Search Results (29)

The increase in garbage generated in modern societies demands the implementation of a more sustainable model as well as new methods for efficient waste management. This article describes the development and implementation of a prototype of a smart bin that automatically sorts waste using a multi-agent system and blockchain integration. The proposed system has sensors that identify the type of waste (organic, plastic, paper, etc.) and uses collaborative intelligent agents to make instant sorting decisions. Blockchain has been implemented as a technology for the immutable and transparent control of waste registration, favoring traceability during the classification process, providing sustainability to the process, and making the audit of data in smart urban environments transparent. For the computer vision algorithm, three versions of YOLO (YOLOv8, YOLOv11, and YOLOv12) were used and evaluated with respect to their performance in automatic detection and classification of waste. The YOLOv12 version was selected due to its overall performance, which is superior to others with mAP@50 values of 86.2%, an overall accuracy of 84.6%, and an average F1 score of 80.1%. Latency was kept below 9 ms per image with YOLOv12, ensuring smooth and lag-free processing, even for utilitarian embedded systems. This allows for efficient deployment in near-real-time applications where speed and immediate response are crucial. These results confirm the viability of the system in both accuracy and computational efficiency. This work provides an innovative solution in the field of ambient intelligence, characterized by low equipment cost and high scalability, laying the foundations for the development of smart waste management infrastructures in sustainable cities. Full article

Electroplating sludge, a hazardous waste generated from the electroplating industry, contains significant quantities of heavy metals such as Cu, Cr, and Ni. Improper disposal of these metals poses severe environmental and health risks. This study proposes a comprehensive resource recovery process for Cu, Ni, and Cr from electroplating sludge, involving leaching, solvent extraction, stripping, and precipitation. The extraction efficiency of three extractants (P507, LIX984, and M5640) was evaluated, with M5640 demonstrating superior performance in Cu recovery (near 100%) at pH 3.0–4.0. Multi-stage extraction and stripping experiments further optimized metal recovery, achieving high efficiencies for Cu, Cr, and Ni. The recovered metals were precipitated as CuCO₃, CrPO₄, and Ni(OH)₂, with wastewater discharge meeting environmental discharge standards. This study not only enriches the technical approaches for the selective recovery of high-value metals from electroplating sludge with complex components, but also closely aligns with the laws, regulations, and policies of the Chinese government regarding environmental governance. It serves as a driving force for promoting the construction of “waste-free cities” and the establishment of a closed-loop circular economy industrial chain. Full article

The fallen leaf has the potential to be energy-valorized in cities with sustainability goals. Thermochemical characterization of garden waste through pyrolysis and combustion kinetics will establish the reactivity of this lignocellulosic biomass as biofuel for thermochemical conversion processes for energy recovery. Herein, the thermal degradation of two types of pellets produced from fallen leaf (pellets without glycerol PG0, and pellets with 5 wt% glycerol PG5) are characterized under inert and oxidative atmospheres using three different approaches: thermogravimetry (TG) and differential thermogravimetry (DTG) analyses, TG-based reactivity, and reaction kinetics from three model-free isoconversional methods. The model-free isoconversional methods are Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), and Friedman, which were applied for estimating the kinetic parameters, activation energy (Eα) and pre-exponential factor, using different heating rates (20, 30, and 40 °C/min) to ensure reliable data interpretation. The pyrolysis results showed that PG5 was more reactive compared to PG0 because the addition of glycerol during the pelletizing process increased the volatile matter and oxygen content in PG5. Likewise, the higher reactivity of PG5 under pyrolysis was determined by average activation energy (Eα) with an average value of 96.82 kJ/mol compared to 106.46 kJ/mol for PG0. During the combustion process, Eα was 90.70 kJ/mol and 90.29 kJ/mol for PG0 and PG5, respectively. Finally, both materials exhibited higher reactivity under an oxidative atmosphere. Therefore, according to our results, the pellets produced from leaf litter can be used as biofuels for thermochemical processes, highlighting that using glycerol as a binder favors the reactivity of the densified garden waste. Full article

