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Ding H, Gao H, Zhu M, Yu M, Sun Y, Zheng M, Su J, Xi B. Spectral and molecular insights into the characteristics of dissolved organic matter in nitrate-contaminated groundwater. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 355:124202. [PMID: 38788994 DOI: 10.1016/j.envpol.2024.124202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/11/2024] [Accepted: 05/17/2024] [Indexed: 05/26/2024]
Abstract
The characteristics of dissolved organic matter (DOM) serve as indicators of nitrate pollution in groundwater. However, the specific DOM components associated with nitrate in groundwater systems remain unclear. In this study, dual isotopes of nitrate, three-dimensional Excitation emission matrices (EEMs) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) were utilized to uncover the sources of nitrate and their associations with DOM characteristics. The predominant nitrate in the targeted aquifer was derived from soil organic nitrogen (mean 46.0%) and manure &sewage (mean 34.3%). The DOM in nitrate-contaminated groundwater (nitrate-nitrogen >20 mg/L) exhibited evident exogenous characteristics, with a bioavailable content 2.58 times greater than that of uncontaminated groundwater. Regarding the molecular characteristics, DOM molecules characterized by CHO + 3N, featuring lower molecular weights and H/C ratios, indicated potential for mineralization, while CHONS formulas indicated the exogenous features, providing the potential for accurate traceability. These findings provided insights at the molecular level into the characterization of DOM in nitrate-contaminated groundwater and offer scientific guidance for decision-making regarding the remediation of groundwater nitrate pollution.
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Affiliation(s)
- Hongyu Ding
- College of Water Science, Beijing Normal University, Beijing, 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Huan Gao
- CCCC Water Transportation Consultants Co., Ltd, Beijing, 100010, China
| | - Mingtan Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Minda Yu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Environment and Civil Engineering, Jiangnan University, Wuxi, 214122, China
| | - Yuanyuan Sun
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Mingxia Zheng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Jing Su
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Beidou Xi
- College of Water Science, Beijing Normal University, Beijing, 100875, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Chen Y, Awais M, Wu J, Li Z, Abbas Naqvi SMZ, Abdulraheem MI, Zhang H, Wang L, Zhang W, Raghavan V, Hu J. Evaluation of agricultural non-point source pollution using an in-situ and automated photochemical flow analysis system. Sci Rep 2024; 14:14434. [PMID: 38910171 DOI: 10.1038/s41598-024-65251-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 06/18/2024] [Indexed: 06/25/2024] Open
Abstract
Off-line leachate collection from agricultural landscapes cannot guarantee precise evaluation of agricultural non-point source (ANPS) due to geospatial variations, time, and transportation from the field to the laboratory. Implementing an in-situ nitrogen and phosphorous monitoring system with a robust photochemical flow analysis is imperative for precision agriculture, enabling real-time intervention to minimize non-point source pollution and overcome the limitations posed by conventional analysis in laboratory. A reliable, robust and in-situ approach was proposed to monitor nitrogen and phosphorous for determining ANPS pollution. In this study, a home-made porous ceramic probe and the frequency domain reflectometer (FDR) based water content sensors were strategically placed at different soil depths to facilitate the collection of leachates. These solutions were subsequently analyzed by in-situ photochemical flow analysis monitoring system built across the field to estimate the concentrations of phosphorus and nitrogen. After applying both natural and artificial irrigation to the agricultural landscape, at least 10 mL of soil leachates was consistently collected using the porous ceramic probe within 20 min, regardless of the depth of the soil layers when the volumetric soil water contents are greater than 19%. The experimental results showed that under different weather conditions and irrigation conditions, the soil water content of 50 cm and 90 cm below the soil surface was 19.58% and 26.08%, respectively. The average concentrations of NH4+-N, NO3--N, PO43- are 0.584 mg/L, 15.7 mg/L, 0.844 mg/L, and 0.562 mg/L, 16.828 mg/L and 0.878 mg/L at depths of 50 cm and 90 cm below the soil surface, respectively. Moreover, the comparison with conventional laboratory spectroscopic analysis confirmed R2 values of 0.9951, 0.9943, 0.9947 average concentration ranges of NH4+-N, NO3--N, and PO43-, showcasing the accuracy and reliability of robust photochemical flow analysis in-situ monitoring system. The suggested monitoring system can be helpful in the assessment of soil nutrition for precision agriculture.
