富营养化水体的营养盐限制性研究综述

水体富营养化是全球目前以及今后相当一段时期内的重大水环境问题。氮、磷作为浮游植物生长所必需的营养盐,是水体富营养化的主要限制因子。通过对近年来水体富营养化受氮、磷营养盐限制的研究进行综述,研究了营养盐来源及其对浮游植物生长的影响,总结了营养盐限制性差异的影响因素,分析了缓解富营养化的营养盐主控因子。分析表明:营养盐的来源主要分为外源和内源,受外界环境及人类活动影响显著;浮游植物的生长受N/P比值及其绝对浓度的共同作用;在不同的水文、气候和人类活动强度下,水体富营养化主要营养盐限制因子存在差异,并且存在限制性转换和共同限制的情况;缓解水体富营养化措施的提出应在综合考虑多种因素的前提下进行。     

Long-term joint e ect of nutrients and temperature increase on algal growth in Lake Taihu, China

To study how global warming and eutrophication a ect water ecosystems, a multiplicative growth Monod model, modified by incorporating the Arrhenius equation, was applied to Lake Taihu to quantitatively study the relationships between algal biomass and both nutrients and temperature using long-term data. To qualitatively assess which factor was a limitation of the improved model, temperature variables were calculated using annual mean air temperature (AT), water temperature (WT), and their average temperature (ST), while substrate variables were calculated using annual mean total nitrogen (TN), total phosphorus (TP), and their weighted aggregate (R), respectively. The nine fitted curves showed that TN and AT were two important factors influencing algal growth; AT limited growth as algal photosynthesis is mainly carried out near the water surface; N leakage of phytoplankton and internal phosphorus load from sediment explains why TN was the best predictor of peak biomass using the Monod model. The fitted results suggest that annual mean algal biomass increased by 0.145 times when annual mean AT increased by 1.0°C. Results also showed that the more eutrophic the lake, the greater the e ect AT had on algal growth. Subsequently, the long-term joint e ect of annual temperature increase and eutrophication to water ecosystems can be quantitatively assessed and predicted.     

Long-term joint effect of nutrients and temperature increase on algal growth in Lake Taihu, China

To study how global warming and eutrophication affect water ecosystems, a multiplicative growth Monod model, modified by incorporating the Arrhenius equation, was applied to Lake Taihu to quantitatively study the relationships between algal biomass and both nutrients and temperature using long-term data. To qualitatively assess which factor was a limitation of the improved model, temperature variables were calculated using annual mean air temperature (AT), water temperature (WT), and their average temperature (ST), while substrate variables were calculated using annual mean total nitrogen (TN), total phosphorus (TP), and their weighted aggregate (R), respectively. The nine fitted curves showed that TN and AT were two important factors influencing algal growth; AT limited growth as algal photosynthesis is mainly carried out near the water surface; N leakage of phytoplankton and internal phosphorus load from sediment explains why TN was the best predictor of peak biomass using the Monod model. The fitted results suggest that annual mean algal biomass increased by 0.145 times when annual mean AT increased by 1.0℃. Results also showed that the more eutrophic the lake, the greater the effect AT had on algal growth. Subsequently, the long-term joint effect of annual temperature increase and eutrophication to water ecosystems can be quantitatively assessed and predicted.     

三峡水库支流大宁河水华特征研究

以三峡水库支流大宁河水华敏感期(2007年4~6月和2008年4~5月)水质和水华的调查数据为依据,研究了其水质变化、营养盐构成及水华特征.结果表明,水华敏感期大宁河自回水段以下氮磷含量较高,总氮范围为0.84~3.21 mg/L,总磷为0.011~0.531 mg/L,氮营养盐主要以TDN为主(TDN/TN为84%),而磷营养盐以TDP占优(TDP/TP为60%);N/P值均高于16,藻类生长受磷限制.高锰酸盐指数和溶解氧含量低且变化稳定.叶绿素a为1.41~219.04 mg.m-3.相关性分析表明Chl-a与TP、高锰酸盐指数、DO、pH呈显著正相关(rChla-TP=0.453、rChla-高锰酸盐指数=0.641、rChla-DO=0.584、rChla-pH=0.409,p0.01),与SD呈显著负相关(rChla-SD=-0.392,p0.01);pH受多参数影响,但受藻类生长影响较大.通过显微镜对藻类进行鉴定,发现大宁河自回水段以下水华敏感期藻类分布较广,共发现8门82属124种,其中硅藻门和绿藻门分布最多,其次为蓝藻门和甲藻门,其余藻种较少.大宁河在水华敏感期暴发了3次自回水段以下大规模水华,水华期间藻密度最高值是正常值的14~1427倍,水华优势种主要有绿藻门的波吉卵囊藻、小空星球藻、土生绿球藻、实球藻和小球藻;裸藻门的扁裸藻、矩圆囊裸藻;硅藻门的小环藻、冠盘藻和舟形藻;甲藻门的埃尔多甲藻等;发生多藻种同时水华的情况;出河口处藻类较少.     

