Efficient Waste Management Research Articles

Strategy for clean phosphate recovery from polymerized aluminum chloride-treated sludge by alkaline anion exchange resins: High alkalinity and desorption

Polyaluminum chloride (PAC) is commonly used as a flocculant in wastewater treatment plants to aid in the removal of phosphorus (P) from wastewater. As a result, the P element present in PAC-treated sludge is predominantly in the form of Al-P. This study proposes the use of alkaline anion exchange resin (AAER) as a pretreatment method for PAC-treated sludge to enhance P extraction and achieve cleaner P recovery from this type of sludge. The findings of the study indicate that the optimal concentration of AAER is 12 g/g TS, resulting in a P extraction efficiency of 67.2 %. This represents a 26.5 % increase compared to alkali treatment at the same pH (pH = 12.23). Stepwise extraction analysis and molecular dynamics simulations suggest that during AAER treatment, Al(OH)3 is converted into dissolved [Al(OH)4]−. These species then agglomerate with PO43− and subsequently get adsorbed by the N(CH3)+ groups on the AAER. Furthermore, even after undergoing five regeneration cycles, the AAER still exhibits a significant adsorption capacity for P. Ultimately, high-purity Ca10(PO4)6(OH)2 is obtained as the final product with a recovery rate of 90.5 %. Meanwhile, the Al extracted by AAER can be reused as a feedstock for polymerized aluminum chloride. This demonstrates that AAER extraction is a promising and efficient waste management strategy for the clean recovery of P and Al from PAC sludge.

Towards efficient waste management: identification of waste flow chains in micro-regional detail through monitored data

AbstractCountries around the world are gradually implementing the transition to a circular economy in waste management. This effort should be initiated already at the waste producers. It is necessary to plan and monitor waste management in as much detail as possible, i.e. at the level of micro-regions. At present, only indicators at the national level are analysed, as more detailed data at the micro-regional level are often not available or are burdened with significant errors and inconsistencies. The calculation of waste management indicators for micro-regions will allow to identify the potential for increasing material or energy recovery and to plan the necessary infrastructure directly to these locations instead of blanket and often ineffective legislative actions. This paper presents an approach for determining the producer-treatment linkage, i.e., provides information about each produced waste, where it was treated, and in what way. Such information is often not available based on historical waste management data as there are repeated waste transfers and often aggregated within a micro-region. The network flow approach is based on an iterative procedure combining a simulation with multi-criteria optimization. The chosen criteria replicate expert estimates in investigated issue such as minimum flow splitting, and minimum transfer micro-regions. A data reconciliation is performed where the deviation from all simulations is minimized, given that the capacity constraints of nodes and arcs resulting from the database must be satisfied. The approach is tested on a generated sample task to evaluate the precision and time complexity of the developed tool. Finally, the presented approach is applied to address a case study in the Czech Republic, within which it is possible to identify treatment location and methods for waste from individual regions.

Sustainable Municipal Solid Waste Management Strategies and Practices: A review

Purpose: This paper introduces a multi-period, multi-objective model for creating an integrated, sustainable municipal solid waste management supply chain. The model includes source separation and a reward-penalty mechanism, aiming to minimize total system costs, greenhouse gas emissions, and environmental impacts on residential areas. Many countries strive to develop efficient solid waste management systems (SWMS) that handle and dispose of daily waste cost-effectively while maintaining sustainability. These systems include waste sources, collection stations, landfills, incinerators, recycling plants, and a transportation network. Methodology: A systematic literature review was conducted on existing literature from various studies. Recent studies were used for this systematic review of sustainable municipal solid waste management strategies and practices. Findings: Decision-makers must design or reconfigure a sustainable MSWM to determine the optimal supply chain network for treating and disposing of daily waste effectively. This paper suggests sustainable waste management strategies and practices from various countries, aiming to determine the best number and locations for facilities and optimal waste flow within the system to minimize daily costs. The primary contribution of this review is the theoretical development of sustainable MSWM practices applicable worldwide. Unique contribution to theory, policy and practice: Cooperation between the private and public sectors involved in solid waste management and the circular economy is imperative to ensure the technical, financial, and social sustainability of waste management systems. Large-scale awareness programs on solid waste management and the circular economy should be implemented, focusing on fostering environmentally responsible behaviors and attitudes, promoting sorting, selective collection, and the recovery of materials and energy from waste.

