Impact of copper mine tailings (stamp sand) on survival and development of aquatic organisms near Gay, Michigan

Heavy metal-rich copper mine tailings, called stamp sands, were dumped by mining companies directly into streams and along the Lake Superior shoreline, degrading Keweenaw Peninsula waterways. One of the largest disposal sites is near Gay, Michigan, where tailings have been moved along the shoreline by currents since mining ceased. As a result, the smallest sand particles have been washed into deeper water and are filling the interstitial spaces of Buffalo Reef, a critical lake trout spawning site. This research is the first to investigate if stamp sand is detrimental to survival and early development of eggs and larvae of lake sturgeon, lake trout, and Northern leopard frogs, and also examines if the presence of stamp sands influences substrate selection of earthworms. This study found that stamp sand had significantly larger mean particle sizes and irregular shapes compared to natural sand, and earthworms show a strong preference for natural substrate over any combination that included stamp sand. Additionally, copper analysis (Cu2+) of surface water over stamp sand and natural sand showed concentrations were significantly higher in stamp sand surface water (100 μg/L) compared to natural sand surface water (10 μg/L). Frog embryos had similar hatch success over both types of sand, but tadpoles reared over natural sand grew faster and had higher survival rates. Eggs of lake sturgeon showed similar hatch success and development over natural vs. stamp sand over 17 days, while lake trout eggs hatched earlier and developed faster when incubated over stamp sand, yet showed similar development over a 163 day period. Copper from stamp sand appears to impact amphibians more than fish species in this study. These results will help determine what impact stamp sand has on organisms found throughout the Keweenaw Peninsula which encounter the material at some point in their life history.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.