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Decreasing levels of water quality and elevated concentrations of heavy metals in freshwaters can pose global challenges for drinking water sources. Multivariate statistical techniques have been applied on data matrices of water quality and heavy metals for keen characterization of their spatio-temporal variations, exploration of latent factors, and identification of pollution sources. Non-metric multidimensional scaling (nMDS), canonical correlation analysis (CCA), and structural equation modeling (SEM) were employed to process data matrices of the water quality and heavy metals with 14 parameters measured at 13 sampling sites in Dongjianghu Lake in March, June, August, and December 2016. The sampling sites were grouped into three clusters using the nMDS, suggesting that the increasing order of the water quality levels was approximately midstream < downstream < upstream and lake. The CCA of 14 parameters proved that the Escherichia coli, COD Mn, TP, TN, TEMP, DO, and pH were the latent factors to distinguish the sampling sites, suggesting that the natural disturbances further influenced the lake and upstream, while the anthropogenic activities further influenced the midstream and downstream. The CCA of the heavy metals exhibited that the COD Mn , F - , and E. coli were the latent factors of the Cu, Zn, and As, while the DO and TEMP were the latent factors of the Cd. This indicated that the Cu, As, and Zn were mainly associated with the anthropogenic activities, while the Cd was predominantly relative to the natural conditions. The SEM of the water quality and heavy metals showed that the weights of COD Mn (28.64%), NH 3 -N (14.96%), BOD 5 (14.32%), TN (12.88%), and TP (10.18%) were higher than those of the pH (8.37%), DO (7.73%), TEMP (2.58%), and E. coli (0.34%). This indicated that the former exhibited strong influences on the heavy metals than the latter. Moreover, the COD Mn and BOD 5 were the key factors of the heavy metals, which should be attributed to the no-point sources, especially the exploitation mining and mill tailings. The water quality assessment by the nMDS, CCA, and SEM can determine the status, trend corresponding to its standards, and trace latent factors and identify possible pollution sources. The study could provide a guide for water quality evaluation and pollution control., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

UV-visible spectroscopy and synchronous fluorescence spectroscopy (SFS) combined with two-dimensional correlation spectroscopy (2D-COS) were applied for extracting fluorescence components, tracing organic functional groups, and revealing variations of dissolved organic matter (DOM) in Puhe River. Water samples were collected from the mainstream and two tributaries (Nanxiaohe River and Huangnihe River). DOM in three rivers was composed of protein-like fluorescent (PLF), microbial humus-like fluorescent (MHLF), fulvic-like fluorescent (FLF), and humic-like fluorescent components, which were relative to aromatic groups, phenolic groups, carboxylic groups, and microbial products. The PLF and MHLF were dominated in DOM fractions in the rivers, and the average content of the PLF was the highest in Nanxiaohe River. Humification degree of DOM was the highest in Puhe River, followed by Huangnihe River and Nanxiaohe River. However, molecular mass of DOM in Puhe River was the lowest, followed by Huangnihe River and Nanxiaohe River. Based on the 2D-COS of the SFS and UV-visible spectra, the variation order of DOM fractions in Puhe River was PLF → MHLF → FLF, and the PLF was consistent with the phenolic groups, aromatic groups, and carboxylic groups, but the adverse trend with the microbial products. The variation order in Nanxiaohe River was MHLF → PLF → FLF, and the MHLF was consistent with the aromatic groups, phenolic groups, carboxylic groups, and microbial products. The variation order in Huangnihe River was MHLF → PLF → FLF too, and the PLF was consistent with the carboxylic groups and aromatic groups. The results of the present study demonstrate that UV-visible spectroscopy and SFS combined with 2D-COS are useful methods to characterize structural composition of DOM from urban black and stinky rivers so as to investigate their pollution status.

