Environments

12 pages, 1705 KB

Open AccessArticle

Microbiological Quality of Purified Water from Vending Machines: Occurrence, Antimicrobial Resistance, and Biofilm Formation of Pseudomonas aeruginosa

by Ricardo Jiovanni Soria-Herrera, Luis F. Muñoz-Mateo, Margarita Hernández-Mixteco, Moisés León-Juárez, Addy Cecilia Helguera-Repetto, Laura Gabriela Flores-Aviña, Virginia A. Robinson-Fuentes, Erika Beatriz Angeles-Morales, Graciela Castro-Escarpulli, Carlos Cortes-Penagos and Jorge Francisco Cerna-Cortés

Environments 2026, 13(4), 207; https://doi.org/10.3390/environments13040207 - 8 Apr 2026

Abstract

Purified water from vending machines offers consumers an alternative source of clean, safe water. However, data regarding its microbiological quality are limited, particularly concerning the prevalence of Pseudomonas aeruginosa harboring virulence traits. This study aimed to evaluate the microbiological quality of 125 purified [...] Read more.

Purified water from vending machines offers consumers an alternative source of clean, safe water. However, data regarding its microbiological quality are limited, particularly concerning the prevalence of Pseudomonas aeruginosa harboring virulence traits. This study aimed to evaluate the microbiological quality of 125 purified water samples collected from vending machines across six cities of Michoacan, Mexico. Additionally, it sought to assess the occurrence of Pseudomonas aeruginosa and characterize its antimicrobial resistance profiles and biofilm-forming capacity. Aerobic mesophilic bacteria (AMB) were detected in all analyzed samples. A total of 71 (56.8%), 40 (32.0%), and 31 (24.8%) samples were positive for total coliforms (TC), fecal coliforms (FC), and Escherichia coli, respectively. Among the samples, 43 (34.4%) were positive for P. aeruginosa. There were significant correlations between the presence of P. aeruginosa and AMB (rho = 0.4445; p < 0.0001), TC (rho = 0.4094; p < 0.0001), FC (rho = 0.3389; p = 0.0001), and E. coli (rho = 0.3242; p = 0.0002). Moreover, the presence of TC in purified water samples increased the risk of P. aeruginosa nearly seven-fold (odds ratio = 6.91; p < 0.001). The resistance rate among P. aeruginosa strains to the most tested antibiotics ranged from 2.3 to 16.3%, and two (4.6%) of the isolates were multidrug-resistant. All P. aeruginosa strains were strong biofilm producers. Consequently, we recommend periodic maintenance of vending machines, the establishment of P. aeruginosa control protocols, and enhanced regulatory monitoring of the water vending industry. Full article

(This article belongs to the Special Issue Environmental Risk Assessment of Aquatic Environments, 2nd Edition)

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23 pages, 818 KB

Open AccessArticle

Environmental Behavior Driving Household E-Waste Recycling in Emerging Urban Contexts

by Wa Ode Uswatun Miladina Putri Harafah, Muhammad Erza Aimar Rizky, Herdis Herdiansyah and Syifa Istighfarani

Environments 2026, 13(4), 206; https://doi.org/10.3390/environments13040206 - 7 Apr 2026

Abstract

Rapid electronic waste (e-waste) accumulation poses a critical challenge for urban sustainability in emerging economies. However, few studies have examined what motivates households to actively participate in formal disposal systems, particularly in contexts where infrastructure remains limited. This study investigates the determinants of [...] Read more.

Rapid electronic waste (e-waste) accumulation poses a critical challenge for urban sustainability in emerging economies. However, few studies have examined what motivates households to actively participate in formal disposal systems, particularly in contexts where infrastructure remains limited. This study investigates the determinants of e-waste recycling intention and behavior in Surabaya, Indonesia. A total of 168 active recyclers are surveyed and analyzed using structural equation modeling and importance–performance mapping. The findings reveal that awareness of environmental consequences significantly influences both recycling intention and actual behavior. Interestingly, while the perceived cost of recycling significantly shapes residents’ intention to participate, it does not translate into a significant effect on their actual recycling behavior. Similarly, the convenience of recycling services shows no significant influence on either intention or behavior. Mediation analysis confirms that environmental awareness indirectly shapes recycling behavior through its effect on intention. These findings suggest that, among early adopters of formal e-waste recycling in a developing-country context, cognitive drivers such as awareness outweigh structural barriers like cost and convenience in shaping long-term recycling engagement. For policymakers, this underscores the importance of highlighting awareness of e-waste impacts and the benefits of proper recycling, alongside efforts to remove physical and financial barriers for broader segments of the population. Full article

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24 pages, 3890 KB

Open AccessArticle

Common Wood Pigeon (Columba palumbus): An Avian Bioindicator of Antimicrobial Resistance at the Human–Wildlife Interface

by Áron Sárközy, Eszter Nagy, Attila Bende, Ágnes Csivincsik, Brigitta Bóta, Gábor Nagy, Melinda Kovács and Tamás Tari

Environments 2026, 13(4), 205; https://doi.org/10.3390/environments13040205 - 6 Apr 2026

Abstract

Antimicrobial resistance (AMR) is a silently escalating global crisis, presenting a specific challenge for the One Health approach. Landscapes can serve as reservoirs of AMR bacteria and genes, while synurban wildlife may act as vectors of bidirectional exchange. However, these species can also [...] Read more.

