Search for: All records

Expanding populations, the impacts of climate change, availability of arable land, and availability of water for irrigation collectively strain the agricultural system. To keep pace and adapt to these challenges, food producers may adopt unsustainable practices that may ultimately intensify the strain. What is a course of technological evolution and adoption that can break this cycle? In this paper we explore a set of technologies and food production scenarios with a new, reduced-order model. First the model is developed. The model combines limitations in the sustainable water supply, agricultural productivity as a function of intensification, and rising food demands. Model inputs are derived from the literature and historical records. Monte Carlo simulation runs of the model are used to explore the potential of existing and future technologies to bring us ever closer to a more sustainable future instead of ever farther. This is the concept of a moving sustainability horizon (the year in the future where sustainability can be achieved with current technological progress if demand remains constant). The sustainability gap is the number of years between the present and the sustainability horizon. As demand increases, the sustainability horizon moves farther into the future. As technology improves and productivity increases, the sustainability horizon is closer to the present. Sustainability, therefore, is achieved when the sustainability horizon collides with the present, closing the sustainability gap to zero. We find one pathway for water management technology adoption and innovation that closes the sustainability gap within the reduced-order model’s outputs. In this scenario, micro-irrigation adoption, minimal climate change impacts, reduced food waste, and additional transformative innovations such as smart greenhouses and agrivoltaic systems are collectively needed. The model shows that, in the absence of these changes, and continuing along our current course, the productivity of the agricultural system would become insufficient in the decade following 2050. 

Agrivoltaic systems are designed to mutually benefit solar energy and agricultural production in the same location for dual-use of land. This study was conducted to compare lamb growth and pasture production from solar pastures in agrivoltaic systems and traditional open pastures over 2 years in Oregon. Weaned Polypay lambs grew at 120 and 119 g head −1 d −1 in solar and open pastures, respectively in spring 2019 ( P = 0.90). The liveweight production between solar (1.5 kg ha −1 d −1 ) and open pastures (1.3 kg ha −1 d −1 ) were comparable ( P = 0.67). Similarly, lamb liveweight gains and liveweight productions were comparable in both solar (89 g head −1 d −1 ; 4.6 kg ha −1 d −1 ) and open (92 g head −1 d −1 ; 5.0 kg ha −1 d −1 ) pastures (all P > 0.05) in 2020. The daily water consumption of the lambs in spring 2019 were similar during early spring, but lambs in open pastures consumed 0.72 L head −1 d −1 more water than those grazed under solar panels in the late spring period ( P < 0.01). No difference was observed in water intake of the lambs in spring 2020 ( P = 0.42). Over the entire period, solar pastures produced 38% lower herbage than open pastures due to low pasture density in fully shaded areas under solar panels. The results from our grazing study indicated that lower herbage mass available in solar pastures was offset by higher forage quality, resulting in similar spring lamb production to open pastures. Our findings also suggest that the land productivity could be greatly increased through combining sheep grazing and solar energy production on the same land in agrivoltaics systems. 

Abstract Habitat for pollinators is declining worldwide, threatening the health of both wild and agricultural ecosystems. Photovoltaic solar energy installation is booming, frequently near agricultural lands, where the land underneath ground-mounted photovoltaic panels is traditionally unused. Some solar developers and agriculturalists in the United States are filling the solar understory with habitat for pollinating insects in efforts to maximize land-use efficiency in agricultural lands. However, the impact of the solar panel canopy on the understory pollinator-plant community is unknown. Here we investigated the effects of solar arrays on plant composition, bloom timing and foraging behavior of pollinators from June to September (after peak bloom) in full shade plots and partial shade plots under solar panels as well as in full sun plots (controls) outside of the solar panels. We found that floral abundance increased and bloom timing was delayed in the partial shade plots, which has the potential to benefit late-season foragers in water-limited ecosystems. Pollinator abundance, diversity, and richness were similar in full sun and partial shade plots, both greater than in full shade. Pollinator-flower visitation rates did not differ among treatments at this scale. This demonstrates that pollinators will use habitat under solar arrays, despite variations in community structure across shade gradients. We anticipate that these findings will inform local farmers and solar developers who manage solar understories, as well as agriculture and pollinator health advocates as they seek land for pollinator habitat restoration in target areas. 

