太湖蓝藻水华暴发主要特征初析

太湖水体富营养化加剧引起了多方面的关注,针对近年实际监测结果,结合历年流域水环境质量的变化,初步归纳了当前太湖蓝藻水华暴发的地域特征、时间周期特点及主要水质指标的变化规律,总结了太湖蓝藻水华的暴发呈多峰形状态.2007年太湖沙渚水源地藻类生物量的两峰三阶段的特征进一步表明,太湖蓝藻水华的暴发进入了高频期.     

杭州市大气细颗粒物PM_(2.5)中多环芳烃含量特征研究

按季节对杭州市大气细颗粒物PM2.5中16种多环芳烃(PAHs)的含量在2006年进行了为期一年(样本数n=47)的测定分析.研究表明,杭州市大气PM2.5中PAHs总浓度为40.66ng/m3,以中环或高环为主,分别占总PAHs的32.23%和47.6%;云栖点位(位于风景名胜区内)PM2.5中PAHs浓度高于朝晖点位(位于商业居民混合区);季节变化呈现春季高,秋季低的特点;PM2.5中苯并[a]芘等效毒性(BEQ)为4.50;PM2.5中PAHs的来源不是单一的.     

Phytoplankton variation and its relationship with the environment in Xiangxi Bay in spring after damming of the Three-Gorges, China

Following the completion of the Three-Gorges Dam, there was a strong spring phytoplankton bloom in Xiangxi Bay of Three-Gorges Reservoir. However, our knowledge of relationship between spring phytoplankton bloom and environmental factors was still limited. In this study, phytoplankton species composition, biomass, chlorophyll a concentration and environmental factors at two sampling sites in Xiangxi Bay were investigated during 25 March to 18 May 2007. The Xiangxi Bay was eutrophic with the lowest values of total nitrogen and total phosphorus being 0.80 and 0.07?mg/L, respectively. A total of 66 algal taxa belonging to seven phyla and 45 genera were identified. Peridiniopsis niei Liu was the most abundant species which preferred standing water. Canonical correspondence analysis and correlation analysis revealed that nitrate was significantly associated with phytoplankton growth. The phytoplankton chlorophyll a concentration was correlated significantly negatively with nitrate concentration, and nitrate concentration was very low during bloom periods. Heavy rainfall was the main reason of phytoplankton chlorophyll a concentration and biomass decreasing and blooms disappearing. In addition, heavy rainfall also brought more nitrate into the Bay which provided sufficient nitrogen source for blooms occurring again.     

Relations of Habitat-Specific Algal Assemblages to Land Use and Water Chemistry in the Willamette Basin, Oregon

Benthic algal assemblages, water chemistry, and habitat were characterized at 25 stream sites in the Willamette Basin, Oregon, during low flow in 1994. Seventy-three algal samples yielded 420 taxa — mostly diatoms, blue-green algae, and green algae. Algal assemblages from depositional samples were strongly dominated by diatoms (76% mean relative abundance), whereas erosional samples were dominated by blue-green algae (68% mean relative abundance).Canonical correspondence analysis (CCA) of semiquantitative and qualitative (presence/absence) data sets identified four environmental variables (maximum specific conductance, % open canopy, pH, and drainage area) that were significant in describing patterns of algal taxa among sites. Based on CCA, four groups of sites were identified: streams in forested basins that supported oligotrophic taxa, such as Diatoma mesodon;small streams in agricultural and urban basins that contained a variety of eutrophic and nitrogen-heterotrophic algal taxa; larger rivers draining areas of mixed land use that supported planktonic, eutrophic, and nitrogen-heterotrophic algal taxa; and streams with severely degraded or absent riparian vegetation (> 75% open canopy) that were dominated by other planktonic, eutrophic, and nitrogen-heterotrophic algal taxa. Patterns in water chemistry were consistent with the algal autecological interpretations and clearly demonstrated relationships between land use, water quality, and algal distribution patterns.     