Antimicrobial resistance (AMR) is a silently escalating global crisis, presenting a specific challenge for the One Health approach. Landscapes can serve as reservoirs of AMR bacteria and genes, while synurban wildlife may act as vectors of bidirectional exchange. However, these species can also be utilised as sentinels of landscape AMR load. Herbivorous avian bioindicators, such as the Common Wood Pigeon (Columba palumbus), continuously sample the landscape during foraging and drinking, providing a homogenous spatial overview on the state of AMR. This study aimed to investigate the potential of this species for assessing the impact of landscape diversity on bacterial communities and their AMR patterns. Toward this objective, two spatial units of 4 km in diameter located at an upstream and a downstream section of a river, relative to a provincial town, were compared using 16 cloacal samples per site. Heterotrophic plate count techniques resulted in 60 isolates, of which 48 were identified, and 35 were tested for AMR using the VITEK 2 Compact system. The association between bacteriological findings and landscape diversity was analysed using Rényi diversity profiles. The Gram-positive/Gram-negative ratio was the only parameter that proved to be significantly different between the two study sites. The investigation detected six MDR isolates, with two methicillin-resistant phenotypes (Staphylococcus gallinarum, Mammaliicoccus lentus) and two carbapenem-resistant Pseudomonas fluorescens isolates. We established that the small sample size limits drawing definitive conclusions. However, exploring the link between landscape diversity and the cultivable faecal microbiota of herbivorous birds is a promising approach for more extensive research. Full article

(This article belongs to the Special Issue Potential Health Effects of Environmental Pollution Exposure on Animals)

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19 pages, 1759 KB

Open AccessArticle

Association Between Traffic Noise and Cognitive Function: A Cross-Sectional Study in a Mid-Sized City in Northern Colombia

by Maria Taboada-Alquerque, Felipe Figueroa, Juan Valdelamar-Villegas and Jesus Olivero-Verbel

Environments 2026, 13(4), 204; https://doi.org/10.3390/environments13040204 - 6 Apr 2026

Abstract

Exposure to road traffic noise is an increasing public health concern in developing countries. However, limited research has explored its effect on children’s cognitive function in contexts with common lifestyles and socioeconomic conditions in these countries. This study aims to evaluate the association [...] Read more.

Exposure to road traffic noise is an increasing public health concern in developing countries. However, limited research has explored its effect on children’s cognitive function in contexts with common lifestyles and socioeconomic conditions in these countries. This study aims to evaluate the association between residential outdoor traffic noise exposure in Sincelejo, Colombia, the multidimensional poverty index (MPI) and the effects on cognitive functions in children with a cross-sectional deisgn. Noise levels were estimated using the CNOSSOS model and spatially linked to selective attention and working memory of children, assessed with standardized cognitive tests. Associations were estimated with logistic regression models adjusted for sociodemographic and school characteristics and stratified by MPI. Sensitivity analyses were conducted to evaluate the consistency of the associations. The results indicated a statistically significant yet weak association between a 1 dBA increase in noise levels and reduced processing speed (≤95) in selective attention tasks, particularly in the area with the highest prevalence of MPI < 50. However, sensitivity analyses did not corroborate these findings, and the observed association should therefore be interpreted with caution as exploratory and hypothesis generating. Full article

(This article belongs to the Special Issue Environmental Pollution Exposure and Its Human Health Risks)

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40 pages, 2498 KB

Open AccessArticle

Environmental Impacts of Italian Food Life Cycle Scenarios for Sustainability Management and Decision Making

by Patrizia Ghisellini, Yanxin Liu, Ivana Quinto, Renato Passaro and Sergio Ulgiati

Environments 2026, 13(4), 203; https://doi.org/10.3390/environments13040203 - 5 Apr 2026

Abstract

Food waste prevention and reduction are some of the important initiatives to improve the environmental sustainability of food systems. The global agenda of the United Nations provides a framework of targets and actions against food waste to which the European Union (EU), within [...] Read more.