RECYCLING OF PHOTOVOLTAIC CELLS – A REVIEW

The growth of solar energy has been remarkable between 2013 and 2022, with a doubling of capacity from 80 GW to 197 GW. To recover valuable materials and mitigate environmental impact, it is imperative to have effective waste management practices in place. While recycling technologies are still in the experimental phase, the EU has put in place legal frameworks for manufacturer liability. There are continuous efforts being made to develop commercially viable technologies for the management of end-of-life PV module waste. An important part of the system of renewable sources is the establishment of a high-quality and efficient waste management system, which is contained within the concept of the circular economy. PV modules will at some point reach the end of their life cycle, which is estimated to be around 25 years, and become waste, therefore a lot of effort is currently being put into research and development of different waste treatment technologies of PV modules. They are still in the experimental phase, and few technologies become commercially available. Also, the management of waste generated at the end of the life cycle of photovoltaic technology is not yet fully regulated. However, at the level of the European Union, there is a legal framework for the liability of PV module manufacturers according to Directive on electric waste and electronic equipment. This paper is a detailed review of recycling technologies based on existing literature.

Efficient and Robust Dynamic Crosslinking for Compatibilizing Immiscible Mixed Plastics through In Situ Generated Singlet Nitrenes.

Creating a sustainable economy for plastics demands the exploration of new strategies for efficient management of mixed plastic waste. The inherent incompatibility of different plastics poses a major challenge in plastic mechanical recycling, resulting in phase-separated materials with inferior mechanical properties. Here, this study presents a robust and efficient dynamic crosslinking chemistry that effectively compatibilizes mixed plastics. Composed of aromatic sulfonyl azides, the dynamic crosslinker shows high thermal stability and generates singlet nitrene species in situ during solvent-free melt-extrusion, effectively promoting C─H insertion across diverse plastics. This new method demonstrates successful compatibilization of binary polymer blends and model mixed plastics, enhancing mechanical performance and improving phase morphology. It holds promise for managing mixed plastic waste, supporting a more sustainable lifecycle for plastics.

Microwave-assisted catalytic gasification of mixed plastics and corn stover for low tar, hydrogen-rich syngas production

The challenge for efficient management of post-consumer plastic and biomass waste has grown over the past few decades due to their dramatic increases. In comparison to conventional gasification, microwave-assisted co-gasification of plastics and corn stover offers many benefits, including increased H2 yield and gas components compared to unfavorable char/tar. Nonetheless, for future commercialization of the process and ease of product separation, further reduction of the undesirable tar is necessary, which can be achieved over the catalytic route. In this work, we studied the catalytic effect of magnetite for microwave-assisted co-gasification of corn stover and plastic to make syngas with higher H2 and lower tar selectivity over non-catalytic conditions. A 1:1:1 ratio of plastic-corn stover-magnetite was used to evaluate the reaction parameters such as temperature, space velocity, heating media, and catalytic cycles under gasification conditions. In comparison with the microwave non-catalytic route, a 100% increase in the total H2 yield with 76% higher H2 production efficiency (mmol/kWh) was achieved in the presence of the magnetite catalyst, while reducing the overall tar formation from 9% to 2%. When magnetite was reduced in situ during the reaction, it coupled with microwave and delivered oxygen radicals that cracked down plastic and corn stover intermediates generated from the synergistic effect under microwave heating. Soon after the oxygen transfer process initiated, magnetite reached its final oxidation state consisting of microwave-active Fe and Fe3C phases that continued coupling with microwaves along with the generated graphitic carbon to maintain the heat necessary to further reduce the generated tar and make additional gaseous products, as confirmed by XRD, Raman, and TGA analyses.

Smart bins for enhanced resource recovery and sustainable urban waste practices in smart cities: A systematic literature review

Waste collection bins with smart capabilities play a crucial role in contemporary urban landscapes, forming integral components of efficient and sustainable waste management practices worldwide. This paper conducts a thorough review of state-of-the-art smart bins, emphasizing advanced features such as material separation and integrated automation. The analysis, based on 79 selected articles from a pool of over 1400 publications, underscores critical gaps in the existing literature. While a widely accepted common ground that outlines the definition for smart bins exists, in the form of waste disposal containers incorporating functionalities such as fill-level monitoring and IoT connectivity, this research identifies substantial areas for improvement. Specifically, material separation practices, including automated waste segregation, and the overall maturity of conceptual frameworks present significant challenges, hindering the optimization of resource recovery essential for pioneering circular economy models. Moreover, a lack of uniformity and standardization in automation techniques is apparent across studies. Various articles propose divergent approaches, each with distinct advantages and drawbacks. Notably, no unified solution emerges that could harness collective strengths and mitigate shortcomings. Identifying these issues is paramount for advancing the field and tackle sustainability-related challenges within modern smart cities.

