Chromophoric dissolved organic matter in inland waters: Present knowledge and future challenges

Exploring the diversity of dissolved organic matter (DOM) properties and sources in different functional areas of a typical macrophyte - derived lake combined with optical spectroscopy and FT-ICR MS analysis

Lake Baiyangdian is one of China's largest macrophyte - derived lakes, facing severe challenges related to water quality maintenance and eutrophication prevention. Dissolved organic matter (DOM) was a huge carbon pool and its abundance, property, and transformation played important roles in the biogeochemical cycle and energy flow in lake ecosystems. In this study, Lake Baiyangdian was divided into four distinct areas: Unartificial Area (UA), Village Area (VA), Tourism Area (TA), and Breeding Area (BA). We examined the diversity of DOM properties and sources across these functional areas. Our findings reveal that DOM in this lake is predominantly composed of protein - like substances, as determined by excitation - emission matrix and parallel factor analysis (EEM - PARAFAC). Notably, the exogenous tyrosine-like component C1 showed a stronger presence in VA and BA compared to UA and TA. Ultrahigh - resolution mass spectrometry (FT - ICR MS) unveiled a similar DOM molecular composition pattern across different functional areas due to the high relative abundances of lignan compounds, suggesting that macrophytes significantly influence the material structure of DOM. DOM properties exhibited specific associations with water quality indicators in various functional areas, as indicated by the Mantel test. The connections between DOM properties and NO3N and NH3N were more pronounced in VA and BA than in UA and TA. Our results underscore the viability of using DOM as an indicator for more precise and scientific water quality management.

Identifying the fate of dissolved organic matter in wastewater treatment plant effluent-dominated urban river based on fluorescence fingerprinting and flux budget approach

Effluent organic matter from wastewater treatment plants (WWTPs) is an important source of dissolved organic matter (DOM) in urban rivers worldwide and is an important water quality factor. Identifying the fate of DOM in urban river is crucial for water quality management. To address this concern, a fluorescent flux budget approach was conducted to probe the fate of DOM in WWTP effluent-dominated urban river, in combination with field measurement and fluorescence fingerprinting. An urban river receiving two WWTP effluents in Hefei City, China was chosen as the study site, where longitudinal measurements of river hydrology and water quality were performed. The fluorescence fingerprinting revealed the presence of two humic-like components (C1, C4), one fulvic-like component (C2) and one protein-like component (C3) in this investigated river, among which C2 and C4 were indicative of anthropogenic influences, closely associated with treated effluents. For each fluorescent component, the WWTP effluent contributed over 80 % of the total fluorescent dissolved organic matter (FDOM) input in this river. Using the developed FDOM flux budget model, it was found that the C1 and C3 were almost conserved within the waterbody, while the C2 and C4 experienced losses due to biogeochemical reactions. The decay rates of C2 and C4 were estimated to be 0.109-0.174 d-1 and 0.096-0.320 d-1, respectively. Spatial heterogeneity of decay rates for C2 and C4 were associated with the varied chemistries of the lateral input sources including two treated effluents and one tributary flow. Our study highlights that after treated effluent is released into the receiving waterbody, the FDOM would undergo loss from the waters particularly for anthropogenic fulvic-like substance C2 and humic-like substance C4. Additionally, the quantified FDOM decay rate in actual urban water environment provides insights for river water quality management, especially when using DOM as the surrogate indicator of organic pollutants.

Composition regulates dissolved organic matter adsorption onto iron (oxy)hydroxides and its competition with phosphate: Implications for organic carbon and phosphorus immobilization in lakes

Dissolved organic matter (DOM) is a heterogeneous pool of compounds and exhibits diverse adsorption characteristics with or without phosphorous (P) competition. The impacts of these factors on the burial and mobilization of organic carbon and P in aquatic ecosystems remain uncertain. In this study, an algae-derived DOM (ADOM) and a commercially available humic acid (HA) with distinct compositions were assessed for their adsorption behaviors onto iron (oxy)hydroxides (FeOx), both in the absence and presence of phosphate. ADOM contained less aromatics but more protein-like and highly unsaturated structures with oxygen compounds (HUSO) than HA. The adsorption capacity of FeOx was significantly greater for ADOM than for HA. Protein-like and HUSO compounds in ADOM and humic-like compounds and macromolecular aromatics in HA were preferentially adsorbed by FeOx. Moreover, ADOM demonstrated a stronger inhibitory effect on phosphate adsorption than HA. This observation suggests that the substantial release of autochthonous ADOM by algae could elevate internal P loading and pose challenges for the restoration of restore eutrophic lakes. The presence of phosphate suppressed the adsorption of protein-like compounds in ADOM onto FeOx, resulting in an increase in the relative abundance of protein-like compounds and a decrease in the relative abundance of humic-like compounds in post-adsorption ADOM. In contrast, phosphate exhibited no discernible impact on the compositional fractionation of HA. Collectively, our results show the source-composition characters of DOM influence the immobilization of both DOM and P in aquatic ecosystems through adsorption processes. The preferential adsorption of proteinaceous compounds within ADOM and aromatics within HA highlights the potential for the attachment with FeOx to diminish the original source-specific signatures of DOM, thereby contributing to the shared DOM characteristics observed across diverse aquatic environments.

Dissolved organic matter quality in thermokarst lake water and sediments across a permafrost gradient, Western Siberia

Thermokarst (thaw) lakes of permafrost peatlands are among the most important sentinels of climate change and sizable contributors of greenhouse gas emissions (GHG) in high latitudes. These lakes are humic, often acidic and exhibit fast growing/drainage depending on the local environmental and permafrost thaw. In contrast to good knowledge of the thermokarst lake water hydrochemistry and GHG fluxes, the sediments pore waters remain virtually unknown, despite the fact that these are hot spots of biogeochemical processes including GHG generation. Towards better understating of dissolved organic matter (DOM) quality at the lake water - sediment interface and in the sediments pore waters, here we studied concentration and optical (UV, visual) properties of DOM of 11 thermokarst lakes located in four permafrost zones of Western Siberia Lowland. We found systematic evaluation of DOM concentration, SUVA and various optical parameters along the vertical profile of lake sediments. The lake size and hence, the stage of lake development, had generally weak control on DOM quality. The permafrost zone exhibited clear impact on DOM porewater concentration, optical characteristics, aromaticity and weight average molecular weight (WAMW). The lowest quality of DOM, reflected in highest SUVA and WAMW, corresponding to the dominance of terrestrial sources, was observed at the southern boundary of the permafrost, in the sporadic/discontinuous zone. This suggests active mobilization of organic matter leachates from the interstitial peat and soil porewaters to the lake, presumably via subsurface or suprapermafrost influx. Applying a substitute space for time scenario for future evolution of OM characteristics in thermokarst lake sediments of Western Siberia, we foresee a decrease of DOM quality, molecular weight and potential bioavailability in lakes of continuous permafrost zone, and an increase in these parameters in the sporadic/discontinuous permafrost zone.

Preliminary analysis on the characteristics of light absorption coefficients in typical rivers of different river basins across China

As a vital constituent of water's optical properties, the absorption coefficients influence the distribution of underwater light field, consequently impacting the structures and functional patterns of riverine ecosystems. In this study, the light absorption of non-algal particulates (ad(λ), m-1), phytoplankton (aph(λ), m-1) and CDOM (ag(λ), m-1) of 380 water samples collected from 133 rivers in eight external river basins across China from 2013 to 2023 were examined to determine the optical absorption characteristics. Results showed significant differences in ad(λ), aph(λ) and ag(λ) across different basins. ① The water bodies of eight basins can be categorized into 5 dominant types of absorption coefficients. ② In eastern China, ag(440) exhibited a northeast-high and southwest-low spatial distribution pattern. The Songliao River Basin had the highest ag(440) than other basins. The higher slope S of ag(λ) in rivers compared to lakes and reservoirs confirm river water primarily derive CDOM from external sources, distinguishing them from lakes and reservoirs. ③ The Huaihe and Haihe River Basins had higher ad(440) and aph(440) values, primarily due to lower terrain and human activities, leading to the accumulation of suspended particles and nutrients. And soil erosion from the Loess Plateau caused significant differences in ad(440) between the upper and middle reaches of the Yellow River Basin. These findings hold significant implications for understanding the optical characteristics of rivers in China.