Food waste prevention and reduction are some of the important initiatives to improve the environmental sustainability of food systems. The global agenda of the United Nations provides a framework of targets and actions against food waste to which the European Union (EU), within the “Farm to Fork” strategy, aims to contribute. In this context, evaluating the impacts of food prevention measures is of great importance for supporting policies. This LCA analyzes the impact of classic lasagna from cradle to grave, through a generic food case study, prepared by food shops in Bologna (Northern Italy). Four scenarios are simulated, comparing the impacts of some end-of-life alternatives for the management of leftover lasagna (landfilling, composting, and redistribution with the digital application of the circular start-up “Squiseat”) versus the ideal scenario where no leftover lasagna is assumed. The results show that the preparation of classic lasagna generates non-negligible impacts on the analyzed LCA categories due to some of its ingredients, such as Bolognese sauce and Parmigiano Reggiano, and their associated production processes. For this reason, it is important to prevent classic lasagna leftovers from being wasted. The comparison of the four scenarios shows that redistribution is the scenario with the lowest impacts in all the investigated impact categories, including global warming (6.24 kg CO₂ eq./kg of lasagna). The impacts are also lower than the ideal scenario due to the assumption of more sustainable means of transport. Normalization of characterized results confirms that Global Warming (GW) is only one of the most relevant impact categories in the life cycle of classic lasagna. The results have practical implications for raising awareness concerning the impacts of food production throughout the whole life cycle and the need for preserving the value of food by avoiding waste. Moreover, this study also shows that a reduction in the impact is a shared outcome that could be achieved by the joint efforts of all the stakeholders involved in the life cycle of food. In this regard, urban centers are confirmed to be important hubs of circular and more sustainable innovation. Finally, the LCA enriches the current research by investigating redistribution through the relationship of the food shop–virtual intermediate–consumer. So far, the prevalent focus of the LCA research allows us to assess the redistribution of collected surplus food from retailers and its delivery to the consumers by means of physical intermediaries and related infrastructures (e.g., food hubs, food banks, and food emporiums). Full article

(This article belongs to the Special Issue Circular Economy in Waste Management: Challenges and Opportunities)

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26 pages, 716 KB

Open AccessReview

Multidrug-Resistant Acinetobacter spp. and Lytic Bacteriophages in Hospital Wastewater—A Five-Year Narrative Review

by Catalin Gabriel Smarandache, Madalina Irina Mitran, Cristina Iulia Mitran, Cristiana Cerasella Dragomirescu, Gabriela Loredana Popa, Andrei Alexandru Muntean and Mircea Ioan Popa

Environments 2026, 13(4), 202; https://doi.org/10.3390/environments13040202 - 5 Apr 2026

Abstract

In recent decades, antibiotic-resistant bacteria have become an increasingly urgent public health concern. The uncontrolled use of antibiotics, along with inadequate implementation of prevention and control measures, is the primary factor contributing to this issue. The hospital environment is a major source of [...] Read more.

In recent decades, antibiotic-resistant bacteria have become an increasingly urgent public health concern. The uncontrolled use of antibiotics, along with inadequate implementation of prevention and control measures, is the primary factor contributing to this issue. The hospital environment is a major source of multidrug-resistant bacteria, and in recent years, there has been growing concern about hospital wastewater, which acts as a significant reservoir for these bacteria and their resistance genes. This situation leads to the spread of multidrug-resistant bacteria in the environment. One particular concern is Acinetobacter, especially Acinetobacter baumannii, which has emerged as a pathogenic threat in healthcare-associated infections. This bacterium is found in high densities in hospital wastewater. Most strains of A. baumannii express resistance not only to carbapenems but also to several other classes of antibiotics, including tetracyclines, fluoroquinolones, and aminoglycosides. These strains must be combated through effective measures. Bacteriophages represent a potential mitigation strategy for antibiotic-resistant Acinetobacter spp. originating from hospital wastewater. This review summarizes studies from online databases regarding the identification and characterization of Acinetobacter strains in hospital wastewater worldwide, and presents progress in isolating and characterizing bacteriophages against A. baumannii found in hospital wastewater. Full article

(This article belongs to the Special Issue Advances in Wastewater Bio-Management: Microbial Community Relationships, Monitoring and Assessment)

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23 pages, 707 KB

Open AccessArticle

Evaluating Circular Economy Performance in Municipal Solid Waste Management: A Hybrid Structural Equation Modeling and Explainable Machine Learning Study from Cajamarca

by Persi Vera-Zelada, Emma Verónica Ramos-Farroñán, Alexander Fernando Haro-Sarango, Luis Alberto Vera-Zelada, Julio Roberto Izquierdo-Espinoza, Kevin Litman Florez-Tolentino, Pamela Maidolly Torres-Moya, Roberto Justo Tejada-Estrada and Gary Christiam Farfán-Chilicaus

Environments 2026, 13(4), 201; https://doi.org/10.3390/environments13040201 - 5 Apr 2026

Abstract

This study evaluates the factors associated with municipal solid waste management performance under a circular economy approach in the municipalities of Cajamarca, Peru. A hybrid analytical design was applied to 120 municipal observations, combining partial least squares structural equation modeling to estimate the [...] Read more.

