Elucidating the Behavior of Cyclic Volatile Methylsiloxanes in a Subarctic Freshwater Food Web: A Modeled and Measured Approach.

Cyclic volatile methylsiloxanes (cVMS) are used in personal care products and emitted to aquatic environments through wastewater effluents, and their bioaccumulation potential is debated. Here, a new bentho-pelagic version of the ACC-HUMAN model was evaluated for polychlorinated biphenyls (PCBs) and applied to cVMS in combination with measurements to explore their bioaccumulation behavior in a subarctic lake. Predictions agreed better with measured PCB concentrations in Arctic char (Salvelinus alpinus) and brown trout (Salmo trutta) when the benthic link was included than in the pelagic-only model. Measured concentrations of decamethylcyclopentasiloxane (D5) were 60 ± 1.2 (Chironomidae larvae), 107 ± 4.5 (pea clams Pisidium sp.), 131 ± 105 (three-spined sticklebacks: Gasterosteus aculeatus), 41 ± 38 (char), and 9.9 ± 5.9 (trout) ng g-1 wet weight. Concentrations were lower for octamethylcyclotetrasiloxane (D4) and dodecamethylcyclohexasiloxane (D6), and none of the cVMS displayed trophic magnification. Predicted cVMS concentrations were lower than measured in benthos, but agreed well with measurements in fish. cVMS removal through ventilation was an important predicted loss mechanism for the benthic-feeding fish. Predictions were highly sensitive to the partition coefficient between organic carbon and water (KOC) and its temperature dependence, as this controlled bioavailability for benthos (the main source of cVMS for fish).

Eutrophication Increases Phytoplankton Methylmercury Concentrations in a Coastal Sea-A Baltic Sea Case Study.

Eutrophication is expanding worldwide, but its implication for production and bioaccumulation of neurotoxic monomethylmercury (MeHg) is unknown. We developed a mercury (Hg) biogeochemical model for the Baltic Sea and used it to investigate the impact of eutrophication on phytoplankton MeHg concentrations. For model evaluation, we measured total methylated Hg (MeHgT) in the Baltic Sea and found low concentrations (39 ± 16 fM) above the halocline and high concentrations in anoxic waters (1249 ± 369 fM). To close the Baltic Sea MeHgT budget, we inferred an average normoxic water column HgII methylation rate constant of 2 × 10-4 d-1. We used the model to compare Baltic Sea's present-day (2005-2014) eutrophic state to an oligo/mesotrophic scenario. Eutrophication increases primary production and export of organic matter and associated Hg to the sediment effectively removing Hg from the active biogeochemical cycle; this results in a 27% lower present-day water column Hg reservoir. However, increase in organic matter production and remineralization stimulates microbial Hg methylation resulting in a seasonal increase in both water and phytoplankton MeHg reservoirs above the halocline. Previous studies of systems dominated by external MeHg sources or benthic production found eutrophication to decrease MeHg levels in plankton. This Baltic Sea study shows that in systems with MeHg production in the normoxic water column eutrophication can increase phytoplankton MeHg content.

Micropollutants in urban wastewater: large-scale emission estimates and analysis of measured concentrations in the Baltic Sea catchment.

Wastewater treatment plants (WWTPs) transmit many chemical contaminants to aquatic environments. Quantitative data on micropollutant emissions via WWTPs are needed for environmental risk assessments and evaluation of mitigation measures. This study compiled published data on substances analysed in effluents from WWTPs in the Baltic Sea region, assessed country related differences in the data sets and estimated micropollutant inputs to the Baltic Sea catchment. Concentration data were found for 1090 substances analysed at 650 WWTPs. Heterogeneity and low number of data points for most substances hindered adequate comparisons of country specific concentrations. Emission estimates were made for the 280 substances analysed in at least five WWTPs in years 2010 to 2019. For selected substances, mass loads were compared to previously published estimations. The study provides data useful for national and Baltic Sea-scale pressure analysis and risk assessments. However, it also highlights the need for broad scope monitoring of micropollutants in wastewater.

