Environmental and Earth Sciences

Abstract: The Challawa and Jakara rivers of Kano State, Nigeria, receive complex multi-class toxic loads from over 300 tannery, textile, and pharmaceutical industries. Conventional physicochemical monitoring is insufficient to capture the cumulative ecological impact of co-occurring contaminants at the regulatory scale required for Sustainable Development Goal (SDG) 6.3 compliance. We applied a dual metagenomic framework; 16S rRNA V3–V4 amplicon sequencing and shotgun metagenomics to characterize microbial community structure, functional gene repertoires, metal resistance genes (MRGs), and antibiotic resistance genes (ARGs) across three hydrological zones of the corridor: upstream reference (Site-R), industrial confluence (Site-I), and downstream recovery (Site-D). Amplicon sequencing (DADA2; 1847 ASVs) revealed significant community restructuring along the contamination gradient; Shannon diversity declined from H′ = 4.2 ± 0.3 (Site-R) to H′ = 2.8 ± 0.2 (Site-I) (PERMANOVA R2 = 0.68, p = 0.001). Metal-tolerant Cupriavidus metallidurans (6.1%), Pseudomonas spp. (14.2%), and Stenotrophomonas maltophilia (8.7%) were selectively enriched at Site-I, while obligate nitrifiers (Nitrosomonadaceae) were suppressed to 0.9% (p < 0.001). Shotgun metagenomics (DESeq2) identified the czc efflux operon and mer volatilisation operon as 5.4-fold and 4.9-fold enriched, respectively, and strongly correlated with cadmium (Spearman ρ = 0.87) and mercury (ρ = 0.83) concentrations. Metal–antibiotic co-selection was confirmed by a partial Mantel test (ρ = 0.74, p = 0.003), with 47 ARG families at Site-I versus 12 at Site-R. A Random Forest classifier trained on normalized functional gene profiles achieved 91.4 ± 2.1% accuracy (AUC = 0.96), comparable to a full physicochemical panel. This metagenomic biosensor framework provides a scalable, cost-effective, and ecologically meaningful tool for SDG 6.3 compliance monitoring in resource-limited regulatory environments.

Abstract: Post-harvest losses remain a significant challenge in Nigeria's agricultural sector, worsening food insecurity and economic instability. This study examines the impact of climatic stressors on PHL, identifying key climatic drivers and assessing their projected influence under future climate scenarios (SSP5-8.5). Using a combination of spatial analysis, Partial Least Squares Discriminant Analysis (PLS-DA), and Random Forest (RF) modelling, the study quantifies the relationship between temperature, precipitation, humidity, and post-harvest losses across Nigeria's six geopolitical regions. Findings reveal that temperature-related variables, such as maximum temperature (Txx), mean temperature (Tas), and heat days exceeding critical thresholds (HD35, HD40), significantly increase PHL, particularly in the northern regions. Conversely, precipitation (Pr) and relative humidity (Hurs) exhibit mixed effects, reducing losses in arid areas but exacerbating spoilage risks in humid zones. Economic implications are severe, with the North Central, North East, and North West regions accounting for over 80% of total financial losses. Additionally, the COVID-19 pandemic contributed to a 22.55% increase in PHL, highlighting vulnerabilities within Nigeria's food supply chain. Future projections under the SSP5-8.5 climate scenario indicate a continuous rise in losses, surpassing 250,000 tons by 2050. In response, climate-smart agriculture (CSA) is explored as a viable mitigation strategy. The adoption of heat- and drought-tolerant crop varieties, improved post-harvest storage technologies, integrated pest management, and climate-smart advisory services are proposed to enhance resilience against climate-induced losses. This study posits the necessity of integrating climatic variables in the quantification of PHL and also climate-responsive strategies into post-harvest loss mitigation frameworks in order to safeguard food security and agricultural sustainability in Nigeria.