Identification of Slovak Tourists’ Attitudes Towards Digitalization for Circular Economy and Waste Management

Abstract The research paper explores the perspectives of a chosen group of Slovak tourists on how digitization drives circular economy practices and promotes efficient waste management in tourism. The study involves data from 103 participants, who expressed their opinions on sustainability concepts like digitization, innovation, circular economy, and waste management in tourism, using a 5-point Likert scale. The research’s main objective is to understand sentiments and attitudes towards integrating digitization and innovation for sustainable practices in the tourism sector. The findings reveal differences in attitudes among respondents. Visual aids like box plots are utilized to help interpret the results and emphasize how factors like interest in new technologies impact respondents’ attitudes. Implementing digital technologies in tourism plays a key role in creating efficient waste management systems and reducing the environmental burden. Data tracking and processing systems enable detailed analysis of waste generation patterns, providing valuable information to optimize collection and recycling processes. Digital technologies contribute to the overall reduction of the impact of tourism on the environment through electronic reservations, intelligent transport systems and other innovative solutions. These initiatives increase waste management efficiency and minimise tourism’s negative ecological impact, contributing to more sustainable and ecologically responsible tourism.

Disparities in the EU-27 Regarding Pollution and Generated Waste

Abstract The paper explores the transition to a circular economy within the European Union, focusing on maintaining the value of products and resources in the economic cycle and reducing waste production (pollution and generated waste). EU environmental policy emphasizes ecologically sound waste management and responsible use of secondary materials, forming the basis for a circular economy. While viewing waste as future resources remains challenging, the concept of "waste management, prevention, and utilization" is the cornerstone of this approach, requiring significant investments in innovation, research, and economic development. The article underscores the impact of pollution as a barrier to socio-economic development and highlights the importance of efficient waste management for environmental protection. The economic analysis, based on simple linear regression, reveals disparities among EU member states regarding pollution levels and waste generation. The increasing quantities and diverse nature of waste generated in the EU pose growing challenges. Municipal waste, representing a substantial proportion, exhibits significant variations in management practices among member states. To achieve sustainability, an integrated approach within the EU is essential, requiring substantial efforts from member states to accelerate the transition to a circular economy. The conclusions highlights the importance of efficient waste management and the need for concrete measures to reduce pollution and promote a sustainable economy.

A Hybrid Model for Dry Waste Classification using Transfer Learning and Dimensionality Reduction

The categorization of waste plays a crucial part in efficient waste management, facilitating the recognition and segregation of various waste types to ensure appropriate disposal, recycling, or repurposing. With the growing concern for environmental sustainability, accurate waste classification systems are in high demand. Traditional waste classification methods often rely on manual sorting, which is time-consuming, labor-intensive, and prone to errors. Hence, there is a need for automated and efficient waste classification systems that can accurately categorize waste materials. In this research, we introduce an innovative waste classification system that merges feature extraction from a pretrained EfficientNet model with Principal Component Analysis (PCA) to reduce dimensionality. The methodology involves two main stages: (1) transfer learning using the EfficientNet-CNN architecture for feature extraction, and (2) dimensionality reduction using PCA to reduce the feature vector dimensionality. The features extracted from both the average pooling and convolutional layers are combined by concatenation, and subsequently, classification is performed using a fully connected layer. Extensive experiments were conducted on a waste dataset, and the proposed system achieved a remarkable accuracy of 99.07%. This outperformed the state-of-the-art waste classification systems, demonstrating the effectiveness of the combined approach. Further research can explore the application of the proposed waste classification system on larger and diverse datasets, optimize the dimensionality reduction technique, consider real-time implementation, investigate advanced techniques like ensemble learning and deep learning, and assess its effectiveness in industrial waste management systems.

