Abstract With current low recycling rates and exponentially increasing production of plastics there is an increase in plastic material wastage, and thus new technologies are needed for waste refining. Presently in Europe, only about 10% of plastic waste is recycled, most of which is achieved through mechanical recycling. Chemical recycling methods like pyrolysis could significantly increase these recycling rates, as it can utilize mixtures of waste plastics unlike mechanical recycling. It can also be used to treat waste of many novel materials, such as composites, especially in the emerging phase when the volumes of the new materials in markets are low making separate collection of waste not a cost-efficient option. Pyrolysis offers an environmentally sound alternative to incineration and inefficient landfilling. Currently, main challenges for pyrolysis of plastic waste are unavailability and inconsistent quality of feedstock, inefficient and hence costly sorting, non-existent markets citing lack for standardized products, and unclear regulations around plastic waste management. Possible solutions could include tight cooperation between feedstock providers and converters for securing steady quantity and quality of feedstock. Advanced pre-treatment would provide the basis for cost-effective recycling. The classification of pyrolysis liquid as a product instead of waste is needed, and the REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals) registration should be carried out to standardise the liquid oil as a product. In addition, sustainability impacts need to be clearly positive.
Waste sorting is highly recommended for municipal solid waste (MSW) management. Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW sorting. Particularly, the field of CV-enabled waste sorting is experiencing an unprecedented explosion of academic research. However, little attention has been paid to understanding its evolvement path, status quo, and prospects and challenges ahead. To address the knowledge gap, this paper provides a critical review of academic research that focuses on CV-enabled MSW sorting. Prevalent CV algorithms, in particular their technical rationales and prediction performance, are introduced and compared. The distribution of academic research outputs is also examined from the aspects of waste sources, task objectives, application domains, and dataset accessibility. The review discovers a trend of shifting from traditional machine learning to deep learning algorithms. The robustness of CV for waste sorting is increasingly enhanced owing to the improved computation powers and algorithms. Academic studies were unevenly distributed in different sectors such as household, commerce and institution, and construction. Too often, researchers reported some preliminary studies using simplified environments and artificially collected data. Future research efforts are encouraged to consider the complexities of real-world scenarios and implement CV in industrial waste sorting practice. This paper also calls for open sharing of waste image datasets for interested researchers to train and evaluate their CV algorithms.
S M Shahinur Rahman, Md Ruhul Amin, A M Almas Shahriyar Azad
et al.
This study presents a robust framework for accurately forecasting medical waste (MW) generation in healthcare settings, addressing escalating environmental and public health concerns. Using machine learning (ML) models, including Linear Regression (LR), Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and Random Forest (RF), the research integrates critical patient-related variables, such as indoor and outdoor patient counts, surgeries, and deaths. Based on eight years of comprehensive data (2016–2023) from the medical colleges in Rajshahi, Bangladesh, the LR model showed the most reliable outcomes, achieving R2 values between 0.91 and 0.95 for all waste categories and outperforming others with mean absolute errors (MAE) as low as 1.39 kg for recyclable waste. Projections reveal a significant 50 % surge in general waste by 2030, reaching approximately 987.75 tons, while infectious waste will grow from 66.54 to 735.23 tons. Monte Carlo simulations quantified variability across waste categories, demonstrating fluctuations within ±5% of mean values, ensuring robustness. Finally, the research represents a novel policy recommendation for zero waste generation at the study location, which advocates for category-specific MW management strategies, aligning with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 12 (Responsible Consumption and Production), and 13 (Climate Action). This work introduces a novel precedent for incorporating artificial intelligence into healthcare operations to attain zero waste generation while tackling public health and environmental issues. Thus, this work offers an innovative methodology that integrates machine learning to link patient data with waste generation, providing practical insights for resource optimization and operational planning.
