UC Riverside

Aerosols particles (hereafter referred to as aerosols) impact the earth system, affecting climate, ecosystems, and health. To understand aerosols’ effects and mitigate their negative impacts we must understand the sources of aerosols and their properties. This work explores two case studies investigating sources: one investigating the sources of mineral dust aerosols and another the sources of aerosol absorption. Additionally, a technique for estimating the uncertainty in the full distribution optical closure method (FDCOM) of refractive index (m) calculations is presented.

In the first study, the sources of aerosols in the Salton Sea Basin, CA, were explored through 2 field campaigns. The Salton Sea Basin is a region of poor air quality, which is thought to be primarily controlled by natural dust emissions. Although mineral dust is often considered a natural source, recently observed increases in dust emissions reveal the importance of anthropogenic controls. In the first field campaign, PM10 was sampled in August 2015 and February 2016. In the second, passive dust samples were collected ~monthly from May 2017 to May 2018. Elemental composition and soluble anion content of the dust samples were used as inputs into positive matrix factorization (PMF). This investigation revealed multiple dust sources traceable to geologic features and anthropogenic activities. An emerging lakebed was identified as a new dust source, possibly worsening regional air quality.

In the second case study, secondary organic aerosol (SOA) generated from the nitrate oxidation of heterocyclic compounds (pyrrole, furan, and thiophene) was investigated as a potential source of absorbing organic aerosol. This investigation employed chamber experiments, on- and offline optical measurements, and on- and offline mass spectroscopy to explore the optical and chemical properties of the gas phase intermediates and aerosols. These experiments revealed pyrrole SOA as a potential source of absorbing aerosol and is possibly an important component of biomass burning SOA.

Lastly, a technique for estimating the uncertainty in FDOCM was developed. Uncertainties in FDOCM results were estimated by repeatedly performing the calculation with perturbed inputs. This method can be applied to help better constrain uncertainty in m calculations and ultimately yield more certain radiative forcing estimations.