Search Results (9,749)

Pb–Zn slag and smelting activities represent a persistent global source of soil contamination, releasing toxic heavy metals—lead (Pb), zinc (Zn), cadmium (Cd), and arsenic (As)—with documented risks to ecosystems and human health. Although previous reviews have addressed heavy metal contamination near smelters and pollution indices as assessment tools, no review has specifically mapped environmental assessment methods for Pb–Zn slag-contaminated soils, and evidence from Central Asia remains absent. This scoping review, following PRISMA-ScR 2018 guidelines, maps the global evidence base on soil contamination from Pb–Zn slag and associated assessment methods. Searches across Dimensions, PubMed, and OpenAlex identified 410 records; 56 studies (2010–2025) met the inclusion criteria. Studies were concentrated in China (35.7%), Poland (8.9%), and Brazil (7.1%); no studies from Kazakhstan were identified despite major Pb–Zn smelting operations in the Shymkent region. All studies reported heavy metal concentrations exceeding regulatory thresholds, with cadmium as the primary ecological risk driver and lead posing the greatest health risk to children. Assessment methods included pollution indices (73.2%), ecological risk assessment (67.9%), GIS-based spatial analysis (57.1%), human health risk frameworks (51.8%), and source apportionment models (50.0%). Post-2018 studies increasingly applied integrated multi-method frameworks. Critical gaps include the absence of Central Asian research, limited predictive modeling, and a lack of standardized protocols. Findings provide a structured evidence map to guide environmental monitoring and remediation at slag-contaminated sites globally. Full article

The location of the decommissioned factory of plastics and chemical products Jugovinil, City of Kaštela, Croatia, has gained significant attention for urban development and the establishment of tourist facilities over the past three decades. Since the site is on the coast of the Adriatic Sea, on the shore of Kaštela Bay, where nautical tourism is already developed, plans for a five-star tourism complex were initiated. Given that the former industrial plant, its coal-powered power plant, and other later industrial activities (small shipyards) caused a certain degree of contamination with NORM (naturally occurring radioactive material) residues and heavy metals, an on-site detailed investigation was conducted into the spatial distribution and concentration evaluation of contaminants within dozens of soil samples, and the distributions of contaminants in the area of interest were shown in the form of maps. This study applies an integrated GIS and geostatistical framework to analyze the spatial distribution of multiple contaminants. Maps highlighting polluted zones are included, along with maps indicating areas with higher cumulative concentrations of contaminants. This paper provides an overview of potential issues related to the detected contaminants, as well as proposals for remediation methods before repurposing the site using retrospective data about sources of residues and contaminants. Full article

As major sources of pollution and carbon emissions, energy enterprises have long faced challenges in their technological transformation due to the industry’s characteristics of high investment costs and strong lock-in effects. While formal mechanisms such as government subsidies can impose short-term constraints, they fail to stimulate the sector’s intrinsic motivation. Can the reputation incentive mechanism be the key to breaking the deadlock? This paper constructs a three-party evolutionary game model involving energy enterprises, the public, and the government from the perspective of informal institutions. For the first time, it incorporates the dual effects of reputation gains and losses into a unified framework. The results show that reputation incentives are not merely a “cherry on top,” but rather independently drive transformation by moderating enterprises’ cost–benefit structures. The evolution of the three-party strategies exhibits dynamic synergy, and the system equilibrium depends on the threshold matching of key parameters. Subsidy policies are effective in the short term, but may crowd out the role of reputation in the long term. This paper reveals the underlying logic by which the integration of informal institutions and formal regulations drives profound transformation, offering new theoretical perspectives and practical guidance for designing incentive-compatible multi-stakeholder governance frameworks. Full article

