Multiple anthropogenic stressors influence the taxonomic and functional homogenization of macroinvertebrate communities on the mainstream of an urban-agricultural river in China.

Biodiversity loss is caused by intensive human activities and threatens human well-being. However, less is known about how the combined effects of multiple stressors on the diversity of internal (alpha diversity) and multidimensional (beta diversity) communities. Here, we conducted a long-term experiment to quantify the contribution of environmental stressors (including water quality, land use, climate factors, and hydrological regimes) to macroinvertebrate communities alpha and beta diversity in the mainstream of the Songhua River, the third largest river in China, from 2012 to 2019. Our results demonstrated that the alpha and beta diversity indices showed a decline during the study period, with the dissimilarity in community composition between sites decreasing significantly, especially in the impacted river sections (upper and midstream). Despite overall improvement in water quality after management intervention, multiple human-caused stressors still have led to biotic homogenization of macroinvertebrate communities in terms of both taxonomic and functional diversities in the past decade. Our study revealed the increased human land use explained an important portion of the variation of diversities, further indirectly promoting biotic homogenization by changing the physical and chemical factors of water quality, ultimately altering assemblage ecological processes. Furthermore, the facets of diversity have distinct response mechanisms to stressors, providing complementary information from the perspective of taxonomy and function to better reflect the ecological changes of communities. Environmental filtering determined taxonomic beta diversity, and functional beta diversity was driven by the joint efforts of stressors and spatial processes. Finally, we proposed that traditional water quality monitoring alone cannot fully reveal the status of river ecological environment protection, and more importantly, we should explore the continuous changes in biodiversity over the long term. Meanwhile, our results also highlight timely control of nutrient input and unreasonable expansion of land use can better curb the ecological degradation of rivers and promote the healthy and sustainable development of floodplain ecosystems.

Heavy haze pollution during the COVID-19 lockdown in the Beijing-Tianjin-Hebei region, China.

To investigate the characteristics of particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) and its chemical compositions in the Beijing-Tianjin-Hebei (BTH) region of China during the novel coronavirus disease (COVID-19) lockdown, the ground-based data of PM2.5, trace gases, water-soluble inorganic ions, and organic and elemental carbon were analyzed in three typical cities (Beijing, Tianjin, and Baoding) in the BTH region of China from 5-15 February 2020. The PM2.5 source apportionment was established by combining the weather research and forecasting model and comprehensive air quality model with extensions (WRF-CAMx). The results showed that the maximum daily PM2.5 concentration reached the heavy pollution level (>150 µg/m3) in the above three cities. The sum concentration of SO42-, NO3- and NH4+ played a dominant position in PM2.5 chemical compositions of Beijing, Tianjin, and Baoding; secondary transformation of gaseous pollutants contributed significantly to PM2.5 generation, and the secondary transformation was enhanced as the increased PM2.5 concentrations. The results of WRF-CAMx showed obviously inter-transport of PM2.5 in the BTH region; the contribution of transportation source decreased significantly than previous reports in Beijing, Tianjin, and Baoding during the COVID-19 lockdown; but the contribution of industrial and residential emission sources increased significantly with the increase of PM2.5 concentration, and industry emission sources contributed the most to PM2.5 concentrations. Therefore, control policies should be devoted to reducing industrial emissions and regional joint control strategies to mitigate haze pollution.

Monitoring history and change trends of ambient air quality in China during the past four decades.

This study summarized the history of ambient air quality monitoring and air pollution prevention and control, and it analyzed the spatiotemporal patterns of ambient air pollutants during 1981-2017 in China. The results showed that monitoring of ambient air quality has changed dramatically in terms of determinants, sampling methods, monitoring extent, and evaluation basis during the previous four decades. Annual average concentrations of total suspended particulates, PM10 and SO2 have shown obvious decreasing trends during the studied period. These improvements have been closely related to the considerable efforts and various approaches undertaken to prevent and control air pollution. However, although policy implementation has been decisive and, at least in part, it has been enforced effectively, significant challenges remain. Air pollution control cannot be accomplished without a long-term strategy designed to achieve clean air in all parts of China.

Hydrodechlorination of carbon tetrachloride with nanoscale nickeled zero-valent iron @ reduced graphene oxide: kinetics, pathway, and mechanisms.

