• Use high performance liquid chromatography with fluorescence detection to track the distribution of fluorescent whitening agents along a southern portion of the Lake Michigan shoreline
• Examine the relationship between these fluorescent whitening agents and E. coli

• Develop a software platform to provide real-time, online access to advisories for consumption of recreationally-caught fish

• To provide information on past low lake levels of Lake Michigan, to better
  understand why there have been lower lake levels in the past, and to better predict and thus prepare for future low lake levels

This project first collated more than 50,000 data records from creel surveys conducted in Illinois and Indiana waters of Lake Michigan. Linear models were used to explore relationships between fisheries data and ancillary data such as fish abundance, fish stocking, prey densities and environmental parameters. The project then estimated an economic valuation of the Lake Michigan shoreline and boat fishing activity to anglers.

• Determine what factors impact year class strength in yellow perch

This research project proposes a computational model validated by experimental testing to improve various characteristics of sustainable cement and concrete by reusing waste materials from the Great Lakes as additives in sustainable building materials. The model will be paired with AI algorithms to efficiently determine the feasibility of recycling bottom sediment from the Great Lakes as a sustainable construction material and analyze the impact of the additive on concrete performance. The goal of the proposed research is to reduce environmental pollution and improve the current ecological system by recycling the bottom sediments in the Great Lakes region, thus improving the efficiency of concrete use in actual construction and the ecological sustainability of the Great Lakes region.