Optimal planning for the sustainable utilization of municipal solid waste

Waste management optimization with NLP modeling and waste-to-energy in a circular economy

This work presents a methodology integrating Non-Linear Programming (NLP) for multi-objective and multi-period optimization, addressing sustainable waste management and energy conversion challenges. It integrates waste-to-energy (WtE) technologies such as Anaerobic Digestion (AD), Incineration (Inc), Gasification (Gsf), and Pyrolysis (Py), and considers thermochemical, technical, economic, and environmental considerations through rigorous non-linear functions. Using Mexico City as a case study, the model develops waste management strategies that balance environmental and economic aims, considering social impacts. A trade-off solution is proposed to address the conflict between objectives. The economical optimal solution generates 1.79M$ with 954 tons of CO2 emissions while the environmental one generates 0.91M$ and reduces emissions by 54%, where 40% is due to gasification technology. Moreover, the environmentally optimal solution, with incineration and gasification generates 9500 MWh/day and 5960 MWh/day, respectively, demonstrates the capacity of the model to support sustainable energy strategies. Finally, this work presents an adaptable framework for sustainable waste management decision-making.

Nitrate-Nitrogen Adsorption Characteristics and Mechanisms of Various Garden Waste Biochars

Nitrate-nitrogen (NO3--N) removal and garden waste disposal are critical concerns in urban environmental protection. In this study, biochars were produced by pyrolyzing various garden waste materials, including grass clippings (GC), Rosa chinensis Jacq. branches (RC), Prunus persica branches (PP), Armeniaca vulgaris Lam. branches (AV), Morus alba Linn. sp. branches (MA), Platycladus orientalis (L.) Franco branches (PO), Pinus tabuliformis Carrière branches (PT), and Sophorajaponica Linn. branches (SL) at three different temperatures (300 °C, 500 °C, and 700 °C). These biochars, labeled as GC300, GC500, GC700, and so on., were then used to adsorb NO3--N under various conditions, such as initial pH value, contact time, initial NO3--N concentration, and biochar dosage. Kinetic data were analyzed by pseudo-first-order and pseudo-second-order kinetic models. The equilibrium adsorption data were evaluated by Langmuir, Freundlich, Temkin and Dubinin-Radushkevich models. The results revealed that the biochar yields varied between 14.43% (PT700) and 47.09% (AV300) and were significantly influenced by the type of garden waste and decreased with increasing pyrolysis temperature, while the pH and ash content showed an opposite trend (p < 0.05). The efficiency of NO3--N removal was significantly influenced by the type of feedstock, preparation process, and adsorption conditions. Higher pH values had a negative influence on NO3--N adsorption, while longer contact time, higher initial concentration of NO3--N, and increased biochar dosage positively affected NO3--N adsorption. Most of the kinetic data were better fitted to the pseudo-second-order kinetic model (0.998 > R2 > 0.927). Positive b values obtained from the Temkin model indicated an exothermic process of NO3--N adsorption. The Langmuir model provided better fits for more equilibrium adsorption data than the Freundlich model, with the maximum NO3--N removal efficiency (62.11%) and adsorption capacity (1.339 mg·g-1) in PO700 under the conditions of pH = 2, biochar dosage = 50 mg·L-1, and a reaction time of 24 h. The outcomes of this study contribute valuable insights into garden waste disposal and NO3--N removal from wastewater, providing a theoretical basis for sustainable environmental management practices.

A hybrid machine learning-mathematical programming optimization approach for municipal solid waste management during the pandemic

This paper provides a mathematical optimization strategy for optimal municipal solid waste management in the context of the COVID-19 epidemic. This strategy integrates two approaches: optimization and machine learning models. First, the optimization model determines the optimal supply chain for the municipal waste management system. Then, machine learning prediction models estimate the required parameters over time, which helps generate future projections for the proposed strategy. The optimization model was coded in the General Algebraic Modeling System, while the prediction model was coded in the Python programming environment. A case study of New York City was addressed to evaluate the proposed strategy, which includes extensive socioeconomic data sets to train the machine learning model. We found the predicted waste collection over time based on the socioeconomic data. The results show trade-offs between the economic (profit) and environmental (waste sent to landfill) objectives for future scenarios, which can be helpful for possible pandemic scenarios in the following years.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03354-2.

