Non-ionizing radiation modeling to predict ambient irradiance in work areas at an indoor cannabis farm

Abstract

Abstract Agricultural workers frequently experience potentially hazardous exposure to non-ionizing radiation from both solar and artificial sources, and measurement of this exposure can be expensive and impractical for large populations. This project develops and evaluates a vegetative radiative transfer model (VRTM) to predict irradiance in a grow room of an indoor cannabis farm. The model uses morphological characteristics of the crop, manufacturer provided lamp emissions data, and dimensional measurements of the grow room and cannabis hedgerows to predict irradiance. A linear regression comparing model predictions with the measurements taken by a visible light spectroradiometer had slopes within 23% of unity and R2 values above 0.88 for visible (400–700 nm), blue (400–500 nm), green (500–600 nm), and red (600–700 nm) wavelength bands. The excellent agreement between the model and the measured irradiance in the cannabis farm grow room supports the potential of using VRTMs to predict irradiance and worker exposure in agricultural settings. Because there is no mechanistic difference between visible and other non-ionizing wavelengths of radiation in regards to mechanisms of radiative transfer, the model developed herein for visible wavelengths of radiation should be generalizable to other radiation bands including infrared and ultraviolet radiation.