Abstract: This study analyzes the changes in land use and land cover over time in the Porto Nacional micro-region, situated in the MATOPIBA agricultural frontier, from 1985 to 2055. It emphasizes the increasing anthropogenic pressure on the ecosystems of the Brazilian Cerrado. The primary goal of this research is to understand how the territory has transformed and to project future scenarios related to agricultural expansion, urbanization, and unplanned land use. The methodology incorporates geoprocessing techniques, spatio-temporal analysis, data from the MapBiomas platform, remote sensing imagery, and time series analysis. Seven categories of land use and land cover were examined, with a focus on forest formations, savannas, agricultural areas, and pastures. Descriptive statistics, trend graphs, and regression methods were used to project changes through 2055. The results indicate a significant reduction in native vegetation, particularly in savanna formations, which is closely linked to the expansion of agricultural, livestock, and urban areas. The model used to simulate vegetation changes over time showed high reliability (R² = 0.98), forecasting that human expansion will continue to encroach on native vegetation through 2055. This underscores the urgent need for territorial planning and public policies to ensure the sustainability of the Cerrado.

Abstract: Agri-food byproducts are increasingly recognized as sustainable feedstocks for high-value bioactive compounds, but their practical valorization requires integrated evidence on recovery conditions, chemical composition, bioactivity, and application readiness. This review critically examines green recovery strategies and chemical profiling platforms for bioactive compounds recovered from peels, pomace, seed residues, hulls, vegetation waters, and pruning waste. Emphasis is placed on how extraction variables shape chemical profiles, extract quality, and reported biological activities. Ultrasound- and microwave-assisted extraction, enzyme- and fermentation-assisted recovery, supercritical fluid extraction, pressurized liquid extraction, pulsed electric field-assisted pretreatment, and green solvent-based extraction are discussed in terms of target-compound selectivity, solvent and energy demand, process safety, scalability, and sustainability-related evidence. Chromatographic, mass-spectrometric, spectroscopic, and metabolomics-based profiling approaches are evaluated for identification, annotation, quantification, fingerprinting, quality-marker selection, and standardization, with confidence levels distinguished according to authentic-standard matching, tandem mass spectrometry evidence, spectral libraries, or fingerprint-level evidence. Circular valorization pathways in food, nutraceutical, cosmetic, pharmaceutical-oriented, and biopesticide-related applications are further considered with attention to feedstock heterogeneity, process standardization, stability, safety, regulatory feasibility, scalability, and techno-economic feasibility. Overall, this review provides a linkage-oriented framework for developing standardized, application-readiness-oriented bioactive candidates from agri-food byproducts.

Abstract: Decarbonizing the transportation sector depends not only on the scale of mitigation programs, but also on whether financing systems are capable of generating measurable emission reductions. In Indonesia, climate finance allocation remains substantially below the level required to achieve the transportation-sector target under the Enhanced Nationally Determined Contribution (ENDC). At the same time, mitigation planning rarely establishes a clear relationship between financial expenditure and verified greenhouse gas (GHG) reduction outcomes, making policy effectiveness difficult to assess. This study examines the relationship between climate finance and mitigation outcomes in Indonesia’s transportation sector using verified emission reduction data and realized mitigation expenditures during 2018–2022. A cost-based assessment approach was applied to estimate the financing required to reduce one ton of CO2e across direct and indirect mitigation actions. The analysis identified 33 mitigation actions categorized under the Avoid–Shift–Improve (ASI) framework and evaluated their contribution to sectoral emission reduction. The results indicate substantial variation in mitigation costs among intervention types. Direct mitigation actions, particularly mass public transportation expansion, generated larger emission reductions at relatively lower costs than enabling or indirect measures. On average, reducing 1 tCO2e in Indonesia’s transportation sector requires approximately USD 184–305 (IDR 3–5 million). Based on the transportation-sector ENDC target, the estimated financing requirement by 2030 ranges from USD 3–17 billion (IDR 42–69 trillion). The findings suggest that climate finance policies should move beyond expenditure-oriented approaches toward financing frameworks that explicitly connect investment allocation with verified mitigation performance.

