Polycyclic aromatic hydrocarbon (PAH) deposition to and exchange at the air-water interface of Luhu, an urban lake in Guangzhou, China

Urban lakes are vulnerable to the accumulation of semivolatile organic compounds, such as PAHs from wet and dry atmospheric deposition. Little was reported on the seasonal patterns of atmospheric deposition of PAHs under Asian monsoon climate. Bulk (dry + wet) particle deposition, air-water diffusion exchange, and vapour wet deposition of PAHs in a small urban lake in Guangzhou were estimated based on a year-round monitoring. The total PAH particle deposition fluxes observed were 0.44-3.46 μg m⁻² day⁻¹. The mean air-water diffusive exchange flux was 20.7 μg m⁻² day⁻¹. The vapour deposition fluxes of PAHs ranged 0.15-8.26 μg m⁻² day⁻¹. Remarkable seasonal variations of particulate PAH deposition, air-water exchange fluxes and vapour wet deposition were influenced by seasonal changes in meteorological parameters. The deposition fluxes were predominantly controlled by the precipitation intensity in wet season whereas by atmospheric concentration in dry season.     

玄武湖挺水植物区与敞水区浮游甲壳动物昼夜水平迁移初探

浮游甲壳动物昼夜垂直迁移(DVM)是深水湖泊中的一种常见的现象,在浅水湖泊中,没有明显的下层滞水层为浮游甲壳动物提供避护所,浮游甲壳动物的垂直迁移活动不明显。但浅水湖泊挺水植物的存在为浮游甲壳动物提供了区别于敞水带的生境,结合理化、浮游植物和鱼的因素,对浅水湖泊玄武湖挺水植物区与敞水区浮游甲壳动物的昼夜水平迁移进行了研究。结果得出：浅水湖泊玄武湖中理化环境（如温度、溶解氧和pH)在荷花区、敞水区、荷花区与敞水区的交界区差异不大,对浮游甲壳动物的昼夜水平迁移不起主导作用。荷花区的浮游植物在质量和数量上低于敞水区,浮游甲壳动物在夜间捕食压力小的情况下会向敞水区移动。敞水区、交界区浮游甲壳动物在白天被捕食的风险要大于荷花区,因而白天时间浮游甲壳动物会迁移到荷花区聚集.     

Use of a food web model to evaluate the factors responsible for high PCB fish concentrations in Lake Ellasjøen, a high Arctic Lake

Background, aim, and scope

Lake Ellasjøen, located in the Norwegian high arctic, contains the highest concentrations of polychlorinated biphenyls (PCBs) ever recorded in fish and sediment from high arctic lakes, and concentrations are more than 10 times greater than in nearby Lake Øyangen. These elevated concentrations in Ellasjøen have been previously attributed, in part, to contaminant loadings from seabirds that use Ellasjøen, but not Øyangen, as a resting area. However, other factors, such as food web structure, organism growth rate, weight, lipid content, lake morphology, and nutrient inputs from the seabird guano, also differ between the two systems. The aim of this study is to evaluate the relative influence of these factors as explanatory variables for the higher PCB fish concentrations in Ellasjøen compared with Øyangen, using both a food web model and empirical data.

Methods

The model is based on previously developed models but parameterized for Lakes Ellasjøen and Øyangen using measured data wherever possible. The model was applied to five representative PCB congeners (PCB 105, 118, 138, 153, and 180) using measured sediment and water concentrations as input data and evaluated with previously collected food web data.

Results

Modeled concentrations are within a factor of two of measured concentrations in 60% and 40% of the cases in Lakes Ellasjøen and Øyangen, respectively, and within a factor of 10 in 100% of the cases in both lakes. In many cases, this is comparable to the variability associated with the data as well as the efficacy of the predictions of other food web model applications.