Atmospheric particulate matter poses a high risk by carrying potentially toxic components such as polycyclic aromatic hydrocarbons (PAHs). The major sources of these potentially toxic compounds include traffic-related emissions and winter heating, implying the combustion of fossil fuels or biomass. Air pollution, especially chronic exposure, poses the most serious human health hazard in childhood, and several studies emphasise the importance of research on the potential impacts of air pollution in school environments. While indoor air quality studies are already available in Hungary, investigations on outdoor air pollution in school environments are missing. To fill this gap, in a medium-sized Hungarian town, Veszprém, six schools were selected to assess air quality in the outdoor environments where schoolchildren spend their breaks and have physical training. These schools represent different locations and conditions, from high-trafficked sites to suburban environments. Using resuspended dust samples, environmental quality was assessed based on PAH contents of the samples and ecotoxicity tests (Vibrio fischeri bacterial bioassay). Ecotoxicity of the samples moved in a wide range, from highly toxic to non-toxic. PAH measurements indicated considerable contamination in the case of one sample taken from a suburban area. Source apportionment demonstrated that winter heating is also an important pollution source. Full article

The solar-assisted air source heat pump (SAHP) is a key technology of low carbon heating. However, the SAHP is still inefficient and unstable at low temperatures. Cascaded latent heat storage (CLHS) can store multi-stage thermal energy, which provides the possibility for the multiple utilization of solar energy. Hence, this paper proposed the SAHP integrated with CLHS for building heating. The high-temperature and medium-temperature latent heat storage (LHS) units are used for direct heating, and the low-temperature LHS unit preheats the air for the air source heat pump (ASHP). The thermal performance of the CLHS device is evaluated through combined numerical simulations and experimental tests. Results show that the average heat storage rate of the cascaded system is 61.1% higher than that of a conventional single-stage LHS unit. The heat storage uniformity of CLHS gradually improves with increasing inlet flow rate, but shows a trend of first increasing and then decreasing with the increase in fluid inlet temperature. Among the three tested levels, 80 °C was found to be the most uniform heat storage of the CLHS device. The performance of the system was further analyzed using TRNSYS to assess seasonal building heating performance. The overall efficiencies of the high/middle/low temperature LHS units are 93.6%, 81.6% and 94.3%, respectively. And the solar heat supply accounts for 70.8% of the total heat supply of the system. Compared with the non-preheating system where the low-temperature LHS unit is removed, the COP of the graded heating system is increased by 18.3%, and the energy consumption is reduced by 16.6%. Further parametric optimization based on the Hooke–Jeeves method reduces total system energy consumption by 20.7% and associated pollutant emissions by 20.6% compared with the pre-optimization system. The findings provide practical insights into the application of CLHS in solar-assisted heat pump systems for building heating. Full article

Rapid urbanisation and intensified agriculture are major drivers of groundwater contamination in peri-urban agricultural aquifers worldwide. Contaminants including nitrates and phosphates accumulate through fertilizer use, wastewater infiltration, and groundwater overextraction, creating complex spatial and temporal patterns. Quantifying these impacts under multiple anthropogenic pressures remains a key challenge for effective water resource management. This study develops a Geo-AI ensemble modeling framework that integrates grid-based spatial analysis with advanced machine learning to assess groundwater contamination dynamics. A composite contamination index (CCI) was constructed to synthesize hydrochemical indicators into a unified measure of aquifer degradation. The AI framework uses Graph Neural Networks (GNNs), Light Gradient Boosting Machine (LightGBM), and Deep Long Short-Term Memory Networks (LSTM). Anthropogenic drivers include population growth, infrastructure density, agricultural intensity, groundwater abstraction, and hydroclimatic variability, providing a comprehensive understanding of contamination sources. The methodology was applied to the urbanised aquifer of Manouba, western suburban Tunis (Tunisia), using 295 samples collected from 85 monitoring wells between 2005 and 2025. Validation results show strong predictive performance, with LightGBM achieving R² = 0.986, RMSE = 13.14, and MAE = 1.72, outperforming GNNs (R² = 0.972) and LSTM (R² = 0.943). The spatial analysis reveals a major shift in contamination patterns, with severe contamination expanding to 55% of the study area in 2025, compared with 7% in 2005, while low and slight contamination declined from 45% to 20%. The results highlight how urban expansion reduces recharge, increases pollutant loading, and amplifies aquifer vulnerability, while agricultural intensification further accelerates contaminant accumulation and degradation processes. This framework provides a transferable, data-driven tool for mapping contamination hotspots and supporting targeted, sustainable groundwater management in peri-urban agricultural aquifers under increasing anthropogenic pressures worldwide. Full article