UV-visible absorption spectroscopy combined with principal component analysis (PCA) and two-dimensional correlation (2D correlation) is used to trace components of dissolved organic matter (DOM) extracted from soils in a larger estuarine delta and to investigate spatial variations of DOM fractions. Soil samples of different depths were collected from native halophyte soils along a saline gradient, i.e., Suaeda salsa Comm. (SSC), Chenopodium album Comm. (CAC), Phragmites australis Comm. (PAC), and Artemisia selengensis Comm. (ASC). Molecular weights of DOM within the SSC soil profile were the lowest, followed by the CAC, PAC, and ASC soil profiles. Humification degree of DOM within the ASC soil profile was the highest, followed by the PAC, SSC, and CAC soil profiles. DOM within the soil profiles mainly contained phenolic, carboxylic, microbial products, and aromatic and alkyl groups through the PCA, which presented the significant differentiation among the four native halophyte soil profiles. The 2D UV correlation spectra of DOM within the SSC soil profile indicated that the variations of the phenolic groups were the largest, followed by the carboxylic groups, microbial products, and humified organic materials according to the band changing order of 285 → 365 → 425 → 520 nm. The 2D UV correlation spectra of DOM within the CAC soil profiles determined that the decreasing order of the variations was phenolic groups > carboxylic groups > microbial products according the band changing order of 285 → 365 → 425 nm. The 2D UV correlation spectra of DOM within the PAC soil profile proved that the variations of the phenolic groups were larger than those of the carboxylic groups according to the band changing order of 285 → 365 nm. The 2D UV correlation spectra of DOM within the ASC soil profile demonstrated that the variations of the phenolic groups were larger than those of the other DOM fractions according to the broad cross-peak at 285/365-700 nm.

UV-visible absorption spectroscopy coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) was applied to characterize spectroscopic components, detect latent factors, and investigate spatial variations of dissolved organic matter (DOM) in a large-scale lake. Twelve surface water samples were collected from Dongjianghu Lake in China. DOM contained lignin and quinine moieties, carboxylic acid, microbial products, and aromatic and alkyl groups, which in the northern part of the lake was largely different from the southern part. Fifteen spectroscopic indices were deduced from the absorption spectra to indicate molecular weight or humification degree of DOM. The northern part of the lake presented the smaller molecular weight or the lower humification degree of DOM than the southern part. E 2/4 , E 3/4 , E 2/3 , and S 2 were latent factors of characterizing the molecular weight of DOM, while E 2/5 , E 3/5 , E 2/6 , E 4/5 , E 3/6 , and A 2/1 were latent factors of evaluating the humification degree of DOM. The UV-visible absorption spectroscopy combined with PCA and HCA may not only characterize DOM fractions of lakes, but may be transferred to other types of waterscape.

Combination of fluorescence excitation-emission matrix spectroscopy with parallel factor analysis (PARAFAC) and principal component analysis (PCA) was engaged to track fluorescent components of dissolved organic matter (DOM) extracted from soils, to seek potential factors, and to reveal their correlations with physico-chemical properties of soils. Soil samples at different depths were collected in Hetao irrigated area of Inner Mongolia, China. Five fluorescent components (C1 to C5) were identified by PARAFAC modeling of DOM extracted from the soil samples. C1 was referred as fulvic-like fluorescent component, by which DOM was dominated in the whole soil samples. C2 was associated with salinity and agriculture, which was similar to marine humic-like fluorescent component. C3 was assigned as traditional humic-like fluorescent component. The three components were of the terrestrial origin. C4 was involved in tryptophan-like fluorescent component, which was autochthonous productions of biological degradation. C5 might be a polycyclic aromatic hydrocarbon contaminant, which could be relative to anthropogenic sources of pesticides. The C1, C2, and C3 were the potential factors of characterizing DOM fractions using PCA on fluorescent components and physico-chemical parameters. Moreover, DOM might restrained by exchangeable sodium percentage, and its formation and decomposition might be influenced by soil moisture.

