<p>1st essay abstract:   </p> <p>This study investigates the economic rents of the wind energy industry in the U.S. and their economic impacts on local economies, using Benton and White counties in Indiana as study regions. By calibrating a partial equilibrium model using 2007-2010 data of the industry, we find a resource rent of $9.72/MWh. We then use a general equilibrium model with Dutch Disease features to study the optimal tax levied on this rent, and the economic impacts of redistributing the tax revenues back to the county residents. An exhaustive rent tax increases real county personal income by as high as 9.1% and as low as 2%, depending on the county’s features. Applying an incentive compatible resource rent tax rate and redistributing the revenues to the county’s laborers leads to an increase of 3.5% and 16% in their income in White and Benton counties, respectively. We also perform robustness checks by allowing labor mobility between counties to examine the impacts of resource rents on the county economy under endogenous labor growth. </p> <p>1st essay data: All data acquired comes from the U.S. Census Bureau, county Quarterly Census of Employment and Wages, the National Renewable Energy Laboratory reports, the Lawrence Berkeley Laboratory, Indeed.com, news articles, and wind developers websites.</p> <p><br></p> <p>2nd essay abstract:   </p> <p>Using the Regional Energy Deployment System (ReEDS) model, we estimate the deadweight loss imposed by county-level wind power development restrictions in the form of increased electricity costs due to suboptimal siting. This is accomplished by optimizing the power system of the United States' Midcontinent Independent System Operator (MISO) from 2020 to 2050. We perform the optimization with and without land-use constraints arising from simulated potential local ordinances restricting wind power development, and under multiple scenarios reflecting different renewable portfolio standards (RPS). We find that local restrictions on wind power increase the total system cost by 0.15%-0.3% and the wholesale electricity price by 1.8%-2.7%, depending on the RPS scenario. Changes in the generation and installed capacity mixes are more substantial and depend on both the level of county restrictions on wind power, and RPS requirements, thus indicating an interaction between RPS requirements and local wind power restrictions. We also find that plausible restrictions on wind development do not pose major barriers to meeting renewable energy targets in a cost-effective manner.</p> <p>2nd essay data: All data is embedded inside the Regional Energy Deployment System (ReEDS) model of the National Renewable Energy Laboratory.</p> <p><br></p> <p>3rd essay abstract:   </p> <p>The USDA promotes adoption of conservation practices beneficial for soil health and environment through agricultural cost-share payment programs such as EQIP or CSP. Although the efficiency of these programs has been evaluated through additionality estimates, which represent the percentage of farmers who would adopt a practice only with payments, the potential complementarities between certain combinations of practices have often been overlooked. Unaccounted for, these complementarities may impact additionality estimates. This paper provides a thorough investigation of additionality estimates of common practices, including no-till, nutrient management and cover crops, accounting for potential complementarities between them. We find no significant differences between traditional additionality estimates and estimates accounted for potential complementarities between the three practices. The results thus indicate that despite agronomic evidence of synergies in co-adopting these three practices, we find no solid indication of adoption complementarity between them in reality. </p> <p>3rd essay data: Data is acquired from the U.S. Department of Agriculture and Esri maps.</p>

<p>Field-edge buffers are a promising way to address nonpoint source pollution from agricultural runoff, but concentrated runoff flow often renders standard fixed-width linear buffers ineffective. AgBufferBuilder (ABB) is a tool within ESRI ArcMap Geographic Information Systems software that designs and evaluates targeted, nonlinear buffers based on hydrologic modeling and other field-specific parameters. We tested ABB on n=45 Areas of Interest (AOIs) stratified based on estimated sediment loading across three sub-watersheds within Michigan’s Saginaw Bay watershed to evaluate the effectiveness of ABB relative to existing practices across a wide range of landscape conditions. We modeled tractor movement around ABB buffer designs to assess more realistic versions of the likely final designs. ABB regularly failed to deliver the desired 75% sediment capture rate using default 9 m x 9 m output raster resolution, with Proposed buffers capturing from 0% to 68.49% of sediment within a given AOI (mean=37.56%). Differences in sediment capture between Proposed and Existing buffers (measured as Proposed – Existing) ranged from -48% to 66.81% of sediment (mean=24.70%). Proposed buffers were estimated to capture more sediment than Existing buffers in 37 of 45 AOIs, representing potential for real improvements over Existing buffers across the wider landscape. In 13 of 45 AOIs, ABB buffers modified for tractor movement captured more sediment than Existing buffers using less total buffer area. We conducted a collaborative design process with three Saginaw Bay watershed farmers to assess their willingness to implement ABB designs. Feedback indicated farmers may prefer in-field erosion control practices like cover cropping and grassed waterways over field-edge ABB designs. More farmer input is needed to better assess farmer perspectives on ABB buffers and to identify preferred data-based design alternatives. Engineered drainage systems with raised ditch berms and upslope catch basins piped underground directly into ditches were encountered several times during site visits. ABB only models surface flow and does not recognize drain output flow entering waterways. Modified ABB functionality that models buffers around drain inlets would greatly improve its functionality on drained sites. This may be accomplishable through modification of user-entered AOI margins but requires further investigation. Unfortunately, the existing tool is built for outdated software and is not widely accessible to non-expert users. We suggest that an update of this tool with additional functionality and user accessibility would be a useful addition in the toolbox of conservation professionals in agricultural landscapes.</p>