Over the last 50 years, conventional fossil-based plastics have become an integral part of our everyday lives. Apart from their low production costs, this is due to a number of their unique properties, including durability, strength, lightness, electrical and thermal insulation, resistance to chemicals and corrosion. The production of plastics has increased from 1.5 million metric tons in 1950 to 359 million metric tons in 2018. Of this total, 61.8 million metric tons were produced in Europe. There are various problems associated with plastic use and disposal that pose a serious threat to both the physical environment and human health. Since public behaviour plays a key role when it comes to the use of plastic, this paper reports on a study that focused on an assessment of attitudes towards plastics and bioplastics in Europe. The results showed that packaging is the most frequent modality of plastic used among participants. In addition, majority of participants are aware that plastic waste can affect environment and human health and therefore segregate and properly dispose plastics. Also, even though most respondents were aware of the environmental problems related to plastic use and showed a positive inclination towards using bioplastic materials, their limited availability and lack of relevant information about bioplastics pose a problem for wider use. Departing from the assumption that the public attitude is a determining factor in the consumption of plastics as a whole and bioplastics in particular, this paper also sheds some light on the current situation, identifying some trends and information gaps which should be addressed in order to encourage a more rational use of plastics in Europe.

In recent years, an increasing trend towards replacement of conventional fossil-based plastics with bio-based plastics was noticed, i.e., production of plastics partly or fully made from biomass is rapidly expanding. Currently, bio-based and biodegradable plastics have a very small market size, approximately only 1% of all plastics produced. However, the forecast of the global bioplastics production capacities predicts an increase from approximately 2.417 million tonnes in 2021 to approximately 7.593 million tonnes in 2026, more than three times the current capacity. Therefore, it is necessary to assess the challenges and identify the barriers for bio-based and biodegradable plastics for waste management and to evaluate the effectiveness of current plastic waste management strategies for the efficient waste management of bio-based and biodegradable plastics. The main barriers and motivators of the biodegradable and biodegradable plastics market that have been identified include macroeconomic factors, regulatory factors, technological factors, and social factors. The bio-based and biodegradable plastics have to be separately collected and treated under mostly controlled, regulated conditions. However, currently, there are no legal provisions providing for the separate collection of bio-based plastics, leading to their disposal with either hazardous waste, conventional plastics, or municipal waste. Since the effective plastic waste management strategy relates to good performance in each step of the waste management process, bio-based and biodegradable plastic waste management could, therefore, be based on an effective strategy for the management of plastic waste. However, there is a need for standardizing waste collection systems and creating a harmonized waste collection infrastructure, which would lead to effective sorting of bio-based plastic waste.

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a promising biodegradable bio-based material, which is designed for a vast range of applications, depending on its composite. This study aims to assess the degradability of a PHBV-based compound under different conditions. The research group followed different methodological approaches and assessed visual and mass changes, mechanical and morphological properties, spectroscopic and structural characterisation, along with thermal behaviour. The Ph-Stat (enzymatic degradation) test and total dry solids (TDS)/total volatile solids (TVS) measurements were carried out. Finally, the team experimentally evaluated the amount of methane and carbon dioxide produced, i.e., the degree of biodegradation under aerobic conditions. According to the results, different types of tests have shown differing effects of environmental conditions on material degradation. In conclusion, this paper provides a summary of the investigations regarding the degradation behaviour of the PHBV-based compound under varying environmental factors. The main strengths of the study lie in its multi-faceted approach, combining assessments of PHBV-based compound degradability under different conditions using various analytical tools, such as visual and mass changes, mechanical and morphological properties, spectroscopic and structural characterization, and thermal behavior. These methods collectively contribute to the robustness and reliability of the undertaken work.

Despite the significant reduction of phosphorus (P) discharge in the Baltic Sea in the last decades, obtained through the implementation of some approaches within the Helsinki Convention, eutrophication is still considered the biggest problem for the Baltic Sea environment. Consequently, the reduction of P load is an urgent need to solve, but the complexity of both the environmental and legislative context of the area makes this process difficult (more than in the past). Eutrophication is an intricate issue requiring a proper framework of governance that is not easy to determine in the Baltic Sea Region where the needs of several different countries converge. To identify the most suitable strategy to reduce the eutrophication in the Baltic Sea, the InPhos project (no. 17022, 2018–2019, funded by the European Institute of Innovation & Technology (EIT) Raw Materials) adopted a holistic approach considering technical, political, economic, environmental and social aspects of P management. With the aims to raise awareness about the P challenge, foster the dialogue among all the stakeholders, and find solutions already developed in other countries (such as Germany and Switzerland) to be transferred in the Baltic Sea Region, the InPhos project consortium applied the methodology proposed in this paper, consisting of three main phases: (i) analysis of the available technologies to remove P from waste streams that contribute to eutrophication; (ii) analysis of the main streams involving P in Baltic Sea countries to highlight the potential of more sustainable and circular P management; (iii) study of the current context (e.g., already-existing initiatives and issues). This approach allowed us to identify four categories of recommendations and practical actions proposed to improve P management in the Baltic Sea region. During the project, the consortium mainly addressed social aspects. Following steps beyond the project will be more quantitative to determine the techno-economic feasibility of circular P management in selected demo cases in the region.

In this study, an evaluation of food waste generation was conducted, using images taken before and after the daily meals of people aged between 20 and 30 years in Serbia, for the period between 1 January and 31 April in 2022. A convolutional neural network (CNN) was employed for the tasks of recognizing food images before the meal and estimating the percentage of food waste according to the photographs taken. Keeping in mind the vast variates and types of food available, the image recognition and validation of food items present a generally very challenging task. Nevertheless, deep learning has recently been shown to be a very potent image recognition procedure, while CNN presents a state-of-the-art method of deep learning. The CNN technique was implemented to the food detection and food waste estimation tasks throughout the parameter optimization procedure. The images of the most frequently encountered food items were collected from the internet to create an image dataset, covering 157 food categories, which was used to evaluate recognition performance. Each category included between 50 and 200 images, while the total number of images in the database reached 23,552. The CNN model presented good prediction capabilities, showing an accuracy of 0.988 and a loss of 0.102, after the network training cycle. The average food waste per meal, in the frame of the analysis in Serbia, was 21.3%, according to the images collected for food waste evaluation.