Characterization of Air Quality Disparities in Inland Southern California
In this work, we seek to determine the spatiotemporal variability in personal exposure to PM2.5 in the inland portion of the Basin, where emissions sources are commonly adjacent to residential areas and secondary pollutant formation is extensive. Further, few personal exposure studies have been conducted for the inland Basin compared to the neighboring, coastal counties of Orange and Los Angeles. In a pilot study, we measure daily PM2.5 exposure for 18 community participants from diverse backgrounds each for one week using advanced, real-time, wearable monitoring technology that samples every 15 seconds. Participants are also outfitted with fast-response GPS data loggers for precise microenvironment characterization. Results elucidate the microenvironments in the Inland Basin that pose the highest risks for PM2.5 exposure. We stratify results by median household income to investigate the relationship between socioeconomic status and exposure in this unique, mixed land-use area.
Sasser et al., Journal of Exposure Science & Environmental Epidemiology (Accepted)
Ozone Responses to Meteorological Phenomena in the South Coast Air Basin
The South Coast Air Basin of California has achieved tremendous reductions in ozone and particulate matter levels over the last five decades, but has recently experienced a leveling off of the reductions and even an uptick in ozone in 2016 and 2017. The immediate question is why? Related to this is how much is related to meteorological trends versus a response to emissions changes? Answering these questions is difficult given the complexities of accurately tracking emissions changes, characterizing all of the meteorological and climate variables that can impact ozone, and the complexities of the formation and fate of ozone and PM on top of the role of long range transport of pollutants impacting the region. In this work, traditional chemical transport modeling and meteorological detrending approaches, as well as “big-data” (e.g., machine learning) approaches are used to investigate why ozone may have increased in the past couple of years. While there are uncertainties in the use of any one of these techniques, together they should provide a much more robust understanding of the likely causes.
Dynamic Emission and Exposure Management
With exponential advancements in environmental sensing capabilities and energy-saving technologies and diminishing computational limitations, implementing multidisciplinary approaches for addressing energy-technology-health challenges becomes more technologically feasible. Here we implement a system to address a growing challenge to collectively increase energy efficiency, reduce vehicular emissions, and protect air quality and human health. Our dynamic system will enable the direct assessment of the environmental impacts and exposure risks due to vehicular emissions and human mobility in the Inland Empire, a region historically burdened by disproportionate air pollution exposure and environmental justice challenges.
High Throughput In-Vitro Modeling of Environmental Pollutant Toxicity
The human exposome contains thousands of organic compounds that bioaccumulate or metabolize in the body and may lead to or exacerbate chronic illnesses. Here we begin to investigate the impact of exposure to trace levels of ambient and indoor air pollutants on targeted human systems and the conditions under which transport is hindered or promoted. We make use of novel in-vitro models to analyze a wide range of environmental conditions to best simulate variability in human exposures.
Ozone enhancement in Nevada from wildfires
We investigate ozone enhancement in rural Nevada due to smoke transport from California during the 2013 Rim Fire and 2014 King Fire. This work supports ongoing wildfire smoke exposure research at the University of Nevada Reno, where the health effects associations with high smoke exposure are under investigation.