Location: Application Technology ResearchTitle: Modeling natural light availability in skyscraper farms
|EATON, MICHAEL - Cornell University - New York|
|SHELFORD, TIMOTHY - Cornell University - New York|
|MATTSON, NEIL - Cornell University - New York|
Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/2021
Publication Date: 8/24/2021
Citation: Eaton, M., Harbick, K.J., Shelford, T., Mattson, N.S. 2021. Modeling natural light availability in skyscraper farms. Agronomy. 11(9). Article 1684. https://doi.org/10.3390/agronomy11091684.
Interpretive Summary: A skyscraper farm is a proposed design for a controlled environment agriculture (CEA) facility. Some have claimed that a glass exterior would allow in sufficient light that minimal supplemental lighting would be required, however to our knowledge this hasn't been rigorously modeled until now. Several computer models were created to compare natural light availability of different combinations of skyscraper dimensions, adjacent buildings, and location. The primary finding is that skyscraper farms would require considerably more supplemental light, and therefore energy, than greenhouse systems with equivalent yield. This is largely due to the fact that when sunlight is maximized at high sun angles, blocking of natural light from the floor above is also maximized. Only the top floor of the building would receive a significant amount of natural light, if it had a glass roof.
Technical Abstract: Lighting is a major component of energy consumption in controlled environment agriculture (CEA) operations. Facilities must meet crop lighting requirements with electrical lighting sources when natural light is insufficient. Skyscraper farms (multilevel production in buildings with transparent glazing) have been proposed as alternatives to greenhouse or plant factories (multilevel production in opaque warehouses) in an attempt to increase space use efficiency while accessing some natural light. However, there are no previous models on natural light availability and distribution in skyscraper farms. Quantifying the amount of light available for plant growth in skyscraper farms can inform designers about the energy impacts of these proposed structures. This study investigated the effects of building geometry and context shading on the availability and spatial distribution of natural light in skyscraper farms for two U.S. locations, Los Angeles (LA) and New York City (NYC). Electric energy consumption for supplemental lighting in 20-story skyscraper farms to reach a daily light integral target for each building level was calculated using simulation results. The computer drafting program Rhinoceros 6 was used to draft building models, the “DIVA for Rhino” software package was used to integrate Rhinoceros 6 with lighting simulation software, Radiance. Using these programs, annual daylight simulations were conducted in hourly time-steps to quantify the natural light available within the interior of the buildings throughout the year. Solar conditions for each location were modeled using the corresponding “Typical Meteorological Year” (TMY) dataset. Natural lighting in our baseline Skyscraper farms in NYC and LA without surrounding buildings provides 13% and 15% of the light required to meet a target of 17 mol m-2 day-1. Comparing the different building configurations – the more elongated buildings which have greater perimeter area require less supplemental light than the squarer building configurations, where up to 27% of the lighting requirements may come from natural light. Though, shading from surrounding buildings can reduce the natural light available considerably; in the worst case, natural light only supplies 5% of the lighting requirements given a dense urban context. Overall, skyscraper farms require between 4-11 times more input for lighting than greenhouses per crop canopy area in the same location. We conclude that the accessibility of natural light in skyscraper farms in crowded urban settings provide little advantage over plant factories.