A fundamental step to foster a sustainable future is enhancing students’ awareness of responsible food consumption. The present research study assessed students’ awareness of food waste (FW) issues, attitudes towards school catering and lunch management, and the reasons for plate waste (PW) in Rezekne city schools, Latvia. A survey was conducted in April 2024 involving 944 students in grades 2 to 7 across four selected schools (S1, S2, S3, and S4), provided with state and municipality-funded free lunches. Statistical analysis methods (Mean ± SD, Kruskal–Wallis H test, Mann–Whitney U post hoc test, and Spearman’s correlation analysis) were used to analyze the results. The findings revealed limited awareness and knowledge of students about FW issues, and generally indifferent attitude towards FW and school meals. In addition, significant dissatisfaction with the sensory qualities of meals was observed, yet sensory satisfaction did not correlate with FW levels, pointing to broader issues within the catering model. The restrictive pre-served portion system was found ineffective in reducing FW and fostering responsible consumption. A sustainable catering model should empower students to independently choose the type and quantity of food, combining their abilities and motivation with practical actions. These findings provide a basis for strategies aimed at reducing FW and promoting responsible and sustainable food consumption in Latvian schools. Full article

Community Restaurants (CRs), part of the Brazilian government’s Popular Restaurant Program (PRP), provide free and/or affordable nutritionally balanced meals as an essential strategy to meet the most vulnerable population’s basic needs and rights. This cross-sectional study evaluated the effectiveness of these CRs’ proposed objectives in cities with ≥100,000 inhabitants in Brazil’s northern and northeastern regions—Brazil’s most vulnerable and historically unequal regions. Effectiveness was assessed using a CR evaluation matrix-based indicator system to classify CRs as “not very effective”, “effective”, or “very effective”. Among the 94 CRs assessed (north: n = 23, 24.5%; northeast: n = 71, 75.5%), most were classified as “effective” or “very effective”, except for the northern states of Amapá and Tocantins, whose only CR was rated as “not very effective” and the northeastern state of Sergipe, which had a PR considered “not very effective”. State-operated CRs predominated (north: 82.6%; northeast: 76.1%) and primarily operated Monday to Friday (north: 87.0%; northeast: 59.2%), with 35.2% of the northeast CRs operating daily, serving lunch as the main meal (100%). Average daily meal counts were 486.5 (north) and 926.9 (northeast), and the average meal offering time was from 10:55 am to 1:21 pm in the north and from 10:35 am to 2:00 pm in the northeast region, with costs averaging USD 0.27 and USD 0.20, respectively. All CRs employed a nutritionist as a technical manager responsible for menu planning and demonstrated compliance with essential infrastructure criteria, including regular waste collection, water supply, and proximity to public transport. Most were in areas with sanitary sewage coverage (north: 91.3%; northeast: 98.6%) and had monitoring mechanisms (91.3% north; 94.4% northeast) and prioritization systems for vulnerable populations (north: 73.9%; northeast: 80.0%). These findings indicate that CRs in these regions effectively strive to address food security goals, demonstrating tangible outcomes that benefit society. Full article

This paper proposes the PDDS model and constructs a three-dimensional analysis framework of policy objectives–policy tools–value chain in order to provide an in-depth analysis of 224 waste-free city policy texts released by China from 2019 to 2024. This study finds that China’s waste-free city policy objectives are macro-oriented, with specific objectives and milestones accounting for a relatively low proportion. Furthermore, there is a structural imbalance in policy tools, with environmental tools dominating and supply- and demand-based tools lagging behind. Additionally, support for each link in the value chain is uneven, with emphasis on the waste generation and disposal link, but the collection and regulation link is weak. In the three-dimensional analysis, China’s waste-free city policy exhibits a pattern of “overall goal leadership + environment-oriented policy tools + green industrial upgrading”. This study proposes a number of refinements to the policy objectives, improvements to the structure of policy instruments, enhanced synergies among the various segments of the value chain, and an increase in the aggregation effect of the policy objectives, instruments, and the evaluation chain. These changes are intended to promote the optimisation of waste-free city policies and the sustainable development of the environment in China and other countries. Full article