Abstract: Assessing the effects of opencast coal mining on surface water is often complex, requiring integrated approaches that combine guideline-based assessments, water quality indices, hydrochemical tools, and statistical analyses. This study evaluated multi-year water qual-ity data (2018 – 2023) from five sites along the Leeuwfonteinspruit, a tributary of the Oli-fants River Catchment, in the Mpumalanga Province of South Africa. Water quality pa-rameters were assessed against the South African Water Quality Guidelines (SAWQG) for domestic, agricultural, and aquatic ecosystem uses. The results indicated frequent ex-ceedances of SAWQGs for Key parameters such as sulphate (SO4), electrical conductivity (EC), total dissolved solids (TDS), magnesium (mg), calcium (Ca), iron (Fe), aluminium (Al), and manganese (Mn), especially at the downstream site, indicating the influence of coal mining activities. Weighted Arithmetic Water Quality Index (WA-WQI) and Canadi-an Council of Ministers of the Environment Water Quality Index (CCME-WQI) assess-ments classified water quality from good at some upstream sites to consistently poor/marginal water quality at downstream. Irrigation suitability, based on sodium ad-sorption ratio (SAR) and exchangeable sodium percentage (ESP), indicated that water is generally suitable for irrigation, though episodic SAR and ESP peaks indicate localised sodicity risks, which may decrease crop productivity in the particular area. Hydrogeo-chemical evaluation using Gibbs diagrams indicated that the upstream water chemistry is dominated by natural rock-water interactions and dilution, while midstream to down-stream sites increasingly reflect evaporation-crystallisation and anthropogenic inputs. The application of multivariate statistical analysis, such as Principal Component Analy-sis (PCA) and correlation analysis, indicated that the quality of water is primarily con-trolled by mining-related salinity and mineralisation, with secondary contributions from agricultural inputs. These findings demonstrate that opencast coal mining significantly compromises surface water quality in the Leeuwfonteinspruit, and highlight the need for strengthened monitoring, proactive mine water management and regulatory enforcement.

Abstract: Selecting native species for ecological restoration remains a challenge, especially when the commercial supply of seedlings does not adequately represent the regional flora. We used the tree flora of Iguaçu National Park as a regional ecological reference to assess its similarity to the species available in forest nurseries in the surrounding region and propose a multicriteria protocol. We sampled 471 individuals belonging to 73 species and 30 botanical families in six permanent plots in Iguaçu National Park. Similarity between the local flora and the nurseries was low, ranging from 0.11 to 0.16, whereas similarity among nurseries was moderate, ranging from 0.438 to 0.574, indicating that seedling supply is partially homogeneous and poorly representative of the reference flora. Based on these results, we applied a weighted multicriteria protocol integrating ecological, operational, and normative criteria to prioritize native species for seedling production in regional nurseries. Phenology, seed storage behavior, threat status, and dormancy were identified as the attributes with the greatest relative contribution to category differentiation. The protocol provides a technical and scientific basis to guide nurseries and restoration actions based on the local reference flora.

Abstract: Concerns regarding poor air quality in environmental justice communities frequently motivate formation of community-academic partnerships. Low-cost air monitors can assess air pollution but require specific training. The RISE Communities program was created to support partnerships in air quality training and community engaged research. The RISE Communities program in-person training took place in Cincinnati, OH in summers 2023 and 2024. The training included hands on workshops, lectures, and monthly webinars with continued expert guidance. A mixed method evaluation included pre-, post-, and one year follow-up surveys, webinar evaluation surveys, and focus groups at the conclusion of each cohort.Participants reported significantly increased confidence in describing the health impacts of air pollution and using low-cost air sensors. Subjective feedback commented on the need for more tailored and interactive webinars and data training. Participants agreed that the goals of the RISE Communities training program were met and skills were sustained. This mixed method evaluation study demonstrates that an immersive training program for academic and community partners resulted in significantly higher confidence levels related to community partnership, data analytics, data visualization, and project planning outcomes.

