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Location, specific topography, and hydrographic setting together with climate change and strong anthropogenic pressure are the main factors shaping the biogeochemical functioning and thus also the ecological status of the Baltic Sea. The recent decades have brought significant changes in the Baltic Sea. First, the rising nutrient loads from land in the second half of the 20th century led to eutrophication and spreading of hypoxic and anoxic areas, for which permanent stratification of the water column and limited ventilation of deep-water layers made favourable conditions. Since the 1980s the nutrient loads to the Baltic Sea have been continuously decreasing. This, however, has so far not resulted in significant improvements in oxygen availability in the deep regions, which has revealed a slow response time of the system to the reduction of the land-derived nutrient loads. Responsible for that is the low burial efficiency of phosphorus at anoxic conditions and its remobilization from sediments when conditions change from oxic to anoxic. This results in a stoichiometric excess of phosphorus available for organic-matter production, which promotes the growth of N2-fixing cyanobacteria and in turn supports eutrophication. This assessment reviews the available and published knowledge on the biogeochemical functioning of the Baltic Sea. In its content, the paper covers the aspects related to changes in carbon, nitrogen, and phosphorus (C, N, and P) external loads, their transformations in the coastal zone, changes in organic-matter production (eutrophication) and remineralization (oxygen availability), and the role of sediments in burial and turnover of C, N, and P. In addition to that, this paper focuses also on changes in the marine CO2 system, the structure and functioning of the microbial community, and the role of contaminants for biogeochemical processes. This comprehensive assessment allowed also for identifying knowledge gaps and future research needs in the fi

Urban wastewater treatment plants are important collection points for many chemical contaminants, often called micropollutants, which are widespread in the aquatic environment. Currently, this issue is not being sufficiently addressed by regional policy and EU-wide legislation. The EU’s Zero Pollution Ambition, the Chemicals Strategy for Sustainability and the likely revision of the Urban Waste-water Treatment Directive now provide opportunities to address this issue. Measures to prevent the emissions of micropollutants via wastewater treatment plants are needed both up- and downstream, to ensure policy coherence between EU water and chemicals legislation.

Food webs are central entities mediating processes and external pressures in marine ecosystems. They are essential to understand and predict ecosystem dynamics and provision of ecosystem services. Paradoxically, utilization of food web knowledge in marine environmental conservation and resource management is limited. To better understand the use of knowledge and barriers to incorporation in management, we assess its application related to the management of eutrophication, chemical contamination, fish stocks, and non-indigenous species. We focus on the Baltic, a severely impacted, but also intensely studied and actively managed semi-enclosed sea. Our assessment shows food web processes playing a central role in all four areas, but application varies strongly, from formalized integration in management decisions, to support in selecting indicators and setting threshold values, to informal knowledge explaining ecosystem dynamics and management performance. Barriers for integration are complexity of involved ecological processes and that management frameworks are not designed to handle such information. We provide a categorization of the multi-faceted uses of food web knowledge and benefits of future incorporation in management, especially moving towards ecosystem-based approaches as guiding principle in present marine policies and directives. We close with perspectives on research needs to support this move considering global and regional change.

This report was written to support the update of the HELCOM Baltic Sea Action Plan (BSAP). The BSAP is a programme to restore good ecological status of the Baltic marine environment by 2021 and was adopted in 2007 by all the HELCOM Contracting Parties. The study addresses the thematic area “Hazardous substances”. It provides background information that is relevant in the process of evaluating the efficiency of currently implemented measures, and for suggesting additional measures, needed to achieve good environmental status in the Baltic Sea.

