固城湖及其出入湖河道水质时空分布差异与历年变化趋势分析

于2012年7月至2013年7月采集固城湖及其出入湖河道水样,测定水体理化特征指标,探讨固城湖水质时空分布差异,并根据2001—2012年水质监测数据,利用PWQTrend 2010软件分析近年来固城湖及官溪河的水质变化趋势。结果表明:固城湖大湖区、港口河和漆桥河水质较好,丰水期处于轻度富营养化状态;小湖区、养殖区排污口、官溪河和胥河受纳污染负荷较大,丰水期处于中度富营养状态,而枯水期大、小湖区及出入湖河道都处于中营养状态。目前水质主要受氮磷污染的影响,主要污染源为水产养殖;2001—2012年官溪河和小湖区总体上属于Ⅲ~Ⅳ类水质,大湖区则属于Ⅲ类水质,受高淳社会经济发展和环境保护措施的影响,官溪河总氮、总磷浓度呈显著下降趋势,小湖区总氮浓度,大湖区总氮、总磷浓度都呈显著上升趋势,因此合理规划养殖业发展规模和模式,减少各类污染源排放量,是保证固城湖可持续发展的必要措施。     

太湖主要入湖河口表层沉积物重金属分布特征及风险评价

为揭示太湖主要入湖河口表层沉积物重金属分布特征及其生态风险,采集太湖西岸和北岸12条主要入湖河口表层沉积物样品,对沉积物中5种重金属元素(Cu、Zn、Ni、Pb、Cd)的含量及空间分布特征进行了分析,并利用地累积指数法和潜在生态风险指数法分别研究了表层沉积物重金属的累积程度及生态风险。结果表明,调查的12条入湖河流河口表层沉积物均受到不同程度的重金属污染,Cu、Zn、Ni、Pb、Cd的平均质量分数分别为63.04、173.11、56.71、37.05、2.23 mg?kg~(-1)。各重金属在空间分布上具有差异性,总体表现为大港河(DGH)、乌溪港(WXG)庙渎港(MDG)、大浦港(DPG)、陈东港(CDG)、官渎港(GDG)、洪巷港(HXG)、社渎港(SDG)河口表层沉积物以重金属Cd污染为主,而沙塘港(STG)、太滆运河(TG)、直湖港(ZHG)、梁溪河(LXH)河口表层沉积物表现为Cu、Zn、Ni、Pb的复合污染。地累积指数法评价表明,各入湖河流河口表层沉积物重金属的污染程度表现为CdCuZnNiPb。潜在风险指数(riE)表明各重金属的潜在生态风险表现为CdCuNiPbZn,主要污染物为Cd。其中庙渎港(MDG)和社渎港(SDG)处于严重风险状态,大港河(DGH)、乌溪港(WXG)、大浦港(DPG)、官渎港(GDG)、洪巷港(HXG)处于重度风险状态,陈东港(CDG)、太滆运河(TG)处于中度风险状态,其余点位生态风险较低。研究表明,西岸入湖河流表层沉积物重金属潜在生态风险等级高于北岸,但北岸入湖河流河口表层沉积物中Cu、Zn、Ni、Pb的累积也应当得到重视。     

太湖入湖河流氮磷时空分布特征

为探究典型入湖河流的水环境状况,选取太湖入湖河流梁溪河为研究对象,于2017年12月—2018年12月进行定期取样监测,开展水体氮磷时空分布特征的分析。结果表明,梁溪河支流的污染状况比干流严重,大多支流为劣Ⅴ类水。其中,干流总氮(TN)、氨氮(NH_4~+-N)、硝酸盐氮(NO_3~--N)、总磷(TP)浓度的变化范围分别为0.57～2.86、0.10～0.75、0.02～0.53和0.05～0.39 mg·L~(-1),支流TN、NH_4~+-N、NO_3~--N、TP浓度的变化范围分别为2.42～5.63、1.12～3.35、0.32～2.33和0.07～0.52 mg·L~(-1)。对其氮磷的相关性分析表明,水体氮磷的输入形式和途径上一致。时间分布上,TN浓度在春季和夏季出现峰值,TP浓度则表现出冬季低、夏季高的趋势;空间分布上,夏季氮磷浓度沿干流流向呈上升趋势,支流氮磷污染严重,并对干流产生影响。在今后的河流修复与整治中,应遵循对干流和支流共同调控的综合修复策略。     

