Unplanned urban expansion poses significant challenges to sustainable territorial development in intermediate cities. This study analyzes the dynamics of urban expansion and land use change in the city of Cajamarca (Peru) during the period 1986−2040, integrating Geographic Information Systems (GIS) techniques, Google Earth Engine (GEE) and CA-Markov prediction models. Landsat satellite images from 1986, 2004 and 2022, classified by Random Forest (RF), were used to generate thematic maps and evaluate their accuracy. Subsequently, a spatial simulation model was implemented to project urban expansion to 2040. The results indicate an increase in the urban area from 789.68 hectares to 5,768.19 hectares, while forests and crops also changed. The driving factors for this expansion include rural-urban migration, the availability of services, and real estate development. Projections highlight growth toward the east, southeast, and south of the city. This approach provides strategic inputs for sustainable urban planning and effective land management in transforming Andean cities.

Exposure to heavy metals during pregnancy poses significant health risks to both pregnant women and the developing fetus. This study aimed to conduct a comprehensive bibliometric analysis of global research on heavy metal exposure during pregnancy and its impact on fetal development over the past five decades (1974−2024). Data were retrieved from the Scopus database, yielding 173 English-language publications for analysis. Bibliometric mapping was performed using VOSviewer, while trend visualization and geographical analysis were conducted using Tableau to identify publication trends, research hotspots, and knowledge gaps. The results revealed a marked increase in research output beginning in 2010, with lead (Pb) and mercury (Hg) emerging as the most extensively investigated metals, followed by growing attention to arsenic (As), cadmium (Cd), and manganese (Mn). Prominent research themes focused on associations between prenatal heavy metal exposure and adverse birth outcomes, including low birth weight, preterm birth, and impaired neurodevelopment. Geographically, research output was dominated by the United States, China, and European countries, whereas contributions from low-income and high-exposure regions remained limited. Frequently occurring author keywords included heavy metals, pregnancy, and fetal development. These findings highlight the need for more targeted research in underrepresented regions and on emerging heavy metals, in alignment with global public health priorities and the Sustainable Development Goals (SDGs). Overall, this analysis provides strategic insights to inform future research directions and policy initiatives aimed at reducing prenatal heavy metal exposure and improving maternal and fetal health outcomes.

Inclusive ecotourism promotes equal access, community participation, and environmental conservation, thereby generating both social and economic benefits. Although scholarly interest in inclusive ecotourism has increased, empirical research examining how specific policy frameworks address the needs of people with disabilities remains limited. This study presents a systematic review of the existing literature to evaluate the extent to which ecotourism policies enhance accessibility, foster community awareness, and support environmental sustainability. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive literature search was conducted using the Scopus, Web of Science, and ProQuest databases. Of the 1,215 records identified, only seven studies met the inclusion criteria, indicating that research in this area is still at an early stage of development. The review highlights several key policy strategies, including the provision of accessible infrastructure, stakeholder engagement, and the integration of sustainability-oriented practices. However, the findings also reveal persistent challenges, such as weak policy enforcement, limited intersectoral collaboration, and gaps in physical infrastructure. By synthesizing insights related to accessibility, community awareness, and environmental policy, this study provides an integrated perspective to inform the development of more inclusive and sustainable ecotourism initiatives. It underscores the need for stronger cross-sector collaboration to address existing policy shortcomings and to promote tourism systems that equitably benefit all visitors, including individuals with disabilities.

The Kara University Hospital generates an average of 17133.1 m$^3$ of wastewater per year. These hospital effluents contain specific substances likely to disseminate pathogenic germs. The objective of the study is to assess the risks associated with the poor management of hospital effluents from the Kara University Hospital. The study involved the characterization of the effluents. The results obtained show that in addition to the temperature and the hydrogen potential (pH), the values of the other physico-chemical parameters in particular, suspended solids (SS) (58.07 mg/L) and nitrates (84.79 mg/L) exceed the discharge standards of World Health Organization (WHO). The values of the microbiological parameters sought, in particular total coliforms (1.106 CFU/100 mL), thermotolerant coliforms (4.105 CFU/100 mL), sulphite-reducing anaerobes (3.6103 CFU/100 mL) and faecal streptococci (5.103 CFU/100 mL) exceed the discharge standards accepted by the WHO. Exposed individuals were identified through an exposure level assessment matrix. The analysis shows that at the production stage, healthcare personnel are the most exposed with a critical rate of 64% (16/25); at the evacuation stage, the workers in charge of evacuation show a moderate exposure level of 48% (12/25). After disposal in nature, populations living near landfill areas are the most exposed with a rate of 48% (12/25). After disposal in nature, populations living near landfill areas are the most exposed with a rate of 48% (12/25). The wearing of personal protective equipment by staff and the establishment of a treatment plant will reduce the risks and ensure sustainable management of effluents from the Kara University Hospital.