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Affiliation(s)
- Yongqi Chen
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
- State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, 450002, China
| | - Muhammad Awais
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
| | - Junfeng Wu
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
| | - Zhenfeng Li
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
| | - Syed Muhammad Zaigham Abbas Naqvi
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
| | - Mukhtar Iderawumi Abdulraheem
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
| | - Hao Zhang
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
- State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, 450002, China
| | - Ling Wang
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
- State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, 450002, China
| | - Wei Zhang
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China
- State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, 450002, China
| | - Vijaya Raghavan
- Department of Bioresource Engineering, Faculty of Agriculture and Environmental Studies, McGill University, Sainte-Anne-de-Bellevue, QC, H9X 3V9, Canada
| | - Jiandong Hu
- Department of Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
- Henan International Joint Laboratory of Laser Technology in Agriculture Science, Zhengzhou, 450002, China.
- State Key Laboratory of Wheat and Maize Crop Science, Zhengzhou, 450002, China.
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Wu C, Zhao Y, Geng Y, Shi K, Zhou S. Characterizing the regional distribution, interaction with microorganisms, and sources of dissolved organic matter for summer rainfall: Insights from spectroscopy, community structure, and back-trajectory analyses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:172086. [PMID: 38556025 DOI: 10.1016/j.scitotenv.2024.172086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 03/15/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024]
Abstract
Dissolved organic matter (DOM) in rainfall participates in many biogeochemical cycles in aquatic environments and affects biological activities in water bodies. Revealing the characteristics of rainfall DOM could broaden our understanding of the carbon cycle. Therefore, the distribution characteristics and response mechanisms of DOM to microorganisms were investigated in different regions of Hebei. The results indicated that the water quality of the northern region was worse than that of the middle and southern regions. The two protein like components (C1, C2) and one humic like component (C3) were obtained; at high molecular weight (MW), the fluorescence intensity is high in the northern region (0.03 ± 0.02 R.U.), while at low MW, the fluorescence intensity is highest in the southern region (0.50 ± 0.18 R.U.). Furthermore, C2 is significantly positively correlated with C1 (P < 0.01), while C2 is significantly negatively correlated with C3 (P < 0.05) was observed. The spectral index results indicated that rainfall DOM exhibited low humification and highly autochthonous characteristics. The southern region obtained higher richness and diversity of microbial species than northern region (P < 0.05). The community exhibits significant spatiotemporal differences, and the Acinetobacter, Enterobacter, and Massilia, were dominant genus. Redundancy and network analyses showed that the effects of C1, C2, and nitrate on microorganisms increased with decreasing MW, while low MW exhibited a more complex network between DOM and microorganisms than high MW. Meanwhile, C1, C2 had a large total effect on β-diversity and function through structural equation modeling. The backward trajectory model indicates that the sources of air masses are from the northwest, local area, and sea in the northern, middle, and southern regions, respectively. This study broadened the understanding of the composition of summer rainfall DOM and its interactions with microorganisms during rainfall.
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Affiliation(s)
- Chenbin Wu
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China
| | - Yuting Zhao
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China
| | - Yuting Geng
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China
| | - Kun Shi
- School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China
| | - Shilei Zhou
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China; School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, PR China.