Marine Pollution and Waste Management

Water covers more than 70% of the surface of the globe. The ocean, which is amazing and significantly controls the world's climate, also has a hidden crisis, namely marine pollution. In the modern world, marine pollution is becoming a bigger issue. Article 1 (1) (4) of UNCLOS : says that “Pollution of the marine environment” means the introduction by man, directly or indirectly, of substances or energy into the marine environment, including estuaries, which results or is likely to result in such deleterious effects as harm to living resources and marine life, hazards to human health, a hindrance to marine activities, including fishing and other legitimate uses of the sea, impairment of quality for use of seawater and reduction of amenities”. Chemicals and garbage, most of which originate on land and are blown or carried into the water, are the two main components of marine pollution. Marine pollution, caused by human activities like improper disposal, shipping, and overfishing, harms ecology, health, and global economic institutions. Solutions include international agreements, sustainable fishing, improved waste disposal, and raising awareness. Education-based campaigns have the power to inspire citizens, groups, and governments to action. The legislative reforms and sustainable practices are significantly aided by environmental organizations and advocacy groups. The government has made several notable efforts, such as the plastic ban, marine protected areas, clean-up programs, and environmentally friendly fishing. Several countries have enacted plastic bags, which have significantly reduced the amount of plastic pollution, while the ocean may not be affected. Creating marine protected zones helps safeguard biodiversity and gives damaged ecosystems a place to recover. This article gives a general overview of the complex issue of marine pollution and shows how important it is to have efficient waste management plans. It investigates diverse marine pollution types and causes, emphasizing the dangers it poses, such as biodiversity loss, potential health hazards for humans, and significant financial expenses.

Implementing Green Constitution: Assessing the Policy of Plastic Waste Payment in Suroboyo Bus Service

This article explores the plastic waste-based payment policy implemented on the Suroboyo Bus Service in Indonesia, examining its alignment with the principles of a Green Constitution. The Green Constitution concept emphasizes the integration of environmental protection into legal frameworks. This study aims to analyze the Suroboyo Bus Service Plastic Waste Payment Policy in the context of the Green Constitution. Our analysis covers various aspects, including the historical background, legal norms, policy effectiveness, and the importance of community participation. The study employs normative-empirical research methods, examining the legal norms underpinning the Suroboyo Bus Service policy and its implementation. Quantitative data is collected through questionnaires distributed to the Suroboyo Bus Service users, revealing insights into public awareness, attitudes, and perceptions regarding the policy. Analysis of legal norms indicates a harmonization between the Suroboyo Bus Service policy and the Green Constitution principles outlined in the 1945 Indonesian Constitution. However, the study identifies a legal vacuum in waste management, suggesting more explicit guidelines are needed. The article also underscores the importance of collaborative efforts between the government and community organizations in efficient waste management.

Enhancing Waste-to-Energy Conversion Efficiency and Sustainability Through Advanced Artificial Intelligence Integration

Artificial intelligence (AI) has emerged as a pivotal tool in optimizing waste-to-energy conversion technology, addressing critical environmental issues while promoting sustainable energy sources. This study delves into the multifaceted role of AI in enhancing the efficiency and effectiveness of waste-to-energy processes. By leveraging AI, significant improvements can be achieved in automated waste sorting, process monitoring, and energy production forecasting. The integration of AI into these domains not only streamlines operations but also enhances the accuracy of data management, analysis, and processing. This results in a more efficient conversion of waste into energy, mitigating adverse environmental impacts and fostering sustainable energy practices. The research highlights the practical applications of AI in optimizing the entire waste-to-energy workflow, underscoring its potential to revolutionize this sector. Moreover, the study addresses the inherent challenges and discusses future prospects for AI implementation in waste-to-energy technologies. Through comprehensive analysis and case studies, the findings reveal that AI can significantly contribute to reducing environmental footprints and promoting a circular economy. This exploration provides valuable insights into how AI-driven innovations can lead to more sustainable and efficient waste management and energy production systems, paving the way for future advancements in this critical field.