Assessing model uncertainty of bioaccumulation models by combining chemical space visualization with a process-based diagnostic approach.

As models describing human exposure to organic chemicals gain wider use in chemical risk assessment and management, it becomes important to understand their uncertainty. Although evaluation of parameter sensitivity/uncertainty is increasingly common, model uncertainty is rarely assessed. When it is, the assessment is generally limited to a handful of chemicals. In this study, a strategy for more comprehensive model uncertainty assessment was developed. A regulatory model (EUSES) was compared with a research model based on more recent science. Predicted human intake was used as the model end point. Chemical space visualization techniques showed that the extent of disagreement between the models varied strongly with chemical partitioning properties. For each region of disagreement, the primary human exposure vector was determined. The differences between the models' process algorithms describing these exposure vectors were identified and evaluated. The equilibrium assumption for root crops in EUSES caused overestimations in daily intake of superhydrophobic chemicals (log K(OW) > 11, log K(OA) > 10), whereas EUSES's approach to calculating bioaccumulation in fish prey resulted in underestimations for hydrophobic compounds (log K(OW) ∼ 6-8). Uptake of hydrophilic chemicals from soil and bioaccumulation of superhydrophobic chemicals in zooplankton were identified as important research areas to enable further reduction of model uncertainty in bioaccumulation models.

Susceptibility of human populations to environmental exposure to organic contaminants.

Environmental exposure to organic contaminants is a complex function of environmental conditions, food chain characteristics, and chemical properties. In this study the susceptibility of various human populations to environmental exposure to neutral organic contaminants was compared. An environmental fate model and a linked bioaccumulation model were parametrized to describe ecosystems in different climatic regions (temperate, arctic, tropical, and steppe). The human body burden resulting from constant emissions of hypothetical chemicals was estimated for each region. An exposure susceptibility index was defined as the body burden in the region of interest normalized to the burden of the same chemical in a reference human from the temperate region eating an average diet. For most persistent chemicals emitted to air, the Arctic had the highest susceptibility index (max 520). Susceptibility to exposure was largely determined by the food web properties. The properties of the physical environment only had a marked effect when air or water, not food, was the dominant source of human exposure. Shifting the mode of emission markedly changed the relative susceptibility of the ecosystems in some cases. The exposure arising from chemical use clearly varies between ecosystems, which makes an understanding of ecosystem susceptibility to exposure important for chemicals management.

Predicting global scale exposure of humans to PCB 153 from historical emissions.

Predicting human exposure to an environmental contaminant based on its emissions is one of the great challenges of environmental chemistry. It has been done successfully on a local or regional scale for some persistent organic pollutants. Here we assess whether it can be done at a global scale, using PCB 153 as a test chemical. The global multimedia fate model BETR Global and the human exposure model ACC-HUMAN were employed to predict the concentration of PCB 153 in human milk for 56 countries around the world from a global historical emissions scenario. The modeled concentrations were compared with measurements in pooled human milk samples from the UNEP/WHO Global Monitoring Plan. The modeled and measured concentrations were highly correlated (r = 0.76, p < 0.0001), and the concentrations were predicted within a factor of 4 for 49 of 78 observations. Modeled concentrations of PCB 153 in human milk were higher than measurements for some European countries, which may reflect weaknesses in the assumptions made for food sourcing and an underestimation of the rate of decrease of concentrations in air during the last decades. Conversely, modeled concentrations were lower than measurements in West African countries, and more work is needed to characterize exposure vectors in this region.

High-throughput evaluation of organic contaminant removal efficiency in a wastewater treatment plant using direct injection UHPLC-Orbitrap-MS/MS.

