Foto: Andre Künzelmann SOLUTIONS for present and future emerging pollutants in land and water resources management - a European Collaborative Project Werner Brack, Rolf Altenburger, Dirk Bunke, Wibke Busch, Guy Engelen, Beate Escher, Bernd Gawlik, Martin Krauss, John Munthe, Peta Neale, Leo Posthuma, Tobias Schulze, Frank Sleeuwaert, Jaroslav Slobodnik, Jos van Gils, Annemarie van Wezel, and more than 100 scientists from 39 institutions Why to deal with chemicals? Foto: Andre Künzelmann • No good ecological status achieved in most European river basins (WFD) • Chemicals play a significant role for degradation • Priority pollutants often don‘t explain effects emerging pollutants? Foto: Werner Brack Page 2 Chemical space of known and 1060 possible chemicals <500 Da unknown compounds 108 chemicals in CAS 105 chemicals in daily use 104 chemicals in environmental samples Abundance TIC: WER046.D 1e+07 9500000 9000000 8500000 8000000 7500000 7000000 6500000 6000000 5500000 5000000 4500000 45 priority pollutants 4000000 3500000 3000000 (WFD) 2500000 2000000 1500000 1000000 500000 0 5.00 10.00 15.00 20.00 25.00 30.00 35.00 Time--> Page 3 We are dealing with complex mixtures rather than individual chemicals! http://www.nuffieldfoundation.org/practical-chemistry/mixtures-and-separation Many chemicals are emerging pollutants (pharmaceuticals, biocides, surfactants ….. ) • in daily use • not regulated, not systematically monitored • often polar, ionic, multi-functional („difficult“) • often poorly retained in WWTPs • Designed for biological activity Foto: Deltares Page 4 How to deal with complex mixtures? How to simplify complexity? http://www.wsj.com/articles/SB10001424127887324000704578386652879032748 Page 5 How to deal with complex mixtures? Typical fingerprints from Abatement options? different sources? Innovative legislation? Chemical footprint? Priority mixtures Solution-oriented assessment Candidate priority pollutants? Effect-based monitoring and River Basin Specific benchmarking? Drivers of Pollutants? Impact of mixture mixtures toxicity Page 6 Are there smart ways to group chemicals? • Modes of action • Hydrophobicity/volatility • Emission patterns • Contamination patterns Page 7 Typical fingerprints? • Agriculture • Domestic activities • Hospitals • Road runoff • Industrial branches • ……. Page 8 Stockholm Resilience Center Chemical pollution First version: Rockström et al., 2009 Still no quantification of global or regional boundaries for chemical pollution http://www.stockholmresilience.org/imag es/18.3110ee8c1495db74432676c/1421 678696891/PB_FIG33_globaia+16+Jan.j pg Page 9 Chemical footprint? “Is there enough water to safely dilute emissions”, or does a city or nation create “overshoot”? Current overshoots Bjørn et al. (2014) ES&T 48:13253 Zijp et al. (2014) ES&T 48:10588 Reprinted with permission from Bjørn et al. (2014) ES&T 48:13253 . Copyright (2014) American Chemical Society Page 10 Abatement options? Relative impact of STPs Page 11 • 6 week river espedition from source to mouth • 34 laboratories from 11 countries • Extensive investigation on • Chemistry • Ecology • Microbiology • Ecotoxicology • Hydromorphology • Radiology Page 12 Effect monitoring River Danube Large volume solid phase extraction in situ (500 L of water) for • Effect screening (about 30 tox. Endpoints) • Target (264 chemicals) and non- target screening Page 13 100 80 60 40 20 100/EC10 (REF) 100/EC10 0 Effect monitoring JDS08JDS22JDS27 JDS29JDS30JDS32 JDS33JDS35JDS36 JDS37JDS39JDS41 JDS44JDS53 JDS55JDS57 JDS59JDS60 JDS63JDS64 JDS65JDS67 Sites Page 14 187 ER AhRNF PXR p53 ox. stress FET -kB Chemical target screening 21 22 21 22 21 12 21 12 21 22 17 21 21 21 21 21 20 12 2 12 21 13 21 21 21 1 22 4 2 19 1 Schulze et al. 2015 90 – 150 targets found per site (< 1 ng/L to several µg/L) Page 15 Chemical target screening Target chemicals represent multiple modes of action Wibke Busch, unpublished Page 16 Target chemicals explain only part of toxic potency 0 .2 5 2 ,4 -D in itro p h e n o l d 5 0 e 0 .2 5 B is p h e n o l S e 2 ,4 -DAintirtarozpinhee n o l n s i D a id z e in n a 0l .2 0 D a id z e in d o 4 0 C a ffe in e p e G e n is te in p 0 .2 0 x D ic lo fe n a c s n i e C a rb a m a z e p in e e r a FET G e n is te in l R d 0 .1 5 s 3 0 p C a rb a ry l e E s 0 .1 5 ER x M e to la c h lo r n f e i e r o a ox. stress t C h lo r o to lu ro n l P e rflu o r o h e p ta n o ic a c id s T p 0n .1 0 2 0 x e 0 .1 0 E o T ri( b uDtoicxlyoeftehnyal)c p h o s p h a te i e v t i F t a a T ric lo s a n c c c c c c v t i i G e n is te