Environmental Science & Technology
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Item Eutrophication, Hypoxia and Trophic Transfer Efficiency in Chesapeake Bay(2002) Hagy, James Dixon III; Boynton, Walter R.; Environmental Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)Coastal eutrophication is a global problem that has contributed to loss of estuarine habitats and potentially decreased fisheries production. Hypoxia is often observed in eutrophic estuaries where it can be an important cause of habitat loss. This study utilized a suite of empirical analyses to examine key linkages relating coastal eutrophication to hypoxia, trophic structure, and trophic transfer efficiency in Chesapeake Bay (CB), USA. A salt- and water-balance model, or "box" model, was developed to quantify large-scale physical transport for CB, an input to many subsequent analyses. Historical ( 1950-1999) dissolved oxygen (DO) data for CB showed that moderate hypoxia (DO<2.0 mg1^-1) increased ~3-fold, modulated by spring river flow. Severe hypoxia (DO<0.7 mg1^1) occurred only in high flow years during 1950-1967, but was present annually since 1968. Analysis using tree-structured regression showed that hypoxia was the most important factor determining patterns of macrobenthic biomass in Chesapeake Bay. Carbon budgets showed that, where habitat quality was poor, macrobenthic biomass was much less than could be supported by the organic carbon supply. In these cases, even dramatic reductions in carbon supply would not be expected to limit benthic production and by extension, trophic transfers to upper trophic levels via the benthos. The effect of eutrophication and hypoxia on trophic structure and trophic transfer efficiency were examined by estimating trophic flow networks for three regions of CB during summer. In addition, a series of "rules" were described and used to infer the trophic flow network for a "restored" middle CB from historical data, comparative ecological relationships and mass balance constraints. Excessive carbon now through bacteria was the most pronounced symptom of eutrophication in the modern mid Bay. The microbial food web transferred organic matter to trophic levels comparable to large piscivorous predators, maintaining average trophic transfer efficiency, even as the fraction of primary production transferred to top predators decreased. In the restored Bay, increased macrobenthic production shifted metabolic activity away from the microbial food web, increasing the potential trophic transfer to fish by 7-fold, even as total primary production decreased to 63% of the current average.Item A COMPARATIVE HYDROLOGIC ANALYSIS OF SURFACE MINED AND FORESTED WATERSHEDS IN WESTERN MARYLAND(2002) Negley, Timothy Lee; Eshleman, Keith N.; Environmental Science & Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)This thesis presents the results of a hydrologic analysis conducted as part of a larger, multi-faceted, collaborative effort to study ecosystem function of a watershed subjected to surface mining and reclamation in the Appalachian Region of the United States. The primary goal of this study was to determine whether a small watershed subjected to surface mine reclamation practices (MAT 1) displayed a stormflow response to rain events that was different from those displayed by a young second-growth forested watershed (NEFl). A secondary goal was to investigate whether intensive surface mining in the Georges Creek basin has altered stormflow response at a larger river basin scale when compared to a similar, but predominantly forested basin (Savage River). At the small watersheds, MATl produced greater a) runoff coefficients (2.5x); b) total runoff (3x); and c) peak runoff rates (2x) compared to NEFl. Total rainfall explained 63% of the variation in total runoff at MAT I compared to only 21 % of the variation in total runoff at NEF I. Regardless of a recent 13% increase in surface mine reclamation in the Georges Creek basin, little difference in stormflow response was observed for 15 storms analyzed across the two larger basins. Georges Creek on average responded 3 hr more quickly than Savage River, However the hydrological response characteristics of the two basins were similar. In addition, hydrological response characteristics for Georges Creek and Savage River remained relatively stable over time. Further research is needed to address inabilities to scale responses observed at the small watersheds.Item AN INVESTIGATION OF THE RELATIONSHIP BETWEEN THE LEVEL OF ANTIBIOTIC RESISTANCE OF ESCHERICHIA COLI IN NONTIDAL WETLANDS AND COMMON WETLAND HEALTH FACTORS(2008-05-25) Agarwal, Neil; Ahearn, Sean; Dudziak, Erik; Khan, Sehba; Marcin, Daniel; Shofnos, Matthew; Skoda, Emily; Venkatachari, Padmasini; Vocke, Robert; Tilley, DavidThis report investigated the prevalence of antibiotic resistance among Escherichia coli in the water of 13 non-tidal mitigation wetlands in Maryland, and its relation to land use and wetland health. At each site, land use, surface and sub-surface water samples, soil samples, and vegetation cover were collected. From the water samples, individual colonies of E. coli were isolated and tested, using the disc diffusion method, for resistance to the antibiotics ampicillin, ciprofloxacin, erythromycin, sulfisoxazole, and tetracycline. According to soils, vegetation and water quality improvement criteria the wetlands function like healthy