Accurate and operative monitoring of municipal solid waste (MSW) landfills is critical for operational safety, spatial planning, and regulatory compliance. Traditional point-based surveying methods are precise, but they are limited in spatial density coverage and hence, efficiency. The objective of the study is to evaluate the application of airborne laser scanning (ALS) for detecting volume changes at operational MSW landfill in the Czech Republic. Specifically, the study determines optimal spatial resolution of digital terrain model (DTM) from ALS for estimation of landfill volume, estimates uncertainties related to slope steepness and different vegetation cover affecting the accuracy of ALS-derived DTM, and formalizes and applies the method for detecting landfill volume changes using ALS. Two ALS datasets (10 points/m2) were collected in a five-month interval and processed at multiple spatial resolutions (0.3 m to 1.5 m). GPS reference points were measured for ALS data co-registration and to assess the accuracy of ALS-derived elevations. Positional errors and their propagation into elevation errors were quantified, and vegetation-induced uncertainties were considered. Results indicate that DTM resolutions of 0.3–0.8 m provide the most reliable estimates of volume change, especially in heterogeneous areas such as vegetated slopes. Differences in the standard deviation (SD) of elevation changes for selected areas at the landfill between the DTM resolution of 0.3 m and coarser resolutions were minimal for stable surfaces such as roads and compacted waste (0.01–0.02 m), but higher for vegetated areas, where the SD increased by up to 0.10 m due to surface roughness and variable laser penetration through the canopy. Comparison with independent GPS reference points showed that finer DTMs (0.3 and 0.5 m) reduced both bias and variability (mean differences ≤ 0.23 m, SD ≤ 0.24 m), whereas coarser DTMs (0.8 and 1.5 m) increased systematic errors due to surface smoothing and vegetation-induced misclassification. The findings recommend acquiring ALS data in early spring or late autumn, when vegetation cover is minimal and the influence of canopy on DTM accuracy is reduced. The study presents a novel workflow integrating ALS data with error modeling to improve landfill monitoring protocols. While the workflow was demonstrated on a specific site, it has potential for adaptation and application in other MSW landfills.
Nur Kamaliah Mustaffa, Zakiah Ahmad, Zadariana Jamil
et al.
The growing demand for engineered wood products (EWP) in Malaysia has intensified wood processing activities, raising sustainability and environmental concerns. This study aims to identify innovative strategies to strengthen sustainability practices in the Malaysian EWP industry. A mixed-methods approach was employed, combining a survey of 67 stakeholders, semi-structured interviews with 11 experts and site assessments of five manufacturing companies to capture current practices, barriers and enabling factors. The survey indicates moderate adoption of sustainability practices. A majority of firms practiced waste minimization and use of recyclable wood (65%), adopted energy conservation policies (55%), utilised wood waste for fuel or feedstock (55%) and applied emission control systems (55%). In contrast, adoption of advanced measures was lower, with 35% incorporating solar energy and 15% applying lifecycle assessment (LCA). The analysis revealed four key innovation pathways: (i) resource management and waste reduction, (ii) energy efficiency and emissions reduction, (iii) technological innovation and adoption and (iv) circular economy and sustainable sourcing. Implementation challenges were grouped into four categories: financial, technical, operational and institutional, highlighting limited investment, weak policy support and shortages of skilled professionals. The study emphasizes that strengthening institutional capacity, establishing credible policy anchors, enhancing technical expertise, capacity-building through training and research and stakeholder collaboration are critical to accelerating sustainability adoption. The study highlights key gaps in the adoption of sustainability and innovation in the EWP industry. The findings establish an evidence base to strengthen policies, industry practices and stakeholder collaboration, supporting actionable strategies toward a more sustainable and competitive EWP sector.
Elsayed AE Ali, Dina Mostafa Mohammed, Fatma Abd El Gawad
et al.
