Digitalization and sustainability have been considered as critical elements in tackling a growing problem of solid waste in the framework of circular economy (CE). Although digitalization can enhance time-efficiency and/or cost-efficiency, their end-results do not always lead to sustainability. So far, the literatures still lack of a holistic view in understanding the development trends and key roles of digitalization in waste recycling industry to benefit stakeholders and to protect the environment. To bridge this knowledge gap, this work systematically investigates how leveraging digitalization in waste recycling industry could address these research questions: (1) What are the key problems of solid waste recycling? (2) How the trends of digitalization in waste management could benefit a CE? (3) How digitalization could strengthen waste recycling industry in a post-pandemic era? While digitalization boosts material flows in a CE, it is evident that utilizing digital solutions to strengthen waste recycling business could reinforce a resource-efficient, low-carbon, and a CE. In the Industry 4.0 era, digitalization can add 15% (about USD 15.7 trillion) to global economy by 2030. As digitalization grows, making the waste sector shift to a CE could save between 30% and 35% of municipalities' waste management budget. With digitalization, a cost reduction of 3.6% and a revenue increase of 4.1% are projected annually. This would contribute to USD 493 billion in an increasing revenue yearly in the next decade. As digitalization enables tasks to be completed shortly with less manpower, this could save USD 421 billion annually for the next decade. With respect to environmental impacts, digitalization in the waste sector could reduce global CO2 emissions by 15% by 2030 through technological solutions. Overall, this work suggests that digitalization in the waste sector contributes net-zero emission to a digital economy, while transitioning to a sustainable world as its social impacts.
Solid waste generation has rapidly increased due to the worldwide population, urbanization, and industrialization. Solid waste management (SWM) is a significant challenge for a society that arises local issues with global consequences. Thus, solid waste management strategies to recycle waste products are promising practices that positively impact sustainable goals. Several developed countries possess excellent solid waste management strategies to recycle waste products. Developing countries face many challenges, such as municipal solid waste (MSW) sorting and handling due to high population density and economic instability. This mismanagement could further expedite harmful environmental and socioeconomic concerns. This review discusses the current solid waste management and energy recovery production in developing countries; with statistics, this review provides a comprehensive revision on energy recovery technologies such as the thermochemical and biochemical conversion of waste with economic considerations. Furthermore, the paper discusses the challenges of SWM in developing countries, including several immediate actions and future policy recommendations for improving the current status of SWM via harnessing technology. This review has the potential of helping municipalities, government authorities, researchers, and stakeholders working on MSW management to make effective decisions for improved SWM for achieving sustainable development.
Currently, generation of solid waste per capita in Malaysia is about 1.1 kg/day. Over 26,500 t of solid waste is disposed almost solely through 166 operating landfills in the country every day. Despite the availability of other disposal methods, landfill is the most widely accepted and prevalent method for municipal solid waste (MSW) disposal in developing countries, including Malaysia. This is mainly ascribed to its inherent forte in terms cost saving and simpler operational mechanism. However, there is a downside. Environmental pollution caused by the landfill leachate has been one of the typical dilemmas of landfilling method. Leachate is the liquid produced when water percolates through solid waste and contains dissolved or suspended materials from various disposed materials and biodecomposition processes. It is often a high-strength wastewater with extreme pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD), inorganic salts and toxicity. Its composition differs over the time and space within a particular landfill, influenced by a broad spectrum of factors, namely waste composition, landfilling practice (solid waste contouring and compacting), local climatic conditions, landfill's physico-chemical conditions, biogeochemistry and landfill age. This paper summarises an overview of landfill operation and leachate treatment availability reported in literature: a broad spectrum of landfill management opportunity, leachate parameter discussions and the way forward of landfill leachate treatment applicability.
