Odor Annoyance Assessment by Using Logistic Regression on an Example of the Municipal Sector

Cannabis Cultivation Facilities: A Review of Their Air Quality Impacts from the Occupational to Community Scale

This review addresses knowledge gaps in cannabis cultivation facility (CCF) air emissions by synthesizing the peer-reviewed and gray literature. Focus areas include compounds emitted, air quality indoors and outdoors, odor assessment, and the potential health effects of emitted compounds. Studies suggest that β-myrcene is a tracer candidate for CCF biogenic volatile organic compounds (BVOCs). Furthermore, β-myrcene, d-limonene, terpinolene, and α-pinene are often reported in air samples collected in and around CCF facilities. The BVOC emission strength per dry weight of plant is higher than most conventional agriculture crops. Nevertheless, reported total CCF BVOC emissions are lower compared with VOCs from other industries. Common descriptors of odors coming from CCFs include "skunky", "herbal", and "pungent". However, there are few peer-reviewed studies addressing the odor impacts of CCFs outdoors. Atmospheric modeling has been limited to back trajectory models of tracers and ozone impact assessment. Health effects of CCFs are mostly related to odor annoyance or occupational hazards. We identify 16 opportunities for future studies, including an emissions database by strain and stage of life (growing cycle) and odor-related setback guidelines. Exploration and implementation of key suggestions presented in this work may help regulators and the industry reduce the environmental footprint of CCF facilities.

Identification of origins and influencing factors of environmental odor episodes using trajectory and proximity analyses

It is challenging for the governmental agencies to provide an instant response and to systematically analyze the huge number of odor complaints which are received frequently by them. This study aimed to establish a data analysis framework featuring trajectory and proximity analyses to confirm odor origins, assess impact areas, and identify determinants and mechanisms of odor episodes based on odor reports. The investigation used 273 odor complaints reported in northern Collierville, Tennessee, between January 1st, 2019 and December 15th, 2020. The location of each complaint was geocoded in Google Map, and the backward wind trajectories were calculated using the web-based Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The nearby Eplex Landfill and Collierville Northwest Sewage Treatment Plant were targeted for the analyses. Odor impacts were evaluated with temporal and spatial characteristics of reported odor episodes. Logistic models were performed to identify weather parameters that significantly influenced odor occurrence. The field inspections indicated two periods targeting different sources. Period 1: from January 1st, 2019 to October 31st, 2020, the landfill appeared as the major source; Period 2: from November 1st, 2020 to December 15th, 2020, the sewage plant emerged as the major source. In Period 1, 65% of the complaints had wind transporting from the landfill, and 88% occurred at residences within 500 m of the landfill. In Period 2, 33% of the complaints had wind that blew from the sewage plant and 85% occurred at residences within 1000 m from the sewage plant. The likelihood of an odor episode day was significantly associated with wind speed [Odds Ratio (OR) = 0.66, 95% Confidence Interval (CI): 0.56-0.77], temperature (OR = 0.97, 95% CI: 0.95-0.98), and rainfall (OR = 1.02, 95% CI: 1.00-1.04). The odor issue in Collierville reflected poor zoning between the odor sources and residential areas. Separation distances of 500 m and 1000 m from the landfill and sewage facilities, respectively, are suggested to prevent odor issues. The proposed data analysis framework can be adopted by governmental agencies for fast responses to odor complaints, odor assessment, and environmental odor management.