Maximilian Chmielinski

Project title: Ultraviolet Radiation Exposure in Cannabis Farms

Degree: PhD | Program: Environmental Public Health (EPH) | Project type: Thesis/Dissertation
Completed in: 2023 | Faculty advisor: Christopher D. Simpson


Laws permitting growth and possession of cannabis for medicinal and recreational use are currently changing rapidly in the United States (U.S.) and internationally. (Carliner et al., 2017; Caulkins et al., 2018; Mahamad and Hammond, 2019) While cultivation and use of cannabis is still considered illegal by the U.S. federal government, multiple U.S. states have passed laws legalizing recreational or medical use of marijuana. (Carliner et al., 2017) Canada has also recently legalized cannabis. (Mahamad and Hammond, 2019) These changes have led to a dramatic expansion of the legal cannabis industry, which now employs approximately 420,000 workers in U.S., and job-growth is among the fastest of any industry in the U.S. (Borchardt, 2017; Barcott et al., 2022) The scale and growth of the industry stands in juxtaposition with federal laws that continue to criminalize cannabis farming, and the contrast impacts the occupational health of a large, novel, and growing group of agricultural workers. A direct impact of cannabis criminalization is the lack of research that has investigated the occupational hazards faced by workers in this emerging industry. (Simpson, 2017) Many cannabis farms grow their crop using artificial lighting, the sun, or a combination of both throughout a crop cycle. The lamps used may emit ultraviolet radiation (UV), and UV overexposure causes a range of negative health outcomes. (IARC, 2012)⁠ Currently, no studies have investigated UV overexposure in this industry, with most existing publications still limited to exploratory overviews of potential occupational hazards. (Martyny et al., 2013; CDPHE, 2017, 2019) However, research investigating specific occupational hazards has begun to trickle into the literature, with some investigated occupational topics including exposure to mold (Green et al., 2018; Couch, Burton, Victory, Green, Lemons, Nayak and Donald H Beezhold, 2019) and exposure to particulate matter and volatile organic compounds. (Silvey et al., 2020) In this thesis, we address three issues related to UV exposure in cannabis farms.

In chapter 2 – we summarize measurements of UV exposure in five cannabis farms, including indoor, outdoor and shade house facilities. Lamp emission testing was performed at each facility and worker exposures to UV radiation (UVR) was measured for 87 work-shifts. Observations of worker activities and use of personal protective equipment in association with the UVR exposure measurements were recorded. For lamp emission measurements, at three feet from the center of the lamp in the 180 to 400nm range, the average irradiances were 4.09x10-4, 6.95x10-8, 6.76x10-9, 3.96x10-9, 1.98x10-9 effective W/cm2 for germicidal lamps, metal halide lamps, high pressure sodium lamps, fluorescent lamps, and light emitting diodes, respectively. The average UVR exposure measured on the workers was 2.91x10-3 effective J/cm2 (range: 1.54x10-6, 1.57x10-2 effective J/cm2). Thirty percent of the work-shifts monitored exceeded the American Conference for Governmental Industrial Hygienists threshold limit value of 0.003 effective J/cm2. Exposures were highest for workers who spent all or part of their work-shift outdoors, and solar radiation was the primary source of the workers’ UVR exposure for most of the work-shifts that exceeded the threshold limit values. Outdoor workers can reduce their UVR exposures by wearing appropriate personal protective equipment. Although the artificial lighting used in the cannabis production facilities included in this study did not contribute substantially to the measured UV exposures, in many cases the lamp emissions would generate theoretical exposures at three feet from the center of the lamp that would exceed the TLV. Therefore, employers should choose low UVR emitting lamps for indoor grow operations and should use engineering controls (e.g., door-interlocks to de-energize lamps) to prevent worker exposure to UVR from germicidal lamps.

In chapter 3 we developed a wearable spectroradiometer to address the limitation of spectral mismatch inherent in all available broadband dosimeters. We developed a microcontroller system and platform that allows for researchers to mount and deploy the Ocean Insight Flame-S Spectroradiometer as a wearable device for measurement of UV and visible wavelengths (300 to 700 nm). The platform validation consisted of comparing measurements from a solar simulator at three different intensities taken under platform control with measurements taken with the spectrometer controlled by a personal computer running the software provided by the spectroradiometer manufacturer. Three Mann–Whitney U-Tests (two-tailed, 95% CI), one for each intensity condition, compared the central tendency between the total spectral power (TSP), the integral of a spectrum measurement, measured under both control schemas. An additional analysis of per pixel agreement and overall platform stability was performed. The three Mann–Whitney tests returned no significant difference between the set of TSPs for each filter condition. These results demonstrate that the spectroradiometer takes measurements of equivalent accuracy under both control schemas and can be deployed as a wearable device for the measurement of wavelength resolved UV and visible radiation. In Chapter 4 we developed and evaluated a vegetative radiative transfer model (VRTM) for predicting worker exposure to non-ionizing radiation – as a surrogate for exposure to UV radiation - in 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 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 to 700nm), blue (400 to 500nm), green (500 to 600nm), and red (600 to 700nm) 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 UVR.