This study evaluates the factors associated with municipal solid waste management performance under a circular economy approach in the municipalities of Cajamarca, Peru. A hybrid analytical design was applied to 120 municipal observations, combining partial least squares structural equation modeling to estimate the measurement and structural properties of four latent constructs—legal-regulatory framework, institutional capacity, operational management, and perceived performance—and XGBoost with SHAP to explore predictive classification of participation in circular economy training. The structural results indicate that operational management plays the central articulating role in linking regulation and institutional capacity to perceived performance, whereas the predictive component showed only modest out-of-sample discrimination (AUC-ROC = 0.519). Overall, the findings suggest that the proposed hybrid pipeline is more informative for explanatory integration and variable-importance analysis than for strong predictive discrimination under the current specification. Full article

(This article belongs to the Special Issue Circular Economy in Waste Management: Challenges and Opportunities)

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21 pages, 2107 KB

Open AccessArticle

Differential Associations of Internal and Residential Lead Exposure Pathways with Body Mass Index: A Mixture Analysis of Biomarkers and Household Dust

by Zaniyah Ward and Emmanuel Obeng-Gyasi

Environments 2026, 13(4), 200; https://doi.org/10.3390/environments13040200 - 4 Apr 2026

Abstract

Background: Human lead exposure is a multi-pathway phenomenon that integrates internal biological burden with persistent residential environmental reservoirs. Although individual lead metrics have been linked to cardiometabolic dysfunction, current research often fails to capture the ‘exposome’ reality of joint, nonlinear, and interaction-dependent effects [...] Read more.

Background: Human lead exposure is a multi-pathway phenomenon that integrates internal biological burden with persistent residential environmental reservoirs. Although individual lead metrics have been linked to cardiometabolic dysfunction, current research often fails to capture the ‘exposome’ reality of joint, nonlinear, and interaction-dependent effects on metabolic outcomes like BMI. Objectives: To evaluate associations between biological (blood and urinary) and residential dust (window and floor) lead measures and BMI, and to characterize nonlinear and interaction-dependent mixture effects using Bayesian Kernel Machine Regression (BKMR). Methods: We analyzed data from NHANES 2001–2002, a nationally representative survey of the U.S. noninstitutionalized civilian population. Window and floor dust lead (µg/ft²) were obtained from the NHANES household dust component, and blood lead (µg/dL) and urinary lead (µg/L) were measured using standardized NHANES laboratory protocols. BMI was calculated from measured height and weight. Missing data were addressed using multivariate imputation by chained equations. Descriptive statistics and multivariable linear regression were used to estimate adjusted associations between individual lead metrics and BMI, controlling for age, gender, income, race/ethnicity, and education. BKMR was then applied to evaluate joint mixture effects, estimate univariate and bivariate exposure–response functions, and quantify relative exposure importance using posterior inclusion probabilities (PIPs). Results: In covariate-adjusted linear regression, blood lead (β = −0.485; 95% CI: −0.566, −0.405; p < 0.001) and window dust lead (β = −0.00047; 95% CI: −0.00067, −0.00026; p < 0.001) were inversely associated with BMI, whereas floor dust lead was positively associated (β = 0.258; 95% CI: 0.209, 0.306; p < 0.001). Urinary lead was inversely but not significantly associated with BMI (β = −0.111; 95% CI: −0.235, 0.013; p = 0.079). In BKMR, blood lead was the dominant contributor, with a posterior inclusion probability (PIP; proportion of iterations in which an exposure is selected) of 1.00. Window dust lead showed modest inclusion (PIP = 0.26), whereas urinary and floor dust lead were not selected (PIP = 0.00). Exposure–response functions indicated modest nonlinearity for blood lead and greater divergence for the blood lead–window dust lead pairing at higher exposure levels. The overall mixture effect declined across increasing joint exposure quantiles, crossing the null near the median and becoming increasingly negative at higher mixture levels. Conclusions: In our study, lead metrics showed heterogeneous associations with BMI, and BKMR indicated that internal lead burden (blood lead) primarily drove mixture-related BMI patterns, with evidence that window dust lead may modify mixture effects at higher co-exposure levels. These findings support evaluating multiple lead exposure pathways jointly and using flexible mixture models to capture nonlinear and interaction-dependent relationships with BMI. Full article

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22 pages, 1047 KB

Open AccessArticle

Geospatial Assessment of the Energy Potential of Agricultural Residual Biomass in Cordoba, Colombia: A Technical Basis for a Decentralised Energy Transition

by Jesus D. Rhenals-Julio, Stiven J. Sofán-Germán, Mirna P. Iriarte, Jorge I. Martínez, Taylor De la Vega González and Jorge M. Mendoza-Fandiño

Environments 2026, 13(4), 199; https://doi.org/10.3390/environments13040199 - 3 Apr 2026

Abstract

This study examines the potential of using agricultural residues for energy production in the Córdoba department of Colombia in response to the need to diversify the energy matrix and reduce inequality in energy access. The aim was to estimate and visually represent the [...] Read more.