The report was written to support the update of the HELCOM Baltic Sea Action Plan (BSAP). The BSAP is a programme to restore good ecological status of the Baltic marine environment by 2021 and was adopted in 2007 by all the HELCOM Contracting Parties. The study addresses the thematic area “Hazardous substances”. It provides background information that is relevant in the process of evaluating the efficiency of currently implemented measures, and for suggesting additional measures, needed to achieve good environmental status in the Baltic Sea

This report was written to support the update of the HELCOM Baltic Sea Action Plan (BSAP). The BSAP is a programme to restore good ecological status of the Baltic marine environment by 2021 and was adopted in 2007 by all the HELCOM Contracting Parties. The study addresses the thematic area “Hazardous substances”. It provides background information that is relevant in the process of evaluating the efficiency of currently implemented measures, and for suggesting additional measures, needed to achieve good environmental status in the Baltic Sea.

This report was written to support the update of the HELCOM Baltic Sea Action Plan (BSAP). The BSAP is a programme to restore good ecological status of the Baltic marine environment by 2021 and was adopted in 2007 by all the HELCOM Contracting Parties. The study addresses the thematic area “Hazardous substances”. It provides background information that is relevant in the process of evaluating the efficiency of currently implemented measures, and for suggesting additional measures, needed to achieve good environmental status in the Baltic Sea.

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.

Human subpopulations experience different exposure to persistent organic pollutants (POPs) because of differences in the structure of their food webs and the extent of environmental contamination. Here we quantify the time-variant exposure of different human populations around the world to one representative POP, namely the polychlorinated biphenyl (PCB) congener 153, based on a dynamic simulation of both global environmental fate (using the model BETR-Global) and human food chain bioaccumulation (using the model ACC-HUMAN). The approach identifies subpopulations whose diets include a carnivorous mammal as experiencing the world's highest PCB-153 exposure, i.e. the very large biomagnification potential of their food web more than makes up for the remoteness of their living environment. However, for subpopulations that do not eat warm-blooded carnivores, the proximity to sources of PCBs is more important than food web structure and environmental conditions for differentiating their exposure to PCBs.

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 10000 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.

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.

The Baltic Sea is a semi-enclosed brackish sea in Northern Europe with a drainage basin four times larger than the sea itself. Riverine organic carbon (Particulate Organic Carbon, POC and Dissolved Organic Carbon, DOC) dominates carbon input to the Baltic Sea and influences both land-to-sea transport of nutrients and contaminants, and hence the functioning of the coastal ecosystem. The potential impact of future climate change on loads of POC and DOC in the Baltic Sea drainage basin (BSDB) was assessed using a hydrological-biogeochemical model (CSIM). The changes in annual and seasonal concentrations and loads of both POC and DOC by the end of this century were predicted using three climate change scenarios and compared to the current state. In all scenarios, overall increasing DOC loads, but unchanged POC loads, were projected in the north. In the southern part of the BSDB, predicted DOC loads were not significantly changing over time, although POC loads decreased in all scenarios. The magnitude and significance of the trends varied with scenario but the sign (+ or -) of the projected trends for the entire simulation period never conflicted. Results were discussed in detail for the middle CO2 emission scenario (business as usual, a1b). On an annual and entire drainage basin scale, the total POC load was projected to decrease by ca 7% under this scenario, mainly due to reduced riverine primary production in the southern parts of the BSDB. The average total DOC load was not predicted to change significantly between years 2010 and 2100 due to counteracting decreasing and increasing trends of DOC loads to the six major sub-basins in the Baltic Sea. However, predicted seasonal total loads of POC and DOC increased significantly by ca 46% and 30% in winter and decreased by 8% and 21% in summer over time, respectively. For POC the change in winter loads was a consequence of increasing soil erosion and a shift in duration of snowfall and onset of the spring flood impacting

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 (K-OC) and its temperature dependence, as this controlled bioavailability for benthos (the main source of cVMS for fish).

Eutrophication is expanding worldwide, but its implication forproduction and bioaccumulation of neurotoxic monomethylmercury (MeHg) isunknown. We developed a mercury (Hg) biogeochemical model for the Baltic Seaand 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 methylationrate constant of 2 × 10−4 d−1. We used the model to compare Baltic Sea’s presentday(2005−2014) eutrophic state to an oligo/mesotrophic scenario. Eutrophication increases primary production and export of organic matter and associated Hgto the sediment effectively removing Hg from the active biogeochemical cycle; thisresults in a 27% lower present-day water column Hg reservoir. However, increasein organic matter production and remineralization stimulates microbial Hgmethylation 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.

