Advancing understanding of hydrochemical and ecological processes controlling the fate of aquatic organic matter, nutrients and pollutants using state-of-the-art methods
Co-organized by HS10
Convener: Magdalena Bieroza | Co-conveners: Andrea Butturini, Bethany FoxECSECS, Diane McKnight, Michael Rode
| Attendance Wed, 06 May, 10:45–12:30 (CEST)

The last two decades have brought major technological advancements in characterisation of aquatic organic matter with spectroscopic and chromatographic methods and collection of water quality data at high spatial and temporal resolution with automated in situ instruments. The aim of this session is to demonstrate if and how this methodological advancement improves our understanding of dominant hydrochemical and ecological processes in aquatic environments controlling the fate of organic matter, nutrients and other pollutants.

Specifically, our ability to characterise different fractions of natural organic matter has increased thanks to a range of analytical methods e.g. fluorescence and absorbance spectroscopy, mass spectrometry and chromatography combined with new data mining tools (self-organising maps, PARAFAC analysis). Matching the water quality measurement interval with the timescales of hydrological responses (from minutes to hours) thanks to automated in situ wet-chemistry analysers, optical sensors and lab-on-a-chip instruments has led to discovery of new hydrochemical and biogeochemical patterns in aquatic environments e.g., concentration-discharge hysteresis and diurnal cycles. We need to understand further how hydrochemical and ecological processes control those patterns, how different biogeochemical cycles are linked in aquatic environments (e.g., carbon, phosphorus, nitrogen, sulphur and iron) and how human activities disturb those biogeochemical cycles by emitting excess amounts of nutrients to aquatic systems. In particular, there is a growing need to better characterise the origins, delivery pathways, transformations and environmental fate of organic matter and nutrients in aquatic environments along with identification of robust numerical tools for advanced data processing and modelling.

Previously in this session: