Open AccessArticle

New Insights into Changes in DOM Fractions in a Crab Farming Park and Key Factors in the Removal Process Using Fluorescence Spectra with MW-2DCOS and SEM

Ruijuan Zhou

¹,

Yan Hao

²,

Benxin Yu

³,

Junwen Hou

^3,4,

Kuotian Lu

^3,4,*

Fang Yang

⁴

and

Qingqian Li

^4,*

Ningxia Hui Autonomous Region Environmental Monitoring Center, Yinchuan 750027, China

School of Environment, Beijing Normal University, Beijing 100875, China

College of Water Sciences, Beijing Normal University, Beijing 100875, China

⁴

State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Authors to whom correspondence should be addressed.

Water 2024, 16(16), 2249; https://doi.org/10.3390/w16162249

Submission received: 5 July 2024 / Revised: 3 August 2024 / Accepted: 6 August 2024 / Published: 9 August 2024

(This article belongs to the Special Issue Water Environment Pollution and Control, Volume III)

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Figure 1
Generalized diagram of the crab farming industry park and locations of sampling sites. "> Figure 2
Variations in water quality parameters in different treatment process sections of the crab farming park. (a) pH, (b) EC, (c) DO, (d) NTU, (e) TOC, (f) CODCr, (g) CODMn, (h) NH3-N, (i) TN, and (j) TP. "> Figure 3
EEM spectroscopies of DOMs from the crab farming wastewater at sampling site. "> Figure 4
UV-visible absorbing spectra at 200–700 nm (a) and 230–500 nm (b). "> Figure 5
PARAFAC components identified from EEM spectroscopies of DOMs in the crab farming industry park. "> Figure 5 Cont.
PARAFAC components identified from EEM spectroscopies of DOMs in the crab farming industry park. "> Figure 6
Fmax (a) and proportions (b) of DOM fractions in the crab farming industry park. "> Figure 7
Synchronous and asynchronous maps as described by 2DCOS of DOMs from the crab farming park between C1 and C2 (a,b), C1 and C3 (c,d), C2 and C5 (e,f), C5 and C6 (g,h), C4 and C6 (i,j), C4 and C7 (k,l). "> Figure 8
MW-2DCOS map of a given unit in the crab farming park of C1 (a), C2 (b), C3 (c), C4 (d), C5 (e), C6 (f), and C7 (g). "> Figure 9
Synchronous map (a) and asynchronous map (b) of 2DCOS using UV-visible absorbing spectra at 230–450 nm. "> Figure 10
Plots based on the RDA of the interactions between response variables and environmental explanatory variables (solid arrows with red fonts are the response variables and hollow arrows with black fonts are the environmental explanatory variables). "> Figure 11
SEM modeling for the relationship between fluorescent components (C1, C2, C4, C5), water quality parameters (CODMn, DO), and spectroscopic indices (SUVA254), and contributions to removal efficiencies of FDOMs and TOC (R-FDOM, R-TOC). Significance levels of standardized path coefficient are: *** p < 0.001, ** p < 0.01, * p < 0.05. ">

Versions Notes

Abstract

With the explosion of crab farming in China, the urgent need to treat crab wastewater can never be overemphasized. Hence, in this study, excitation–emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC), moving window two-dimensional correlation spectroscopy (MW-2DCOS) and structural equation modeling (SEM) were employed to identify changes in the dissolved organic matter (DOM) fractions in a crab farming park and reveal latent factors associated with removal processes. Seven components (C1–C7) were extracted from DOMs by EEM-PARAFAC as follows: C1: microbial byproduct-like substances, C2: visible-tryptophan-like substances, C3: fulvic-like substances, C4: phenolic-like substances, C5: ultraviolet tyrosine-like substances, C6: D-tryptophan-like substances and C7: L-tryptophan-like substances. Interestingly, C7 (39.20%), a representative component of DOM in the crab farming pond, was deeply degraded in the aeration pond by aerobic microbes, whereas C6 was absent in the crab pond. According to 2DCOS, the changing order of the components was C7 → C4 → C6 → C5 → C2 → C1 → C3, and the changing order of the functional groups was carboxylic → phenolic → aromatic. As assessed by MW-2DCOS, the Fmax of the components, especially components C2, C5 and C6 (and with the exception of C4 and C7) exponentially increased in the aeration pond, where an accumulative effect occurred. C2, C5 and C7 were removed by 24.26%, 39.42% and 98.25% in the crab farming system, and were deeply degraded in the paddy-field, purification pond and aeration pond, respectively. As assessed by SEM, the latent factors of organic matter removal were C1, C2, C4, C5, SUVA254, COD_Mn and DO. This study could be conducive to comprehensively characterizing the removal of components and functional groups of DOMs in crab farming parks.

