Compositions and sources of fluorescent water-soluble and water-insoluble organic aerosols.

Brown carbon (BrC), the light-absorbing component of organic aerosols, plays a significant role in climate change and atmospheric photochemistry. However, the water-insoluble fractions of BrC have not been extensively studied, limiting the assessment of the overall climate effects of BrC. In this study, water-soluble and -insoluble organic carbon (i.e., WSOC and WIOC) in wintertime aerosols in Hefei were subsequently fractionated, and their fluorescence properties were comparatively investigated with the excitation-emission matrix method. WIOC contributing 57.1 % was the major component of organic carbon. WSOC with the largest contribution from humic-like regions exhibited a redshift compared to WIOC. Three humic-like substances (HULIS) with different oxidation degrees and one protein-like substances (PRLIS) were identified as the major fluorescent components by the parallel factor analysis. WSOC had more highly oxygenated HULIS, whereas low-oxygenated HULIS dominated WIOC. Nighttime WIOC contained more less-oxygenated species. The positive matrix factorization analysis suggested that biomass burning (43 %) was the largest source of both fluorescent WSOC and WIOC. Coal combustion contributed much more to fluorescent WIOC (40 %), whereas secondary formation contributed more to fluorescent WSOC (12 %). During aerosol pollution episodes, the increase in fluorescence efficiency was much greater for WIOC (25 %) than for WSOC (12 %), and WSOC and WIOC experienced a redshift and blueshift in emission wavelength, respectively. WSOC had more highly oxygenated HULIS, while WIOC had more less-oxygenated HULIS in aerosol episodes than the non-episodic periods. In addition, aerosol pollution was accompanied by the increased contributions of biomass burning and coal combustion to both fluorescent WSOC and WIOC, while the decreased relative contribution of secondary formation to fluorescent WSOC. Our findings highlighted the different fluorescence properties, compositions and sources of fluorescent WSOC and WIOC, providing a comprehensive view of BrC aerosols.

Persistence of dissolved organic matter in sediments influenced by environmental factors：Implication for nutrition and carbon cycle.

The persistence of dissolved organic matter (DOM) plays a crucial role in the cycling and distribution of carbon and nutrients. Nonetheless, our understanding of how environmental alterations affect the persistence of sedimentary DOM remains incomplete. Excitation Emission Fluorescence Matrix-Parallel Factor Analysis (EEM-PARAFAC) was used to examine the fluorescence and compositional characteristics of hydrophilic and hydrophobic DOM (separated using XAD-8 resin) within sediments from twelve lakes and reservoirs. Fluorescence analysis indicated that DOM persistence is dependent on the proportions of the three components derived from PARAFAC. The Mantel test showed that climatic factors had the most significant impact on DOM persistence (Mantel's r = 0.46-0.54, Mantel's p = 0.001-0.007), while anthropogenic (Mantel's r = 0.24-0.32, Mantel's p = 0.03-0.05) and hydrological factors (Mantel's r = 0.03-0.22, Mantel's p = 0.06-0.40) had a somewhat lesser influence. Environmental changes resulted in a consistent decline in DOM persistence from Northeast to Southwest China, accompanied by an increase in gross primary productivity (GPP). Reduced DOM persistence due to climate, hydrological, and anthropogenic factors may lead to elevated concentrations of total phosphorus (TP), contributing to deteriorating water quality and events such as algal blooms. The decline in water quality due to reduced DOM persistence in lakes with high GPP can exacerbate the transition from carbon sinks to carbon sources. Consequently, the persistence of sedimentary DOM significantly influences nutrient and carbon cycling in lakes. Investigating DOM persistence in lakes across diverse geographic locations offers a new perspective on lake eutrophication and carbon emissions. Furthermore, it is crucial to develop targeted recommendations for lake restoration and management.

Qualitative and Quantitative Analysis of Three-Dimensional Fluorescence Spectra by Improved Parallel Factor Analysis with Internal Standard Sample Embedding.