In recent years, carbon tetrachloride (CT) has been frequently detected in surface water and groundwater around the world; it is necessary to find an effective way to treat wastewater contaminated with it. In this study, Ni/Fe bimetallic nanoparticles were immobilized on reduced graphene oxide (NF@rGO), and used to dechlorinate CT in aqueous solution. Scanning electron microscopy (SEM) demonstrated that the two-dimensional structure of rGO could disperse nanoparticles commendably. The results of batch experiments showed that the 4N4F@rGO (Fe/GO = 4 wt./wt., and Ni/Fe = 4 wt.%) could reach a higher reduction capacity (143.2 mgCT/gcatalyst) compared with Ni/Fe bimetallic nanoparticles (91.7 mgCT/gcatalyst) and Fe0 nanoparticles (49.8 mgCT/gcatalyst) respectively. That benefited from the nickel metal as a co-catalyst, which could reduce the reaction activation energy of 6.59 kJ/mol, and rGO as an electrical conductivity supporting material could further reduce the reaction activation energy of 4.73 kJ/mol as presented in the conceptual model. More complete dechlorination products were generated with the use of 4N4F@rGO. Based on the above results, the reductive pathway of CT and the catalytic reaction mechanism have been discussed.

Quantitative assessment on soil concentration of heavy metal-contaminated soil with various sample pretreatment techniques and detection methods.

Detection and quantification of heavy metals in soil samples are significant in terms of environmental monitoring and risk assessment for metals. In order to improve the accuracy and precision to detect heavy metal, in this study, four standard samples (NASS-4, NASS-5, NASS-9, and NASS-16) were analyzed by evolving heating (electric heating plate, water bath, and microwave) and acidic systems (includes HCl, HNO3, HF, and HClO4). The result shows that different pretreatment methods have different effects on the extraction of heavy metal elements and five heavy metal elements (Cu, Zn, Pb, Ni, and Cr) were selected for optimization through pretreatment methods. Although the contents of heavy metals were same but we found diversity in the results. Under optimal conditions, the selected standard samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma atomic emission spectroscopy (ICP-AES), and atomic absorption spectroscopy (AAS), and the results were compared. The results show that different elements have their own most suitable detection methods, such as for Pb, the most suitable method is ICP-MS; and for Zn, the most suitable method is AAS. Pretreatment methods and detection techniques are combined to find and improve accuracy of results for certain elements. This study provides a reliable detection method for the accurate detection of heavy metals in the environment.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin, northeastern China, from 2011 to 2015.

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD5) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.

Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China.

Owing to the vast territory of China and strong regional characteristic of ozone pollution, it's desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It's important to assess its current pollution status as well as spatial and temporal variation patterns across China. Recent advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function (REOF) analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3years' observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations (O3-8hr) from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6±14.6 and 133.9±25.8µg/m3, respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population.

Health Risk Assessment Research on Heavy Metals Ingestion Through Groundwater Drinking Pathway for the Residents in Baotou, China.

Drinking groundwater is a significant pathway for human exposure to heavy metals. To evaluate the health effect of some heavy metals ingestion through the groundwater drinking pathway, the authors collected 35 groundwater samples from the drinking water wells of local residents and the exploitation wells of waterworks in Baotou, China. The monitoring results indicate that the groundwater had been polluted by heavy metals in some regions of the study area. A health risk assessment model derived from the U.S. Environmental Protection Agency was used to determine the noncarcinogenic and carcinogenic effects to residents who drink groundwater. All the respondents in the study area were at potential risk of carcinogenic health effects from arsenic when using the lowest safe standard for carcinogenic risk (1E-06). The hazard quotient values for noncarcinogenic health risk of arsenic exceeded 1 in 14.3% of the sampling wells in the study area. The research results could provide baseline data for groundwater utilization and supervision in the Baotou plain area.

Environmental distribution and associated human health risk due to trace elements and organic compounds in soil in Jiangxi province, China.

The government of China launched its first national soil quality and pollution survey (NSQPS) during April 2006 to December 2013. Data gathered in several earlier soil surveys were rarely used to understand the status of pollution. In this study, the dataset collected at the provincial level was analyzed for the first time. Concentrations, distribution, diversity, and human health risks of trace elements (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Se, V and Zn) and organic pollutants (benzene hexachloride (BHCs), dichlorodiphenyltrichloroethanes (DDTs), phthalic acid esters (PAEs), polycyclic aromatic hydrocarbon (PAHs), polychlorinated biphenyls (PCBs), and petroleum hydrocarbons (PHCs)) in surface soil samples collected across Jiangxi province,China were presented. The results showed that, the proportion of contaminants with concentrations higher than their corresponding regulatory reference value ranged from 0.12% to 17%. It is worth note that, the local residents are exposed to moderate non-carcinogenic and carcinogenic risks at some sites. The comprehensive analysis of soil pollutants provide baseline information for establishing a long-term soil environmental monitoring program in Jiangxi province, China.

