Abstract: In the past three years, electric vehicle (EV) sales in Indonesia have increased significantly, reflecting a positive trend in the country’s efforts to reduce carbon emissions. However, research by Canals Casals et al. (2016) highlights that EV adoption in developing countries may not always lead to effective carbon emission reductions. The environmental benefits of EVs are highly dependent on the electricity generation mix of a given country. Since Indonesia still relies heavily on fossil fuel-based power plants, the positive impact of EV usage on emission reduction needs to be critically assessed. this paper examines the adoption of electric vehicles (EVs) as a strategic pathway to reduce fossil fuel import dependency and carbon emissions. Using emissions data provided by the Google Environmental Insights Explorer (EIE) in West Nusa Tenggara Province (NTB), this study adopts a System Dynamics approach to explore various policy and energy transition scenarios that could maximize the environmental benefits of EV use. The findings of this research are expected to serve as a foundation for formulating more effective electric vehicle development policies in Indonesia.

Abstract: Since 2007, the Yellow Sea has experienced the world's largest green tides, with Ulva prolifera as the dominant species. Those blooms severely impacted the local tourism and aquaculture, resulting in significant economic losses, as well as negative social and ecological consequences. Unlike other global green tides, those in the Yellow Sea are characterized by long-distance drifting and an astonishing scale. These destructive events display significant temporal and spatial variability, which is largely driven by dynamic environmental conditions and human activities. In this review, we summarize recent advancements in understanding the spatiotemporal patterns of long-distance transport, the interannual variability in bloom size, and the underlying mechanisms driving these fluctuations. Additionally, we highlight important knowledge gaps that need further investigation to support the development of effective management strategies for mitigating the impacts of green tides in the Yellow Sea.

Abstract: Wetland restoration has led to land-use changes of coastal zone and also effected on soil nutrient distribution and dynamics. To characterize the differences of typical biogenic elements (C, N and P) distribution and trends of soil induced by wetland restoration policy, we studied two intervention strategies which covered woodland or cropland converted into wetland from four wetland use conditions (ash grove (AG), permanent wetland (PW), wheat field (WF) and seasonal wetland (SW)) in the Yellow River Delta (YRD). The results demonstrated that conversion to permanent wetland showed a more or less significant increase in concentrations and stoichiometric ratios of soil C, N and P, while reclamation of seasonal wetland increased soil N and soil P and the ratio of soil N:P (RNP). We observed the mean soil C concentrations of PW and SW increased by 31.1% and 6.3% in the 0-50cm soil profile separately, compared to their former wetland use, confirming powerful C sequestration of coastal wetlands. PW after 25 years of conversion of woodland to wetland showed an increase in soil C:N (RCN, 25.7%) and C:P (RCP, 30.0%) and SW after 12 years of returning cropland to wetland showed an increase by 17.6% in RCN throughout the soil profile, while similar differences of soil in top 5 cm layers turned out to be even apparent in the studied four wetland use conditions, suggesting the varying of different wetland intervention strategies and implementation period. The underlying changes in nutrient distribution and stoichiometric ratio dynamics are mainly due to C sequestration of wetland and N/P fertilization of reclamation. This brings new insights and helps to increase the knowledge the long-term effect of wetland restoration on soil nutrient distribution and trends in YRD. Understanding these effects can provide sensible policymaking for the conservation and management of coastal wetlands, which is helpful to realize ecological functionality of coastal wetland and achieve carbon neutrality in China.

Abstract: Nanotechnology is transformative in its ability to meet the world's major agricultural challenges of climate change, soil erosion, and food insecurity. This research examines nanotechnology in the context of improving productivity and environmental sustainability with innovations like nano-fertilizers, nano-pesticides, and nano-sensors. North America, Europe, Asia, and Africa case studies illustrate dramatic increases in yields (15–20%), decreased use of agrochemicals (30–50%), and effective management of resources. Nano-remediation methods, including nano-zero-valent iron, eliminate 70–90% of water and soil contaminants, ensuring cleaner environments. Although promising, there are challenges such as regulatory loopholes, expense, and environmental hazards. The research supports uniform policies, education of farmers, and global cooperation to facilitate safe and fair use. Nanotechnology becomes a prime motivator for sustainable agriculture, reconciling productivity with sustainability.