Abstract: Organic farming in the European Union is strongly shaped by Common Agricultural Policy (CAP) support, yet participation durability remains less examined than supported organic area or organ-ic–conventional comparisons. This study assesses whether the length of participation in CAP-supported organic farming is associated with the organizational, production, and economic out-comes of organic farms in Poland. It applies a two-level approach: CAP support trajectories based on ARMA data for 2008–2025 and organic production duration based on Polish FSDN data for 2008–2022. The results show that organic farming in Poland is highly CAP-dependent and follows an unstable trajectory, with expansion up to 2012–2013, subsequent decline, and renewed growth after 2019. Longer participation is associated with differences in land resources, supported organic UAA, ANCs conditions, production organization, and livestock presence, indicating both adapta-tion and structural selectivity. FSDN data show that fully organic farms have lower land and labor productivity than conventional farms, but persistent fully organic farms achieve similar income per hectare when subsidies are included; without subsidies, their income remains much weaker. The findings indicate that the evaluation of organic farming support should move beyond benefi-ciary counts and certified organic area to include participation durability, production-system co-herence, economic viability, and territorial embeddedness. More differentiated instruments are needed to strengthen durable, knowledge-intensive, and territorially embedded organic farming systems.

Abstract: Data-driven aeration optimization is an effective approach for reducing energy consumption in wastewater treatment plants (WWTPs). However, newly established or emerging-market WWTPs often lack historical aeration logs, making it difficult to construct high-precision surrogate models. Conventional cross-plant model deployments face severe data distribution shifts, and standard multi-objective optimization algorithms are prone to generating non-physical extrapolation errors, such as achieving compliance with "zero aeration" under low-concentration conditions. To break through inter-plant data barriers, this study proposes an intelligent aeration decision-making framework that integrates cross-domain transfer learning with physics-informed constraints. First, this study designs an adversarial network based on air-to-water ratio and removal rate features. By employing a gradient reversal layer (GRL) to extract domain-invariant representations, this network achieves cross-plant knowledge transfer. Second, this study proposes a physics-informed multi-objective particle swarm optimization (PI-MOPSO) algorithm, which embeds the theoretical oxygen demand as a physical penalty into the fitness function, ensuring the physical reliability of the optimization decisions. Experiments demonstrate that the surrogate model restricts the prediction errors for effluent chemical oxygen demand (COD) and total nitrogen (TN) removal rates to within 1%. Validated by statistical tests, the improved algorithm effectively circumvents non-physical prediction biases. Its Pareto front achieves a spacing metric of 0.0027, outperforming baseline algorithms in hypervolume stability. This framework provides optimal aeration scheduling strategies conforming to biochemical dynamics for target WWTPs lacking aeration action labels, demonstrating substantial practical engineering value.

Abstract: The purpose of this study is to explore how Zimbabwean firms use Environmental Management Accounting (EMA) and climate risk disclosure in times of policy uncertainty and how these relate to sustainable growth and macroeconomic stability. The study was couched in the interpretivist research philosophy and adopted the inductive research approach. A case study research design, which aligns with a qualitative research design, was chosen for the study. The study employed in-depth interviews with management accountants, finance executives, and industry leaders across firms in Harare. The study adopted the cross-sectional time horizon and analysed data using thematic analysis to develop insights into the role of EMA and climate risk disclosure in times of policy uncertainty. The study's findings show that climate policy uncertainty compels business leaders to reconfigure management accounting systems to integrate environmental performance measures and scenario-based capital planning. The findings indicate that strategic EMA is essential because it enhances cost visibility, which, in turn, supports proactive risk management and stabilises investment decision-making within an enterprise. Firms that have integrated climate disclosure frameworks were found to demonstrate stronger stakeholder confidence and had high adaptability capacity. In an uncertain policy environment, firm-level adjustments support macroeconomic resilience and sustainable growth by lowering regulatory shock sensitivity and reducing the costs they impose. The study contributes to the literature by connecting the discussions of macroeconomic stability with micro-level accounting procedures and providing a process-based approach and understanding of how strategic EMA disclosure serves as a transmission mechanism between economic resilience and climate policy uncertainty. The study contributes to the emerging discourse on climate risk accounting within the fragile macroeconomic context of developing countries. It is therefore recommended that the regulatory institutional pillar be strengthened to reduce uncertainty and enhance the EMA's strategic adaptation.