Essential oils (EOs) are valuable sources of bioactive compounds derived from food processing waste by-products (FPWB). This study focuses on the valorization of FPWB to enhance both the quantity and quality of EOs extracted using eco-friendly methods, with applications in human and animal food systems. Green extraction techniques, such as microwave-assisted extraction, ultrasound extraction, and cold plasma methods, offer numerous advantages. These include improved extraction efficiency, higher yields, reduced waste, and the preservation of EO quality. Additionally, these methods promote sustainability by lowering energy consumption. The study highlights the positive impact of EOs across various sectors. EOs act as natural preservatives in human food systems, enhancing food safety and stability. Animal nutrition contributes to improved animal health and feed palatability. The extraction process and the chemical composition of EOs significantly influence physicochemical properties. The quality and composition of EOs are largely determined by the extraction techniques used, which positively affect their physicochemical properties. While these methods are associated with challenges, advanced delivery systems and ongoing research in green extraction techniques hold promise for overcoming these limitations and optimizing the application of EOs in food preservation, animal nutrition, and other fields. Continued advancements in technology and innovation will drive progress in this area.
Federico Gibellini, Piero Fraternali, Giacomo Boracchi
et al.
Improper solid waste management represents both a serious threat to ecosystem health and a significant source of revenues for criminal organizations perpetrating environmental crimes. This issue can be mitigated thanks to the increasing availability of Very-High-Resolution Remote Sensing (VHR RS) images. Modern image-analysis tools support automated photo-interpretation and large territory scanning in search of illegal waste disposal sites. This paper illustrates a semi-automatic waste detection pipeline, developed in collaboration with a regional environmental protection agency, for detecting candidate illegal dumping sites in VHR RS images. To optimize the effectiveness of the waste detector at the core of the pipeline, extensive experiments evaluate such design choices as the network architecture, the ground resolution and geographic span of the input images, as well as the pretraining procedures. The best model attains remarkable performance, achieving 92.02 % F1-Score and 94.56 % Accuracy. A generalization study assesses the performance variation when the detector processes images from various territories substantially different from the one used during training, incurring only a moderate performance loss, namely an average 5.1 % decrease in the F1-Score. Finally, an exercise in which expert photo-interpreters compare the effort required to scan large territories with and without support from the waste detector assesses the practical benefit of introducing a computer-aided image analysis tool in a professional environmental protection agency. Results show that a reduction of up to 30 % of the time spent for waste site detection can be attained.
Christia Meidiana, Florin-Constantin Mihai, Tonni Agustiono Kurniawan
et al.
This study investigates the factors influencing illegal waste dumping in Bangkalan District, a rapidly urbanizing rural area in Indonesia. Illegal dumping has become a significant environmental and public health concern due to inefficient waste management systems, irregular collection schedules, and inadequate infrastructure. The research identifies key socio-economic, demographic, and technical factors contributing to illegal dumping behaviors. Through data collected from 387 households, a Multilinear Regression (MLR) analysis reveals that six factors such as low income, lower education levels, larger family sizes, irregular waste collection services, easy accessibility and short distance to illegal dump site (IDS) significantly increase illegal dumping rates. The findings emphasize the need for improving waste management infrastructure, enhancing public awareness, and addressing economic constraints to mitigate illegal dumping. By identifying the primary drivers of illegal dumping, this research contributes to achieving several United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 3 (Good Health and Well-being), and SDG 12 (Responsible Consumption and Production). The study concludes with policy recommendations for improved waste management and enforcement, offering insights for addressing this issue in other rapidly urbanizing rural areas.
Shilpy Rani Basak, Samin Azhan Chowdhury, Rafiuzzaman Khan
et al.
Tannery residues possess the potential to produce biogas through anaerobic co-digestion processes. Research related to anaerobic co-digestion of food wastes and easily biodegradable wastes is ongoing and a vast advancement has been observed already to reclaim biogas as recycled energy. However, a review on the co-digestion of tannery residues and their potentiality to produce recycled energy has been initiated very limitedly. As these residues are more persistent compared to the biodegradable ones, their conversion to a simpler and safer form is highly required. To fill in this gap, an approach to review the co-digestion of tannery residues and its potential degradation kinetics has been initiated here so that the prime co-digestion- and kinetic- parameters are evaluated. Moreover, four generic equations with 45 parameters (variable and constant) have been developed based on the existing literature to explain the bacterial growth with substrate- and product- inhibition as well as substrate degradation. This review outcome will lead to the biochemical modelling of the degradation of tannery residues for various co-digestion elements. It will lead the modelers to find not only the potential parameters to be considered during co-digestion but also the effective initiations of related experiments.