基于分位数回归的洱海藻类对氮、磷及水温的响应特征

基于云南洱海长时间尺度水质观测数据,运用分位数回归方法分析浮游藻类叶绿素a(Chl-a)对氮(N)、磷(P)、水温的定量响应关系.结果表明过去20余年洱海藻类生物量受水温、N、P共同影响,随着洱海富营养化程度的加剧,水温对藻类生物量的相对重要度在持续下降,斜率平均值从2.70下降至0.44.而营养物对藻类的促进效应明显在提升,尤其是TP对藻类的相对重要度持续在攀升,斜率平均值从-0.3增长至0.8.TN对藻类生物量整体表现为较稳定的正效应,但近些年(2008~2013年)TN对藻类正效应达到最低.2002之后,P已逐渐取代N成为最重要的营养物限制因子.在季节方面,春季和秋季以水温和N的共同限制为主导,但春季当Chl-a8 mg·m-3时,N和水温对藻类的正效应逐渐被P取代.夏季完全以N、P共同限制效应占主导,当Chl-a3 mg·m-3时,TP的正效应逐渐超过TN,冬季则以P和水温的共同限制效应为主导.在气候变暖的大背景下,洱海富营养化控制应以"控P"为主和N、P协同削减的策略.当前富营养化控制过程中,应着重监控春、秋两季温度短期快速上升可能引发的全湖藻华风险.     

太湖不同湖区夏季蓝藻生长的营养盐限制研究

采集太湖6个湖区水样,利用营养盐添加,现场培养实验研究了水华蓝藻在不同湖区水体中生长的氮、磷限制情况和蓝藻的生长潜力.结果表明,梅梁湾水体只有氮、磷同时添加才对蓝藻生物量具有显著的促进作用,表明该湖区水华蓝藻的生长不仅存在磷限制,而且存在明显的氮限制.在太湖西部河口区、竺山湾和贡湖湾,蓝藻对单独的氮添加没有反应,而单独磷添加和氮磷同时添加对蓝藻生长具有同样的促进作用,表明磷是这些区域藻类生长的主要限制因子.东太湖水体不论氮磷单独还是同时添加对蓝藻生长均没有促进作用,表明存在氮磷以外的限制因子.氮磷供应充足的情况下,梅梁湾和西部河口区水体培养的蓝藻生长速率最高,表明这两个水域蓝藻的生长潜力最大,氮磷输入极易刺激蓝藻大量增殖,这在一定程度上解释了为什么蓝藻水华在这两个区域更为严重.蓝藻在贡湖湾和胥口湾水体中生长速率较低,在东太湖水体中的生长速率最低,因此这些水域的蓝藻增殖潜力较低.     

滨海地区混盐水体富营养化主因子识别与分析——以天津市清净湖为例

水质与水体营养化程度密切相关,提炼识别其中的主要影响因素并合理控制是水体富营养化防治的有效途径.我国滨海地区地表水咸化问题突出,混盐水体(含盐量500~30000 mg·L-1)众多,其中,许多混盐水体还同时面临富营养化加剧及水华的威胁.因此,本文以天津滨海地区典型混盐水体清净湖为研究对象,通过对其水环境监测数据的统计学分析,结合藻类生长模拟实验,对其富营养化主要影响因子进行识别与分析.结果表明,总磷和矿化度为清净湖藻类生长的主要影响因子,叶绿素a浓度与矿化度呈显著负相关关系,与总磷呈显著正相关关系,以总磷和矿化度为自变量的多元线性回归模型可较好地预测叶绿素a动态.水体含盐量在15000~25000 mg·L-1的范围适宜藻类生长增殖,而当盐度小于10000 mg·L-1或大于30000 mg·L-1时,藻类生长受到抑制;在清净湖当前氮浓度水平下,磷含量增加会促进藻类生长增殖,藻类生长速率呈P3组(10∶1,氮磷比)P4组(5∶1)P2组(20∶1)P1组(50∶1)P0组(无磷培养液),氮磷比为10∶1时最适宜藻类生长.     

