Sampling Strategies, Methodologies, and Modeling of Complex Mixtures within Galveston Bay and the Houston Ship Channel
Abstract
With recent climate data indicating a likely increase in future heavy precipitation events, Galveston Bay and the Houston Ship Channel (GB/HSC) serve as a natural case-study for disaster response research. For example, the region is known to be affected by regular flooding events and hurricanes. GB/HSC is also an urban estuary where several chemical classes have historically been detected in the region (e.g., PCBs, dioxins/furans (Dx/F), pesticides, metals). One chemical class of interest for this research are polycyclic aromatic hydrocarbons (PAHs). PAHs are ubiquitous and a representative complex mixture due to variable origins and excessive levels in the environment may cause adverse health effects.
After Hurricane Harvey, sediment redistribution within the City of Houston and Galveston Bay was a concern for both disaster response research (DR2) and environmental health. This research uses several tools to identify a representative complex environmental mixture within GB/HSC. The first tool used is a systematic evidence map (SEM), where (Dx/F) and mercury (Hg) were identified as the most common chemicals detected in GB/HSC. However, chemical data were inconsistently recorded, which made it difficult to discern whether a baseline chemical dataset existed. The second tool used is a geospatial technique called kriging. This particular tool is used to estimate PAH concentrations within GB/HSC sediments after Hurricane Harvey. Our comparative analysis with historical data found a small, but detectable increase in surface sediment PAH concentrations; however, the levels detected did not exceed sediment quality guideline levels.
The third tool applied in this research was a KinExA Inline Biosensor (biosensor) technology. This biosensor uses a monoclonal antibody to quantify available PAHs in porewater (Cfree). By detecting Cfree PAH concentrations, the goal was to prioritize environmental samples for targeted analysis, since traditional methods (e.g., gas chromatography-mass spectrometry) are resource and time intensive. Our results show the biosensor is a rapid and cost-effective field ready technology capable of detecting Cfree in both soils and sediments. Collectively, the results of this dissertation share three tools capable of characterizing complex environmental mixtures. The findings from this dissertation will be useful for exposure science, DR2, public health, and environmental risk assessment.
Citation
Camargo, Krisa M (2021). Sampling Strategies, Methodologies, and Modeling of Complex Mixtures within Galveston Bay and the Houston Ship Channel. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /195621.