Terrestrial dissolved organic matter inputs accompanied by dissolved oxygen depletion and declining pH exacerbate CO2 emissions from a major Chinese reservoir

Terrestrial inputs and subsequent degradation of dissolved organic matter (DOM) in lake ecosystems can result in rapid depletion of dissolved oxygen (DO). Inputs of terrestrial DOM including organic acids can also lead to decreases in pH. However, to date, few studies have investigated the linkages between terrestrial DOM inputs, DO and pH levels in the water column, and carbon dioxide (CO2) emissions from lake ecosystems. Based on monthly field sampling campaigns across 100 sites in Lake Qiandao, a major man-made drinking water reservoir in China, from May 2020 to April 2021, we estimated an annual CO2 efflux (FCO2) of 37.2 ± 29.0 gC m-2 yr-1, corresponding to 0.02 ± 0.02 TgC yr-1 from this lake. FCO2 increased significantly with decreasing DO, chlorophyll-a (Chl-a) and δ2H-H2O, while FCO2 increased with increasing specific UV absorbance (SUVA254) and a terrestrial humic-like component (C2). We found that DO concentration and pH declined with increasing terrestrial DOM inputs, i.e. increased SUVA254 and terrestrial humic-like C2 levels. Vertical profile sampling revealed that the partial pressure of CO2 (pCO2) increased with increasing terrestrial DOM fluorescence (FDOM), while DO, pH, and δ13C-CO2 declined with increasing terrestrial FDOM. These results highlight the importance of terrestrial DOM inputs in altering physico-chemical environments and fueling CO2 emissions from this lake and potentially other aquatic ecosystems.

Humification levels of dissolved organic matter in the eastern plain lakes of China based on long-term satellite observations

Under the influence of intensive human activities and global climate change, the sources and compositions of dissolved organic matter (DOM) in the eastern plain lake (EPL) region in China have fluctuated sharply. It has been successfully proven that the humification index (HIX), which can be derived from three-dimensional excitation-emission matrix fluorescence spectroscopy, can be an effective proxy for the sources and compositions of DOM. Therefore, combined with remote sensing technology, the sources and compositions of DOM can be tracked on a large scale by associating the HIX with optically active components. Here, we proposed a novel HIX remote sensing retrieval (IRHIX) model suitable for Landsat series sensors based on the comprehensive analysis of the covariation mechanism between HIX and optically active components in different water types. The validation results showed that the model runs well on the independent validation dataset and the satellite-ground synchronous sampling dataset, with an uncertainty ranging from 30.85 % to 36.92 % (average ± standard deviation = 33.6 % ± 3.07 %). The image-derived HIX revealed substantial spatiotemporal variations in the sources and compositions of DOM in 474 lakes in the EPL during 1986-2021. Subsequently, we obtained three long-term change modes of the HIX trend, namely, significant decline, gentle change, and significant rise, accounting for 74.68 %, 17.09 %, and 8.23 % of the lake number, respectively. The driving factor analysis showed that human activities had the most extensive influence on the DOM humification level. In addition, we also found that the HIX increased slightly with increasing lake area (R2 = 0.07, P < 0.05) or significantly with decreasing trophic state (R2 = 0.83, P < 0.05). Our results provide a new exploration for the effective acquisition of long-term dynamic information about the sources and compositions of DOM in inland lakes and provide important support for lake water quality management and restoration.

Increased dominance of terrestrial component in dissolved organic matter in Chinese lakes

The source composition of chromophoric dissolved organic matter (CDOM) in lakes is closely related to regional environmental changes, human activities, and the carbon cycle. The spectral slope ratio (SR) is an important parameter of CDOM optical components, and combined with remote sensing technology, the source composition of CDOM can be tracked comprehensively and efficiently in large regions. Here, we proposed a CDOM source tracking remote sensing model (CDOM-SR) based on the hue angle (α) to assess the spatial pattern and long-term trend of the CDOM source composition in Chinese lakes (surface area ≥ 1 km2) from 1986 to 2021. Validation results show that the CDOM-SR model has a good SR estimation performance with a median absolute percentage difference, root mean square deviation, median ratio, and median deviation of 17.91 %, 0.23, 1.02, and 0.03, respectively. We found that the average SR of Chinese lakes presents an obvious spatial pattern of high in the west and low in the east due to the difference in human activity intensity and the natural geographical environment. Additionally, we found that the average SR of Chinese lakes from 1986 to 2021 decreased at a rate of - 0.06/10 years, of which 64.37 % of lakes decreased significantly, 15.42 % of lakes had no significant change, and only 20.20 % of lakes increased. The widespread decrease in the average SR indicates that the increasing human activity discharge of terrestrial organic matter has had an important impact on the source composition of the CDOM in Chinese lakes. Our results provide a new resource for remote sensing monitoring of CDOM sources and important insights into lake carbon cycling under the influence of ongoing human activities.

Unveiling changes in the complexation of dissolved organic matter with Pb(II) by photochemical and microbial degradation using fluorescence EEMs-PARAFAC

Dissolved organic matter (DOM) is very important in determining the speciation, behaviors, and risk of metal pollutants in aquatic ecosystems. Photochemical and microbial degradation are key processes in the cycling of DOM, yet their effects on the DOM-Pb(II) interaction remain largely unknown. This was studied by examining the complexation of river DOM with Pb(II) after degradation, using fluorescence quenching titration and excitation-emission matrices-parallel factor analysis (EEMs-PARAFAC). Three humic-like and two protein-like components were identified, with strong removals of humic-like components and decreasing average molecular weight and humification degree of DOM by photo- and photo-microbial degradation. The changes in humic-like abundance and structure resulted in notable weakening of their interaction with Pb(II). The tryptophan-like C2 was also mainly removed by photo-degradation, while the tyrosine-like C3 could be either removed or accumulated. The Pb(II)-binding of protein-like components was generally weaker but was enhanced in some degradation groups, which might be related to the lowering competition from humic-like components. The binding parameters correlated significantly with the DOM indices, which were dominated by photo-degradation for humic-like components but by seasonal variations for the tyrosine-like component. These results have implications for understanding the key mechanisms underlying the variability of the DOM-metal interaction in aquatic environments.

Hexabromocyclododecane in sediments from riverine, port, and coastal areas of Kaohsiung, Taiwan: levels, spatial distribution, and potential ecological risk

The widespread use of hexabromocyclododecane (HBCD), a brominated flame retardant, is a major public health concern because of the toxic, persistent, and bioaccumulative nature of HBCD. However, there is limited information available regarding the distribution and transportation of HBCD in sediments across various environmental settings, spanning from riverine to marine environments in the Kaohsiung area of Taiwan. In this study, we comprehensively investigated the level and distribution of and potential ecological risk posed by HBCD in surface sediments in the Kaohsiung area of Taiwan. In sediment samples from stations on the Love River and Kaohsiung Port area, the concentrations of HBCD ranged from 10.6 to 320.1 μg/kg dry weight (dw) and nondetectable (n.d.) to 58.4 μg/kg dw, respectively. The concentrations of HBCD in sediment collected from the M1, M2, and M3 sites, located in the Cijin coastal area, were 896.2 μg/kg dw, 3.2 μg/kg dw ( 1. The M1 site had the highest risk level (RQ = 5.27). These data suggest that domestic sewage and industrial wastewater discharge pose a potential risk to marine environments. Consequently, timely measures to control HBCD-related risks are required. Our study offers insight into the environmental effects of HBCD contamination of sediment and provides valuable information that can be used to guide environmental policy and safety measures.

Distribution pattern of dissolved organic matter in pore water of sediments from three typical areas of western Lake Taihu and its environmental implications

The migration, transformation, and accumulation of dissolved organic matter (DOM) in pore water of sediment cores play a pivotal role in lacustrine carbon cycling. In order to understand the dynamics of DOM in the sediments of large shallow eutrophic lakes, we examined the vertical profiles of DOM and the benthic fluxes of dissolved organic carbon (DOC) in sediment cores located in algae accumulated, dredged, and central areas of eutrophic Lake Taihu, China. Optical properties showed the significant influence of terrestrial inputs on the DOM components of pore water in the algae accumulated area but an abundant accumulation of autochthonous DOM in the central area. The benthic fluxes of DOC ranging from -458.2 to -139.4 mg·m-2·d-1 in the algae accumulated area displayed an opposite diffusion direction to the other two areas. The flux ranges of 9.5-31.2 mg·m-2·d-1 in the dredged area and 14.6-48.0 mg·m-2·d-1 in the central area were relatively smaller than those in the previously reported lake ecosystems with low trophic levels. Dredging engineering disturbed the pre-dredging distribution patterns of DOM in sediment cores. The deposition, accumulation, and transformation of massive algae scums in eutrophic lakes probably promoted the humification degree of sediments.