小尺度流域河湖水质关联性分析

选取巢湖潜溪河流域和六叉河流域作为江淮农业小流域代表,采用灰色关联分析(GRA)方法,对比研究小尺度流域入湖河流对河湖交汇区水质的影响.河水及河湖交汇区水质周年变化状况监测结果表明,巢湖水质1 a中富营养化最为严重时段是10-12月,营养元素N、P和溶解性金属离子Mn、Fe、Al含量也达到年内最高.河湖水质灰色关联分析结果表明,2个流域河流水质与河湖交汇区水质高度关联,灰色关联度为0.687～0.896.对于小尺度流域而言,湖泊水质对于流域河流水质变化响应迅速,农业流域面源污染对湖泊水体污染的贡献明显.     

基于AQUATOX模型的乌梁素海富营养化模拟及控制研究

乌梁素海是典型的寒旱区湖泊,具有多草、多藻、水浅及寒区气候等特征。针对乌梁素海湖泊富营养化及水华问题,运用AQUATOX模型对乌梁素海湖区主要营养盐的季节变化以及不同藻类(蓝藻、绿藻、硅藻)的演替规律进行了模拟。模拟结果显示,该研究建立的乌梁素海生态系统模型,能较好的模拟水域中营养盐的动态变化以及不同藻类(蓝藻、绿藻、硅藻)的季节演替规律,与乌梁素海实际水环境状况大体吻合。在模拟的基础上,对控制入湖氮、磷污染负荷后营养盐浓度及藻类生物量的响应关系进行探讨。结果显示,在氮磷与营养物响应关系方面,消减入湖氮磷负荷能有效降低乌梁素海湖区相应营养物浓度,且随消减量的加大,其浓度也不断降低。同时消减入湖N,P负荷的20%,营养物TN,TP浓度分别降低17.06%和4.83%;消减入湖N,P负荷的30%,营养物TN,TP浓度分别降低25.62%和6.92%;消减入湖N,P负荷的50%,营养物TN,TP浓度分别降低42.58%和11.56%。在氮磷与藻类响应关系方面,消减氮磷负荷可以有效降低湖内绿藻、蓝藻生物量。同时消减入湖N,P负荷的20%、30%和50%,绿藻及蓝藻生物量平均降幅分别为7.77%、12.60%、19.54%和6.05%、10.60%、13.12%。单一控制磷负荷亦能有效降低绿藻和蓝藻生物量,且作用更加明显,而单一控制氮反而会使蓝藻的生物量增加。因此,在乌梁素海富营养化的治理中,需采取同时消减入湖氮磷负荷或者单一消减磷负荷的措施,以实现抑制水华暴发、改善区域生态的目的。     

高外源性藻类输入的城市河道嗅味物质分布特征及影响因素

利用顶空固相微萃取-气相色谱/质谱联用（HS-SPME-GC/MS）技术测定梁溪河干流及支浜8个点位水体及沉积物中6种嗅味物质浓度（二甲基二硫醚、二甲基三硫醚、2-甲基异茨醇、土臭素、β-环柠檬醛和β-紫罗兰酮）,结合环境因子分析了6种嗅味物质的空间分布特征及其主要影响因素.研究结果表明,梁溪河水体及沉积物中嗅味物质以β-环柠檬醛和2-甲基异茨醇为主,其浓度最高值分别为342.70 ng·L^-1和2664.58 ng·kg^-1.梁溪河水体及沉积物中嗅味物质浓度在干流和支浜中的分布不一致,干流水体高于支浜水体,支浜沉积物高于干流沉积物.影响嗅味物质分布的主要原因可能是蓝藻水华大量输入引起的水体及沉积物营养物质增加及微环境的改变,表现为多种嗅味物质浓度与叶绿素浓度及TOC、TN和N/P呈正相关.由此,本研究为高外源性藻类输入城市河道的治理及异味问题防范提供理论支持.     