wetlands. The wetlands' E. coli exhibit resistance to all of the antibiotics tested, except for ciprofloxacin. There were statistically significant relationships found between land use and antibiotic resistance, vegetation, soil and water chemistry. Surprisingly, E. coli in wetlands with smaller stocks of carbon and nitrogen in their soil exhibited more resistance to tetracycline, possibly indicating that soil quality plays an important role in fostering or fighting antibiotic resistance. The work demonstrates that antibiotic resistance is present in Maryland's wetlands, but that its spread could be subdued by healthy wetlands.Item Advanced imaging and data mining technologies for medical and food safety applications(2009) Jiang, Lu; Tao, Yang; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As one of the most fast-developing research areas, biological imaging and image analysis receive more and more attentions, and have been already widely applied in many scientific fields including medical diagnosis and food safety inspection. To further investigate such a very interesting area, this research is mainly focused on advanced imaging and pattern recognition technologies in both medical and food safety applications, which include 1) noise reduction of ultra-low-dose multi-slice helical CT imaging for early lung cancer screening, and 2) automated discrimination between walnut shell and meat under hyperspectral florescence imaging. In the medical imaging and diagnosis area, because X-ray computed tomography (CT) has been applied to screen large populations for early lung cancer detection during the last decade, more and more attentions have been paid to studying low-dose, even ultra-low-dose X-ray CTs. However, reducing CT radiation exposure inevitably increases the noise level in the sinogram, thereby degrading the quality of reconstructed CT images. Thus, how to reduce the noise levels in the low-dose CT images becomes a meaningful topic. In this research, a nonparametric smoothing method with block based thin plate smoothing splines and the roughness penalty was introduced to restore the ultra-low-dose helical CT raw data, which was acquired under 120 kVp / 10 mAs protocol. The objective thorax image quality evaluation was first conducted to assess the image quality and noise level of proposed method. A web-based subjective evaluation system was also built for the total of 23 radiologists to compare proposed approach with traditional sinogram restoration method. Both objective and subjective evaluation studies showed the effectiveness of proposed thin-plate based nonparametric regression method in sinogram restoration of multi-slice helical ultra-low-dose CT. In food quality inspection area, automated discrimination between walnut shell and meat has become an imperative task in the walnut postharvest processing industry in the U.S. This research developed two hyperspectral fluorescence imaging based approaches, which were capable of differentiating walnut small shell fragments from meat. Firstly, a principal component analysis (PCA) and Gaussian mixture model (PCA-GMM)-based Bayesian classification method was introduced. PCA was used to extract features, and then the optimal number of components in PCA was selected by a cross-validation technique. The PCA-GMM-based Bayesian classifier was further applied to differentiate the walnut shell and meat according to the class-conditional probability and the prior estimated by the Gaussian mixture model. The experimental results showed the effectiveness of this PCA-GMM approach, and an overall 98.2% recognition rate was achieved. Secondly, Gaussian-kernel based Support Vector Machine (SVM) was presented for the walnut shell and meat discrimination in the hyperspectral florescence imagery. SVM was applied to seek an optimal low to high dimensional mapping such that the nonlinear separable input data in the original input data space became separable on the mapped high dimensional space, and hence fulfilled the classification between walnut shell and meat. An overall recognition rate of 98.7% was achieved by this method. Although the hyperspectral fluorescence imaging is capable of differentiating between walnut shell and meat, one persistent problem is how to deal with huge amount of data acquired by the hyperspectral imaging system, and hence improve the efficiency of application system. To solve this problem, an Independent Component Analysis with k-Nearest Neighbor Classifier (ICA-kNN) approach was presented in this research to reduce the data redundancy while not sacrifice the classification performance too much. An overall 90.6% detection rate was achieved given 10 optimal wavelengths, which constituted only 13% of the total acquired hyperspectral image data. In order to further evaluate the proposed method, the classification results of the ICA-kNN approach were also compared to the kNN classifier method alone. The experimental results showed that the ICA-kNN method with fewer wavelengths had the same performance as the kNN classifier alone using information from all 79 wavelengths. This demonstrated the effectiveness of the proposed ICA-kNN method for the hyperspectral band selection in the walnut shell and meat classification.Item Evaluation of the effects of wetland restoration design on hydraulic residence time and nutrient retention(2009) Strano, Stephen; Felton, Gary K; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Hydraulic