Root causes of underperforming urban waste services in developing countries: Designing a diagnostic tool, based on literature review and qualitative system dynamics

Cities in developing countries struggle with providing good waste collection services to all their citizens. Daily practice mostly shows low service coverage, especially in the poorer parts of cities. Up until now, research has mainly dealt with the symptoms of poor performance. This article aims at designing a qualitative System Dynamics model of the urban system that may serve as a diagnostic tool to find the root causes and leverage points for interventions. The research presented here uses a broad literature review to draw up a complex causal loop diagram describing all relevant urban variables (demographic, economic, social, financial, technical and governance-related) and their relations. The diagram is analysed using qualitative methods, partly derived from graph theory. It results in an evaluation of all variables, paths, loops and branches of the model, and finally in a simplified model. This simplified model is helpful in diagnosing waste management problems in cities, in formulating interventions and their points of leverage and even in formulating a new taxonomy that classifies cities with regard to the effect and delay in their urban processes. When it comes to interventions, the model suggests that the root cause is in populations growing faster than their economies, and that the enabling circumstances are mainly in poor governance practices that are unable to secure that tax incomes keep pace with needed budgets for sound services.

Optimal waste management during the COVID-19 pandemic

There have been many problems generated by the COVID-19 pandemic. One of them is the worrying increase in the generation of medical waste due to the great risk they represent for health. Therefore, this work proposes a mathematical model for optimal solid waste management, proposing a circular value chain where all types of waste are treated in an intensified industrial park. The model selects the processing technologies and their production capacity. The problem was formulated as a mixed-integer linear programming problem to maximize profits and the waste processed, minimizing environmental impact. The proposed strategy is applied to the case study of the city of New York, where the increase in the generation of medical waste has been very significant. To promote recycling, different tax rates are proposed, depending on the amount of waste sent to the landfill. The results are presented on a Pareto curve showing the trade-off between profits and processed waste. We observed that the taxes promote recycling, even of those wastes that are not very convenient to recycle (from an economic point of view), favoring profits, reducing the environmental impact, and the risk to health inherent to the medical waste.

An Optimization Model for the Design of a Sustainable Municipal Solid Waste Management System

Solid waste management is critical to sustainable, healthy, and eco-friendly cities and societies. In developing countries, only a small percentage of municipal solid waste is disposed safely, while the majority remains in the streets or disposed in open landfills. Most countries seek to establish effective and efficient solid waste management system (SWMS) that can handle and dispose of the daily generated waste at minimum cost and in a sustainable manner. Those systems usually consist of waste sources, waste collection stations, landfills, incinerators, and recycling plants, in addition to the transportation system that integrates the different sub-systems. The problem facing decision-makers while designing or reconfiguring a SWMS is to determine the optimal supply chain network design for such systems in a way that ensures the treatment and disposal of all daily generated waste at the lowest cost. In this context, this paper aims to develop a generic optimization model suitable for application in SWMS optimization in developing countries. A new mixed-integer linear programming (MILP) model is formulated for a SWMS configuration that integrates waste generation sources, collection/transfer stations, recycling plants, incinerators, and landfills. The proposed MILP model is formulated to determine the optimal number and locations of the different facilities, and the optimal flow of waste in the system that minimizes the net daily cost incurred in the system. The model has been applied in a case study on the SWMS in Fayoum Governorate, Egypt. The main contribution of this research refers both to the theoretical development of a generic MILP model that can be applied to optimally design the SWMS in developing countries, and to its operational counterpart, as per the design solutions provided in the SWMS of Fayoum Governorate (Egypt).