Short-term photodegradation of autochthonous and allochthonous dissolved organic matter in Lake Taihu, China

Photochemistry is one of the key processes that shape the quality of dissolved organic matter (DOM) in aquatic systems, yet the photoreactivity of DOM from different sources remains largely unclear. In this study, DOM from 10 typical autochthonous and allochthonous sources in Lake Taihu basin were exposed to simulated sunlight, and quantitative and compositional changes of the DOM were explored by measuring its UV-Visable absorption and fluorescence spectroscopy. Photochemical release of nutrients was also explored during the incubations. Results showed that, although DOM from most sources experienced photobleaching effects with decreased absorption coefficients at 254 nm (a(254)) and fluorescence component intensities after light exposure, photochemical alterations of DOM linked to their original composition. Macrophyte-derived (Potamogeton malaianus) DOM, with the largest molecular size, showed increased a(254), humic- and protein-like fluorescence component (C1 and C2) abundances, and inorganic nutrient concentrations relative to dark controls, indicating photo-release of labile components. However, DOM with relatively higher aromaticity, e.g., from agricultural water and the lake, showed photobleaching effects and increased humification degree, probably due to the loss of aromatic components. Allochthonous anthropogenic DOM, e.g., from sewage, showed stronger photo-ammonification, likely relating to the fresh labile N-containing compositions. The form of inorganic nutrient releases during the DOM photolysis also varied with the original DOM sources. Macrophyte-derived DOM incubations showed larger photo-releases of NO3- and PO43-, while NO2- dominated inorganic nutrient releases during groundwater DOM light incubations. Thus, this study concludes that the photoreactivity of DOM closely relates to its original composition and sources.

Remote sensing for chromophoric dissolved organic matter (CDOM) monitoring research 2003-2022: A bibliometric analysis based on the web of science core database

Chromophoric dissolved organic matter (CDOM) occupies a critical part in biogeochemistry and energy flux of aquatic ecosystems. CDOM research spans in many fields, including chemistry, marine environment, biomass cycling, physics, hydrology, and climate change. In recent years, a series of remarkable research milestone have been achieved. On the basis of reviewing the research process of CDOM, combined with a bibliometric analysis, this study aims to provide a comprehensive review of the development and applications of remote sensing in monitoring CDOM from 2003 to 2022. The findings show that remote sensing data plays an important role in CDOM research as proven with the increasing number of publications since 2003, particularly in China and the United States. Primary research areas have gradually changed from studying absorption and fluorescence properties to optimization of remote sensing inversion models in recent years. Since the composition of oceanic and freshwater bodies differs significantly, it is important to choose the appropriate inversion method for different types of water body. At present, the monitoring of CDOM mainly relies on a single sensor, but the fusion of images from different sensors can be considered a major research direction due to the complex characteristics of CDOM. Therefore, in the future, the characteristics of CDOM will be studied in depth inn combination with multi-source data and other application models, where inversion algorithms will be optimized, inversion algorithms with low dependence on measured data will be developed, and a transportable inversion model will be built to break the regional limitations of the model and to promote the development of CDOM research in a deeper and more comprehensive direction.

Remote sensing identification of urban water pollution source types using hyperspectral data

Owing to accelerated urbanisation, increased pollutants have degraded urban water quality. Timely identification and control of pollution sources enable relevant departments to effectively perform water treatment and restoration. To achieve this goal, a remote sensing identification method for urban water pollution sources applicable to unmanned aerial vehicle (UAV) hyperspectral images was established. First, seven fluorescent components were obtained through three-dimensional excitation-emission matrix fluorescence spectroscopy of dissolved organic matter (DOM) combined with parallel factor analysis. Based on the hierarchical cluster analysis of the seven fluorescence components and three spectral indices, four pollution source (PS) types were determined, namely, domestic sewage, terrestrial input, agricultural and algal, and industrial wastewater sources. Second, several water colour and optical parameters, including the absorption coefficient of chromophoric DOM at 254 nm, humification index, chlorophyll-a concentration, and hue angle, were utilised to develop an identification method with a recognition accuracy exceeding 70% for the four PSs that is suitable for UAV hyperspectral data. This study demonstrated the potential of identifying PSs by combining the fluorescence characteristics of DOM with the optical properties of water, thus expanding the application of remote sensing technologies and providing more comprehensive and reliable information for urban water quality management.

Semi-empirical models for remote estimating colored dissolved organic matter (CDOM) in a productive tropical estuary

Inland waters are important components of the global carbon cycle as they regulate the flow of terrestrial carbon to the oceans. In this context, remote monitoring of Colored Dissolved Organic Matter (CDOM) allows for analyzing the carbon content in aquatic systems. In this study, we develop semi-empirical models for remote estimation of the CDOM absorption coefficient at 400 nm (a_CDOM) in a tropical estuarine-lagunar productive system using spectral reflectance data. Two-band ratio models usually work well for this task, but studies have added more bands to the models to reduce interfering signals, so in addition to the two-band ratio models, we tested three- and four-band ratios. We used a genetic algorithm (GA) to search for the best combination of bands, and found that adding more bands did not provide performance gains, showing that the proper choice of bands is more important. NIR-Green models outperformed Red-Blue models. A two-band NIR-Green model showed the best results (R² = 0.82, RMSE = 0.22 m^-1, and MAPE = 5.85%) using field hyperspectral data. Furthermore, we evaluated the potential application for Sentinel-2 bands, especially using the B5/B3, Log(B5/B3) and Log(B6/B2) band ratios. However, it is still necessary to further explore the influence of atmospheric correction (AC) to estimate the a_CDOM using satellite data.

Photoreduction of Hg(II) by typical dissolved organic matter in paddy environments

The photochemical behavior of dissolved organic matter (DOM) in surface water and its effect on Hg(II) photoreduction has been extensively studied, but the contribution of DOM in paddy water to Hg(II) photoreduction is largely unknown. Herein, the effect of DOM from biochar (BC_DOM), rice straw (RS_DOM), and chicken manure (CM_DOM) on Hg(II) photoreduction were examined. The comparable reduction efficiency of Hg(II) suggested that DOM-like fraction (62.3-63.7%) contributes more than suspended particulate matter-like fraction (17.7-23.4%) and bacteria-like fraction (13.0-20.0%) in paddy water. Under irradiation, the typical DOM significantly promoted Hg(II) photoreduction, and the reduction efficiency of BC_DOM (65.5 ± 2.1%) was higher than that of CM_DOM (48.3 ± 2.6%) and RS_DOM (32.8 ± 2.4%) in 6 h. The quenching and kinetics experiments showed that superoxide anion (O₂^•-) was the main reactive species for Hg(II) photoreduction. Fluorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry revealed that DOM with a higher degree of lignin/carboxy-rich acyclic molecules, condensed aromatics structures, and phenolic compounds could promote the formation of O₂^•-. These findings highlight the importance of DOM in Hg(II) photoreduction and provide new ideas for regulating Hg cycling and bioavailability in paddy environments.

Separately tracking the sources of hydrophobic and hydrophilic dissolved organic matter during a storm event in an agricultural watershed

The hydrophobicity of dissolved organic matter (DOM) affects various aspects of its environmental impacts in terms of water quality, sorption behaviors, interactions with other pollutants, and water treatment efficiency. In this study, source tracking of river DOM was conducted separately for hydrophobic acid (HoA-DOM) and hydrophilic (Hi-DOM) fractions using end-member mixing analysis (EMMA) in an agricultural watershed during a storm event. EMMA with optical indices of bulk DOM revealed larger contributions of soil (24 %), compost (28 %), and wastewater effluent (23 %) to riverine DOM under high versus low flow conditions. Molecular level analysis of bulk DOM revealed more dynamic features, showing an abundance of CHO and CHOS formulae in riverine DOM under high- and low flow conditions. CHO formulae originated from soil (78 %) and leaves (75 %) and contributed to the increasing CHO abundance during the storm event, whereas CHOS formulae likely originated from compost (48 %) and wastewater effluent (41 %). The characterization of bulk DOM at the molecular level demonstrated that soil and leaves are the dominant contributors for the high-flow samples. However, in contrast to the results of bulk DOM analysis, EMMA with HoA-DOM and Hi-DOM revealed major contributions from manure (37 %) and leaf DOM (48 %) during storm events, respectively. The results of this study highlight the importance of individual source tracking of HoA-DOM and Hi-DOM for the proper evaluation of the ultimate roles of DOM in affecting river water quality and for a better understanding of DOM dynamics and transformation in natural and engineered systems.

