Challenge
Pollution of freshwaters from industry, agriculture and urban settings is a major global pressure on human and ecological health. Effective and robust monitoring of water quality is vital to safeguard our water supplies and manage the health of our aquatic ecosystems.
Traditional monitoring has relied on fairly expensive physical sensors operating at low spatial resolution that require frequent servicing and maintenance by skilled personnel. These sensing systems are thus often beyond the affordability and skills base of environmental monitoring agencies. As a consequence, a fuller understanding of water quality over time and the movement of pollutants is often lacking and posing a challenge for cost-effective and targeted environmental management.
There is an urgent need for gathering data at a low-cost, that goes beyond the currently available simple physical sensors towards chemical and biological sensing of pollutants and key environmental parameters at higher frequencies (< daily) and higher spatial densities. This will facilitate better quantification of trends and pressures, underpin predictive modelling and provide the foundation for robust and cost-effective management of the aquatic environment.
With recent breakthroughs in pump- and label-free fluid processing as well as label-free high sensitivity sensing, complex sample processing workflows can now be greatly simplified. This offers a pathway to create high density networks of automated sensors or enrolling members of the general public in gathering data with simple sensors.
Approach
To address this challenge, we bring together a diverse team of Hull-based scientists. Experts in environmental sciences for marine, coastal and river waters work hand-in-hand with researchers specialising in lab-on-a-chip, nanophysics sensing technologies and lifecycle engineering, as well as computer scientists.
PhD student Mila Sari is setting out on mapping heavy metal pollution in river water with paper-based devices through citizen science. Engineer Aleksei Iurkov is developing analysis platforms for automated in-situ sensing of geochemicals in caves. Mohammad AlHurani is designing lab-on-a-chip platforms that can sort micro-plankton populations. This will help us build a picture of the plankton community structure and marine food chain. Physicists Thomas Henry and Stephen Wilkinson employ cutting-edge nano-optical spectroscopy and nanogap electronics to detect microparticles and hormone pollutants in aquatic systems, respectively. Whilst computer scientist Onatkut Dagtekin combines our obtained data sets with publicly available environmental data and applies deep learning methodologies to help understand and predict movement of chemicals in the environment.
We can harness our excellent research and training environment with cutting-edge Lab-on-a-Chip, 3D printing and Nanopatterning Facilities, as well as our state-of-the-art High Performance Computing capability. We have access to a wide range of sample sites including streams and rivers, aquaculture farms, estuarine and oceanic sites, as well as a Transportable Environmental Analytical Laboratory (TEAL).
Impact
- High-frequency chemical and biological sensing will allow us to develop a fundamental understanding of fate of pollutants in our surroundings.
- We will form a picture of water quality and pollution dynamics and as well as the movement of geochemicals through our environment, leading to a better prediction of how climate change affects carbon cycles and terrestrial carbon budgets.