This study aims to analyze the implementation of election-level simplification from a legal perspective to overcome the waste of election resources and costs. Elections in Indonesia have faced various challenges, including waste in excessive paper usage, overlapping stages, and inefficient budget allocations. These inefficiencies not only burden the General Elections Commission (KPU) but also affect the effectiveness and transparency of the democratic process. Simplification of election levels is expected to be an effective solution to reduce the administrative and material burdens that hinder the implementation of elections. By streamlining the structure and reducing redundant stages, election organizers can focus more on quality, security, and public participation. This study uses a normative juridical approach by analyzing relevant laws and regulations, such as Law Number 7 of 2017 concerning General Elections, as well as various policies and proposals related to election-level simplification. The analysis also includes legal principles such as efficiency, effectiveness, and legal certainty. Furthermore, the study examines how other democratic countries manage election logistics efficiently to draw lessons that can be contextualized in Indonesia. The results of this study are expected to provide concrete policy recommendations that support the implementation of simplified election systems. These recommendations are aimed at optimizing the election process by minimizing waste, both in terms of budget and the use of natural and human resources, while maintaining the integrity and legitimacy of the democratic process. Thus, this study contributes to the discourse on election reform and democratic strengthening in Indonesia.
Runit Isaac, Shaziya Siddiqui, Prerna Higgins
et al.
This study analyzed the water quality of the Yamuna river in Prayagraj across nine locations where the sampling was done upstream, downstream and middle stream from May 2019 to April 2020 using fourteen water quality parameters. Quarterly samples showed good Water Quality Index (WQI) values for summer (95.19), monsoon (77.28), and winter (90.77), but a decline in spring (102.11) due to religious activities was observed. Inductively coupled plasma mass spectroscopy suggested high concentration of Ca2+, Mg2+, K, and P in the river. Principal Component Analysis revealed 9 significant factors (eigen value >0.5) covering 25.13 – 93.89 % variance. Strong correlations included TDS-EC (0.853) and Ca2+ – Mg2+ (1.00) was observed. The correlation between water quality parameters generated by principal component analysis showed that the main parameters affecting the water quality vary in all the seasons. Based on the water quality indicators, anthropogenic activities are accountable to deteriorate the quality of river water. Therefore, the pollution status of the river need to be made publicly.
Traditional methods for evaluating the bioconversion capacity of organic solid waste are known for time-consuming property and often exhibit low prediction accuracy. However, leveraging fractal dimensions offers a more precise characterization of the complexity, irregularity, and spatial structure of organic solid waste. In this study, a novel and efficient method for evaluating the bio-accessibility of straw's anaerobic transformation, based on fractal dimensions, was introduced. To comprehensively compare the structural differences, this research encompasses the measurement of nine different varieties of straw under ten distinct pretreatment conditions. The regression sum of squares for these correlations consistently exceeds 0.83, highlighting the robustness of our findings. The results unequivocally demonstrate the close relationship between the fractal dimension and the structural characteristics of straw. This relationship underscores the utility of fractal dimension analysis as a reliable tool for evaluating the anaerobic bio-accessibility of organic solid waste.
Chukwunonso O. Aniagor, A.A. Aly, Laifa.A Mohamed
et al.