Limited studies have assessed the specific health risks associated with ozone exposure among informal waste workers in landfill environments, particularly in developing countries. This study addresses this gap by evaluating the Risk Quotient (RQ) of ozone pollutants among scavengers at the Sarimukti Landfill, West Bandung Regency, Indonesia. Applying the Environmental Health Risk Assessment (EHRA) approach, ozone concentrations were measured over three periods across two sampling points. Data were collected from 101 scavengers, including variables such as exposure time, frequency, body weight, and inhalation rate. Intake values, RQ, safe concentration thresholds (Cnk), safe exposure duration (t$_\text{Enk(safe)}$), and safe exposure frequency (f$_\text{Enk(safe)}$) were calculated under both real-time and 30-year projection scenarios. The results showed that real-time RQ values substantially exceeded the safe threshold (mean RQ = 27.183), indicating substantial short-term health risks. Although the projected 30-year values were lower (mean RQ = 7.630), they remained above the acceptablelimit (RQ $>$ 1), reflecting potential chronic health risks. The average safe exposure time at maximum concentration was only 0.147 hours/day, while the safe frequency was limited to 5 days/year. These findings highlight the urgent need for integrating occupational health protections, air quality monitoring, and regulatory enforcement into landfill waste management systems.

The functional value of a watershed is often degraded by anthropogenic activities. Land cover changes, urban expansion, and industrial development can significantly affect river water quality. Consequently, rapid and comprehensive monitoring is required to represent conditions across the entire river system. Advances in Earth observation satellite technology provide efficient tools for monitoring natural resources and environmental quality. This study aims to estimate concentrations of Total Suspended Solids (TSS) and Dissolved Oxygen (DO) in the Krueng Pase River Basin, North Aceh, Indonesia, using satellite imagery. The analysis employed Sentinel-2A data acquired during both dry and rainy seasons from 2020 to 2022, with a spatial resolution of 60 m. Concurrent field measurements collected by the Aceh Environmental Service were used for accuracy assessment. The results reveal seasonal variations in sediment levels within the Krueng Pase Watershed. Validation against in situ observations produced Nash–Sutcliffe Efficiency (NSE) values of 0.949 (very good) for Period I and 0.645 (satisfactory) for Period II. Percent Bias (PBIAS) values were 15.668 (very good) and 21.0307 (very good), respectively. These findings are supported by the estimated DO concentrations, which consistently $>$5 mg/L. Such levels indicate good oxygen conditions, sufficient to sustain productive aquatic biota and showing no evidence of severe pollution. This study demonstrates that satellite imagery-based estimation of TSS and DO concentrations is a reliable approach for land and water management, particularly in evaluating water pollution.

Chemical dyes are routinely discharged into ecosystems via textile industry effluents and landfill leachates. Adsorption using engineered adsorbents presents a viable strategy for pollutant removal in water treatment. Activated carbon (AC) and carbon nanoparticles are composite materials that integrate nanomaterials, rendering them less susceptible to these processes. This study involved preparing and characterizing AC using UV-Vis, fourier-transform infrared (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. We subsequently assessed its capacity to remove methylene blue (MB) under varying conditions of pH, initial dye concentration, adsorbent dosage, and contact time. The dye is often utilized in the textile and chemical industries. The adsorbent achieved a removal efficacy of 99.9% under optimal conditions: a temperature of 25 ℃, a pH range of 7–9, and a contact time of 60–120 minutes. The removal process was characterized by pseudo-second-order kinetics and the Freundlich isotherm model. The results indicated that the adsorbent’s surface was heterogeneous, consisting of many layers. The calculated thermodynamic parameters were $\Delta G^{\circ}$ = -4.24 kJ/mol, $\Delta H^{\circ}$ = -0.0975 kJ/mol, and $\Delta S^{\circ}$ = -0.3125 kJ/kg/K.