绿潮硬毛藻分解对天鹅湖水体氮磷水平的影响

为了解绿潮硬毛藻衰亡分解对上覆水体营养水平的影响,以荣成天鹅湖不同湖区的沉积物和暴发的硬毛藻为试材,通过室内模拟研究了藻类分解过程中水体氮磷水平及理化性质的变化,并评价了不同湖区沉积物中氮磷的释放潜力.结果表明:硬毛藻衰亡分解使上覆水体中ρ(TN)和ρ(NH₄+-N)均明显上升,并且前期(0~16 d)上升较快,ρ(TN)和ρ(NH₄+-N)最高分别可达12.40和7.98 mg/L;水体中ρ(TP)和ρ(SRP)表现为前期变化不大,19 d后大幅增加,含量变幅分别为0.02~1.14和0.01~0.40 mg/L.在试验中后期(约16 d后),不同湖区沉积物处理的水体中ρ(TN)、ρ(NH₄+-N)、ρ(TP)、ρ(SRP)均表现为有沉积物含藻处理>无沉积物含藻处理>有沉积物无藻处理.在藻分解的条件下,不同湖区沉积物的氮磷释放能力存在很大差异,氮释放量的顺序为湖中心>西北部>南部,而磷表现为西北部>湖中心>南部.在硬毛藻绿潮的衰亡阶段,由于初期藻体营养盐的直接释放和后期促进沉积物内源释放的间接影响,水体中ρ(TN)和ρ(TP)均明显增加,进而加重了天鹅湖水体的富营养化水平.      

三峡水库支流大宁河冬、春季水华调查研究

以三峡水库主要支流--大宁河冬、春季2次不同类型水华的调查数据为依据,分析并比较了不同水华期间水质的变化、营养盐的构成及水华的特征.结果表明,大宁河冬季水华以唐家湾为中心,叶绿素a(Chl-a)含量较高[(Chl-a)_(max)/(Chl-a)_(min)=260];随着藻类的生长总氮(TN)、总磷(TP)和高锰酸盐指数出现富集而含量升高,溶解氧(DO)和pH却出现低值;水华高峰期水体藻类较少,共发现2门4种,水华优势种为铜绿微囊藻和水华微囊藻,藻密度高达3.15×10~7个/L,相关加权综合营养状态指数为80,属于重度富营养化水体.而春季水华属于自回水段以下整体性暴发,Chl-a含量也较高[(Chl-a)_(max)/(Chl-a)_(min)=140];TN、TP和高锰酸盐指数均是随着水华的发生逐渐升高;水华高峰期藻类种群丰富,共发现5门44种,各断面水华优势种和藻密度均不同,相关加权综合营养状态指数显示东坪坝和白水河为轻度富营养化水体.相关性分析表明,冬季水华期间Chl-a与TN、TP、高锰酸盐指数、水温呈显著正相关,与DO、透明度(SD)呈显著负相关;春季水华Chl-a与TP、高锰酸盐指数、DO、pH呈显著正相关,与SD呈显著负相关.冬季水华pH与SD呈显著正相关,与TN、TP、高锰酸盐指数呈显著负相关;而春季水华pH与Chl-a、TP、高锰酸盐指数、DO、气温呈显著正相关,与SD呈显著负相关.     

