## 3 Results and Discussion
### Overall Litter Density and Sample Composition
With regard to the latter, 3% of the objects consisted of disposable face masks, highlighting a worryingly increasing trend of plastic dispersion derived from the recent and ongoing global pandemic [5]. These three categories together represented approximately 71% of beach litter (Figure 3b), while unknown objects and building material represented 23% and 5% of found objects, respectively. Moreover, even if this was not a great contribution to the litter, it is interesting to note that about 1% of the collected items (n = 3 detected in VG and TP) was represented by biofilm carriers from wastewater treatment plants (WWTPs). Considering the size distribution, the majority of the collected objects were of small size (less than 5 cm on the maximum axis) in almost all the sites. Only one site (CE) showed a similar number of litter objects in the <5 cm and 5-10 cm size classes (Figure S1). This is in accordance with other studies, both in the seawater and freshwater environments, and indicates that the fragmentation of plastic objects after their dispersion leads to a higher abundance of small particles [62; 63]. Polymer Degradation and Alteration of Collected Samples: Problems in Recognition and Possible Environmental Consequences  
Considering the comparison with the Open Specy database [52] for polymeric recognition, the most common polymers generally presented a reliable method of identification (especially PP and PE, with average R\({}^{2}\) values of 0.93 for PP and of 0.94 for PE), while other abundant polymers (i.e., PS and PU) showed a lower value for the Pearson coefficient (with average R\({}^{2}\) values of between 0.75 and 0.8, Table S2). Figure 3: Pie chart showing polymeric composition (**a**) and category (**b**) of the collected objects. In fact, since the reference databases of the plastics were largely composed of pure polymers, the chemical identification of plastic objects (often containing multi-polymer blends and a differential load of additives) might show different hindrances [64]. Moreover, different physicochemical processes are known to affect the FTIR spectra of aged plastic samples, such as UV radiation, thermo-oxidative processes, mechanical abrasion, and colonization by different microbial consortia (i.e., biofouling) [17]. All these issues negatively affect recognition efficiency. Specifically, oxidation processes can easily alter the FTIR spectra in the regions of the carboxylic (1800-1700 cm\({}^{-1}\)) and hydroxyl wavelengths (3500-3000 cm\({}^{-1}\)): this process is known to especially affect carbon backbone polymers (e.g., PE and PP [65], Figure 4) and it can be induced by thermo-oxidative or UV-induced oxidation and biodegradation [66; 67]. These are also the mechanisms that are known to lead to plastic embrittlement and mechanical instability, inevitably leading to the production of secondary MPs [68; 69]. In addition to polymer matrix oxidation, other chemical alterations can occur in plastic objects, such as the leaching of additives. The FTIR spectra of PET, for example, are observed to vary in relation to environmental deterioration [70], whereas native peaks decrease, the adsorption or release of additives may originate in new ones (Figure 4). Beyond changes in the FTIR spectra, the leaching of (toxic) additives can lead to increasing ecotoxicological effects in plastic polluted environments [71]. Additionally, the mechanical degradation of plastic polymers can lead to problems in their recognition, enhancing the surface roughness of the materials, and thus negatively affecting the signal-to-noise ratio [72]. In our study, the mechanical ageing of plastic objects is also observable by the high percentage of the unknown typologies of objects (fragments and degraded objects, Figure 3b), which account for almost 25% of the sampled litter. Finally, biofouling is another phenomenon that is known to affect plastic after its dispersion in the environment (and especially in water).