Keywords:

DOM; EEMs; MW-2DCOS; structural equation model; crab farming park

1. Introduction

Aquaculture has been extensively complimented, and could be a convincing alternative to the fishing industry [1]. Remarkably, the demand for aquatic products will likely exceed safety limits with the global population explosion [2]. In 2022, global production of aquaculture arrived at approximately 87.5 million tons, with China accounting for more than 60% of annual production [3]. Crab farming, a specific aquaculture area, commonly occurs in China, whose annual production was over 1 million tons in 2022 [4,5]. Such large-scale aquaculture produced a lot of aquaculture wastewater, which then entered the environment [6]. To achieve sustainable development, it is necessary to intensify aquaculture production and enhance the efficiency of wastewater treatment by utilizing technologies, such as water recycling systems, to provide appropriate treatment that maintains this valuable resource without burdening the environment excessively [7]. Crab farming can be associated with fresh or seawater aquaculture, but the annual production of the former is about 2.5 times more than the latter. Crab farming areas are mainly located in the eastern, central, northeast, northwestern, northern and southern areas of China, whose percentages of production are 67.28%, 21.40%, 9.47%, 0.85%, 0.62% and 0.39%, respectively [8].

The saline–alkali soils present in northwestern China could represent up to 96.11% of the national total, and exist widely across Xinjiang Uygur Autonomous Region, Ningxia Hui Autonomous Region, Inner Mongolia Autonomous Region, Qinghai Province and Gansu Province. The high salinity and alkalinity of these soils usually has negative impacts on many organisms, but they exhibit positive effects on the crab [9]. The strong oxidation in the saline–alkali environment might not only promote crab growth, but also develop its immune ability [10]. Hence, crab farming in the northwestern region of China has witnessed conspicuous growth in recent years.

However, a great deal of aquaculture wastewater has been generated from the intensification of crab aquaculture, which could lead to concern about overfeeding, metabolite residues and abuse of drugs and chemicals [11,12,13]. The wastewater in aquaculture ponds could inhibit the growth of crabs, and the wastewater discharged has a negative impact on the environment [14,15]. This could not only significantly undermine the sustainability of crab aquaculture, but also deteriorate the ecological environment. This problem is especially severe in northwest China, where the water shortage and supply crisis is a significant issue. The urgent need to treat the crab wastewater can never be overemphasized. This ordinarily includes on-site bioremediation and out-site treatment. The former refers to the treatment of the crab wastewater inside the pond during the culture period, while the latter relates to the treatment of wastewater outside of the contaminated site. Currently, combined approaches of both on-site and out-site treatments have been widely applied to process the crab wastewater [14,15,16]. Furthermore, aquaculture wastewater treatment technology mainly relies on physical technology, chemical technology and biotechnology. As microorganisms can effectively decompose organic substances in aquaculture wastewater, as well as reduce the content of ammonia, nitrogen, nitrite, hydrogen sulfide and other harmful substances, biotechnology has been widely used [17,18,19]. Previous studies have focused on the assessment of the efficiency of nutrient removal during aquaculture wastewater treatment [20,21]. However, it is still unclear how aquaculture wastewater treatment changes the molecular composition of dissolved organic matter (DOMs), which are the main nutrients for the organism and play a crucial role in regulating the movement and transformation of contaminants.

Hence, a crab aquaculture system with a dam pond and paddy-field was selected to investigate the removal of pollutants and DOMs in the crab wastewater and to explore the changing order of DOM components during the crab feeding period. In this study, a novel method involving fluorescence spectroscopy combined with two-dimensional correlation spectroscopy analysis (2D-COS) and moving window-2DCOS (MW-2DCOS), was employed to qualitatively characterize the changes in DOM fractions during the treatment of crab aquaculture wastewater. This study could be advantageous for comprehensively enhancing the efficiency of wastewater treatment, and consequently improving the efficiency of water recycling. The objectives of this study were (i) to assess the removal efficiencies of the pollutants and DOM fractions in the wastewater using excitation–emission matrix (EEM) fluorescence spectroscopy with parallel analysis (PARAFAC); (ii) to elaborate on the varying order of the components and functional groups, identified by UV-visible spectroscopy, of the successive units using 2D-COS and the changing magnitude of each unit using MW-2DCOS; and (iii) to trace the latent factors of wastewater purification in the crab farming park through redundancy analysis (RDA), thus exploring their contributions to the removal of DOMs by structural equation modeling (SEM).

2. Material and Methods

2.1. Sampling Collection and Measurement for Physico-Chemical Analysis

The sampling campaign was performed at a large-scale crab farming park located in Ningxia Hui Autonomous Region, China, whose area was approximately 200 ha. A combined unit, with 3 ponds/2 dams and a paddy-field, was used to treat the wastewater, which then returned to the crab-pond through the eco-ditch (Figure 1). The sampling sites were placed near the effluent of the crab pond (#1), aeration pond (#2), eco-purification (#3), paddy-field (#4) and eco-ditch (#5) (before reflux into the crab pond). At any given sampling site, triplicate samples were collected, with a 5 L DOM water sampler, into two acid-washed and sterilized glass bottles and shipped to the laboratory in a cooled container for analysis.

