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Various types of photovoltaic (PV) modules have been developed to exploit solar energy, a major renewable energy resource. One of the popular types of PV modules is building-integrated photovoltaics (BIPV), which are PV modules used as building materials. The goal of this study is to conduct an economic feasibility analysis of BIPV on the rooftop of the Keith D. McFarland Science Building at Texas A&M University, Commerce, Texas. To this end, a polynomial regression (PR) model is developed to estimate the electricity generation quantity of solar energy in the subject area, where the maximum temperature is 104 °F (40 °C) in summer. The developed PR models are used to estimate the potential profit of BIPV on the rooftop of the subject building, and the results are compared with the profit of a green roof system at the subject building. The economic feasibility analyses show that the levelized cost of electricity (LCOE) of the green roof system is approximately 39.77% higher than that of the BIPV system at a discount rate of 5%. Thus, the BIPV system is more profitable than the green roof system; consequently, this research will contribute to the implementation of BIPV on building rooftops and the expansion of renewable energy use in preference to fossil fuel. [ABSTRACT FROM AUTHOR]

Vetivergrass [Chrysopogon zizanioides (L.) Roberty] is a multi‐purpose crop that has an untapped potential for biofuel production. We conducted a field study at Temple, TX, to determine plant growth characteristics that make vetivergrass an ideal candidate bioenergy feedstock crop. Overall, the high biomass yield (avg. 18.4 ± 0.7 Mg ha−1) can be attributed to the high leaf area index (LAI, avg. 12.7 ± 2.5) and crop growth rates that ranged from 2.7 ± 0.1 to 15.7 ± 0.1 g m−2 d−1. Plant tissue N and P concentrations ranged from 0.59–1.66% and 0.06–0.15%, respectively. Surprisingly, the radiation use efficiency (RUE, avg. 2.2 ± 0.1 g MJ−1) was not high relative to other highly productive grasses. Biomass yield was highly correlated to plant height (avg. 2.1 ± 0.1 m) and LAI (Pearson, r = 0.96 and 0.77, respectively). Data from the field experiment provided plant coefficients that were used to develop an Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) vetivergrass model to assess dryland and irrigated interannual and spatial biomass yields across Texas. ALMANAC simulated dryland and irrigated yields ranged from 0.8–39.3 (avg. 17.2) Mg ha−1 and 9.1–47.0 (avg. 25.4) Mg ha−1, respectively. There was huge spatial variation in dryland and irrigated yields, with CV values of 20 and 15%, respectively. Similarly, dryland and irrigated inter‐annual yields respectively had CV values of 25 and 17%. State‐wide simulation model assessments complement field studies, and furthermore allow bioenergy companies and investors to better estimate biofuel feedstock potential for new crops such as vetivergrass. [ABSTRACT FROM AUTHOR]

This study aims at introducing a modeling and simulation approach for a green roof system which can reduce energy cost of a building exposed to high temperatures throughout the summer season. First, to understand thermal impact of a green roof system on a building surface, a field-based study has been conducted in Commerce, Texas, U.S., where the average maximum temperature in summer is 104 °F (40 °C). Two types of analyses were conducted: (1) comparison of temperature between different plant type via Analysis of variance (ANOVA) and (2) polynomial regression analysis to develop thermal impact estimation model based on air temperature and presence of a green roof. In addition, an agent-based simulation (ABS) model was developed via AnyLogic® University 8.6.0 simulation software, Chicago, IL, U.S., in order to accurately estimate energy cost and benefits of a building with a photovoltaic-green roof system. The proposed approach was applied to estimate energy reduction cost of the Keith D. McFarland Science Building at Texas A&M University, Commerce, Texas (33.2410° N, 95.9104° W). As a result, the proposed approach was able to save $740,325.44 in energy cost of a heating, ventilation, and air conditioning (HAVC) system in the subject building. The proposed approach will contribute to the implementation of a sustainable building and urban agriculture. [ABSTRACT FROM AUTHOR]

Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high. [ABSTRACT FROM AUTHOR]