Explore the vast range of titles available.

With the rapid increase in household waste, environmental degradation becomes more serious. It is imperative to promote household waste sorting in China. Therefore, this paper mainly studies the influencing factors of intention and behavior for household waste sorting. An extended theory of planned behavior (TPB) theoretical model is established by integrating TPB with the theory of environmental regulation. We investigate the moderating roles of knowledge, moral obligation and personal involvement on the relationship between perceived behavior control and low-carbon household waste sorting behavior. Based on 441 valid questionnaires data and structure equation model and multiple regression analysis and differencing analysing, we found that environmental regulation has the highest effect on behavioral intention for household waste sorting, followed by perceived behavioral control and attitude toward house waste sorting in the extended TPB model. In addition, intention and perceived behavior control for household waste sorting positively impact on behavior, followed by perceived behavior control. Knowledge, personal involvement, and moral responsibility have a positive moderating effect on the mechanism between perceived behavior control and household waste sorting behavior, respectively. It is important to enhance the residents' responsibility, personal involvement, and knowledge for household waste soring in China.

A study was carried out in a waste sorting plant (WSP) located in France, treating dry recyclable household waste (DRHW) as well as dry recyclable commercial and industrial waste (DRCIW). Stationary and personal inhalable samples were collected in the WSP in order to investigate bioaerosols (sampling on a filter; 2 L/min and 10 L/min) and airborne dust (CIP; 10 L/min). The aim of the study was to assess the extent to which the measurement of concentration, species composition, and particle size distribution contributes to a better assessment of the biological risks associated with exposure. The results confirmed that waste and waste sorting activities are sources of airborne fungi. Indeed, ambient concentrations ranged from 7.3 × 103 to 8.5 × 105 colony-forming units (CFU)/m3 for culturable fungi and up to 4 mg/m3 for dust. Personal exposure to inhalable dust was found up to 3 mg/m3 for dust and ranged from 8.6 × 103 to 1.5 × 106 CFU/m3 for fungi. Airborne fungal communities were found to be dominated by the Penicillium genera in both bioaerosols and settled dust samples, followed by the Aspergillus, Cladosporium, Wallemia, Mucor, and Rhizopus genera. Fungi were carried by particles of aerodynamic diameters, mainly between around 2.0 and 10.0 µm. The findings dealing with size distribution and biodiversity of bioaerosols suggest that employees are exposed to complex bioaerosols during their work and help to make a finer diagnosis of the risks involved, which is often difficult in the absence of any occupational exposure limit (OEL) value for bioaerosols in general.

The exponential increase in waste generation is a significant global challenge with serious implications. Addressing this issue necessitates the enhancement of waste management processes. This study introduces a method that improves waste separation by integrating learning models at various levels. The method begins with the creation of image features as a new matrix using the Multi-Scale Local Binary Pattern (MLBP) technique. This technique optimally represents features and patterns across different scales. Following this, an ensemble model at the first level merges two Convolutional Neural Network (CNN) models, with each model performing the detection operation independently. A second-level CNN model is then employed to obtain the final output. This model uses the information from the first-level models and combines these features to perform a more accurate detection. The study’s novelty lies in the use of a second-level CNN model in the proposed ensemble system for fusing the results obtained from the first level, replacing conventional methods such as voting and averaging. Additionally, the study employs an MLBP feature selection approach for a more accurate description of the HW image features. It uses the Simulated Annealing (SA) algorithm for fine-tuning the hyperparameters of the CNN models, thereby optimizing the system’s performance. Based on the accuracy metric, the proposed method achieved an accuracy of 99.01% on the TrashNet dataset and 99.41% on the HGCD dataset. These results indicate a minimum improvement of 0.48% and 0.36%, respectively, compared to the other methods evaluated in this study.

