Updated Polychlorinated Biphenyl Mass Budget for Lake Michigan.

This study revisits and updates the Lake Michigan Mass Balance Project (LMMBP) for polychlorinated biphenyls (PCBs) that was conducted in 1994-1995. This work uses recent concentrations of PCBs in tributary and open lake water, air, and sediment to calculate an updated mass budget. Five of the 11 LMMBP tributaries were revisited in 2015. In these five tributaries, the geometric mean concentrations of ∑PCBs (sum of 85 congeners) ranged from 1.52 to 22.4 ng L-1. The highest concentrations of PCBs were generally found in the Lower Fox River and in the Indiana Harbor and Ship Canal. The input flows of ∑PCBs from wet deposition, dry deposition, tributary loading, and air to water exchange, and the output flows due to sediment burial, volatilization from water to air, and transport to Lake Huron and through the Chicago Diversion were calculated, as well as flows related to the internal processes of settling, resuspension, and sediment-water diffusion. The net transfer of ∑PCBs is 1240 ± 531 kg yr-1 out of the lake. This net transfer is 46% lower than that estimated in 1994-1995. PCB concentrations in most matrices in the lake are decreasing, which drove the decline of all the individual input and output flows. Atmospheric deposition has become negligible, while volatilization from the water surface is still a major route of loss, releasing PCBs from the lake into the air. Large masses of PCBs remain in the water column and surface sediments and are likely to contribute to the future efflux of PCBs from the lake to the air.

Modeling the Relative Importance of Nutrient and Carbon Loads, Boundary Fluxes, and Sediment Fluxes on Gulf of Mexico Hypoxia.

The Louisiana continental shelf in the northern Gulf of Mexico experiences bottom water hypoxia in the summer. In this study, we applied a biogeochemical model that simulates dissolved oxygen concentrations on the shelf in response to varying riverine nutrient and organic carbon loads, boundary fluxes, and sediment fluxes. Five-year model simulations demonstrated that midsummer hypoxic areas were most sensitive to riverine nutrient loads and sediment oxygen demand from settled organic carbon. Hypoxic area predictions were also sensitive to nutrient and organic carbon fluxes from lateral boundaries. The predicted hypoxic area decreased with decreases in nutrient loads, but the extent of change was influenced by the method used to estimate model boundary concentrations. We demonstrated that modeling efforts to predict changes in hypoxic area on the continental shelf in relationship to changes in nutrients should include representative boundary nutrient and organic carbon concentrations and functions for estimating sediment oxygen demand that are linked to settled organic carbon derived from water-column primary production. On the basis of our model analyses using the most representative boundary concentrations, nutrient loads would need to be reduced by 69% to achieve the Gulf of Mexico Nutrient Task Force Action Plan target hypoxic area of 5000 km(2).

The Lake Michigan eutrophication model, LM3-Eutro: model development and calibration.

A eutrophication model developed to generate primary-production estimates in Lake Michigan can simulate 17 state variables, including three plankton classes and several nutrients. The model, known as the Lake Michigan Eutrophication model (LM3-Eutro), has a high-resolution computational grid that enables good spatial description of spring temperature and phytoplankton concentrations, which have significant gradients in the lakes. The grid also allows the model to predict concentrations in nearshore areas and other regions of interest. The model provided more accurate estimates of algal light limitation based on three-hour intervals compared to daily averages that are used in most eutrophication models, especially during sunny summer days when algal photo-inhibition often occurs. Model output was compared to field data using statistical parameters such as squares of the correlation coefficients to determine the best model fit. The calibrated model output fit the field data reasonably well for nutrients and phytoplankton, which provided confidence in the framework, governing equations, and coefficients used.