Since 2019, eighteen major ministries and commissions, including the National Development and Reform Commission, have launched trials for a “zero-waste city”. Shenzhen, Baotou, Tongling, and 16 other cities and regions have entered the practical operation stage, and the significance of the economic effect of the policy pilot needs to be tested through empirical evaluation. This study systematically gathers time series data from 281 prefecture-level cities in China from 2005 to 2022 and constructs an innovative experimental framework for the construction of a zero-waste city. It implements a series of rigorous robustness testing procedures using the difference-in-differences (DID) method to scientifically and objectively measure the actual effects of waste-free city construction strategies in promoting the city’s social development along a high-quality development path. This study provides deep insights into the zero-waste city construction strategy as a strong driving force. Our results indicate that the high-quality development stage has a positive impact on the city as a whole that cannot be ignored. At the same time, in-depth analysis shows that this strategy exhibits strong regional differences in the process of promoting high-quality urban development. For the two core regions of eastern and central China, the implementation of zero-waste city policies has significantly accelerated the pace of high-quality development, and further analysis reveals that, compared with the developed eastern region, the implementation of this policy in the central region has achieved superior results in terms of high-quality development. Third, the benefits of waste-free city policies are related to the economic bases of cities, the number of green patents granted, national policies, geographical location, and other factors. Full article

Food waste is a significant concern when it comes to food safety. It is a well-known fact that fruit and vegetable wastage is high worldwide; however, quantitative data, especially on such waste in the retail sector, are limited. Wasted vegetables are sources of essential dietary compounds, benefiting from their revalorization. Studies related to the evaluation of the quantity and quality of these vegetables discarded in the retail sector can allow for the proposal of relevant alternatives for their use and the guarantee of food safety. This study aimed to assess wasted vegetables (beetroot, carrot, chayote, and cucumber) in the city of Pirassununga (Brazil) and characterize the purees obtained from these vegetable wastes. The purees were characterized in terms of microbiological aspects, color, proximal and mineral composition, phenolic concentration, and antioxidant activity. It was observed that 90% of the discarded vegetables were free from microbiological contamination and could be considered suitable for consumption according to the adopted classifications. Additionally, the purees had high nutritional levels, such as phenolics and fiber. Thus, considering the high levels of vegetable waste generated in the retail sector, and high value nutritional, vegetable waste could be viable in the development of new products, making it an important retail strategy for the circular economy. Full article

With rapid urban development, the “waste-free city” concept has emerged. Therefore, the accurate prediction of the amount of C&D waste is of great importance. However, many countries and regions, including China, have not yet established C&D waste databases and standard prediction methods. This study proposed a method using a weighted combination of the grey theory model (GM) and the autoregressive integrated moving average (ARIMA) model to predict the quantity of urban C&D waste in the future. Based on a case study in Guangzhou, this study compared the prediction results of three prediction models, namely the GM, the ARIMA, and the proposed weighted combined model of the GM and the ARIMA (GM-ARIMA). The results of this study proved that the proposed combined GM-ARIMA model had a better predictive performance than both the separated models. The mean absolute percentage errors (MAPE) of the GM and ARIMA models were 12.11% and 14.26%, respectively, whereas the proposed GM-ARIMA model had a lower MAPE (8.5%). This study found that the generation of C&D waste in Guangzhou will continue to grow steadily. From 2024 to 2035, the quantity of C&D waste is expected to reach 850 million tons cumulatively, with an annual growth rate of 7.1%. Full article

Finding a method to provide the installed Internet of Things (IoT) nodes with energy that is both ubiquitous and long-lasting is crucial for ensuring continuous smart city optimization. These and other problems have impeded new research into energy harvesting. After the COVID-19 pandemic and the lockdown that all but ended daily activity in many countries, the ability of human remote connections to enforce social distancing became crucial. Since they lay the groundwork for surviving a lockdown, Internet of Things (IoT) devices are once again widely recognised as crucial elements of smart cities. The recommended solution of energy collection would enable IoT hubs to search for self-sustaining energy from ecologically large sources. The bulk of urban energy sources that could be used were examined in this work, according to descriptions made by researchers in the literature. Given the abundance of free resources in the city covered in this research, we have also suggested that energy sources can be application-specific. This implies that energy needs for various IoT devices or wireless sensor networks (WSNs) for smart city automation should be searched for near those needs. One of the important smart, ecological and energy-harvesting subjects that has evolved as a result of the advancement of intelligent urban computing is intelligent cities and societies. Collecting and exchanging Internet of Things (IoT) gadgets and smart applications that improve people’s quality of life is the main goal of a sustainable smart city. Energy harvesting management, a key element of sustainable urban computing, is hampered by the exponential rise of Internet of Things (IoT) sensors, smart apps, and complicated populations. These challenges include the requirement to lower the associated elements of energy consumption, power conservation, and waste management for the environment. However, the idea of energy-harvesting management for sustainable urban computing is currently expanding at an exponential rate and requires attention due to regulatory and economic constraints. This study investigates a variety of green energy-collecting techniques in relation to edge-based intelligent urban computing’s smart applications for sustainable and smart cities. The four categories of energy-harvesting strategies currently in use are smart grids, smart environmental systems, smart transportation systems, and smart cities. In terms of developed algorithms, evaluation criteria, and evaluation environments, this review’s objective is to discuss the technical features of energy-harvesting management systems for environmentally friendly urban computing. For sustainable smart cities, which specifically contribute to increasing the energy consumption of smart applications and human life in complex and metropolitan areas, it is crucial from a technical perspective to examine existing barriers and unexplored research trajectories in energy harvesting and waste management. Full article

This study aims to assess the current status of green agricultural development and its influencing factors in Lincang City, a national innovation demonstration zone for sustainable development; it also seeks to enhance the potential and competitiveness of green agricultural development in underdeveloped border areas. To achieve this, an evaluation index system is constructed encompassing six dimensions. Using a coupled coordination and obstacle degree approach, this study explores the spatiotemporal differences in the level of green agricultural and sustainable development, as well as the power, coupled coordination degree, and factors that negatively impact green agricultural development in Lincang City from 2010 to 2019. The Liang-Kleeman information flow method is applied to uncover the key information flow factors that influence the coupled coordination degree in each county and district of Lincang City. The results reveal several insights: First, the comprehensive score of sustainable green agricultural development increased from 0.4405 to 0.5975 during the study period. Second, the coupling coordination degree of green agricultural development was relatively low, fluctuating between 0.1821 and 0.2816. Overall, the development has shifted from severe imbalance to mild imbalance. Third, the obstacle degree increased by 3.75%. From a systemic perspective, the “resource conservation” layer had the highest barrier level, with the maximum value being observed in Yun County at 25.5%. Further analysis of the indicators reveals that the use of outdated water-saving irrigation techniques has resulted in low irrigation efficiency and excessive water resource waste. This is the main cause of the high barrier levels in terms of water-saving irrigation intensity and effective irrigation area. Moreover, the excessive use of chemical pesticides to enhance vegetable production has contributed to high barrier levels for achieving yields of pollution-free vegetable production per unit area. Finally, the information flow values of the factors influencing the coordinated and harmonious development of green agriculture exhibit significant regional heterogeneity among counties and districts. The highest information flow value for the area of drought- and flood-resistant crop cultivation is in Zhengkang County at 1.86. Based on these results, local government departments and decision-makers should focus on promoting comprehensive improvements in the level of green agricultural development. It is crucial to tailor measures to the specific needs of each county to address the shortcomings in green agricultural development. Additionally, efforts should be made to strengthen the innovation-driven chain of green agricultural development, including production, processing and sales. Enhancing the green agricultural development system is essential for long-term progress. Full article