Optimal Process Network for Integrated Solid Waste Management in Davao City, Philippines

Municipal solid waste management (MSWM) systems in developing countries adopt practices from developed countries to reduce their environmental burdens. However, several complex issues specific to developing countries hinder the full implementation of these practices. The future of MSWM in Davao City, Philippines, is envisaged as a notable example of the combination of new infrastructure and local MSWM practices. A linear programming model was developed, following material flow analysis and life cycle assessment, to design an optimal system for Davao City. The performance of the system was evaluated in terms of greenhouse gas emissions, energy and revenue generated, and the amount of landfill waste. The results show that the proposed system positively affects the environment compared to the current system, due to additional treatment options. However, the main allocation concern transitions from organic waste in the current system to plastic waste in future scenarios. Furthermore, the mitigation of greenhouse gas emissions and the extension of landfill life will be heavily influenced by trade-offs between sorting operations and the management of incinerated wastes with high calorific values. Therefore, plastic-waste-specific treatment options will be critical for future MSWM systems. The results herein underscore the need for sustainable MSWM in the study area, considering the region-specific conditions.

Application of MCAT to provide multi-objective optimization model for municipal waste management system

Choosing an appropriate municipal waste management method is a very complicated environmental problem in cities. This research introduces an optimization model for waste management in the southwest region of Tehran province. It was developed by a metaheuristic algorithm that was used to minimize the economic and environmental costs. Incineration, composting, recycling and landfilling waste management methods were considered. Three scenarios were developed to determine the optimum allocation of waste to each method such to fulfill the objective of overall minimum of environmental burdens and costs. A multi-objective scenario selection model was implemented by the compromise programming method in MCAT software. Considering the budget limitation and available facilities on site, optimum allocations to recycling, composting, incineration and landfilling methods were obtained as 115,486, 132,094, 71,905 and 45,516 tons/year, respectively. The results of this study indicated that the metaheuristic algorithm in MCAT software was an efficient tool in decision making about waste management systems and thus, it was suggested to municipality managers and regional planning authorities.

Energy, environmental, resource recovery, and economic dimensions of municipal solid waste management paths in Mexico city

Growing municipal solid waste (MSW) generation is a source of environmental, economic, and social concerns, especially in developing world megacities where poor MSW practices prevail. Mexico City (CDMX), one of the world's largest megacities, daily produces ∼ 13,073 Mg of MSW whose management poses a tremendous challenge to local authorities and calls for additional research to conceive sound MSW strategies. This study evaluates the fossil energy use, GHG emissions, resource recovery, and economic cost dimensions of current and five alternative MSW paths in CDMX to compare their performance and identify more sustainable MSW practices for the megacity. Impacts and benefits from the MSW paths were modeled using 2018 MSW generation data, information supplied by local authorities, and literature values. Current MSW path consumes ∼ 387 MJ_fossil, generates ∼ 501 kg-CO₂e, and costs ∼ 57 USD₂₀₁₈ per Mg of MSW managed while it only valorizes < 33% of total MSW mostly via informal truck-picking. The alternative MSW paths considerably reduce GHG emissions (∼129-360 kg-CO₂e/Mg) and enhance MSW valorization (∼47-88%) though, they entail higher fossil energy consumption (447-582 MJ_fossil/Mg) and, in general, higher cost expenditures (43-208 USD₂₀₁₈/Mg). Heavy reliance on landfilling, large GHG emissions, and low MSW valorization make current MSW path in CDMX unsustainable. Incineration-based MSW paths perform better in most aspects evaluated but their high costs seem prohibitive. Results suggest MSW paths featuring open windrow composting, mechanical-biological pre-treatment, material recovery facilities, and refuse-derived fuel production may be more appropriate to improve the sustainability of CDMX MSW management.

Adoption of sustainable solid waste management and treatment approaches: A case study of Iran

Developing countries face serious environmental, social and economic challenges when it comes to managing different kinds of solid waste. Iran, as one such country, is forced to deal with many difficulties including the absence of a comprehensive policy framework, a lack of technical know-how, insufficient financial resources and lack of proper disposal facilities. This study attempts to suggest ways to overcome those problems by providing applicable waste management solutions to the local conditions. The research was performed in four structured phases: diagnosis of the existing solid waste management system practised, identification of areas of weakness in the waste management frameworks, bridging the gaps to ensure the sustainability of the concepts offered, and finally the provision of affordable solutions. A source-separated collection system for wet and dry fractions was drawn up. Establishment of a mechanical biological treatment facility and the introduction of biological treatment technology were considered as the main treatment options. From the economic point of view, the extended producer responsibility concept was provided as a resource management tool. The involvement of the stakeholders, as well as the public-private partnership model, was identified as the cornerstone in the planning and implementing of the new approaches. A roadmap was consequently designed aimed at gradually introducing a waste management system in a sustainable and environmentally sound manner.