Field evidences of fluorescent dissolved organic matter (FDOM) as potential fingerprints for agricultural and urban sources in river environment

Field evidences of the fluorescence differences between agricultural and urban river reaches are still lack. In this study, the middle reaches of Danhe River (DH) and Mihe River (MH) in Shouguang, China, were designed as agricultural and urban river reaches, respectively, to compare the the fluorescence differences in disparate river reaches using excitation-emission matrix coupled with parallel factor analysis (EEM-PARAFAC). Three fluorescence components were identified. C1 (Ex/Em=230,255,295 nm/420 nm) was categorized as humic-like fluorophores, C2 (Ex/Em=230,275 nm/330 nm) was recognized as tryptophan-like substances, and C3 (Ex/Em=215 nm/290 nm) was noted as tyrosine-like and phenylalanine-like compounds. The results showed that the FDOM posed significant differences between agricultural and urban river reaches (P < 0.001). The monitoring sites in DH were rich in C2 (1.90 ± 0.62 Raman Unit (RU), mean ± standard deviation), and the monitoring sites in MH were rich in C3 (1.32 ± 0.51 RU). Redundancy analysis revealed that C2 could be regarded as a fluorescence indicator of agricultural sewage in river environment, while C3 was recognized as a fluorescence indicator of domestic sewage in river environment. In conclusion, this study provided field evidences of FDOM as potential fingerprints for agricultural and urban sources in river environment.

Elevated methylmercury production in mercury-contaminated paddy soil resulted from the favorable dissolved organic matter variation created by algal decomposition

Algae-derived organic matter (AOM) may considerably regulate methylmercury (MeHg) production and accumulation in the paddy fields by changing the soil-dissolved OM (SDOM) properties. In this study, a 25-day microcosm experiment was performed to compare the responding mechanisms of MeHg production in the Hg-contaminated paddy soil-water system to the input of algae-, rice-, and rape-derived OMs. Results showed that algal decomposition could release much more cysteine and sulfate than crop straws. Compared with crop straw-derived OMs, AOM input greatly increased the dissolved organic carbon concentrations in soil but resulted in a greater decrease in tryptophan-like fractions while accelerated the formation of high-molecular-weight fractions in soil DOM. Moreover, AOM input significantly increased MeHg concentrations in the pore water by 19.43%-3427.66% and 52.81%-5846.57% compared to rape- and rice-derived OMs, respectively (P < 0.05). And, a similar MeHg changing pattern was also observed in the overlying water (10-25 d) and the soil solid-phase particles (15-25 d) (P < 0.05). Correlation analysis revealed that MeHg concentrations in the AOM-added soil-water system had significantly negative and positive relationships with the tryptophan-like C4 fraction and molecular weight (E2/E3 ratio) of soil DOM, respectively (P < 0.01). These findings suggest that AOM has a higher capacity than crop straw-derived OMs to promote MeHg production and accumulation in the Hg-contaminated paddy soils by creating a favorable soil DOM variation and providing more microbial electron donors and receptors.

Spatiotemporal response of dissolved organic matter diversity to natural and anthropogenic forces along the whole mainstream of the Yangtze River

The Yangtze River, the largest river in Asia, plays a crucial role in linking continental and oceanic ecosystems. However, the impact of natural and anthropogenic disturbances on composition and transformation of dissolved organic matter (DOM) during long-distance transport and seasonal cycle is not fully understood. By using a combination of elemental, isotopic and optical techniques, as well as Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), we investigated DOM abundance and composition along the whole mainstream at highly spatial resolution in the dry and early wet seasons. Our findings showed that the concentration and flux of dissolved organic carbon (DOC) in the Yangtze River was much lower compared with other worldwide larger rivers. The distribution of δ¹³C_DOC and higher abundance of humic-like fluorescent component and highly unsaturated and phenolics (HUPs) compound reflected a prominent contribution of allochthonous DOM. Further optical and molecular analysis revealed humic-like fluorescent components were coupled with CHO molecules and HUPs compound with higher aromatic, unsaturated, molecular weight and stable characteristics between upstream and midstream reaches. With increasing agricultural and urban land downstream, there were more heteroatomic formulae and labile aliphatic and protein-like compounds which were derived from human activities and in situ primary production. Meanwhile, DOM gradually accumulates with slow water flow and additional autochthonous organics. Weaker solar radiation and water dilution during the dry/cold season favours highly aromatic, unsaturated and oxygenated DOM compositions. Conversely, higher discharge during the wet/warm season diluted the terrestrial DOM, but warm temperatures could promote phytoplankton growth that releases labile aliphatic and protein-like DOM. Besides, chemical sulfurization, hydrogenation and oxygenation were found during molecular cycling processes. Our research emphasizes the active response of riverine DOM to natural and anthropogenic controls, and provides a valuable preliminary background to better understand the biogeochemical cycling of DOM in a larger river.

How does anthropogenic activity influence the spatial distribution of dissolved organic matter in rivers of a typical basin located in the Loess Plateau, China

River ecosystems interact strongly with adjacent terrestrial environments and receive dissolved organic matter (DOM) from a variety of sources, all of which are vulnerable to human activities and natural processes. However, it is unclear how and to what extent human and natural factors drive DOM quantity and quality changes in river ecosystems. Here, three fluorescence components were identified via optical techniques, including two humic-like substances and one protein-like component. The protein-like DOM was mainly accumulated in anthropogenically impacted regions, while humic-like components exhibit the opposite trend. Furthermore, the driving mechanisms of both natural and anthropogenic factors on the variations in DOM composition were investigated using partial least squares structural equation modelling (PLS-SEM). Human activities, especially agriculture, positively influence the protein-like DOM directly by enhancing anthropogenic discharge with protein signals and also indirectly by affecting water quality. Water quality directly influences the DOM composition by stimulating in-situ production through a high nutrient load from anthropogenic discharge and inhibiting the microbial humification processes of DOM due to higher salinity levels. The microbial humification processes can also be restricted directly by a shorter water residence time during the DOM transport processes. Furthermore, protein-like DOM was more sensitive to direct anthropogenic discharge than indirect in-situ production (0.34 vs. 0.25), especially from non-point source input (39.1%), implying that agricultural industry optimization may be an efficient way to improve water quality and reduce protein-like DOM accumulation.

Explore variations of DOM components in different landcover areas of riparian zone by EEM-PARAFAC and partial least squares structural equation model

Dissolved organic matter (DOM) plays key roles in species-distribution of contaminants and the biogeochemical cycle of carbon in ecosystems. Riparian zone is the representative of water-land ecotone and controls the DOM exchange between water and land. However, the variance of DOM in different landcover areas of an urban river riparian zone is unknown. In this study, fluorescence excitation-emission matrix (EEM) spectroscopy coupled with parallel factor analysis (PARAFAC) and partial least squares structural equation model (PLS-SEM) was applied to character dissolved organic matter (DOM) fractions in four types of landcover riparian areas (natural forest, artificial forest, semi-natural grassland, and cropland) of Puhe River and trace latent factors. Soil samples were collected at 0-20 cm, 20-40 cm, 40-60 cm, and 60-80 cm. The results showed that soil DOM components and humification varied between forests with grassland and cropland samples, and soil humification was obviously higher in the forest samples than that in the grassland and cropland samples. In the natural and artificial forest soils, the humic/fulvic-like were the dominant fractions of DOM, whose variations were smaller than the protein-like with soil depths. However, the tyrosine-like was the representative component in the grassland and cropland soils, whose variation was smaller than the humus substances. According to the PLS-SEM, the DOM components and humification were affected by soil physiochemical properties and DOM sources. The humification in the forest soils had a positive correlation with tryptophan-like, which derived from blended source of the autochthonous and terrigenous. Nevertheless, a positive correlation was observed between humification and humus substances, which could derive from microbial degradation of tyrosine-like, in the grassland and cropland soils. Moreover, the soil physiochemical properties were negatively related to DOM components in all soil samples, which could affect indirectly soil humification. Therefore, EEM combined with PARAFAC and PLS-SEM might be an effective method to investigate DOM fractions and trace the latent factors in different landcover areas of the riparian zone.

Elucidating the characteristic of leachates released from microplastics under different aging conditions: Perspectives of dissolved organic carbon fingerprints and nano-plastics

Despite numerous studies that have been devoted to investigating the aging behaviors of microplastics (MPs), dissolved organic carbon (DOC) and nano-plastics (NPs) released from MPs under different aging conditions were limited. Herein, the characterizations and underlying mechanisms of DOC and NPs leaching from MPs (PVC and PS) in the aquatic environment for 130 days under different aging conditions were investigated. The results showed that aging could reduce the abundance of MPs, and high temperature and UV aging generated small-sized MPs (< 100 μm), especially UV aging. DOC-releasing characteristics were related to MP type and aging condition. Meanwhile, MPs were prone to release protein-like and hydrophilic substances except for 60 °C aging of PS MPs. Additionally, 8.77 × 10⁹-8.87 × 10¹⁰ and 4.06 × 10⁹-3.94 × 10¹⁰ NPs/L were detected in leachates from PVC and PS MPs-aged treatments, respectively. High temperature and UV promoted the release of NPs, especially UV irradiation. Meanwhile, smaller sizes and rougher NPs were observed in UV-aged treatments, implying higher ecological risks of leachates from MPs under UV aging. This study highlights the leachate released from MPs under different aging conditions comprehensively, which could offset the knowledge gap between the MPs' aging and their potential threats.