Solar energy has the potential to offset a significant fraction of non-renewable electricity demands globally, yet it may occupy extensive areas when deployed at this level. There is growing concern that large renewable energy installations will displace other land uses. Where should future solar power installations be placed to achieve the highest energy production and best use the limited land resource? The premise of this work is that the solar panel efficiency is a function of the location’s microclimate within which it is immersed. Current studies largely ignore many of the environmental factors that influence Photovoltaic (PV) panel function. A model for solar panel efficiency that incorporates the influence of the panel’s microclimate was derived from first principles and validated with field observations. Results confirm that the PV panel efficiency is influenced by the insolation, air temperature, wind speed and relative humidity. The model was applied globally using bias-corrected reanalysis datasets to map solar panel efficiency and the potential for solar power production given local conditions. Solar power production potential was classified based on local land cover classification, with croplands having the greatest median solar potential of approximately 28 W/m2. The potential for dual-use, agrivoltaic systems may alleviate land competition or other spatial constraints for solar power development, creating a significant opportunity for future energy sustainability. Global energy demand would be offset by solar production if even less than 1% of cropland were converted to an agrivoltaic system. 

Abstract Solar energy has the potential to offset a significant fraction of non-renewable electricity demands globally, yet it may occupy extensive areas when deployed at this level. There is growing concern that large renewable energy installations will displace other land uses. Where should future solar power installations be placed to achieve the highest energy production and best use the limited land resource? The premise of this work is that the solar panel efficiency is a function of the location’s microclimate within which it is immersed. Current studies largely ignore many of the environmental factors that influence Photovoltaic (PV) panel function. A model for solar panel efficiency that incorporates the influence of the panel’s microclimate was derived from first principles and validated with field observations. Results confirm that the PV panel efficiency is influenced by the insolation, air temperature, wind speed and relative humidity. The model was applied globally using bias-corrected reanalysis datasets to map solar panel efficiency and the potential for solar power production given local conditions. Solar power production potential was classified based on local land cover classification, with croplands having the greatest median solar potential of approximately 28 W/m². The potential for dual-use, agrivoltaic systems may alleviate land competition or other spatial constraints for solar power development, creating a significant opportunity for future energy sustainability. Global energy demand would be offset by solar production if even less than 1% of cropland were converted to an agrivoltaic system. 

Abstract. Near-surface wind speed is typically only measured by point observations. The actively heated fiber-optic (AHFO) technique, however, has thepotential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scaleprocesses. Before AHFO can be widely used, its performance needs to be tested in a range of settings. In this work, experimental results on thisnovel observational wind-probing technique are presented. We utilized a controlled wind tunnel setup to assess both the accuracy and the precisionof AHFO under a range of operational conditions (wind speed, angles of attack and temperature difference). The technique allows for wind speedcharacterization with a spatial resolution of 0.3 m on a 1 s timescale. The flow in the wind tunnel was varied in a controlledmanner such that the mean wind ranged between 1 and 17 m s−1. The AHFO measurements are compared to sonic anemometer measurements andshow a high coefficient of determination (0.92–0.96) for all individual angles, after correcting the AHFO measurements for the angle ofattack. Both the precision and accuracy of the AHFO measurements were also greater than 95 % for all conditions. We conclude that AHFO has thepotential to measure wind speed, and we present a method to help choose the heating settings of AHFO. AHFO allows for the characterization ofspatially varying fields of mean wind. In the future, the technique could potentially be combined with conventional distributed temperature sensing(DTS) for sensible heat flux estimation in micrometeorological and hydrological applications.