This study examines the potential of using agricultural residues for energy production in the Córdoba department of Colombia in response to the need to diversify the energy matrix and reduce inequality in energy access. The aim was to estimate and visually represent the energy potential of nine key crop residues using agricultural data from 2015 to 2018, physical-energy characterisation, and UPME and SERI models integrated into a geographic information system (GIS). A total annual generation of 2.6 million tonnes of residual biomass was identified, with Tierralta, Lorica and Montería emerging as the main generators. Although maize did not produce the largest volume of residue, it had the highest theoretical energy potential (2621 GWh/year) due to its low moisture content and high calorific value. The total theoretical energy potential of the available biomass was estimated at 4550 GWh/year, which could cover over twice the department’s electricity demand and avoid around 745 thousand tonnes of CO₂ emissions per year. This study demonstrates that the strategic use of this biomass can promote a just and sustainable energy transition and proposes a replicable model combining technical and territorial analysis to inform public policy and encourage decentralised bioenergy projects. Full article

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8 pages, 213 KB

Open AccessEditorial

Risk Assessment, Digital Tools and Environmental Management Can Explain Residual Impact Risk Factors

by Tilemachos K. Koliopoulos and Gregorio García-Fernández

Environments 2026, 13(4), 198; https://doi.org/10.3390/environments13040198 - 3 Apr 2026

Abstract

Today, the risks and hazards arising from climate change should be reduced by implementing appropriate environmental strategies, health and safety standards, monitoring schemes, geoinformation utilities, and digital risk management tools for sustainable development [...] Full article

(This article belongs to the Special Issue Environmental Pollution Risk Assessment)

24 pages, 308 KB

Open AccessArticle

Environmental Assessment of Community Readiness for Cattle Waste Management as Needs as an Energy Transition to Climate Change

by Dinda Azizah, Evi Frimawaty and Ernoiz Antriyandarti

Environments 2026, 13(4), 197; https://doi.org/10.3390/environments13040197 - 2 Apr 2026

Abstract

The adoption of biogas technology in smallholder livestock systems is increasingly recognized as a dual solution for rural energy transition and livestock waste management; however, actual implementation remains limited due to low community readiness, particularly driven by knowledge gaps and resource constraints. This [...] Read more.

The adoption of biogas technology in smallholder livestock systems is increasingly recognized as a dual solution for rural energy transition and livestock waste management; however, actual implementation remains limited due to low community readiness, particularly driven by knowledge gaps and resource constraints. This study examines the determinants of community readiness for biogas adoption in rural Indonesia, addressing the limited attention of prior studies to readiness factors at the household level. A cross-sectional survey of 98 smallholder cattle farmers was conducted using structured questionnaires, and the data were analyzed using descriptive statistics and multiple linear regression to identify key determinants of readiness. The results indicate generally positive perceptions toward biogas, with knowledge, prior waste processing experience, perception scores, education level, and herd size significantly influencing readiness (p < 0.05). While awareness of biogas benefits and willingness to process manure emerged as key drivers, limited technical knowledge and time and cost constraints remained major barriers, suggesting an awareness–adoption gap. These findings align with behavioral adoption frameworks, highlighting the roles of knowledge, perceived benefits, and enabling conditions in shaping adoption readiness. Policy interventions emphasizing capacity-building, financial incentives, and adaptable biogas technologies are therefore essential to support rural adoption. Full article

18 pages, 5471 KB

Open AccessArticle

Annual Levoglucosan Variability and Its Relationship with Meteorological Conditions at an Urban Background Site in Croatia

by Silvije Davila, Suzana Sopčić, Gordana Pehnec and Ivan Bešlić

Environments 2026, 13(4), 196; https://doi.org/10.3390/environments13040196 - 2 Apr 2026

Abstract

Levoglucosan (LG), a tracer of biomass-burning air pollution, was measured in PM₁₀ particulate matter during a year-long study at an urban background site in Zagreb, Croatia. It is known that the atmospheric lifetime of LG is not constant and undergoes degradation through [...] Read more.

Levoglucosan (LG), a tracer of biomass-burning air pollution, was measured in PM₁₀ particulate matter during a year-long study at an urban background site in Zagreb, Croatia. It is known that the atmospheric lifetime of LG is not constant and undergoes degradation through reactions with hydroxyl radicals, ozone, photooxidation, etc. In this study, daily variations in LG were examined and evaluated in relation to NO₂, O₃, and meteorological conditions, including temperature, relative humidity, solar irradiance, UV index, and wind characteristics. The annual mean PM₁₀ concentration was 22 µg m⁻³, while LG average was 0.312 µg m⁻³, both exhibiting pronounced seasonal variability. Elevated LG levels occurred during winter and autumn, consistent with residential wood combustion and stable atmospheric conditions, whereas markedly lower concentrations were observed in spring and summer. Moderate correlations of LG with PM₁₀ and NO₂ indicate contributions from combustion sources, while weak wind speeds and limited dispersion favored pollutant accumulation. In contrast, significant negative relationships were found between LG and ozone, temperature, and UV index. The results revealed non-linear behavior and an exponential decrease in LG with increasing oxidant levels, suggesting pseudo–first-order degradation driven by enhanced photochemical activity and hydroxyl radical formation. These findings highlight the importance of considering both emission patterns and atmospheric processing when using levoglucosan as a tracer of biomass burning in urban environments. Full article