The strategy of parallel factor analysis, combined with the internal standard method, has been increasingly applied to the qualitative and quantitative analysis of three-dimensional fluorescence spectra of unknown mixed fluorophores. Nevertheless, the disparity in the number of fluorophores included in the internal standard sample set and the number included in test samples may impact the qualitative and quantitative outcomes of parallel factor analysis. In this work, we systematically established the framework of the parallel factor analysis with internal standard sample embedding (ISSE-PARAFAC) strategy. We applied this framework to six datasets representing two scenarios and a real dataset and conducted a detailed discussion on the effects of the disparity between the number of fluorophores in the internal standard sample set and the number in the test set on both qualitative and quantitative results. Additionally, we introduced an enhancement to PARAFAC by aggregating fluorophores with similar emission wavelengths, corresponding to the peaks of emission loadings (spectra) obtained from PARAFAC, as a single fluorophore. This aggregation aimed to mitigate the strong correlation between similar fluorophores. The results imply that the presence of irrelevant fluorophores in the internal standard sample set, whether increased or decreased, does not significantly affect the qualitative and quantitative analysis of target fluorophores in the test set. Moreover, we demonstrated that the improved parallel factor analysis with internal standard sample embedding not only fully decomposes the uncorrelated mixed fluorophores for qualitative analysis but also allows the established linear concentration model for fluorescent components to predict the corresponding fluorophore concentration of test samples, enabling quantitative analysis at the ppm level (mg/L).

Spectral characterization, degradation behavior, quenching, and semi-quantification of fluoroquinolone antibiotics in the antibiotic-humic mixture using fluorescence spectroscopy.

Antibiotics, one of the significant emerging contaminants, are intensifying their continual spread out into the environment and affecting human health and the ecosystem in the developing country Bangladesh. This study characterizes widely used fluoroquinolone (FQ) antibiotics, formulates the method to spectrally distinguish them from ubiquitous, and important reactive, adsorbent, and altering catalytic macromolecule humic substances (HS), and further quantifies them using fluorescence spectroscopy. The presence of identical fluorophore at Excitation/Emission = 225-230/285-295 nm wavelength, possession of fluorescence spectra at short emission wavelength (<350 nm) during 275 nm excitation, different emission maxima, and various fluorescing components in antibiotics identified through three-dimensional excitation-emission matrix (EEM) and parallel factor analysis (PARAFAC) models distinguished them from the humic substance as well as from each other. Stern-Volmer equation and its modified version were applied to identify quenching and binding capability, and fluorescence intensity quenching rate of antibiotics and humic in their mixture. Unlike poor and inconsistent quenching mechanisms of humic, FQ antibiotics reduced HS intensity throughout the entire photo-irradiation experiment affirming the functioning of the stable quenching methods. Static quenching of fluorophores was identified from the redshift of excited wavelength on the electronic ground state. Temperature differences during daylight and dark conditions played contrasting roles during the fluorescence quenching of FQ. Unique spectral response at emission wavelength < 350 nm during 275 nm excitation in FQ was considered as its least intensity in the antibiotic-humic mixture and was also used to formulate distinct spectral pattern of each FQ antibiotic. The study also identified the traces of FQ antibiotics with various intensities at different lakes in Bangladesh.

Deep learning models with optimized fluorescence spectroscopy to advance freshness of rainbow trout predicting under nonisothermal storage conditions.

This study established long short-term memory (LSTM), convolution neural network long short-term memory (CNN_LSTM), and radial basis function neural network (RBFNN) based on optimized excitation-emission matrix (EEM) from fish eye fluid to predict freshness changes of rainbow trout under nonisothermal storage conditions. The method of residual analysis, core consistency diagnostics, and split-half analysis of parallel factor analysis was used to optimize EEM data, and two characteristic components were extracted. LSTM, CNN_LSTM, and RBFNN models based on characteristic components of EEM used to predict the freshness indices. The results demonstrated the relative errors of RBFNN models with an R2 above 0.96 and relative errors less than 10% for K-value, total viable counts, and volatile base nitrogen, which were better than those of LSTM and CNN_LSTM models. This study presents a novel approach for predicting the freshness of rainbow trout under nonisothermal storage conditions.

Molecular spectra and docking simulations investigated the binding mechanisms of tetracycline onto E. coli extracellular polymeric substances.