Abstract:

Formaldehyde (HCHO), a prevalent indoor air pollutant released from furniture and building materials, poses significant health risks due to its carcinogenic nature. In this study, a binary cuprous oxide–titanium dioxide (Cu₂O–TiO₂) composite photocatalyst was synthesized via a hydrothermal method to enable efficient visible-light-driven degradation of gaseous formaldehyde at ambient temperature. The structural, mor-phological, and optical properties of the as-prepared catalysts were characterized us-ing XRD, SEM, TEM, EDX, and UV-Vis spectroscopy. While pristine Cu₂O exhibited a formaldehyde degradation efficiency of approximately 68% under white light illumi-nation, the incorporation of TiO₂ markedly enhanced the photocatalytic performance. Among the different mass ratios tested, the Cu₂O–TiO₂ (1:1) composite demonstrated the highest activity, achieving 83% degradation of formaldehyde within 240 minutes under white light. Enhanced performance is attributed to the formation of a hetero-junction that reduces the effective bandgap, promotes charge separation, and sup-presses electron–hole recombination. Additionally, the generation of carbon dioxide and water as end products confirmed complete mineralization. The catalyst also showed good reusability, retaining over 81% efficiency after five cycles. This work presents a cost-effective, stable, and visible-light-active Cu₂O–TiO₂ heterojunction photocatalyst with strong potential for indoor air purification applications.

Abstract: Maintaining food systems in the face of climate change (CC) is a major concern. Palm oil is included in many commodities and this food system will be affected detri-mentally by inclement future climate, when oil palm (OP) will experience increased disease and declining growth. The OP diseases considered are basal stem rot (BSR), bud rot (BR) and fusarium wilt (FW), where the attempts to control them have been un-successful. An approach may be to replace compromised OP with different crops better suited to future climate: These plants will have less disease because of the “Parasites Lost” phenomenon. Maintaining a vegetable oil product is an important advantage. How CC will affect OP and associated ailments has been determined previously by CLIMEX modelling. The modelling of future suitable climate (FSC) has also been car-ried out for soybean, maize and the common bean (CB) using the same modelling pa-rameters. This enables direct comparisons in the OP producing countries of Colombia, Nigeria and Papua New Guinea (PNG). Limited data for rapeseed are also discussed. The FSC for OP was much reduced in these countries and that for soybean was higher. Soybeans will have less disease as it would be an introduced and annual crop. Maize had much fewer advantages and the CB and rapeseed had none. Maize had potential advantages in Nigeria until 2050. A novel method for adapting to the serious diseases of OP and poor growth would be to grow soybeans in similar regions to where OP grows currently. Plans could be made for replacing OP with soybeans which could be modified when real time data becomes available. The paper provides a novel method for mitigating future diseases and poor growth of OP, which are otherwise unavailable, whilst maintaining a valuable oil product.

Abstract: This study examines the implications of El Niño on the Indian industrial economy in the context of climate change, with a focus on sectoral risks, economic disruptions, and emerging growth opportunities. The study adopts a qualitative and analytical approach using historical El Niño trends, secondary economic data, sectoral performance analysis, and climate-related industrial indicators to evaluate the impact on major industries in India. The findings indicate that El Niño negatively affects agriculture, commodity supply chains, and food inflation due to weak monsoon conditions and rising temperatures. However, industries related to cooling appliances, irrigation and water technologies, renewable energy backup systems, healthcare, and consumer durables show strong growth potential during El Niño years. Climate change is further accelerating the demand for climate-resilient infrastructure and adaptive industrial strategies. This study provides an integrated perspective linking climate phenomena with industrial economics in India. It highlights how El Niño acts not only as an environmental risk but also as a catalyst for industrial transformation, investment opportunities, and climate-resilient economic development.