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29 pages, 2250 KB

Open AccessSystematic Review

Decarbonization Strategies in the Wine Supply Chain: From Environmental Mitigation Towards Integrated Sustainability Management

by Christian Bux, Mariarosaria Lombardi, Roberto Leonardo Rana and Caterina Tricase

Environments 2026, 13(4), 195; https://doi.org/10.3390/environments13040195 - 2 Apr 2026

Abstract

The decarbonization of agri-food supply chains represents a critical challenge and an opportunity for achieving global climate targets and Sustainable Development Goals, extending beyond pure environmental mitigation to integrated sustainability management. This study focuses on the wine industry, a major global sector with [...] Read more.

The decarbonization of agri-food supply chains represents a critical challenge and an opportunity for achieving global climate targets and Sustainable Development Goals, extending beyond pure environmental mitigation to integrated sustainability management. This study focuses on the wine industry, a major global sector with significant macroeconomic weight and substantial potential for emission reductions. Through a systematic literature review, this research maps scientific trends and identifies strategies to reduce greenhouse gas emissions across the entire supply chain, from viticulture and winemaking to distribution and waste valorization. Analyzing 65 publications, this study identifies three thematic clusters: (i) agronomic and environmental practices (Cluster 1); (ii) innovation, social welfare, and corporate governance (Cluster 2); and (iii) energy transitions and methodological accounting tools (Cluster 3). The key findings highlight that while packaging and logistics remain primary emission hotspots, significant mitigation can be achieved through soil carbon sequestration, renewable energy adoption, and circular economy practices. This research contributes a cohesive set of sustainability-oriented operational strategies derived from previously fragmented technical mitigation strategies. By acknowledging that decarbonization strategies extend beyond ecological metrics, this framework address the intersecting socioeconomic and operational impacts experienced by local communities. The results reveal a disconnect between macro-level legislative frameworks, such as the European Green Deal, and micro-level operationalization. This review highlights the need for a shift toward harmonized governance and standardized metrics to reconcile competitiveness with climate stewardship. Full article

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37 pages, 1209 KB

Open AccessSystematic Review

Statistical Interpolation for Mapping Wastewater-Derived Pollutants in Environmental Systems: A GIS-Based Critical Review and Meta-Analysis

by Mona A. Abdel-Fatah and Ashraf Amin

Environments 2026, 13(4), 194; https://doi.org/10.3390/environments13040194 - 2 Apr 2026

Abstract

Effective management of wastewater discharges requires understanding the spatial distribution of pollutants both within engineered infrastructure and in receiving environments. However, spatial data sparsity constrains comprehensive assessment. This critical review examines the role of Geographic Information Systems (GIS) and statistical interpolation techniques in [...] Read more.

Effective management of wastewater discharges requires understanding the spatial distribution of pollutants both within engineered infrastructure and in receiving environments. However, spatial data sparsity constrains comprehensive assessment. This critical review examines the role of Geographic Information Systems (GIS) and statistical interpolation techniques in bridging these data gaps for wastewater-derived pollutants. Moving beyond a simple compilation of methods, this paper provides a synthesizing framework that categorizes and evaluates interpolation techniques-from deterministic and geostatistical approaches to emerging machine learning (ML) and hybrid models- based on their ability to address specific challenges in wastewater systems. A key contribution is a systematic review and meta-analysis following PRISMA guidelines, synthesizing evidence from 22 studies that directly compare interpolation methods for wastewater-relevant parameters (BOD₅, COD, nutrients, heavy metals) in both engineered systems and impacted water bodies. Results indicate that machine learning methods significantly outperform traditional approaches, with a pooled 21% reduction in RMSE compared to Ordinary Kriging (95% CI: 15–27%). However, subgroup analyses reveal context dependency: ML advantages are most pronounced for organic pollutants (29% reduction) and data-rich environments (27% reduction with n > 100), while geostatistical methods remain competitive for physical parameters (8% reduction, non-significant) and data-sparse scenarios (12% reduction with n < 50). Co-Kriging achieves 15% RMSE reduction over Ordinary Kriging when auxiliary variables are available. The review explores applications in pollutant tracking, infrastructure planning, and environmental impact assessment, highlighting how integration of real-time sensor data (IoT) and remote sensing is transforming static maps into dynamic monitoring tools. Finally, a forward-looking research roadmap is presented, emphasizing hybrid modeling frameworks, digital twin integration, and improved uncertainty communication for decision support. By quantitatively synthesizing the current state-of-the-art and identifying critical knowledge gaps, this review aims to guide future research towards more intelligent, adaptive, and reliable spatial assessments of wastewater-derived pollutants. Full article

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71 pages, 2175 KB

Open AccessSystematic Review

Applying Artificial Intelligence (AI) Innovative Tools for Ecological Research and Monitoring of Transitional Water Ecosystems: A Systematic Review

by Armando Cazzetta, Francesco Zangaro, Francesca Marcucci, Olumide Temitope Julius, Marco Rainò, Mahallelah Shauer, Roberto Massaro, Teodoro Semeraro, Alberto Basset and Maurizio Pinna

Environments 2026, 13(4), 193; https://doi.org/10.3390/environments13040193 - 1 Apr 2026

Abstract

Transitional water ecosystems exhibit pronounced spatio-temporal variability and increasing anthropogenic pressures, posing substantial challenges for ecological monitoring and management. Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has emerged as a powerful framework for addressing the structural complexity of these [...] Read more.