The removal efficiency (RE) of organic contaminants in wastewater treatment plants (WWTPs) is a major determinant of the environmental impact of these contaminants. However, RE data are available for only a few chemicals due to the time and cost required for conventional target analysis. In the present study, we applied non-target screening analysis to evaluate the RE of polar contaminants, by analyzing influent and effluent samples from a Swedish WWTP with direct injection UHPLC-Orbitrap-MS/MS. Matrix effects were evaluated by spiking the samples with isotope-labeled standards of 40 polar contaminants. For 85% of the compounds, the matrix effects in the influent and effluent were not significantly different. Approximately 10 000 compounds were detected in the wastewater, of which 319 were identified by using the online database mzCloud. Level 1 identification confidence was achieved for 31 compounds for which we had reference standards, and level 2 was achieved for the remainder. RE was calculated from the ratio of the peak areas in the influent and the effluent from the non-target analysis. Good agreement was found with RE determined from the target analysis of the target compounds. The method generated reliable estimates of RE for large numbers of contaminants with comparatively low effort and is foreseen to be particularly useful in applications where information on a large number of chemicals is needed.

Evaluating the consumption of chemical products and articles as proxies for diffuse emissions to the environment.

In this study we have evaluated the use of consumption of manufactured products (chemical products and articles) in the EU as proxies for diffuse emissions of chemicals to the environment. The content of chemical products is relatively well known. However, the content of articles (products defined by their shape rather than their composition) is less known and currently has to be estimated from chemicals that are known to occur in a small set of materials, such as plastics, that are part of the articles. Using trade and production data from Eurostat in combination with product composition data from a database on chemical content in materials (the Commodity Guide), we were able to calculate trends in the apparent consumption and in-use stocks for 768 chemicals in the EU for the period 2003-2016. The results showed that changes in the apparent consumption of these chemicals over time are smaller than in the consumption of corresponding products in which the chemicals are present. In general, our results suggest that little change in chemical consumption has occurred over the timespan studied, partly due to the financial crisis in 2008 which led to a sudden drop in the consumption, and partly due to the fact that each of the chemicals studied is present in a wide variety of products. Estimated in-use stocks of chemicals show an increasing trend over time, indicating that the mass of chemicals in articles in the EU, that could potentially be released to the environment, is increasing. The quantitative results from this study are associated with large uncertainties due to limitations of the available data. These limitations are highlighted in this study and further underline the current lack of transparency on chemicals in articles. Recommendations on how to address these limitations are also discussed.

In situ benthic flow-through chambers to determine sediment-to-water fluxes of legacy hydrophobic organic contaminants.

Contaminated sediment can release hydrophobic organic contaminants (HOCs) and thereby act as a secondary source of primarily legacy hazardous substances to the water column. There is therefore a need for assessments of the release of HOCs from contaminated sediment for prioritization of management actions. In situ assessment of HOC sediment-to-water flux is currently done with (closed) benthic flux chambers, which have a sampling time exceeding one month. During this time, the water inside the chamber is depleted of oxygen and the effect of bioturbation on the sediment-to-water release of HOCs is largely ignored. Here we present a novel benthic flux chamber, which measures sediment-to-water flux of legacy HOCs within days, and includes the effect of bioturbation since ambient oxygen levels inside the chamber are maintained by continuous pumping of water through the chamber. This chamber design allows for sediment-to-water flux measurements under more natural conditions. The chamber design was tested in a contaminated Baltic Sea bay. Measured fluxes were 62-2300 ng m-2 d-1 for individual polycyclic aromatic hydrocarbons (PAHs), and 5.5-150 ng m-2 d-1 for polychlorinated biphenyls (PCBs). These fluxes were 3-23 times (PAHs) and 12-74 times (PCBs) higher than fluxes measured with closed benthic chambers deployed in parallel at the same location. We hypothesize that the observed difference in HOC flux between the two chamber designs are partly an effect of bioturbation. This hypothesized effect of bioturbation was in accordance with literature data from experimental studies.

Application of a novel modeling tool with multistressor functionality to support management of organic contaminants in the Baltic Sea.

Organic contaminants constitute one of many stressors that deteriorate the ecological status of the Baltic Sea. When managing environmental problems in this marine environment, it may be necessary to consider the interactions between various stressors to ensure that averting one problem does not exacerbate another. A novel modeling tool, BALTSEM-POP, is presented here that simulates interactions between climate forcing, hydrodynamic conditions, and water exchange, biogeochemical cycling, and organic contaminant transport and fate in the Baltic Sea. We discuss opportunities to use the model to support different aspects of chemicals management. We exemplify these opportunities with a case study where two emission-reduction strategies for a chemical used in personal care products (decamethylcyclopentasiloxane) are evaluated, and where the confounding influence of future climate change and eutrophication on the impact of the emission-reduction strategies are assessed.

