Abstract
The assessment of historical data is important to understand long-term changes in the marine environment. Whereas time series analyses based on monitoring data typically span one or two decades, this work aimed to integrate 40 years of monitoring and research data on polychlorinated biphenyls (PCBs) and metals in the Belgian Part of the North Sea (BPNS). Multiple challenges were encountered: sampling locations changed over time, different analytical methods were applied, different grain size fractions were analyzed, appropriate co-factors were not always analyzed, and measurement uncertainties were not always indicated. These issues hampered the use of readily available, highly standardized trend modeling approaches like those proposed by regional sea conventions such as OSPAR, named after the Oslo and Paris conventions.Therefore, we applied alternative approaches, allowing us to include most older historical data that have been obtained during the nineteen seventies and eighties. Our approach included reproducible and quality controlled procedures from data collection up to data assessment. It included spatial clustering, data normalization and parametric linear mixed effect modeling. A Ward hierarchical clustering was applied on recently obtained contaminant data, as the basis for a spatial division of the BPNS into five distinct areas with different contamination profiles. To minimize the risk of normalization errors for the metal data analyses, four normalization approaches were applied and mutually compared: granulometric and nickel (Ni) normalization, next to two hybrid normalization methods combining aluminum (Al) and iron (Fe) normalization. The long-term models revealed decreasing trends for most metals, except zinc (Zn) for which three out of four models showed increasing concentrations in all five zones of the BPNS. Offshore sediments contained the lowest normalized mercury (Hg) and cadmium (Cd) concentrations but high arsenic (As) concentrations. Trend analysis revealed a strong decrease in PCB concentrations in the nineteen eighties and nineties, followed by a slight increase over the last decade. The extended timeframe for contaminant assessment, as applied in this study, is of added value for scientists and policy makers, as the approach allows to detect trends and effects of anthropogenic activities within the marine environment within a broad perspective.
Highlights
To evaluate the contamination status of the marine environment, it is important to compare actual concentrations of pollutants with defined values below which no adverse effect is expected, and to assess and understand how contamination evolves over time
This paper presents a unique approach to assess more than four decades of PCB and metals monitoring data, in which spatial clustering, alternative normalization approaches and parametric trend modeling are combined to gain insight in long-term trends in PCB and metal contamination in marine sediments of the Belgian part of the North Sea (BPNS)
Four datasets have been used: (Dataset 1- DS1) the main dataset for trend modeling as compiled during the 4DEMON project, spanning four decades (1971–2015) of marine monitoring data at the BPNS; (Dataset 2- DS2) a subset, spanning the period 2007–2011, which is used for the spatial clustering; (Dataset 3DS3) a number of fractionized sediment samples taken in March 2015, to determine optimal co-factors; and (Dataset 4- DS4) a number of pure sand samples, gathered in the most offshore zone of the BPNS in the period 2008–2014, to determine the normalization constants
Summary
To evaluate the contamination status of the marine environment, it is important to compare actual concentrations of pollutants with defined values below which no adverse effect is expected, and to assess and understand how contamination evolves over time. BAC values indicate whether contamination levels are “near background” (for naturally occurring substances) or “close to zero” (for man-made substances) (OSPAR, 2009). For these assessments, an eminent procedure is applied with a high degree of harmonization and standardization. The second approach relies on the use of a proxy to reflect the binding capacity of the sediment in function of its mineralogy and grain size This proxy or co-factor has to be a conservative element, like Aluminum (Al), which reflects the clay mineral content and whose content is unaffected by other contaminant inputs (Herut and Sandler, 2006)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