Intelligent simultaneous quantitative online analysis of environmental trace heavy metals with total-reflection X-ray fluorescence.

Total-reflection X-ray fluorescence (TXRF) has achieved remarkable success with the advantages of simultaneous multi-element analysis capability, decreased background noise, no matrix effects, wide dynamic range, ease of operation, and potential of trace analysis. Simultaneous quantitative online analysis of trace heavy metals is urgently required by dynamic environmental monitoring and management, and TXRF has potential in this application domain. However, it calls for an online analysis scheme based on TXRF as well as a robust and rapid quantification method, which have not been well explored yet. Besides, spectral overlapping and background effects may lead to loss of accuracy or even faulty results during practical quantitative TXRF analysis. This paper proposes an intelligent, multi-element quantification method according to the established online TXRF analysis platform. In the intelligent quantification method, collected characteristic curves of all existing elements and a pre-estimated background curve in the whole spectrum scope are used to approximate the measured spectrum. A novel hybrid algorithm, PSO-RBFN-SA, is designed to solve the curve-fitting problem, with offline global optimization and fast online computing. Experimental results verify that simultaneous quantification of trace heavy metals, including Cr, Mn, Fe, Co, Ni, Cu and Zn, is realized on the online TXRF analysis platform, and both high measurement precision and computational efficiency are obtained.

Heavy metal pollution and ecological risk assessment of the paddy soils near a zinc-lead mining area in Hunan.

Soil pollution by Cd, Hg, As, Pb, Cr, Cu, and Zn was characterized in the area of the mining and smelting of metal ores at Guiyang, northeast of Hunan Province. A total of 150 topsoil (0-20 cm) samples were collected in May 2012 with a nominal density of one sample per 4 km(2). High concentrations of heavy metals especially, Cd, Zn, and Pb were found in many of the samples taken from surrounding paddy soil, indicating a certain extent of spreading of heavy metal pollution. Sequential extraction technique and risk assessment code (RAC) were used to study the mobility of chemical forms of heavy metals in the soils and their ecological risk. The results reveal that Cd represents a high ecological risk due to its highest percentage of the exchangeable and carbonate fractions. The metals of Zn and Cu pose a medium risk, and the rest of the metals represent a low environmental risk. The range of the potential ecological risk of soil calculated by risk index (RI) was 123.5~2791.2 and revealed a considerable-high ecological risk in study area especially in the neighboring and surrounding the mining activities area. Additionally, cluster analyses suggested that metals such as Pb, As, Hg, Zn, and Cd could be from the same sources probably related to the acidic drainage and wind transport of dust. Cluster analysis also clearly distinguishes the samples with similar characteristics according to their spatial distribution. The results could be used during the ecological risk screening stage, in conjunction with total concentrations and metal fractionation values to better estimate ecological risk.

Acclimation of aerobic-activated sludge degrading benzene derivatives and co-metabolic degradation activities of trichloroethylene by benzene derivative-grown aerobic sludge.

The acclimation of aerobic-activated sludge for degradation of benzene derivatives was investigated in batch experiments. Phenol, benzoic acid, toluene, aniline and chlorobenzene were concurrently added to five different bioreactors which contained the aerobic-activated sludge. After the acclimation process ended, the acclimated phenol-, benzoic acid-, toluene-, aniline- and chlorobenzene-grown aerobic-activated sludge were used to explore the co-metabolic degradation activities of trichloroethylene (TCE). Monod equation was employed to simulate the kinetics of co-metabolic degradation of TCE by benzene derivative-grown sludge. At the end of experiments, the mixed microbial communities grown under different conditions were identified. The results showed that the acclimation periods of microorganisms for different benzene derivatives varied. The maximum degradation rates of TCE for phenol-, benzoic acid-, toluene-, aniline- and chlorobenzene-grown aerobic sludge were 0.020, 0.017, 0.016, 0.0089 and 0.0047 mg g SS(-1) h(-1), respectively. The kinetic of TCE degradation in the absence of benzene derivative followed Monod equation well. Also, eight phyla were observed in the acclimated benzene derivative-grown aerobic sludge. Each of benzene derivative-grown aerobic sludge had different microbial community composition. This study can hopefully add new knowledge to the area of TCE co-metabolic by mixed microbial communities, and further the understanding on the function and applicability of aerobic-activated sludge.