Transformation of algal-dissolved organic matter via sunlight-induced photochemical and microbial processes: interactions between two processes

Algal-dissolved organic matter (ADOM) is an important fraction of dissolved organic carbon (DOC) in eutrophic water. Although ADOM is known to be readily transformed by microbes, the role of sunlight-induced photochemical process and the interactions between two processes on ADOM transformation remains unclear. In this study, three types of treatments for ADOM, including photochemical process under natural solar light (L treatment), microbial process (M treatment), and the simultaneous photochemical plus microbial process (L&M), were performed for 18 days. Our results showed that M treatment was more effective for the loss of DOC, chromophoric DOM (CDOM) at short wavelengths (a₂₅₄ and a₂₈₀), than L treatment, while L treatment was more effective for the transformation of a₃₅₀ and the fluorescent components of the ubiquitous humic-like component and the tryptophan-like component. Comparison in the decay kinetics of DOC and CDOM in the three treatments showed that the simultaneous photochemical and biological processes exhibited an inhibitory effect on DOC decay rate but not the percentage of labile DOC fraction. Higher relative abundance of protein-like substances was found after L&M treatment, while the relative abundance of humic-like substance and aromaticity increased after M treatment, and the low molecular-weight compounds were produced after L treatment. Our results emphasized the importance of photochemistry in processing ADOM to mediate the chemodiversity in natural water.

Characterization of Dissolved Organic Matter from Agricultural and Livestock Effluents: Implications for Water Quality Monitoring

There is growing concern about the impact of agricultural practices on water quality. The loss of nutrients such as nitrogen and phosphorous through agricultural runoff poses a potential risk of water quality degradation. However, it is unclear how dissolved organic matter (DOM) composition is associated with pollution levels in water bodies. To address this, we conducted a cross-year investigation to reveal the nature of DOM and its relationship to water quality in agricultural effluents (AEs) and livestock effluents (LEs). We discovered that DOM fluorescence components of AEs were mainly from autochthonous and terrestrial sources, while in LEs it was primarily from autochthonous sources. LEs showed a higher β:α and biological index (BIX) than AEs, indicating that LEs had higher biological activity. Compared to the LEs, DOM in AEs exhibited a higher humification index (HIX), illustrating that DOM was more humic and aromatic. Overall, our results suggest that the BIX and fluorescence index (FI) were best suited for the characterization of water bodies impacted by LEs and AEs. Excitation-emission matrix spectroscopy and parallel factor (EEMs-PARAFAC) analysis showed that DOM in AEs was mainly a humic-like material (~64%) and in LEs was mainly protein-like (~68%). Tryptophan-like compounds (C1) were made more abundant in AEs because of the breakdown of aquatic vegetation. The microbial activity enhanced protein-like substances (C1 and C2) in LEs. Our study revealed a positive correlation between five-day biochemical oxygen demand (BOD₅) concentrations and tyrosine-like substance components, suggesting that fluorescence peak B may be a good predictor of water quality affected by anthropogenic activities. For both LEs and AEs, our results suggest that peak D may be a reliable water quality surrogate for total phosphorus (TP).

Remote sensing of fluorescent humification levels and its potential environmental linkages in lakes across China

The pollution or eutrophication affected by dissolved organic matter (DOM) composition and sources of inland waters had attracted concerns from the public and government in China. Combined with remote sensing techniques, the fluorescent DOM (FDOM) parameters accounted for the important part of optical constituent as chromophoric dissolved organic matter (CDOM) was a useful tool to trace relative DOM sources and assess the trophic states for large-scale regions comprehensively and timely. Here, the objective of this research is to calibrate and validate a general model based on Landsat 8 OLI product embedded in Google Earth Engine (GEE) for deriving humification index (HIX) based on EEMs in lakes across China. The Landsat surface reflectance was matched with 1150 pairs fieldtrip samples and the nine sensitive spectral variables with good correlation with HIX were selected as the inputs in machine learning methods. The calibration of XGBoost model (R² = 0.86, RMSE = 0.29) outperformed other models. Our results indicated that the entire dataset of HIX has a strong association with Landsat reflectance, yielding low root mean square error between measured and predicted HIX (R² = 0.81, RMSE = 0.42) for lakes in China. Finally, the optimal XGBoost model was used to calculate the spatial distribution of HIX of 2015 and 2020 in typical lakes selected from the Report on the State of the Ecology and Environment in China. The significant decreasing of HIX from 2015 to 2020 with trophic states showed positive control of humification level of lakes based on the published document of Action plan for prevention and control of water pollution in 2015 of China. The calibrated model would greatly facilitate FDOM monitoring in lakes, and provide indicators for relative DOM sources to evaluate the impact of water protection measures or human disturbance effect from Covid-19 lockdown, and offer the government supervision to improve the water quality management for lake ecosystems.

Estimation of dissolved organic carbon from inland waters at a large scale using satellite data and machine learning methods

Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quantify DOC content in inland waters, especially over large-scale areas. This study presents the first attempt to estimate DOC in inland waters over a large-scale area using satellite data and ML methods with the newly published open-source dataset AquaSat. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were trained using more than 16 thousand samples across the continental United States matched with satellite data from Landsat 5, 7 and 8 missions. Satellite data from the Landsat missions were further extended with environmental data from the ERA5-Land product and used as input to train the ML algorithms. Our results show that including environmental data as inputs considerably improved the prediction of DOC for all ML algorithms, with GPR showing the most promising performance results with moderate estimation errors (RMSE: 4.08 mg/L). Permutation feature importance analysis showed that the wavelength range in the visible Green band (from Landsat) and the monthly average air temperature (from ERA5-Land) were the most important variables for the ML approaches. The results demonstrate the predictive strength of GPR and its useful feature to derive per pixel standard deviations for detailed analysis. Our results further highlight the important role of considering environmental processes to explain DOC variations over large scales. The application and performance of the GPR in mapping spatiotemporal variations of DOC in an entire water body were discussed by taking Lake Okeechobee (the 8^th largest freshwater lake in the U.S.) as an illustrative example. While performance evaluation showed that DOC concentrations can be retrieved with adequate accuracy, algorithm development was challenged by the heterogenous nature of large-scale open source in situ data, issues related to atmospheric correction, and the low spatial and temporal resolution of the environmental predictors. This research demonstrates how open source, large-scale datasets like AquaSat in combination with ML and satellite remote sensing can make research toward large-scale estimation of inland water DOC more realistic while highlighting its remaining limitations and challenges.

A review of long-term change in surface water natural organic matter concentration in the northern hemisphere and the implications for drinking water treatment

Reduced atmospheric acid deposition has given rise to recovery from acidification - defined as increasing pH, acid neutralization capacity (ANC), or alkalinity in surface waters. Strong evidence of recovery has been reported across North America and Europe, driving chemical responses. The primary chemical responses identified in this review were increasing concentration and changing character of natural organic matter (NOM) towards predominantly hydrophobic nature. The concentration of NOM also influenced trace metal cycling as many browning surface waters also reported increases in Fe and Al. Further, climate change and other factors (e.g., changing land use) act in concert with reductions in atmospheric deposition to contribute to widespread browning and will have a more pronounced effect as deposition stabilizes. The observed water quality trends have presented challenges for drinking water treatment (e.g., increased chemical dosing, poor filter operations, formation of disinfection by-products) and many facilities may be under designed as a result. This comprehensive review has identified key research areas to be addressed, including 1) a need for comprehensive monitoring programs (e.g., larger timescales; consistency in measurements) to assess climate change impacts on recovery responses and NOM dynamics, and 2) a better understanding of drinking water treatment vulnerabilities and the transition towards robust treatment technologies and solutions that can adapt to climate change and other drivers of changing water quality.

