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Eutrophication pollution seriously threatens the sustainable development of Lake Taihu, China. In order to identify the primary parameters of water quality and the potential pollution sources, the water quality dataset of Lake Taihu (2010-2014) was analyzed with the water quality index (WQI) and multivariate statistical analysis methods. Principle component analysis/factor analysis (PCA/FA) and correlation analysis screened out five significant water quality indicators, i.e. potassium permanganate index (COD Mn ), total nitrogen (TN), total phosphorus (TP), chloride ion (Cl - ) and dissolved oxygen (DO), to represent the whole datasets and evaluate the water quality with WQI. Since northwestern of Lake Taihu was the most heavily polluted area, the parameters of the water quality were analyzed to further explore the potential sources and their contributions. Five potential pollution sources of northwestern lake were identified, and the contribution rate of each pollution source was calculated by the absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models. In brief, the PMF model was more suitable for pollution source apportionment of the northwestern lake, and the contribution rate was ranked as agricultural non-point source pollution (26.6%) > domestic sewage discharge (23.5%) > industrial wastewater discharge and atmospheric deposition (20.6%) > phytoplankton growth (16.0%) > rainfall or wind disturbance (13.4%). This study might provide useful information for the optimization of water quality management and pollution control strategies of Lake Taihu., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

In this study, the generalized additive model (GAM) was used to analyze seasonal monitoring data from Lake Taihu, collected from 2010 to 2014, with the aim to explore the correlation between chlorophyll a (Chla) and other water quality parameters. The selected optimal multivariable GAM could effectively explain the concentration variation of Chla occurring during each season, and the interpretation degree followed the order: summer > autumn > spring > winter. The fitting results indicated that the concentration variation of Chla could reflect that of biochemical oxygen demand and chemical oxygen demand in all seasons. In addition, the total phosphorus showed strong ability to explain the concentration change of Chla in spring and summer, as the growth of algae would be affected when the concentration of phosphorus shifted high or low. Nitrogen showed strong ability to explain the variations in Chla concentration in autumn. The conclusions of the optimal multivariable GAM could provide decision basis for the eutrophication control. In other words, the prevention of eutrophication outbreaks could be carried out via the targeted control of key water pollutants. According to these results, the concentration of Chla was higher in northern and western lake during summer and autumn, the management should focus on nutrient input of adjacent rivers., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Our study illustrated the ecological conditions in the rivers of Lake Taihu Basin (LTB) using an index of biotic integrity based on phytoplankton (P-IBI), and its performance was compared with the previously developed water quality index (WQI). Samples were collected seasonally at 96 sites covering the major rivers from September 2014 to January 2016. Three critical ecological indices, i.e., phytoplankton density, chlorophyll a (chl a), and Menhinick, were selected from a pool of 22 candidate indices mainly according to the correlations among indices and environmental parameters. The results indicated that the ecological status of LTB based on P-IBI was significantly different at spatial (especially between Tiaoxi and the other 5 river systems) and seasonal scales. Furthermore, the proposed P-IBI effectively identified the major environmental parameters (total nitrogen, ammonium, total phosphorus, and permanganate index) associated with each level (bad, low, and moderate). Moreover, the P-IBI was closely and positively correlated with the WQI at the spatial scale regardless of season. However, the ecological conditions were significantly worse according to the P-IBI at both the spatial (P < 0.001) and seasonal scales (P values of 0.018 in winter and < 0.001 in other seasons, respectively), and the seasonal distribution pattern differed between the two methods. Our study suggests that the P-IBI provides an essential supplement for the assessment of ecological conditions of rivers and that the selected critical indices (phytoplankton density, chl a, and Menhinick) are suitable for river ecosystems. Additionally, compared with WQI, the water quality condition was generally worse when using P-IBI, and this phenomenon requires further attention during water quality assessments, as well as different seasonal distribution patterns., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Antibiotics have become a global public concern due to the widespread presence of antibiotic-resistant bacteria and genes. This study investigated the spatial and seasonal variation of conventional water quality parameters and 10 selected antibiotics in rivers inflowing into Taihu Lake. The results showed that total nitrogen, as a pollution driver factor, varied with the seasons, and higher concentrations of pollutants were generally found in the dry season compared with the wet season. For antibiotics, seven of them were detected in surface waters (n = 66) with detection frequencies (DFs) of 1.52–100% and eight antibiotics with DFs of 2.56–100% in sediments (n = 39). Sulfamethoxazole (SMZ, median: 1.47 ng/L), trimethoprim (TMP, median: 0.35 ng/L), and roxithromycin (ROX, median: 0.47 ng/L) with 100% DFs followed by erythromycin (ERY, median: 0.56 ng/L) with a DF of 90.91% accounted for a median percentage of 44.54%, 9.08%, 20.42%, and 13.16% of the ΣABs concentrations in surface waters. In contrast, enrofloxacin (ENR, median: 0.54 ng/g) and ROX (median: 0.29 ng/g) with 100% DFs accounted for a median percentage of 58.21% and 31.71% of the ΣABs concentrations in sediments. Antibiotics in surface waters were mainly related to T, DO, TN and NH 3 –N, but were mainly related to T, pH and TN for antibiotics in sediments. Furthermore, most of the detected antibiotics showed higher concentrations and more species of antibiotics in winter than in summer or autumn. Similarly, the ecological risk values of antibiotics showed higher in winter than in the other two seasons, whereas the overall risk levels were considered acceptable. [Display omitted] • High concentrations and ecological risk in the dry season than the wet season. • Total nitrogen was a pollution driver factor for conventional water quality parameters. • Strongly significant correlations were found among conventional water quality parameters and antibiotics. • The dominant antibiotic was SMX in surface water, ENR in sediments, whereas ROX for ecological risk. [ABSTRACT FROM AUTHOR]

• A macroinvertebrate-based multimetric index (MMI) was developed for shallow lakes. • The MMI is comprised of three taxonomic and two functional metrics. • The MMI could capture the influence of eutrophication on lake ecological status. • Functional metrics could complement the information provided by taxonomic metrics. Benthic macroinvertebrates have a long history of use in environmental monitoring. However, macroinvertebrate-based multimetric approach has not been well developed to assessment aquatic ecosystems in China, particularly in lake ecosystems. Eutrophication has been recognized as one of the main pressures affecting shallow lakes in China and elsewhere and it is thus desirable to quantify its effects on ecological integrity of lake ecosystems. Here, 41 subtropical shallow lakes in the Eastern Plain Lake Ecoregion of China were sampled and defined as three groups along eutrophication gradients. A macroinvertebrate-based multimetric index, consisting of three taxonomic metrics (No. of Gastropoda taxa, biological pollution index, and Margalef index) and two functional metrics (functional evenness and relative abundance of deposit feeder) was developed based on the datasets of the 41 lakes, and the results of multiple linear regression showed that the MMI was significantly related to the concentration of TP and macrophyte cover. This finding indicated that the MMI could characterize the influence of eutrophication on lake ecosystems. Our results also indicated that functional metrics could complement the information provided by taxonomic metrics, and we recommend to properly use functional metrics in lake biomonitoring. The macroinvertebrate-based MMI proposed here is the first attempt using biological quality element to assess the ecological status of shallow lakes in the view of eutrophication at the regional scale and could provide complementary information to traditional water quality assessment for the development of management strategies. [ABSTRACT FROM AUTHOR]