residence time (HRT) is a critical factor that can be integrated into wetland restoration designs to promote nutrient retention, but HRT in the context of wetlands with storm-driven hydrology is not well understood. A model for nutrient retention optimization based on HRT was evaluated using three indicators of HRT and nutrient stocks in above-ground plant biomass. Results indicated that a commonly used indicator of HRT, the ratio of wetland to watershed area, may be insufficient, while nominal HRT provided an overestimate for wetlands receiving storm runoff. While there was little relationship between total nitrogen and HRT, results suggested that HRT may explain some variation in total phosphorus. Results also indicated that the studied wetland restorations were not designed to provide sufficient HRT to promote the retention of dissolved nutrients, and that staged outlets could be used to provide significant HRT's for a range of storm events.Item Modeling Approaches for Treatment Wetlands(2009) Carleton, James N.; Montas, Hubert J; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Although treatment wetlands can reduce pollutant loads, reliably predicting their performance remains a challenge because removal processes are often complex, spatially heterogeneous, and incompletely understood. Although initially popular for characterizing wetland performance, plug flow reactor models are problematic because their parameters exhibit correlation with hydraulic loading. One-dimensional advective-dispersive-reactive (ADE) models are also inadequate because longitudinal dispersion in wetlands is often non-Fickian as a result of steep velocity gradients. Models that make use of residence time distributions have shown promise in improving performance characterization, particularly when interdependencies of stream-tube scale velocities and reaction rate coefficients are considered (the "DND" approach). However this approach is limited to steady-state conditions, and to an assumption that transverse mixing is nil. This dissertation investigates three aspects of wetland modeling and is organized in a journal paper format. The first paper describes development of a DND model which accommodates non-steady-state conditions. The model processes flow and inlet concentration time series, and calculates as output effluent concentration time series. A version of the code allows optimization of model parameters by minimization of summed squared deviations between predicted and measured effluent concentrations. In example comparisons, model results compare favorably with measured data. The second paper develops an analytical solution to a two-dimensional advective-dispersive-reactive equation, in which all flux terms are expressed as power functions of the transverse dimension. For uniform inlet concentration this idealized heterogeneity model is similar to a DND model, but with the inclusion of transverse diffusion. An example is used to illustrate the beneficial impact that transverse mixing has on reactor performance. The third paper describes development of a model based upon a stochastic interpretation of the ADE. The solution technique that is employed results in a bicontinuum model that for steady-state conditions becomes a weighted sum of two exponential decline functions. For low and intermediate degrees of mixing, model results nicely match those of the corresponding idealized heterogeneity model, and for high mixing they match results of the corresponding one-dimensional ADE. Comparisons against data suggest the bicontinuum model may represent wetland performance better than the DND model in some but not all cases.Item Hyperspectral Reflectance as an Indicator of Foliar Nutrient Levels in Hybrid Poplar Clone OP-367 Grown on Biosolid Amended Soil(2009) Griffeth, Tommy; Felton, Gary; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Trees of the genus Populus are fast growing trees that require considerable amounts of water and nutrients to meet physiological growth demands. The determination of correlations between hybrid poplar leaf spectral reflectance in the 325-1100 nm range, laboratory foliar analysis of leaf macronutrient and micronutrient concentrations, and leaf water potential datasets were analyzed using Full Cross-Validation and Test Set Models via the partial least squares (PLS) method of regression analysis. Based on an evaluation of the slope of the Predicted vs. Measured regression line, the root mean squared error (RMSE), and r-squared, the majority of the models constructed did not adequately model foliar concentrations from spectral data. However, the models for H, N, P, K, Cu and Al had values (slope of the Predicted vs. Measured regression line greater than 0.50 and r-squared values greater than 0.50 in at least one type of model) that warrant future study.Item RESPIRATORY MECHANICS OF FLOW LIMITATION AND CHARACTERIZATION OF RESISTANCE MEASUREMENTS WITH A NON-INVASIVE DEVICE(2009) Coursey, Derya; Johnson, Arthur T; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Resistance measurements with the airflow perturbation device (APD) were compared to directly measured pulmonary resistances with an esophageal balloon to validate the APD. The APD perturbs the flow and the mouth pressure during regular breathing. The ratio of mouth pressure perturbations to the flow perturbations was used to calculate the