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Pan T, Zhang Y, Yang F, Liao H, Feng W, Sun F, Jiang W, Wang Q, Ji M, Yang C, Leppäranta M. Characteristics of the presence and migration patterns of DOM between ice and water in the cold and arid Daihai Lake. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170876. [PMID: 38367733 DOI: 10.1016/j.scitotenv.2024.170876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 02/04/2024] [Accepted: 02/08/2024] [Indexed: 02/19/2024]
Abstract
Seasonal ice cover plays a crucial role in shaping the physical characteristics of lakes in cold and arid regions. Moreover, the ice significantly affects the level and quality of dissolved organic matter (DOM) in the water column. We utilized spectroscopy and mass spectrometry to analyze the molecular composition and distribution of DOM in ice cores and under-ice water in Daihai Lake. We identified the main environmental factors affecting DOM migration through structural equation modelling (SEM). The freezing process created a repulsive effect on DOM, with water samples demonstrating a greater DOM content than ice. The dominant part of the DOM in the ice cores was mainly comprised of protein-like materials (71.45 %), whereas water consisted of humus-like materials (54.81 %). The average molecular weight of the ice cover DOM (m/z = 396.77) was smaller than in the under-ice water (m/z = 405.42). While low-molecular and low-aromatic protein-like material tended to be trapped in the ice layer during ice formation, large-molecular and highly aromatic humic substances were more easily expelled into the water. Interestingly, condensed aromatic hydrocarbons were found to occur less frequently in the ice phase (11 %) compared to the aqueous phase (13 %). Both the lipid and protein/aliphatic compound structures exhibited slightly higher ratios in the ice (6 % and 8 %, respectively) than in water (1 % and 5 %, respectively). SEM between the ice cover environment and DOM indicated that the ice can influence the distribution pattern of DOM through the regulation of internal solute factors and other chemicals. The nature of the DOM and the rate of ice growth also play critical roles in determining the distribution mechanism of DOM for ice and water. The pollutant distribution characteristics and migration patterns between ice and water are essential for comprehending environmental water pollution and promoting pollution management and protection measures in cold region lakes.
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Affiliation(s)
- Ting Pan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yimeng Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; Shandong Huankeyuan Environmental Engineering Co., Ltd, Jinan 250000, China
| | - Fang Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Haiqing Liao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Weiying Feng
- School of Space and Environment, Beihang University, Beijing 100191, China
| | - Fuhong Sun
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Weilong Jiang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Qianqian Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Meichen Ji
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Chenglei Yang
- Shandong Huankeyuan Environmental Engineering Co., Ltd, Jinan 250000, China
| | - Matti Leppäranta
- Institute for Atmospheric and Earth System Research, University of Helsinki, 00014 Helsinki, Finland
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Peng Y, Liu L, Wang X, Teng G, Fu A, Wang Z. Source apportionment based on EEM-PARAFAC combined with microbial tracing model and its implication in complex pollution area, Wujin District, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 346:123596. [PMID: 38369097 DOI: 10.1016/j.envpol.2024.123596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/12/2024] [Accepted: 02/15/2024] [Indexed: 02/20/2024]
Abstract
Further improving the quality of surface water is becoming more difficult after the control of main point-sources, especially in the complex pollution area with mixed industrial and agricultural productions, whereas the pollution source apportionment might be the key to quantify different pollution sources and developing some effective measures. In this study, a technical framework for source apportionment based on three-dimensional fluorescence and microbial traceability model is developed. Based on screening of the main environmental factors and their spatiotemporal characteristics, potential pollution sources have been tentatively identified. Then, the pollution sources are further tested based on the analysis of fluorescence excitation-emission matrix (EEM) and the similarity of fluorescence components in surface water and potential pollution sources. At the same time, the correlation between microbial species and pollution sources is constructed by analyzing the spatiotemporal characteristics of microbial composition and the response of main species to environmental factors. Therefore, pollution source apportionment is quantified using PCA-APCS-MLR, Fast Expectation-maximization for Microbial Source Tracking (FEAST), and Bayesian community-wide culture-independent microbial source tracking (SourceTracker). PCA-APCS-MLR could not effectively distinguish the contributions of different industrial sources in the complex environment of this study, and the contribution of unknown sources was high (average 39.60%). In contrast, the microbial traceability model can accurately identify the contribution of 7 pollution sources and natural sources, effectively reduce the proportion of unknown sources (average of FEAST is 19.81%, SourceTracker is 16.72%), and show better pollution identification and distribution capabilities. FEAST exhibits a more sensitive potential in source apportionment and shorter calculation time than SourceTracker, thus might be used to guide the precise regional pollution control, especially in the complex pollution environments.