IOT Garbage Monitoring System with Weight Sensing

This paper presents a novel approach towards efficient waste management utilizing Internet of Things (IoT) technology. The proposed system integrates garbage monitoring and weight sensing capabilities to create a smart waste management solution. Traditional waste collection methods are often inefficient and lack real-time monitoring, leading to overflows, environmental hazards, and unnecessary resource allocation. By employing IoT sensors embedded within garbage bins, real-time data on fill-level and weight can be collected and transmitted to a central server. AI calculations are applied to break down the information and predict future fill levels, optimizing waste collection schedules and routes. The system also includes a command-line interface available through web or mobile applications, enabling users to request timely pickups or report issues. Furthermore, the weight sensing functionality provides insights into the type and volume of waste being generated, facilitating better waste categorization and recycling initiatives. Field tests conducted in urban environments demonstrate the adequacy of the proposed system, reducing operational costs, minimizing environmental impact, and enhancing overall waste management efficiency. The coordination of IoT innovation with garbage monitoring and weight sensing represents a significant advancement towards sustainable and smarter cities

Enhancing trash classification in smart cities using federated deep learning

Efficient Waste management plays a crucial role to ensure clean and green environment in the smart cities. This study investigates the critical role of efficient trash classification in achieving sustainable solid waste management within smart city environments. We conduct a comparative analysis of various trash classification methods utilizing deep learning models built on convolutional neural networks (CNNs). Leveraging the PyTorch open-source framework and the TrashBox dataset, we perform experiments involving ten unique deep neural network models. Our approach aims to maximize training accuracy. Through extensive experimentation, we observe the consistent superiority of the ResNext-101 model compared to others, achieving exceptional training, validation, and test accuracies. These findings illuminate the potential of CNN-based techniques in significantly advancing trash classification for optimized solid waste management within smart city initiatives. Lastly, this study presents a distributed framework based on federated learning that can be used to optimize the performance of a combination of CNN models for trash detection.

Upcycling of SARS-CoV-2 Rapid Antigen Test Cassettes into Flame Retardant Plastics.

The COVID-19 pandemic resulted in the generation of large quantities of medical waste and highlighted the importance of efficient waste management systems. One good example of this is rapid antigen tests, which contain valuable resources, and which are usually incinerated after their use. The present study aimed to evaluate the potential of waste rapid antigen test cassettes (RATCs) as a resource for the preparation of sustainable flame-retardant plastics. Milled RATCs were compounded with different concentrations (10-30 wt.%) of aluminium diethylphosphinate (ADP) and injection moulded into test specimens. Prepared samples were exposed to ultraviolet (UV) ageing for varying durations and characterised by Fourier-transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA), tensile tests, Charpy impact tests, and vertical burning tests. FT-IR analysis revealed that RATCs are composed mainly of high-impact polystyrene (HIPS), which was further confirmed by suitable glass transition temperatures (Tg) determined by DSC and DMA. The addition of ADP resulted in progressive embrittlement of HIPS with increasing concentration, while flammability decreased significantly and reached V-1 classification at loading of 30 wt.%. UV ageing caused photo-oxidative degradation of HIPS, which resulted in decreased strain-at-break, while flammability was not affected.

IoT-based waste management: hybrid optimal routing and waste classification model.

Internet of Things (IoT) makes connectivity between physical devices which are embedded with sensors, software, and connectivity that let them to communicate and transfer data. This technology makes it possible to collect and transfer data from a vast network device, opening the door to the development of automatic and more efficiency systems. The term "waste management" refers to all of the responsibilities essential to regulate trash, from the point of gathering through reusing and monitoring. Reducing the hazardous consequences of such garbage on the environment and human health is the goal of waste management. By considering these hazardous consequences, this research work is interested in working on an efficient waste management system. The utilization of IoT devices enables municipalities to optimize waste management operations by leveraging data insights. This information aids in scheduling waste collections more effectively and planning optimal routes. Therefore, the research work proposes an IoT-based waste management system with two vital processes such as IoT routing and waste management. At first, routing in IoT is done by proposing hybrid optimization algorithm named Snake Optimization Updated Beluga Whale Optimization algorithm (SOUBWO) under constraints such as distance, energy, link quality, delay, and trust. Secondly, waste management is worked on by following steps including pre-processing, segmentation, feature extraction, and classification. The waste images collected by IoT devices are transmitted from source node (SN) to destination node (DN) by optimal routing. Those transmitted waste images are pre-processed by Wiener filtering process. Consequently, the pre-processed images are segmented by employing proposed Balanced Iterative Reducing and Clustering Using Hierarchies-Altered Distance Metrics (BIRCH-ADM) algorithm. Subsequently, features such as multi-text on histogram feature, proposed Local Gabor XOR Pattern (LGXP)-based feature using novel image processing techniques, and statistical features are extracted. Finally, these extracted features are efficiently classified by hybrid classification model which is formed by integrating conventional deep maxout and Bidirectional-Long Short Term Memory (Bi-LSTM) networks. The effectiveness of the proposed approach is validated through various analyses, including performance and statistical analyses. Moreover, the proposed scheme demonstrates minimal energy consumption, with a recorded value of 0.123. In contrast, conventional methodologies exhibit higher energy consumption, with values such as SOA = 0.237, BWO = 0.146, BES = 0.183, SMO = 0.158, CHOA = 0.174, and PSO = 0.189, respectively. By this hybrid classification model, the process of classification on waste is effectively done and moreover its effectiveness is proved by various analyses.