Modeling bioaccumulation in humans using poly-parameter linear free energy relationships (PPLFERS).

Chemical partition coefficients between environmental media and biological tissues are a key component of bioaccumulation models. The single-parameter linear free energy relationships (spLFERs) commonly used for predicting partitioning are often derived using apolar chemicals and may not accurately capture polar chemicals. In this study, a poly-parameter LFER (ppLFER) based model of organic chemical bioaccumulation in humans is presented. Chemical partitioning was described by an air-body partition coefficient that was a volume weighted average of ppLFER based partition coefficients for the major organs and tissues constituting the human body. This model was compared to a spLFER model treating the body as a mixture of lipid (≈ octanol) and water. Although model agreement was good for hydrophobic chemicals (average difference 15% for log K(OW)>4 and log K(OA)>8), the ppLFER model predicted ~90% lower body burdens for hydrophilic chemicals (log K(OW)<0). This was mainly due to lower predictions of muscle and adipose tissue sorption capacity for these chemicals. A comparison of the predicted muscle and adipose tissue sorption capacities of hydrophilic chemicals with measurements indicated that the ppLFER and spLFER models' uncertainties were similar. Consequently, little benefit from the implementation of ppLFERs in this model was identified.

Evaluation of a novel high throughput screening tool for relative emissions of industrial chemicals used in chemical products.

Tens of thousands of chemicals are currently marketed worldwide, but only a small number of these compounds has been measured in effluents or the environment to date. The need for screening methodologies to select candidates for environmental monitoring is therefore significant. To meet this need, the Swedish Chemicals Agency developed the Exposure Index (EI), a model for ranking emissions to a number of environmental matrices based on chemical quantity used and use pattern. Here we evaluate the EI. Data on measured concentrations of organic chemicals in sewage treatment plants, one of the recipients considered in the EI model, were compiled from the literature, and the correlation between predicted emission levels and observed concentrations was assessed by linear regression analysis. The adequacy of the parameters employed in the EI was further explored by calibration of the model to measured concentrations. The EI was found to be of limited use for ranking contaminant levels in STPs; the r² values for the regressions between predicted and observed values ranged from 0.02 (p = 0.243) to 0.14 (p = 0.007) depending on the dataset. The calibrated version of the model produced only slightly better predictions although it was fitted to the experimental data. However, the model is a valuable first step in developing a high throughput screening tool for organic contaminants, and there is potential for improving the EI algorithm.

Addressing temporal variability when modeling bioaccumulation in plants.

Steady state models are commonly used to predict bioaccumulation of organic contaminants in biota. However, the steady state assumption may introduce errors when complex dynamic processes such as growth, temperature fluctuations, and variable environmental concentrations significantly affect the major chemical uptake and elimination processes. In this study, a strategy for addressing temporal variability in bioaccumulation modeling is proposed. Chemical partitioning space plots are used to show the time necessary for organic contaminants to approach steady state in plant leaves and roots as well as the dominant uptake/elimination fluxes of chemicals as a function of the contaminants' physical chemical properties. The plots were produced with a novel nonsteady state model of bioaccumulation in plants, which is presented, parameterized, and evaluated. The first prerequisite identified for using a steady state model is that the duration of chemical exposure exceeds the time to approach steady state. Next, the dominant chemical transport processes for the chemical in question should be identified and the variability of parameters affecting these processes compared to the time to approach steady state. A major systematic variation in one of these parameters on a time scale similar to the time to approach steady state may cause an unacceptable deviation between the predicted and true chemical concentrations in vegetation. In such cases a nonsteady state model such as the one presented here should be used. The chemical partitioning plots presented provide guidance for understanding the dominant uptake/elimination processes and the time to approach steady state in relation to the partitioning properties of organic compounds.