Comparison of common dredging equipment air emissions

The purpose of this study is to provide a procedure to include emissions to the atmosphere resulting from the combustion of diesel fuel during dredging operations into the decision-making process of dredging equipment selection. The proposed procedure is demonstrated for typical dredging methods and data from the Illinois Waterway as performed by the U.S. Army Corps of Engineers, Rock Island District. The equipment included in this study is a 16-inch cutterhead pipeline dredge and a mechanical bucket dredge used during the 2005 dredging season on the Illinois Waterway. Considerable effort has been put forth to identify and reduce environmental impacts from dredging operations. Though environmental impacts of dredging have been studied no efforts have been applied to the evaluation of air emissions from comparable types of dredging equipment, as in this study. By identifying the type of dredging equipment with the lowest air emissions, when cost, site conditions, and equipment availability are comparable, adverse environmental impacts can be minimized without compromising the dredging project. A total of 48 scenarios were developed by varying the dredged material quantity, transport distance, and production rates. This produced an “envelope” of results applicable to a broad range of site conditions. Total diesel fuel consumed was calculated using standard cost estimating practices as defined in the U.S. Army Corps of Engineers Construction Equipment Ownership and Operating Expense Schedule (USACE, 2005). The diesel fuel usage was estimated for all equipment used to mobilize and/or operate each dredging crew for every scenario. A Limited Life Cycle Assessment (LCA) was used to estimate the air emissions from two comparable dredging operations utilizing SimaPro LCA software. An Environmental Impact Single Score (EISS) was the SimaPro output selected for comparison with the cost per CY of dredging, potential production rates, and transport distances to identify possible decision points. The total dredging time was estimated for each dredging crew and scenario. An average hourly cost for both dredging crews was calculated based on Rock Island District 2005 dredging season records (Graham 2007/08). The results from this study confirm commonly used rules of thumb in the dredging industry by indicating that mechanical bucket dredges are better suited for long transport distances and have lower air emissions and cost per CY for smaller quantities of dredged material. In addition, the results show that a cutterhead pipeline dredge would be preferable for moderate and large volumes of dredged material when no additional booster pumps are required. Finally, the results indicate that production rates can be a significant factor when evaluating the air emissions from comparable dredging equipment.

Investigation of the effect of using data collection technology on students' attitudes to science instruction

The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.

Comparing remote sensing and ground-based methods of quantifying cover type and carbon storage in an urban forest

Understanding the canopy cover of an urban environment leads to better estimates of carbon storage and more informed management decisions by urban foresters. The most commonly used method for assessing urban forest cover type extent is ground surveys, which can be both timeconsuming and expensive. The analysis of aerial photos is an alternative method that is faster, cheaper, and can cover a larger number of sites, but may be less accurate. The objectives of this paper were (1) to compare three methods of cover type assessment for Los Angeles, CA: handdelineation of aerial photos in ArcMap, supervised classification of aerial photos in ERDAS Imagine, and ground-collected data using the Urban Forest Effects (UFORE) model protocol; (2) to determine how well remote sensing methods estimate carbon storage as predicted by the UFORE model; and (3) to explore the influence of tree diameter and tree density on carbon storage estimates. Four major cover types (bare ground, fine vegetation, coarse vegetation, and impervious surfaces) were determined from 348 plots (0.039 ha each) randomly stratified according to land-use. Hand-delineation was better than supervised classification at predicting ground-based measurements of cover type and UFORE model-predicted carbon storage. Most error in supervised classification resulted from shadow, which was interpreted as unknown cover type. Neither tree diameter or tree density per plot significantly affected the relationship between carbon storage and canopy cover. The efficiency of remote sensing rather than in situ data collection allows urban forest managers the ability to quickly assess a city and plan accordingly while also preserving their often-limited budget.

Parameter identification of a copper-zeolite SCR catalyst model using reactor data

The selective catalytic reduction system is a well established technology for NOx emissions control in diesel engines. A one dimensional, single channel selective catalytic reduction (SCR) model was previously developed using Oak Ridge National Laboratory (ORNL) generated reactor data for an iron-zeolite catalyst system. Calibration of this model to fit the experimental reactor data collected at ORNL for a copper-zeolite SCR catalyst is presented. Initially a test protocol was developed in order to investigate the different phenomena responsible for the SCR system response. A SCR model with two distinct types of storage sites was used. The calibration process was started with storage capacity calculations for the catalyst sample. Then the chemical kinetics occurring at each segment of the protocol was investigated. The reactions included in this model were adsorption, desorption, standard SCR, fast SCR, slow SCR, NH3 Oxidation, NO oxidation and N2O formation. The reaction rates were identified for each temperature using a time domain optimization approach. Assuming an Arrhenius form of the reaction rates, activation energies and pre-exponential parameters were fit to the reaction rates. The results indicate that the Arrhenius form is appropriate and the reaction scheme used allows the model to fit to the experimental data and also for use in real world engine studies.

BALTHMETRIC SURVEY IN THE KEWEENAW WATER WAY IN MICHIGAN, USA, MAKING 3D MODEL, AND COMPARING SONAR EQUIPMENT OF THE MODERN AUV AND THE TRADITIONAL SINGLE BEAM SONAR

This thesis represents the overview of hydrographic surveying and different types of modern and traditional surveying equipment, and data acquisition using the traditional single beam sonar system and a modern fully autonomous underwater vehicle, IVER3. During the thesis, the data sets were collected using the vehicles of the Great Lake Research Center at Michigan Technological University. This thesis also presents how to process and edit the bathymetric data on SonarWiz5. Moreover, the three dimensional models were created after importing the data sets in the same coordinate system. In these interpolated surfaces, the details and excavations can be easily seen on the surface models. In this study, the profiles are plotted on the surface models to compare the sensors and details on the seabed. It is shown that single beam sonar might miss some details, such as pipeline and quick elevation changes on the seabed when we compare to the side scan sonar of IVER3 because the single side scan sonar can acquire better resolution. However, sometimes using single beam sonar can save your project time and money because the single beam sonar is cheaper than side scan sonars and the processing might be easier than the side scan data.