Microplastic (MP) contamination has become a global environmental and public health concern due to the extensive use of plastics and ineffective waste management. These microscopic particles are now detected in air, water, soil, and food products, raising serious concerns about their persistence, bioaccumulation, and potential risks. Microplastics (MPs) have been shown to disrupt marine biodiversity, affect plant metabolism, and enter food webs, leading to accumulation in human tissues. Chronic exposure is increasingly linked to reproductive toxicity, carcinogenesis, neurotoxicity, and metabolic disorders. This review provides a comprehensive overview of the sources, pathways, and environmental fate of microplastics, with an emphasis on their ecotoxicological effects and human health implications. It also summarises key analytical methods for detecting microplastics in environmental and food matrices, including spectroscopy, microscopy, and emerging sensor-based technologies. Finally, the review highlights the need for improved waste management, stronger policy interventions, and enhanced public awareness to mitigate microplastic pollution and protect ecosystem and human health. Full article

Pavement sediments are a significant source of microplastics (MPs) in urban environments and a major contributor to stormwater runoff pollution. In this study, we investigated the abundance and characteristics of microplastics in Beijing’s major road networks and functional zones by collecting road sediment samples, and assessed the ecological risks posed by microplastics in road surface sediments in Beijing. The results showed that the average abundance of microplastics in Beijing pavement sediments was 960.9 items/kg, with the highest abundance observed in commercial areas (1505.7 items/kg). The main characteristics of microplastics were black in color (22.4%), fibrous in shape (55.29%), small to medium in size (10–500 µm, 46.95%), with polyethylene (PE) being the most abundant polymer type (30.69%). The Polymer Risk Index (PRI) method showed clearer differentiation of spatial risk patterns in the Beijing study area, with 5 low-risk sites, 8 medium-risk sites and 15 high-risk sites among the sampling sites. Full article

Microplastic (MP) pollution has emerged as a significant environmental crisis across the Arabian Gulf, driven by rapid urbanization, industrialization, and infrastructure challenges in waste management. Studies indicate that MPs are ubiquitous in nature and are present in different environmental compartments, including coastal waters, sediments, marine biota, and the atmosphere. The region is characterized by high salinity, high UV index, and frequent dust storms that can affect the physical and chemical behavior of plastic debris. A consistent finding across regional studies highlights the fibrous polyethylene (PE) and polypropylene (PP) polymer types as dominant microplastic particles. This prevalence of fibrous MPs highlights the role of secondary microplastics that are derived from the fragmentation of larger plastic items and textile-derived materials as a major contaminant source. Ecological impacts are increasingly observed, with studies reporting MP ingestion in commercially important fish species and the potential for biomagnification into the human food web. However, there exist key knowledge gaps regarding the long-term toxicological impacts on human health. This review synthesizes existing data to improve the understanding of microplastic distribution in Qatar and the Arabian Gulf while highlighting the need for standardized monitoring approaches and appropriate waste management strategies. Full article