Abstract: Microplastic contamination in agricultural soils has become a growing concern due to its potential impact on soil quality and ecosystem health. This study investigates the abundance, shape, and vertical distribution of microplastics in agricultural soils under different tillage practices. A split-split-plot experimental design was used at two sites, comparing conventional tillage (ST), conservation tillage (deep and shallow), and fertilization treatments. Results indicate that microplastics were present in all soil samples, with significantly lower concentrations in conservation shallow tillage (CTS) compared to deep conservation tillage (CTD). Vertical distribution was found to be homogeneous in ST and CTS but heterogeneous in CTD, suggesting an influence of soil disturbance levels on microplastic migration. Fertilization significantly affected microplastic accumulation at one site, supporting the hypothesis that inorganic fertilizers contribute to microplastic input as well. These findings highlight the need for soil management practices that mitigate microplastic accumulation and mobility.

Abstract: The decrease in river streamflow and rainfall volumes due to climate change and/or variability has been affecting several environmental and socioeconomic aspects of the Pantanal floodplain in Brazil. This study analyzed 37-year-long (1986-2023) hydrological time series of rainfall, streamflow and flooded areas in three contributing basins of the Pantanal floodplain (Jauru - JB, Taquari-TB and Miranda-MB), revealing distinct hydrological trends influenced by climate systems and ENSO patterns. Significant decreasing trends in rainfall and streamflow were observed in the northern JB and TB basins, while the southern MB basin showed increasing behavior. As a consequence, the downstream flooded areas in the Pantanal floodplain showed a decreasing trend in the period. Long-term memory processes (Hurst phenomenon) were identified in the time series of the basin flooded surface and also in the Paraguay river stage data, indicating a persistent and aggregated reduction in the hydrologic variables, affecting both the ranching and fishing activities in the region, and the regional ecology. These findings reinforce the need for adaptative management strategies to tackle the impacts of water surface loss, increasing fire risk, and climate variability in the Upper Paraguay basin.

Abstract: Groundwater is the main source of water for both domestic and agricultural use in arid regions. This study assessed the hydrogeochemical characteristics and suitability of groundwater for drinking and irrigation in Kenya’s Ewaso Ng’iro–Lagh Dera Basin. A total of 129 borehole samples were collected and analyzed for pH, electrical conductivity (EC), total hardness, and major ions. The groundwater was found to be mostly neutral to slightly alkaline and ranged from marginal to brackish in salinity. The dominant water type is Na-HCO₃, with the ionic order Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ and HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻. Mineral saturation indices indicate the water is undersaturated with gypsum and anhydrite, but saturated with calcite, dolomite, and aragonite. Groundwater chemistry is primarily influenced by ion exchange and rock weathering processes. The Water Quality Index (WQI) reveals that much of the groundwater is rated poor to unsuitable for drinking, largely due to high levels of sodium, EC, and bicarbonate. Similarly, the Irrigation Water Quality Index (IWQI) places most samples in the moderate to severe restriction category due to salinity and sodicity. These findings highlight the need for proper treatment before use.

Abstract: Wildfires serve both ecological and destructive roles—supporting biodiversity and nu-trient cycling while also threatening ecosystems and economies, especially as climate change drives increases in fire frequency and intensity. This study investigates the impact of wildfires and subsequent vegetation recovery in the Bosco Difesa Grande forest in southern Italy, focusing on the 2017 and 2021 fire events. Using Google Earth Engine (GEE), remote sensing techniques were applied to assess burn severity and post-fire re-growth. The analysis utilized Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 imagery. Burn severity was classified through differenced NBR (dNBR), while vegetation recovery was monitored via differ-enced NDVI (dNDVI) and multi-year NDVI time series. Results show that low-severity zones recovered more quickly than high-severity areas, which often failed to regain pre-fire vegetation levels. These findings suggest a potential shift from forested areas to shrubland or mixed vegetation in severely burned zones. Key recovery influencers in-clude climate variability, soil erosion, and repeated fire exposure. This study highlights the value of remote sensing for post-fire assessment and emphasizes the need for adaptive land management and ecological restoration strategies to support long-term ecosystem resilience in Mediterranean fire-prone landscapes.

Abstract: Carpathian Orogen represents a natural laboratory for studying geodynamic interactions between lithospheres of different ages. The ancient Archean Craton, such as the East European Craton, and Proterozoic platforms like the Scythian and Moesian platforms, collided with the younger Tisza and Dacia Mega-Units, resulting in the formation of the current architecture of the Carpathian Mountains. To better understand how lithospheric structure on Romanian territory changes from the East European Craton to younger European microplates, we used earthquake data recorded at permanent broadband seismic stations of the Romanian National Seismic Network (RSN). Applying the Multiple Filtering Technique, we examine the dispersion of Rayleigh wave group velocities for earthquakes located within a 4000 km radius of the epicenter. Travel time tomography, conducted through Fast Marching Surface Tomography, helps us to construct group velocity maps for periods between 30 and 80 s. Our findings highlight a low velocity body in front of the Vrancea slab, indicating asthenospheric upwelling due to slab verticalization.