A hybrid remote sensing approach for estimating chemical oxygen demand concentration in optically complex waters: A case study in inland lake waters in eastern China

Chemical oxygen demand concentration (C_COD) is widely used to indicate the degree of organic pollution of lakes, reservoirs and rivers. Mastering the spatiotemporal distribution of C_COD is imperative for understanding the variation mechanism and controlling of organic pollution in water. In this study, a hybrid approach suitable for Sentinel 3A/Ocean and Land Colour Instrument (OLCI) data was developed to estimate C_COD in inland optically complex waters embedding the interaction between C_COD and the absorption coefficients of optically active constituents (OACs). Based on in-situ sampling in different waters, the independent validations of the proposed model performed satisfactorily in Lake Taihu (MAPE = 23.52 %, RMSE = 0.95 mg/L, and R² = 0.81), Lake Qiandaohu (MAPE = 21.63 %, RMSE = 0.50 mg/L and R² = 0.69), and Yangtze River (MAPE = 29.34 %, RMSE = 0.83 mg/L, and R² = 0.64). In addition, the approach not only showed significant superiority compared with previous algorithms, but also was suitable for other common satellite sensors equipped same or similar bands. The hybrid approach was applied to OLCI images to retrieve C_COD of Lake Taihu from 2016 to 2020 and reveals substantial interannual and seasonal variations. The above results indicate that the proposed approach is effective and stable for studying spatiotemporal dynamic of C_COD in optically complex waters, and that satellite-derived products can provide reliable information for lake water quality management.

Changes in Water Chemistry Associated with Rainstorm Events Increase Carbon Emissions from the Inflowing River Mouth of a Major Drinking Water Reservoir

Large reservoirs are hotspots for carbon emissions, and the continued input and decomposition of terrestrial dissolved organic matter (DOM) from upstream catchments is an important source of carbon emissions. Rainstorm events can cause a surge in DOM input; however, periodic sampling often fails to fully capture the impact of these discrete rainstorm events on carbon emissions. We conducted a set of frequent observations prior to and following a rainstorm event in a major reservoir Lake Qiandao (China; 580 km²) from June to July 2021 to investigate how rainstorms alter water chemistry and CO₂ and CH₄ emissions. We found that the mean CO₂ efflux (FCO₂) (13.2 ± 9.3 mmol m^-2 d^-1) and CH₄ efflux (FCH₄) (0.12 ± 0.02 mmol m^-2 d^-1) in the postrainstorm campaign were significantly higher than those in the prerainstorm campaign (-3.8 ± 3.0 and +0.06 ± 0.02 mmol m^-2 d^-1, respectively). FCO₂ and FCH₄ increased with increasing nitrogen and phosphorus levels, elevated DOM absorption (a₃₅₀), specific UV absorbance SUVA₂₅₄, and terrestrial humic-like fluorescence. Furthermore, FCO₂ and FCH₄ decreased with increasing chlorophyll-a (Chl-a), dissolved oxygen (DO), and pH. A five-day laboratory anoxic bioincubation experiment further revealed a depletion of terrestrial-DOM concurrent with increased CO₂ and CH₄ production. We conclude that rainstorms boost the emission of CO₂ and CH₄ fueled by the surge and decomposition of fresh terrestrially derived biolabile DOM in this and likely many other reservoir's major inflowing river mouths.

Comparison of organic matter (OM) pools in water, suspended particulate matter, and sediments in eutrophic Lake Taihu, China: Implication for dissolved OM tracking, assessment, and management

Suspended particulate matter (SPM) and sediments are important sources of dissolved organic matter (DOM) in lake water. However, studies on what extent and how both sources affect DOM composition are lacking, which hampers DOM management. Herein, DOM, SPM-extracted particulate organic matter (POM), and sediment-extracted organic matter (SOM) were characterized and compared in terms of absorption spectral properties and chemical composition in Lake Taihu, a large cyanobacterial bloom-affected shallow lake. A statistical method was proposed to quantify the similarity of organic matter (OM) in the different states and to evaluate the potential effects of SPM and sediments on DOM. Results showed that POM and DOM were mainly composed of small-molecular-size and low-humified organic components (i.e., 27 %-38 % tryptophan-like and ~30 % protein-like substances), and most of them were derived from autochthonous sources. While tyrosine-like (57 %) and humic-like (27 %) substances were dominant in SOM. The OM similarity between POM and DOM was approximately 1.5 times higher than that between SOM and DOM, indicating the greater effect of SPM than sediments on DOM composition. High pH and low nitrogen (e.g., nitrate and ammonia) were positively correlated to the OM similarity between POM and DOM. Further, the findings indicated that nitrogen limitation enhanced the OM exchange between POM and DOM by promoting the production of extracellular polymeric substances (EPS) in cyanobacterial aggregates. The obtained findings highlighted the importance of SPM in shaping the DOM composition relative to sediments and facilitating the DOM management in bloom-affected lakes.

Wavelength trends of photoproduction of reactive transient species by chromophoric dissolved organic matter (CDOM), under steady-state polychromatic irradiation

The formation quantum yields of photochemically produced reactive intermediates (PPRIs) by irradiated CDOM (in this study, Suwannee River Natural Organic Matter and Upper Mississippi River Natural Organic Matter) decrease with increasing irradiation wavelength. In particular, the formation quantum yields of the excited triplet states of CDOM (³CDOM*) and of singlet oxygen (¹O₂) have an exponentially decreasing trend with wavelength. The ^•OH wavelength trend is different, because more effective ^•OH production occurs under UVB irradiation than foreseen by a purely exponential function. We show that the parameter-adjustable Weibull function (which adapts to both exponential and some non-exponential trends) is suitable to fit the mentioned quantum yield data, and it is very useful when CDOM irradiation is carried out under polychromatic lamps as done here. Model calculations suggest that, thanks to the ability of CDOM to also absorb visible radiation, and despite its decreasing quantum yield of ^•OH generation with increasing wavelength, CDOM would be able to trigger ^•OH photogeneration in deep waters, to a higher extent than UVB-absorbing nitrate or UVB + UVA-absorbing nitrite.

Effects of Photodegradation on the Optical Indices of Chromophoric Dissolved Organic Matter from Typical Sources

Chromophoric dissolved organic matter (CDOM) plays important roles in aquatic environments, and its optical properties provide a series of indices for evaluating the source and composition of dissolved organic matter (DOM). However, little is known about the varying photodegradation of CDOM from different sources and the effects on the optical indices of DOM composition. This was studied for typical natural and anthropogenic sources (plant and leaf litter leachates, the influent and effluent of a wastewater treatment plant, and a river). The CDOM absorption (a₂₈₀) showed a lower degradability for the plant leachate than other sources, mainly due to its low molecular weight and aromaticity. Four fluorescent components were identified with excitation-emission matrices-parallel factor analysis (EEMs-PARAFAC), namely benzoic acid/monolignol-like C1, humic-like C2 and C3, and tryptophan-like C4. The plant leachate contained mainly C1, which was photodegraded moderately, while other sources had more C2 and C3 with higher photodegradability. C4 was photodegraded in most sources but was photoproduced in the leaf litter leachate. The absorption slope (S_275-295) and slope ratio (S_R) increased while the humification index (HIX) decreased, suggesting a decreasing molecular weight and humic content by photodegradation. This was consistent with the decreasing %C2 and %C3 but increasing %C4, which indicated preferential removal of humic-like components. The %C1, %C2, biological index (BIX), and fluorescence index (FI) were less affected by photodegradation than other indices for most sources. These results have implications for a better understanding of the photochemistry of CDOM and the applications of optical indices.

Concentrations of dissolved organic matter and methane in lakes in Southwest China: Different roles of external factors and in-lake biota

Many factors have been reported to affect material cycling in lakes, but the combined and cascading impacts of external environmental factors and in-lake biota on lake carbon cycling are poorly understood. We elucidated the influencing pathways of geoclimatic factors, lake morphometry, land-use type, chemical and physical factors, and biological taxa (phytoplankton and macroinvertebrates) on the concentrations of two important components of carbon cycling, i.e., dissolved organic matter (DOM) and methane (CH₄) based on datasets from 64 plateau lakes in Southwest China. Partial least squares path modelling (PLS-PM) indicated that (1) geoclimatic factors influenced DOM and CH₄ by affecting land use and lake physical factors (e.g., water temperature), (2) lake morphometry (water depth and lake area) had a direct and great negative effect on the CH₄ concentration related to the production and oxidation of CH₄ and affected phytoplankton and macroinvertebrates by influencing chemical and physical factors, (3) land-use type affected DOM and CH₄ concentrations in both direct and indirect ways, (4) terrestrial humic-like DOM was mainly discharged from forestland and also affected by macroinvertebrates, while the impacts of agricultural and construction land on autochthonous DOM and CH₄ concentrations mainly occurred by changing nutrients and then the aquatic biota. Moreover, changes in aquatic biota, primarily affected by water quality, influenced DOM spectral properties, and the two biotas affected DOM and CH₄ concentrations differently. Phytoplankton, especially cyanobacteria contributed to (protein-like and humic-like) DOM in both direct and indirect ways related to eutrophication, whereas macroinvertebrates influenced DOM possibly by utilization, bioturbation, and microbial decomposition of feces according to their different relationships with DOM spectral indices. Additionally, CH₄ production can be enhanced by DOM accumulation, and the significant positive correlations of CH₄ concentrations with protein-like DOM and biological index indicate that autochthonous DOM may play an important role for the CH₄ production. Our findings contribute to the understanding of lake carbon cycling under natural conditions and anthropogenic disturbances.