The pH, electrical conductivity (EC), dissolved oxygen (DO) and turbidity of each sample were measured in situ using a YSI 600 multi-probe (Xylem Inc., Yellow Springs, OH, USA). The chemical oxygen demand (COD_Cr), permanganate index (COD_Mn), ammonia nitrogen (NH₃-N), total nitrogen (TN) and total phosphorus (TP) were determined based on national standards [22]. The total organic carbon (TOC) of the sample was measured using a Shimadzu V-CPH analyzer.

2.2. Spectroscopy Measurements and Optical Indices

The samples were passed across glass fiber filters (Millipore, 0.45 μm fiber Ø), before spectroscopy measurements. Excitation-emission matrices (EEMs) spectroscopy was performed using a Hitachi fluorescence spectrophotometer (F-7000) with a 150 W Xenon lamp and a 1 cm quartz cuvette. PMT voltage was 700 V with a scanning speed of 2400 nm min⁻¹ [23]. The range of excitation (Ex) wavelength was 200–450 nm, and the range of emission (Em) was 260–550 nm. Both Ex and Em had an interval of 5 nm. The milli-Q deionized water spectrum was used as a blank reference, and it was subtracted from all sample EEMs to correct for internal filtering effects [24]. Fluorescence index (FI), biological index (BIX) and humification index (HIX), which could be related to the freshness level of the precursors and the humification degree of the organic matter, were calculated in MATLAB 2020a.

UV-visible spectroscopy was conducted in a 1 cm quartz cuvette at room temperature, using a Shimadzu UV-1700 spectrophotometer equipped with UV Probe 2.01 for data-processing. The wavelengths varied between 200 and 700 nm. Specific absorption at 254 nm (absorption per mass unit DOC) was defined as SUVA254 to indicate the aromatic degree of the DOM [25]. The absorption ratio at 250 to 365 nm (E₂/E₃) was used to trace variations in the relative sizes of the organic matter molecules, and the absorption ratio at 240 to 420 nm (E₂/E₄) was utilized as an indicator of the humification degree of the organic matter [26].

2.3. Analysis Methods

2.3.1. Parallel Factor Analysis

PARAFAC modeling was utilized to extract the fluorescent components of the DOMs, employing MATLAB R2017b (MathWorks, Natick, MA, USA) with the DOM-Fluor toolbox. The prime number, or the represented components, could be determined by split-half analysis, residual analysis and visual inspection [24]. The relative quantities are symbolized by the maximum fluorescence intensity (Fmax) of the independent fluorescent components. The relative proportions of the different PARAFAC components in a given treatment unit were measured for each individual component as the % of the sum of the Fmax values for all components (%Fmax).

2.3.2. Two-Dimensional Correlation Spectroscopy

A program featuring 2D Shige 1.3 software, developed by Kwansei-Gakuin University, was used to perform generalized 2D-COS and hetero-2D-COS. Due to the large variations seen in the DOM fractions in the AFW treatment process, the consecutive treatment units were regarded as external perturbations. Therefore, a matrix of treating unit-dependent SFS/UV-Vis was developed, which was referred to as synchronous and asynchronous maps. Furthermore, the window size was defined as 3 (2m + 1), which generated distinct MW-2D-COS spectrums. Detailed information has been described in previous literature [27,28].

2.3.3. Structural Equation Modeling

SEM, a statistical model, has drawn close attention as it allows for the discrimination of multiple correlations between potential variables, and can combine empirical data with a theoretical model to elucidate complicated causal networks and verify hypothetical interconnections [29,30]. SEM was carried out in this study to reveal the latent transformation of the characteristic organic pollution in the AFW treatment process. SEM was performed by the software package AMOS 26 (IBM Corporation Software Group, Somers, NY, USA) using the maximum likelihood estimation method.

3. Results and Discussion

3.1. Characterizing Water Quality and Pollutant Removal

The average pH value was 8.01 ± 0.34, indicating that alkalescence occurred in the crab farming system, and pH variations remained limited (Figure 2a). The EC at sampling site #4 was much larger than at the other sites (Figure 2b), indicating that the paddy-field exhibited a higher level of salinity than the other units. This proves that secondary salinization can occur in the paddy-field. Among the sites, the lowest DO occurred at site #1, while the highest DO existed at site #3 (Figure 2c). This can be explained as while the growth and development of the crabs consumes oxygen in the crab pond, DO should steadily increase with artificial aeration and plant photosynthesis. This convincingly indicates that the system is an efficient and stable operation. The average turbidity was 20.46 ± 2.68 NUT (Figure 2d), which also had limited variation.