Statistical surveys about rabbits in households brought interesting results about their breeding. The survey shows that approx. 8.3% of Slovak households breed rabbits, of which the majority are bred in the countryside (61%), followed by breeding in cities (35%), and 4% of households stated both options. As part of the investigation, information was also obtained on the method of breeding rabbits. The results showed that housing with the restriction of movement is the predominant breeding method. Housing without the restriction of movement is higher in cities compared to rural areas, while free breeding is absent in households for both options. The information on excrement recovery showed that approximately 59.5% of all farm waste is composted, 15.8% of respondents said that they apply farm excrement to the soil, and the remaining respondents did not answer. The post-processing survey results led to new estimates of methane and nitrous oxide emissions from domestic rabbit farming. The emissions were estimated using the methodology of the tier 2 approach outlined in the IPCC 2019 Refinement. The results indicated that rabbit breeding in households and farms in Slovakia generates an average of 0.51 Gg of methane and 0.13 Gg of nitrous oxide annually. Additionally, when free-range rabbit breeding is considered, emissions are 0.001 Gg of nitrous oxide. These greenhouse gas emissions from rabbit farming contribute to 7% of the total emissions from animal farming, ranking it as the third highest emitter after sheep. Consequently, it is imperative to prioritize the inclusion of this category in Slovakia’s national emissions report. Full article

The South Saskatchewan River (SSR) is one of the most important river systems in Saskatchewan and, arguably, in Canada. Most of the Saskatchewan residents, industries, and powerplants depend on the SSR for their water requirements. An established 1D modelling approach was chosen and coupled with the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). The WASP (Water Quality Analysis Simulation Program) stream transport module, TOXI, is coupled with flow routing for free-flow streams, ponded segments, and backwater reaches and is capable of calculating the flow of water, sediment, and dissolved constituents across branched and ponded segments. Copper and nickel were chosen as two metals with predominantly anthropogenic (agriculture, mining, and municipal and industrial waste management) and geogenic (natural weathering and erosion) sources, respectively. Analysis was carried out at ten different sites along the South Saskatchewan River, both upstream and downstream of the City of Saskatoon, in the years 2020 and 2021. Model performance was evaluated by comparing model predictions with concentrations of copper and nickel measured in a previously published study. The model performed well in estimating the concentrations of copper and nickel in water samples and worked reasonably well for sediment samples. The model underestimated the concentration values at certain segments in both water and sediment samples. In order to calibrate the model more accurately, extra diffusive contaminant loads were added. While several default parameter values had to be used due to the unavailability of primary historical data, our study demonstrates the predictive power of combining WASP—TOXI and HEC-RAS models for the prediction of contaminant loading. Future studies, including those on the impacts of global climate change on water quality on the Canadian prairies, will benefit from this proof-of-concept study. Full article

Hydrogen has universally been considered a reliable source of future clean energy. Its energy conversion, processing, transportation, and storage are techno-economically promising for sustainable energy. This study attempts to maximize the production of H₂ energy using nanocatalysts from waste aluminum chips, an abundant metal that is considered a potential storage tank of H₂ energy with high energy density. The present study indicates that the use of waste aluminum chips in the production of H₂ gas will be free of cost since the reaction by-product, Al₂O₃, is denser and can be sold at a higher price than the raw materials, which makes the production cost more efficient and feasible. The current framework investigates seven different copper oxide-based graphene nanocomposites that are synthesized by utilizing green methods and that are well-characterized in terms of their structural, morphological, and surface properties. Reduced graphene oxide (rGO) and multi-layer graphene (MLG) are used as graphene substrates for CuO and Cu₂O NPs, respectively. These graphene materials exhibited extraordinary catalytic activity, while their copper oxide composites exhibited a complete reaction with feasible techno-economic production. The results revealed that the H₂ production yield and rates increased twofold with the use of these nanocatalysts. The present study recommends the optimum reactor design considerations and reaction parameters that minimize water vaporization in the reaction and suggests practical solutions to quantify and separate it. Furthermore, the present study affords an economic feasibility approach to producing H₂ gas that is competitive and efficient. The cost of producing 1 kg of H₂ gas from waste aluminum chips is USD 6.70, which is both economically feasible and technically applicable. The unit cost of H₂ gas can be steeply reduced by building large-scale plants offering mass production. Finally, the predicted approach is applicable in large, medium, and small cities that can collect industrial waste aluminum in bulk to generate large-scale energy units. Full article

Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities’ administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents’ attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is ‘full,’ ‘not full,’ or ‘empty.’ This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time. Full article