Roles of microplastic-derived dissolved organic matter on the photodegradation of organic micropollutants

Microplastic-derived dissolved organic matter (MP-DOM) is ubiquitous in water environment and exhibits photosensitivity. However, little is known about the effects of MP-DOM on the photodegradation of organic micropollutants in natural water. In this study, we investigated the effect of MP-DOM derived from two typical plastics, i.e., polystyrene (PS), and polyethylene (PE), on the photodegradation of a typical organic micropollutants sulfamethoxazole (SMX) in a simulative natural water system. MP-DOM exerted a significant inhibition on the SMX photodegradation, mainly attributed to the direct photolysis inhibition of SMX caused by the inner filter effect and the complexation effect. Despite the enhanced reactive oxygen species (ROS) generation with the increase of their steady-state concentration by 41.1 - 160.7 %, PS-DOM exhibited high oxidation resistance, causing an inhibition on the photodegradation of SMX probably through transferring electrons to the SMX intermediates. This study helps to deepen the understanding of microplastic photochemical behavior in natural water.

Riverine dissolved organic matter (DOM) as affected by urbanization gradient

Rapid urbanization has considerably altered carbon biogeochemical cycle and river hydrology. However, the influences of urban land use and urban-induced nutrient increase on dissolved organic matter (DOM) characteristics are poorly understood. Here we hypothesize that the alterations significantly change sources and levels of DOM in river systems that drain the urban areas. To test the hypothesis, we investigated DOM in headwater rivers with varied urban intensities in the Three Gorges Reservoir Area (TGRA), China, through field sampling conducted in the dry and wet seasons. We found positive relationships of urban land (%Urban) with DOC concentration and chromophoric DOM (CDOM) absorption coefficients a₂₅₄, a₂₈₀ and a₃₅₀, as well as fluorescence index (FI₃₇₀), indicating the significantly increased levels of DOM and autochthonous sources along an urbanization gradient. A stepwise regression analysis demonstrated that occurrences of DOC and CDOM can be predicted by %Urban, while increasing autochthonous source is predictable by the increase in riverine nitrogen. Moreover, a₂₅₄, a₂₈₀ and FI₃₇₀ values showed distinct seasonal variations, with significantly higher CDOM concentration in the wet season and with much higher autochthonous signal in the dry season with high nitrogen loading. Based on the findings, we conclude that urbanization influences occurrences and sources of DOM, with increasing urbanization making an important and direct contribution to DOM, and an indirect effect of urban induced nutrient enrichment, i.e., enhanced nutrient loadings increase autochthonous DOM production in rivers.

Degradation of pesticide wastewater with simultaneous resource recovery via ozonation coupled with anaerobic biochemical technology

The effective treatment of pesticide wastewater with high organic content, complex composition and high-toxicity has attracted enormous attention of researchers. This work proposes a new idea for removing the pesticide wastewater with simultaneous resource recovery, which is different from the traditional view of mineralization of pesticide wastewater via composite technology. This novel strategy involved a sequential three-step treatment: (a) acidic Ozonation process, to remove the venomous aromatic heterocyclic compounds; (b) hydrolysis and ozonation in alkaline conditions, enhancing the biodegradability of pesticide wastewater, mainly due to the dehalogenation, elimination of C=C bonds and production of low molecular-weight carboxylate anions; (c) the final step is anaerobic biological reactions. Based on the characterizations, this two-stage acidic-alkaline ozonation can efficiently degraded the virulence of pesticide wastewater and enhance its biodegradability from 0.08 to 0.32. The final anaerobic biochemical treatment can stably remove the residuals and convert the low molecular-weight organics into CH₄, achieving the resource recovery. This work explored the pH-dependent of ozonized degradation of pesticide wastewater and gives a new perspective of wastewater treatment.

The Impacts of Precipitation on Fluorescent Dissolved Organic Matter (FDOM) in an Urban River System

Precipitation is considered a key factor influencing the fluorescent dissolved organic matter (FDOM) of urban rivers. However, the multiple effects of precipitation on FDOM in urban rivers and the long-term impacts of precipitation on the spatial patterns of FDOM are seldom known. Spatiotemporal variations of FDOM at 36 sites from the urban rivers of Jinan City during dry and wet seasons were investigated in this study. Four components were identified using an excitation–emission matrix and parallel factor analysis. Overall, the total fluorescence intensities in dry and wet seasons ranged from 6.59 to 35.7 quinine sulfate units (QSU) and 3.42 to 69.3 QSU, respectively. Significant variations were found for different components that C2 and C3 declined but C4 increased in the wet season (p < 0.05). The temporal variations for different components could be explained by the different combined effects of precipitation dilution and flushing. Three different reference FDOM sources, including background water, spring water, and wastewater treatment plant (WWTP) outlets, were illustrated using principal coordinate analysis (PCoA). The places of FDOM in most sites were more closed to the PCoA location of WWTP outlets in the dry season while central shifted in the wet season. The changes of FDOM sources in the wet season could be explained by the mixed effect of precipitation. In conclusion, this study provided new insights into the multiple impacts of precipitation on FDOM in urban river systems, and also data support for precise pollution discharge and water resource management.

UAV Multispectral Image-Based Urban River Water Quality Monitoring Using Stacked Ensemble Machine Learning Algorithms—A Case Study of the Zhanghe River, China

Timely monitoring of inland water quality using unmanned aerial vehicle (UAV) remote sensing is critical for water environmental conservation and management. In this study, two UAV flights were conducted (one in February and the other in December 2021) to acquire images of the Zhanghe River (China), and a total of 45 water samples were collected concurrently with the image acquisition. Machine learning (ML) methods comprising Multiple Linear Regression, the Least Absolute Shrinkage and Selection Operator, a Backpropagation Neural Network (BP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) were applied to retrieve four water quality parameters: chlorophyll-a (Chl-a), total nitrogen (TN), total phosphors (TP), and permanganate index (CODMn). Then, ML models based on the stacking approach were developed. Results show that stacked ML models could achieve higher accuracy than a single ML model; the optimal methods for Chl-a, TN, TP, and CODMn were RF-XGB, BP-RF, RF, and BP-RF, respectively. For the testing dataset, the R2 values of the best inversion models for Chl-a, TN, TP, and CODMn were 0.504, 0.839, 0.432, and 0.272, the root mean square errors were 1.770 μg L−1, 0.189 mg L−1, 0.053 mg L−1, and 0.767 mg L−1, and the mean absolute errors were 1.272 μg L−1, 0.632 mg L−1, 0.045 mg L−1, and 0.674 mg L−1, respectively. This study demonstrated the great potential of combined UAV remote sensing and stacked ML algorithms for water quality monitoring.

Adsorption of humic acids to lake sediments: Compositional fractionation, inhibitory effect of phosphate, and implications for lake eutrophication

Humic acid (HA) and phosphate interactions play a vital role in the biogeochemical cycle of carbon and nutrients and thus the trophic state of a lake. The adsorption behavior of HAs to sediments in the absence and presence of phosphate was investigated in this study. Three types of HAs were used, AHA from algae-dominated lake sediments, MHA from macrophyte-dominated lake sediments, and a reference HA (RHA) with terrestrial sources. The adsorption capacity of lake sediments was highest for AHA, which can be explained by that AHA contained more carboxyl-containing molecules, proteinaceous compounds and polysaccharides that were preferentially adsorbed by minerals. Phosphate showed a stronger inhibitory effect on MHA adsorption than on AHA adsorption, suggesting that AHA can more effectively replace phosphate adsorbed to sediments. Our findings show that the functional groups of organic compounds control not only their fractionation and burial but also their ability to replace phosphate in sediments. We propose a novel mechanism to explain the legacy effect of lake eutrophication. That is, as lakes shift from a macrophyte-dominated state to more eutrophic, algae-dominated state, increasing algae-derived organic compounds can promote the release of phosphate from sediments, forming a positive feedback loop that sustains internal phosphorus loading and hence lake eutrophication.

