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Quantifying Dissemination of Antibiotic Resistance Genes in Air from a Dairy Farm and Swine Farm
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Abstract This study explores the effects of various parameters on wake interactions between offshore wind farms, with a particular focus on the Revolution-Southfork Wind and Vineyard Wind projects. The research examines how factors such as Euclidean distances, turbine-rated power, rotor diameters, and the number of turbines at upstream farms impact the annual energy production (AEP) of downstream installations. The results reveal significant variations in AEP losses, with the Nygaard model demonstrating a marked sensitivity to changes in turbine-rated power, rotor diameter, and the differing Euclidean distances between farms. Our findings indicate that strategic planning regarding turbine characteristics and farm placements is essential for optimizing energy output and reducing wake-induced power losses. These insights lay the groundwork for further analytical research.more » « less
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Low-fidelity engineering wake models are often combined with linear superposition laws to predict wake velocities across wind farms under steady atmospheric conditions. While convenient for wind farm planning and long-term performance evaluation, such models are unable to capture the time-varying nature of the waked velocity field, as they are agnostic to the complex aerodynamic interactions among wind turbines and the effects of atmospheric boundary layer turbulence. To account for such effects while remaining amenable to conventional system-theoretic tools for flow estimation and control, we propose a new class of data-enhanced physics-based models for the dynamics of wind farm flow fluctuations. Our approach relies on the predictive capability of the stochastically forced linearized Navier–Stokes equations around static base flow profiles provided by conventional engineering wake models. We identify the stochastic forcing into the linearized dynamics via convex optimization to ensure statistical consistency with higher-fidelity models or experimental measurements while preserving model parsimony. We demonstrate the utility of our approach in completing the statistical signature of wake turbulence in accordance with large-eddy simulations of turbulent flow over a cascade of yawed wind turbines. Our numerical experiments provide insight into the significance of spatially distributed field measurements in recovering the statistical signature of wind farm turbulence and training stochastic linear models for short-term wind forecasting.more » « less
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In nine of the last 10 years, the United States Department of Agriculture (USDA) has reported that the average funds generated on-farm for farm operators to meet living expenses and debt obligations have been negative. This paper pieces together disparate data to understand why farm operators in the most productive agricultural systems on the planet are systematically losing money. The data-driven narrative we present highlights some troubling trends in US farm operator livelihoods. Though US farms are more productive than ever before, rising input costs, volatile production values, and rising land rents have left farmers with unprecedented levels of farm debt, low on-farm incomes, and high reliance on federal programs. For many US farm operators, the indicators of a “good livelihood”—stability, security, equitable rewards for work—are largely absent. We conclude by proposing three axes of intervention that would help US agriculture better sustain all farmers' livelihoods, a crucial step toward improving overall agricultural sustainability: (1) increase the diversity of people, crops, and cropping systems, (2) improve equity in access to land, support, and capital, and (3) improve the quality, accessibility, and content of data to facilitate monitoring of multiple indicators of agricultural “success.”more » « less
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This mixed methods study investigates student learning outcomes from undergraduate STEM and non-STEM courses, employing farm-situated place-based experiential learning (PBEL) modules at a private liberal arts university in the Midwest. Given that these courses occurred during both COVID-19 and U.S. police brutality protests, this study critically interrogates the influence of this "dual pandemic" on student meaning-making. The study examines how student scores on environmental science literacy, civic-mindedness, sense of place, and scientific reasoning measures changed throughout the PBEL courses. With the exception of scientific reasoning, change in each measure was statistically significant (p<0.001). A stepwise linear regression determined whether any measures predicted civic-mindedness. Environmental science literacy and university place attachment were found to be predictive of civic-mindedness. Focus group data revealed how PBEL modules affected student learning outcomes Forand how the dual pandemic affected student civic-mindedness and place attachment.more » « less