in i i i i c c i i i % c d x x x x x 1 0 x t i x 0 .0 5 x e o 0 .0 5 o o o o o f t t t t t T r ie th y l c itr a te t c L o o x L L f t t o o o o o o D M e to p ro lo l e D t t D t t t t o a o o t t y y y y y y M M o M y y < C C C < C C C < N C C % % 0 p -N itr o p h e n o l 0 0.0.000 8 2 282 722292370 23 29 3330335233633 73 53 9346134743593 45 51 5474559365056 53 76 4569566076 3 6 4 6 5 6 7 8 2 2 2 7 2 9 3 0 3 2 3 3 3 5 3 6 3 7 3 9 4 1 4 4 5 3 5 5 5 7 5 9 6 0 6 3 6 4 6 5 6 7 S a lic y lic a c id J D S JSDiteS NSuitmeb Ne ru m b e r T ric lo s a n J D S S ite N u m b e r Neale et al. Submitted to ES&T Page 17 Chemical non-target screening Example Rivers from Elbe catchment 4000 P1 3500 DB C1 H2 3000 C2 Homologe series 2500 B2 P2 H1 WE 2000 SP M4 Ilm LN Eu Correlation S6 Z B1 M6 S5 1500 S3 Sol M2 M5 S4 Go number of LA S1 S2 S7 Total number of PeaksTotal numberof (ESI+) 1000 M1 S8 peaks vs. 500 Fraction of 0 10 20 30 wastewater40 50 60 1600 Fraction of treated wastewater [%] H2 1400 C1 P1 1200 SP Sol C2 1000 WE Ilm DB LN 800 B2 S6 Z Eu M4 S4 M6 P2 600 H1 S3 B1 M5 S5 LA S7 400 S2 S1 Go S8 Total number of PeaksTotal numberof (ESI-) M1 M2 200 0 0 10 20 30 40 50 60 Krauss et al., in prep. Fraction of treated wastewater [%] Page 18 Effect-directed analysis Page 19 Environment: exposure-response model Species Sensitivity Distribution Data: EC50’s ( 5000 only) of various species, one compound Potentially Affected Fraction Predicted Concentration Picture from: Hauschildt en Huijbregts, 2015. Life Cycle Impact Assessment. Springer. Page 20 Example: Joint Danube Survey (draft outcomes mixture toxic pressures, data-rich substances) Sampling sites differ - Regarding mixture toxic pressures - Thus, ecological integrity - Some expected high impact sites - It works, confirm with field impacts? - Prioritization of compounds & sites Page 21 The prospective approach: Integrated system of models and databases Objectives: Goal Page 22 The prospective approach: Integrated system of models and databases Chemicals Chemicals properties Prediction of exposure and Production and use Emissions risks in river basins and on European System scale properties Landscape http://www.centerforinquiry.net/amazon/the_amazon_river_basin/ Page 23 The prospective approach: Integrated system of models and databases Use volumes Emissions use types sub-model (M2) partitioning Waste water & Solid waste management Emissions to air, soil, groundwater, surface water model(s) (M4) - Transport & fate sub-model (M3) partitioning, Hydrology decay Meteorology External data Waterbodies exposure Soils Socio-economy Substance Substance properties sub Risk characterization sub-model (M5) toxicity Species sensitivities mode of action Species traits Food webs Page 24 Validation in trans-European case studies Example: Danube measured exposure, monitoring impact, risk mutual validation predicted exposure, impact, risk modeling confirmed toxicants Page 25 Validation in trans-European case studies Example: Danube (PFOS) Lindim et al., 2016. Chemosphere 144:803 Page 26 The prospective approach: Drivers of tomorrow - trends + models Demographic change Page 27 SOLUTIONS for Existing databases endusers SOLUTIONS IDPS SOLUTIONS data Existing models and tools RiBaTox decision tool SOLUTIONS models and tools Page 28 IDPS - Integrated Data Portal for SOLUTIONS Project info IDPS info IDPS contacts Participant databases Search for chemical by CAS by name by INChlKey Select for module Environmental Structure and Emission and Eco-toxicology Legislation monitoring Properties Abatement Open the selected link Information on the link Links RiBaTox IPCheM Page 30 Thanks to a great consortium For more information see http://www.solutions-project.eu/ The Project 39 partners Start: 1.10.2013 Duration: 5 years funded by the European Commission (Grant Nr. 603437) Page 32 Modelling integrated scenarios of land use, climate and water management with the iCLUE model Verena Huber García, Swen Meyer, David Gampe, Ralf Ludwig Ludwig-Maximlians-Universität München (LMU) 1st GLOBAQUA Conference, 11th of January 2016, Freising - Verena Huber García Introduction – Impacts of land use/cover change (LUCC) 1st GLOBAQUA Conference, 11th of January 2016, Freising - Verena Huber García 34 Introduction – The case study 1st GLOBAQUA Conference, 11th of January 2016, Freising - Verena Huber García 35 Introduction – LUCC in the Ebro 1st GLOBAQUA Conference, 11th of January 2016, Freising - Verena Huber García 36 Modelling LUCC – The model iCLUE = Conversion of Land Use and its Effects (Verweij, P.