A novel cooperative model in the collection of infectious waste in COVID-19 pandemic

Purpose

Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors.

Design/methodology/approach

Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time.

Findings

The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model.

Originality/value

The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

Multi-objective Optimization Approach Based on Deterministic and Metaheuristic Techniques to Resource Management in Health Crisis Scenarios Under Uncertainty

This paper presents an optimization strategy based on mathematical programming to solve resource management problems regarding hospitalization of sick patients, considering emergency scenarios, such as those that can occur in a pandemic. This optimization strategy is based on the use of efficient optimization tools in solving complex problems in which other strategies are not efficient. The mathematical modeling of epidemiological phenomena is a useful tool to predict the direction of a disease, as well as to adequately and timely manage the available resources and thus save as many lives as possible. This work uses a mathematical model formulation based on deterministic optimization developed in general algebraic modeling system (GAMS) environment. The main user interface has been developed in a Microsoft™ (MS) Excel worksheet, which is familiar to many users. The linking code to send values from MS Excel to GAMS has been programmed in visual basic for applications (VBA) and it uses GAMS data exchange (GDX) files. The proposed optimization methodology is applied to case studies based on data obtained from affected people by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the virus that causes coronavirus disease 2019 (COVID-19). The distances were taken as example from severely affected cities in the USA. The obtained results offer attractive alternatives for the specified objective function in an acceptable computation time.

Process optimization for the anaerobic digestion of poplar (Populus L.) leaves

This study investigates the optimized condition for enhancing biogas production in the anaerobic digestion of fallen poplar leaves. Two experiments were conducted: (1) The calcium hydroxide concentration, bacteria concentration, and composting time were used as three parameters to optimize the fermentation pretreatment condition and contrasting tests were performed; and (2) a series of fermentation tests were conducted to explore the best process parameters and biogas production characteristics. The results showed that a biological and chemical combined pretreatment effectively improved the biogas productivity of poplar leaves as fermentation substrates, and the parameter that had the greatest effect during anaerobic digestion was temperature followed by the solid concentration and pH value. The optimal pretreatment condition was: alkali concentration 4.61%, bacterial concentration 0.20‰, and a composting time of 6.6 days. By considering the factors that affect the fermentation of poplar leaves and the cumulative gas production, the optimum condition for poplar leave digestion was found to be a temperature of 30°C, a pH of 7, and a 10% solid concentration. In addition, the methane yield of the optimized trial was well fitted using the modified Gompertz model.

Optimization of municipal solid waste management using a coordinated framework

Municipal solid waste (MSW) management is an important but complex logistical problem. The deployment of MSW management systems is hindered by the ever-growing generation of waste and the often insufficient infrastructure to manage, process, and dispose of waste. This paper presents a coordinated framework for complex MSW management systems. The framework accommodates multiple key stakeholders in MSW systems, such as suppliers of waste, consumers of waste and derived products, and providers of transportation and processing services. Here, the stakeholders submit bids to a coordinator that solves an optimization problem to determine allocations and clearing prices that maximize the collective profit for all stakeholders and that balance supply and demand for waste and products. Furthermore, the clearing process guarantees that the individual profits are non-negative (no stakeholder loses money). Notably, the framework operates as a competitive market that accelerates transactions between stakeholders and that handles complex logistical constraints that would be difficult to handle in peer-to-peer transactions. The framework also facilitates the integration of policy incentives and the monetization of environmental impacts. In this regard, we evaluate a tax applied to open dump disposal. To illustrate the applicability, an MSW system in Mexico was analyzed as a case study. Results reveal that taxation can be used to incentivize the provision of services for all stakeholders. Specifically, we found that an appropriate tax can completely avoid disposal in open dumps. A tax of 5.1 USD/tonne was identified as the minimum penalization that avoids diverting waste to open dumps.