Metal, carbon and conducting polymer nanoparticles are blended with organic phase change materials (PCMs) to enhance the thermal conductivity, heat storage ability, thermal stability and optical property. However, the existing nanoparticle are expensive and need to be handle with high caution during operation as well during disposal owing to its toxicity. Subsequently handling of solid waste and the disposal of organic PCM after longevity usage are of utmost concern and are less exposed. Henceforth, the current research presents a new dimension of exploration by green synthesized nanoparticles from a thorny shrub of an invasive weed named Prosopis Juliflora (PJ) which is a agro based solid waste. Subsequently, the research is indented to decide the concentration of green synthesized nanoparticle for effective heat transfer rate of organic PCM (Tm = 35-40 °C & Hm = 145 J/g). Furthermore, an in-depth understanding on the kinetic and thermodynamic profile of degradation mechanism involved in disposal of PCM after usage via Coats and Redfern technique is exhibited. Engaging a two-step method, we fuse the green synthesized nanomaterial with PCM to obtain nanocomposite PCM. On experimental evaluation, thermal conductivity of the developed nanocomposite (PCM + PJ) increases by 63.8% (0.282 W/m⋅K to 0.462 W/m⋅K) with 0.8 wt% green synthesized nanomaterial owing to the uniform distribution of nanoparticle within PCM matrix thereby contributing to bridging thermal networks. Subsequently, PCM and PCM + PJ nanocomposites are tested using thermogravimetric analyzer at different heating rates (05 °C/min; 10 °C/min; 15 °C/min & 20 °C/min) to analyze the decomposition kinetic reaction. The kinetic and thermodynamic profile of degradation mechanism involved in disposal of PCM and its nanocomposite of PCM + PJ provides insight on thermal parameters to be considered on large scale operation and to understand the complex nature of the chemical reactions. Adopting thirteen different chemical mechanism model under Coats and Redfern method we determine the reaction mechanism; kinetic parameter like activation energy (Ea) & pre-exponential factor (A) and thermodynamic parameter like change in enthalpy (ΔH), change in Gibbs free energy (ΔG) and change in entropy (ΔS). Dispersion of PJ nanomaterial with PCM reduces Ea from 370.82 kJ/mol-1 to 342.54 kJ/mol-1 (7.7% reduction), as the developed nanomaterial is enriched in carbon element and exhibits a catalytic effect for breakdown reaction. Corresponding, value of ΔG for PCM and PCM + PJ sample within heating rates of 05-20 °C/min varies between 168.95 and 41.611 kJ/mol-1. The current research will unbolt new works with focus on exploring the pyrolysis behaviour of phase change materials and its nanocomposite used for energy storage applications. This work also provides insights on the disposal of PCM which is an organic solid waste. The thermo-kinetic profile will help to investigate and predict the optimum heating rate and temperature range for conversion of micro-scale pyrolysis to commercial scale process.
Refined red palm-pressed mesocarp olein (PPMO) is recovered from palm-pressed mesocarp fiber, which is a by-product from palm oil mill. Its utilization in food industry is extremely limited even though it contains various phytonutrients. Thus, this study aimed to evaluate its toxicity effects by using the male Sprague-Dawley rat model. The rats were administered with a single dose of 2 g/kg PPMO in an acute toxicity study while administered with 2, 1, or 0.5 g/kg PPMO daily for 28 days in a sub-chronic toxicity study. The mortality, oral LD50 value, clinical observation, body and organ weight, hematological and biochemical analyses, pathological and histopathological examinations were assessed. The overall outcomes indicated that PPMO is non-toxic up to 2 g/kg and considered safe to be used in food application, especially as functional food ingredient and supplement attributed to its phytonutrients. Besides, this study provides an insight in alternative utilization of the wastes from palm oil mill.
The present study investigated adsorptive removal of toluene and ethylbenzene from the aqueous media via using biochar derived from municipal solid waste (termed "MSW-BC") in a single and binary contaminant system at 25-45 °C. The adsorption was evaluated at different pH (3-10), experimental time (up to 24 h), and initial adsorbate concentrations (10-600 μg/L) in single and binary contaminant system. A fixed-bed column experiment was also conducted using MSW-BC (0.25%) and influent concentration of toluene and ethylbenzene (4 mg/L) at 2 mL/min of flow rate. The adsorption of toluene and ethylbenzene on the MSW-BC was mildly dependent on the pH, and the peak adsorption ability (44-47 μg/g) was recorded at a baseline pH of ~8 in mono and dual contaminant system. Langmuir and Hill are the models that match the isotherm results in a single contaminant environment for both toluene (R2 of 0.97 and 0.99, respectively) and ethylbenzene (R2 of 0.99 and 0.99, respectively) adsorption. In the binary system, the isotherm models matched in the order of Langmuir > Hill > Freundlich for toluene, whereas Hill > Freundlich > Langmuir for ethylbenzene. The adsorption in the batch experiment was likely to take place via cooperative and multilayer adsorption onto MSW-BC involving hydrophobic, π- π and n- π attractions, specific interaction such as hydrogen-π and cation-π interactions, and van der Waals interactions. The thermodynamic results indicate exothermic adsorption occurred by physical attractions between toluene and ethylbenzene, and MSW-BC. The breakthrough behavior of toluene and ethylbenzene was successfully described with Yoon-Nelson and Thomas models. The data demonstrate that the low-cost adsorbent derived from the municipal solid waste can be utilized to remove toluene and ethylbenzene in landfill leachate.