inspiratory, expiratory and average respiratory resistance. Six healthy subjects were tested during tidal breathing when known external resistances were added during inspiration, during expiration, and during both inspiration and expiration. The difference between the averaged APD measured and directly measured pulmonary resistances was 0.59 ± 1.25 (mean ± SD) cmH2O/L/s. Compared to the magnitude of the known increase in added resistance, the APD measured resistance increased by 79 %, while the directly measured pulmonary resistance increased only by 56%. During addition of external resistances to both inspiration and expiration, the changes in inspiratory and expiratory pulmonary resistance were only 36 % and 62 % of the added resistance, respectively. On the other hand, the APD inhalation and exhalation resistance measured between 82 % and 76 % of added resistance change. It was concluded that the APD detects changes in external resistance at least as well and probably better than classical measurements of pulmonary resistance. Additionally, expiratory isovolume pressure - flow (IVPF) curves, which show the pressure at which the flow becomes limited during forced expiration, were constructed in six healthy subjects with the classical invasive method of esophageal balloon (EB) and the alternative noninvasive method of stop - flow (SF) at 25, 50, and 75 % vital capacity (VC). The difference between the pressures (Pmax) and flow (Qmax) at which flow limitation first occurs and correlation with the stop - flow and esophageal balloon methods were studied. Additionally, the resistance at flow limitation was compared to the APD resistance during forced breathing. On average, PSF,max was 5.6 and 4.4 times PEB,max at 25 %VC and 50 %VC, respectively. QSF,max was 0.68 and 0.59 times QEB,max at 25 %VC and 50 %VC, respectively. No correlation was found between the stop - flow and esophageal balloon methods as well as between the resistances at flow limitation.Item PROSPECTIVE HEAD MOVEMENT CORRECTION FOR HIGH-RESOLUTION MRI USING AN IN-BORE OPTICAL TRACKING SYSTEM(2009) Qin, Lei; Tao, Yang; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In MRI of the human brain, subject motion is a major cause of magnetic resonance image quality degradation. To compensate the effects of head motion during data acquisition, an in-bore optical motion tracking system is proposed. The system comprises one or two MR compatible infrared cameras that are fixed on a holder right above and in front of the head coil. The resulting close proximity of the cameras to the object allows precise tracking of its movement. During image acquisition, the MRI scanner uses this tracking information to prospectively compensate for head motion by adjusting gradient field direction and RF phase and frequency. Experiments performed on subjects demonstrate the system's robustness, exhibiting an accuracy of better than 0.1mm and 0.15˚.Item Pedogenesis in Rain Gardens: The Role of Earthworms and Other Organisms in Long-Term Soil Development(2009) Ayers, Emily Mitchell; Kangas, Patrick; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As bioretention comes into widespread use, it has become increasingly important to understand the development of bioretention soils over time. The objective of this research is to investigate the development of bioretention soils and the importance of ecological processes in the performance of rain gardens. The research includes descriptive studies of pre-existing rain garden soil profiles, laboratory experiments quantifying the effect of earthworms on infiltration rates, and a simulation model describing the influence of earthworms and soil organic matter on infiltration. Surveys of several different rain gardens of various ages provide the first detailed descriptions of rain garden soil profiles. The study revealed a great deal of biological activity in rain gardens, and evidence of pedogenesis even in very young sites. The uppermost soil layers were found to be enriched with organic matter, plant roots, and soil organisms. The field sites surveyed showed no signs of clogging due to the trapping of suspended solids carried in stormwater runoff. Some evidence was found of higher than expected infiltration rates at the field sites, which may be attributable to the effects of bioturbation by living organisms. The ability of earthworms to mitigate the effects of trapped suspended solids on bioretention soils was assessed in the laboratory. Results show that earthworms are capable of maintaining the infiltration rate of bioretention soils, but that their effects have a high degree of variability. This variability is attributed to soil aggregate instability caused by the oversimplification of the ecosystem. Other organisms play a significant role in stabilizing earthworm burrows and casts, and may be essential ingredients in a self-maintaining bioretention ecosystem. A simulation model of the action of earthworms on soil infiltration rates was developed in order to illustrate the physical processes taking place as a result of earthworm activity. The model was calibrated using data from the field study and microcosm experiment. This research is intended to provide a first glimpse into the biological processes at work in rain garden soils. The research shows that soil organisms are present in rain gardens, and suggests that their impact on bioretention performance may be significant.