The largest input source of carbon to the Baltic Sea catchment is river discharge. A tool for modeling riverine particulate organic carbon (POC) loads on a catchment scale is currently lacking. The present study describes a novel dynamic model for simulating flows of POC in all major rivers draining the Baltic Sea catchment. The processes governing POC input and transport in rivers described in the model are soil erosion, in-stream primary production and litter input. The Baltic Sea drainage basin is divided into 82 sub-basins, each comprising several land classes (e.g. forest, cultivated land, urban areas) and parameterized using GIS data on soil characteristics and topography. Driving forces are temperature, precipitation, and total phosphorous concentrations. The model evaluation shows that the model can predict annual average POC concentrations within a factor of about 2, but generally fails to capture the timing of monthly peak loads. The total annual POC load to the Baltic Sea is estimated to be 0.34 Tg POC, which constitutes circa 7-10 % of the annual total organic carbon (TOC) load. The current lack of field measurements of POC in rivers hampers more accurate predictions of seasonality in POC loads to the Baltic Sea. This study, however, identifies important knowledge gaps and provides a starting point for further explorations of large scale POC mass flows.

The coupled physical-biogeochemical model BALTSEM, previously used to assess nutrient/carbon cycles and eutrophication in the Baltic Sea, has been expanded to include algorithms for calculations of organic contaminant environmental transport and fate. This novel model version (BALTSEM-POP) is evaluated for polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and hexachlorobenzene (HCB) in Baltic Sea surface water and sediment. Modeled dissolved concentrations are usually within a factor of 2-4 of observed concentrations, however with larger deviations for furans. Calculated concentrations in particulate organic matter are less accurate (within factors of 1-700), likely due to errors in estimated pelagic biomass, particulate matter-water partitioning, and large natural variability in field data. Concentrations in sediments are usually predicted within a factor of 6. The good performance of the model illustrates its usefulness for exploration of contaminant fate in response to variations in nutrient input and climatic conditions in the Baltic Sea marine environment., AuthorCount:3

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.

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 KOWN4 and log KOAN 8), the ppLFER model predicted ~90% lower body burdens for hydrophilic chemicals (log KOWb0). 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. 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.

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) similar to 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., authorCount :2

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 parameterized 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.

Thousands of chemicals are used in society, but the exposure to humans and other organisms has been measured only for a small number of compounds. Modeling tools constitute low-cost and effective alternatives to measurements for the assessment of exposure. In this thesis, the prerequisites for the application of modeling tools in environmental exposure assessment of organic pollutants were explored. The first aspect discussed was emission estimates, which are crucial for any quantitative modeling study. In Paper I, the only currently existing high throughput tool for ranking emissions was evaluated and found to have limited predictive power, suggesting that further research is necessary to enable exposure based screening. The second aspect was the model’s treatment of dynamic processes. A strategy for deciding on the temporal resolution required for the description of dynamic processes was proposed in Paper II, which involved identification of major transport routes and time to approach steady state. The third aspect was prediction of partition coefficients for use in bioaccumulation models. The traditional single parameter regressions (spLFER) employed for this purpose were compared to the more mechanistically sound ppLFER equations in Paper III. The two methods had a similar accuracy when compared to measured data, implying that the choice of approach should be based on other factors than methodology (e.g. availability of accurate input data). The fourth aspect was the influence of system characteristics on human exposure. The susceptibilities of several ecosystems with diverging characteristics to exposure to organic chemicals were compared in Paper IV. The strong variation in exposure susceptibilities found suggests that the choice of model system can be relevant for exposure assessment and that models may have to be tailored to the ecosystem of interest. In the broader context, this work provides methodologies for handling model complexity in exposure modeling., At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Submitted. Paper 3: Submitted.

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.