Determining strategic locations for the development of integrated agroindustry—encompassing aquaculture areas, industrial zones, and ecotourism sites within coastal regions—presents a complex challenge. Each sector carries distinct interests and characteristics, often leading to spatial conflicts. Moreover, ensuring coastal ecological sustainability must remain a top priority throughout the planning process. A comprehensive approach is required to identify locations that not only minimize environmental impacts but also maximize cross-sectoral economic value. This study aims to identify potential locations for the development of an integrated agroindustry in the aquaculture–ecotourism sector. The Analysis of Operational Area of Nature-Based Tourism Attractions (AOA-NBTA) was employed to assess ecotourism potential. The Analytical Hierarchy Process (AHP) was applied to assign weights to industrial development parameters, while Geographic Information Systems (GIS) were used for spatial analysis of potential locations for integrated agroindustrial development. The AOA-NBTA analysis identified Tanjung Pakis Beach as the most promising ecotourism location, with a cumulative score of 3.175. Spatial overlay analysis in the Bekasi–Karawang coastal region revealed that highly suitable (S1) areas account for 20.27% (1,950.961 ha), suitable (S2) areas 18.10% (1,742.823 ha), and unsuitable areas 61.63% (5,933.175 ha). These findings provide a foundation for spatial decision-making in formulating sustainable development policies, particularly in coastal zones.

The learning process plays a crucial role in developing character values, including environmental care value. Given the critical importance of the environment to human existence, addressing the increasing environmental challenges today requires the integration of environmental education into core learning processes. Developing learning that promote environmental values is essential for effective implementation. This study aims to: (1) develop a Green Education model through Eco-Clubs for students at Universitas Negeri Malang (UM), (2) evaluate the effectiveness of the Green Education model through Eco-Clubs for students, and (3) assess the wastepreneurship skills of students’ participation in the Green Education model through Eco-Clubs. The study employed a Research and Development (R&D) methodology utilizing the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model. The research subjects were students of UM enrolled in the Entrepreneurship course. Data analysis employed a mixed-method approach. Results indicate that the Green Education model implemented through Eco-Clubs significantly enhances students’ wastepreneurship competencies. Achieving successful environmental projects requires high levels of cooperation, creativity, and a strong sense of environmental responsibility. These factors significantly influence students’ ability to address environmental issues, particularly waste management, both on campus and within the community. Furthermore, the implementation of the Green Education model using Eco-Clubs has enhanced student engagement in environmental initiatives, yielding beneficial outcomes for both the campus and broader community stakeholders.

The Fallujah Cement Plant constitutes a cornerstone of reconstruction efforts in Al-Anbar Province, yet it simultaneously represents one of the largest stationary sources of air pollution in the region. This study presents the first integrated assessment of ambient air quality impacts from a major Iraqi cement facility by combining field measurements with the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD). Concentrations of seven pollutants—sulfur dioxide (SO$_2$), nitrogen dioxide (NO$_2$), carbon monoxide (CO), carbon dioxide (CO$_2$), total suspended particulates (TSP), particulate matter $\leq$ 10 $\mu$m (PM$_{10}$), and fine particulate matter $\leq$ 2.5 $\mu$m (PM$_{2.5}$)—were monitored at three receptor sites surrounding the plant. Results revealed that measured concentrations consistently exceeded model predictions, particularly for CO$_2$ (+221%) and CO (+441%). Field data indicated exceedances of Iraqi national standards and World Health Organization (WHO) guidelines by up to 23-fold for SO$_2$ and 12-fold for PM$_{2.5}$. Spatial analysis confirmed that pollutant plumes predominantly extend southeastward under prevailing northwesterly winds, with the highest risks observed in nearby residential complexes located 2 km downwind. Overall, the findings demonstrate that the Fallujah Cement Plant poses significant public health risks, underscoring the urgent need for advanced emission-control technologies and the establishment of vegetative buffer zones to mitigate environmental and health impacts.

Heavy metals tracing and magnetic susceptibility are generally used as a proxy indicator of pollution in various depositional environments. This research focused on tracing the significant record of pollution of the Muntingia calabura tree to understand the sensitivity in recording pollution and mining production. The area of this research is a hydrocarbon mining site of Wonocolo Geopark in the Bojonegoro, East Java Indonesia. The samples were taken both polluted and non-polluted leaf and bark, from 20 sampling points. Polluted leaves then were characterized by the existence of elevated levels of Pb, Fe, Cu and Zn. The average magnetic susceptibility of leaves increases from 0.86 × 10$^{-8}$ m$^3$/kg in non-polluted samples to 13.55 × 10$^{-8}$ m$^3$/kg in polluted samples and in the same way, increasing of magnetic susceptibility was also seen in the barks, from an average of 0.21 × 10$^{-8}$ m$^3$/kg in non-polluted sample, to 2.55 × 10$^{-8}$ m$^3$/kg in polluted sample. The pattern of magnetic susceptibility on leaves and barks at each sampling point is also the same as the pattern of hydrocarbon production which is related to the level of pollution in the area. The increase of magnetic susceptibility in polluted leaves and barks is thought caused by input of magnetic minerals and heavy metals from the fly ash of diesel engines used for hydrocarbon mining process. The heavy metal concentration has the average of Pb (0.070 ppm), Fe (13.322 ppm), Cu (8.434 ppm), and Zn (11.668 ppm). This value has exceeded the threshold of heavy metals content and have a worst impact on health and the environment. Based on Pollution Load Index (PLI) calculations, the most of areas affected by heavy metal pollution in very high and extremly high levels with the highest pollutants input are Fe, Cu, Zn and Pb respectively.

