Search Results (375)

Acid rain poses a significant threat to forest ecosystems globally, with substantial impacts on soil organic carbon decomposition. This study employs a meta-analysis of 361 datasets from 63 published studies to investigate the response of SOC decomposition in forest ecosystems to acid rain. Our analysis reveals that acid rain has a significant inhibitory effect on SOC decomposition. Precipitation emerges as a crucial large-scale environmental factor that differentially modulates this effect; it alleviates acid rain’s suppressive impact on litter decomposition by diluting H⁺ ions but intensifies the inhibition of soil decomposition due to the soil’s strong adsorption capacity. Furthermore, our results indicate that acid rain exerts a more pronounced inhibitory effect on soil organic carbon decomposition than on litter decomposition. Compared to small-scale factors, precipitation plays a more significant role in regulating the inhibitory effects of acid rain on organic carbon decomposition. These findings underscore the need to integrate precipitation into carbon-cycle models and tailor management strategies to specific climates for sustainable forest carbon management. It also provides a theoretical foundation for predicting the response of forest carbon decomposition to environmental change and for balancing ecological protection with sustainable development in acid rain-impacted regions. Full article

Urban flooding and the management of stormwater present significant challenges that necessitate innovative and sustainable solutions. This research examines the effectiveness of green stormwater infrastructure (GSI) for resilient storm sewer systems using the Storm Water Management Model (SWMM), based on customized local climate scenarios. Daily climate data downscaled by four CMIP6 models—CESM2, GFDL-CM4, GFDL-ESM4, and NorESM2-MM—was used. The daily data was disaggregated into 15 min temporal resolution using the HyetosMinute R-package. Two GSI types—bio-retention and rain gardens—were evaluated with a maximum coverage of 30%. The analysis focuses on two future climate scenarios, SSP2-4.5 and SSP5-8.5, predicted under the Shared Socioeconomic Pathways (SSPs) framework. The performance of the stormwater network was assessed for mid-century (2041–2060) and late century (2081–2100), both before and after integration of GSI. Three performance metrics were applied: node flooding volume, number of nodes flooded, and pipe surcharging duration. The simulation results showed an average reduction in flooding volumes ranging between 86 and 98% over the area after integration of GSI. Similarly, reductions ranging between 78 and 89% and between 75 and 90% were observed in pipe surcharging duration and number of nodes vulnerable to flooding, respectively, following GSI. These findings underscore the potential of GSI in fostering sustainable urban water management and enhancement of sustainable development goals (SDGs). Full article

The water–energy–food (WEF) nexus provides a critical framework for addressing the interconnected challenges of resource scarcity and sustainability in the face of global population growth and climate variability. This study investigates the application of a WEF nexus approach within the operation and management of a hydroponic greenhouse unit in Central Greece, with the aim of enhancing the unit’s energy autonomy and resource sufficiency. Hydroponics, a soilless cultivation method, optimizes water and land use but relies heavily on energy inputs, necessitating integrated solutions. Through the case study approach, we analyze the unit’s resource dynamics per hectare of water (68 MWh equivalent from desalination), energy (125 MWh or 321 GJ/ha plus 74.5 GJ/ha for fertigation), and food production (~295 tons, which contains 50,250,000 kcal and corresponds to 210 GJ) and propose technical solutions: photovoltaic panels as greenhouse coverings and water rain harvesting regulated with a small reservoir. These innovations could reduce external energy dependency by 90–95% and water use by 25–35%. Energy efficiency is quantified using the energy ratio (ER) and net energy gain (NEG), while resilience is assessed via system reliability under resource variability. Conclusively, this study illustrates how a nexus-based approach can effectively upgrade systems into climate-resilient, resource-efficient models as the abundance or scarcity of one source affects the availability or limitation of the others. Overall, the approach presented in this study could also be used to safeguard the supply chains in megacities. Full article

Temporary architecture, as an expression of the concept of impermanence, offers adaptable and time-sensitive spatial interventions that promote community engagement and encourage experimentation within the urban environment. Beyond its physical and functional qualities, this architectural approach acts as a social mediator, fostering dialogue, networking, and the exchange of ideas between local communities and professionals, while contributing to the development of a socio-cultural common ground. This paper explores the Greenfeel Architecture wooden pavilion as a case study of small-scale architecture embedded within a landscape dedicated to urban agriculture and community-driven activities. The design process was guided by the need to balance functional requirements—providing shelter from the sun and rain and facilitating social interactions—with the protection of the existing vegetation and the enhancement of local biodiversity, with particular emphasis on supporting bee populations. In line with sustainable construction principles, the pavilion was built through the reuse of recovered materials, including used bricks for pavement, wooden slabs for the facade and roof, and several structural components sourced from previous building projects. Since its completion, the pavilion has acted as an urban acupuncture point within the surrounding area and has become a host for various outdoor activities and educational workshops aimed at diverse groups, including children, adults, professionals, and laypersons alike. The duality between the scale of the pavilion and the scale of its social, cultural, or ecological influence highlights the potential of temporary architecture to become a tool for both physical and socio-cultural sustainability in an urban environment. Full article