秦皇岛主要入海河流污染及其对近岸海域影响研究

利用饮马河、洋河、汤河和戴河的水文和水质监测资料,分析了各河流的污染状况、营养状态、污染物入海通量及其对海域水质的影响。结果表明：秦皇岛市入海河流中饮马河和洋河污染较重;通过污染分担率分析,秦皇岛入海河流的首要污染物为DIN、COD,其次为PO43--P;采用综合营养状态指数法评价,汤河处于轻度富营养状态,戴河处于中度富营养状态,而洋河和饮马河都已达到重度富营养化状态,可见秦皇岛入海河流的富营养化现象非常严重;秦皇岛主要河流污染物入海通量近年来基本呈减小趋势,饮马河和洋河年均入海污染物量占到秦皇岛市陆源入海污染物总量的94.91%;通过相关分析表明,秦皇岛近岸海域的水质主要受入海河流影响,尤其是CODMn、DIN、PO43--P在河、海间存在线性关系,具有强相关性。因此应加强对入河污染物的管理,重点应放在生活污水、农业面源污染的治理上,从而改善近岸海域的水质状况。     

三峡库区笋溪河流域面源污染及其与土壤可蚀性k值的关系

研究三峡库区面源污染特征及其与水土流失的关系,可为库区氮磷污染和土壤侵蚀控制提供依据.选择三峡库区库尾笋溪河流域,在流域内分园地、林地和耕地3种土地利用类型共采集126个土壤样品,并在主干和支流采集52个水质样品.根据EPIC模型计算土壤可蚀性k值,分析流域内土壤可蚀性k值对面源污染的影响.结果表明,笋溪河流域面源污染主要是氮污染,总氮均值达1.37 mg/L,氮素的主要形态为硝态氮,占总氮的71.2%;总磷浓度为0.1 mg/L.流域内土壤可蚀性k值均值为0.040,随着土层加深土壤可蚀性k值呈上升趋势;林地土壤可蚀性k值显著低于园地和耕地.笋溪河流域总氮浓度与园地和耕地0-20 cm土壤可蚀性k值有关,硝态氮浓度与耕地0-40 cm土壤可蚀性k值有关.因此,笋溪河流域面源污染严重,主要来源是耕地和园地,应实行免耕、植物篱等措施,同时减少化肥施用,增加有机肥比例,以增加土壤抗侵蚀能力,进而控制流域水土流失和面源污染.(图6参37)     

温榆河沉积物中壬基酚和双酚A的分布

采用GC/MS对温榆河上游及干流的主要排污口、重点闸坝、主要入河口等河段表层沉积物中的壬基酚(NPs)和双酚A(BPA)进行了分析测定. 结果表明,样品中普遍检出NPs和BPA,浓度范围分别为125-8157.9 ng·g-1和0.6-59.6 ng·g-1. 其浓度水平与水中总有机碳(TOC),总磷(TP)和总氮(TN)具有显著的正相关,结合采样点周边入河污染源的分布情况,判断其主要来自沿岸入河排污口和污染支流.     

网围养殖对骆马湖水体富营养化的影响

对骆马湖1998年度湖体内网围养殖入湖营养盐的研究结果表明,入湖氮、磷量分别为339 和57 t,分别占湖体滞留氮、磷总量的27%和33%,说明网围养殖对湖体水质有一定影响.另外,从近10 a湖区网围养殖面积和产量变化状况分析,1995年以来网围养殖面积趋于稳定,因此网围养殖对湖体水质富营养化的影响也趋于稳定.     

Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

● A machine learning model was used to identify lake nutrient pollution sources. ● XGBoost model showed the best performance for lake water quality prediction. ● Model feature size was reduced by screening the key features with the MIC method. ● TN and TP concentrations of Lake Taihu are mainly affected by endogenous sources. ● Next-month lake TN and TP concentrations were predicted accurately. Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources, for which mathematical modeling is commonly adopted. In contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling, we employed an ensemble machine learning (ML) model to identify the key nitrogen and phosphorus sources of lakes. Six ML models were developed based on 13 years of historical data of Lake Taihu’s water quality, environmental input, and meteorological conditions, among which the XGBoost model stood out as the best model for total nitrogen (TN) and total phosphorus (TP) prediction. The results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality, while the lake TP is predominantly from endogenous sources. The prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication control. Finally, one-month-ahead prediction of lake TN and TP concentrations (R² of 0.85 and 0.95, respectively) was achieved based on this model with sliding time window lengths of 9 and 6 months, respectively. Our work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction, which may provide valuable references for early warning and rational control of lake eutrophication.     

