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.     

A global assessment of chromium pollution using sperm whales (Physeter macrocephalus) as an indicator species

Chromium (Cr) is a well-known human carcinogen and a potential reproductive toxicant, but its contribution to ocean pollution is poorly understood. The aim of this study was to provide a global baseline for Cr as a marine pollutant using the sperm whale (Physeter macrocephalus) as an indicator species. Biopsies were collected from free-ranging whales around the globe during the voyage of the research vessel The Odyssey. Total Cr levels were measured in 361 sperm whales collected from 16 regions around the globe detectable levels ranged from 0.9 to 122.6 μg Cr g tissue⁻¹ with a global mean of 8.8 ± 0.9 μg g⁻¹. Two whales had undetectable levels. The highest levels were found in sperm whales sampled in the waters near the Islands of Kiribati in the Pacific (mean = 44.3 ± 14.4) and the Seychelles in the Indian Ocean (mean = 19.5 ± 5.4 μg g⁻¹). The lowest mean levels were found in whales near the Canary Islands (mean = 3.7 ± 0.8 μg g⁻¹) and off of the coast of Sri Lanka (mean = 3.3 ± 0.4 μg g⁻¹). The global mean Cr level in whale skin was 28-times higher than mean Cr skin levels in humans without occupational exposure. The whale levels were more similar to levels only observed previously in human lung tissue from workers who died of Cr-induced lung cancer. We conclude that Cr pollution in the marine environment is significant and that further study is urgently needed.     

Monitoring household waste recycling centres performance using mean bin weight analyses

This paper describes a modelling approach used to investigate the significance of key factors (vehicle type, compaction type, site design, temporal effects) in influencing the variability in observed nett amenity bin weights produced by household waste recycling centres (HWRCs). This new method can help to quickly identify sites that are producing significantly lighter bins, enabling detailed back-end analyses to be efficiently targeted and best practice in HWRC operation identified. Tested on weigh ticket data from nine HWRCs across West Sussex, UK, the model suggests that compaction technique, vehicle type, month and site design explained 76% of the variability in the observed nett amenity weights. For each factor, a weighting coefficient was calculated to generate a predicted nett weight for each bin transaction and three sites were subsequently identified as having similar characteristics but returned significantly different mean nett bin weights. Waste and site audits were then conducted at the three sites to try and determine the possible sources of the remaining variability. Significant differences were identified in the proportions of contained waste (bagged), wood, and dry recyclables entering the amenity waste stream, particularly at one site where significantly less contaminated waste and dry recyclables were observed.     

Research priorities for managing the impacts and dependencies of business upon food,energy, water and the environment

Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the ‘nexus’ of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.     

Green Toxicology: a strategy for sustainable chemical and material development

Green Toxicology refers to the application of predictive toxicology in the sustainable development and production of new less harmful materials and chemicals, subsequently reducing waste and exposure. Built upon the foundation of “Green Chemistry” and “Green Engineering”, “Green Toxicology” aims to shape future manufacturing processes and safe synthesis of chemicals in terms of environmental and human health impacts. Being an integral part of Green Chemistry, the principles of Green Toxicology amplify the role of health-related aspects for the benefit of consumers and the environment, in addition to being economical for manufacturing companies. Due to the costly development and preparation of new materials and chemicals for market entry, it is no longer practical to ignore the safety and environmental status of new products during product development stages. However, this is only possible if toxicologists and chemists work together early on in the development of materials and chemicals to utilize safe design strategies and innovative in vitro and in silico tools. This paper discusses some of the most relevant aspects, advances and limitations of the emergence of Green Toxicology from the perspective of different industry and research groups. The integration of new testing methods and strategies in product development, testing and regulation stages are presented with examples of the application of in silico, omics and in vitro methods. Other tools for Green Toxicology, including the reduction of animal testing, alternative test methods, and read-across approaches are also discussed.     

Activated carbon amendment to sequester PAHs in contaminated soil: a lysimeter field trial

Activated carbon (AC) amendment is an innovative method for the in situ remediation of contaminated soils. A field-scale AC amendment of either 2% powder or granular AC (PAC and GAC) to a PAH contaminated soil was carried out in Norway. The PAH concentration in drainage water from the field plot was measured with a direct solvent extraction and by deploying polyoxymethylene (POM) passive samplers. In addition, POM samplers were dug directly in the AC amended and unamended soil in order to monitor the reduction in free aqueous PAH concentrations in the soil pore water. The total PAH concentration in the drainage water, measured by direct solvent extraction of the water, was reduced by 14% for the PAC amendment and by 59% for GAC, 12 months after amendment. Measurements carried out with POM showed a reduction of 93% for PAC and 56% for GAC. The free aqueous PAH concentration in soil pore water was reduced 93% and 76%, 17 and 28 months after PAC amendment, compared to 84% and 69% for GAC. PAC, in contrast to GAC, was more effective for reducing freely dissolved concentrations than total dissolved ones. This could tentatively be explained by leaching of microscopic AC particles from PAC. Secondary chemical effects of the AC amendment were monitored by considering concentration changes in dissolved organic carbon (DOC) and nutrients. DOC was bound by AC, while the concentrations of nutrients (NO(3), NO(2), NH(4), PO(4), P-total, K, Ca and Mg) were variable and likely affected by external environmental factors.     

