Categorization of nearshore sampling data using oil slick trajectory predictions

Area of Science:

• Environmental Chemistry
• Ecotoxicology
• Human Health Risk Assessment

Background:

• Oil spill chemicals (OSCs) pose significant risks to environmental and human health, particularly in coastal recreational zones.
• Accurate assessment of OSC concentrations in nearshore environments is crucial for human health risk evaluations.
• Understanding chemical distribution across environmental matrices is key to managing spill impacts.

Purpose of the Study:

• To evaluate nearshore sampling data of OSC concentrations.
• To categorize data based on proximity to oiling events (pre-oiling, post-oiling, unimpacted).
• To analyze concentration patterns within different environmental matrices and time-space categories.

Main Methods:

• Collected and categorized nearshore sampling data for OSC concentrations.
• Utilized an Oil Spill Trajectory Model to define time-space impact categories.
• Analyzed concentration data across environmental matrices (e.g., water, sediment).

Main Results:

• OSC concentrations were generally higher in post-oiling categories compared to pre-oiling and unimpacted categories.
• Distinct Polycyclic Aromatic Hydrocarbon (PAH) concentration patterns were observed within each matrix and category.
• Concentration frequency distributions for most chemicals followed a log-normal distribution.

Conclusions:

• Nearshore OSC concentrations vary significantly based on proximity to oiling events.
• Environmental matrices exhibit different patterns of chemical contamination.
• Log-normal distribution of chemical concentrations aids in statistical analysis and risk modeling.