Site #3 showed the highest concentration of TOC, as well as COD_Cr and COD_Mn, among the five sites (Figure 2e–g). These findings prove that less-degraded materials with a high oxidation potential should emerge in the eco-purification pond, along with fresher organic substances. The removal efficiencies of TOC, COD_Mn and COD_Cr were 23.84%, 36.59% and 33.37% in the system. Peculiarly, the concentrations both of NH₃-N and TN at site #1 were higher than those at the other sites (Figure 2h,i), which could be attributed to the feed used for the crabs. The feed contains an average of 30−40% crude protein, of which only 20–25% is utilized by crabs, leaving the rest in the pond as organic waste. Moreover, crab excreta contains a large amount of NH₃-N and TN. Obviously, the TP concentrations at sites #2 and #3 were much higher than the other sites (Figure 2j), indicating that the accumulation of phosphorus, especially undissolved phosphorus, could be dominant. The removal efficiencies of NH₃-N, TN and TP were 91.99%, 89.10% and 66.67%, respectively, which were much higher than those of TOC, COD_Mn and COD_Cr.

3.2. Characterization of Spectroscopies

3.2.1. Characterizing Fluorescence Spectra

Seven peaks occurred in the EEMs of the DOMs at all sites (Figure 3). Concerning the published papers [23,31,32], peaks B1 and B2, which are located at Ex/Em = 225–280/300 nm, could be associated with tyrosine-like materials, and T1 and T2, situated at Ex/Em = 230–280/350 nm, could be related to tryptophan-like materials. Peaks A and C, seated at Ex/Em = 265–375/440 nm, could be defined as ultraviolet/visible fulvic-like materials. Peak M, which exists between peak A and peak C, could be related to microbial byproduct-like materials. Additionally, the fluorescence intensity of peak T1 was much higher than those of the other peaks at site #1, which significantly increased at site #2 and continuously decreased from sites #3 to #5. The varying trend of peak T2 was similar to peak T1. Peak A, at either site #4 or #5, exhibited a stronger intensity than the other peaks (Figure 3d,e).

The value of the FI at each site was more than 1.90, indicating that autochthonous organic matter occurred in the units, instead of matter from allochthonous sources [33,34]. The value of the BIX at site #1 was 1.13, while the values at the other sites were 0.90–1.00. This suggests that the DOMs in the crab pond are from either a biological or aquatic bacterial origin, while the DOMs in the other units had strong autochthonous components [35]. The ascending order of the HIX was site #2 (0.76) < site #3 (0.90) < site #1 (1.36) < site #4 (3.15) < site #5 (3.25), indicating that the humification degree of the DOMs in the sediment–aeration–purification pond was the lowest, followed by the crab pond, paddy-field and eco-ditch.

3.2.2. Characterizing UV-Visible Spectra

The regular UV-visible absorption spectra of the DOMs in the crab farming park exhibited a similar absorbance, descending monotonously with the ascending wavelength from 200–700 nm (Figure 4a). A strong absorption appeared below the wavelength of 230 nm, which is well-known to be the contribution of inorganic irons [36]. Furthermore, an absorption platform at the wavelength of 240–400 nm could be associated with aromatic or unsaturated compounds (Figure 4b), which might represent conjugate double bonds (C=C, N=N and C=O) [36].

The SUVA254 values of the DOMs at sites #1 and #5 (7.14–8.22) were much less than those at the other sites (13.49–15.25), while the values at sites #2 to #4 ranged from 1.35–1.52. This indicates that the abundances of aromatic carbon in the aeration pond, paddy-field and eco-ditch are much higher than those in the crab pond and eco-purification pond. The E2/E3 value of the DOMs at site #1 (8.82) was much higher than those at sites #2 to #5 (5.78–7.16), revealing that the molecular sizes of the DOMs in the former were larger than those in the latter. This might be related to the large amount of feed thrown into the crab pond. The E2/E4 showed a larger value (28.75) at site #1 than those at sites #2 to #5 (12.94–19.39) too, illuminating that the abundance of humus could be much more at the latter site than at the former sites. These results prove that the DOMs with high-level molecular weights in the crab pond could be of biological or aquatic bacterial origin.