Green growth has emerged as a crucial central policy objective for reconciling economic performance with environmental sustainability. This study investigates the determinants of green growth in OECD countries over the period 1990−2022. Specifically, it evaluates the roles of environmental policies (EPS), research and development (R&D), and institutional quality, particularly the Rule of Law (IQRL), in shaping economic green growth. To address cross-country interdependence and structural heterogeneity, we employ the Common Correlated Effects Estimator with a Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) framework. The approach appropriates the dataset exhibiting unobserved common factors, cross-sectional dependence, and mixed order of integration. The model effectively manages cross-sectional dependence, accommodates heterogeneous dynamics, and addresses mixed stationarity. It therefore provides reliable estimates of both short-run and long-run effects and is well suited for modern applied panel data analysis. The empirical results show that an inclusive strategy promoting technological innovation, strong environmental governance, and following the Rule of Law is essential for advancing green growth in advanced economies. Trade openness, GDP per capita, and population growth are found to be significant positive drivers. In contrast, renewable energy consumption (REC) exerts a negative effect, suggesting the presence of short-term adjustment costs associated with the energy transition. Overall, these findings highlight the importance of coordinated environmental governance, sustained R&D support, and strong institutional frameworks in advancing green growth. Policymakers should prioritize targeted R&D investments, strengthen environmental policy design, and enhance the institutional frameworks that support the ecological transformation.

Industrialization and population growth pose significant environmental issues, particularly in water quality, making many sources unsuitable for domestic use. Natural organic compounds and metal nanoparticles (NPs) are used as wastewater adsorbents. The current research investigated the adsorption kinetics, isotherms, and reusability of the manganese oxide NPs synthesized from star anise (SA) (Illicium verum) extract (MnO@SE) to aid in the creation of environmentally friendly water purification solutions. MnO@SE was prepared with SA extract and manganese acetate (II) tetrahydrate solution. The green-synthesized biosorbent was characterized employing methods including Fourier transform infrared spectroscopy, X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), and scanning electron microscopy (SEM). These evaluations offered good information on surface shape and surface-available functional groups. The influences of pH, adsorbent dosage, ion concentration, and contact time on metal ion adsorption were all examined. The results revealed that model solutions with a pH of 2.0, a biosorbent dosage of 0.8 g/L, an initial concentration of 25 mg/L, and a contact time of 50 minutes produced the best removal efficiency (96.34% for Cr(VI) and 87.01% for Pb(II)). The adsorption processes of both metal ions occurred in a multilayer fashion on the heterogeneous surface of the biosorbent through diffusion kinetics, according to the isotherm and kinetic findings. The adsorption process is endothermic and spontaneous, according to thermodynamic analysis. The study revealed that the green-synthesized MnO@SE effectively removed 96.34% Cr(VI) and 87.01% Pb(II) under optimal conditions, promoting eco-friendly water purification through multilayer, endothermic, spontaneous, and diffusion-driven adsorption.

The purpose of this work was to study purolate (porous carbons from the Kuzbass deposits, Russia). Thermograms in the temperature range 150−700 ℃ showed an up to 8.7% mass loss in the purolate samples. It was proven that purolate has a large range of particle size (from 0.1 to 3 mm) and pH (8.0−9.0) and a low total pore volume in water (0.5 cm$^3$/g). It was found that in addition to C and O$_2$, Zn (5,346.8 mg/kg), Ba (256 mg/kg), Sr (304 mg/kg), Cu (541 mg/kg), and MnO (119 mg/kg) are present in significant amounts in purolate; it does not contain Al$_2$O$_3$, SiO$_2$, Rb, and Zr. It was established that the service life of the sorbent layer is 380 min at an adsorption temperature of 28−30 ℃ (analysis of the adsorption breakthrough curve). The final degree of purification from the model mixture ranged from 35.4% for manganese ions to 98.1% for iron ions. Analysis of the kinetic curves of ion extraction found that the highest adsorption (0.07 g/g) for 250 min was observed during the extraction of manganese ions, the lowest (0.045 g/g) for 300 min, during the extraction of nitrite ions. The development of a new technology using anthracite-based adsorbents for treating water from coal mining operations would help address environmental concerns in resource-dependent areas and contribute to the rehabilitation and revitalization of aquatic ecosystems.

