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.

Agrivoltaic systems combine solar photovoltaic energy production with agriculture to improve land-use efficiency. We provide an upper-bound reduced-order cost estimate for widespread implementation of Agrivoltaic systems in the United States. We find that 20% of the US’ total electricity generation can be met with Agrivoltaic systems if less than 1% of the annual US budget is invested into rural infrastructure. Simultaneously, Agrivoltaic systems align well with existing Green New Deal goals. Widescale installation of Agrivoltaic systems can lead to a carbon dioxide (CO₂) emissions reduction equivalent to removing 71,000 cars from the road annually and the creation of over 100,000 jobs in rural communities. Agrivoltaics provide a rare chance for true synergy: more food, more energy, lower water demand, lower carbon emissions, and more prosperous rural communities.

The challenge of meeting growing food and energy demand while also mitigating climate change drives the development and adoption of renewable technologies ad approaches. Agrivoltaic systems are an approach that allows for both agricultural and electrical production on the same land area. These systems have the potential to reduced water demand and increase the overall water productivity of certain crops. We observed the microclimate and growth characteristics of Tomato plants (Solanum lycopersicon var. Legend) grown within three locations on an Agrivoltaic field (control, interrow, and below panels) and with two different irrigation treatments (full and deficit). Total crop yield was highest in the control fully irrigated areas a, b (88.42 kg/row, 68.13 kg/row), and decreased as shading increased, row full irrigated areas a, b had 53.59 kg/row, 32.76 kg/row, panel full irrigated areas a, b had (33.61 kg/row, 21.64 kg/row). Water productivity in the interrow deficit treatments was 53.98 kg/m³ greater than the control deficit, and 24.21 kg/m³ greater than the panel deficit, respectively. These results indicate the potential of Agrivoltaic systems to improve water productivity even for crops that are traditionally considered shade-intolerant.

Taylor’s frozen turbulence hypothesis is the central assumption invoked in most experiments designed to investigate turbulence physics with time resolving sensors. It is also frequently used in theoretical discussions when linking Lagrangian to Eulerian flow formalisms. In this work we seek to quantify the effectiveness of Taylor’s hypothesis on the field scale using water vapour as a passive tracer. A horizontally orientated Raman lidar is used to capture the humidity field in space and time above an agricultural region in Switzerland. High resolution wind speed and direction measurements are conducted simultaneously allowing for a direct test of Taylor’s hypothesis at the field scale. Through a wavelet decomposition of the lidar humidity measurements we show that the scale of turbulent motions has a strong influence on the applicability of Taylor’s hypothesis. This dependency on scale is explained through the use of dimensional analysis. We identify a ‘persistency scale’ that can be used to quantify the effectiveness of Taylor’s hypothesis, and present the accuracy of the hypothesis as a function of this non-dimensional length scale. These results are further investigated and verified through the use of large-eddy simulations.

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.