Concentrations and seasonal variation of ambient PM(2.5) and associated metals at a typical residential area in Beijing, China.

In this study, continuous monitoring of PM2.5 was carried out for 1 year period at one of the largest residential areas in Beijing. Annual mean of PM2.5 during sampling period was 100.4 µg/m(3). The seasonal variation trend of PM2.5 was winter > spring > autumn and summer. The total mass concentrations of metals in PM2.5 ranged from 0.4 to 13.2 µg/m(3). There were significant (p < 0.05) seasonal variations for concentrations of Ca, Al, Mn, As, Rb, Cr, Ni, Cd and Co, seasonal variations in PM-associated metals were not necessarily the same as the seasonal variation in PM2.5, related to differing seasonal trends in source types. The impact of meteorological factors (e.g., wind speed) on metals levels of PM2.5 was found to be significant by regression models. The EFs value of Ag, Ca, Cd, Pb, Zn, As, Cu, and Cr were higher than ten, suggesting that those elements were primarily contributed by anthropogenic sources. Seasonal characteristic of EFs were found for As, Cr, Ca and Ag, which indicating the seasonal pollution sources types for those metals. Overall, these findings indicated that the pollution control of ambient PM2.5 should not be negligible in residential area in Beijing and the local government should pertinent and accurate prevent and control of air pollution as well as protect human health.

Ecological risk of nonylphenol in China surface waters based on reproductive fitness.

It has been recognized that ecological risk assessment based on traditional endpoints of toxicity are unable to provide adequate protection because some chemicals may affect reproductive fitness of aquatic organisms at much lower concentrations. In this paper, predicted no effect concentrations (PNECs) for 4-nonylphenol (NP) were derived based either on endpoints of survival, development, and growth or on some nonlethal biomarkers of reproduction, biochemical and molecular biology data. The PNECs derived from reproductive lesion ranged from 0.12 to 0.60 µg NP L(-1), which was significantly lower than those derived from other endpoints. An assessment of ecological risks posed by NP to aquatic organisms in surface waters of China was conducted based on concentration levels of NP in 16 surface waters of 4 major river basins and PNECs derived from reproductive fitness by a tiered ecological risk assessment (ERA). The results showed that 14.2% and 76.5% of surface waters in China may have ecological risks resulting from reproductive fitness if the thresholds of protection for aquatic organisms were set up as 5% (HC5) and 1% (HC1), respectively. The risks were significantly greatest in the Yangtze River Basin than in other major river basins. In comparison with the risks assessed based on traditional endpoints, such as lethality, for those chemicals causing adverse effects on reproduction due to modulation of endocrine function, to be protective of ecosystem structure and function, lesser PNECs, based on sublethal effects of reproduction, were appropriate.

Kinetics of the aerobic co-metabolism of 1,1-dichloroethylene by Achromobacter sp.: a novel benzene-grown culture.

Batch experiments were performed for the aerobic co-metabolism of 1,1-dichloroethylene (1,1-DCE) by Achromobacter sp., identified by gene sequencing of 16S rRNA and grown on benzene. Kinetic models were employed to simulate the co-metabolic degradation of 1,1-DCE, and relevant parameters were obtained by non-linear least squares regression. Benzene at 90 mg L(-1) non-competitively inhibited degradation of 1,1-DCE (from 125 to 1,200 µg L(-1)). The maximum specific utilization (kc) rate and the half-saturation constant (Kc) for 1,1-DCE were 54 ± 0.85 µg h(-1) and 220 ± 6.8 µg L(-1), respectively; the kb and Kb for benzene were 13 ± 0.18 mg h(-1) and 28 ± 0.42 mg L(-1), respectively. This study provides a theoretical basis to predict the natural attenuation when benzene and 1,1-DCE occur as co-contaminants.

[Effect freezing and thawing cycles on fluorescence characterization of black soil dissolved organic matter].