3.3. Assessing Removal of DOM Fractions

3.3.1. Extracting PARAFAC Components

Seven fluorescent components (C1 to C7) were identified from the EEMs of the DOMs by PARAFAC (Figure 5). C1, with an Ex/Em = 260–373/410 nm, might be microbial byproduct-like substances, which could indicate microbial activities [37]. C2, with a blue-shift of 5 nm along the Em wavelength (Ex/Em = 280/290 nm), might be visible-tryptophan-like substances, which could originate from autochthonous organic matter [38]. C3, with an Ex/Em = 265–285/450 nm, should be typical fulvic-like substances, representing degradation products or microbial oxidation products [39]. C4, with two broad peaks from 340 nm to 420 nm along the Em wavelength, might be phenolic-like substances, which could be attributed to pesticides, feed additives and antibiotics [40]. C5, with an Ex/Em-225/300 nm, might be ultraviolet tyrosine-like substances, which could represent phytoplankton activities. C6, with Ex/Em = 215–265/350 nm, could be D-tryptophan-like substances, which mainly exist in plants and microorganisms [41]. C7, with Ex/Em = 230/340 nm, could be L-tryptophan-like substances, which widely occur in medicine, crab feed, etc. [42].

3.3.2. Assessing Removal of Fluorescent Components

Figure 6 presents the Fmax and proportions of the PARAFAC components in the crab farming industry park. The total Fmax of the seven components at site #2 (5639.90 ± 266.38) was the largest, followed by site #3 (3768.64 ± 188.48), site #1 (2726.44 ± 136.11), site #4 (2151.56 ± 103.52) and site #5 (1677.63 ± 93.72), indicating that the decreasing order of the fluorescent material contents was aeration pond > purification pond > crab pond > paddy-field > eco-ditch. This expounds that the DOM fractions might represent a cumulative effect in the sediment–aeration pond, and then are substantially decreased in the following units. Remarkably, C7 (only occurring in site #1), had a far higher Fmax than that of other components, whose percentage was 39.20 ± 2.25%. This suggests that L-tryptophan-like compounds are dominant in the crab farming wastewater, and might be mainly derived from the unutilized feed and excrement of the crabs. The Fmax of C1, in continuum units, increased first and then decreased, similarly to C2, C3 and C5. These prove that the microbial byproduct-like, tryptophan-like, fulvic-like and tyrosine-like components, as autochthonous components, have cumulative effects in the 3 pond/2 dam system. The Fmax of C4 exhibited a decline first and then a rise, indicating that phenolic-like components can be degraded in the 3 pond/2 dam system, and increase with the excessive use of pesticide and chemical fertilizers in the paddy-field. C6 disappeared at site #1, and continuously reduced in units, especially at the purification pond. C7 only occurs at site #1 and is almost reduced in the sediment–aeration pond.

The %C1 ranged from 10.02% to 22.58%, with these relatively high values occurring at sites #4 and #5. This explains that DOMs should be removed through microbial degradation in the paddy-field and eco-ditch. The varying trend of both %C3 and %C5 was similar to that of %C1. The %C2 showed a wide span of 14.13–46.84%, where the maximum value existed at site #3. This provides evidence that tryptophan-like components could originate from autochthonous sources, i.e., metabolism and the residues of aquatic plants. The %C4 changed from 0.57% to 23.46%, with these relatively high values appearing at sites #2 and #3. This allows for speculation that phenolic-like components can be mainly degraded by microorganisms. The %C6 extended from 0 to 30.38% and the maximum was at site #2. This verifies that D-tryptophan-like components can appear in the sediment–aeration pond.

The removal efficiencies of C1, C2, C3, C4, C5 and C7 between the crab pond and eco-ditch were −28.07%, 24.26%, −66.87%, −19.93%, 39.42% and 98.25%, respectively. These indicated that C1, C3 and C4 had increased by 28.08%, 66.87% and 19.93%, respectively, after the continuous processing units, while C2, C5 and C7 had decreased by 24.26%, 39.42% and 98.25%. Obviously, tryptophan-like, tyrosine-like and L-tryptophan-like components, which are well-known as fresh and degradable components, can be degraded by microbes. Moreover, the increase in C4 after the connective processing system can be mainly attributed to the tremendous increase in the Fmax of C4 in the paddy-field, suggesting fertilizer and pesticide inputting in the paddy-field.

