Tracing the source of groundwater for three different coastal peatlands along Lake Superior

The goal of this project was to investigate the influence of a large inland lake on adjacent coastal freshwater peatlands. The specific aim was to determine the source of groundwater for three differently formed peatlands located on the southern shore of Lake Superior. The groundwater study was conducted at Bete Grise, a peatland complex in a dune-swale system; Pequaming, a peatland developed in the swale of a tombolo; and Lightfoot Bay, a peatland developed in a barrier beach wetland complex. To determine the source of groundwater in the peatlands, transects of six groundwater monitoring wells were established at each study site, covering distinctly different vegetation zones. At Pequaming and Lightfoot Bay the transects monitored two vegetation zones: transition zone from upland and open fen. At Bete Grise, the transects monitored dunes and swales. Additionally, at all three sites, upland groundwater was monitored using three wells that were installed into the adjacent upland forest. Biweekly measurements of well water pH and specific conductance were carried out from May to October of 2010. At each site, vegetation cover, peat depths and surface elevations were determined and compared to Lake Superior water levels. From June 14 – 17, July 20 – 21 and September 10 – 12, stable isotopes of oxygen (18O/16O) ratios were measured in all the wells and for Lake Superior water. A mixing model was used to estimate the percentage of lake water influencing each site based on the oxygen isotope ratios. During the sampling period, groundwater at all three sites was supported primarily by upland groundwater. Pequaming was approximately 80 % upland groundwater supported and up to 20 % Lake water supported in the uppermost 1 m layer of peat column of the transition zone and open fen. Bete Grise and Lightfoot Bay were 100 % upland groundwater supported throughout the season. The height of Lake Superior was near typical levels in 2010. In years when the lake level is higher, Lake water could intrude into the adjacent peatlands. However, under typical hydrologic conditions, these coastal peatlands are primarily supported by upland groundwater.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.