Extracellular polymeric substances (EPS), which were an important fraction of natural organic matter (NOM), played an important role in various environmental processes. However, the heterogeneity, complexity, and dynamics of EPS make their interactions with antibiotics elusive. Using advanced multispectral technology, this study examined how EPS interacts with different concentrations of tetracycline (TC) in the soil system. Our results demonstrated that protein-like (C1), fulvic-like (C2), and humic-like (C3) fractions were identified from EPS. Two-dimensional synchronous correlation spectroscopy (2D-SF-COS) indicated that the protein-like fraction gave faster responses than the fulvic-like fraction during the TC binding process. The sequence of structural changes in EPS due to TC binding was revealed by two-dimensional Fourier Transformation Infrared correlation spectroscopy (2D-FTIR-COS) as follows: 1550 > 1660 > 1395 > 1240 > 1087 cm-1. It is noteworthy that the sensitivity of the amide group to TC has been preserved, with its intensity gradually increasing to become the primary binding site for TC. The integration of hetero-2DCOS maps with moving window 2D correlation spectroscopy (MW2DCOS) provided a unique insight into understanding the correlation between EPS fractions and functional groups during the TC binding process. Moreover, molecular docking (MD) discovered that the extracellular proteins would provide plenty of binding sites with TC through salt bridges, hydrogen bonds, and π-π base-stacking forces. With these results, systematic investigations of the dynamic changes in EPS components under different concentrations of antibiotic exposure demonstrated the advanced capabilities of multispectral technology in examining intricate interactions with EPS in the soil environment.

The deciphering of microplastics-derived fluorescent dissolved organic matter in urban lakes, canals, and rivers using parallel factor analysis modeling and mimic experiment.

The aim of the study is to investigate the leaching of fluorescent dissolved organic matter (fDOM) from microplastics. In addition, this study identifies the connection between fDOM and microplastics in the aquatic environment. Three-dimensional excitation-emission matrix identified five fluorophores, that is, peak A, M, T, Tuv, and Wuv, and the parallel factor analysis modeling identified five components, that is, tryptophan-like, p-hydroxy acetophenone, humic acid (C-like), detergent-like, and fulvic acid (M-like) in the urban surface water. Mimic experiments using commonly used synthetic plastic (like microplastics) in Mili-Q water under solar radiation and dark environments demonstrate the release of fDOM from plastic. Two fluorophore peaks were observed at Ex/Em = 250/302 nm and Ex/Em = 260/333 nm for the expanded polystyrene plastic polymer and one fluorophore peak at Ex/Em = 260/333 nm for the low-density polyethylene. Fluorophore and component intensity exhibited notable associations with microplastics in the aquatic environment. These findings indicated that the characteristics and dynamics of fDOM in urban surface water are influenced by microplastics. PRACTITIONER POINTS: Fluorescent dissolved organic matters were identified in urban surface waters. Expanded polystyrene (EPS) had shown two fluorophores at Em/Ex = 250/302 and Em/Ex = 260/333. Low-density polyethylene (LDPE) had one fluorophore at Em/Ex = 260/333. Fluorophore and component intensity in the aquatic settings exhibited associations with microplastics.

Tracking the changes of dissolved organic matter throughout the city water supply system with optical indices.

Dissolved organic matter (DOM) is important in determining the drinking water treatment and the supplied water quality. However, a comprehensive DOM study for the whole water supply system is lacking and the potential effects of secondary water supply are largely unknown. This was studied using dissolved organic carbon (DOC), absorption spectroscopy, and fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC). Four fluorescent components were identified, including humic-like C1-C2, tryptophan-like C3, and tyrosine-like C4. In the drinking water treatment plants, the advanced treatment using ozone and biological activated carbon (O3-BAC) was more effective in removing DOC than the conventional process, with the removals of C1 and C3 improved by 17.7%-25.1% and 19.2%-27.0%. The absorption coefficient and C1-C4 correlated significantly with DOC in water treatments, suggesting that absorption and fluorescence could effectively track the changes in bulk DOM. DOM generally remained stable in each drinking water distribution system, suggesting the importance of the treated water quality in determining that of the corresponding network. The optical indices changed notably between distribution networks of different treatment plants, which enabled the identification of changing water sources. A comparison of DOM in the direct and secondary water supplies suggested limited impacts of secondary water supply, although the changes in organic carbon and absorption indices were detected in some locations. These results have implications for better understanding the changes of DOM in the whole water supply system to help ensure the supplied water quality.