Abstract: Macroalgae are an integral part of estuarine primary production, however their excessive growth may have severe negative impacts on the ecosystem. Although it is generally believed that algal blooms may be caused by a combination of excessive nutrients and temperature, their occurrences are hard to predict, and quantitative monitoring is a logistical challenge which requires development of reliable and inexpensive technique. This can be achieved by implementation of processing algorithms and indices on multi-spectral satellite images. Tuggerah Lakes estuary on the Central Coast of NSW was studied because of the regular occurrences of blooms, primarily of green filamentous algae. The detection of algal blooms based on the red-edge effect of the chlorophyll provided consistent results supported by direct observations. Floating Algae Index (FAI) was chosen as the most accurate index detecting algal blooms in shallow areas. Logistic regression was implemented where FAI was used as a predictor of two clusters, “bloom” and “non-bloom”. FAI was calculated for multi-spectral satellite images based on pixels of 20x20 meters, covering the entire area of the Tuggerah Lakes. Seven sample points (pixels) were chosen, and the optimal threshold was found for each pixel to assign it to one of the two clusters. Logistic regression model was trained for each pixel; then the optimal parameters for its coefficients and the optimal classification threshold were obtained by cross validation and bootstrapping. Probabilities for classifying clusters as either “bloom” or “non-bloom” were predicted with respect to the optimal threshold. The resulting model can be used to estimate probability of macroalgal blooms in coastal estuaries allowing quantitative monitoring through time and space.

Abstract: Liming is a common practice for improving the quality of soils affected by acidity, due to climate change, acid rain, nitrate leaching, and oxidation of sulphide minerals. This study aimed not only to assess the efficiency of fine and coarse lime application at 3 t/ha and 6 t/ha doses in mitigating soil acidity, but also to determine which of the options has a stronger impact on improving subsoil characteristics. Over a period of two years, several key parameters were monitored: pH, exchangeable base cations (Caexch, Mgexch, and Kexch), and Alexch. In the topsoil, the highest increase in pH was observed 6 months after the ap-plication of 3 t/ha fine lime, while in the subsoil, only a modest increase was noted. The highest values of exchangeable base cations in the topsoil were: Caexch = 9.06 cmol/kg soil; Mgexch = 1.15 cmol/kg soil; Kexch = 0.360 cmol/kg soil. These were recorded 24 months after applying 6 t/ha of fine aglime, and were higher than those obtained in the subsoil. While in topsoil Alexch reached 0 at T3, in subsoil, the largest decrease was 38% at T3. The release rate of ca Ca and its mobility depend on the particle size and dose of aglime, playing an important role in alleviating aluminium toxicity.

Abstract: Superabsorbent Polymers (SAPs) have been increasingly studied for their potential to enhance soil water holding capacity and reduce irrigation needs, particularly in water-scarce agricultural regions. The objective of this study is to maximize water holding capacity and minimize water irrigation by evaluating the effectiveness of SAPs on Soil Texture, Water Holding Capacity, and pH Content under controlled treatments in Purok Kabelen. The researchers conducted experiments using different SAPs and water treatments by analyzing their effects through ANOVA, Regression Analysis, and Sensitivity Analysis. Findings from the study indicate that SAPs application significantly influences soil physical characteristics. The ANOVA results showed that SAPs had a statistically significant effect on soil texture, water holding capacity, and pH content, with F-values of 309.254, 1309.8, and 401989, respectively (p < 0.05). Regression analysis further confirmed a strong correlation between SAPs application and increased water retention, as well as changes in soil pH. Specifically, the highest water holding capacity of 82.74% was achieved at a 10g SAP: 200mL water per 500g soil treatment by marking a 34.9% increase from the control. Soil texture analysis revealed a rise in clay content from 37% to 83.9%, and soil pH shifted from 6.27 (moderately acidic) to 7.83 (slightly alkaline). The sensitivity analysis examines the effects of Superabsorbent Polymer (SAP) and water on soil texture, Water Holding Capacity (WHC), and pH. SAP applications significantly altered soil texture, with sand content decreasing by up to 83.01% at 5g SAP and silt content dropping by 74.13% at 40g SAP. In contrast, clay content increased, peaking at 126.76% at 5g SAP before stabilizing. Water Holding Capacity improved by 34.87% at 10g SAP, with smaller gains beyond 20g SAP. pH content increased by 24.88% at 80g SAP, shifting the soil toward alkalinity. However, excessive SAPs application beyond the optimal level did not yield proportionate improvements in water holding capacity. This study aligns with the United Nations Sustainable Development Goals (SDGs), particularly Sustainable Development Goal 12 (SDG 12): Responsible Consumption and Production and Sustainable Development Goal 15 (SDG 15): Life on Land. By improving irrigation efficiency, and reducing excessive water use, this study promotes responsible resource management and supports sustainable land practices in agriculture.