This article presents a comprehensive assessment of sediment contamination in the Irtysh River within the industrial zone of the city of Ust-Kamenogorsk, using the Specific Combinatorial Sediment Pollution Index (SCSPI). This study includes a set of priority chemical elements characteristic of the region’s technogenic load (Be, Cu, Zn, As, Se, Cd, Te, Hg, Pb), taking into account their hazard class, persistence in bottom sediments, and ability to accumulate in fine-grained (pelitic) fractions. The assessment was carried out based on the calculation of the frequency index of background exceedance (S_α) and the exceedance multiplicity index (S_β), relative to the effective local background value, followed by the determination of the partial pollution indices (Ki) and the integral SCSPI indicator. It was established that, for most elements, the frequency of exceedance ranges from 75% to 100%, indicating widespread surpassing of the effective local background. The partial indices vary within 4–7 points, with cadmium and zinc making the greatest contribution to the formation of integrated pollution due to the presence of local accumulation zones. Correlation analysis showed that the proportion of the pelitic fraction (<0.01 mm) is most strongly associated with the accumulation of Cd (r = 0.67) and Se (r = 0.66), indicating the preferential accumulation of these elements in fine-grained sediments. Principal component analysis revealed stable geochemical associations among the elements. For the <2.0 mm fraction, the first three principal components explain 73.57% of the total variance, with PC1 mainly associated with Pb, Se, and Cd. For the <0.2 mm fraction, the first three components explain 72.44% of the total variance, and PC1 is characterized by high loadings of Zn, Cd, As, and Se, reflecting the strengthening of the technogenic association in fine-grained material. The SCSPI values across the studied cross-sections range from 5.0 to 5.6, corresponding to a moderately polluted state of bottom sediments (Classes 3a–3b). The spatial distribution of the index reflects the combined influence of technogenic sources and hydrodynamic processes responsible for the redistribution of fine-grained material. The obtained results confirm the applicability of the Specific Combinatorial Sediment Pollution Index (SCSPI) for an integrated assessment of the ecological condition of bottom sediments and for identifying zones of increased technogenic load. A comprehensive approach to the analysis of bottom sediment pollution is proposed, enabling a more accurate identification of spatial distribution patterns of contaminants and their accumulation zones. This provides a scientific basis for the development of adaptive strategies for monitoring and management of aquatic ecosystems. This study is of significant practical importance for advancing sustainable environmental management and the rational use of natural resources under increasing anthropogenic impact. Full article

The glass industry contributes to long-term soil contamination. This study assesses the impact of over 150 years of industrial activity and over a century of glassmaking processes in the Serbian Glass Factory in Paraćin. Focusing on potentially toxic elements (PTEs) and polycyclic aromatic hydrocarbons (PAHs), ecological and human health risks were evaluated. Sampling was conducted at 34 locations within the factory area, including 33 soil samples (0–30 cm) and one industrial waste (IW) sample. Soil analyses indicate that Zn, Ni, Cu, and Cd exceeded both the maximum permissible concentrations (MPCs) and remediation values (RVs) in many samples, while As and Hg showed fewer exceedances. Based on the Potential Ecological Risk Index (RI), about 33% of soil samples were moderately to highly polluted, and Cd, Pb, As, and Hg were identified as the main contributors. High levels of PAHs and PTEs reflect the cumulative impact of long-term industrial operations, a historical fire, and secondary sources, including traffic-related emissions from nearby highways. These factors resulted in elevated total carcinogenic risk (TCR) for Ni, Cr, and As. This study highlights soil contamination and associated health risks at the glass factory, emphasizing the need for environmental monitoring and management. Full article

This research explores public awareness, perceptions, and behavioral attitudes toward renewable energy in Saudi Arabia, drawing on data from a sample of 217 respondents predominantly based in the Riyadh region. The demographic profile reveals a diverse age distribution, with a notable concentration of younger participants, particularly those aged 16–25, who constituted 40.1% of the sample. Employing a descriptive survey design, the research explores key themes including environmental attitudes, economic considerations, personal behavior, media influence, and educational engagement. The findings indicate strong public support for the national transition to renewable energy, with 73.4% of the respondents expressing confidence in its potential as a primary energy source. Many of the respondents recognized both the ecological and financial advantages of renewable technologies, such as reduced emissions and job creation. The participants widely acknowledged the environmental and economic benefits of renewable technologies, such as reduced pollution and job creation. However, concerns persist regarding fossil fuel dependency, energy transition costs, and the adequacy of current educational and media efforts. The statistical analysis revealed significant associations between awareness levels and favorable attitudes toward investing in renewables. The results underscore the importance of targeted educational initiatives, strengthened communication strategies, and enhanced institutional transparency to reinforce public engagement and facilitate Saudi Arabia’s sustainable energy goals under Vision 2030. Full article