Development of dissolved organic matter-based indicators to understand the degradation of organic contaminants in reverse osmosis concentrate from potable reuse systems.

Reverse osmosis (RO)-based treatment of municipal wastewater effluent allows for potable reuse, but this process generates reverse osmosis concentrate (ROC) that needs further treatment before disposal. This study investigated the application of UV-based advanced oxidation processes (AOPs) to degrade nine contaminants of emerging concern (CECs) from real ROC waste streams, using UV-only and UV-AOPs with hydrogen peroxide, free chlorine, and persulfate. Dissolved organic matter (DOM) in ROC was characterized using fluorescence excitation emission matrix data and analyzed by a four-component parallel factor (PARAFAC) analysis model. UV-only treatment showed considerable removal of CECs that displayed high values of quantum yields and molar absorption coefficients. UV-AOP treatment of ROC exhibited heavy scavenging of reactive species during CEC degradation. A probe-based approach established that hydroxyl radical was the dominant reactive species in all UV-AOPs. A kinetic analysis of PARAFAC components of DOM showed that the visible humic-like and protein-like components exhibited the higher reaction kinetics compared to UV humic-like and nutrient-like components. The strong linear correlation of protein-like component and seven of the nine CECs across multiple AOPs indicated that they have similar reactivity, enabling the establishment of chemical-reactivity based surrogates for prediction CEC fate in ROC wastes.

The biotic effects of lignite on humic acid components conversion during chicken manure composting.

Targeted regulation of composting to convert organic matter into humic acid (HA) holds significant importance in compost quality. Owing to its low carbon content, chicken manure compost often requires carbon supplements to promote the humification progress. The addition of lignite can increase HA content through biotic pathways, however, its structure was not explored. The Parallel factor analysis revealed that lignite can significantly increase the complexity of highly humified components. The lignite addition improved phenol oxidase activity, particularly laccase, during the thermophilic and cooling phases. The abundance and transformation functions of core bacteria also indicated that lignite addition can influence the activity of microbial transformation of HA components. The structural equation model further confirmed that lignite addition had a direct and indirect impact on enhancing the complexity of HA components through core bacteria and phenol oxidase. Therefore, lignite addition can improve HA structure complexity during composting through biotic pathways.

A tensor decomposition scheme for EEG-based diagnosis of mild cognitive impairment.

Mild Cognitive Impairment (MCI) is the primary stage of acute Alzheimer's disease, and early detection is crucial for the person and those around him. It is difficult to recognize since this mild stage does not have clear clinical signs, and its symptoms are between normal aging and severe dementia. Here, we propose a tensor decomposition-based scheme for automatically diagnosing MCI using Electroencephalogram (EEG) signals. A new projection is proposed, which preserves the spatial information of the electrodes to construct a data tensor. Then, using parallel factor analysis (PARAFAC) tensor decomposition, the features are extracted, and a support vector machine (SVM) is used to discriminate MCI from normal subjects. The proposed scheme was tested on two different datasets. The results showed that the tensor-based method outperformed conventional methods in diagnosing MCI with an average classification accuracy of 93.96% and 78.65% for the first and second datasets, respectively. Therefore, it seems that maintaining the spatial topology of the signals plays a vital role in the processing of EEG signals.

Responses of soil dissolved organic carbon properties to the desertification of desert wetlands in the Mu Us Sandy Land.