Abstract: The Arteni volcanic complex (Armenia) represents a distinctive volcanic landscape characterized by well-preserved pyroclastic deposits, rhyolitic domes, extensive obsidian flows, and significant archaeological evidence. This study aims to evaluate the geoheritage value of the complex and to develop a scientifically grounded geotouristic trail model based on the targeted selection of representative viewpoints. Field-based investigations were integrated with semi-quantitative viewpoint assessment and GIS-supported spatial analysis, including morphometric, viewshed, and accessibility analyses. The results allowed the identification of key viewpoints (VP1–VP9), effectively representing the principal stages of volcanic evolution, including explosive eruptions, lava flow emplacement, and dome formation. Spatial analysis demonstrates that the selected view-points enable the development of a coherent, accessible, and scientifically meaningful geotouristic route while balancing scientific representativeness with visitor accessibility and safety. In addition, the widespread occurrence of obsidian and associated archaeological artifacts highlights the combined geological and cultural significance of the area. The proposed approach provides a transferable framework for the development of scientific geotourism in volcanic regions and contributes to geoheritage conservation, geoeducation, and sustainable regional development.

Abstract: Accurate rainfall data are essential for hydrological forecasting and climate modeling. However, many developing regions, including Tunisia, struggle with significant data gaps in rainfall measurements, particularly from gauge stations. These missing data impair climate model validation and reduce forecasting accuracy across both spatial and temporal dimensions. To overcome these limitations, we conduct a comprehensive evaluation of novel deep learning (DL) architectures designed for imputing missing rainfall gauge data and generating monthly rainfall forecasts. Our framework systematically compares multiple DL approaches: Long Short-Term Memory (LSTM), a hybrid Bidirectional LSTM with a Transformer attention mechanism (BiLSTM-Transformer), and a pure Transformer model. Subsequently, we employ Principal Component Analysis (PCA), K-Means clustering, and quantile techniques to further refine DL model outputs. The processed data are then analyzed using Light Gradient Boosting Machine (LightGBM) to produce final results. Our rigorous evaluation across 47 Tunisian gauges covering 1983–2012 (70% training, 30% testing) demonstrates that the BiLSTM-Transformer hybrid delivers superior performance, achieving an 18.4% reduction in root mean squared errors (RMSE) compared to conventional interpolation methods (14.2 mm versus 17.4 mm monthly error) and improving R2 values by 0.15–0.23 across all test stations. The model shows particular strength in capturing Mediterranean rainfall patterns, correctly predicting 83% of extreme rainfall events (greater than 95th percentile). Furthermore, spatial graph networks boost performance at data-sparse stations by 12.7% through explicit modeling of topographic influences.

Abstract: The increasing accumulation of nano-/microplastics (NMPs) in agricultural soils has become an emerging environmental concern, posing risks to soil health, crop productivity, and food safety. Due to their persistence and small size, NMPs can disrupt soil structure, alter microbial communities, and facilitate the transport and uptake of contaminants by plants. In this context, biochar has attracted significant attention as a climate-smart soil amendment capable of improving soil quality while mitigating emerging pollutants. This review explores the potential role of biochar, including modified biochar, as a sustainable strategy for enhancing soil health and reducing the risks associated with NMPs contamination in agricultural systems. The unique physicochemical properties of biochar—such as its high surface area, porous structure, and abundant functional groups—enable interactions with plastic particles and associated contaminants through adsorption, aggregation, and immobilization processes. These interactions can reduce mobility, bioavailability, and plant uptake of NMPs in soil. In addition, biochar contributes to soil fertility improvement by enhancing nutrient retention, increasing water holding capacity, improving soil structure, and stimulating beneficial microbial activity. Biochar application also plays an important role in climate change mitigation by stabilizing carbon in soils and reducing greenhouse gas emissions from agricultural systems. Although biochar is considered a promising material for sustainability, some types of biochar may have adverse effects in saline–alkaline soils due to their high pH and salinity, particularly when produced at high pyrolysis temperatures. Overall, integrating biochar or modified biochar into sustainable agricultural practices offers multiple co-benefits, including soil restoration, pollutant mitigation, improved soil health, and enhanced climate resilience. This review synthesizes recent advances in understanding the mechanisms by which biochar influences NMPs behavior in soil–plant systems and highlights current knowledge gaps and future research directions needed to support its effective application in sustainable agriculture.