In this study, lupine seed (Lu-SP) and pumpkin seed shells (PSSP) biomasses were used to create alternative and effective adsorbents. Methylene blue (MB) dye was removed from wastewater using the as-prepared adsorbents at variables solution pH 2.0 –11.0, contact period (0–180 min), and adsorbent mass (0.2–2.0 g/L). The solution pH had a synergistic effect on the improved removal of MB and the optimal adsorption removal for both adsorbents occurred at pH 8.0 and 120 min. The adsorption isotherm modelling results showed a good fit with the Langmuir model, with a maximum monolayer adsorption capacity of 48.98 and 77.48 mg/g for PSSP and Lu-SP, respectively. Similarly, the pseudo-first-order (PFO) model is regarded as the best-fit kinetic model for both adsorbents and suggests the predominance of physisorption via interfacial diffusion. Mechanistic investigation of the present system suggests that both intraparticle diffusion and surface sorption mechanisms control the adsorption rate. Notably, the Lu-SP with a lower surface area (54.013 m2/g) outperformed the PSSP (235.992 m2/g) in terms of adsorption capacity under varying pH. Therefore, in addition to electrostatic interaction, adsorption into the micropores via volume filling is considered one of the adsorption mechanisms. This study, therefore, revealed that the PSSP and Lu-SP may be very helpful for removing cationic MB dye from contaminated wastewater.
Keyur K. Moradiya, C. Srisangari, Sachin V. Jadhav
et al.
Common effluent treatment plants (CETPs) offer extensive benefits for wastewater treatment in developing countries in terms of cost-effectiveness, industrial synergy, and resource conservation. Evaluating the performance of CETPs is essential to ensure sustainable practices in wastewater management. The present study aims to assess the environmental impacts of a CETP situated in Maharashtra, India, using the life cycle assessment method (LCA) as per ISO 14040:14044. The plant comprises a primary, secondary, and tertiary treatment unit along with a sludge handling unit. The inventory analysis was performed using the averaged data collected from the plant for a year. The secondary inputs were taken from the GaBi 10.6 database suited to the Indian context. The study employed a gate-to-grave LCA approach and the functional unit was assumed to be 1000 m3 of treated water. The impact analysis was conducted with the help of the CML 2001: Aug 2016 method. It was found that the primary and secondary treatment units offered the highest environmental burden. Both the treatment units contribute about 70–80 % to all the categories except for ADP-elemental, where the contribution is about 98 %. Electricity was identified as a predominant factor contributing to the impacts under most midpoint categories except for ADP-elemental. A scenario analysis was undertaken to estimate the possibility of adapting to renewable energy to reduce environmental footprints. The impacts generated under such a scenario were lower than the original observations, except for the ADP–elemental category. The study emphasizes how LCA helps optimize areas under investigation and fosters sustainable treatment practices in wastewater treatment.
Bashir Aderemi Hamzat, Aiman Hakim Supee, Muhammad Abbas Ahmad Zaini
Water pollution is a critical environmental concern, and this study explores the potential of utilizing adsorbents from palm fatty acid distillate (PFAD) for the removal of methylene blue (MB) and congo red (CR) dyes from aqueous solution. The PFAD, a by-product of palm oil refining is a valuable adsorbent feedstock because it is freely available, abundant and high in carbon content. The PFAD adsorbents were synthesized via zinc chloride activation and characterized for elemental composition, specific area, surface chemistry and morphology. The process converts the semi-solid PFAD into solid adsorbents with surface area ranging from 22 m2/g to 222 m2/g. The specific area significantly increased with pyrolysis temperature, and so the adsorption of dyes. The results provide insights into the viability of PFAD adsorbents for effective removal of MB and CR dyes. Nonetheless, the process optimization and the true potential of PFAD adsorbents should be further explored.
Abdul-Rahaman Afitiri, Simon Appah Aram, Marion Martienssen
Solar disinfection treatment technologies (SODIS) have emerged as simple and effective microbiological water treatment techniques especially for deprived communities in Low-and Middle-Income Countries (LMICs) lacking access to safe drinking water systems. While the integration of Advanced Oxidation Processes (AOP) techniques with SODIS for drinking water treatment has been advocated for such communities often lacking not only clean water but also reliable energy, the status of knowledge on empirical testing of these advancements remain fragmented and yet to be fully understood. In this intervention, we synthesize the literature to understand the progress made so far, the cumulative effect of AOP integration with SODIS and remaining questions for future empirical studies on AOP integrations with SODIS for sustainable clean water supply for all. Using the PRISMA methodology, we included and analyzed data from 16 empirical testing of AOP and SODIS integration between 1995 and 2022 reported in 37 studies retrieved from databases including PubMed, Web of Science, ScienceDirect, and Google Scholar. Results show AOP integration with SODIS significantly reduces time for complete disinfection of contaminants in relation to SODIS alone; non-recovery of inactivated organisms as well as the inactivation of SODIS resistance organisms for improved water production. The availability of suitable catalyst (reagents), sunlight availability and intensity as well as simple operational designs are some factors that inform the feasibility and operation of SODIS systems and their integration with AOP. It is recommended that future development agenda and research on water systems should focus on laboratory-scale experiments to pilot projects and improving inactivation efficiency for different AOP and their combined effects on water contaminants.