A mixed integer linear programming model for long-term planning of municipal solid waste management systems: Against restricted mass balances

Long-term planning of municipal solid waste management systems is a complex decision making problem which includes a large number of decision layers. Since all different waste treatment and disposal processes will show different responses to each municipal solid waste component, it is necessary to separately evaluate all waste components for all processes. This obligation creates an obstacle in the programming of mass balances for long-term planning of municipal solid waste management systems. The development of an ideal mixed integer linear programming model that can simultaneously respond to all essential decision layers including waste collection, process selection, waste allocation, transportation, location selection, and capacity assessment has not been made possible yet due to this important modeling obstacle. According to the current knowledge of the literature, all mixed integer linear programming studies aiming to address this obstacle so far have had to restrict many different possibilities in their mass balances. In this study, a novel mixed integer linear programming model was formulated. ALOMWASTE, the new model structure developed in this study, was built to take into consideration different process, capacity, and location possibilities that may occur in complex waste management processes at the same time. The results obtained from a case study showed the feasibility of new mixed integer linear programming model obtained in this study for the simultaneous solution of all essential decision layers in an unrestricted mass balance. The model is also able to provide significant convenience for the multi-objective optimization of financial-environmental-social costs and the solution of some uncertainty problems of decision-making tools such as life cycle assessment.

A Benefit–Cost Analysis of Food and Biodegradable Waste Treatment Alternatives: The Case of Oita City, Japan

As the generation of food scrap, kitchen, and biodegradable wastes increases, the proper handling of these wastes is becoming an increasingly significant concern for most cities in Japan. A substantial fraction of food and biodegradable waste (FBW) ends up in the incinerator. Therefore, an analytic hierarchy process (AHP) benefit–cost analysis technique was employed in this study to compare different FBW treatment technologies and select the most appropriate FBW disposal technology for Oita City. The four FBW treatment options considered were those recommended by the Japanese Food Waste Recycling Law: anaerobic digestion, compost, landfill, and incineration, which is currently in use. The fundamental AHP was separated into two hierarchy structures for benefit analysis and cost analysis. The criteria used in these two analyses were value added, safety, efficiency, and social benefits for benefit analysis, and cost of energy, cost of operation and maintenance, environmental constraints, and disamenity for cost analysis. The results showed that anaerobic digestion had the highest overall benefit while composting had the least cost overall. The benefit–cost ratio result showed that anaerobic digestion is the most suitable treatment alternative, followed by composting and incineration, with landfill being the least favored. The study recommends that composting could be combined with anaerobic digestion as an optimal FBW management option in Oita City.

Municipal solid waste management considering NGO’s role in consumer environmental awareness and government regulations for air pollution

Purpose

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs).

Design/methodology/approach

This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern.

Findings

This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased.

Research limitations/implications

In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results.

Practical implications

Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW.

Originality/value

The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

A System Dynamics-Based Approach to Help Understand the Role of Food and Biodegradable Waste Management in Respect of Municipal Waste Management Systems

The long-term plan of any city in Japan is to become a material recycling society. The use of all types of municipal waste is essential in maximizing the full potential of material recovery. As such, municipalities are responsible for managing their waste, including food and biodegradable waste (FBW), and this results in some complex schemes. This study uses the system dynamics approach to illustrate and investigate the benefits of separate treatment of FBW. At the same time, to understand the dynamic interactions between all aspects and elements of the current municipal solid waste management system in Oita City. The developed model includes total environmental benefit, motivation to manage waste and resources, and yield from treatment facilities. The result shows that with the introduction of an anaerobic digester (AD) plant for FBW increases the efficiency of incineration. Furthermore, the result indicates that strengthening the regulation of waste sorted and the reduction in the amount of FBW treated in incineration will improve the current system. This study concludes that any policy or regulation less than the proposed result will yield less benefit. Thus, strengthening regulation is a crucial part of the sustainability of FBW management in the long run.