Synchronous fluorescence spectroscopy (SFS) combined with two-dimensional correlation and principle component analysis (PCA) can provide an excellent challenge to capture fluorescent components of dissolved organic matter (DOM) and reveal its spatial variations in an urban river. Water samples were collected from Baitapuhe River along human impact gradient, i.e., the rural, town, and urban regions. DOM in Baitapuhe River was composed of protein-like, microbial humic-like, fulvic-like, and humic-like fluorescent components. The protein-like was the dominant component, which consisted of tyrosine-like and tryptophan-like components. In the rural region, the variation of the microbial humic-like was higher than that of the protein-like according to the band changing order of 335 → 281 nm, and both components changed in the same direction. In the town region, the variation of the microbial humic-like was the highest followed by the protein-like and fulvic-like on the basis of the changing band order of 335 → 281 → 369 nm, and these components varied in the same trend too. In the urban region, the variation of the protein-like was the highest, followed by the microbial humic-like, fulvic-like, and humic-like based on the changing band order of 282 → 335 → 369 → 470 nm, and the protein-like variation was opposite to the other components. The SFS combined with PCA and two-dimensional correlation can be used as a powerful tool in investigating fluorescent components of DOM and revealing spatial variations of these fluorescent components.

Excitation-emission matrix (EEM) fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) and multivariable analysis were employed to compare components of dissolved (DOM) and particulate (POM) organic matter and to reveal their correlations with water quality in Baitapuhe River and Xihe River in Shenyang City of northeast China. Eighteen water samples in Baitapuhe River and 16 water samples in Xihe River were collected along a human impact gradient. The DOM concentrations in Baitapuhe River were lower than those in Xihe River, so were the POM concentrations. The DOM in Baitapuhe River mainly derived from livestock wastewater and domestic sewage, which had strong biodegradability. However, the DOM in Xihe River mainly originated from industrial wastewater, which exhibited weak biodegradability. Four PARAFAC components (C1 to C4) were extracted from the DOM and POM. C1 was defined as fulvic-like component, and C2 was assigned as microbial humic component. C3 and C4 were ubiquitous protein-like component, which were referred as tryptophan-like and tyrosine-like components, respectively. The C3 was representative for the DOM in Baitapuhe River. The C3 and C4 were the main fractions of the DOM in Xihe River across the centralized wastewater-discharge region, whereas the C2 was the major component across the dispersed wastewater-discharge region. POM was dominated by the C4 in both rivers. Latent factors of water quality included the DOM, DO, Chl a, NO3-N, and NH4-N in Baitapuhe River, but the latent factors contained DOM, DO, BOD5, and COD in Xihe River. Baitapuhe River was under the aerobic condition, but Xihe River was under the anaerobic condition.

Introduction: Environmental heterogeneous methods were used for analysing data sets of trophic state with 11 parameters measured at 12 different sites at Chaohu Lake for the period 2004 to 2006. The aim of this research was to determine spatial/temporal variations in water quality, to assess trophic state and to identify pollution sources. Protective measures and schemes were proposed to improve water quality in the lake., Discussion: Hierarchical cluster analysis (CA) grouped the 12 sampling sites into two clusters (Eastern Chaohu Lake and Western Chaohu Lake). Temporal CA classified the 12 months into four periods (March-May; June-August; September-November; January, February and December) with a distinct regular seasonal cycle in Eastern Chaohu Lake and four periods (January-April and December; May, July and November; June, September and October; August) with an irregular seasonal cycle in Western Chaohu Lake. Trophic state index analysis showed that Eastern Chaohu Lake was in mesotrophic levels, while Western Chaohu Lake was in eutrophic and hypereutrophic levels. Based on pollutant source statistics data, the dominant pollution sources were identified as domestic sewage and non-point pollution in Eastern Chaohu Lake. Domestic sewage, industrial and non-point sources were contributed to eutrophication in Western Chaohu Lake.