This study explores the revival of cotton (Gossypium spp. L.) farming in Italy through sustainable practices, addressing economic and water-related challenges by integrating cultivar selection, arbuscular mycorrhizal fungi (AMF) inoculation, and deficit irrigation under organic farming. Field trials evaluated two widely grown Mediterranean cultivars (Armonia and ST-318) under three irrigation levels (I-100: 100% crop water requirement; I-70: 70%; I-30: 30%) across two Sicilian soil types (sandy loam vs. clay-rich). Under I-100, lint yields reached 0.99 t ha⁻¹, while severe deficit (I-30) yielded only 0.40 t ha⁻¹. However, moderate deficit (I-70) maintained 75–79% of full yields, proving a viable strategy. AMF inoculation significantly enhanced plant height (68.52 cm vs. 65.85 cm), boll number (+22.1%), and seed yield (+12.5%) (p < 0.001). Cultivar responses differed: Armonia performed better under water stress, while ST-318 thrived with full irrigation. Site 1, with higher organic matter, required 31–38% less water and achieved superior irrigation water productivity (1.43 kg m⁻³). Water stress also shortened phenological stages, allowing earlier harvests—important for avoiding autumn rains. These results highlight the potential of combining adaptive irrigation, resilient cultivars, and AMF to restore sustainable cotton production in the Mediterranean, emphasizing the importance of soil-specific management. Full article

Recent years have seen frequent heavy rainfall events in Japan, often linked to Baiu fronts and typhoons. These events are exacerbated by global warming, leading to an increased frequency and intensity. As floods represent a serious threat to sustainable urban development and community resilience, this study contributes to sustainability-focused risk reduction through integrated analysis. This study focuses on the 2 June 2023 heavy rain disaster in Toyohashi City, Japan, which caused extensive damage due to flooding from the Yagyu and Umeda Rivers. Using numerical models, this study accurately reproduces flooding patterns, revealing that high tides amplified the inundation area by 1.5 times at the Yagyu River. A resident questionnaire conducted in collaboration with Toyohashi City identifies key trends in evacuation behavior and disaster information usage. Traditional media such as TV remain dominant, but younger generations leverage electronic devices for disaster updates. These insights emphasize the need for targeted information dissemination and enhanced disaster preparedness strategies, including online materials and flexible training programs. The methods and findings presented in this study can inform local and regional governments in building adaptive disaster management policies, which contribute to a more sustainable society. Full article

The development of slow-release fertilizers (SRFs) based on production residues is a promising strategy to improve nutrient use efficiency and promote circular economy practices in agriculture. In this study, a series of experimental formulations were designed and tested using pumice scraps, liquid and dried blood, and bone meal, aiming at producing sustainable and low-cost N-P-K SRFs. These were processed through mixing and granulation, both in the laboratory and on a semi-industrial scale. The formulations were evaluated through release tests in 2% citric acid solution simulating the acidic conditions of the rhizosphere, and in acetic acid to assess potential nutrient leaching under acid rain conditions. The results showed a progressive cumulative release of macronutrients (NPKs), ranging from approximately 8% at 24 h to 73% after 90 days for the most effective formulation (WBF6). Agronomic trials on lettuce confirmed the effectiveness of WBF6, resulting in significant biomass increases compared with both the untreated control and a conventional fertilizer. The use of livestock waste and minerals facilitated the development of a scalable product aligned with the principles of sustainable agriculture. The observed release behavior, combined with the simplicity of production, positions these formulations as a promising alternative to conventional slow-release fertilizers. Full article

This study introduces an algorithm for quantifying oceanic wind speed and identifying sound sources in the local underwater soundscape. Utilizing low-complexity metrics like one-minute spectral kurtosis and power spectral density levels, the algorithm categorizes different soundscapes and estimates wind speed. It detects rain, vessels, fin and blue whales, as well as clicks and whistles from dolphins. Positioned as a foundational tool for implementing the Ocean Sound Essential Ocean Variable (EOV), it contributes to understanding long-term trends in climate change for sustainable ocean health and predicting threats through forecasts. The proposed soundscape classification algorithm, validated using extensive acoustic recordings (≥32 kHz) collected at various depths and latitudes, demonstrates high performance, achieving an average precision of $89\%$ and an average recall of $86.59\%$ through optimized parameter tuning via a genetic algorithm. Here, wind speed is determined using a cubic function with power spectral density (PSD) at 6 kHz and the MASLUW method, exhibiting strong agreement with satellite data below 15 m/s. Designed for compatibility with low-power electronics, the algorithm can be applied to both archival datasets and real-time data streams. It provides a straightforward metric for ocean monitoring and sound source identification. Full article

