Proceedings of the World Conference on Waste Management

CLASSIFYING AND MANAGING OF ASBESTOS CONTAINING WASTE: ITALIAN EXPERIENCE

2022-06-23T05:31:19+0530

Until the 1990s Italy was the first world producer of asbestos, although in 1992 it became one of the first countries to ban this substance internationally, introducing law 257/1992, which prohibits the extraction and production of asbestos and asbestos containing products. The aim of this job is to describe some international experiences in the field of asbestos containing waste (ACW) management, focusing on the acceptance of waste in landfills and deposits and/or pre-treatment centers. In particular, the methodology envisages the analysis of the European and Italian legislation, study of waste classification and management in the main European countries, data analysis of mapping of Italian landfills and quantification of ACW disposed there. The results show criticalities on the classification and management of ACW or non-compliance on a local scale with European and National regulations. Such inconsistencies are the result of an inadequate interpretation of the sector legislation, which is complex and articulated, while, in other cases, of intentional illegal activities. In this paper the main problems of the sector are will be highlighted, and it could be a useful tool for a better classification and management of the ACW. These indications could also be adopted as a reference by various public authorities and trade associations involved in the management of this type of waste. Finally, this study will report the specific tables with indications on the main ACW, on the relevant European waste classification codes to be applied and on the correct final destination in landfills where they should be disposed of; it is a useful manual for classifying worldwide ACPs (asbestos containing products) based on their physical state.

APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR SOLID WASTE PROJECTION AND ENERGY CONTENT EVALUATION

2022-03-25T08:29:47+0530

Forecasts of the heterogeneous municipal solid waste (MSW) generation are vital for sustainable MSW management. Artificial neural network (ANN) models have been successfully demonstrated to predict complex MSW trends, but the negligence of the MSW’s heterogeneous characteristics hinders the further application of the predictions. This study aims to adopt robust ANN models coupling Bayesian hyperparameter optimization and uncertainty analysis to forecast the heterogeneous MSW generation in a country with further application in energy content evaluation. The impact of the hyperparameter optimization is illustrated by comparing the forecast uncertainties of ANN models using the Bayesian-optimized hyperparameters and default hyperparameters using ensemble forecasts. The relative standard deviations of the ensemble forecasts show that overfitting is more susceptible in the default models (11.1% – 44,400%) than in the Bayesian-optimized models (3.64% – 27.7%). By using the Bayesian-optimized models, Malaysia’s heterogeneous MSW generation is projected individually based on its physical composition. The total MSW generation in Malaysia is expected to grow by 12% from 2020 to 2030, with food waste as the dominant composition (44%). The energy content of the overall MSW is evaluated based on the lower calorific value of the forecasted MSW. The forecasted increase in food waste generation reduces the lower caloric value of Malaysia’s MSW below the lower limit to burn without supporting fuel (i.e., 6.5 MJ/kg). An alternative scenario where food waste is segregated from the overall MSW shows an increase in the lower calorific value from 5.874 MJ/kg to 10.31 MJ/kg. Without food waste segregation, the development of organic waste treatment facilities in Malaysia should be emphasized instead of incinerators. This study not only offers useful information for capacity planning of MSW treatment facilities using a data-driven approach, but it also broadens the scope for future related research by examining the application of the forecasted outcomes using ANN models.

IMPLEMENTING A SUSTAINABLE WASTE REDUCTION STRATEGY: A CASE STUDY AT GENERAL MOTORS

2022-06-23T06:00:39+0530

In congruence with General Motors launching a Zero Waste circular economy program, it has committed to diverting more than 90% of operational waste from landfills and thermal processing facilities by 2025. To achieve this goal for GM North America, a methodical waste reduction program was developed through the amalgamation of two interrelated strategies, the Strategic Planning Process and the Operational Strategy Process. This dual approach benefits from a companywide integrated focus on the organization’s strategic goals, yet remains efficient and engaging on a facility level, allowing for operational flexibility of design. To implement this novel methodology, GM established the team-of-teams approach to program management, creating roles in both the Sustainability team and Strategic Programs & Partnerships (SP2) team. The Sustainability team took ownership of the Strategic Planning Process, designing the Zero Waste tracking methodology and establishing annual waste diversion targets for the corporation. The SP2 team led the Operational Strategy Process, owning the specific Zero Waste Budget, and creating waste-centric innovation workshops, such as the Zero Waste Treasure Hunt program and Zero Waste Mini-Missions, which focused on quality improvement techniques, such as PDCA (Plan-Do-Check-Act) and DMAIC (Define-Measure-Analyze-Improve-Control). Projects that are ideated through the program are then submitted through the Zero Waste Projects Module, where they are reviewed based on various funding guidelines and prioritization benchmarks, ensuring funds are awarded to high impact ventures. This methodology has proven successful in surpassing 2021 diversion targets, with a real world 2021 diversion rate of 86.4%, and setting the groundwork to further expand support to meet the company’s Zero Waste diversion glidepath through 2025.