Transitional water ecosystems exhibit pronounced spatio-temporal variability and increasing anthropogenic pressures, posing substantial challenges for ecological monitoring and management. Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has emerged as a powerful framework for addressing the structural complexity of these systems. This systematic review synthesizes peer-reviewed studies applying ML and DL to ecological research and monitoring in transitional waters. A structured search of the Scopus^® database was conducted up to 31 December 2024, and studies were screened according to predefined eligibility criteria and PRISMA 2020 guidance; methodological quality was appraised using a structured assessment framework. Ninety-six studies met the inclusion criteria. Regression was the most frequent analytical task (44.1%), followed by classification (36.2%) and clustering (19.7%), with water quality monitoring representing the dominant thematic domain. Tree-based and kernel-based ML models prevailed overall, whereas DL architectures increased markedly after 2020, particularly in remote sensing and high-dimensional applications. Despite methodological heterogeneity and variable validation practices, the evidence indicates that ML and DL approaches effectively accommodate non-linearity, data heterogeneity, and scale mismatches typical of transitional waters. Standardized validation strategies and improved model interpretability remain essential for robust ecological inference and operational implementation. Full article

(This article belongs to the Collection Trends and Innovations in Environmental Impact Assessment)

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21 pages, 1946 KB

Open AccessArticle

Tracing the Legacy of Historical PCB Pollution and Contemporary PAH Contamination in the Kupa River (Danube Basin, Croatia)

by Snježana Herceg Romanić, Ivana Jakovljević, Maja Đokić, Nina Bilandžić, Goran Jakšić, Gordana Mendaš, Martina Biošić, Gordana Pehnec, Tijana Milićević and Gordana Jovanović

Environments 2026, 13(4), 192; https://doi.org/10.3390/environments13040192 - 1 Apr 2026

Abstract

The Kupa River (Croatia), a tributary of the Danube basin forming part of the Slovenian border, was heavily contaminated with polychlorinated biphenyls (PCBs) between 1962 and 1985 due to improper handling and downstream transport via the Krupa and Lahinja rivers. This study evaluated [...] Read more.

The Kupa River (Croatia), a tributary of the Danube basin forming part of the Slovenian border, was heavily contaminated with polychlorinated biphenyls (PCBs) between 1962 and 1985 due to improper handling and downstream transport via the Krupa and Lahinja rivers. This study evaluated the occurrence, interspecific distribution, and human health implications of PCBs and polycyclic aromatic hydrocarbons (PAHs) in fish (Northern pike, Common carp, Grass carp, Pike-perch, Wels catfish, Bream, and Chub) from the Croatian Kupa River. PCB concentrations were consistently higher than PAH levels across all species. In 30% of samples, Σ6 non-dioxin-like PCBs exceeded the European Commission maximum permissible level for freshwater fish (125 ng⋅g⁻¹ wet weight). Of the 11 PAHs analyzed, only fluoranthene and pyrene were detected. Self-Organizing Map identified distinct pollutant patterns, with chub showing the highest variability and accumulation. PCB concentrations position the Kupa River among moderately to highly impacted European freshwater systems affected by legacy industrial contamination. Health risk assessment, incorporating updated national consumption data, indicates that long-term, uncontrolled consumption of Kupa River fish may pose risks due to PCB exposure, while PAH-related risks appear negligible. These findings highlight the persistence of legacy PCB pollution and the need for integrated sediment–biota monitoring. Full article

(This article belongs to the Special Issue Occurrence, Fate, and Environmental Risk Assessment of Organic Pollutants in Water)

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27 pages, 6049 KB

Open AccessArticle

Impact of Coal-Fired Power Plant Activities on the Ecological Status of River Ecosystems: Case Study of Sokolitsa River, Bulgaria

by Vanina Mitseva, Tsvetelina Isheva, Mila Ihtimanska and Emilia Varadinova

Environments 2026, 13(4), 191; https://doi.org/10.3390/environments13040191 - 1 Apr 2026

Abstract

Coal-fired power plants can adversely affect aquatic ecosystems through wastewater discharge, waste landfills, and the atmospheric deposition of toxic substances released during coal combustion. These processes degrade the water quality of nearby surface and underground water bodies. The study presents the impact of [...] Read more.