Accurate weed detection in soybean fields is essential for enhancing crop yield and reducing herbicide usage. This study proposes a YOLO-SW model, an improved version of YOLOv8, to address the challenges of detecting weeds that are highly similar to the background in natural environments. The research stands out for its novel integration of three key advancements: the Swin Transformer backbone, which leverages local window self-attention to achieve linear O(N) computational complexity for efficient global context capture; the CARAFE dynamic upsampling operator, which enhances small target localization through context-aware kernel generation; and the RTDETR encoder, which enables end-to-end detection via IoU-aware query selection, eliminating the need for complex post-processing. Additionally, a dataset of six common soybean weeds was expanded to 12,500 images through simulated fog, rain, and snow augmentation, effectively resolving data imbalance and boosting model robustness. The experimental results highlight both the technical superiority and practical relevance: YOLO-SW achieves 92.3% mAP@50 (3.8% higher than YOLOv8), with recognition accuracy and recall improvements of 4.2% and 3.9% respectively. Critically, on the NVIDIA Jetson AGX Orin platform, it delivers a real-time inference speed of 59 FPS, making it suitable for seamless deployment on intelligent weeding robots. This low-power, high-precision solution not only bridges the gap between deep learning and precision agriculture but also enables targeted herbicide application, directly contributing to sustainable farming practices and environmental protection. Full article

Potato (Solanum tuberosum L.) is a chlorine-sensitive crop. When soil Cl⁻ concentrations exceed optimal thresholds, the yield and quality of potatoes are limited. Consequently, chloride-containing fertilizers are rarely used in actual agricultural production. Therefore, two years of field experiments under natural rainfall regimes with three chlorine application levels (37.5 kg ha⁻¹/20 mg kg⁻¹, 75 kg ha⁻¹/40 mg kg⁻¹, and 112.5 kg ha⁻¹/60 mg kg⁻¹) were conducted to investigate the leaching characteristics of Cl⁻ in field soils with two typical textures for Northeast China (loam and sandy loam soils). In this study, the reliability of Cl⁻ residual estimation models across different soil types was evaluated, providing critical references for safe chlorine-containing fertilizer application in rain-fed potato production systems in Northeast China. The results indicated that the leaching efficiency of Cl⁻ was significantly positively correlated with both the rainfall amount and the chlorine application rate (p < 0.01). The Cl⁻ migration rate in sandy loam soil was significantly greater than that in loam soil. However, the influence of soil texture on the Cl⁻ leaching efficiency was only observed at lower rainfall levels. When the rainfall level exceeded 270 mm, the Cl⁻ content in all the soil layers became independent of the rainfall amount, soil texture, and chlorine application rate. Under rain-fed conditions, KCl application at 80–250 kg ha⁻¹ did not induce Cl⁻ accumulation in the primary potato root zone (15–30 cm), suggesting a low risk of toxicity. In loam soil, the safe application range for KCl was determined to be 115–164 kg ha⁻¹, while in sandy loam soil, the safe KCl application range was 214–237 kg ha⁻¹. Furthermore, a predictive model for estimating Cl⁻ residuals in loam and sandy loam soils was validated on the basis of rainfall amount, soil clay content, and chlorine application rate. The model validation results demonstrated an exceptional goodness-of-fit between the predicted and measured values, with R² > 0.9 and NRMSE < 0.1, providing science-based recommendations for Cl-containing fertilizer application to chlorine-sensitive crops, supporting both agronomic performance and environmental sustainability in rain-fed systems. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

Low-impact development (LID) offers environmental, economic, and social benefits, yet research on optimizing facility combinations remains limited. This study evaluates four representative LID types—green roofs, sunken green spaces, permeable pavement, and rain gardens—using an integrated framework combining the Storm Water Management Model (SWMM), NSGA-II genetic algorithm, and Analytic Hierarchy Process (AHP) at Taiyuan University of Technology in Shanxi Province, China. Based on site constraints, each LID type was pre-assigned to suitable subareas, and optimization focused on determining proportional allocations within these areas. SWMM simulations revealed that permeable paving achieved the highest runoff reduction (up to 19.4% at 65% coverage) and strong cost-effectiveness (0.013 USD per % reduction). NSGA-II was used to generate a set of optimal solutions by minimizing construction costs and maximizing runoff and pollutant reductions. AHP then ranked these solutions according to their environmental, economic, and social benefits. In this case, the ideal mix—subject to site-specific constraints and model assumptions—includes 28.58% green roofs, 19.37% sunken green spaces, 48.68% permeable paving, and 3.37% rain gardens. The study proposes a sponge campus renewal strategy, offering theoretical and practical insights for sustainable urban development and precise environmental management. Full article