RELATIONSHIP BETWEEN LEVEL OF AWARENESS AND WILLINGNESS TO PARTICIPATE IN RECYCLING

2022-04-21T02:19:19+0530

Municipal solid waste is increasingly becoming a significant environmental challenge as a result of population growth and rapid development. Accordingly, environmental degradation such as air and water pollution as well as disease spread could happen. Recycling is the best approach to reduce environmental impacts from mismanagement of municipal solid waste. This study focuses on the recycling awareness level and willingness to participate in recycling practices as these two elements are the key factors affecting recycling behavior. Puchong suburban residential area is selected as the study area because most of the waste is generated in residential areas. A total of 424 residents were selected through multistage sampling, a combination of cluster random sampling and simple random sampling to participate in this research. The respondents are surveyed through a mixed-mode method to gather their perspectives towards recycling practices in daily lives. The questionnaires distributed consisted of three sections for socio-demographic background, recycling awareness and willingness to participate, respectively. The results discovered that the residents had a high awareness level of recycling with an overall mean of 4.08. Moreover, the residents were greatly willing to participate in recycling with an overall mean of 4.07. Besides, Kendall’s tau-b correlation, r = 0.451 and Spearman rank-order correlation, r = 0.600 showed that there was a moderate correlation between recycling awareness and willingness to participate. Therefore, to encourage the public’s participation and contribution towards recycling, local authorities shall continually take decisive actions to promote recycling awareness and disseminate recycling information. In addition, this research contributes to the knowledge of relationship between the two variables.

DESIGNING OUT WASTE FROM THE PRODUCTION OF A LEARNING TOWER THROUGH MATERIAL FLOW ANALYSIS

2022-04-30T07:01:31+0530

Malaysia's furniture manufacturing industry is made up of small and medium enterprises (SMEs), which contribute significantly to the country's economy. One major issue that these SMEs face is sustainable manufacturing: lowering throughputs and increasing production efficiencies. The study aims to improve the efficiency of producing a learning tower; a furniture product by an SME called Industerior Design by implementing material flow analysis (MFA) to monitor production throughputs. The MFA was used to compare two different learning tower designs (Design A and B). The most sustainable design was determined based on the MFA. A cause-and-effect analysis was also carried out using the Ishikawa fishbone diagram to identify potential causes of production inefficiencies. Both designs were proven to have the same processes involved and the same waste stream generated; however, Design A produces four learning towers from a single wood plank with 15.5% waste generated, while Design B produces only two towers with 44.6% waste generated. Of the waste generated by both designs, 60% from Design B was recyclable, while for Design A only 25% was reusable. Inefficiencies can be caused by a lack of skilled workers, a lack of or infrequent maintenance of equipment, or the design of the product itself. When the amount of recyclable waste that can be used for other future projects was considered, it was determined that Design B was more sustainable in the long run. MFA is thus thought to be a simple but powerful tool that can be easily implemented by SMEs in designing out waste from their products as the furniture industry moves toward more sustainable manufacturing and a more circular economy.

MAKING A DECISION USING ANALYTICAL HIERARCHY PROCESS (AHP) IN SELECTING SUITABLE FOOD WASTE MANAGEMENT METHOD: A CONCEPTUAL FRAMEWORK

2022-05-08T01:33:46+0530

Food waste in Malaysia has the highest composition in municipal solid waste (MSW) stream which, occupied around 44.5% of the total waste in mass. As food wastes are commonly disposed to landfill, during the process of degradation, it produces harmful pollutants such as leachate which cause contamination to the water sources while landfill gases lead to global warming and climate change. However, land scarcity is an issue in Malaysia where it is soon coming into a limit in spaces for landfilling. Hence, it is vital to look into a suitable food waste management method upon the issues. The application of Multi Criteria Decision Making (MCDM) is important in assisting the decision-making process by suggesting suitable food waste management treatment method. It helps to select shortlisted criteria that fulfill the requirements in line with the preferences and suggest on suitable treatment selection for decision. Analytical Hierarchy Process (AHP), which is one of the MCDM techniques, able to provide a rational decision-making framework by incorporating many relevant criteria and alternative that is support by scientific values of the suggestion. With the aid of the decision-making technique, food waste can be properly managed through suitable management treatment method and promotes on circular economy, reducing impacts towards the environment. From the results analyzed through MCDM, it is encouraged to practice on Anaerobic digestion (AD) treatment as it results in significant reduction of impact towards the environment. The use of AD treatment has significantly show contribution towards the environment. This study allows in showing on how food waste can be management properly in the suitable and preferred method that allows in the reduction of environment pollution