Particles in swimming pool filters--does pH determine the DBP formation?

The formation was investigated for different groups of disinfection byproducts (DBPs) during chlorination of filter particles from swimming pools at different pH-values and the toxicity was estimated. Specifically, the formation of the DBP group trihalomethanes (THMs), which is regulated in many countries, and the non-regulated haloacetic acids (HAAs) and haloacetonitriles (HANs) were investigated at 6.0≤pH≤8.0, under controlled chlorination conditions. The investigated particles were collected from a hot tub with a drum micro filter. In two series of experiments with either constant initial active or initial free chlorine concentrations the particles were chlorinated at different pH-values in the relevant range for swimming pools. THM and HAA formations were reduced by decreasing pH while HAN formation increased with decreasing pH. Based on the organic content the relative DBP formation from the particles was higher than previously reported for body fluid analogue and filling water. The genotoxicity and cytotoxicity estimated from formation of DBPs from the treated particle suspension increased with decreasing pH. Among the quantified DBP groups the HANs were responsible for the majority of the toxicity from the measured DBPs.     

Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China

In densely populated countries like China, clean water is one of the most challenging issues of prospective politics and environmental planning. Water pollution and eutrophication by excessive input of nitrogen and phosphorous from nonpoint sources is mostly linked to soil erosion from agricultural land. In order to prevent such water pollution by diffuse matter fluxes, knowledge about the extent of soil loss and the spatial distribution of hot spots of soil erosion is essential. In remote areas such as the mountainous regions of the upper and middle reaches of the Yangtze River, rainfall data are scarce. Since rainfall erosivity is one of the key factors in soil erosion modeling, e.g., expressed as R factor in the Revised Universal Soil Loss Equation model, a methodology is needed to spatially determine rainfall erosivity. Our study aims at the approximation and spatial regionalization of rainfall erosivity from sparse data in the large (3,200 km²) and strongly mountainous catchment of the Xiangxi River, a first order tributary to the Yangtze River close to the Three Gorges Dam. As data on rainfall were only obtainable in daily records for one climate station in the central part of the catchment and five stations in its surrounding area, we approximated rainfall erosivity as R factors using regression analysis combined with elevation bands derived from a digital elevation model. The mean annual R factor (R _a) amounts for approximately 5,222 MJ?mm?ha^?1?h^?1?a^?1. With increasing altitudes, R _a rises up to maximum 7,547 MJ?mm ha^?1?h^?1 a^?1 at an altitude of 3,078 m a.s.l. At the outlet of the Xiangxi catchment erosivity is at minimum with approximate R _a?=?1,986 MJ?mm?ha^?1?h^?1?a^?1. The comparison of our results with R factors from high-resolution measurements at comparable study sites close to the Xiangxi catchment shows good consistance and allows us to calculate grid-based R _a as input for a spatially high-resolution and area-specific assessment of soil erosion risk.     

Characterization of organic chemical contaminants in sediments from Jobos Bay, Puerto Rico

Jobos Bay, located on the southeastern coast of Puerto Rico, contains a variety of habitats including mangroves, seagrass meadows, and coral reefs. The watershed surrounding the bay includes a number of towns, agricultural areas, and the Jobos Bay National Estuarine Research Reserve (NERR). Jobos Bay and the surrounding watershed are part of a Conservation Effects Assessment Project (CEAP), involving the Jobos Bay NERR, the US Department of Agriculture, and the National Oceanic and Atmospheric Administration (NOAA) to assess the benefits of agricultural best management practices (BMPs) on the terrestrial and marine environments. As part of the Jobos Bay CEAP, NOAA collected sediment samples in May 2008 to characterize over 130 organic chemical contaminants. This paper presents the results of the organic contaminant analysis. The organic contaminants detected in the sediments included polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls, and the pesticide DDT. PAHs at one site in the inner bay near a boat yard were significantly elevated; however, all organic contaminant classes measured were below NOAA sediment quality guidelines that would have indicated that impacts were likely. The results of this work provide an important baseline assessment of the marine environment that will assist in understanding the benefits of implementing BMPs on water quality in Jobos Bay.