Discussion

We next used the model to quantify the relative importance of five major differences between Ellasjøen and Øyangen by replacing variables representing each of these factors in the Ellasjøen model with those from Øyangen, in separate simulations. The model predicts that the elevated PCB concentrations in Ellasjøen water and sediment account for 49%–58% of differences in modeled fish PCB concentrations between lakes. These elevated sediment and, to a lesser extent, water concentrations in Ellasjøen are due to PCB loadings from seabird guano. However, sediment–water fugacity ratios of PCBs are consistently greater in Ellasjøen compared with Øyangen, which suggests that internal lake processes also contribute to differences in sediment and water concentrations. We hypothesize that the nutrients associated with guano influence sediment–water fugacity ratios of PCBs by increasing the stock of pelagic algae. As both these algae and the guano settle, their organic carbon content is degraded faster than PCBs, which causes an extra magnification step in Ellasjøen before these detrital particles are consumed by benthic organisms, which are in turn consumed by fish. The model predicts that the remaining ～50% of the differences in PCB concentrations observed between the fish of these lakes are due to other subtle differences in their food web structures.

Conclusions

In conclusion, based on the results of a food web model, we found that the most dominant factors influencing the higher PCB fish concentrations in Lake Ellasjøen compared with Øyangen are the higher sediment and water concentrations in Ellasjøen, caused by seabird guano. Together, sediment and water are predicted to account for 49%–58% of differences in fish concentrations between lakes. Although seabird guano provides a source of nutrients to the lake, in addition to contaminants, empirical data and indirect model results suggest that nutrients are not leading to decreased bioaccumulation, in contrast to what has been observed in temperate, pelagic food webs.

Recommendations and perspectives

The results of this study emphasize the importance of considering even small differences in food web structure when comparing bioaccumulation in two lakes; although the food web structures of Ellasjøen and Øyangen differ only slightly, the model predicts that these differences account for most of the remaining ～50% of the differences in PCB fish concentrations between the two lakes. This study further demonstrates the utility of food web models as we were able to predict and tease apart the influence of various factors responsible for the elevated concentrations in the fish from Lake Ellasjøen, which would have been difficult using the field data alone.     

Ra–Po–Pb isotope systematics in waters of Sambhar Salt Lake,Rajasthan (India): geochemical characterization and particulate reactivity

The Sambhar Salt Lake hydrological system, including river waters, groundwaters, evaporating pans and sub-surface brines, has been analyzed for the salt content (TDS) and naturally occurring radionuclides (²¹⁰Po, ²¹⁰Pb and ^226,228Ra). The abundance of these radionuclides and their activity ratios show a wide variation in different hydrological regimes, which helps to geochemically characterize the lake system. A significantly lower Ra to total dissolved solids (TDS) ratio in the brines (by two to three orders of magnitude), when compared to the groundwaters and river waters, suggests removal of dissolved Ra by co-precipitation with Ca–Mg minerals at an early stage of the brine evolution. The concentration of Ra in evaporating lake/pan waters saturates at a value of about 35 Bq L⁻¹ over the salinity range of 100–370 g L⁻¹; attributable to its equilibration with the clay minerals. The two distinct regimes, saline lake system (lake water, evaporating pans and sub-surface brines) and groundwaters have been identified based on their differences in the distribution of ^226,228Ra isotopes. This observation points to the conclusion that the groundwaters and the lake brines are not intimately coupled in terms of their origin and evolution. The abundances of ²¹⁰Po and ²¹⁰Pb along with their activity ratios (²¹⁰Po/²¹⁰Pb) are markedly different among the surface lake waters/evaporating pans, sub-surface lake brines and groundwaters. These differences are explained in terms of different geochemical behaviour of these nuclides in presence of algae and organic matter present in these water regimes.     

利用中巴地球资源卫星数据反演武汉市湖泊营养状态指数

以武汉市主要湖泊为例,研究了利用中巴地球资源卫星（CBERS2）数据反演水体营养状态指数（TLI）。研究旨在评估利用中巴地球资源卫星数据来估算内陆水体富营养化程度的可能性。首先利用地面水质监测数据计算武汉市某些湖泊监测点的“真实的”营养状态指数（包括综合营养状态指数和修正的Carlson营养状态指数）,同时,在事先经过辐射校正和几何校正的CBERS2图像上,以9×9像元为采样窗口,提取各个对应地点的灰度值均值（从波段1至波段4）;然后,采用多元逐步回归分析,以各波段灰度值均值为自变量,建立营养状态指数经验遥感反演模型;最后,利用模型对整个湖泊水体的营养化状态指数进行反演,并绘制了其空间分布图。 结果显示,营养状态指数的自然对数值与CBERS2图像各波段灰度值之间存在较好相关关系,回归系数平方值(R²)为0.51。利用反演模型反演得到的湖区水质分布与实际情况基本相符。由于CBERS2图像数据可以从我国许多数据分发中心免费获取,这为低成本的水质遥感监测提供了一条途径。     

基于CA-Markov模型的艾比湖流域平原区景观格局动态模拟预测

利用“3S”技术及CA-Markov模型,按照是否实施跨流域调水工程2种预案情况,以2005年为起始时刻,对新疆艾比湖流域平原区2020年景观格局进行模拟预测。结果显示：在调水工程未实施的情况下,2020年研究区的生态环境将进一步恶化,其突出表现为艾比湖湖泊水面将持续萎缩、裸露湖底盐漠面积进一步扩大,水资源短缺及生态环境恶化的结果将严重制约研究区社会经济的发展;在调水工程实施的情况下,2020年研究区内艾比湖湖泊水面将稳定增加至800 km^2以上、裸露湖底盐漠面积相应有所减少,生态环境恶化趋势得到改善,区域水资源短缺问题将有所缓解,可有效地促进研究区内社会经济的发展。     

洪泽湖湿地生态系统保护与修复关键技术研究

分析了洪泽湖湿地生态系统属性及其在南水北调工程实施后的演变趋势,利用野外实验研究,在生境改变条件下,适用于不同湿地退化状况的人工辅助恢复技术;在实验监测的基础上,对洪泽湖几种典型湿地生态系统的生态功能进行了定量评价,为生态恢复工程的设计提供必要的技术支持。     

典型湖泊水华特征及相关影响因素分析

通过2011-2015年对太湖、巢湖和滇池水华高发季节的连续监测,以藻类密度和水华面积为判据评价了3个湖体的水华情况及变化趋势,探讨了水华发生的主要影响因素。结果表明：太湖水华程度以"轻度水华"为主,巢湖水华程度以"轻微水华"为主,滇池水华程度以"中度水华"为主;太湖、巢湖和滇池水华规模均以"零星性水华"为主;太湖和巢湖藻类密度与水温、pH、溶解氧、总氮、总磷和高锰酸盐指数均呈显著正相关,与透明度呈显著负相关,与氨氮无显著相关性;滇池藻类密度与水温、总磷和高锰酸盐指数均呈显著正相关,与透明度和氨氮呈显著负相关,与pH、溶解氧和总氮无显著相关性。     

滇池浮游藻类群落构成调查

对滇池浮游藻类群落组成和空间分布开展了2次调查,鉴定出藻类8门66属159种及变种,绿藻种类最多,蓝藻次之。5、12月滇池全湖平均藻类密度分别为1.398×108、2.180×108个/升,蓝藻门微囊藻属为优势藻类。5月的调查中滇池外海藻类生物量呈北高南低的格局,而12月则呈现南部和中部高,北部低。外海的藻类生物量明显高于草海,草海藻类群落构成与外海明显不同,主要表现为绿藻门藻类所占比例较高。12月滇池外海及全湖藻类生物量都显著高于5月。与上一次(2006—2007年)滇池浮游藻类的系统调查相比,滇池(主要是外海)浮游藻类在物种数量、常见藻类、优势藻类及生物量水平方面与之接近。     

射阳湖浮游动物群落结构特征及其与环境因子相关性研究

2016—2017年对射阳湖开展浮游动物群落结构和水质指标逐月监测。结果表明,射阳湖共鉴定出浮游动物61种,其中原生动物、轮虫、枝角类和桡足类分别为25种、24种、7种和5种。浮游动物种类数呈现春夏季多于秋冬季的变化趋势。浮游动物优势种数量较多、分布广,群落结构相对复杂且稳定。运用Shannon-Wiener指数、均匀度指数和B/T指数对射阳湖水质作评价,结果表明,该湖处于轻度—中度污染状态,生物学指标评价法与常规水质评价结果一致。浮游动物群落结构与水质指标相关性分析表明,水温、透明度、Chl-a和DO是影响射阳湖浮游动物群落结构的主要水质指标。