微囊藻毒素检测方法的研究进展

随着水体富营养化日益严重,有毒蓝藻水华引起的污染事件在世界范围内频繁发生,其产生的毒素对生物有潜在的危害。所以迫切需要建立一种工作原理简单易行、分析速度快、灵敏度较高的统一的检测方法,对水体中特别是饮用水源中的微囊藻毒素进行检测。文章简要介绍了近年来发展起来的几类微囊藻毒素检测技术,以及微囊藻毒素检测技术尚要解决的问题和未来的发展方向。     

Modelling the Effect of Weather Conditions on Cyanobacterial Bloom Outbreaks in Lake Dianchi: a Rough Decision-Adjusted Logistic Regression Model

Lake Dianchi, one of the main water sources for Kunming, China, experiences severe cyanobacterial blooms due to rapid urbanization and local industrial development. Scientific interest in the mechanisms that cause blooms has been increasing. An integrated model combining rough set theory with binary logistic regression was used to examine the correlation between weather conditions and cyanobacterial blooms in Lake Dianchi based on daily monitoring data. The binary logistic regression yielded quantitative correlations between cyanobacterial blooms and the assessed meteorological variables, including temperature, wind velocity, and wind direction. The rough decision process connected the weather conditions and cyanobacterial blooms, which were used to verify the binary regression model results. It was shown that by comparing the methods, the rough decision-adjusted binary logistic regression model significantly improved model accuracy. The integrated model of cyanobacterial blooms in Lake Dianchi may inform decision-makers at local water purification plants of the water quality in the lake and assist them in making more cost-effective decisions.     

Mobility of Different Phosphorus Pools in the Sediment of Lake Dianchi during Cyanobacterial Blooms

By the method of P fractionation, we examined sedimentary P fractions in Lake Dianchi before and during cyanobacterial blooms, namely in April 2004 and August 2004, respectively. In this study, the whole lake is divided into four areas to discuss P fractions in sediment and the relationship between them and water quality or the nutrient status. The results show that where the water body was much more eutrophic (higher levels of total phosphorus, total nitrogen, chlorophyll and trophic status index) in Lake Dianchi, there can be more potentially available phosphorus (BD–P and NaOH–P) and less no available phosphorus (HCl–P and residual P) in the corresponding sediments. Statistical analysis and statistical plots are used to compare the distribution of every P fraction during cyanobacterial blooms with that before cyanobacterial blooms, and the results indicate that the different P fractions had the different mobility. HCl–P and residual P were relatively stable, while NaOH–P, BD–P and NH4Cl–P were more mobile. BD–P can intensively be released from sediment to water and consequently promote cyanobacterial blooms, and at the same time the NaOH–P concentration increased in sediment, which can result from that BD–P released can be partly immobilized to NaOH–P. During cyanobacterial blooms BD–P can be as a source, but NaOH–P as a sink. Besides, total phosphorus in sediment had no significant differences between two samplings.     

Effect of El Nĩno on demographic,morphological, and chemical parameters in turtle-grass (Thalassia testudinum): an unexpected test of indicators

We examined the response of demographic, morphological, and chemical parameters of turtle grass (Thalassia testudinum), to much-higher-than-normal rainfall associated with an El Niño event in the winter of 1997–1998. Up to 20 inches of added rain fell between December 1997 and March 1998, triggering widespread and persistent phytoplankton blooms along the west coast of Florida. Water-column chlorophyll concentrations estimated from serial SeaWiFS imagery were much higher during the El Niño event than in the previous or following years, although the timing and magnitude of phytoplankton blooms varied among sites. Seagrass samples collected in 1997, 1998, and 1999 provided an excellent opportunity to test the responsiveness of Thalassia to decline and subsequent improvement of water quality and clarity in four estuaries. Using a scoring technique based on temporal responsiveness, spatial consistency, and statistical strength of indicators, we found that several morphological parameters (Thalassia shoot density, blade width, blade number, and shoot-specific leaf area) were responsive and consistent measures of light stress. Some morphological parameters, such as rhizome apex density, responded to declines and subsequent improvement in water clarity, but lacked the statistical discriminating power necessary to be useful indicators. However, rhizome sugar, starch, and the total carbohydrate concentrations also exhibited spatially and temporally consistent variation as well as statistical strength. Because changes in shoot density, as well as water clarity, affect rhizome carbohydrate levels, a composite metric based on Thalassia shoot density and rhizome carbohydrate levels together is probably more useful than either parameter alone as an indicator of seagrass health.     