3.4. Identifying Changes in Components and Functional Groups of DOMs

3.4.1. Changes in Fluorescent Components in the Crab Farming Park

2DCOS was applied to identify the changing order of the fluorescent components of the DOMs in the crab farming park, which could reveal dynamic variations of the DOM fractions [33]. C1 showed a positive correlation with C2 in the synchronous map (Figure 7a), and a negative correlation with C2 in the asynchronous map (Figure 7b). This explains the fact that the changing order was C2 → C1. A positive relationship between C1 and C3 occurred in both the synchronous and asynchronous maps (Figure 7c,d), indicating that the changing order was C1 → C3. C2 was positively related to C5 in the synchronous map (Figure 7e), while it was negatively related to C5 in the asynchronous map (Figure 7f). This explains that the changing order was C5 → C2. The trends of C5 and C6 were the same as those of C2 and C5 (Figure 7g,h), and the changing order was C5 → C6. There were positive correlations between C4 and C6, both in the synchronous and asynchronous maps (Figure 7i,j), illustrating that the changing order was C4 → C6. A positive correlation of C4 with C7 appeared in the synchronous map (Figure 7k), with a negative correlation in the asynchronous map (Figure 7l). This indicated that the changing order was C7 → C4. Based on the above results, the order of the components was C7 → C4 → C6 → C5 → C2 → C1 → C3, which identified that the variations of C7, C4 and C6 were relatively larger than those of C5, C2, C1 and C3. This suggests that L-tryptophan-like components should occur in the crab farming pond, where D-tryptophan-like components should not happen. Furthermore, phenolic-like components associated with pesticides, feed additives and antibiotics should be deeply removed in the purification pond.

MW-2DCOS was employed to trace the variation of each fluorescent component in the connected units. A peak existed at sites #2 and #4 (Figure 8a), where C1 varied. This provides evidence that the Fmax of microbial byproduct-like components could substantially increase in the aerobic pond, reaching its maximum value in the purification pond, and then decreasing in the paddy-field. A broad excitation peak appeared at sites #2 and #3 (Figure 8b), at which C2 varied significantly. This proves that the Fmax of tryptophan-like components increases remarkably in the aerobic and purification ponds. There was only one peak that occurred at site #2 (Figure 8c), indicating a prominent variation in the C3 Fmax in the aerobic pond. This suggests that fulvic-like components should accumulate in the sedimentation pond and aerobic pond. A broad peak extended from sites #2 to #3 (Figure 8d), where the Fmax of C4 rapidly decreased. This identifies that phenolic-like components are sequentially removed in the aerobic pond and purification pond. A broad peak stretched from sites #2 to #3 too (Figure 8e), indicating that tyrosine-like components are dramatically increased, especially in the aerobic pond. The tendency of C6 was similar to that of C5 (Figure 8f), where tyrosine-like components increased dramatically, especially in the aerobic pond. Interestingly, a narrow and broad peak spread between sites #2 and #4 (Figure 8g), where the Fmax of C7 was almost zero. This suggests that L-tryptophan-like components could originate only in the crab farming pond, and are completely removed in the aerobic pond.

3.4.2. Changes of Functional Groups in the Crab Farming Park

2DCOS was accomplished to trace the changing order of the functional groups with double bonds within the DOMs in the crab farming park. Three weak auto-peaks of symmetric spectra, resulting in a diagonal line, appeared at 254, 310 and 350 nm in the synchronous map (Figure 9a), which are associated with carboxylic, phenolic, and aromatic groups. The intensities of the carboxylic groups were much higher than those of the phenolic and aromatic groups, as the absorbance of the former is larger than that of the latter groups. Moreover, a weak off-diagonal peak existed at the wavelengths of 254 and 350 nm, whose intensity was positive. This expounds that the absorbance of the carboxylic groups increases with a rise in the absorbance of the aromatic groups (Figure 4).

There was a cross-peak with a negative intensity at 254/310 nm in the asynchronous map (Figure 9b), which means that the carboxylic groups are negatively related to the phenolic groups. Coupled with the positive relationship between the carboxylic and phenolic groups, the changing order should be carboxylic → phenolic groups. Furthermore, another cross-peak at 310/350 nm had a negative intensity in the asynchronous map (Figure 9b). Noticeably, a negative correlation between the phenolic and aromatic groups was exhibited in the asynchronous map, while a positive correlation was seen in the synchronous map (Figure 9a). This implies a changing order of phenolic → aromatic. Based on the above results, the changing order of the functional groups was carboxylic → phenolic → aromatic groups. This suggests that fresh DOMs with large molecular sizes can be more easily degraded into carboxylic groups than into phenolic and aromatic groups.

3.5. Tracing Latent Factors and Identifying Their Contributions to DOM Removal

3.5.1. Tracing Latent Factors of DOM Removal

RDA might hypothesize an emphatic and diagrammatic interaction between response variables and environmental variables [24]. The response variables refer to the removal efficiencies of both total organic matter (R-TOC) and fluorescent materials in the DOMs (R-FDOMs), and environmental variables involved in the PARAFAC components, spectroscopic indices, and water quality parameters. The axes demonstrate 62.04% of the total variance, whereas AX1 accounts for 46.24% of the total variance. In the CCA biplot (Figure 10), R-TOC, C3, C4, C7, physico-chemical parameters of water quality and spectroscopic indices with angles less than 90°, point towards the positive direction of AX1. Among the physico-chemical parameters of water quality, both pH and EC exhibited positive relationships with R-TOC and R-FDOMs, which indicates that relatively higher values of pH and EC benefit the removal of DOMs. In comparison, C2, C5, C6 and nutrients with angles less than 90° moved toward the negative direction of AX1. This expounds that AX1 can be associated with the origin of the organic matter. This indirectly proves that phenolic-like components originate from pesticides, feed additives and antibiotics, L-tryptophan-like components are derived from crab feed, fulvic-like components have a terrestrial origin, and tyrosine-like, tryptophan-like and D-tryptophan-like components have an autochthonous origin.

