We use the extensive set of aircraft and ground‐based observations from the NSF/National Center for Atmospheric Research (NCAR) and State of Colorado Front Range Air Pollution and Photochemistry Éxperiment and the NASA DISCOVER‐AQ experiments in summer 2014 together with the regional chemical transport model Weather Research and Forecast Model with Chemistry (WRF‐Chem) to study the ozone production and chemical regimes in the Northern Colorado Front Range (NFR). We apply the model's Integrated Reaction Rate capability and chemical tendencies diagnostics and present results from an in‐depth analysis of the ozone formation in various NFR regions for a case study of 12 August 2014. We further apply these diagnostics along a WRF online trajectory to assess the chemical evolution of an airmass during transport. The results show efficient ozone production within the NFR driven by the availability of NO_x and an abundance of highly reactive volatile organic compound and also continued ozone production during the transport into the mountains. We identify CO, formaldehyde, higher alkanes, acetaldehyde, and isoprene among the volatile organic compound species with the highest efficiency in ozone production. Formaldehyde and acetaldehyde concentrations in the NFR have a significant contribution from photochemical production, which in turn is linked back to methane oxidation and to emissions of higher alkanes, isoprene, ethane, and propane. This study provides valuable policy information into the chemical fingerprint of surface ozone in the NFR, an area that is in nonattainment of the U.S. EPA ozone health standards and demonstrates the capability of the newly added diagnostic tool in WRF‐Chem to address the drivers behind secondary production of pollutants in greater detail.

The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions from motor vehicle emission sources. It can estimate air pollutant, greenhouse gas, and air toxin criteria at any spatial resolution based on the spatiotemporal resolutions of input datasets. The CARS is designed to utilize local vehicle activity data, such as vehicle travel distance, road-link-level network geographic information system (GIS) information, and vehicle-specific average speed by road type, to generate an automobile emissions inventory for policymakers, stakeholders, and the air quality modeling community. The CARS model adopted the European Environment Agency's on-road automobile emissions calculation methodologies to estimate the hot exhaust, cold start, and evaporative emissions from on-road automobile sources. It can optionally utilize average speed distribution (ASD) of all road types to reflect more realistic vehicle speed variations. In addition, through utilizing high-resolution road GIS data, the CARS can estimate the road-link-level emissions to improve the inventory's spatial resolution. When we compared the official 2015 national mobile emissions from Korea's Clean Air Policy Support System (CAPSS) against the ones estimated by the CARS, there is a significant increase in volatile organic compounds (VOCs) (33 %) and carbon monoxide (CO) (52 %) measured, with a slight increase in fine particulate matter (PM_2.5) (15 %) emissions. Nitrogen oxide (NO_x) and sulfur oxide (SO_x) measurements are reduced by 24 % and 17 %, respectively, in the CARS estimates. The main differences are driven by different vehicle activities and the incorporation of road-specific ASD, which plays a critical role in hot exhaust emission estimates but was not implemented in Korea's CAPSS mobile emissions inventory. While 52 % of vehicles use gasoline fuel and 35 % use diesel, gasoline vehicles only contribute 7.7 % of total NO_x emissions, whereas diesel vehicles contribute 85.3 %. However, for VOC emissions, gasoline vehicles contribute 52.1 %, whereas diesel vehicles are limited to 23 %. Diesel buses comprise only 0.3 % of vehicles and have the largest contribution to NO_x emissions (8.51 % of NO_x total) per vehicle due to having longest daily vehicle kilometer travel (VKT). For VOC emissions, compressed natural gas (CNG) buses are the largest contributor at 19.5 % of total VOC emissions. For primary PM_2.5, more than 98.5 % is from diesel vehicles. The CARS model's in-depth analysis feature can assist government policymakers and stakeholders in developing the best emission abatement strategies.

The legal commercialization of cannabis for recreational and medical use has effectively created a new and almost unregulated cultivation industry. In 2018, within the Denver County limits, there were more than 600 registered cannabis cultivation facilities (CCFs) for recreational and medical use, mostly housed in commercial warehouses. Measurements have found concentrations of highly reactive terpenes from the headspace above cannabis plants that, when released in the atmosphere, could impact air quality. Here we developed the first emission inventory for cannabis emissions of terpenes. The range of possible emissions from these facilities was 66–657 t yr⁻¹ of terpenes across the state of Colorado; half of the emissions are from Denver County. Our estimates are based on the best available information and highlight the critical data gaps needed to reduce uncertainties. These realizations of inventories were then used with a regulatory air quality model, developed by the state of Colorado to predict regional ozone impacts. It was found that most of the predicted changes occur in the vicinity of CCFs concentrated in Denver. An increase of 362 t yr⁻¹ in terpene emissions in Denver County resulted in increases of up to 0.34 ppb in hourly ozone concentrations during the morning and 0.67 ppb at night. Model predictions indicate that in Denver County every 1000 t yr⁻¹ increase in terpenes results in 1 ppb increase in daytime hourly ozone concentrations and a maximum daily 8 h average (MDA8) increase of 0.3 ppb. The emission inventories developed here are highly uncertain, but highlight the need for more detailed cannabis and CCF data to fully understand the possible impacts of this new industry on regional air quality.