Precision soil management is fundamental to the sustainable production of high-quality tea, yet the spatial integration of fertility and heavy metal safety remains a significant challenge. This study aimed to delineate multi-dimensional management zones (MZs) in the tea plantations of Tianmuhu, Jiangsu Province, by evaluating three clustering algorithms: K-means (KM), Fuzzy C-means (FCM), and Iterative Self-Organizing Data Analysis Technique (ISODATA). A total of 70 representative soil samples were analyzed for 10 properties. Descriptive statistics revealed pronounced spatial heterogeneity, particularly for Hg (CV = 71.04%) and P (CV = 61.83%). Pearson correlation and Principal Component Analysis (PCA) demonstrated strong synergistic relationships among organic matter (OM), nitrogen (N), and potassium (K) (r = 0.49–0.69, p < 0.01), which formed a distinct Fertility Factor on PC1. Conversely, PCA identified divergent sources for heavy metals, with Cr primarily governed by pedogenic processes (PC2), while Cd were associated with anthropogenic inputs. Guided by these distinct spatial drivers, this study separately delineated fertility and heavy metal safety MZs. The optimal number of clusters was determined by balancing statistical validity with spatial operationality via the Silhouette Coefficient (SC) and Smoothness Index (SI), with results indicating that a 2–3 zone scheme yielded the most favorable scores. Comparative analysis showed that for soil fertility, ISODATA outperformed KM and FCM by effectively capturing the high variability of P and producing statistically distinct zones (p < 0.05). For heavy metal pollution, FCM provided better partitioning by reflecting the continuous gradients of composite contaminants. Validation results showed that while 61% of the area was classified as high-fertility (ISODATA), approximately 63–75% fell into relatively higher heavy metal accumulation categories. This dual-objective zoning framework provides a scientific basis for site-specific fertilization and targeted environmental monitoring in the regional tea industry. Full article

Owing to topographical constraints, rural domestic sewage management in karst areas faces unique challenges (scattered pollution sources, fragile hydrogeology, and inadequate infrastructure), but research on decentralized treatment technologies and their microbial mechanisms in this area remains scarce. This study aimed to evaluate the efficiency of a physicobiological process (pre-treatment + BAF) for decentralized rural sewage treatment in karst areas and clarify the relationship between microbial community composition and treatment efficiency under different scales. Annual analyses of influent/effluent pollutants and 16S rRNA gene sequencing were conducted for BAF systems of varying scales. The average removal rates of COD, TN, NH₃-N, and TP were 65.35–79.25%, 32.09–66.66%, 49.50–75.42%, and 44.92–67.69%, respectively. Treatment efficiency varied significantly with scale, being higher in larger systems (p < 0.001). All scales shared a core microbial community (dominated by Proteobacteria, Bacteroidetes, and Chlorobi), but the relative abundance of core taxa decreased with decreasing scale. Nitrification and denitrification were positively associated with NH₃-N and TN removal, respectively. Smaller treatment units were more prone to miscellaneous bacteria proliferation, potentially reducing treatment stability. This study fills the research gap of decentralized BAF application in rural karst areas and provides a scientific basis for the scale optimization of rural wastewater treatment facilities. Full article

There is increasing interest in delivering greater resilience to climate change through integrated catchment management that includes Nature-based Solutions (NbS) such as riparian buffer strips, tree-planting and wetlands. Governmental organisations also seek to use water quality modelling to understand the mass of different pollutants avoided per feature for appraisal of nutrient-neutrality purposes, but the assessment of efficacy is not yet fully developed, nor is it clear what it implies at the catchment-scale. We introduce three open, freely distributable models to help understanding efficacy and risk-reduction of buffer-strips at the plot (JUMP), waterbody (Fieldmouse), and national (HYPE) scales to help understand risk-reduction and help objectively quantify improvements in catchment resilience. These approaches have been developed across a range of projects but are also being investigated in more detail as part of the modelling element to the NERC Freshwater Quality programme QUANTUM project. Here we report how the particle tracking model predicts the need for very slow velocities, high loss rates or other processes to achieve buffer strip efficacies in common use—slowing the flow alone is unlikely to achieve these results. Upscaling these results to the catchment scale on the Yeo highlights another significant concept, that of the need to define a catchment scale efficacy for a particular Nature-based Solution, given the practicalities of implementation. We demonstrate how HYPE can be used to target and model mitigations and permits both upscaling nationally and through-time source apportionment to help identify when design efficacies may not be achieved in practice. Full article