Furthermore, C1, TOC, COD_Cr, DO and R-FDOM, whose angles were less than 90°, trend toward the positive direction of AX2. This suggests that organic matter can be degraded by aerobic microorganisms in the crab farming park. Noticeably, the variables with a longer module had a deeper influence, and the variables with a smaller angle had a significant relationship between the variables. Based on the above results, the latent factors of R-TOC and R-FDOMs in the crab farming park are mainly related to the DOM fractions (C1, C2, C4 and C5), water quality (DO, COD_Mn) and spectroscopic indices (SUVA254).

3.5.2. Identifying Contributions to DOM Removal

Based on the RDA, seven parameters (C1, C2, C4, C5, SUVA254, DO and COD_Mn) were chosen to explore the latent driving factors and potential pathways for DOM removal (Figure 11). A potential path for the influence of DOM components and physico-chemical conditions on pollutant removal was built by an SEM approach, which is presented as a conceptual model to describe the causal relationship and trace latent factors. The results showed that C1, with a coefficient of −0.95, was significantly negatively correlated with R-FDOMs, and, with a coefficient of 0.94, exhibited a significant positive relationship with DO, which was positively correlated with R-FDOMs, with a coefficient of 0.76 (Figure 11). This indicates that C1 could affect DOM removal efficiencies through direct and indirect pathways. On the one hand, C1, as a microbial byproduct-like substance, increased, leading to a simultaneous increase in DO, and providing favorable conditions for the DOM removal. However, on the other hand, C1 is a fluorescent DOM; its increase indeed leads to a reduction in R-FDOMs. C2, with a coefficient of 0.98, was significantly positively correlated with CODMn, and indirectly affected R-TOC through CODMn. C4 could directly affect R-TOC, with a coefficient of 0.46. Meanwhile, C4 showed an indirect pathway to affect R-TOC through SUVA254, which indicates that the existence of C4 could alter the abundance of aromatic carbon, which in consequence affects R-TOC. C5, with a coefficient of −0.38, exhibited a significant negative relationship with DO, which was positively correlated with R-FDOMs, with a coefficient of 0.76. This implies that C5 could affect R-FDOMs by influencing DO, which consequently affects R-TOC. To sum up, for R-FDOM, two significant potential pathways were identified: C1 → R-FDOMs, and C1 → DO → R-FDOMs. For R-TOC, six significant potential pathways were determined: C2 → CODMn → R-TOC, C4 → R-TOC, C4 → SUVA254 → R-TOC, C5 → DO → R-FDOM → R-TOC, C1 → R-FDOM → R-TOC, and C1 → DO → R-FDOM → R-TOC (Figure 11). C4, of all the fluorescent components, has the greatest effect on R-FDOMs. The higher the C4 content, the greater the R-FDOMs.

4. Conclusions

Changes and removals of DOM fractions could be explored in the crab farming park, and their associated latent factors might be traced. DOMs can be associated with seven PARAFAC components C1 to C7, i.e., microbial byproduct-like, visible-tryptophan-like, fulvic-like, phenolic-like, ultraviolet tyrosine-like, D-tryptophan-like and L-tryptophan-like components, respectively. Noticeably, L-tryptophan-like substances were a dominant component of DOMs in the crab farming pond, which were completely degraded in the aeration pond by aerobic microbes. However. D-tryptophan-like components were absent in the crab pond. The changing order of the components was exhibited to be C7 → C4 → C6 → C5 → C2 → C1 → C3, and the changing order of the functional groups was shown to be carboxylic → phenolic → aromatic. C1, C3 and C4 increased by 28.08%, 66.87% and 19.93% in the crab farming system, while C2, C5 and C7 were removed by 24.26%, 39.42% and 98.25%. The latent factors of organic matter removals were C1, C2, C4, C5, SUVA254, COD_Mn and DO. This study might contribute to insight into the removal of components and functional groups of DOMs in the crab farming park. These findings suggest that the abundance of aromatic carbon and the concentration of DO are key factors in the removal of pollutants from crab aquaculture wastewater. To gain a more comprehensive understanding of the removal of pollutants, further work needs to investigate the response mechanisms of different DO concentrations and various component of DOMs on the treatment of crab aquaculture wastewater, and consequently improve the efficiency of crab aquaculture wastewater treatment.