Scatterscore: A Reconnaissance Method To Evaluate Changes In Water Quality

Water quality data collected in periodic monitoring programs are often difficult to evaluate, especially if the number of parameters is large, the sampling schedule varies, and values are of different orders of magnitude. The Scatterscore Water Quality Evaluation was developed to yield a quantitative score, based on all measured variables in periodic water quality reports, indicating positive, negative or random change. This new methodology calculates a reconnaissance score based on the differences between up-gradient (control) versus down-gradient (treatment) water quality data sets. All parameters measured over a period of time at two or more sampling points are compared. The relationship between the ranges of measured values and the ratio of the medians for each parameter produces a data point that falls into one of four sections on a scattergram. The number and average values of positive, negative and random change points is used to calculate a Scatterscore that indicates the magnitude and direction of overall change in water quality. The Scatterscore Water Quality Evaluation, a reconnaissance method to track general changes, has been applied to 20 sites at which coal utilization by-products (CUB) were used to control acid mine drainage (AMD).     

洪泽湖水质富营养化评价

对洪泽湖及其入湖河流水质现状进行了评价,得知洪泽湖及其入湖河流总体水质为劣Ⅴ类,影响两者水质的主要污染物为总磷和总氮。对洪泽湖浮游植物的时空分布及相关因子进行分析,得知洪泽湖目前为轻富营养水平。最后对洪泽湖第一次发生蓝藻聚集现象的原因进行了分析。     

Water quality assessment using integrated modeling and monitoring in Narva Bay, Gulf of Finland

A coupled three-dimensional hydrodynamic–ecological model was used for the assessment of water quality in Narva Bay during one biologically active season. Narva Bay is located in the south-eastern Gulf of Finland. Narva River with a catchment’s area covering part of Russia and Estonia discharges water and nutrients to Narva Bay. The ecological model includes phytoplankton carbon, nitrogen and phosphorus, chlorophyll a, zooplankton, detritus carbon, nitrogen and phosphorus, inorganic nitrogen, inorganic phosphorus and dissolved oxygen as state variables. Both the hydrodynamic and ecosystem models were validated using a limited number of measurements. The hydrodynamic model validation included comparison of time series of currents and temperature and salinity profiles. The ecological model results were compared with the monitoring data of phytoplankton biomass, total nitrogen and phosphorus and dissolved oxygen. The comparison of hydrodynamic parameters, phytoplankton biomass, surface layer total phosphorus and dissolved oxygen and near-bottom layer total nitrogen was reasonable. Time series of spatially mean values and standard deviations of selected parameters were calculated for the whole Narva Bay. Combining model results and monitoring data, the characteristic concentrations of phytoplankton biomass, total nitrogen and phosphorus and near-bottom dissolved oxygen were estimated. Phytoplankton biomass and total phosphorus showed seasonal variations, of 0.6–1.1 and 0.022–0.032 mg/l, respectively, during spring bloom, 0.1–0.3 and 0.015–0.025 mg/l in summer and 0.2–0.6 and 0.017–0.035 mg/l during autumn bloom. Total nitrogen and near-bottom oxygen concentrations were rather steady, being 0.25–0.35 and 2–6 mg/l, respectively. The total nitrogen and phosphorus concentrations show that according to the classification of Estonian coastal waters, Narva Bay water belongs to a good water quality class.     