Growing populations, expanding economies, industrialisation, and urbanisation pose a problem for waste management in developing countries. Their waste management methods, on the other hand, are not as efficient as they could be. Most developing countries' current waste management practices do not fully conform to developed countries' best practices for meeting socioeconomic goals. As a result, the importance of waste management in developing countries has grown in recent years. In order to highlight the socioeconomic perspectives of waste management practices, the present study examines the existing literature, policies, information, and records on waste management in developing nations. The findings indicate that essential socioeconomic factors such as finances, population density, per capita income, education level, policies, and technology have a significant impact on waste management, which encompasses waste generation, collection, composition, and disposal/treatment. Nonetheless, waste management has a number of economic benefits, including financial stability, job creation, and community cohesion. This study will inspire further research on the need for developing nations to consider the socioeconomic benefits of proper waste management and to develop a policy plan to achieve these benefits.
The purpose of this work is to remove Pb(II) from the aqueous solution using a type of hydrogel composite. A hydrogel composite consisting of waste linear low density polyethylene, acrylic acid, starch, and organo-montmorillonite was prepared through emulsion polymerization method. Fourier transform infrared spectroscopy (FTIR), Solid carbon nuclear magnetic resonance spectroscopy (CNMR)), silicon(-29) nuclear magnetic resonance spectroscopy (Si NMR)), and X-ray diffraction spectroscope ((XRD) were applied to characterize the hydrogel composite. The hydrogel composite was then employed as an adsorbent for the removal of Pb(II) from the aqueous solution. The Pb(II)-loaded hydrogel composite was characterized using Fourier transform infrared spectroscopy (FTIR)), scanning electron microscopy (SEM)), and X-ray photoelectron spectroscopy ((XPS)). From XPS results, it was found that the carboxyl and hydroxyl groups of the hydrogel composite participated in the removal of Pb(II). Kinetic studies indicated that the adsorption of Pb(II) followed the pseudo-second-order equation. It was also found that the Langmuir model described the adsorption isotherm better than the Freundlich isotherm. The maximum removal capacity of the hydrogel composite for Pb(II) ions was 430mg/g. Thus, the waste linear low-density polyethylene-g-poly (acrylic acid)-co-starch/organo-montmorillonite hydrogel composite could be a promising Pb(II) adsorbent.
Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine learning models are applied for MSW-related trend prediction to provide insights on future waste generation or carbon emissions trends and assist the formulation of effective low-carbon policies. Yet, the existing machine learning models are diverse and scattered. This inconsistency poses challenges for researchers in the MSW domain who seek to identify and optimize the machine learning techniques and configurations for their applications. This systematic review focuses on MSW-related trend prediction using the most frequently applied machine learning model, artificial neural network (ANN), while addressing potential methodological improvements for reducing prediction uncertainty. Thirty-two papers published from 2013 to 2023 are included in this review, all applying ANN for MSW-related trend prediction. Observing a decrease in the size of data samples used in studies from daily to annual timescales, the summarized statistics suggest that well-performing ANN models can still be developed with approximately 33 annual data samples. This indicates promising opportunities for modeling macroscale greenhouse gas emissions in future works. Existing literature commonly used the grid search (manual) technique for hyperparameter (e.g., learning rate, number of neurons) optimization and should explore more time-efficient automated optimization techniques. Since there are no one-size-fits-all performance indicators, it is crucial to report the model's predictive performance based on more than one performance indicator and examine its uncertainty. The predictive performance of newly-developed integrated models should also be benchmarked to show performance improvement clearly and promote similar applications in future works. The review analyzed the shortcomings, best practices, and prospects of ANNs for MSW-related trend predictions, supporting the realization of practical applications of ANNs to enhance waste management practices and reduce carbon emissions.