Coal-fired power plants can adversely affect aquatic ecosystems through wastewater discharge, waste landfills, and the atmospheric deposition of toxic substances released during coal combustion. These processes degrade the water quality of nearby surface and underground water bodies. The study presents the impact of the coal-fired power plant Contour Global Maritza East 3 on the ecological status of the Sokolitsa River, reflected by changes in the composition and structure of the sensitive phytobenthos and macrozoobenthos communities and supporting environmental variables, including water temperature, pH, dissolved oxygen, conductivity, nutrients, sulfates, calcium, and calcium carbonate hardness. Methods for monitoring and assessing the ecological status of surface water bodies compliant with European and national legislation were applied to the studied biological quality elements and key physicochemical variables. Historical monitoring data from a ten-year period, 2013–2022, together with data collected during the study in 2023 and 2024 were analyzed and evaluated. The results indicated a significant increase in most physicochemical variables downstream of the CFPP compared with the upstream site, including water temperature, conductivity, calcium carbonate hardness, calcium, sulfates and nitrogen (N) nutrients (ammonium N, nitrite N, nitrate N, total N). The ecological status of the river deteriorated, as indicated by the negatively affected aquatic habitats and the changes in the taxonomic richness and abundance of the studied organism groups. Full article

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17 pages, 503 KB

Open AccessArticle

Structural Changes in National Greenhouse Gas Intensity:Development of a Composite GHG Intensity Index for OECD Member Countries (2000–2020)

by Soongil Kwon, Hyewon Kim, Chiung Ko and Yoon-Seong Chang

Environments 2026, 13(4), 190; https://doi.org/10.3390/environments13040190 - 1 Apr 2026

Abstract

This study assesses long-term structural changes in greenhouse gas (GHG) intensity across 38 OECD member countries over the period of 2000–2020 using a multidimensional Z-score standardization framework. GHG intensity was measured using three activity-based indicators—emissions per unit of land area, per capita emissions, [...] Read more.

This study assesses long-term structural changes in greenhouse gas (GHG) intensity across 38 OECD member countries over the period of 2000–2020 using a multidimensional Z-score standardization framework. GHG intensity was measured using three activity-based indicators—emissions per unit of land area, per capita emissions, and emissions per unit GDP—which were then aggregated into a Composite GHG Intensity Score (GHGIS) to facilitate cross-country comparison while accounting for differences in territorial scale, demographic structure, and economic output. The results reveal substantial heterogeneity in both the level and trajectory of composite GHG intensity across OECD member states. Countries such as Sweden (ΔScore = −0.84) and Denmark (ΔScore = −0.67) demonstrated a decrease in GHGIS, reflecting relative improvements in emission efficiency, while Korea (ΔScore = +0.92) and Türkiye (ΔScore = +1.15) recorded positive shifts in relative positioning over the study period. Several countries, including the United Kingdom, Germany, Japan, and Israel, exhibited divergent trends across land-, population-, and GDP-based measures, highlighting the multidimensional nature of national emission structures. These findings demonstrate that relative changes in GHG intensity vary across structural dimensions and cannot be adequately characterized by single-indicator measures alone. While the analysis does not identify causal drivers of observed patterns, the standardized composite framework provides a transparent and replicable tool for examining long-term comparative shifts in multidimensional emission intensity. By applying a consistent methodology across all OECD member countries over two decades, the study contributes to comparative assessments of structural GHG intensity dynamics. Full article

(This article belongs to the Special Issue Greenhouse Gas Emission Reduction and Green Energy Utilization, 2nd Edition)

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16 pages, 3249 KB

Open AccessArticle

Hydro-Ecology of Household Life: Comparative Determination of Water Use Behavior in Mitigating Climate Change in Urban Areas

by Dwi Rahayu Nugraheni, Dwinowo Martono and Ernoiz Antriyandarti

Environments 2026, 13(4), 189; https://doi.org/10.3390/environments13040189 - 1 Apr 2026

Abstract

Sustainable water use behavior in households is a crucial component in facing the impacts of climate change on water conditions, especially in urban areas and their surroundings in countries like Indonesia. This study examines household water use behavior in urban and peri-urban areas [...] Read more.

Sustainable water use behavior in households is a crucial component in facing the impacts of climate change on water conditions, especially in urban areas and their surroundings in countries like Indonesia. This study examines household water use behavior in urban and peri-urban areas of Surabaya and Sidoarjo in Indonesia by integrating environmental spatial characteristics and using psycho-social factors. This research methodology includes statistical analysis with the aim of examining the variable in relation to household water behavior and then integrating with spatial analysis using nearest neighborhood analyses and spatial overlay with land use/land cover (LULC) and Urban Heat Island (UHI) data, doing so to identify behavioral clustering patterns and assess spatial risk distribution. The results suggest that there is generally positive orientation toward sustainable household water use among respondents. Households in peri-urban areas show better water management behavior than those in urban areas. The implications of spatial risk in urban areas are higher due to poor behavior facing high environmental pressures. On the other hand, when overlaid with clusters of well-behaved respondents, the risk of water shortages decreases, supporting climate change mitigation efforts. Full article

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