Abstract: Environmental Education (EE) and Education for Sustainable Development (ESD) play a crucial role in fostering environmentally responsible citizens and supporting the achievement of sustainability goals. This study aims to investigate primary school teachers’ knowledge, attitudes, and perceptions regarding EE/ESD, as well as the factors influencing their implementation in the educational process. A quantitative research design was employed using a structured questionnaire distributed to a sample of 500 teachers across Greece. Data were analyzed using descriptive statistics, content analysis, exploratory factor analysis, reliability testing, correlation analysis, and multiple regression analysis with the use of SPSS software. The results indicate that teachers generally demonstrate positive attitudes toward EE/ESD and recognize its importance in promoting environmental awareness, behavioral change, and students’ social development. Content analysis revealed that key environmental concerns identified by participants include pollution, climate change, and waste management, while EE/ESD is mainly associated with environmental practices and awareness. Factor analysis identified five core dimensions shaping teachers’ attitudes: (i) perceived value and impact, (ii) social and personal development outcomes, (iii) pedagogical design and evaluation understanding, (iv) institutional and structural barriers, and (v) practical implementation challenges. Significant correlations were found among these factors, particularly between perceived value and pedagogical understanding, as well as between institutional barriers and implementation challenges. Regression analysis showed that demographic and experiential variables have a modest but significant effect on perceived challenges, with age and participation in EE/ESD programs negatively associated with difficulties, while years of involvement increased awareness of implementation constraints. Overall, the findings highlight that although teachers possess a satisfactory level of awareness and positive attitudes toward EE/ESD, limited training, insufficient institutional support, and structural barriers hinder effective implementation. The study underscores the need for enhanced training opportunities, stronger policy support, and systematic integration of EE/ESD into school curricula to promote sustainable education practices.

Abstract: Ammonia-oxidizing bacteria (AOB) are vital for the nitrogen cycle and wastewater treatment, yet their recalcitrance to isolation and cultivation hampers industrial application. To isolate an efficient strain and optimize its culture conditions for high-ammonia wastewater treatment, we collected water samples from a polluted river in Zhongshan City. After enrichment, a strain was isolated via gradient dilution and silica gel plating, identified by scanning electron microscopy and 16S rDNA sequencing as Nitrosomonas europaea W4 (99.93% similarity to the type strain). Single-factor medium optimization examined CaCO₃ and Fe²⁺/Fe³⁺, while temperature and initial ammonia nitrogen effects were tested, and landfill leachate was used for verification. CaCO₃ shortened the lag phase without affecting maximum specific growth rate; replacing Fe³⁺ with Fe²⁺ further reduced lag and enhanced the ammonia oxidation rate. Optimal growth occurred at 25–30 °C and an initial ammonia nitrogen concentration of ~2000 mg/L. In landfill leachate, the strain increased the ammonia degradation rate 6.3-fold. Overall, N. europaea W4 exhibits high ammonia oxidation efficiency, and the optimized medium and conditions improve its proliferation and metabolic stability, providing a basis for cultivation and application in treating high-strength ammonia nitrogen wastewater.

Abstract: China’s pollutant discharge permit system mandates total-quantity emission control for industrial volatile organic compounds (VOCs), yet the actual utilization of permitted capacity remains poorly studied. This study developed an “emission idle rate” (IR = 1 − actual/permitted emissions) framework and applied it to 130 chemical enterprises across three cities in Jiangsu Province using 2020–2024 panel data. The mean idle rate reached 78.1%, with no significant inter-city differences (H = 0.96, p = 0.619), attributable to both production underutilization and systematic over-estimation of emission ceilings inherent in the design-capacity-based permit methodology. Ward hierarchical clustering revealed three emission behavioral patterns: Persistent Surplus (n = 74, IR = 0.95), Declining Surplus (n = 32, IR = 0.69), and Growing Surplus (n = 19, IR = 0.59), exhibiting distinct idle rate levels and temporal trajectories. Cluster differentiation was significantly associated only with production-side emission characteristics, while enterprise economic variables showed no significant effects. The estimated tradeable emission surplus reached 668.3 t/a, though its realization faces transaction cost barriers including the lack of standardized transfer mechanisms and formal VOC trading infrastructure. A quadrant-based strategy matrix integrating idle rate levels with temporal trends is proposed for differentiated permit management.