Abstract: We have used a rapid, portable assay (Bacterisk) to determine bacterial water quality along several inland waters in SW England. Water samples were compared by conventional membrane filter and culture methods for faecal indicator bacteria (FIB; E. coli and enterococci) and endotoxin measurement by Bacterisk. The Bacterisk data, measured in near real-time, correlates well with both E. coli and enterococci, but also allowed the presence of potential pathogens of non-faecal origin to be detected. The sensitivity was calculated to be 92.96% with a specificity of 46.3% for E. coliwith an expanded uncertainty of 22.07% and an Endotoxin Risk detection limit of 25 units. The presence of Bacterisk detectable non-faecal pathogenic bacteria in the water samples was successfully confirmed by Illumina MiSeq sequencing followed by target species-specific qPCR. Sequencing showed the presence of pathogens including Pseudomonas aeruginosa, Salmonella typhi, Acinetobacter baumannii, Shigella spp, Legionella spp as well as antimicrobial resistance genes. Furthermore, the portable Bacterisk assay was able to acquire data on water quality from different locations and at different time points providing a comprehensive surveillance tool that challenges the time to results by conventional methods (minutes instead of days), yielding compatible results.

Abstract: This study investigates the impact of flare tariff on the volume of gas flared in Nigeria. Using 52 years data, we find that the imposition of flare tariffs significantly reduces the volume of gas flared; however, the extent of this reduction varies depending on the stringency of the tariff. To better capture these differences, the analysis distinguishes between tariff regimes implemented before and after 2018, when a more substantial tariff was introduced under new regulations. The results reveal that pre-2018 tariffs led to a minimal reduction of 0.08% in gas flaring volumes, whereas post-2018 tariffs resulted in a more pronounced reduction of 6.92%. Other factors that significantly influence gas flaring volume include oil production and oil price. These findings underscore the importance of setting adequate flare tariffs to achieve meaningful reductions in global gas flaring.

Abstract: In this study, a vision-based deep learning approach is proposed for altitude estimation for unmanned aerial vehicles (UAVs) as an alternative to traditional methods—such as GPS, barometric sensors, and laser altimeters—that are susceptible to environmental limitations. A comprehensive dataset comprising over 300,000 Nadir images, acquired using Mavic 2 Pro and Mavic 2 Zoom platforms under diverse weather, illumination, and terrain conditions, was employed. The images underwent extensive preprocessing, including data augmentation (e.g., rotations and zooming), the integration of GPS data extracted from EXIF metadata with Digital Elevation Model (DEM) information, coordinate transformations, and scaling adjustments to account for differences in camera systems. A pre-trained ResNet50 model, originally trained on the ImageNet dataset, was adapted for regression tasks and trained over 200 epochs using the Adam optimization algorithm and mean squared error (MSE) loss. Experimental results demonstrate that the proposed method achieves high accuracy, with a mean absolute error (MAE) of 4.09 meters in urban areas and 6.06 meters in rural settings, alongside a high overall coefficient of determination (R² = 0.9981 in urban and 0.9884 in rural environments). These findings indicate that the vision-based deep learning approach can serve as a reliable alternative or complement to conventional sensor technologies for UAV altitude estimation.

Abstract: The integration of energy sectors and the optimisation of resource use are fundamental elements of sustainable development. This study presents a model for analysing energy use based on the structure of Energy Cost Centres (ECCs). The model facilitates a systematic identification and optimisation of energy flows in industrial and urban environments. The developed methodology was tested on a case study of an energy-intensive industry, where we analysed the potential utilisation of renewable energy sources, hydrogen production, electricity storage, and the use of excess heat for the local community. The results indicate that the systematic application of the model could achieve total electricity savings of 9,598 MWh, alongside 4,116,850 Nm³ of natural gas savings through excess heat utilisation. These measures collectively contribute to an annual CO₂ emissions reduction of 10,984 tonnes. The approach enhances the integration of sustainable energy solutions, strengthens stakeholder collaboration, and increases the economic viability of projects. Moreover, the model can be adapted for use in other industrial and urban settings. Despite potential barriers such as data availability and initial implementation costs, the results confirm the approach´s value in the strategic planning of sustainable energy systems.

