Search Results (104)

Artisanal fisheries in southern Chile rely heavily on the Patagonian red octopus (Enteroctopus megalocyathus) as a valuable resource, contributing significantly to local economies. This octopus species accounts for 25–40% of Chilean octopus landings. It is a merobenthic species, characterized by a semelparous life cycle and a long brooding period, and it is distributed along the Pacific and Atlantic coasts of the southern tip of South America, inhabiting holes and crevices in rocky substrates. However, this fishery faces critical challenges to both its ecological sustainability and the food safety of octopus products. The primary fishing method, using hooks, poses a risk to reproductive capacity as it can capture brooding females. Food safety concerns arise from microbial contamination during pre- and post-harvest handling, bioaccumulation of toxins from algal blooms, and the presence of heavy metals in the marine environment. While evisceration effectively reduces the risk of consuming toxins and heavy metals, inadequate hygiene practices and insufficient ice usage throughout the production chain represent significant food safety risks. Chilean fishing Law No. 18892/1989 defines artisanal fishing and establishes territorial use rights in fisheries (TURFs) to promote sustainable extraction of benthic resources. Integrating training programs on post-harvest handling, hygiene practices, and food safety measures into the TURFs framework, along with targeted investments in infrastructure and technical assistance, is crucial to ensure the long-term sustainability of the E. megalocyathus fishery, protect consumer health, and maintain the economic viability and environmental sustainability of this vital resource for local communities. Full article

The Qinling Mountains serve as the main water source for the Weihe River and Hanjiang River. However, the lack of sufficient observational data limits a deeper understanding and the utilization of its water resources. In this study, the Variable Infiltration Capacity (VIC) hydrological model is used to quantitatively analyze runoff changes and their impacts on these rivers, based on meteorological, land use, and elevation data. By using the hydrological parameter transplantation method, a parameterized system was established to simulate runoff variations from 1970 to 2020. Results showed that the total runoff of the Qinling Mountains in Shaanxi Province ranged between 13.26 and 44.47 billion m³/year, with an average perennial runoff of 25.05 billion m³/year. Over the past 51 years, the runoff volume has exhibited a slightly decreasing trend. The average runoff at the northern foothills is 3.56 billion m³/year, which accounts for 62.4% of the natural average runoff of the Weihe River (Huaxian Station). In contrast, the average runoff at the southern foothills is 21.49 billion m³/year, which accounts for 68.1% of the natural average runoff of the Hanjiang River (Huangjiagang Station). The significant variation in water vapor transport from the western equatorial Pacific to the region via the South China Sea has been identified as the primary reason for the changes in runoff. This quantitative study of runoff changes in the Qinling Mountains clarifies their influence on the Weihe River and the Hanjiang River and will provide a basis for the rational usage of ecological water. Full article

Hydrogen is a crucial energy carrier for the Clean Energy Sustainable Development Goals and the just transition to low/zero-carbon energy. As a top CO₂-emitting country, hydrogen (especially green hydrogen) production in South Africa has gained momentum due to the availability of resources, such as solar energy, land, wind energy, platinum group metals (as catalysts for electrolysers), and water. However, the demand for green hydrogen in South Africa is insignificant, which implies that the majority of the production must be exported. Despite the positive developments, there are unclear matters, such as dependence on the national electricity grid for green hydrogen production and the cost of transporting it to Asian and European markets. Hence, this study aims to explore opportunities for economic expansion for sustainable production, transportation, storage, and utilisation of green hydrogen produced in South Africa. This paper uses a thematic literature review methodology. The key findings are that the available renewable energy sources, incentivizing the green economy, carbon taxation, and increasing the demand for green hydrogen in South Africa and Africa could decrease the cost of hydrogen from 3.54 to 1.40 €/kgH₂ and thus stimulate its production, usage, and export. The appeal of green hydrogen lies in diversifying products to green hydrogen as an energy carrier, clean electricity, synthetic fuels, green ammonia and methanol, green fertilizers, and green steel production with the principal purpose of significant energy decarbonisation and economic and foreign earnings. These findings are expected to drive the African hydrogen revolution in agreement with the AU 2063 agenda. Full article

Studying the development of land green utilization efficiency and the factors that influence it in the Beijing–Tianjin–Hebei region can improve the distribution of land resources among regions and reinforce interregional integrated planning. By constructing a super-efficiency SBM model, calculating the Malmquist–Luenberger index, and constructing a Tobit model, this study explores the spatial features and temporal variations of land green use efficiency in the Beijing–Tianjin–Hebei region from 2010 to 2022. It also examines the mechanism that drives land green use efficiency in the context of the Beijing–Tianjin–Hebei synergistic development. According to this research, Beijing has consistently had the highest land green usage efficiency and a strong green development strength, whereas Baoding, Xingtai, Handan, and other cities in Hebei Province have lower land green utilization efficiency. According to the geographical dimension, the research area’s land green use efficiency exhibits a pattern of “high in the middle and low in the surroundings”, with Cangzhou, Langfang, and Tangshan standing out in terms of both industrial transformation and ecological building. Based on the results of the driving mechanism of land green use efficiency, it is evident that while the degree of urbanization and population concentration has a negative effect on land green use efficiency, the degree of economic development, industrial synergy, opening up to the outside world, environmental regulation, and ecological output all have positive and promoting associations with it. In summary, increasing the optimization of the economic and industrial structure, bolstering technological innovation and policy coordination, and attaining a harmonious coexistence of the economy and ecology are all essential steps in the process to increase the land green use efficiency in the research area when attempting to achieve the goal of sustainable development in the region. Full article