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Affiliation(s)
- Yuanjun Peng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Lili Liu
- State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, East China University of Science and Technology, Shanghai, 200237, China
| | - Xu Wang
- State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, East China University of Science and Technology, Shanghai, 200237, China
| | - Guoliang Teng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Anqing Fu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhiping Wang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Gao X, Liu Y, Tang C, Lu M, Zou J, Li Z. Evaluating river health through respirogram metrics: Insights from the Weihe River basin, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170805. [PMID: 38342463 DOI: 10.1016/j.scitotenv.2024.170805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/18/2024] [Accepted: 02/06/2024] [Indexed: 02/13/2024]
Abstract
Human activities pose a significant threat to rivers, requiring robust assessment methods for effective river management. This study focuses on the Weihe River Basin in Shaanxi province and introduces the respirogram as an innovative assessment technique. The respirogram allows the simultaneous assessment of river health from two important aspects: pollution levels and microbial status. Specifically, the in-situ respiration ratio (Rs/t) serves as an indicator of pollution, with higher Rs/t values correlating with increased pollution levels. Conversely, the recovery index (RI) measures microbial vitality, with values below 0.15 indicating greater microbial activity and recovery potential. Using predefined thresholds of Rs/t = 0.3 and RI = 0.15, water bodies were categorized into four types. For example, rivers with Rs/t > 0.3 and RI > 0.15 were identified as receiving sewage, characterized by high pollution and low microbial vitality. Similarly, different assessment criteria delineated urban rivers, natural rivers, and wastewater treatment plants. Based on these classifications, targeted engineering measures were proposed to enhance the self-purification capabilities of rivers of different statuses.
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Affiliation(s)
- Xingdong Gao
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Yanxia Liu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Congcong Tang
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Meng Lu
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Jiageng Zou
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Zhihua Li
- Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Xi'an Key Laboratory of Intelligent Equipment Technology for Environmental Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.
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Wang K, Jiang J, Zhu Y, Zhou Q, Bing X, Tan Y, Wang Y, Zhang R. Characteristics of DOM and Their Relationships with Potentially Toxic Elements in the Inner Mongolia Section of the Yellow River, China. TOXICS 2024; 12:250. [PMID: 38668473 PMCID: PMC11054287 DOI: 10.3390/toxics12040250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/29/2024]
Abstract
The characterization of dissolved organic matter (DOM) is important for better understanding of the migration and transformation mechanisms of DOM in water bodies and its interaction with other contaminants. In this work, fluorescence characteristics and molecular compositions of the DOM samples collected from the mainstream, tributary, and sewage outfall of the Inner Mongolia section of the Yellow River (IMYR) were determined by using fluorescence spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). In addition, concentrations of potentially toxic elements (PTEs) in the relevant surface water and their potential relationships with DOM were investigated. The results showed that the abundance of tyrosine-like components increased significantly in downstream waters impacted by outfall effluents and was negatively correlated with the humification index (HIX). Compared to the mainstream, outfall and tributaries have a high number of molecular formulas and a higher proportion of CHOS molecular formulas. In particular, the O5S class has a relative intensity of 41.6% and the O5-7S class has more than 70%. Thirty-eight PTEs were measured in the surface water samples, and 12 found above their detective levels at all sampling sites. Protein-like components are positively correlated with Cu, which is likely indicating the source of Cu in the aquatic environment of the IMYR. Our results demonstrated that urban wastewater discharges significantly alter characteristics and compositions of DOM in the mainstream of IMYR with strongly anthropogenic features. These results and conclusions are important for understanding the role and sources of DOM in the Yellow River aquatic environment.