The present study was undertaken to determine the bacterial agents present in various clinical solid wastes, general waste and clinical sharp waste. The waste was collected from different wards/units in a healthcare facility in Penang Island, Malaysia. The presence of bacterial agents in clinical and general waste was determined using the conventional bacteria identification methods. Several pathogenic bacteria including opportunistic bacterial agent such as Pseudomonas aeruginosa, Salmonella spp., Klebsiella pneumoniae, Serratia marcescens, Acinetobacter baumannii, Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Streptococcus pyogenes were detected in clinical solid wastes. The presence of specific pathogenic bacterial strains in clinical sharp waste was determined using 16s rDNA analysis. In this study, several nosocomial pathogenic bacteria strains of Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Lysinibacillus sphaericus, Serratia marcescens, and Staphylococcus aureus were detected in clinical sharp waste. The present study suggests that waste generated from healthcare facilities should be sterilized at the point of generation in order to eliminate nosocomial infections from the general waste or either of the clinical wastes.
Increasing population, urbanization and industrial activities have increased the amount of solid waste worldwide. Food waste (FW) and sewage sludge (SS) are some of the solid wastes. Co-digesting of both substrates may improve process stabilization to increase biogas production and overcome the nutrients imbalance. Thus, anaerobic co-digestion has been recognized as a technology that could provide a clean renewable energy source and help reducing the landfill problem. In this study, the interaction between FW and SS as co-substrates in anaerobic digestion was studied under mesophilic temperature 36C (± 0.5). The experiments were conducted using five batch reactors with different ratios of substrates. There are four different analyses used to identify the characteristics of FW and SS, which are pH, reducing sugar (RS), total solid (TS), and total carbohydrate (TC). Water displacement method was used to record biogas yield. The experimental results showed that the highest biogas yield was from the composition of 50:50 (FW: SS) with a biogas volume of 1150.14 mL, while the least was the composition of 0:100 (FW: SS) with 170.47 mL biogas produced. The results for substrate degradation showed that the composition of 100:0 (FW: SS) has the highest percentage degradation for reducing sugar with the percentage of 56%, while the minimum was 0:100 (FW: SS) with a percentage of 35%. Besides, for TC, the highest percentage of degradation was the composition 50:50 (FW: SS) with 84%, and the least was 0:100 (FW: SS) with 44%. This study proves that using FW and SS enhanced biogas production as well as reducing the current issues of waste disposal.
Biogas is an economical and environmentally friendly renewable energy which can be produced by anaerobic digestion (AD). This biochemical method converts organic compounds (mainly from wastes) into a sustainable source of energy. Anaerobic co-digestion (AcoD) is a method combining more than one substrate to resolve the difficulties faced in a single substrate AD system. Solid wastes increases as the population increase so do the urbanization and industrial industries. Food waste and sewage sludge are examples of one of the solid wastes. Co-digesting of both substrates may improve process stabilization to increase biogas production and overcome the nutrients imbalance. Thus, anaerobic co-digestion has been recognized as a technology that could provide a clean renewable energy source and helps reduce the landfill problem. The objective of this paper is to investigate the recent achievements and perspectives on the interaction of co-digestion between food waste and sewage sludge to improve biogas production. This may provide valuable information on the optimization of combinations of substrates: food waste and sewage sludge and prediction of bioreactor performance.
In order to address slagging, fouling and high-temperature corrosion problems caused by alkali metals in Municipal Solid Waste (MSW), in-situ measurement of alkali metal in MSW incinerators is needed. The paper presents experimental measurements of temperatures and alkali metal concentrations in two MSW incinerators based on Flame Emission Spectroscopy (FES). Through the analysis of spontaneous emission spectra and a calibration procedure, the concentration of gas phase sodium (Na) and potassium (K), temperature and thermal radiation in the incinerator were in-situ measured by a portable spectral system simultaneously. Experimental results showed MSW composition has significant effect on the measured gaseous Na and K. Higher volatile content in MSW may enhance the alkali metal emission. Besides that, the released gaseous Na and K in the two incinerators are correlated with temperature in incinerators. The study provided a low cost and effective solution for in-situ measurement of temperature and alkali metal concentration in MSW incinerators.
