Streamlining long-term trends detection in benthic contamination: A Santa Monica Bay (USA) test case

Area of Science:

• Environmental Science
• Marine Chemistry
• Time Series Analysis

Background:

• Benthic contamination trends are crucial for environmental management and sustainable practices.
• Traditional trend analysis using time series plots often lacks clarity due to seasonality and irregularities.
• A robust method is needed to accurately assess long-term environmental contamination trends.

Purpose of the Study:

• To develop and demonstrate a method for unambiguously identifying trends in benthic contamination.
• To analyze long-term trends of specific contaminants (DDTs, PCBs, Cr, Cu, As, Zn, Pb, Ni) and sediment grain size.
• To evaluate the method's ability to handle data gaps and analytical changes.

Main Methods:

• Applied a time series analysis method to suppress seasonality and irregularity components.
• Analyzed sediment data collected over 33 years from three distinct stations in Santa Monica Bay, California.
• Utilized linear regression to assess contaminant trends and correlations with sediment grain size.

Main Results:

• All analyzed contaminants (DDTs, PCBs, Cr, Cu, As, Zn, Pb, Ni) and fine grain proportions showed unambiguous downward trends at all three stations (r² = 1.00).
• Rates of decrease were similar at the outfall and coastline stations, but faster in the canyon station.
• No significant correlation was observed between contaminant levels and fine grain proportions at C1 and E6, but was observed at Z2. Correlations between effluent and outfall sediment contaminant levels were not observed.

Conclusions:

• The proposed time series analysis method effectively clarifies long-term benthic contamination trends.
• Sediment contamination has unambiguously decreased across multiple stations in Santa Monica Bay over 33 years.
• The study highlights the method's utility in environmental monitoring and risk assessment, accommodating data complexities.