Managing the uncertainty problems of municipal solid waste disposal

In waste management systems, several parameters such as the rate of waste production, disposal facility, treatment cost, and their relations may be uncertain and can influence the associated optimization processes. These uncertainty problems in waste management were addressed by using various inexact programming methods. For example, fuzzy, stochastic programming, and interval programming techniques were generally used for solving the uncertainty-related waste management problems. The analysis revealed that the efficiency of waste management system can be maximized by the proper use of these optimization techniques. In this approach, an uncertainty problem is reduced into several subproblems with sureness by using the minimax regret optimization technique. And these subproblems are focused on a calculation where the lament of not getting the goal is minimized. The analysis also revealed that the fuzzy-stochastic method was increasingly used for dealing with the waste management system uncertainty in recent times. This paper gives an overview of dealing with the uncertainty problems of waste disposal in urban areas. An indication of the solid waste disposal problems and its management in conjunction with the repercussion of the investigation is described. The rationale and setting of the uncertainty issues in proper waste management are detailed. The applications of fuzzy analysis approach and integrated waste management in dealing with the uncertainty problems are presented. The applications of these techniques in diverse case studies worldwide are discussed and finally, the conclusions of the literature analysis are summarized.

Gateway of Landfilled Plastic Waste Towards Circular Economy in Europe

For decades, significant work has been conducted regarding plastic waste by dealing with rejected materials in waste masses through their accumulation, sorting and recycling. Important political and technical challenges are involved, especially with respect to landfilled waste. Plastic is popular and, notwithstanding decrease policies, it will remain a material widely used in most economic sectors. However, questions of plastic waste recycling in the contemporary world cannot be solved without knowing the material, which can be achieved by careful sampling, analysis and quantification. Plastic is heterogeneous, but usually all plastic waste is jointly handled for recycling and incineration. Separation before processing waste through the analytical approach must be applied. Modern landfill mining and site clean-up projects in contemporary waste management systems require comprehensive material studies ranging from the macro-characterization of waste masses to a more detailed analysis of hazardous constituents and properties from an energy calorific standpoint—where, among other methods, thermogravimetric research coupled with life cycle assessment (LCA) and economic assessment is highly welcomed.

Current status of waste management in Botswana: A mini-review

Effective waste management practices are not all about legislative solutions, but a combination of the environmental, social, technical, technically skilled human resources, financial and technological resources, resource recycling, environmental pollution awareness programmes and public participation. As a result of insufficient resources, municipal solid waste (MSW) in transition and developing countries like Botswana remains a challenge, and it is often not yet given highest priority. In Botswana, the environment, public health and other socio-economic aspects are threatened by waste management practices due to inadequate implementation and enforcement mechanisms of waste management policy. This mini-review paper describes the panorama of waste management practices in Botswana and provides information to competent authorities responsible for waste management and to researchers to develop and implement an effective waste management system. Waste management practices in Botswana are affected by: lack of effective implementation of national waste policy, fragmented tasks and overlapping mandates among relevant institutions; lack of clear guidelines on the responsibilities of the generators and public authorities and on the associated economic incentives; and lack of consistent and comprehensive solid waste management policies; lack of intent by decision-makers to prepare national waste management plans and systems, and design and implement an integrated sustainable municipal solid waste management system. Due to these challenges, there are concerns over the growing trend of the illegal dumping of waste, creating mini dumping sites all over the country, and such actions jeopardize the efforts of lobbying investors and tourism business. Recommendations for concerted efforts are made to support decision makers to re-organize a sustainable waste management system, and this paper provides a reference to other emerging economies in the region and the world.

A multi-objective model for sustainable recycling of municipal solid waste

The efficient management of municipal solid waste is a major problem for large and populated cities. In many countries, the majority of municipal solid waste is landfilled or dumped owing to an inefficient waste management system. Therefore, an optimal and sustainable waste management strategy is needed. This study introduces a recycling and disposal network for sustainable utilisation of municipal solid waste. In order to optimise the network, we develop a multi-objective mixed integer linear programming model in which the economic, environmental and social dimensions of sustainability are concurrently balanced. The model is able to: select the best combination of waste treatment facilities; specify the type, location and capacity of waste treatment facilities; determine the allocation of waste to facilities; consider the transportation of waste and distribution of processed products; maximise the profit of the system; minimise the environmental footprint; maximise the social impacts of the system; and eventually generate an optimal and sustainable configuration for municipal solid waste management. The proposed methodology could be applied to any region around the world. Here, the city of Tehran, Iran, is presented as a real case study to show the applicability of the methodology.

