UC Riverside

Different air pollutants have unique properties and spatial and temporal distributions that requiredifferent approaches to accurately measure and characterize them. This dissertation presents four different approaches for characterizing air pollutants in various regions using unmanned aerial systems (UAS), environmental chambers, and mobile laboratories. An onboard sensor-based UAS measurement system was developed to measure vertical ozone and particulate matter profiles in Riverside, CA from August to November 2020. The profiles were compared with ground monitoring and Community Multiscale Air Quality (CMAQ) model simulations. The study investigated the sensitivity of the model to various factors. The study found biases in the default versions of the model's planetary boundary layer (PBL) scheme and NOx emissions, which contribute the model's bias. The second project aimed to develop a solution for quantifying methane emissions using UAS. The sample collection system with wind estimation was validated for locating, identifying, and quantifying methane emissions. The results demonstrated the real potential of UAS for improving our understanding of emissions of methane and other greenhouse and pollutant gases. The third project studied new particle formation (NPF) and growth using the Captive Aerosol Growth and Evolution (CAGE) chamber system at the DOE Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site in Oklahoma. The study investigated the sensitivity of particle growth to injected seed particle composition, liquid water content, and precursor gases. The time dependence of the growth rate was quantified. The fourth project was conducted in the Houston, TX metropolitan area in the summer of 2022. A mobile laboratory was deployed at five sites over various atmospheric conditions to gather data on particle size distributions, cloud condensation nuclei activity, aerosol optical properties, aerosol composition, trace gas concentrations, and meteorological parameters. The collected data were analyzed to investigate the spatial and temporal variability and meteorological impacts on new particle formation and growth. These approaches using UAS, environmental chambers, and mobile laboratories are helpful for improving air pollution characterization. The results of these studies can be used to develop targeted and effective air quality control policies, and to provide insights for more accurate climate modeling.