The COVID-19 pandemic has imposed a global emergency and also has raised issues with waste management practices. This study emphasized the challenges of increased waste disposal during the COVID-19 crisis and its response practices. Data obtained from the scientific research papers, publications from the governments and multilateral organizations, and media reports were used to quantify the effect of the pandemic towards waste generation. A huge increase in the amount of used personal protective equipments (facemasks, gloves, and other protective stuffs) and wide distribution of infectious wastes from hospitals, health care facilities, and quarantined households was found. The amount of food and plastic waste also increased during the pandemic. These factors caused waste treatment facilities to be overwhelmed, forcing emergency treatment and disposals (e.g., co-disposal in a municipal solid waste incinerator, cement kilns, industrial furnaces, and deep burial) to ramp up processing capacity. This paper discussed the ways the operation of those facilities must be improved to cope with the challenge of handling medical waste, as well as working around the restrictions imposed due to COVID-19. The study also highlights the need for short, mid, and longer-term responses towards waste management during the pandemic. Furthermore, the practices discussed in this paper may provide an option for alternative approaches and development of sustainable strategies for mitigating similar pandemics in the future.
This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image's gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.
In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.
Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.
The present study intends to evaluate the potential of co-digestion for utilizing Organic fraction of Municipal Solid Waste (OFMSW) and sewage sludge (SS) for enhanced biogas production. Metagenomic analysis was performed to identify the dominant bacteria, archaea and fungi, changes in their communities with time and their functional roles during the course of anaerobic digestion (AD). The cumulative biogas yield of 586.2 mL biogas/gVS with the highest methane concentration of 69.5% was observed under an optimum ratio of OFMSW:SS (40:60 w/w). Bacteria and fungi were found to be majorly involved in hydrolysis and initial stages of AD. Probably, the most common archaea Methanosarsina sp. primarily followed the acetoclastic pathway. The hydrogenotrophic pathway was less followed as indicated by the reduction in abundance of syntrophic acetate oxidizers. An adequate understanding of microbial communities is important to manipulate and inoculate the specific microbial consortia to maximize CH4 production through AD.
Studies on marine debris have gained worldwide attention since many types of debris have found their way into the food chain of higher organisms. Thus, it is crucial that more focus is given to this area in order to curb contaminations in sea food. This study was conducted to quantify plastic debris buried in sand at selected beaches in Malaysia. Marine debris was identified according to size range and distribution, and this information was related to preventive actions to improve marine waste issues. For the purpose of this study, comparison of plastic waste abundance between a recreational beach and fish-landing beaches was also carried out, since the different beach types represent different activities that produce debris. Six beaches along the Malaysian coastline were selected for this study. The plastic types in this study were related to the functions of the beach. While recreational beaches have abundant quantities of plastic film, foamed plastic including polystyrene, and plastic fragment, fish-landing beaches accumulated line and foamed plastic. A total of 2542 pieces (265.30 g m(-2)) of small plastic debris were collected from all six beaches, with the highest number from Kuala Terengganu, at 879 items m(-2) on Seberang Takir Beach, followed by Batu Burok Beach with 780 items m(-2). Findings from studies of Malaysian beaches have provided a clearer understanding of the distribution of plastic debris. This demonstrates that commitments and actions, such as practices of the 'reduce, reuse, recycle' (3R) approach, supporting public awareness programmes and beach clean-up activities, are essential in order to reduce and prevent plastic debris pollution.
Home composting can be an effective way to reduce the volume of municipal solid waste. The aim of this study is to evaluate the effect of Effective Microorganism™ (EM) for the home scale co-composting of food waste, rice bran and dried leaves. A general consensus is lacking regarding the efficiency of inoculation composting. Home scale composting was carried out with and without EM (control) to identify the roles of EM. The composting parameters for both trials showed a similar trend of changes during the decomposition. As assayed by Fourier Transform Infrared Spectroscopy (FTIR), the functional group of humic acid was initially dominated by aliphatic structure but was dominated by the aromatic in the final compost. The EM compost has a sharper peak of aromatic CC bond presenting a better degree of humification. Compost with EM achieved a slightly higher temperature at the early stage, with foul odour suppressed, enhanced humification process and a greater fat reduction (73%). No significant difference was found for the final composts inoculated with and without EM. The properties included pH (∼7), electric conductivity (∼2), carbon-to-nitrogen ratio (C: N 100%), humic acid content (4.5-4.8%) and pathogen content (no Salmonella, <1000 Most Probable Number/g E. coli). All samples were well matured within 2 months. The potassium and phosphate contents in both cases were similar however the EM compost has a higher nitrogen content (+1.5%). The overall results suggested the positive effect provided by EM notably in odour control and humification.