INTERACTIVE CONTROLS OF WATER TABLE POSITION AND PLANT FUNCTIONAL TYPES ON PEAT POREWATER CHARACTER IN NORTHERN BOG ECOSYSTEMS: IMPLICATIONS FOR CARBON CYCLING DYNAMICS

Northern wetlands, and particularly peatlands, have been shown to store around 30% of the world's soil carbon and thus play a significant role in the carbon cycle of our planet. Changes in climate are altering peatland hydrology and vegetation communities. These changes are possibly resulting in declines in the ability of peatlands to sequester carbon because losses through carbon oxidation and mineralization are likely to increase relative to C inputs from net primary production in a warmer, drier climate. However, the consequences of interactive effects of altered hydrology and vegetation on carbon storage are not well understood. This research evaluated the importance of plant species, water table, and their interactive effects on porewater quality in a northern peatland with an average pH of 4.54, ranging from 4.15 to 4.8. We assessed the effects of plant functional group (ericaceous shrubs, sedges, and bryophytes) and water table position on biogeochemical processes. Specifically, we measured dissolved organic carbon (DOC), total dissolved nitrogen (TDN), potential enzyme activity, organic acids, anions and cations, spectral indexes of aromaticity, and phenolic content. Our results indicate that acetate and propionate concentrations in the sedge-dominated communities declined with depth and water table drawdown, relative to the control and ericaceous treatments. DOC increased in the lowered water table treatments in all vegetation community types, and the peat porewater C:N ratio declined in the sedge-dominated treatments when the water table was lowered. The relationship between DOC and ferrous iron showed significant responses to vegetation type; the exclusion of Ericaceae resulted in less ferrous iron per unit DOC compared to mixed species treatments and Ericaceae alone. This observation was corroborated with higher mean oxidation redox potential profiles (integrating 20, 40, and 70 cm) measured in the sedge treatments, compared with the mixed and Ericaceae species treatments over a growing season. Enzymatic activities did not show as strong of a response to treatments as expected; the oxidative enzyme peroxidase and the hydrolytic enzyme phosphatase were the only enzymes to respond to water table, where the potential activity of both enzymes increased with water table drawdown. Overall, there were significant interactive effects between changes in vegetation and water table position on peat porewater composition. These data suggest that vegetation effects on oxidation reduction potentials and peat porewater character can be as important as water table position in northern bog ecosystems.

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.