Remote monitoring of total dissolved phosphorus in eutrophic Lake Taihu based on a novel algorithm: Implications for contributing factors and lake management

Understanding the spatiotemporal dynamics of total dissolved phosphorus concentration (C_TDP) and its regulatory factors is essential to improving our understanding of its impact on inland water eutrophication, but few studies have assessed this in eutrophic inland lakes due to a lack of suitable bio-optical algorithms allowing the use of remote sensing data. We developed a novel semi-analytical algorithm for this purpose and tested it in the eutrophic Lake Taihu, China. Our algorithm produced robust results with a mean absolute square percentage error of 29.65% and root mean square error of 9.54 μg/L. Meanwhile, the new algorithm demonstrates good portability to other waters with different optical properties and could be applied to various image data, including Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Ocean and Land Color Instrument (OLCI). Further analysis based on Geostationary Ocean Color Imager observations from 2011 to 2020 revealed a significant spatiotemporal heterogeneity of C_TDP in Lake Taihu. Correlation analysis of the long-term trend between C_TDP and driving factors demonstrated that air temperature is the dominant regulating factor in variations of C_TDP. This study provides a novel algorithm allowing remote-sensing monitoring of C_TDP in eutrophic lakes and can lead to new insights into the role of dissolved phosphorus in water eutrophication.

Progress in the interaction of dissolved organic matter and microbes (1991-2020): a bibliometric review

Dissolved organic matter (DOM) and microbes are key in the planetary carbon cycle, and research on them can lead to a better understanding of the global carbon cycle and an improved ability to cope with environmental challenges. Several papers have reviewed one or several aspects of the interaction of DOM and microbes, but no overall review has been performed. Here, we bibliometrically analyzed all publications from the Web of Science on DOM and microbes (1991-2020). The results showed that studies on DOM and microbes grew exponentially during this period; the USA contributed the most to the total publications, and China has had the fastest increasing rate since 2010. Moreover, we used the Latent Dirichlet Allocation model to identify topics and determine their (cold or hot) trends by analyzing the abstracts of 9851 publications related to DOM and microbes. A total of 96 topics were extracted, and these topics that are related to the source, composition, and removal path of DOM and the temporal-spatial patterns of DOM and microbes consistently rose from 1991 to 2020. Most studies have used accurate and rapid methods combined with microbiological genetic approaches to study the interaction of DOM and microbes in terrestrial and aquatic ecosystems. The results also showed that the impacts of climate change and land use on the interaction of DOM and microbes, and topics related to human health have received considerable attention. In the future, the interaction mechanism of DOM and microbes and its response to environmental change should be further elucidated.

Photogeochemistry of particulate organic matter in aquatic systems: A review

Photochemical transformation of natural organic matter in aquatic environments strongly impacts the environmental behaviors of carbon, nutrients, and pollutants by affecting their solubility, toxicity, bioavailability, and mobility. However, the role of particulate organic matter (POM) in environmental photogeochemistry has received much less attention than that of dissolved organic matter (DOM). In this study, a systematic overview was conducted to summarize the photodissolution and photoflocculation of POM in aquatic systems. The photodissolution of various POM, such as resuspended sediments and algal detritus, could be a potential and important source of DOM in the overlying waters, and these photoreleased DOM were dominated by humic-like components. The photogeochemistry of POM is thought to proceed via direct photochemical reactions and reactive radical-dominated indirect processes. Photodissolution can modify the bioavailability of organic matter and influence the biogeochemical cycling of nutrients, heavy metals, and organic pollutants. In addition, the photo-induced flocculation of DOM to POM could also influence the transport and transformation of organic matter and its associated pollutants. The photochemistry of POM can be significantly influenced by several environmental factors, including irradiation wavelength and intensity, organic matter properties, and radical oxygen species. POM photogeochemistry is one of the most important components of the global cycling of natural organic matter. Further studies regarding photogeochemistry should be conducted to overcome the potential problems arising from the concurrent photodegradation of organic matter and to further develop more filed investigations and analytical methods.

Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters.

Characterizing variations in dissolved organic matter (DOM) properties in Nansi Lake: a typical macrophytes-derived lake in northern China

Nansi Lake is the largest lake along the eastern route of China's South-to-North Water Diversion Project (SNWDP). It is divided into the upper lake and the lower lake by a dam. By using UV-Vis spectroscopy, synchronous fluorescence (SF) spectroscopy, excitation-emission matrix and parallel factor analysis (EEM-PARAFAC), spatial, and temporal differences in the properties of dissolved organic matter (DOM) were found in the 2 areas of Nansi Lake under different hydrological conditions. A total of 5 fluorescence components were obtained by EEM-PARAFAC, which included 3 humic-like components (C1-C3) and 2 protein-like components (C4 and C5). On the spatial scale, the fluorescence intensities (F_max) of humic-like substances and the ratio of the fluorescence intensity of humic-like components to the total fluorescence intensity (%F_max) and degree of humification (HIX) in the upper lake were higher than those in the lower lake. This indicated the strong contributions of terrestrial sources to the upper lake, while DOM properties in the lower lake were more endogenous than those in the upper lake. On the temporal scale, protein-like substances played a more important role in DOM properties in April (F_max=0.72±0.03 in the upper lake and 1.84±0.13 in the lower lake) and July (F_max=1.10±0.05 in the upper lake and 1.49±0.04 in the lower lake) than in October. This result might be related to the water transfer of the eastern route of the SNWDP and to the death of submerged plants. However, the contents of humic-like substances (ranging from 55.61±1.23% to 66.56±0.58% for the upper lake and 29.98±1.56% to 61.98±0.99% for the lower lake) and degree of humification (from 2.23±0.06 to 3.10±0.05 for the upper lake and 1.06±0.05 to 2.62±0.08 for the lower lake) in Nansi Lake showed an increasing trend from April to October. In addition, significant correlations and good linear relationships between humic-like components, a₂₅₄, and DOC in the 3 months reflected the continuous contribution of humic-like substances to DOM properties in Nansi Lake. Rapid changes in the fluorescence signal were largely dependent on changes in water quality. The fluorescence signal could be a tool for the management of water quality in Nansi Lake.

Urban Water Quality Assessment Based on Remote Sensing Reflectance Optical Classification

With the acceleration of urbanization, increasing water pollution means that monitoring and evaluating urban water quality are of great importance. Although highly accurate, traditional evaluation methods are time consuming, laborious, and vastly insufficient in terms of the continuity of spatiotemporal coverage. In this study, a water quality assessment method based on remote sensing reflectance optical classification and the traditional grading principle is proposed. In this method, an optical water type (OWT) library was first constructed using the measured in situ remote sensing reflectance dataset based on fuzzy clustering technology. Then, comprehensive scoring rules were established by combining OWTs and 12 water quality parameters, and water quality was graded into different urban water quality levels (UWQLs) based on the scoring results. Using the proposed method, the relative water quality of urban waterbodies was qualitatively evaluated at the macro level based on images from the multispectral imager of Sentinel-2. In addition, there was a significant positive correlation between the UWQLs and the water quality index (WQI). These results indicate the potential of this method for quantitative assessment of urban water quality, providing a new way to evaluate water quality using remote sensing algorithms in the future.

Machine Learning Algorithms for Chromophoric Dissolved Organic Matter (CDOM) Estimation Based on Landsat 8 Images

Chromophoric dissolved organic matter (CDOM) is crucial in the biogeochemical cycle and carbon cycle of aquatic environments. However, in inland waters, remotely sensed estimates of CDOM remain challenging due to the low optical signal of CDOM and complex optical conditions. Therefore, developing efficient, practical and robust models to estimate CDOM absorption coefficient in inland waters is essential for successful water environment monitoring and management. We examined and improved different machine learning algorithms using extensive CDOM measurements and Landsat 8 images covering different trophic states to develop the robust CDOM estimation model. The algorithms were evaluated via 111 Landsat 8 images and 1708 field measurements covering CDOM light absorption coefficient a(254) from 2.64 to 34.04 m−1. Overall, the four machine learning algorithms achieved more than 70% accuracy for CDOM absorption coefficient estimation. Based on model training, validation and the application on Landsat 8 OLI images, we found that the Gaussian process regression (GPR) had higher stability and estimation accuracy (R2 = 0.74, mean relative error (MRE) = 22.2%) than the other models. The estimation accuracy and MRE were R2 = 0.75 and MRE = 22.5% for backpropagation (BP) neural network, R2 = 0.71 and MRE = 24.4% for random forest regression (RFR) and R2 = 0.71 and MRE = 24.4% for support vector regression (SVR). In contrast, the best three empirical models had estimation accuracies of R2 less than 0.56. The model accuracies applied to Landsat images of Lake Qiandaohu (oligo-mesotrophic state) were better than those of Lake Taihu (eutrophic state) because of the more complex optical conditions in eutrophic lakes. Therefore, machine learning algorithms have great potential for CDOM monitoring in inland waters based on large datasets. Our study demonstrates that machine learning algorithms are available to map CDOM spatial-temporal patterns in inland waters.