When will the TBT go away? Integrating monitoring and modelling to address TBT's delayed disappearance in the Drammensfjord, Norway

Abstract

Despite a substantial decrease in the use and production of the marine antifouling agent tributyltin (TBT), its continuing presence in harbors remains a serious environmental concern. Herein a case study of TBT's persistence in the Drammensfjord, Norway, is presented. In 2005, severe TBT pollution was measured in the harbor of the Drammensfjord, with an average sediment concentration of 3387 μg kg(-1). To chart natural recovery in the Drammensfjord, an extensive sampling campaign was carried out over six years (2008-2013), quantifying TBT in water, settling particles and sediments. The monitoring campaign found a rapid decrease in sediment TBT concentration in the most contaminated areas, as well as a decrease in TBT entering the harbor via rivers and urban runoff. Changes observed in the more remote areas of the Drammensfjord, however, were less substantial. These data, along with measured and estimated geophysical properties, were used to parameterize and calibrate a coupled linear water-sediment model, referred to as the Drammensfjord model, to make prognosis on future TBT levels due to natural recovery. Unique to this type of model, the calibration was done using a Bayesian Monte Carlo (BMC) updating approach, which used monitoring data to calibrate predictions, as well as reduce the uncertainty of input parameters. To our knowledge, this is the first use of BMC updating to calibrate a model describing natural recovery in a lake/harbor type system. Prior to BMC updating, the non-calibrated model data agreed with monitoring data by a factor of 4.3. After BMC updating, the agreement was within a factor 3.2. The non-calibrated model predicted an average sediment concentration in the year 2025 of 2.5 μg kg(-1). The BMC calibrated model, however, predicted a higher concentration in the year 2025 of 16 μg kg(-1). This discrepancy was mainly due to the BMC calibration increasing the estimated riverine and runoff TBT emission levels relative to the initial input levels. Future monitoring campaigns can be used for further calibration of emission levels, and a clearer prognosis of when natural recovery will remove TBT pollution.

Keywords: Bayesian Monte Carlo updating; Emissions; Monitored natural recovery; Sediment-water box model; Tributyltin.