Impact of climate factors on cyanobacterial dynamics and their interactions with water quality in South Taihu Lake,China

Cyanobacterial bloom events in South Taihu Lake cause serious water quality problems and disturb aesthetic view of lake’s environment. In this study, correlations between cyanobacterial blooms and hydro-meteorological factors, including water quality, temperature and precipitation were investigated. Results demonstrated that South Taihu Lake was heavily affected by cyanobacteria and the proliferation of cyanobacteria due to variations in hydro-meteorological factors and water quality conditions. Water quality parameters, including COD, NH₃-N, TN and TP improved significantly since 2008 even at an elevated cyanobacterial bloom situation. Correlation analyses have shown that the development of cyanobacterial density and chlorophyll a concentration was sensitive to a wider temperature variation. The optimum temperature for cyanobacteria was 20°C, while extremely low and high temperatures were found to suppress their growth. Moreover, unusual rainfall patterns were measured during the study period (2003–2009), which showed an adverse impact on cyanobacterial development. Findings from this study suggested that seasonal lake’s water quality monitoring; suitable treatment of cyanobacterial blooms and strict policy implementation can solve the water quality issues in highly eutrophic lakes like Taihu.     

应用物种敏感性分布法分析太湖及天目湖水体的生态风险

采用物种敏感性分布法(SSDs法),应用水生生物急性和慢性毒性数据计算了31种污染物在水中和其中疏水物质在沉积物中的预测无效应浓度(PNECwater和PNECsed),通过收集以往报道的16种污染物在太湖和天目湖的环境浓度,用商值法求得物质的风险商并进行排序.结果发现:蒽、菲、萘、荧蒽、阿特拉津和马拉硫磷在太湖的梅梁湾和五里湖具有很大的生态风险;毒死蜱、三丁基锡氧化物和环己锡虽无环境浓度报道但很有可能具有风险.     

太湖地区“禁磷”措施的效果及在富营养化控制中的作用

通过太湖地区采取“禁磷”措施前后城市生活污水、主要入湖河水和湖体水域中磷浓度与富营养化指数变化的分析 ,证实“禁磷”措施对降低居民生活污水中磷浓度的作用较为明显 ,降幅为 2 4 %左右 ,但对入湖河道和湖体水域中磷浓度与水体富营养化的影响则不明显。表明太湖富营养化的改善 ,除了实施“禁磷”措施外 ,尚需结合流域内其它污染治理措施 ,进行综合治理 ,才能取得较好的效果。     

太湖重污染湖区和水源地水质概况及藻毒素污染环境风险

近年来太湖流域局部水质状况有所改善,但太湖藻型生境条件还未根本改变,水污染防治任务依然艰巨。确保太湖湖体水质稳定达标,尤其是加强对太湖重点湖区和水源地重点污染物的调查研究十分重要。在此背景下,本文调研了太湖重点湖区和水源地水质概况、藻毒素污染时空分布特征、环境影响因子和迁移转化规律,并总结了藻毒素的环境和健康风险研究的最新进展,指出了太湖西部湖区和饮用水源地的主要环境风险,以及未来太湖藻毒素污染相关研究需解决的关键技术问题,以期为促进太湖流域重点污染物的控制和治理,确保太湖饮用水源地安全提供有益借鉴。     

浮叶植物重建对富营养化湖泊氮磷营养水平的影响

利用太湖五里湖污染底泥，在不破坏表层沉积物形态和结构的情况下，利用大口径的采样器采集沉积物柱状样，研究浮叶植物荇菜（Limnanthemun nymphoides）在此底泥上适应性生长情况及其对水体以及沉积物中氮磷的影响。结果表明，在培养实验过程中，荇菜生长使上覆水体中的氮、磷营养水平逐渐降低，藻类的生长明显受到克制，水体透明度增加，水质逐渐改善。通过植物根系对沉积物和问隙水中营养盐的直接吸收，使表层（0～5cm）沉积物与问隙水中氮磷营养盐的水平在实验结束后有明皿下降，对于控制沉积物内源营养盐释放有重要的作用。因此，恢复以水生植物为丰的水生生态系统足重建富营养湖泊生态系统和控制湖泊内源负荷的重要措施。     

A model on the carbon cycling in Lake Taihu, China

A model of the carbon cycling in Lake Taihu was developed based on the previous developed model EcoTaihu Model, which couples the hydrology, the nutrient cycling and a number of biological processes. The carbon cycling model (abbreviated CCM) has in addition to the states variables of the EcoTaihu Model, the carbon in phytoplankton, zooplankton, fish, macroplant, hydrogen carbonate carbon, carbonate carbon, dissolved carbon, abiotic organic carbon in water, organic carbon in sediment, soluble organic carbon in pore water, inorganic carbon in sediments, soluble inorganic carbon in pore water and pH. The calibration and validation of the CCM showed that the model results are in good accordance with the observations (from the period February17 to December. 5, 2003). It implies that the model can be used to assess the variation of the carbon dioxide flux at the water-air interface, and to find the pH value of the lake water as function of time. According to the model, the carbon dioxide flux at the water-air interface has clear, diurnal variations. Eutrophied water is a sink for the atmospheric carbon dioxide due to the phytosynthesis during the summer. Due to the terrestrial input of carbon to the lake, Lake Taihu is, however, a source of atmospheric carbon dioxide. The total annual flux is almost equal to the terrestrial input of carbon to the lake.     

