different samples (Class level) (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
Water 16 01054 g007
Water 16 01054 g008
Figure 8. The relative abundances of the top 10 dominant genera from the J-O and J-H bacterial communities (J-O: aerobic zone, J-H: anaerobic zone, ** p < 0.01, * p < 0.05).
Figure 8. The relative abundances of the top 10 dominant genera from the J-O and J-H bacterial communities (J-O: aerobic zone, J-H: anaerobic zone, ** p < 0.01, * p < 0.05).
Water 16 01054 g008
Table 1. Seawater quality standard.
Table 1. Seawater quality standard.
GradeCOD≤
(mg/L)		DIN≤
(mg/L)		Applicable Site
I20.20Marine fishery waters
II30.30Aquaculture areas
III40.40Industrial water function zone
IV50.50Ocean port waters
Table 2. The removal effect of nitrogen nutrients by the HSFCW.
Table 2. The removal effect of nitrogen nutrients by the HSFCW.
IndexAverage Inlet
(mg/L)		Average Outlet
(mg/L)		Average Removal Amount (g/m2·d−1)Average Removal (100%)
TN1.44 ± 0.410.90 ± 0.170.78 ± 0.4336.94
NO3−-N0.09 ± 0.030.13 ± 0.02−0.10 ± 0.08−52.02
NO2−-N0.03 ± 0.020.01 ± 0.000.03 ± 0.0278.54
NH4+-N0.11 ± 0.020.06 ± 0.020.07 ± 0.0245.07
DIN0.230.200.0410.88
DON1.210.700.7441.82
Table 3. Variation in the main algae density in influent and effluent.
Table 3. Variation in the main algae density in influent and effluent.
PhylaGeneraFrequencyInlet Abundance
(×103 ind./L)		Outlet Abundance
(×103 ind./L)		Average Removal
(100%)
CyanophytaMicrocystis630,577.292957.5590.33
Synechocystis52673.7065.9497.53
Stanieria477.331.6097.93
Oscillatoria42.4013.22−450.87
BacillariophytaPhaeodactylum524,030.0074.6499.69
Melosira5135.3025.5581.12
Cylindrotheca540.123.3391.70
Navicula639.7312.3968.81
Stephanopyxis638.9813.6664.96
ChlorophytaDunaliella4148.69691.80−365.25
Chlamydomonas36.874.8030.10
Ulothrix42.968.98−203.16
Platymonas119.603.6081.63
Alexandrium2346.9415.2895.60
Table 4. Comparison of species diversity, richness, and coverage index in water samples and substrates (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
Table 4. Comparison of species diversity, richness, and coverage index in water samples and substrates (S-1: inlet, S-2: outlet, J-O: aerobic zone, J-H: anaerobic zone).
SampleShannonAceChao1Coverage
S-13.4891315.871147.280.99
S-24.431903.071860.980.99
J-O6.253200.593200.450.98
J-H6.563782.293778.420.98
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, C.; Yang, G.; Chen, X.; Li, P.; Chen, J.; Yan, M.; Guo, C. Treatment Effect of Long-Term Subsurface-Flow Constructed Wetland on Mariculture Water and Analysis of Wetland Bacterial Community. Water 2024, 16, 1054. https://doi.org/10.3390/w16071054

AMA Style

Chen C, Yang G, Chen X, Li P, Chen J, Yan M, Guo C. Treatment Effect of Long-Term Subsurface-Flow Constructed Wetland on Mariculture Water and Analysis of Wetland Bacterial Community. Water. 2024; 16(7):1054. https://doi.org/10.3390/w16071054

Chicago/Turabian Style

Chen, Chen, Guijun Yang, Xuechu Chen, Pengquan Li, Jingfei Chen, Maocang Yan, and Chong Guo. 2024. "Treatment Effect of Long-Term Subsurface-Flow Constructed Wetland on Mariculture Water and Analysis of Wetland Bacterial Community" Water 16, no. 7: 1054. https://doi.org/10.3390/w16071054

APA Style

Chen, C., Yang, G., Chen, X., Li, P., Chen, J., Yan, M., & Guo, C. (2024). Treatment Effect of Long-Term Subsurface-Flow Constructed Wetland on Mariculture Water and Analysis of Wetland Bacterial Community. Water, 16(7), 1054. https://doi.org/10.3390/w16071054

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop