Accumulation and maternal transfer of polychlorinated biphenyls in Steller Sea Lions (Eumetopias jubatus) from Prince William Sound and the Bering Sea, Alaska

The western stock of the Steller sea lion (Eumetopias jubatus) in the northern Pacific Ocean has declined by approximately 80% over the past 30 years. This led to the listing of this sea lion population as an endangered species in 1997. Chemical pollution is a one of several contributing causes. In the present study, 145 individual PCBs were determined in tissues of male sea lions from Tatitlek (Prince William Sound) and St. Paul Island (Bering Sea), and placentae from the Aleutian Islands. PCBs 90/101, 118, and 153 were abundant in all the samples. The mean toxic equivalents (TEQ) were 2.6, 4.7 and 7.4 pg/g lw in the kidney, liver, and blubber samples, respectively. The mean TEQ in placentae was 8 pg/g lw. Total PCBs concentrations (2.6-7.9 μg/g lw) in livers of some males were within a range known to cause physiological effects. Further suggesting the possibility of adverse effects on this stock.     

Polybrominated diphenyl ethers (PBDEs) and indicator polychlorinated biphenyls (PCBs) in marine fish from four areas of China

The levels of polybrominated diphenyl ethers (PBDEs) and indicator polychlorinated biphenyls (PCBs) were determined in marine fish from four areas of China (South China Sea, Bohai Sea, East China Sea, and Yellow Sea) using GC/NCI-MS and GC/ITMS, respectively. Total concentrations of eight PBDEs (BDE-28, 47, 99, 100, 153, 154, 183 and 209) in all samples ranged from 0.3 ng g⁻¹ ww (wet weight) to 700 ng g⁻¹ ww, with median and mean values of 85 ng g⁻¹ ww and 200 ng g⁻¹ ww, respectively. BDE-209 and BDE-47 were the major congeners in all samples, contributing 54% and 19% to the total concentration, respectively. The sum of seven indicator PCB levels (CB-28, 52, 101, 118, 138, 153, and 180) ranged from 0.3 ng g⁻¹ ww to 3.1 μg g⁻¹ ww, with median and mean values of 6.4 ng g⁻¹ ww and 398 ng g⁻¹ ww, respectively. High contributions of CB-138 (32%) and CB-153 (25%) were found in all samples. In general, pollutants measured in this study were at high levels when compared with previous studies from other regions in the world. The relative abundance of BDE-209 may suggest that deca-BDE sources existed in studied area. And principal component analysis (PCA) showed that there were other PBDE sources in Yellow Sea. The pattern and PCA showed that PCB pollutions came from similar sources in the studied areas. In addition, concentrations of ∑₇PBDEs (u/209) were strongly correlated with those of ∑₇PCBs in all fish (r = 0.907, n = 44).     

Polychlorinated naphthalenes in human adipose tissue from New York, USA

Polychlorinated naphthalenes (PCNs) are persistent, bioaccumulative, and toxic contaminants. Prior to this study, the occurrence of PCNs in human adipose tissues from the USA has not been analyzed. Here, we have measured concentrations of PCNs in human adipose tissue samples collected in New York City during 2003-2005. Concentrations of PCNs were in the range of 61-2500 pg/g lipid wt. in males and 21-910 pg/g lipid wt. in females. PCN congeners 52/60 (1,2,3,5,7/1,2,4,6,7) and 66/67 (1,2,3,4,6,7/1,2,3,5,6,7) were predominant, collectively accounting for 66% of the total PCN concentrations. Concentrations of PCNs in human adipose tissues were 2-3 orders of magnitude lower than the previously reported concentrations of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs). Concentrations of PCNs were not correlated with PCB concentrations. The contribution of PCNs to dioxin-like toxic equivalents (TEQs) in human adipose tissues was estimated to be <1% of the polychlorinated dibenzo-p-dioxin/dibenzofuran (PCDD/F)-TEQs.     

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.     

热分解技术在修复多氯联苯污染土壤中的应用

针对我国土壤中PCBs的污染特点,介绍了一种修复土壤的热分解技术,并详述了该技术的工作流程、影响因素、处理效率等问题。最后对该技术的发展趋势进行了展望,并对其在推广过程中可能遇到的困难进行了分析。     

中日多氯联苯（PCBs）废弃物回收处置技术比较

自上世纪80年代伊始,我国含有多氯联苯的电力电容器等相继进入报废阶段,许多地区采用回收后山洞贮存、地下封存等方式处置,而其他处置方式在我国尚处于初级试验阶段。日本一些企业所采用的多氯联苯处置技术,值得我们学习和借鉴。     

官厅水库和永定河沉积物中多氯联苯和有机氯农药的污染

利用气相色谱-电子捕获检测(GC-ECD)方法对官厅水库-永定河流域沉积物中26种多氯联苯(PCBs)同系物和13种有机氯农药进行了分析测定,在4个采样点均检出多氯联苯和部分有机氯农药.其中PCBs和有机氯农药总量的最高点均出现在永定河下游的三家店,分别为9.7ng*g-1和26.7ng*g-1,按照国际关于沉积物质量的同类研究结果,判定为轻度污染水平.HCH最高仅为4.50ng*g-1,属轻度污染,DDT浓度以八号桥和三家店样点最高,分别为23.2ng*g-1和26.7ng*g-1,属中度污染.有机氯农药总量分布为三家店＞八号桥＞官厅大坝＞雁翅,表明永定河下游多氯联苯和有机氯农药不仅来自官厅上游,也来自下游地区.     

筛选试剂盒法在土壤多氯联苯检测中的应用

用筛选试剂盒法对5个场地土壤样品中的多氯联苯(PCBs)进行了快速筛选检测,并用气相色谱-质谱法对筛选结果进行了验证。结果表明,筛选试剂盒法的筛选结果准确,但是个别样品测试结果偏高,其原因可能是样品中其他含氯有机物的干扰所致。     

Monitoring and Assessment of Persistent Organochlorine Residues in Sediments from the Daliaohe River Watershed, Northeast of China

Surface sediment samples from 12 sites of the three selected rivers in Daliaohe River watershed (Hunhe River, Taizihe River and Daliaohe River) were analyzed with the objective of establishing sources and hazard of the organochlorinae pesticides (OCPs) and polychlorinated biphenyl (PCBs) in surface sediments. The total concentrations of OCPs varied from 3.06 to 23.24 ng g⁻¹. ∑HCH (α-HCH, β-HCH, δ-HCH, γ-HCH), ∑DDT (p, p′-DDE, p, p′-DDD, o, p′-DDT, p, p′-DDT) and ∑Cyclodiene (Heptachlor, Aldrin, Heptachlor epoxide, Dieldrin, Endrin) ranged from 1.86 to 21.48, 0.5 to 2.81 and 0.56 to 1.53 ng g⁻¹, respectively. Results of OCPs also illustrate that the most dominant pollutants among the OCPs was ∑HCH, and γ-HCH was the most dominant isomer in HCH, which was evidence of recent input of lindane. It possibly came from the runoff of polluted soils and long-scale transportation. Total PCB concentrations ranged between 1.88 and 16.88 ng g⁻¹. The peak concentrations of PCBs were found in sediments from station T5 and D3, which are in the vicinity of industrial areas and ferry, respectively. These data show a moderate level of OCPs and PCBs contaminations compared to that in other countries.     

北京大气沉降样品中的PCBs

采集了4个北京大气沉降样品,包括3个总沉降与1个湿沉降样品.利用高分辨率气质联用仪(HRGC-HRMS),参照国际标准方法分析测定了其中的多氯联苯(PCBs)含量.总沉降样品的PCBs含量水平为4.47～7.08ng·g-1(平均为5.52ng·g-1)和TEQ为0.55～5.43 pg·g-1(平均为2.27 pg·g-1).湿沉降样品含量水平为15.02 ng·g-1,其TEQ为2.87 pg·g-1.首钢样品的TEQ远高于其它3个样品.根据我国大气降尘数据,粗略估计北京PCBs大气沉降通量平均值为67.9 ng·m-2·m-1和TEQ平均通量为27.9 pg·m-2·m-1.首钢样品中,IUPAC编号为77的类二(噁)英PCBs含量异常高,但TEQ仍以编号为126的PCBs所占比例最高.随着取代氯原子数的增加,同族体的含量逐渐降低.