Waste Management & Research最新文献

Waste management has gained global importance, aligning with the escalating impact of the COVID-19 pandemic and the associated concerns regarding medical waste, which poses threats to public health and environmental sustainability. In Istanbul, medical waste is considered a significant concern due to the rising volume of this waste, along with challenges in collection, incineration and storage. At this juncture, precise estimation of the waste volume is crucial for resource planning and allocation. This study, thus, aims to estimate the volume of medical waste in Istanbul using the nonlinear grey Bernoulli model (NGBM(1,1)) and the firefly algorithm (FA). In other words, this study introduces a novel hybrid model, termed as FA-NGBM(1,1), for predicting waste amount in Istanbul. Within this model, prediction accuracy is enhanced through a rolling mechanism and parameter optimization. The effectiveness of this model is compared with the classical GM(1,1) model, the GM(1,1) model optimized with the FA (FA-GM(1,1)), the fractional grey model optimized with the FA (FA-FGM(1,1)) and linear regression. Numerical results indicate that the proposed FA-NGBM(1,1) hybrid model yields lower prediction error with a mean absolute percentage error value 3.47% and 2.57%, respectively, for both testing and validation data compared to other prediction algorithms. The uniqueness of this study is rooted in the process of initially optimizing the parameters for the NGBM(1,1) algorithm using the FA for medical waste estimation in Istanbul. This study also forecasts the amount of medical waste in Istanbul for the next 3 years, indicating a dramatic increase. This suggests that new policies should be promptly considered by decision-makers and practitioners.

Medical waste management is an essential component of healthcare delivery globally due to the toxic and contagious potentials on human health and the environment. There are resource limitations in developing nations when it comes to the appropriate handling of medical wastes. In this article, we examined previous studies to evaluate the practices of medical waste management in China and Nigeria. Contextually, this work addresses medical waste practices in the context of waste generation, segregation, collection, storage, transportation, treatment and disposal. In addition to reviewing additional important aspects of medical waste management, the current study addresses potentials and challenges for efficient medical waste management in both countries. For this study; Scopus, Web of Science, Google Scholar, PubMed, Agencies, Conferences, National and International Conventions were searched from 1998 up to 2023 for all studies reporting medical waste management in China and Nigeria. To further guarantee that only resource materials with similar research interests in medical waste management were selected, a double screening process was employed. The challenges of medical waste management in both countries are limited financing, inadequate training, ineffective legislation, ineffective medical waste transport system and insufficient treatment technology. Furthermore, this study offers practical recommendations by identifying the particular areas that require attention and development, such as training of healthcare workers, adequate financing of medical waste management projects, including research and development on efficient toxic emission reducing technologies, and partnership with other relevant authorities and stakeholders to ensure enforcement of national and local legislation.

The integration of mineral-based waste materials is crucial for achieving a sustainable and circular construction sector. Whilst technological and economic aspects receive attention, this mini review spotlights overlooked legal 'regulatory hurdles'. It explores major barriers within the European Union, aiming to compress the current ~30-year material development pipeline. Significant hurdles include the absence of harmonized end-of-waste criteria (Waste Framework Directive), the need for consensus-building in chemical risk assessments (REACH & CLP), scarcity of up-to-date harmonized product standards (Construction Products Regulation) and precision values for limit state analysis in structural codes (Eurocodes). This mini review serves as a practical manual, outlining the intricate regulatory landscape for industry experts, regulators and researchers. Emphasizing the parallel importance of environmental safety considerations and performance, our study presented in this mini-review, underscores the necessity for a multi-stakeholder approach to alleviate regulatory barriers. By illuminating regulatory intricacies, this mini review establishes the foundations for wider discussions and in-depth analysis as to the future outlook for consensus development procedures in a rapidly changing and challenging global construction sector. The manuscript also provides stakeholders with vital insights for informed decision-making, helping to facilitate the paradigm shift towards a sustainable and circular construction sector.

Refuse sorting is an important cornerstone of the recycling industry, but ever-changing refuse compositions and the desire to increase recycling rates still pose many unsolved challenges. The digitalisation of refuse sorting plants promises to overcome these challenges by optimising and automatically adapting the sorting process. This publication describes a system for image capturing, segmentation-based refuse recognition and data analysis of shredded refuse streams. The image capturing collects multispectral 2D and 3D images of the refuse streams on conveyor belts. The image recognition performs a semantic segmentation of the images to determine the refuse composition from the 2D images, whereas the 3D images approximate the volumes on the conveyor belts. The semantic segmentation is done by a combined convolutional neural network model, consisting of a foreground-background and a refuse class segmentation. Both models rely on synthetic training data to reduce the necessary amount of manually labelled training data, whereas the final segmentation performance reaches an Intersection over Union of up to 75%. The results of the semantic segmentation and volume estimation are combined with data of the shredding machinery by transforming it into a unified representation. This combined dataset is the basis for estimating the processed refuse masses from the semantic segmentation and volume estimation.

The use of the polypropylene (PP) recyclates in certain processing methods and applications is still limited by their quality. The high melt flow rate (MFR) and the inconsistent properties of recyclates are common obstacles to their use. Therefore, this work aims to identify possible reasons for the low and inconsistent quality of PP recyclates depending on the source material in PP waste bales. The levels of polymeric and non-polymeric contaminants were assessed. As mixing of different PP grades is an issue for the MFR, the proportions of the different processing grades were also investigated and the potential of sorting by processing method to produce lower MFR recyclates was assessed. The analysis showed that the waste bales, although pre-sorted, still contained high amounts of contaminants. Injection moulding was found to be the predominant processing method in the bales, explaining the high MFR of PP recyclates. However, a sufficiently high amount of low MFR products was found in the bales, which seems promising for the production of low MFR recyclates. Seasonal variations in the composition of the waste bales were identified as one of the reasons for the inconsistent qualities of recyclates. These results highlight the importance of proper sorting and treatment of PP waste bales prior to reprocessing in order to obtain high-quality recycled products.

The recycling of bio-waste from households is an essential factor in achieving the recycling quotas for municipal waste laid down by the EU. A major problem is posed by impurities in the bio-waste collected, such as plastics, metals and glass. It is virtually impossible for compost producers to produce quality-assured compost from bio-waste with an impurity content of more than 3 wt%_OS. The draft of the new Austrian Compost Ordinance stipulates a limit of 2 wt%_OS of interfering substances in accepted bio-waste. A rapid measurement method has been developed and comprehensively validated for the immediate on-site checking of contaminant content at the bio-waste bin or in a vehicles. Data on the type and amount of impurities collected in the course of sorting analyses carried out over several years in 10 selected areas in Styria, Austria showed an average impurity content of 2.1 wt%_OS. This impurity content can be considered representative for rural and urban communities in Austria. Among the interfering substances, plastics predominate, at 53%, of which pre-collection bags made of plastics form the highest proportion. A more detailed examination of pre-collection bags shows a higher proportion of use of biodegradable plastic bags, which have become more numerous in recent years in the more rural communities. In order to reduce mis-sorting, the effect of a wide variety of measures on citizens was tested in selected areas. Here, the distribution of paper bags as well as the threat of a cost increase due to special collections in combination with distribution of these bags were the methods with the greatest effect. Motivational letters and the threat of special collections, however, showed no significant result.