* e-mail: antonio.diguardo@uninsubria.it European environmental scenarios of chemical bioavailability in freshwater systems Melissa Morselli1, Giuseppe Morabito2, Paul Van den Brink3, Frederik De Laender4, and Antonio Di Guardo1 * 1 Department of Science and High Technology, University of Insubria, Como, Italy 2 National Research Council, Institute for Ecosystem Study, Verbania-Pallanza, Italy 3 Wageningen Environmental Research (Alterra), Wageningen, The Netherlands 4 Department of Aquatic Ecology and Water Quality Management, Wageningen University, The Netherlands 5 University of Namur, Research Unit in Environmental and Evolutionary Ecology, Belgium * e-mail: antonio.diguardo@uninsubria.it SETAC Brussels, May 11th, 2017

Presentation outline 1. Framework and objectives 2. Exposure model: ChimERA fate  Model background  Improvement (phytoplankton, detritus and DOM dynamics) 3. Scenario development 4. Results  Scenario description  Bioavailable concentrations in the different scenarios 5. Conclusions and ongoing work

Models Environmental Risk Assessment Framework and objectives (1) Models Environmental Risk Assessment Many chemicals + ecosystem complexity  simple standardized models Exposure  Steady-state models  Constant chemical emissions  Static scenarios (no environmental-ecological dynamics) Simplicity, low amount of input data Lack of ecological realism and relevance Optimize this slide to drive the reader (maybe integrate slide 3 and 4) Among the new challenges for ERA: more dynamic and realistic models and scenarios…

Framework and objectives (2) Evidences General lack of data concerning environmental/ecological dynamics Issues Sampling campaigns to produce data with high temporal and spatial resolution are often expensive and difficult to carry out Variability of exposure concentrations (environmental heterogeneity) Importance of including temporal dynamics of biomass and organic phases in models and scenarios 5 realistic environmental scenarios for shallow water bodies representative of different European conditions Temporal profiles of water temperature + autochthonous phytoplankton biomass, detritus and dissolved organic matter Optimize this slide to drive the reader (maybe integrate slide 3 and 4)

Exposure model: ChimERA fate (1) Chemical emission Det DOM Contaminatedsediment Background * Model unit Compartments/sub-compartments: water, sediment, detritus, dissolved organic matter (DOM), macrophytes Layered sediment Output: hourly chemical concentrations in all compartments + chemical fluxes * Morselli et al. (2015) Sci Total Environ 526, 338-345

Exposure model: ChimERA fate (2) Background * Spatialization Chemical emission Simplified pond (side view) Optional, simply shows spatialization * Morselli et al. (2015) Sci Total Environ 526, 338-345

Exposure model: ChimERA fate (3) Improvements * Chemical emission Det DOM Contaminatedsediment Mention model evaluation for phytoplankton Phytoplankton compartment included (exchanging chemical with water) ** Ordinary differential equations (ODEs) included to calculate temporal profiles of phytoplankton biomass, detritus and dissolved organic matter (DOM) concentrations * Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246 ** Del Vento and Dachs (2002) Environ Toxicol Chem 21(10), 2099-2107

Exposure model: ChimERA fate (4) Improvements * ODEs Phyto ** Det ** Solved simultaneously with chemical mass balance (5th-order accurate, diagonally implicit Runge-Kutta with adaptive time stepping) Brief overview of equations, without going into details DOM *** * Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246 ** De Laender et al. (2015) Environ Int 74, 181-190 *** De Laender et al. (2008) Chemosphere 71, 529-545

Scenario development (1) 5 realistic scenarios for meso-eutrophic, lowland, shallow water bodies located at different latitudes Temporal (annual) profiles of water temperature, phytoplankton biomass, detritus and DOM concentration Data from a reference water body + ODE parameterization Scandinavia UK Central Europe Northern Italy Mediterranean

Scenario development (2) Ref. water body Lake Candia Piedmont Region, Northern Italy Meso-eutrophic small (1.26 km2) and shallow lake (avg. depth 4.7 m) Data available for all the parameters of interest Measurements performed at least on a monthly basis for years

Results: scenario description Temperature Detritus 30 0.7 25 0.6 0.5 20 T (°C) 0.4 15 Detritus (mg C L-1) 0.3 10 0.2 5 0.1 Phytoplankton DOC 8 4 7 3.5 6 3 5 2.5 Biomass (mg w.w. L-1) 4 DOC (mg C L-1) 2 3 1.5 2 1 1 0.5 J F M A M J J A S O N D J F M A M J J A S O N D Mediterranean Northern Italy Central Europe UK Scandinavia Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246

Results: bioavailable concentrations PCB52 1.6E-02 1.2E-02 Conc. (ng L-1) 8.0E-03 4.0E-03 log KOW PCB52 6.1 PCB153 6.9 PCB208 8.16 0.0E+00 PCB153 1.6E-02 1.2E-02 Conc. (ng L-1) 8.0E-03 4.0E-03 0.0E+00 PCB208 5.0E-03 4.0E-03 3.0E-03 Conc. (ng L-1) 2.0E-03 1.0E-03 0.0E+00 J F M A M J J A S O N D Mediterranean Northern Italy Central Europe UK Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246 Scandinavia

Results: exposure variability vs. log KOW Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246

Results: depleting capacity of scenarios % depletion Predicted depletion (%) with respect to maximum concentrations as a function of log KOW and POC concentration (mg/L) for two scenarios Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246

Conclusions (1) Phytoplankton European scenarios Exposure variations Graphical abstract of the paper... Speaks by itself Di Guardo et al. (2017) Sci Total Environ 580, 1237-1246

Conclusions (2) ChimERA fate: useful tool for predicting exposure dynamics in shallow water environments (now includes primary producers and carbon dynamics) Dynamic realistic scenarios for meso-eutrophic shallow water bodies developed → investigation of potential exposure variations at different latitudes Future work Sensitivity and uncertainty analyses Calibration and validation (literature + experiments) Scenario improvement, e.g., considering allochthonous carbon Related work Coupling between ChimERA fate and effect models (TK/TD-IBM sub- models)

Thanks for your attention Acknowledgements The ChimERA project was financed by the Long-range Initiative of CEFIC (www.cefic-lri.org) (project code: LRI-ECO19) Thanks for your attention