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Affiliation(s)
- Kuo Wang
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
| | - Juan Jiang
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
- College of Environment, Hohai University, Nanjing 210098, China
| | - Yuanrong Zhu
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
| | - Qihao Zhou
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
| | - Xiaojie Bing
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Yidan Tan
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
| | - Yuyao Wang
- State Key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (K.W.); (J.J.); (Q.Z.); (X.B.); (Y.T.); (Y.W.)
| | - Ruiqing Zhang
- School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China;
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Xiong Q, Song Y, Shen J, Liu C, Chai Y, Wang S, Wu X, Cheng C, Wu J. Fluorescence fingerprint as an indicator to identify urban non-point sources in urban river during rainfall period. ENVIRONMENTAL RESEARCH 2024; 245:118009. [PMID: 38141914 DOI: 10.1016/j.envres.2023.118009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 12/25/2023]
Abstract
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 = ∼230(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.
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Affiliation(s)
- Qiuran Xiong
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yiming Song
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jian Shen
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Chuanyang Liu
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Yidi Chai
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Siting Wang
- Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China
| | - Xiaojin Wu
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Cheng Cheng
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
| | - Jing Wu
- Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision, School of Environment, Tsinghua University, Beijing, 100084, China; Research and Development Center of Advanced Environmental Supervision Technology and Instrument, Research Institute for Environmental Innovation (Suzhou) Tsinghua, Suzhou, 215163, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
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9
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Cai X, Lei S, Li Y, Li J, Xu J, Lyu H, Li J, Dong X, Wang G, Zeng S. Humification levels of dissolved organic matter in the eastern plain lakes of China based on long-term satellite observations. WATER RESEARCH 2024; 250:120991. [PMID: 38113596 DOI: 10.1016/j.watres.2023.120991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/23/2023] [Accepted: 12/07/2023] [Indexed: 12/21/2023]
Abstract
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.
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Affiliation(s)
- Xiaolan Cai
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Shaohua Lei
- National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China
| | - Yunmei Li
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China.
| | - Jianzhong Li
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Jie Xu
- Yangtze River Basin Ecological Environment Monitoring and Scientific Research Center, Yangtze River Basin Ecological Environment Supervision and Administration Bureau, Ministry of Ecological Environment, Wuhan 430010, China
| | - Heng Lyu
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Junda Li
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Xianzhang Dong
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Gaolun Wang
- School of Geography, Key Laboratory of Virtual Geographic Environment of Education Ministry, Jiangsu Center for Collaboration Invocation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
| | - Shuai Zeng
- Ministry of Ecology and Environment, South China Institute of Environmental Science, Guangzhou 510535, China
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10
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Pan B, Liu S, Wang Y, Li D, Li M. FT-ICR-MS combined with fluorescent spectroscopy reveals the driving mechanism of the spatial variation in molecular composition of DOM in 22 plateau lakes. ENVIRONMENTAL RESEARCH 2023:116272. [PMID: 37276978 DOI: 10.1016/j.envres.2023.116272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/21/2023] [Accepted: 05/27/2023] [Indexed: 06/07/2023]
Abstract
Dissolved organic matter (DOM) is the largest carbon pool and directly affects the biogeochemistry in lakes. In the current study, fourier transform ion cyclotron mass spectrometry (FT-ICR-MS) combined with fluorescent spectroscopy was used to assess the molecular composition and driving mechanism of DOM in 22 plateau lakes in Mongolia Plateau Lakes Region (MLR), Qinghai Plateau Lakes Region (QLR) and Tibet Plateau Lakes Region (TLR) of China. The limnic dissolved organic carbon (DOC) content ranged from 3.93 to 280.8 mg L-1 and the values in MLR and TLR were significantly higher than that in QLR. The content of lignin was the highest in each lake and showed a gradually decreasing trend from MLR to TLR. Random forest model and structural equation model implied that altitude played an important role in lignin degradation while the contents of total nitrogen (TN) and chlorophyll a (Chl-a) have a great influence on the increase of DOM Shannon index. Our results also suggested that the inspissation of DOC and the promoted endogenous DOM production caused by the inspissation of nutrient resulted in a positive relationship between limnic DOC content and limnic factors such as salinity, alkalinity and nutrient concentration. From MLR to QLR and TLR, the molecular weight and the number of double bonds gradually decreased but the humification index (HIX) also decreased. In addition, from the MLR to the TLR, the proportion of lignin gradually decreased, while the proportion of lipid gradually increased. Both above results suggested that photodegradation was dominated in lakes of TLR, while microbial degradation was dominated in lakes of MLR.
