## 1 Introduction
Visual identification alone is not enough to draw any conclusions on the chemical nature of the marine litter, and this makes source assignment impossible for meso- and microplastics. Raman or Fourier transform infrared (FTIR) spectroscopy is often used in combination with visual identification under the microscope in laboratory settings [11]. A common disadvantage of these methods is that they are expensive, require qualified staff, and have to be placed in the laboratory and thus cannot be used in the field. Marine litter engages the general public, but this unexploited capacity has not been utilized to its full extent in, for example, the Citizen Science [12; 13]. Standardized methods--sampling and identification--of marine plastic litter should be developed in such a way that the results can be fed into international monitoring strategies to map plastic pollution distribution. Only with large scale monitoring and source identification will mitigation measures be efficient. The development of easy to use \"plug and play devices\" to identify polymer types down to the microplastic range (1 mm) is expected to help bridge science to society. Recently, a number of hand-held near-infrared spectrometers were developed [14; 15; 16] that could be a good alternative to very expensive, large, and complicated techniques, i.e., FTIR. Some of these instruments have already been applied to polymer identification in line with the complex methods of classes classification. Examples are an identification system of plastic solid waste based on NIR spectroscopy in combination with support vector machine [15], with machine learning models [16] or hyper spectral imaging [17]. In this paper, we describe our experience in the application of a simple method to detect polymer type down to the micro range (1 mm) using a portable NIR spectrometer MicroNIR that is expected to be a major step towards large-scale monitoring of marine plastic litter. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Full Name** & **Short Name** & **RIC** & **Density, g/cm\({}^{3}\)** & \begin{tabular}{c} **Worldwide** \\ **Production, \%** \\ \end{tabular} & \
\begin{tabular}{c} **Found on the beaches,** \\ **\% of Total Litter** \\ \end{tabular} & **Products** \\ \hline Polyethylene & PET & 1 & 1.3-1.4 & _7.7_ & 9 & Bottles for water, soft drinks, juices, cleaners, polyester fabric, etc. \\ \hline Polyethylene high & HDPE & 2 & 0.93-0.97 & 12.2 & 11 & Toys, milk bottles, shampoo bottles, pipes, houseware, etc. \\ \hline Polyvinylchloride & PVC & 3 & 1.3-1.45 & 10 & - & Window frames, profiles, floor and wall covering, pipes, cable insulation, etc. \\ \hline Polyethylene low density & LDPE & 4 & 0.91-0.94 & 17.5 & 17 & Bagg, trays and containers, agricultural film, food packaging film, etc. \\ \hline Polypropylene & PP & 5 & 0.895-0.92 & 19.3 & 24 & Food packaging, sweet and snack wrappers, hinged caps, microwave containers, pipes, automotive parts, etc. \\ \hline Polystyrene & PS & 6 & 0.96–1.02 & 6.4 & 7 & Food packaging, building insulation, electrical and electronic equipment, inner liner for ridges, eyeglasses frames, etc. \\ \hline Polyurethane & PUR &
\begin{tabular}{c} 7 \\ (other) \\ \end{tabular} & 0.87–1.42 & _7.9_ & - & Building insulation, pillows and mattresses, insulating foams for ridges, etc. \\ \hline Polyamide & PA & 7 & 1.13-1.4 & \(\sum=19\) & - & Fishing lines, nylon fabric (PA); eyeglasses lenses, roofing sheets (PC); medical implants, surgical devices, membranes, protective coatings, etc. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Worldwide production of different polymer types and their discovery on beaches.