Occurrence of heavy metals and contaminants on the surface of adjacent rivers

Water is fundamental to the survival of living beings. It registers every impact and can function as an indicator of environmental stressors. Our objective in the current study was to assess the sanitary conditions of the waters in the Açude, Maria Lucinda and Santa Rosa streams. This was done by checking pH, running quantitative analyses of heavy metals and testing for total coliforms. The effect of ultraviolet (UV) rays on samples positive for coliforms was evaluated. The average pH of the streams ranged between 4 and 7 and changed between drought and rainy season conditions. Chromium and nickel values were above those permitted by the Brazilian National Council on the Environment, CONAMA. In the dry season, zinc values were above those established by CONAMA for waterbodies of Classes 1 and 2. Thermotolerant coliforms were present in all samples collected and above permitted values. After exposing the bacteria to UV light, it was noted that UV irradiation was unable to decrease the bacteria count. Ninety residents who use stream water were interviewed: 24% of interviewees said they use the waters of the Açude and Mary Lucinda streams and along the Santa Rosa stream, 95% of inhabitants said they use the water.

Multi-criteria decision making to support waste management: A critical review of current practices and methods

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Comparison of fuel value and combustion characteristics of two different RDF samples

Generation of Municipal Solid Waste (MSW) tends to increase with the growing population and economic development of the society; therefore, establishing environmentally sustainable waste management strategies is crucial. In this sense, waste to energy strategies have come into prominence since they increase the resource efficiency and replace the fossil fuels with renewable energy sources by enabling material and energy recovery instead of landfill disposal of the wastes. Refuse Derived Fuel (RDF), which is an alternative fuel produced from energy-rich Municipal Solid Waste (MSW) materials diverted from landfills, is one of the waste to energy strategies gaining more and more attention. This study aims to investigate the thermal characteristics and co-combustion efficiency of two RDF samples in Turkey. Proximate, ultimate and thermogravimetric analyses (TGA) were conducted on these samples. Furthermore, elemental compositions of ash from RDF samples were determined by X-Ray Fluorescence (XRF) analysis. The RDF samples were combusted alone and co-combusted in mixtures with coal and petroleum coke in a lab scale reactor at certain percentages on energy basis (3%, 5%, 10%, 20% and 30%) where co-combustion processes and efficiencies were investigated. It was found that the calorific values of RDF samples on dry basis were close to that of coal and a little lower compared to petroleum coke used in this study. Furthermore, the analysis indicated that when RDF in the mixture was higher than 10%, the CO concentration in the flue gas increased and so the combustion efficiency decreased; furthermore, the combustion characteristics changed from char combustion to volatile combustion. However, RDF addition to the fuel mixtures decreased the SO2 emission and did not change the NOx profiles. Also, XRF analysis showed that the slagging and fouling potential of RDF combustion was a function of RDF portion in fuel blend. When the RDF was combusted alone, the slagging and fouling indices of its ash were found to be higher than the limit values producing slagging and fouling.

Is bigger better? An empirical analysis of waste management in New South Wales

Across the world, rising demand for municipal solid waste services has seen an ongoing increase in the costs of providing these services. Moreover, municipal waste services have typically been provided through natural or legal monopolies, where few incentives exist to reduce costs. It is thus vital to examine empirically the cost structure of these services in order to develop effective public policies which can make these services more cost efficient. Accordingly, this paper considers economies of size and economies of output density in the municipal waste collection sector in the New South Wales (NSW) local government system in an effort to identify the optimal size of utilities from the perspective of cost efficiency. Our results show that - as presently constituted - NSW municipal waste services are not efficient in terms of costs, thereby demonstrating that 'bigger is not better.' The optimal size of waste utilities is estimated to fall in the range 12,000-20,000 inhabitants. However, significant economies of output density for unsorted (residual) municipal waste collection and recycling waste collection were found, which means it is advantageous to increase the amount of waste collected, but maintaining constant the number of customers and the intervention area.