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Affiliation(s)
- Baozhu Pan
- State Key Laboratory of Eco-hydraulic in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, 710048, Shaanxi, PR China
| | - Siwan Liu
- College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China
| | - Yeyong Wang
- College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China
| | - Dianbao Li
- State Key Laboratory of Eco-hydraulic in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, 710048, Shaanxi, PR China
| | - Ming Li
- College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi, PR China.
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11
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Zhang T, Chen Z, Zhang Z, Zhou S, Meng J, Chen Z, Zhang J, Cui J, Chai B. Spatial and temporal dynamic response of abundant and rare aerobic denitrifying bacteria to dissolved organic matter in natural water: A case study of Lake Baiyangdian, China. ENVIRONMENTAL RESEARCH 2023; 224:115524. [PMID: 36813068 DOI: 10.1016/j.envres.2023.115524] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/07/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Revealing the responses of abundant and rare aerobic denitrifying bacteria to dissolved organic matter (DOM) composition is essential for understanding the aquatic N cycle ecosystems. In this study, fluorescence region integration and high-throughput sequencing techniques were used to investigate the spatiotemporal characteristics and dynamic response of DOM and aerobic denitrifying bacteria. The DOM compositions were significantly different among the four seasons (P < 0.001) without spatial differences. Tryptophan-like substances (P2, 27.89-42.67%) and microbial metabolites (P4, 14.62-42.03%) were the dominant components, and DOM exhibited strong autogenous characteristics. Abundant (AT), moderate (MT), and rare taxa (RT) of aerobic denitrifying bacteria showed significant and spatiotemporal differences (P < 0.05). The responses of α-diversity and niche breadth of AT and RT to DOM differed. The DOM explanation proportion for aerobic denitrifying bacteria exhibited spatiotemporal differences based on redundancy analysis. Foliate-like substances (P3) had the highest interpretation rate of AT in spring and summer, while humic-like substances (P5) had the highest interpretation rate of RT in spring and winter. Network analysis showed that RT networks were more complex than AT networks. Pseudomonas was the main genus associated with DOM in AT on a temporal scale, and was more strongly correlated with tyrosine-like substances (P1), P2, and P5. Aeromonas was the main genus associated with DOM in AT on a spatial scale and was more strongly correlated with P1 and P5. Magnetospirillum was the main genus associated with DOM in RT on a spatiotemporal scale, which was more sensitive to P3 and P4. Special operational taxonomic units were transformed between AT and RT with seasonal changes, but not between the two regions. To summarize, our results revealed that bacteria with different abundances utilized DOM components differently, and provides new insight on the spatiotemporal response of DOM and aerobic denitrifying bacteria in aquatic ecosystems of biogeochemical significance.
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Affiliation(s)
- Tianna Zhang
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Zhaoying Chen
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Ziwei Zhang
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Shilei Zhou
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China.
