ANALYSIS AND SIMULATION OF ENERGY USE AND COST AT A MUNICIPAL WASTEWATER TREATMENT PLANT

The cost of electricity, a major operating cost of municipal wastewater treatment plants, is related to influent flow rate, power price, and power load. With knowledge of inflow and price patterns, plant operators can manage processes to reduce electricity costs. Records of influent flow, power price, and load are evaluated for Blue Plains Advanced Wastewater Treatment Plant. Diurnal and seasonal trends are analyzed. Power usage is broken down among treatment processes. A simulation model of influent pumping, a large power user, is developed. It predicts pump discharge and power usage based on wet-well level. Individual pump characteristics are tested in the plant. The model accurately simulates plant inflow and power use for two pumping stations [R2 = 0.68, 0.93 (inflow), R2 =0.94, 0.91(power)]. Wet-well stage-storage relationship is estimated from data. Time-varying wet-well level is added to the model. A synthetic example demonstrates application in managing pumps to reduce electricity cost.

Modeling Flood Stage-Duration-Frequency: A Risk Assessment of Critical Infrastructure in the Tidal Potomac

The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

Interactive Effects of Plant Species and Organic Carbon on Nitrate Removal in Chesapeake Bay Treatment Wetlands

Nitrate from agricultural runoff are a significant cause of algal blooms in estuarine ecosystems such as the Chesapeake Bay. These blooms block sunlight vital to submerged aquatic vegetation, leading to hypoxic areas. Natural and constructed wetlands have been shown to reduce the amount of nitrate flowing into adjacent bodies of water. We tested three wetland plant species native to Maryland, Typha latifolia (cattail), Panicum virgatum (switchgrass), and Schoenoplectus validus (soft-stem bulrush), in wetland microcosms to determine the effect of species combination and organic amendment on nitrate removal. In the first phase of our study, we found that microcosms containing sawdust exhibited significantly greater nitrate removal than microcosms amended with glucose or hay at a low nitrate loading rate. In the second phase of our study, we confirmed that combining these plants removed nitrate, although no one combination was significantly better. Furthermore, the above-ground biomass of microcosms containing switchgrass had a significantly greater percentage of carbon than microcosms without switchgrass, which can be studied for potential biofuel use. Based on our data, future environmental groups can make a more informed decision when choosing biofuel-capable plant species for artificial wetlands native to the Chesapeake Bay Watershed.