基于宏条形码技术的白洋淀水华藻类识别及其驱动因子分析

浮游藻类是引起水华暴发的主要原因.为筛选潜在水华藻类,评估白洋淀水华风险区域,于2020年8月对白洋淀373点位展开浮游藻类调查.利用宏条形码技术分析,解析水华藻类群落组成,同时采用显微镜计数法统计藻密度.根据总藻密度对白洋淀不同区域的水华程度进行评估,同时进一步针对水华藻类群落,耦合淀区水质条件,探究白洋淀不同区域水华藻类群落空间差异驱动因子,以甄别影响水华藻类群落结构关键环境因子.结果表明,95%以上采样区域无水华风险(藻类密度<2×10⁶个·L^-1),仅5个样点存在轻微水华风险.但水华藻类群落分析共检测到了90种水华藻类,其中优势水华藻种有20种,隶属于以绿藻门、蓝藻门和裸藻门为主.水华藻类群落结构在不同区域上具有显著空间异质性(P<0.05).关键驱动因子解析结果表明,总磷(TP)、总氮(TN)和氨氮(NH⁺₄-N)是造成水华藻类群落结构差异的关键因子.其中,门水平上,蓝藻门水华藻类与以上关键因子显著正相关;种水平上,硅藻门和绿藻门水华藻类与关键因子响应更显著.因此,水华藻类群落...     

三峡水库春季营养盐和浮游植物空间分布及其影响机制

为研究三峡水库春季水体营养盐与浮游植物的空间分布状况,于2013年3月对三峡水库22条支流及干流的6个断面进行采样监测. 结果表明:来水、回水、河口和干流4类断面ρ(TN)平均值分别为1.69、1.84、2.01、1.51 mg/L;ρ(TP)平均值分别为0.115、0.191、0.179和0.181 mg/L;不同类型断面间ρ(TN)、ρ(TP)差异不显著;水体中N、P的主要形态分别为NO₃--N和PO₄3--P;N/P〔n(N)/n(P)〕从来水(110.8)至干流(18.9)逐渐降低. 三峡水库总体上为中营养状态,回水和河口区富营养化程度较高,富营养断面比例分别为45.4%和36.4%. 研究期间共检出浮游植物8门98属,其中以绿藻门、硅藻门和蓝藻门为主,分别检出42、26和17属;从组成上看,来水和干流断面以硅藻-绿藻为主,回水、河口断面以绿藻-硅藻为主. 浮游植物丰度由高到低依次为回水、河口、来水和干流断面. 调查期间,22条支流中有15条支流在不同位置发生水华,但主要集中在回水区;拟多甲藻水华为主要类型且集中在库区的下游支流,而库区中上游支流则以隐藻、衣藻、小球藻、小环藻等水华为主. 环境因子排序分析表明,在水华集中的回水-河口区域,影响浮游植物丰度分布的主要环境因子数明显少于其他区域,温度和ρ(DO)为该区域浮游植物丰度分布的主要影响因子,而ρ(TN)、ρ(TP)的影响不明显.      

Phytoplankton community from Lake Taihu, China, has dissimilar responses to inorganic and organic nutrients

To evaluate the response of phytoplankton from Lake Taihu to di erent types of nutrients, the phytoplankton responses were measured after adding inorganic nitrogen (N) and phosphorus (P) or decomposed algal scum (Microcystis spp.) into the lake water. Both types of nutrients promoted an increase in phytoplankton biomass as determined by chlorophyll a and algal wet weight. The addition of decomposed algal scum resulted in a significantly greater phytoplankton response than the addition of inorganic N and P alone. The dissolved inorganic N and P in the inorganic nutrient treatment were found not limit phytoplankton growth. The higher algal biomass obtained in the treatment with decomposed algal scum indicated the importance of other organic nutrients besides N and P such as trace elements, as well as the importance of the form of N since the levels of ammonia nitrogen (NH4 +-N) from the decomposed algal treatment were actually higher than that of the inorganic N and P addition. Microcystis spp. (Cyanobacteria), Scenedesmus spp. (Chlorophyta) and Synechocystis spp. (Cyanobacteria) were the dominant taxa in the control, inorganic N and P treatment, and the decomposed algal scum treatment, respectively. Microcystis never bloomed in response to both types of nutrient additions indicating that the bloom propagation is not solely related to nutrient additions, but may be related to the absence of selective grazing from zooplankton.     