| | - Jiajing Meng
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Zhe Chen
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Jiafeng Zhang
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Jiansheng Cui
- Pollution Prevention Biotechnology Laboratory of Hebei Province, School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, PR China
| | - Beibei Chai
- Hebei Collaborative Innovation Center for the Regulation and Comprehensive Management of Water Resources and Water Environment, Hebei University of Engineering, Handan, 056038, PR China
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12
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Ma N, Gao L, Ge Z, Li M. Hydrochemical characteristics of groundwater in a plain river network region: Establishing linkages between source and water quality variables. CHEMOSPHERE 2023; 331:138809. [PMID: 37127199 DOI: 10.1016/j.chemosphere.2023.138809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 04/15/2023] [Accepted: 04/28/2023] [Indexed: 05/03/2023]
Abstract
The chemical characteristics of groundwater can indicate water quality condition and provide useful information for pollution source identification. This study aimed to understand the effects of dissolved organic matter (DOM) on ionic composition of groundwater and identify the main ions and sources of pollution. The Lake Taihu is a typical eutrophic lake in China. In this study, the hydrochemical composition of groundwater in the surrounding aquifer of Lake Taihu Basin was analyzed. The results showed that the values of water quality index (WQI) range from 13.29 to 56.26 (good water quality). The dominant hydrochemical type of groundwater was Ca-Mg-HCO3 type, and the rock dominance was the major mechanism controlling the groundwater chemistry. With an increasing concentration in dissolved organic carbon (DOC), the Na+, Mg2+, and HCO3- concentrations all showed a sharp increase followed by a slow increase, while the NO3- concentration showed an opposite trend, indicating the DOM can affect the ions composition. In addition, K+ was positively correlated with NO3-, As, and Cd. Hence, DOM input may directly or indirectly change the hydrochemistry of groundwater. Besides, the NO3- concentration in groundwater was much higher than that in Lake Taihu, indicating that the NO3- in groundwater mainly came from surface soil leaching. The anthropogenic sources are probably the main sources of different ions, including K+, NO3-, As, and Cd. This study can help to better understand the effects of lake eutrophication on groundwater and its pathways.
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Affiliation(s)
- Ning Ma
- College of Natural Resources and Environment, Northwest A & F University, Yangling, 712100, PR China
| | - Li Gao
- Institute for Sustainable Industries and Liveable Cities, Victoria University, PO Box 14428, Melbourne, Victoria, 8001, Australia
| | - Zhengkui Ge
- College of Natural Resources and Environment, Northwest A & F University, Yangling, 712100, PR China
| | - Ming Li
- College of Natural Resources and Environment, Northwest A & F University, Yangling, 712100, PR China.
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13
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Zhang Y, Cheng D, Song J, Pang R, Zhang H. How does anthropogenic activity influence the spatial distribution of dissolved organic matter in rivers of a typical basin located in the Loess Plateau, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 340:117984. [PMID: 37084646 DOI: 10.1016/j.jenvman.2023.117984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/26/2023] [Accepted: 04/18/2023] [Indexed: 05/03/2023]
Abstract
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.
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Affiliation(s)
- Yixuan Zhang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China; State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Dandong Cheng
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Jinxi Song
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China.
| | - Rui Pang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Hangzhen Zhang
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
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14
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Zhu J, Duo J, Zhang Z, Pei L, Li W, Wufuer R. Spectral Characteristics of Dissolved Organic Matter in Farmland Soils around Urumqi, China. TOXICS 2023; 11:376. [PMID: 37112603 PMCID: PMC10145649 DOI: 10.3390/toxics11040376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 06/19/2023]
Abstract
The dissolved organic matter (DOM) is one of the most sensitive indicators of changes in the soil environment, and it is the most mobile and active soil component that serves as an easily available source of nutrients and energy for microbes and other living organisms. In this paper, DOM structural characteristics and main properties were investigated by three-dimensional fluorescence spectroscopy (EEM) and UV-visible spectrum technology in the farmland soils around Urumqi of China, and its possible sources and pathways were analyzed by spectroscopic indices. The results showed that humic-like substances were the main composition of the soil DOM, and its autogenesis characteristics were not obvious. Main DOM properties such as aromatability, hydrophobicity, molecular weight, molecular size, and humification degree in the southern region of Urumqi were higher than those of the northern region of Urumqi and Fukang in China, and higher on the upper layers of the soil (0-0.1 and 0.2 m) than in the deeper layer (0.2-0.3 m).This may be because the tilled layer is more subjected to fertilization and conducive to microbial activities. The spectroscopic analysis showed that the source of DOM of these regions is mainly from microbial metabolites. These results provide basic scientific data for the further research on the environmental chemical behavior of pollutants and pollution control in this region.