Spatial and temporal variability in the relationship between cyanobacterial biomass and microcystins

The increasing incidence of toxic cyanobacterial blooms, together with the difficulties to reliably predict cyanobacterial toxin (e.g. microcystins) concentration, has created the need to assess the predictive ability and variability of the cyanobacterial biomass–microcystin relationship, which is currently used to assess the risk to human and ecosystems health. To achieve this aim, we assessed the relationship between cyanobacterial biomass and microcystin concentration on a spatiotemporal scale by quantifying the concentration of cyanobacterial biomass and microcystin in eight lakes over 9 months. On both a temporal and spatial scale, the variability of microcystin concentration exceeded that of cyanobacterial biomass by up to four times. The relationship between cyanobacterial biomass and microcystin was weak and site specific. The variability of cyanobacterial biomass only explained 25 % of the variability in total microcystin concentration and 7 % of the variability of cellular microcystin concentration. Although a significant correlation does not always imply real cause, the results of multiple linear regression analysis suggest that the variability of cyanobacterial biomass and cellular microcystin concentration is influenced by salinity and total phosphorus, respectively. The weak cyanobacterial biomass–microcystin relationship, coupled with the fact that microcystin was present in concentrations exceeding the WHO drinking water guidelines (1 μg?L^?1) in most of the collected samples, emphasizes the high risk of error connected to the traditional indirect microcystin risk assessment method.     

Multiple Effects of Environmental Factors on Algal Growth and Nutrient Thresholds for Harmful Algal Blooms: Application of Response Surface Methodology

Systematic understanding of the co-effects of environmental factors on phytoplankton proliferation can enable more effective control of harmful algal blooms in eutrophic lakes and reservoirs. A batch of statistically designed experiments using response surface methodology was recently conducted on mixed algae samples collected from Changtan Reservoir. The central composite designed response surface model was established to evaluate multiple effects of various physical and chemical factors (total nitrogen, total phosphorus, temperature, and light intensity) on algal density and chlorophyll a content. Analysis of variance indicated an excellent correlation between modeling results and experimental responses. Among the selected environmental variables, promotion of the interactive effects of nitrogen and phosphorus together with the optimum total nitrogen/phosphorus mass ratio (between 7.9 and 10.1) was determined to be the most significant stimulating parameter associated with algal blooming development dominated by non-nitrogen-fixing species. The favorable effects of strong illumination were shown to be greater than those of high temperature. The border values of total nitrogen and phosphorus concentrations leading to a critical value of algal density under different water temperatures and light intensities could be predicted as nutrient loading thresholds for harmful algal blooms by our second-order polynomial regression model.     

Seasonal and spatial variation of reservoir water quality in the southwest of Ethiopia

This research investigated the spatiotemporal variation of water quality in the Gilgel Gibe reservoir, Ethiopia, using physicochemical water quality parameters. Nonparametric tests and multivariate statistical techniques were used to evaluate data sets measured during dry and rainy seasons. Electrical conductivity (EC), pH, biochemical oxygen demand (BOD₅), total phosphorus (TP), total nitrogen (TN), nitrate (NO₃^?), total dissolved solids (TDSs), and total suspended solids (TSSs) were all significantly different among seasons (Mann-Whitney U test, p?<?0.01). In addition, principal component analysis distinguished dry season samples from wet season samples. The dry season was positively associated with EC, pH, TP, TN, NO₃^?, TDS, and TSS and negatively associated with BOD₅. The wet season was in contrast associated with high values of turbidity, soluble reactive phosphorus (SRP), water temperature, and dissolved oxygen (DO). Within the reservoir, spatial variation was observed for some of the water quality parameters, with significant difference at p?=?<?0.05. Overall, high nutrient concentrations suggest eutrophic conditions, likely due to high nutrient loading from the watershed. Levels of TSS, attributed to inputs from tributaries, have been excessive enough to inhibit light penetration and thus have a considerable impact on the aquatic food web. Our findings indicate that the reservoir is at high risk of eutrophication and siltation, and hence, urgent action should target the planning and implementation of integrated watershed management for this and similar reservoirs in the region.     