三峡库区次级河流营养状态及营养盐输出影响

通过对三峡库区15条次级河流TP、TN、Chla、高锰酸盐指数、SD和浮游植物的测定,分析了次级河流的营养状态及营养盐输出状况.结果表明,次级河流TN、TP、高锰酸盐指数、Chla含量和SD差异较大,SD范围为0.45～1.5 m,TN含量范围为0.65～4.27 mg·L^-1,TP含量范围为0.011～0.432mg·L^-1,高锰酸盐指数范围为0.657～5.37mg·L^-1,Chla值范围为0.57～12.2mg·m^-3.次级河流受到不同程度污染,水体中N含量丰富,部分次级河流富营养化的限制因子为P.利用综合营养状态指数法评价了次级河流富营养化程度,结果表明3条达到轻度富营养化,2条为贫营养,10条河流为中营养.次级河流藻类7门67属129种,种类数以硅藻、绿藻和蓝藻最多.浮游植物的群落类型以硅-绿藻型、硅-蓝藻型和蓝-绿藻型为主,种类和数量随水域不同而呈现差异,水体营养特征为浮游植物响应型.15条次级河流年排放TN、TP和高锰酸盐指数分别为3.14×１０⁵ t、1.76×１０⁴ t和2.74×１０⁵ t.三峡水库完工后,由于次级河流河口区水体流速减缓,富营养化趋势可能加重.     

水华过程水质参数与浮游植物定量关系的研究——以太湖梅梁湾为例

考虑到太湖水华暴发过程中水质参数（如营养盐或水体理化参数）对浮游植物增殖的滞后效应,利用有滞后变量参与的格兰杰因果关系检验和向量自回归模型,分析了太湖梅梁湾湖区2000年~2012年的监测数据,探讨了湖泊水质参数对于水华暴发的影响和定量关系.结果发现,表征浮游植物生物量的叶绿素a（Chl-a）浓度与总磷（TP）、氮磷比（N/P）、水温（WT）之间存在长期的均衡关系,格兰杰因果关系模型和向量自回归模型（VAR）的结果显示,水体中TP浓度、N/P和WT是Chl-a含量变化的格兰杰原因,上述结果提供了湖泊水质参数与蓝藻生物量的定量关系,在其他水质参数保持不变的情况下,约1%湖泊TP含量、N/P和水温的变化分别造成0.97%、0.078%和0.55%的浮游植物生物量的变化.本研究为水华暴发研究过程中水质参数的定量化影响提供一个新颖的视角,考虑了时间滞后变量的时间序列分析方法也可以加深对水华暴发过程的理解.     

淀山湖营养物输入响应关系的分位数回归分析

采用分位数回归方法研究了淀山湖富营养化输入(总氮和总磷)及响应指标(叶绿素a)之间的关系.结果表明,淀山湖营养物TP和TN(输入指标)对不同分位叶绿素a(响应指标)的影响不同.在低分位(0.10~0.50)时,淀山湖的藻类生物量(叶绿素a)主要受TP的控制;在高分位(0.60~0.90)时,淀山湖的藻类生物量同时受TP和TN的控制;TN对藻类生长的抑制作用随分位数升高而加强.0.60分位时是TP和TN对藻类增长影响发生变化的分位.普通最小二乘法(OLS)方法得到的经验方程,不能估计淀山湖多个因素不同变化速率对湖泊营养物输入响应关系的影响.     

藻类生物膜技术脱氮除磷效果研究

利用藻类生物膜去除水体氮磷为富营养化的防治提供了1种新途径,实验室条件下研究了以巨颤藻（Oscillatoria princeps）占优势的藻类生物膜对人工合成污水、污水处理厂二级污水和富营养化湖水氮（N）、磷（P）的去除效果.结果表明,通过5 d的处理,藻类生物膜对人工合成污水、污水处理厂二级污水和富营养化湖水总氮（TN）去除率分别为57.1%、94.5%和93.8%,对总磷（TP）去除率分别为93%、73%和79%.藻类产量达到3.7～7.2　g·(m²·d)^-1;收获藻体总凯氏氮（TKN）达5.7%～7.2%,TP达0.78%～2.44%,对污水N、P的回收率分别达20%～39%和65%～82%.     

Effect of nutrient level on phytoplankton community structure in di erent water bodies

Increasing levels of pollution within water bodies can cause eutrophication and an associated rapid growth in and reproduction of phytoplankton. Although most frequently occurring in bodies of water such as lakes and dams, in recent years an increasing number of river systems in China have suffered serious algal blooms. The community structure of phytoplankton may differ, however, dependent on the hydrodynamic conditions and nutrient levels within the water body. The field investigation results obtained fro...     