Fluorescence characterization of soil dissolved organic matter (DOM), which is one of the most important indexes concerning study on soil organic matter, can be effected by freezing and thawing cycles. In this paper, the fluorescence characterization of black soil DOM under the effect of freezing and thawing cycles was studied, using three-dimensional excitation-emission-matrix fluorescence spectroscopic (EEM). Based on the transformation of fluorescence characterization, the influences of humification degree and active humus in black soil were analysed. The result showed, compared with untreated by freezing and thawing cycles, (1) The phenomena red-shift of UV fulvic-like was found in soil DOM. It meant that the aromatization and humification degree increased. (2) Protein-like fluorescence peak was observed in some soil samples, which meant microbial activity was enhanced. (3) Active humus and humification degree are the indexs of soil fertility. The content of TOC in the active humus rose, just the same as the value of humification degree. It meant that soil fertility was improved. (4) Compared with the ratio of UV: visible humic-like fluorescence (r(a,c)), there were positive correlations with the active humus and humification degree. It meant that r(a, c) of soil DOM was one of the indexs on active humus, humification degree and soil fertility effected by freezing and thawing cycles.

[Study of three-dimensional fluorescence spectra for measuring chlorobenzene in water].

Quantitative analysis of chlorobenzene (CB) in water by three-dimensional fluorescence spectrometry was discussed in the present paper. The study showed that there is only one fluorescence peak for CB which lies in the range of excitation wavelength (lambdaex) 210-240 nm and emission wavelength (lambdaem) 330-370 nm. When measuring CB solution of concentration 0.002-0.05 mg x L(-1), the fluorescence intensity was the strongest as lamdaex/lamdaem was 225/340 nm, which presented linear correlation with concentration, and the related coefficient was 0.99967. The study proved that three-dimensional fluorescence spectrometry can be adopted for quantitative analysis of CB in water. With this method, the detection limit was 3.68 X 10(-6) mg x L(-1) and the standard deviation was 0.04% at 90% confidence level.

Developing an integrated framework for source apportionment and source-specific health risk assessment of PAHs in soils: Application to a typical cold region in China.

Here, a new integrated methodology framework has been proposed for source apportionment and source-oriented risk evaluation, and applied to identify the characteristics, sources and health risks of PAHs in the soils of a typical cold region in Northeastern China. To this end, a large-scale data set containing 1780 soil samples and 16 priority PAHs has been collected from the study area. Two advanced receptor models, positive matrix factorization (PMF) and multivariate curve resolution-weighted alternating least-squares (MCR-WALS), have been comparatively employed to apportion the pollution sources of soil PAHs, with the help of a set of modified literature PAH source fingerprints. Further, the apportionment results have been incorporated into a probabilistic incremental lifetime cancer risk model for assessing the source-specific health risk of soil PAHs. Notably, the PMF and MCR-WALS models have apportioned essentially same results. The coal combustion and gasoline engine are identified as the main contributors of soil PAHs, with contributions of 57.9-58.1% and 25.2-22.2%, respectively. The health risks posed by PAHs in the soils are negligible for both adult and children; relatively, source-oriented risk assessment shows coal combustions make the largest contribution to the total risk of PAHs (56.1%), followed by gasoline engine (22.5%) and coke oven (21.4%).

[Periphytic Algae Community Structure and Its Relation to Environment Factors in the Main Stream of the Songhua River from 2014 to 2019].

Periphytic algae are often used as an indicator to evaluate water quality. Here, the community structure of periphytic algae and its relationship with environment factors were analyzed in the main stream of the Songhua River during the summers of 2014 to 2019. The status and trends in ecological water quality were also evaluated based on bioassessments. Phytoplankton species belonging to 4 phyla and 58 genera were recorded, including 28 Bacillariophyta genera, 17 Chlorophyta genera, 10 Cyanophyta genera, and 3 Euglenophyta genera; Bacillariophyta, Chlorophyta, and Cyanophyta accounted for 48.28%, 29.31%, and 17.24% of the community, respectively. Cell densities varied between 1.29×104 and 8.42×104 ind·cm-3, with an average of 4.35×104 ind·cm-3. The dominant genera were Cyclotella, Melosira, Asterionella, Cymbella, Synedra, Pinnularia, Navicula, and Scenedesmus. The physicochemical water quality showed notable changes during the past six-year monitoring period. Specifically, the dissolved oxygen content increased year on year; ammonia nitrogen, total phosphorus, and total nitrogen first increased and then decreased; and, overall, water quality significantly improved in 2019. Relationship between periphytic algae and environmental factors was further examined using redundancy analysis (RDA), which showed that time was the main factor driving the succession of algal community structure. Dissolved oxygen (DO), ammonia nitrogen (NH4+-N), total nitrogen (TN), total phosphorus (TP), five-day biochemical oxygen demand (BOD), and chemical oxygen demand (COD) were also important environmental variables affecting algal community structure.