ALBERT

Description: Laser diodes preferable to conventional lasers or incandescent lamps for Schlieren flow analysis because they are smaller, more rugged, less costly and have lower power requirements.

Description: Comparing paleoclimate time series is complicated by a variety of typical features, including irregular sampling, age model uncertainty (e.g., errors due to interpolation between radiocarbon sampling points) and time uncertainty (uncertainty in calibration), which—taken together—result in unequal and uncertain observation times of the individual time series to be correlated. Several methods have been proposed to approximate the joint probability distribution needed to estimate correlations, most of which rely either on interpolation or temporal downsampling. Here, we compare the performance of some popular approximation methods using synthetic data resembling common properties of real world marine sediment records. Correlations are determined by estimating the parameters of a bivariate Gaussian model from the data using Markov Chain Monte Carlo sampling. We complement our pseudoproxy experiments by applying the same methodology to a pair of marine benthic O records from the Atlantic Ocean. We find that methods based upon interpolation yield better results in terms of precision and accuracy than those which reduce the number of observations. In all cases, the specific characteristics of the studied time series are, however, more important than the choice of a particular interpolation method. Relevant features include the number of observations, the persistence of each record, and the imposed coupling strength between the paired series. In most of our pseudoproxy experiments, uncertainty in observation times introduces less additional uncertainty than unequal sampling and errors in observation times do. Thus, it can be reasonable to rely on published time scales as long as calibration uncertainties are not known.

Description: Plastic pollution in inland waters and the open ocean is a long recognized problem for marine wildlife, coral reefs,the fishing industry and shipping transport safety. Microplastics, defined as particles 〈 5 mm, form a considerableportion of this pollution and have increasingly received public attention following recent discoveries that not onlycan these particles be ingested by planktonic animals, but also outnumber natural food items in some ocean ar-eas. Microplastic research has mainly concentrated on open seas, while riverine plumes and coastal areas remainlargely unexplored despite their hypothesized importance as microplastic sources. This work models coastal accu-mulation along the Adriatic coastline of microplastic particles (1-5 mm) emitted by the Po River, northern Italy,over 1.5 years. We hypothesize that river-induced microplastic accumulation on adjacent coasts can be predictedusing (1) hydrodynamic-based and (2) remote sensing-based modelling. Model accumulation maps were validatedagainst sampling at nine beaches (analyzed particle size range: 1-5 mm), with sediment microplastic concentra-tions up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed that discharged particle amount is onlysemi-coupled to beaching rates, which are strongly river mouth dependent and occur primarily within the first tendays after discharge. Particles which did not beach within this period, representing more than 80% of all modelledparticles, were transported offshore and remained offshore. Remote sensing modelling was found to better captureriver mouth relative strength, and accumulation patterns were found largely consistent with hydrodynamic mod-elling. Comparison with remote sensing based accumulation maps and validation against in situ beach samplingare discussed. Suggestions are presented for future development of an operational monitoring system to assessmicroplastic pollution being emitted by a major river and its distribution along adjacent coastlines as well as intothe open ocean.