This paper discusses the present state of Municipal Solid Waste (MSW) disposal in Argentina, focusing on the particular situation of the city of Salta, and suggests the future trend of the anaerobic treatment of this residue. Source-sorted household solid waste was determined by means of a statistical design. Municipal solid waste produced 147,103 kg per day +/-6.7 %, the major portion corresponds to the biodegradable organic fraction (55.4 %). The plastic, metal, paper, glass, and other material production was also evaluated. The organic municipal waste was chemically and biologically characterized, in order to study its behaviour during anaerobic digestion. The ratio normally found in organic fractions from MSW in Salta, Argentina, was in the optimum range which is 126:7:1 (C:N:P, w/w). The stability of the anaerobic process was analized in a 18 liter batch reactor. Its pH, biogas production, alkalinity, and volatile fatty acid production was determined. Although the work has been carried out at a small scale it appears to be sufficiently promising to encourage further work at a larger scale.

Background Poor waste disposal practices hamper the progress towards an integrated solid waste management in households. Knowledge of current practices and perception of household solid waste management is necessary for accurate decision making in the move towards a more sustainable approach. This study investigates the household waste practices and perceptions about waste management in Panji, one of the sub-districts in Kota Bharu, Kelantan, Malaysia. Methods A stratified random sampling technique using a cross-sectional survey questionnaire was used to collect data. A total of 338 households were interviewed in the survey and data were analyzed using SPSS. Chi-square goodness of fit test was used to determine the relationships between categorical variables, whereas Chi-square bivariate correlation test was performed to observe the correlation between the perceptions of waste segregation with socio-demographic background of the respondents. The correlation between perception of respondents with the locality, house type and waste type were also conducted. Principal component analysis was used to identify grouping of variables and to establish which factors were interrelated in any given construct. Results The results of the study revealed that 74.3 % of households disposed of food debris as waste and 18.3% disposed of plastic materials as waste. The study also showed that 50.3% of the households segregate their waste while 49.7% did not. About 95.9% of the respondents were aware that improper waste management leads to disease; such as diarrhea and malaria. There were associations between locality, age and house type with waste segregation practices among respondents (Chi-square test, p<0.05). Associations were also found between locality with the perception of improper waste management which lead to disease (Chi-square test, p<0.05). Principal Component Analysis showed that 17.94% of the variance has high positive loading (positive relationship) with age, marital status and, type of house. Conclusion This study highlights the importance to design waste separation programs that suit the needs of targeted population as a boost towards sustainable solid waste management practices.

Municipal solid waste (MSW) represents an inevitable by-product of human activity and a major crisis for communities across the globe. In recent times, the recycling of MSW has drawn attention as the process can add value through resources from the recovered waste materials and facilitates the process of circular economy. However, during the unprecedented coronavirus (COVID-19) outbreak, the risk of infection with the highly contagious virus has proven detrimental to the continuation of MSW as a valuable resource. The volume of waste, especially household waste, is higher; face masks, PPE (personal protective equipment), and hazardous materials such as batteries and empty chlorine bottles are examples of extra waste that have arisen during the pandemic. Various countries have set up initiatives for MSW management, including safety measurements for employees in the MSW management sector. The use of disinfectant prior to sorting waste, as well as storing waste for 9 days, may help to inactivate the COVID-19 virus, ensuring an appropriate safety level for MSW management. This work aimed at studying different MSW management strategies, specific challenges, and possible solutions for better understanding for those involved in waste management, in addition to providing a possible management strategy during and post-COVID-19 pandemic. Graphical abstract

Poor solid waste management remains a major environmental and public health concern in low- and middle-income countries, including Ghana. Solid waste includes non-hazardous materials like plastics, organic waste, and recyclables, as well as hazardous substances that can cause environmental and health risks if not properly disposed of. This study examined household waste disposal practices, management challenges, and environmental impacts in three communities within the Ahafo Region, Ghana. A descriptive cross-sectional survey was conducted with 384 participants selected through cluster sampling from Yamfo, Susuanso, and Tanoso. Data were collected using structured questionnaires and analysed with STATA version 14 to generate descriptive statistics and regression models. The findings indicated that burning (44%) and using public bins (30%) were the primary methods of waste disposal, while 9% resorted to open dumping. Waste segregation was uncommon, with 76% of participants reporting no separation of plastics or organic matter. Regression analysis revealed that irregular collection (OR = 11.25, 95% CI 60–27.47) and poor enforcement of regulations (OR = 1586, 95% CI 247–10,194.51) significantly increased the risk of clogged drains. Blocked drains and flooding (28.5%) and land pollution (28.1%) were the most frequently reported environmental issues. Inadequate collection services, poor supervisory oversight, and limited recycling infrastructure perpetuate unsafe waste disposal practices in the Ahafo Region. These findings underscore the need for immediate, community-driven waste management interventions in developing countries to safeguard public health and the environment.