南太湖入湖口蓝藻水华时空分布规律及相关响应因子分析

利用2008年和2009年南太湖蓝藻监测数据,分析研究主要入湖口的蓝藻水华时空分布规律,寻找与蓝藻生长密切相关的响应因子并将其作为蓝藻预警指示指标,为环保部门制定蓝藻应急监测预案、提高蓝藻预警预测的准确性提供科学参考。     

太湖蓝藻水华暴发程度年度预测

近年来,尽管太湖主要水质指标有所改善,但蓝藻水华暴发的频次和面积并未明显减少.为了探讨太湖蓝藻水华暴发的环境驱动因子,统计了2012—2020年历年4—10月预警期间的太湖蓝藻水华发生规模与频次,结合同步浮标自动监测数据和实验室分析数据,构建了蓝藻水华预测模型.以太湖蓝藻水华综合指数(Ic)表征蓝藻水华强度,并通过Ic...     

The dynamics of toxic and nontoxic Microcystis during bloom in the large shallow lake,Lake Taihu,China

Lake Taihu is a large shallow freshwater lake (surface area 2,338 km², mean depth 1.9 m) in China, which has experienced toxic cyanobacterial bloom dominated by Microcystis annually during the last few decades. In the present study, the dynamics of toxic and nontoxic Microcystis in three sampling stations (Meiliang Bay (site N2), Gonghu Bay (site N4), and the lake center area (site S4)) were quantified using quantitative real-time PCR (qPCR) during bloom periods from April to September, 2010. Our data showed that the abundance of toxic Microcystis and the toxic proportion gradually increased from April to August in water samples and reached the peak in August. During the study period, toxic Microcystis genotypes comprised between 26.2 and 64.3, between 4.4 and 22.1, and between 10.4 and 20.6 % of the total Microcystis populations in the three sampling sites, respectively. Correlation analysis suggested that there was a strong positive relationship between total Microcystis, toxic Microcystis and the toxic proportion. Chlorophyll a, total phosphorus, and water temperature were positively correlated with the abundances of total Microcystis and toxic Microcystis. Furthermore, the toxic proportion was positively correlated with total phosphorus (P?<?0.05) and water temperature (P?<?0.01), showing that global warming together with eutrophication could promote more frequent toxic blooms.     

Eutrophication conditions and ecological status in typical bays of Lake Taihu in China

Sampling was conducted at three site groups, group E (in East Taihu Bay), G (in Gonghu Bay) and M (in Meiliang Bay) in Lake Taihu. TN and TP concentrations among site groups was in the increasing order of E < G < M. TP level at G sites is at the critical threshold for loss of submersed macrophytes. Mean values of DO and Transparence showed different trend, i.e., E > G > M. The mean phytoplankton fresh-weight biomass at M sites was 5.81 mg/l, higher than that at E sites (4.96 mg/l) and G sites (5.18 mg/l). Mean zooplankton fresh-weight biomass was in the decreasing order of M (6.4 mg/l) > G (4.9 mg/l) > E (2.7 mg/l). However, Rotifera density was in the sequence of E > G > M. Both zooplankton biomass and phytoplankton biomass increased with the rise of TN and TP concentrations. Relationships between zooplankton biomass and phytoplankton biomass showed that zooplankton played a limited role in the control of algae in eutrophic lakes. Nutrient availability is much more important than zooplankton grazing pressure in controlling phytoplankton growth in lakes. For most sites in Lake Taihu, reduction of nutrient loading, as well as macrophyte conservation, zappears to be especially important in maintaining high water quality and regulating lake biological structure, but for M sites, it’s urgent to control nutrient inputs rather than to restore macrophyte community.     

Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada

Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO₄, and NO₃ concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models.     

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.