Landslide susceptibility modeling (LSM) in data scarce environments remains limited by weak interpretability and the absence of calibrated predictive uncertainty, reducing its reliability for operational decision making. This study introduces a cloud-native LSM framework that unifies SHapley Additive exPlanations (SHAP) for transparent model interpretation with Conformal Prediction (CP) for statistically valid uncertainty quantification, implemented end-to-end within Google Earth Engine (GEE). Multi-sensor remote sensing datasets were processed in GEE, and four machine learning (ML) classifiers, Random Forest (RF), Gradient Boosted Trees (GBT), Support Vector Machine (SVM), and Classification and Regression Trees (CART) were trained using a spatially stratified, balanced inventory of 238 landslide and 227 non-landslide locations in Pune District, India. CART achieved the highest predictive performance (Accuracy = 0.8655; Kappa = 0.6142; Precision = 0.8055), while RF was selected for SHAP and CP analyses due to its smoother probability outputs. SHAP identified rainfall, elevation, slope, normalized difference vegetation index (NDVI), and topographical wetness index (TWI) as the dominant predictors. CP mapped high confidence ($<$5% uncertainty) susceptibility in steep, high rainfall escarpments and elevated uncertainty ($>$30%) in data sparse plains. The resulting explainable, uncertainty aware hazard maps, deployed via a public GEE application, provide policy ready insights and offer a transferable template for monsoon prone, low inventory regions.

The study goal was to evaluate the effectiveness of school eco-clubs and digital technologies as instruments for fostering environmental responsibility amid the environmental challenges in rural areas of Southeast Kazakhstan. A descriptive-analytical design with mixed methods was applied. The sample consisted of 186 “student–parent” pairs from 10 schools in the Almaty Region and 30 experts. Data was collected from September 2023 to April 2024 using validated questionnaires, focus groups, and expert interviews. A statistically significant relationship was identified between the duration of participation in eco-clubs and the level of students’ environmental knowledge ($p$ $<$ 0.01) and between the intensity of intergenerational communication and changes in family practices: safe handling of agrochemicals (62.2% of families), composting organic waste (55.1%), and the use of organic fertilizers (38.8%). Regression analysis showed that practical demonstrations ($\beta$ = 0.42, Cohen’s d = 0.89) and virtual reality (VR) technologies ($\beta$ = 0.35, Cohen’s d = 0.74) are the strongest predictors of changes in environmental behavior ($R^2$ = 0.51, $p$ $<$ 0.001). VR outperforms traditional methods: knowledge acquisition is 35% higher (4.6 versus 3.4 points), and practical application is twice as high (89.3% and 45.2%, respectively). The study confirms the effectiveness of school eco-clubs as a catalyst for environmental changes in rural families. The authors demonstrate the potential of virtual technologies in compensating for the limitations of environmental education in remote agricultural regions.

Groundwater contamination, exacerbated by improper solid waste disposal, is a critical environmental problem, especially in regions such as the Toluca Valley, where water supply depends on aquifers. This study quantified leachate generation at the Metepec landfill in the State of Mexico using the Water Balance Model (WBM) and the Hydrologic Evaluation of Landfill Performance model (HELP 3). Three hydrological years (dry, average, and wet) were analyzed to represent contrasting scenarios. The results showed that leachate generation is directly related to precipitation. In dry months, infiltration represented less than 17% of annual rainfall, while in some months evapotranspiration was higher. The HELP 3 model estimated higher volumes due to the moisture generated by waste decomposition. Comparative analysis revealed that, in the absence of barriers, percolation exceeded 12% of annual precipitation. When a clay layer was implemented, infiltration was practically eliminated, and with a geomembrane it was reduced to approximately 1% of total precipitation. These results demonstrate the effectiveness of structural configurations in reducing leachate generation. The study concludes that the implementation of impermeable barriers and post-closure monitoring programs is essential to mitigate environmental impacts and protect groundwater resources.