Many cities in developing countries lack adequate drainage and waste management infrastructure. Consequently, city residents face economic and health impacts from flooding and waterlogging, which are aggravated by solid waste infiltrating and blocking drains. City governments have recourse to two strategies to address these problems: a) ‘hard’ infrastructure-related interventions through investment in the expansion of drainage and waste transportation networks; and/or, b) ‘soft’, low-cost behavioural interventions that encourage city residents to change waste disposal practices. This research examines whether behavioural interventions, such as information and awareness raising alongside provision of inexpensive street waste bins, can improve waste management in the city. We undertook a cluster randomized controlled trial study in Bharatpur, Nepal, where one group of households was treated with a soft, low-cost intervention (information and street waste bins) while the control group of households did not receive the intervention. We econometrically compared baseline indicators – perceived neighbourhood cleanliness, household waste disposal methods, and at-source waste segregation – from a pre-intervention survey with data from two rounds of post-intervention surveys. Results from analysing household panel data indicate that the intervention increased neighbourhood cleanliness and motivated the treated households to dispose their waste properly through waste collectors. The intervention, however, did not increase household waste segregation at source, which is possibly because of municipal waste collectors mixing segregated and non-segregated waste during collection. At-source segregation, a pre-requisite for efficiently managing municipal solid waste, may improve if municipalities arrange to collect and manage degradable and non-degradable waste separately.

Today, the topic of waste separation has been raised for a long time, and some waste separation devices have been installed in large communities. However, the vast majority of domestic waste is still not properly sorted and put out, and the disposal of domestic waste still relies mostly on manual classification. The research in this paper applies deep learning to this persistent problem, which has important significance and impact. The domestic waste is classified into four categories: recyclable waste, kitchen waste, hazardous waste and other waste. The garbage classification model trained based on MobileNetV2 deep neural network can classify domestic garbage quickly and accurately, which can save a lot of labor, material and time costs. The absolute accuracy of the trained network model is 82.92%. In comparison with CNN network model, the classification accuracy of MobileNetV2 model is 15.42% higher than that of CNN model. In addition, the trained model is light enough to be better applied to mobile.

Background Segregation of household waste at the source is an effective and sustainable strategy for management of municipal waste. However, household segregation levels remain insufficient as waste management approaches are mostly top down and lack local support. The realisation and recognition of effective, improved and adequate waste management may be one of the vital drivers for attaining environmental protection and improved health and well-being. The presence of a local level motivator may promote household waste segregation and ultimately pro-environmental behaviour. The present cluster randomized control trial aims to understand if volunteer based information on waste segregation (I-MISS) can effectively promote increased waste segregation practices at the household level when compared with existing routine waste segregation information in an urban Indian setting. Methods This paper describes the protocol of an 18 month two-group parallel,cluster randomised controlled trialin the urban setting of Ujjain, Madhya Pradesh, India. Randomization will be conducted at ward level, which is the last administrative unit of the municipality. The study will recruit 425 households in intervention and control groups. Assessments will be performed at baseline (0 months), midline (6 months), end line (12 months) and post intervention (18 months). The primary outcome will be the comparison of change in proportion of households practicing waste segregation and change in proportion of mis-sorted waste across the study period between the intervention and control groups as assessed by pick analysis. Intention to treat analysis will be conducted. Written informed consent will be obtained from all participants. Discussion The present study is designed to study whether an external motivator, a volunteer selected from the participating community and empowered with adequate training, could disseminate waste segregation information to their community, thus promoting household waste segregation and ultimately pro-environmental behaviour. The study envisages that the volunteers could link waste management service providers and the community, give a local perspective to waste management, and help to change community habits through information, constant communication and feedback. Trial registration The study is registered prospectively with Indian Council of Medical Research- Clinical Trial Registry of India ( CTRI/2020/03/024278 ).