In desert wetlands, the decline in ground water table results in desertification, triggering soil carbon and nutrient loss. However, the impacts of desertification on soil dissolved organic carbon (DOC) properties which determine the turnover of soil carbon and nutrients are unclear. Here, the desertification gradient was represented by the distance from the wetland center (0∼240 m) traversing reed marshes, desert shrubs and bare sandy land in the Hongjian Nur Basin, north China. Soil DOC properties were determined by ultraviolet and fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC). Results showed that soil DOC content decreased significantly from 107.23 mg kg-1 to 8.44 mg kg-1 by desertification (p < 0.05). However, the proportion of DOC to soil organic carbon (SOC) was gradually significantly increased. According to spectral parameters, microbial-derived DOC decreased from 0 to 120 m (reed marshes to desert shrubs) but increased from 120 to 240 m (desert shrubs to bare sandy lands), with a reverse hump-shaped distribution pattern. The molecular weight and aromaticity of DOC increased from 0 to 120 m but decreased from 120 to 240 m, with a hump-shaped distribution pattern. For the DOC composition, although the relative abundances of humic-acid components remained stable (p > 0.05), they were ultimately decreased by serious desertification and the amino acids became the dominant component. A similar change pattern was also found for humification index. Additionally, MBC and C:N were the two most important variables in determining the content and spectral properties, respectively. Together, these findings relationships between the soil DOC properties and desertification degree, especially the increase in DOC proportion and the decrease in humification degree, which may reduce soil C stabilization in the Hongjian Nur Basin.

Resolving fluorescence spectra of Maillard reaction products formed on bovine serum albumin using parallel factor analysis.

Formation of Maillard reaction products (MRPs) is increasingly studied by the use of fluorescence spectroscopy, and most often, by measuring single excitation/emission pairs or use of unresolved spectra. However, due to the matrix complexity and potential co-formation of fluorescent oxidation products on tryptophan and tyrosine residues, this practice will often introduce errors in both identification and quantification. The present study investigates the combination of fluorescence excitation emission matrix (EEM) spectroscopy and parallel factor analysis (PARAFAC) to resolve the EEMs into its underlying fluorescent signals, allowing for better identification and quantification of MRPs. EEMs were recorded on a sample system of bovine serum albumin incubated at 40 °C for up to one week with either glucose, methylglyoxal or glyoxal added. Ten unique PARAFAC components were resolved, and assignment was attempted based on similarity with fluorescence of pure standards of MRPs and oxidation products and reported data from literature. Of the ten fluorescent PARAFAC components, tyrosine and buried and exposed tryptophan were resolved and identified, as well as the formation of specific MRPs (argpyrimidine and Nα-acetyl-Nδ-(5-methyl-4-imidazolon-2-yl)ornithine) and tryptophan oxidation products (kynurenine and dioxindolylalanine). The formation of the PARAFAC resolved protein modifications were qualitatively validated by liquid chromatography-mass spectrometry.

Using machine learning to trace the pollution sources of disinfection by-products precursors compared to receptor models.

To increase the efficiency of managing backup water resources, it is critical to identify and allocate pollution sources. Source apportionment of dissolved organic matter (DOM) was investigated in our work. Parallel factor analysis (PARAFAC) and the Spearman correlation analysis were used for source identification. After that, a newly hybrid model applying the fuzzy c-means and support vector regression (FCM-SVR) was employed for source apportionment compared to receptor models. The results demonstrated that the FCM-SVR model exhibited excellent generalization, and only required standardization and normalization as pre-processing steps for dataset. According to the results, microbial sources played a key role (28.1 %) in the formation potential of disinfection byproducts (DBPFPs). Additionally, shipping marine sources exhibited a substantial contribution (21.2 %) to DBPFPs. The prediction accuracy of DBPFPs was matched or exceeded receptor models, and the R2 of DOC (0.884) was significantly high. Therefore, we recommend the FCM-SVR model combined with PARAFAC to trace the source of DBPFPs as its significant effectiveness in source identification, source apportionment, and prediction accuracy, possessing the potential for further applicability in tracking more organic compounds. ENVIRONMENTAL IMPLICATION: The disinfection byproducts precursors in water sources, which were thought to be hazardous materials in this study, are proved to be chlorinated into carcinogenic disinfection byproducts (DBPs) during drinking water treatment, However, the source apportionment methods of DBPs are not well developed compared to other inorganic matter, e.g., heavy metals and ammonia nitrogen. We proposed a new FCM-SVR model to trace the source of DBPs, which required easier pre-treatment and resulted a better source apportionment and prediction accuracy. As a result, it could provide a different prospect and useful management advices to trace the source of DBPs.

Deciphering DOM-metal binding using EEM-PARAFAC: Mechanisms, challenges, and perspectives.