Author Contributions

R.Z.: Data curation and analysis, Visualization, Writing—original draft; Y.H.: Conceptualization, Methodology, Writing—review and editing; B.Y. and J.H.: Investigation, Validation, Visualization; K.L.: Supervision, Writing—review and editing; F.Y.: Investigation, Data analysis; Q.L.: Supervision, Funding acquisition, Writing—review and editing; All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Research Program of Ningxia Hui Autonomous Region, Department of Ecology and Environment in 2024, the Key Technologies of Focused Industries for the Monitoring and Assessment of New Pollutants and Application Demonstration Program of Ningxia Hui Autonomous Region (2024BEG02003), and the Youth Top-Notch Talent Program of Ningxia Hui Autonomous Region (2022077).

Data Availability Statement

Data will be made available on request.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations

Excitation–emission matrix fluorescence spectroscopy (EEM), Parallel factor analysis (PARAFAC), Two-dimensional correlation spectroscopy analysis (2D-COS), Moving window two-dimensional correlation spectroscopy (MW-2DCOS), Structural equation modeling (SEM), Redundancy analysis (RDA), Electrical conductivity (EC), Dissolved oxygen (DO), Chemical oxygen demand (COD_Cr), Permanganate index (COD_Mn), Ammonia nitrogen (NH₃-N), Total nitrogen (TN), Total phosphorus (TP), Total organic carbon (TOC), Dissolved organic matter (DOM), Excitation (Ex), Emission (Em), Component 1–7 (C1–7), Fluorescence index (FI), Biological index (BIX), Humification index (HIX), Specific absorption at 254 nm (SUVA254), Absorption ratio at 250 to 365 nm (E₂/E₃), Absorption ratio at 240 to 420 nm (E₂/E₄), Removal efficiencies of total organic matter (R-TOC), Removal efficiencies of fluorescent dissolved organic matter (R-FDOM).

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Figure 1. Generalized diagram of the crab farming industry park and locations of sampling sites.

Figure 2. Variations in water quality parameters in different treatment process sections of the crab farming park. (a) pH, (b) EC, (c) DO, (d) NTU, (e) TOC, (f) COD_Cr, (g) COD_Mn, (h) NH₃-N, (i) TN, and (j) TP.

Figure 3. EEM spectroscopies of DOMs from the crab farming wastewater at sampling site.

Figure 4. UV-visible absorbing spectra at 200–700 nm (a) and 230–500 nm (b).

Figure 5. PARAFAC components identified from EEM spectroscopies of DOMs in the crab farming industry park.

Figure 6. Fmax (a) and proportions (b) of DOM fractions in the crab farming industry park.

Figure 7. Synchronous and asynchronous maps as described by 2DCOS of DOMs from the crab farming park between C1 and C2 (a,b), C1 and C3 (c,d), C2 and C5 (e,f), C5 and C6 (g,h), C4 and C6 (i,j), C4 and C7 (k,l).

Figure 8. MW-2DCOS map of a given unit in the crab farming park of C1 (a), C2 (b), C3 (c), C4 (d), C5 (e), C6 (f), and C7 (g).

Figure 9. Synchronous map (a) and asynchronous map (b) of 2DCOS using UV-visible absorbing spectra at 230–450 nm.

Figure 10. Plots based on the RDA of the interactions between response variables and environmental explanatory variables (solid arrows with red fonts are the response variables and hollow arrows with black fonts are the environmental explanatory variables).

Figure 11. SEM modeling for the relationship between fluorescent components (C1, C2, C4, C5), water quality parameters (CODMn, DO), and spectroscopic indices (SUVA254), and contributions to removal efficiencies of FDOMs and TOC (R-FDOM, R-TOC). Significance levels of standardized path coefficient are: *** p < 0.001, ** p < 0.01, * p < 0.05.

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Zhou, R.; Hao, Y.; Yu, B.; Hou, J.; Lu, K.; Yang, F.; Li, Q. New Insights into Changes in DOM Fractions in a Crab Farming Park and Key Factors in the Removal Process Using Fluorescence Spectra with MW-2DCOS and SEM. Water 2024, 16, 2249. https://doi.org/10.3390/w16162249

AMA Style

Zhou R, Hao Y, Yu B, Hou J, Lu K, Yang F, Li Q. New Insights into Changes in DOM Fractions in a Crab Farming Park and Key Factors in the Removal Process Using Fluorescence Spectra with MW-2DCOS and SEM. Water. 2024; 16(16):2249. https://doi.org/10.3390/w16162249

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Zhou, Ruijuan, Yan Hao, Benxin Yu, Junwen Hou, Kuotian Lu, Fang Yang, and Qingqian Li. 2024. "New Insights into Changes in DOM Fractions in a Crab Farming Park and Key Factors in the Removal Process Using Fluorescence Spectra with MW-2DCOS and SEM" Water 16, no. 16: 2249. https://doi.org/10.3390/w16162249

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