This article examines the modeling of sustainable development in transport logistics, focusing on the impact of climate factors, changing weather conditions, and digitalization processes. The study analyzes the complex influence of adverse weather phenomena, such as fog, rain, snow, extreme temperatures, and strong winds, whose frequency and intensity are increasing due to climate change, on the efficiency, safety, and reliability of transport systems across all modes except pipelines. Special attention is paid to the integration of weather-resilient sensor technologies, including LiDAR, thermal imaging, and advanced monitoring systems, to strengthen infrastructure resilience and ensure uninterrupted transport operations under environmental stress. The methodological framework combines comparative analytical methods with economic–mathematical modeling, particularly Leontief’s input–output model, to evaluate the mutual influence between the transport sector and sustainable economic growth within an interconnected ecosystem of economic and technological factors. The findings confirm that data-driven management strategies, the digital transformation of logistics, and the strengthening of centralized hubs contribute significantly to increasing the resilience and flexibility of transport systems, mitigating the negative economic impacts of climate risks, and promoting long-term sustainable development. Practical recommendations are proposed to optimize freight flows, adapt infrastructure to changing weather risks, and support the integration of innovative digital technologies as part of an evolving ecosystem. Full article

The carbon metabolism activity of rhizosphere soil microbial communities is an essential indicator for assessing soil ecosystem health, as it directly affects soil nutrient cycling and the stability of organic matter. However, there is a limited understanding of the carbon metabolism characteristics of rhizosphere soil microorganisms in alfalfa (Medicago sativa L.) of different ages and their relationships with soil physicochemical properties. This study used Biolog EcoPlates to evaluate the carbon metabolism activity, functional diversity, and carbon-source utilization preferences of rhizosphere soil microbial communities in 5-, 7-, and 9-year-old alfalfa grasslands on the semi-arid Loess Plateau of western China. We analyzed the relationships between soil physicochemical properties and microbial carbon metabolism characteristics, considering their potential covariation. The results showed that, with the extension of alfalfa planting years, the rhizosphere soil water content decreased significantly, pH decreased slightly, but soil organic carbon, total nitrogen, and total phosphorus contents increased significantly. The rhizosphere soil microbial community of 9-year-old alfalfa exhibited the highest carbon metabolism activity, Shannon diversity index, and carbon-source utilization. Rhizosphere soil microorganisms from different-aged alfalfa showed significantly different preferences for carbon-source utilization, with microorganisms from 9-year-old alfalfa preferentially utilizing carbon sources such as N-acetyl-D-glucosamine, D-mannitol, and D-cellobiose. Redundancy analysis revealed that soil water content was among the most important factors influencing the carbon metabolism activity of rhizosphere soil microbial communities while acknowledging that the relative contributions of soil water content, organic carbon, and nitrogen require careful interpretation, owing to their potential collinearity. This study demonstrates that, under rain-fed conditions in the semi-arid Loess Plateau, the continuous cultivation of alfalfa for nine years led to a significant decrease in soil water content but enhanced the rhizosphere soil nutrient status and microbial carbon metabolism activity, with no apparent signs of microbial functional degradation, although soil water depletion was observed. These findings highlight the complex interactions among multiple soil factors in influencing microbial carbon metabolism, providing valuable microbiological insights for understanding the sustainability of alfalfa grasslands and a theoretical basis for the scientific management of alfalfa grasslands in the semi-arid Loess Plateau region. Future research should consider longer planting periods to determine the critical age of alfalfa grassland degradation under semi-arid conditions and its associated microbial mechanisms. Full article

Nitrogen (N) plays a decisive role in the growth and yield of crops. Hence, a high maize grain yield depends upon substantial N inputs. In the present study, morphological traits and yield components, grain yield, rain use efficiency (RUE), and N partial factor productivity (NPFP) were analyzed in two maize hybrids (ZP666 and NS6030) for 2 yr using four N rates (0 (N0), 60 (N60), 120 (N120), and 180 (N180) kg N ha⁻¹). In a climatically more favorable year (2022), the studied traits and NPFP were higher, while RUE was lower. Hybrid ZP666 had higher values of morphological traits and yield component traits, except 1000-grain weight, grain yield, RUE, and NPFP, than hybrid NS6030. The highest values for morphological traits, yield components, grain yield (9383 and 9456 kg ha⁻¹), and RUE (27.1 and 27.2 kg ha⁻¹ mm⁻¹) were obtained at 120 and 180 kg N ha⁻¹. The NPFP decreased significantly with increasing N input, from 137.6 (control) to 52.5 kg grain per kg fertilizer N (180 kg N ha⁻¹). A suitable hybrid selection and the application of a moderate N fertilizer rate of 120 kg N ha⁻¹ could contribute to high yields and lower nitrogen losses to the environment and promote sustainable agriculture. Full article