Dissolved organic matter (DOM) is a pivotal component of the biogeochemical cycles and can combine with metal ions through chelation or complexation. Understanding this process is crucial for tracing metal solubility, mobility, and bioavailability. Fluorescence excitation emission matrix (EEM) and parallel factor analysis (PARAFAC) has emerged as a popular tool in deciphering DOM-metal interactions. In this review, we primarily discuss the advantages of EEM-PARAFAC compared with other algorithms and its main limitations in studying DOM-metal binding, including restrictions in spectral considerations, mathematical assumptions, and experimental procedures, as well as how to overcome these constraints and shortcomings. We summarize the principles of EEM to uncover DOM-metal association, including why fluorescence gets quenched and some potential mechanisms that affect the accuracy of fluorescence quenching. Lastly, we review some significant and innovative research, including the application of 2D-COS in DOM-metal binding analysis, hoping to provide a fresh perspective for possible future hotspots of study. We argue the expansion of EEM applications to a broader range of areas related to natural organic matter. This extension would facilitate our exploration of the mobility and fate of metals in the environment.

Fluorescence fingerprint as an indicator to identify urban non-point sources in urban river during rainfall period.

Nowadays, the urban non-point source (NPS) pollution gradually evolved as the main contributor to urban water contamination since the point source pollution was effectively controlled. It was imperative to perform urban NPS identification in urban river to meet the requirements of precise source governance. In this study, the real-time detection about water quality parameters and fluorescence fingerprints (FFs) was performed for BX River and its outlets during rainfall period. EEM-PARAFAC and component similarity analyses discovered that the pollution encountered by BX River mainly came from road runoff and untreated municipal wastewater (UMWW) overflow. The C1 (tryptophan-like) and C3 (terrestrial humic-like) components located at Ex/Em = âˆ¼230(280)/340 and ∼275/430 nm were both detected in these two kinds of urban NPS. The C2 components of road runoff and UMWW overflow displayed remarkable differences, which located at Ex/Em = 250/385 and 245/365 nm, respectively, thus could be served as indicators for distinguishing them. During rainfall period, the outflow from rainwater outlets (RWOs) constantly showed similar FF features to road runoff, while the FFs of outflow from combined sewer outlets (CSOs) alternated between those of road runoff and UMWW overflow. The FF features of sections in BX River changed in response to the dynamic variations in FFs of the outlets, which revealed real-time pollution causes of BX River. This work not only realized the identification and differentiation of urban NPS, but also elucidated the dynamic variations of pollution characteristics throughout the entire process of "urban NPS-outlets-urban river", and demonstrated the feasibility of FF technique in quickly diagnosing the pollution causes of urban river during rainfall period, which provided important guidance for urban NPS governance.

Potential Linkage between Heavy Metal Pollution Risk Assessment and Dissolved Organic Matter Spectra in the WWTPs-River Integrated Area-Case Study from Ashi River.

Direct sewage discharge can cause severe damage to the water environment of the river. However, the impacts of dissolved organic matter (DOM) in the discharge on the original pattern of DOM and the distribution of heavy metals (HMs) in the river are little known. How to monitor such areas in a long-term and systematic manner also needs to be urgently addressed. In this paper, we characterized the DOM of the sediments in the WWTPs (wastewater treatment plants)-river integrated zone by ultraviolet-visible absorption spectroscopy (UV-vis), three-dimensional excitation-emission matrix (3D-EEM) combined with parallel factor (PARAFAC) method. The effects of WWTP on receiving waters were investigated, and the potential link between DOM and HM pollution was explored. Hg (Igeo: 3.94 ± 0.65; EF: 44.83 ± 31.11), Cd (Igeo: 1.81 ± 0.69; EF: 8.02 ± 2.97), Cu (Igeo: 1.61 ± 0.83; EF: 6.85 ± 2.37), Zn (Igeo: 1.55 ± 0.54; EF: 7.24 ± 3.58), and Ni (Igeo: 1.46 ± 0.56; EF: 6.12 ± 1.99) in rivers were the primary risk sources of HM. The combined pollution risk indicates that the WWTPs-river integrated area is in a high pollution risk state. Moreover, α(254) has a significant correlation with pollution indicators and can be used as a proxy indicator. These results help to understand better the impact of WWTPs on receiving water bodies and the potential connection between DOM and HM pollution and provide new ideas for monitoring the water environment in highly polluted areas.

Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal.

The Bay of Bengal (BoB) is the largest sink to retain discharges from major rivers and the Sundarbans Mangrove Forest in Bangladesh and upholds significant ecological and resource diversity. This study aims to characterize, and identify sources, spatial dynamics, and the fate of the principal ecological web driver that is fluorescent dissolved organic matter (FDOM) in the BoB using advanced techniques of excitation-emission matrix (EEM) fluorescence spectroscopy and multivariate parallel factor (PARAFAC) analyses. The identified four protein-, two humic- and one detergent-like FDOM components mostly showed higher abundance in the shallow water than deep unlike a protein-like component. Such exceptional protein-like component was identified to form colloidal structure under elevated salinity in deep water. Autochthonous humic-like FDOM originated from primary production and water temperature counteracted microbial polymerization in shallow and deep water, respectively. The annual mass deposition indicated the influx of anthropogenic pollutants from both terrestrial and internal marine systems.

[Spectral Characteristics and Source Analysis of Chromophoric Dissolved Organic Matter in Surface Water of Taihu Lake Before Cyanobacterial Blooming].

Chromophoric dissolved organic matter (CDOM) is an important part of the nutrient biogeochemical cycle in aquatic ecosystems. To explore the characteristics and sources of CDOM components in the surface water of Taihu Lake, UV-visible spectroscopy and excitation emission matrix fluorescence spectroscopy-parallel factor analysis were used to analyze CDOM components in surface water. Combined with CDOM optical parameters (a355, SUVA254, a250/a365, FI, BIX, and HIX), the spatial differences and pollution sources were identified, and a preliminary comparison was made between this study and the historical data of CDOM components in Taihu Lake. According to the results, a355, SUVA254, and a250/a365 showed the characteristics of high concentration, high aromatic ability, and low relative molecular weight of CDOM in the surface water of the eastern part of Taihu Lake; however, the northern part showed the opposite characteristics. Four components were isolated from CDOM using parallel factor analysis:one tyrosine-like (C1), two types of tryptophan (C2 and C4), and one fulionic acid (C3). The main component C1 had a strong linear relationship with the C2 and C3 components, suggesting that different components originated from similar pollution sources. The fluorescence index showed that CDOM in different areas of Taihu Lake were differently affected by endogenous and terrestrial inputs; however, the overall humification degree was low. This indicated that the CDOM components in Taihu Lake were primarily protein-like (C1, C2, and C4) (>85%) and autogenous, with good biochemical availability.

Air nanobubble water improves plant uptake and tolerance toward cadmium in phytoremediation.

Heavy metal contamination continues to be a persistent environmental problem. To address this issue, this study evaluated the impact of air nanobubbles (NBs) in water on the uptake of heavy metals by Alternanthera philoxeroides (A. philoxeroides), a common aquatic plant in China known for its rapid growth, strong vitality, and high capacity for heavy metal remediation. This study found that diluted air NBs (25% concentration) boosted cadmium uptake of A. philoxeroides by 17.39%. They also enhanced plant growth (25-50%) and photosynthetic pigments (10-20%) even at low cadmium levels (0.1 mM). Furthermore, the incorporation of 25% air NBs has been demonstrated to significantly amplify the performance of key antioxidant enzymes, such as superoxide dismutase and catalase, alongside heightened levels of crucial antioxidants such as malondialdehyde. This heightened activity of antioxidant defenses offers a compelling explanation for the potential amelioration of cadmium toxicity and concurrent enhancements in overall plant growth rates. Notably, a comprehensive analysis utilizing the excitation emission matrix-parallel factor analysis (EEM-PARAFAC) technique has revealed alterations in the composition of rhizosphere dissolved organic matter due to the presence of NBs. This ncomposition change of the rhizosphere dissolved organic mattermposition has subsequently exerted an influence on plant complexation processes and the subsequent uptake of cadmium. This study demonstrates that the strategic implementation of air NBs in water systems holds the potential to significantly enhance the plant's ability to detoxify cadmium and improve the uptake of heavy metals during phytoremediation processes.