Abstract: A Climate change and its adverse effects are now the greatest threats faced by society. As a consequence, it is essential to adopt strategic instruments and adaptation measures – especially in the most vulnerable and susceptible areas, such as coastal zones. An analysis has been carried out on the instruments and adaptation measures designed to combat the effects of climate change in coastal countries of the European Union. A bibliographic search of technical and scientific documents has been carried out using various information platforms. Strategic planning instruments were subsequently studied and adaptation measures were classified. The results of this study indicate that, in relation to strategic instruments, there has been a significant and progressive increase in the adoption of adaptation plans and strategies that address problems faced by coastal areas. Physical-structural adaptation measures are the most widely used, especially ecosystem-based and engineering measures, even in specific projects implemented at different territorial scales of governance. One of the main conclusions drawn from the analysis is that, from an operational perspective, the local scale is the most suitable for implementing adaptation measures.

Abstract: The objective is to show that the known features of global average sea-level over the last 120,000 years can be accounted for by eleven periodic functions associated with planetary orbits – the hypothesis. The method shows that proxy data for relative global average sea-level during the last glacial cycle, with errors measured in meters, and a modern sea-level reconstruction based on tide gauges, with errors measured in millimeters, are accurately fit using these periods and a single constant. The eleven periods, sine and cosine for each, and constant correspond to twenty-three functions. Reasons for including each period are provided. The fit predicts a maximum in global average sea-level on date 9,726 with elevation 12 meters above the 1930 level. Reasonable variations of the input data also predict a maximum in global average sea-level between years 9,726 and 12,605.

Abstract: BACKGROUND AND OBJECTIVES: In 2002, Bangladesh became the first country to implement a ban on the use of polyethylene bags. However, after 20 years, it appears that the ban has not been implemented. Taking this considera-tion, this study investigates the political and economic barriers to the implementations of polyethene bag ban in Bangladesh. METHODS: This study employed a multi-faceted methodology to compre-hensively investigate plastic pollution and management strategies. In this study, content analysis involved reviewing several key documents, including national policies and international frame-works. Spatial analysis using ArcGIS contributed spatial insights, while face-to-face Key Informant Interviews and an online survey captured diverse perspectives. FINDINGS: This study found that low pricing of polythene bag, no available alternatives of polythene bag, high price of alternatives, lack of financial and infrastructural support for the eco-friendly alternatives are the main economic barrier to the polyethene bag bans. Notably, 91 participants (57.90%) think that lack of cheaper alternatives such as polyethene bags is the main barrier to implement of the ban in Bangladesh. The results also indicated that cheaper price (22%), easy availability (36%), and high price of alternative (27%) were the main reasons for preferring polyethene bags among participants. The finding of this study is that a cheaper and environment friendly alternative is needed in our country to implement the ban successfully. Additionally, the public and private sectors should come forward to invest in the alternative bag sector to make it cheaper for consumers. The government's initiatives, while commendable, necessitate stringent enforcement, amendments for specificity, and expansion beyond Dhaka to ensure holistic efficacy. CONCLUSION: The central government's role in influencing plastic waste management through taxation and incentives is pivotal, requiring alignment NGOs and civil society, for fostering public awareness and collaboration. This comprehensive examination serves as a foundation for informed policymaking and sustainable interventions to address the pressing challenges of plastic waste in Bangladesh.

Abstract: Nuisance and harmful algal blooms can negatively impact freshwater, estuarine, and coastal marine systems globally, and pose serious risks to water quality, human and ecosystem health, and food production. Algae can produce toxic compounds, directly interfere with aquaculture species through (e.g.) production of foam or mucilage and can result in hypoxic conditions when the bloom senesces. Application of US Environmental Protection Agency (USEPA) registered algaecides can be effective, scalable, and inexpensive, but there is growing interest in plant or bacterial derived compounds that do not require the use of chemicals such as hydrogen peroxide or copper. The algaecide C7X1 is a plant based organic algaecide that proves effective against a wide variety of algae, including harmful algal species such as Microcystis, Heterosigma, and Pseudo-nitzschia. Performance is comparable to other USEPA-registered algaecides, with minimal toxin extracellular toxin release and a potential lifetime of weeks in treated waters. The mode of action is inhibition of photosynthesis, suggesting that direct off-target impacts to zooplankton and other organisms would be minimal.