Conversión de residuos lignocelulósicos urbanos en fuente de bioenergía mediante carbonización hidrotérmica

El proceso de carbonización hidrotérmica ha llamado la atención de la comunidad académica y científica como una tecnología emergente y ecológica para la transformación de los residuos lignocelulósicos urbanos en fuente de bioenergía en forma sólida (hidrocarbón), líquida y gaseosa. Esta revisión aborda la comprensión de las propiedades y el potencial uso de estos residuos como fuente de bioenergía. Se analizan las propiedades fisicoquímicas y energéticas de estos residuos, así como los parámetros de operación que influyen en su transformación. Además, se presentan nuevas perspectivas sobre los desafíos futuros relacionados con el uso potencial de estos residuos y el proceso de carbonización. La conversión sostenible de estos residuos urbanos en una fuente de bioenergía contribuirá a reducir la dependencia de los combustibles fósiles, minimizar las emisiones de gases de efecto invernadero, garantizar una gestión eficiente de los residuos urbanos y desarrollar una bioeconomía circular.

Community participation in municipal solid waste management: Special reference to Gampaha municipality

Effective management of municipal solid waste is a pressing issue for numerous developing countries, including Sri Lanka. Despite efforts to implement eco-friendly waste disposal methods, many nations struggle with open landfills and unregulated dumping, causing detrimental effects on both public health and the environment. This study delves into the impact of community participation on solid waste management, with Sri Lanka serving as a case study. Urbanization and shifting consumption patterns exacerbate the challenges surrounding solid waste management. In Sri Lanka's urban areas, the absence of adequate waste management mechanisms emphasizes the necessity for active community involvement. Identifying the types and sources of solid waste is crucial for devising efficient waste management strategies. Concepts like the 3R approach (reduce, reuse, recycle) and composting play pivotal roles in sustainable waste management. Employing logistic regression analysis, the study assesses how community participation influences solid waste management. Results indicate that community involvement positively affects waste reduction, recycling, and composting efforts. However, while a considerable portion of the community actively engages in waste reduction, participation in waste reuse and recycling is limited. This highlights the significance of promoting the 3R concept and enhancing community involvement in waste management endeavors. Overall, the study underscores the instrumental role of community participation in achieving sustainable municipal solid waste management. Recommendations include prioritizing the 3R approach, investing in composting initiatives, and fostering greater community engagement in waste management practices. By adopting these strategies, municipalities can effectively address solid waste challenges while promoting environmental sustainability and public health.

Roles and Barriers to Waste Management among Garbage Collectors in Port-Harcourt Metropolis, Rivers State, Nigeria

Efficient waste management continues to be a significant public health challenge in Nigeria and other developing nations owing to a number of factors facing the personnel of waste management authorities, potentially leading to a disruption in the environment. Aim: To investigate the waste management roles and barriers faced by municipal waste collectors in Port Harcourt metropolis, Rivers State. Study Design: A descriptive, cross-sectional design was used. Place and Duration of Study: Port Harcourt metropolis, River State, Nigeria over a six month period. Methodology: The study was conducted among 302 municipal waste collectors through cluster random sampling, using pretested, structured, interviewer-administered questionnaires. Data entry and analysis were done using MS-Excel and analyzed using Statistical Package for Social Sciences version 20. Categorical variables were summarized using frequencies and proportions. Results: All study participants were males aged 20 years and above. They collected and sorted waste from both approved and unapproved receptacles. However, poor waste segregation at households, collection and processing practices, disruptive activities of scavengers, use of old, frequently dysfunctional equipment, poor training and insufficient remuneration/welfare and lack of public support were identified as the existing challenges faced by the garbage collectors. Conclusion: Unified efforts from relevant stakeholders such as households, organized private sector and the government are required to surmount the challenges faced by waste collectors. This will lead to the implementation of measures which could significantly promote sustainable development and environmental protection.