Chinedu M. Agu, Kingsley A. Ani, Prince O. Abiazieije
et al.
Biodiesel from vegetable or animal feedstock can serve as a suitable source for renewable energy. This study utilized heterogeneous catalyst obtained from fish bone for biodiesel production from raw cat fish waste (CFW) oil. The CFW oil yield obtained using wet reduction extraction method was 96.85 %. The heterogeneous catalyst was prepared by calcination at 600 °C, for 4 h and characterized using SEM-EDX. Catalyst characterization showed suitable elements that can improve the catalytic activity. Physiochemical characterization results showed that viscosity of CFW oil (48.782 mm2/s), reduced to 9.391 mm2/s in the produced biodiesel. Similarly, after transesterification free fatty acid (3.593 mg/KOH/Kg) and acid value (7.186 mg/KOH/Kg) of CFW oil reduced to 1.48 mg/KOH/Kg and 2.96 mg/KOH/Kg, respectively, in the biodiesel. Finding from the Fourier Transform Infrared (FTIR) Spectrum of the raw CFW oil showed the presence of –OH and was assigned to the axial deformation of water molecule. However, the –OH group disappeared in the FTIR spectrum of biodiesel due to the transesterification process. This observation is consistent with the findings for moisture contents of raw CFW oil (0.073 %) and biodiesel (0.00 %), which showed disappearance of water after transesterification. The biodiesel yield was further modeled using three algorithms (Scaled conjugate gradient, Bayesian regularization and Levenberg maraquardt) of the artificial neural network (ANN). It was evident that the predictions from the Scaled conjugate gradient algorithm were comparable to the experimental responses. Finally, transesterification of raw CFW oil using heterogeneous catalyst from fish bone, was a cost-effective approach for biodiesel production.
This study analysed the composition and leaching results for 12 IFA samples from a local incineration plant by XRF and leaching tests based on BS EN12457-1:2002. XRF results show that the main elements are Ca, Cl and S in all IFA samples. Leaching test results shows a high leachability of Na, Cl, Br, Pb, Zn and Cu. The accelerated carbonation with (NH4)2CO3 was attempted to inhibit heavy metals leaching and remove soluble salts. The effect of (NH4)2CO3 concentration on carbonation efficiency and inhibition of heavy metal leaching was systematically investigated. TGA and ICP-MS were used to determine carbonation capacity and heavy metal leaching, respectively. TGA results show the maximum carbonation capacity is achieved in one hour with 10 wt% (NH4)2CO3 and 76% carbonation occurs -in the first 10 min. Leaching test results reveal that Cu and Pb are efficiently immobilised when the concentration of (NH4)2CO3 is as low as 2 wt% with a s/l ratio of 1:5 within 1 hr. Increasing the concentration of (NH4)2CO3 to 4 wt%, the leaching rate of Zn is also below NEA RVs (National Environment Agency of Singapore). Carbonation is also effective to immobilise Cd and Ni, but not for Cr since it exists as CrO42- and cannot be carbonated. XRF results from a larger scale reaction confirm the significant removal of soluble salts, and lower leachability (except SO42-) is substantiated by leaching tests. By integrating the processes of CO2 capture with ammonia and accelerated carbonation, our work contributes to CO2 sequestration and IFA detoxification.