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Affiliation(s)
- Jianhua Zhu
- Geological Environment Monitoring Institute of Xinjiang Uygur Autonomous Region, Urumqi 830091, China
| | - Jia Duo
- Xinjiang Key Laboratory of Environmental Pollution and Bioremediation, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Zizhao Zhang
- School of Geology and Mining Engineering, Xinjiang University, Urumqi 830046, China
| | - Liang Pei
- Xinjiang Key Laboratory of Environmental Pollution and Bioremediation, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Wenfeng Li
- Xinjiang Key Laboratory of Environmental Pollution and Bioremediation, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Rehemanjiang Wufuer
- Xinjiang Key Laboratory of Environmental Pollution and Bioremediation, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
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15
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Xie R, Qi J, Shi C, Zhang P, Wu R, Li J, Waniek JJ. Changes of dissolved organic matter following salinity invasion in different seasons in a nitrogen rich tidal reach. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163251. [PMID: 37023805 DOI: 10.1016/j.scitotenv.2023.163251] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/26/2023] [Accepted: 03/30/2023] [Indexed: 04/15/2023]
Abstract
Dissolved organic matter (DOM) is a heterogeneous mixture of dissolved material found ubiquitously in aquatic systems and dissolved organic nitrogen is one of its most important components. We hypothesised nitrogen species and salinity intrusions affect the DOM changes. Here, using the nitrogen rich Minjiang River as an easily accessible natural laboratory 3 field surveys with 9 sampling sites (S1-S9) were conducted in November 2018, April and August 2019. The excitation emission matrices (EEMs) of DOM were explored with parallel factor (PARAFAC) and cosine-histogram similarity analysis. Four indices including fluorescence index (FI), biological index (BIX), humification index (HIX) and the fluorescent DOM (FDOM) were calculated and the impact of physicochemical properties was assessed. The results suggested that the highest salinities of 6.15, 2.98 and 10.10, during each campaign corresponded to DTN concentrations of 119.29-240.71, 149.12-262.42 and 88.27-155.29 μmol·L-1, respectively. PARAFAC analysis revealed the presence of tyrosine-like proteins (C1), tryptophan-like proteins or a combination of the peak N and tryptophan-like fluorophore (C2) and the humic-like material (C3). The EEMs in the upstream reach (i.e. S1-S3) were complex with larger spectra ranges, higher intensities and similar similarity. Subsequently, the fluorescence intensity of three components decreased significantly with low similarity of EEMs (i.e. S4-S7). At the downstream, the fluorescence levels dispersed significantly and no obvious peaks were seen except in August. In addition, FI and HIX increased, while BIX and FDOM decreased from upstream to downstream. The salinity positively correlated with FI and HIX, and negatively related to BIX and FDOM. Besides, the elevated DTN had a significant effect on the DOM fluorescence indices. Altogether, salinity intrusion and elevated nitrogen are relevant for the distribution of the DOM, which is helpful for the water management tracing the DOM source according to the on-line monitoring of salinity and nitrogen in estuaries.
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Affiliation(s)
- Rongrong Xie
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, China; Key Laboratory of Pollution Control and Resource Recycling of Fujian Province, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Environmental Monitoring Internet of Things Laboratory, Fujian Normal University, Fuzhou 350007, China.
| | - Jiabin Qi
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, China
| | - Chengchun Shi
- Fujian Provincial Academy of Environmental Sciences, Fuzhou 350013, China
| | - Peng Zhang
- School of Environmental and Municipal Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
| | - Rulin Wu
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, China
| | - Jiabing Li
- College of Environmental Science and Engineering, Fujian Normal University, Fuzhou 350007, China; Key Laboratory of Pollution Control and Resource Recycling of Fujian Province, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Environmental Monitoring Internet of Things Laboratory, Fujian Normal University, Fuzhou 350007, China
| | - Joanna J Waniek
- Leibniz Institute for Baltic Sea Research, Warnemünde, Rostock 18119, Germany.
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