太湖表层沉积物中重金属的形态分析

采用BCR三步分级提取法和ICP-AES测定了太湖沉积物中8种重金属不同形态的含量，初步评估了太湖沉积物中重金属的生物有效性，探讨了沉积物总有机碳（TOC）与重金属不同形态之间的关系。     

太湖浮游植物群落结构及其与水质指标间的关系

为了探讨太湖浮游植物群落结构时空分布特征、以及太湖浮游植物群落指标与水质指标间的关系,于2013年1月─2013年12月对太湖7个点位浮游植物群落结构和水质指标（水温、透明度、pH、溶解氧、电导率、总氮、总磷、氨氮、高锰酸盐指数、化学需氧量、氟化物、生化需氧量、硝酸盐氮、亚硝酸盐氮、溶解性磷酸盐和叶绿素a）进行月度调查,研究其浮游植物群落结构和湖泊水质的时空分布;并利用Pearson相关性分析浮游植物密度、浮游植物多样性与水质指标间的关系;找出影响太湖浮游植物群落结构的主要水质指标。结果表明：太湖7个点位共获得124种浮游植物物种,其中蓝藻门（Cyanophyta）30种、绿藻门（Bacillariophyta）47种、硅藻门（Chlorophyta）34种、隐藻门（Cryptophyta）3种、裸藻门（Euglenophyta）6种和甲藻门（Dinoflagellate）4种;其中蓝藻门的微囊藻属（Microcystis spp.）为绝对优势种群,优势度为80.8%;太湖浮游植物总密度与蓝藻门密度呈极显著正相关（r=1.000,P＜0.0001）;绿藻门和硅藻门占浮游植物总密度百分比分别和蓝藻门占浮游植物总密度百分比呈极显著负相关（r=-0.497,P＜0.0001;r=-0.814,P＜0.0001）。太湖7个点位水质首要污染物为总氮,其次是总磷和化学需氧量;西太湖污染物浓度最高。从空间上看,太湖浮游植物总密度最高值出现在贡湖湾（远离其入湖口处）,且贡湖湾浮游植物群落多样性相对低于太湖其他点位,同时贡湖湾微囊藻属密度百分比达90.1%,远高于太湖其他点位;从时间上看,太湖浮游植物总密度最高值出现在12月份、其次是6月份;通过浮游植物群落指标与水质指标相关性分析,水温、透明度、总氮、化学需氧量、叶绿素a是影响太湖浮游植物群落结构的主要水质指标。控制太湖入湖口水质污染物浓度排放和修?     

Quantitative characterization of Cu binding potential of dissolved organic matter （DOM） in sediment from Taihu Lake using multiple techniques

Dissolved organic matter （DOM） plays an important role in heavy metal speciation and distribution in the aquatic environment especially for eutrophic lakes which have higher DOM concentration. Taihu Lake is the third largest freshwater and a high eutrophic lake in the downstream of the Yangtze River, China. In the lake, frequent breakout of algae blooms greatly increased the concentration of different organic matters in the lake sediment. In this study, sediment samples were collected from various part of Taihu Lake to explore the spatial difference in the binding potential of DOM with Cu. The titration experiment was adopted to quantitatively characterize the interaction between Cu（II） and DOM extracted from Taihu Lake sediments using ion selective electrode （ISE） and fluorescence quenching technology. The ISE results showed that the exogenous DOM had higher binding ability than endogenous DOM, and DOM derived from aquatic macrophytes had a higher binding ability than that derived from algae. The fluorescence quenching results indicated that humic substances played a key role in the complexation between DOM and Cu（II） in the lake. However, because of the frequent breakout of algae blooms, protein-like matters are also main component like hnmic matters in Taihu Lake. Therefore, the metals bound by protein-like substances should be caused concern as protein-like substances in DOM were unstable and they will release bound metal when decomposed.