Seasonal variation of nitrogen and phosphorus in Xiaojiang River—A tributary of the Three Gorges Reservoir

A yearlong monitoring program in the backwater area of Xiaojiang River (XBA) was launched in order to investigate the eutrophication of backwater areas in tributaries of the Yangtze River in the Three Gorges Reservoir (TGR) in China, starting after the impoundment water level of the TGR reached 156 m. From March 2007 to March 2008, the average concentration of total nitrogen (TN) and total phosphorus (TP) were (1553±484) μg·L⁻¹ and (62±31) μg·L⁻¹, respectively. The mean value of chlorophyll was (9.07±0.91) μg·L⁻¹. The trophic level of XBA was meso-eutrophic, while the general nutrient limitation was phosphorus. The results indicated that XBA has a strong ability to purify itself and has non-point source pollution from terrestrial runoff. The variation of TN/TP ratio was caused by a variation in TN rather than in TP when TN/TP < 22. N-fixation from cyanobacteria occurred and became an important process in overcoming the nitrogen deficit under a low TN/TP ratio. When TN/TP ⩾ 22, the variation of TP affected the TN/TP ratio more significantly than TN. The increase of TP in XBA was caused mainly by particulate phosphorus, which could originate from a non-point source as adsorptive inorganic forms after heavy rainfall and surface runoff. An increase in the river’s flow could also contribute to an unstable environment for the growth of phytoplankton.     

Selection of water source for water transfer based on algal growth potential to prevent algal blooms

Water transfer is becoming a popular method for solving the problems of water quality deterioration and water level drawdown in lakes. However, the principle of choosing water sources for water transfer projects has mainly been based on the effects on water quality, which neglects the influence in the variation of phytoplankton community and the risk of algal blooms. In this study, algal growth potential (AGP) test was applied to predict changes in the phytoplankton community caused by water transfer projects. The feasibility of proposed water transfer sources (Baqing River and Jinsha River) was assessed through the changes in both water quality and phytoplankton community in Chenghai Lake, Southwest China. The results showed that the concentration of total nitrogen (TN) and total phosphorus (TP) in Chenghai Lake could be decreased to 0.52 mg/L and 0.02 mg/L respectively with the simulated water transfer source of Jinsha River. The algal cell density could be reduced by 60%, and the phytoplankton community would become relatively stable with the Jinsha River water transfer project, and the dominant species of Anabaena cylindrica evolved into Anabaenopsis arnoldii due to the species competition. However, the risk of algal blooms would be increased after the Baqing River water transfer project even with the improved water quality. Algae gained faster proliferation with the same dominant species in water transfer source. Therefore, water transfer projects should be assessed from not only the variation of water quality but also the risk of algal blooms.     

香溪河库湾水质特征与非回水区水华响应关系

为探究香溪河在受倒灌影响较弱的河段水华暴发征兆及机理,于水华高发期5~8月对香溪河进行监测,分析电导率、水温、叶绿素a（Chl-a）以及流速.结果表明,在6~8月,香溪河倒灌现象于XX05点（峡口镇）处基本结束,XX06~XX09受倒灌来水影响较弱;香溪河于7月暴发水华,各个监测点位上Chl-a含量均值达到100μg/L以上,XX05~XX06与XX07-XX09点位上暴发不同种水华;在水华暴发前后,水体温度无显著变化,且并无明显分层现象,说明水温分层是水华暴发的主要原因这一理论并不能很好的适用于非回水区;通过对电导率数值的研究发现,数值在垂向上出现显著拐点,而拐点出现在临界层与光补偿层之间,同时与叶绿素a含量分布呈现显著负相关性.香溪河总氮（TN）、总磷（TP）平均值为1.849mg/L和0.157mg/L,均超过富营养化的阈值,水体氮磷含量与Chl-a浓度无显著相关性,水体中除N、P营养盐外的其它离子对香溪河水华的暴发起着重要作用.在水华消退后,电导率数值又逐渐恢复表层高底层低的垂向线性分布特性,与水华的暴发、消退有着明显的响应.