The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can only realize limited functions, and shared parking is far from being implemented on a large scale. Since off-street parking provides the majority of potential shared parking spaces, this paper takes periodic off-street parking lots as the starting point for opening the shared parking market. Based on data from the Ningbo Yongcheng parking platform, power spectral density (PSD) and the autocorrelation function (ACF) are used to identify periodic parking lots. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based method is applied to clustering the occupancy time series. Land use, user type, parking duration, and parking patterns are then analyzed to study shared parking supply characteristics. The results show that (1) 31.3% of off-street parking lots are periodic parking lots, and 90.3% of them have regular users exceeding 50%. (2) Periodic parking lots are classified into four types. Most parking lots show convex flat peak, double peak, or triple peak characteristics. (3) The shared parking spaces demonstrate spatial and temporal imbalances. But in a small area, even considering the concentration of land use and the peak period, there are still enough spaces available. The above research is of significance for the large-scale implementation of shared parking, which can promote the sustainable development of a city. Full article

This study takes the Beijiang River Basin in Guangdong Province as an example, examining the changes in land usage throughout time and space between 1980 and 2020. Using multidimensional ecosystem service functions and the loop theory, this study constructs ecological constraints (ES) for the Beijiang River Basin. Based on these ecological constraints, an ES-PLUS model is developed to simulate future land cover changes under multiple scenarios in the Beijiang River Basin by 2050. The results indicate the following: (1) Currently, the major land use types in the Beijiang River Basin are forest, cropland, and grassland, accounting for over 95% of the area. Significant changes in land use were observed between 1980 and 2020, including the severe degradation of forests and grasslands, a notable expansion of construction land, intense human–land conflicts, and the highest single land use dynamic degree for unused land at 5.67%, with a comprehensive land use dynamic degree of 0.18%. (2) In the four development scenarios of the Beijiang River Basin in 2050, construction land increased by 32.97%, 74.75%, 26.01%, and 45.50%, respectively, suggesting that ecological constraints as flexible constraint spaces can effectively control the disorderly expansion of construction land. Therefore, formulating ecological protection policies, optimizing the land use structure in the Beijiang River Basin, and constructing ecological sources and corridors in line with the distribution of urban areas, roads, and railroads in the basin may offer direction for the best use of land resources, the preservation of the environment, and sustainable growth in the Beijiang River Basin. Full article

Push–pull technology (PPT) integrates maize with the legume fodder Desmodium sp. and the border crop Brachiaria sp., aiming to enhance maize production in Rwanda. Despite its potential, the adoption of complementary soil management practices (SMP), vital for PPT’s success, remains low. This study employs spatial econometric methods to evaluate the determinants of SMP adoption and the interdependencies in decision-making among PPT-practicing farmers. We constructed a spatial weight matrix based on a global Moran’s I index and identified optimal model parameters through principal component analysis. Utilizing a spatial Durbin probit model (SDPM), we assessed the spatial interdependence of SMP adoption decisions among maize farmers. Our findings reveal significant spatial dependence in SMP adoption within a 1.962 km radius, with improved seed usage, household income, yield, farmer group membership and size of land cultivated being key factors positively influencing adoption. We propose a “nonequilibrium promotion strategy” to enhance SMP adoption, emphasizing the establishment of pilot regions to broaden outreach. Additionally, fostering technical training and selecting farmers with adequate resources as demonstration leaders can enhance spatial spillover effects. This research provides insights for developing policies to scale up push–pull technology in Rwanda and across Sub-Saharan Africa. Full article

Land management is critical for the conservation of natural resources, particularly in agroforestry systems which rely heavily on land productivity and availability. Optimizing land utilization is critical for sustainable biomass production and is a key component of achieving effective, long-term sustainable land management. This study assesses the resource efficiency of agroforestry production systems with a novel exergy-based indicator (ΔEF). The indicator was used in the Biobío and Ñuble regions to assess the resource balance between six agricultural and two forestry production systems. The ΔEF values ranged from positive to negative, with positive values indicating better resource usage and negative values suggesting the opposite. Eucalyptus globulus had higher ΔEF values (18.06–19.5 MJex/m².yr) than Pinus radiata (−2.71 to −1.47 MJex/m².yr), indicating better sustainability due to its high biomass yields and lower harvesting period and resource consumption. Sugar beet, wheat, and potatoes were the most sustainable (8.57–154.6 MJex/m².yr) because of their high yields and less intensive harvesting methods. Disparities in biomass yield, potential net primary production (NPP_pot), and land management intensity drive differences in ΔEF across regions. Our findings enhance the understanding of local and non-local resource efficiency in agroforestry systems, revealing significant drivers to encourage more sustainable land management practices. Full article

To effectively manage the sustainable urban development of cities, it is crucial to quickly understand the geological and geotechnical attributes of the underground. Carrying out such studies entails significant investments and focused reconnaissance efforts, which might not align seamlessly with large-scale territorial planning initiatives within a city accommodating more than 3 million inhabitants, like Casablanca in Morocco. Additionally, various specific investigations have been conducted by municipal authorities in recent times. The primary aim of this study is to furnish city managers and planners with a tool for informed decision-making, enabling them to explore the geological and geotechnical properties of soil foundations using Geographic Information Systems (GISs) and geostatistics. This database, initially intended for utilization by developers and construction engineers, stands to economize a substantial amount of time and resources. During the urban planning of cities and prior to determining land usage (five- or seven-floor structures), comprehending the mechanical traits (bearing capacity, water levels, etc.) of the soil is crucial. To this end, geological and geotechnical maps, along with a collection of 100 surveys, were gathered and incorporated into a GIS system. These diverse data sources converged to reveal that the underlying composition of the surveyed area comprises silts, calcarenites, marls, graywackes, and siltstones. These formations are attributed to the Middle Cambrian and the Holocene epochs. The resultant geotechnical findings were integrated into the GIS and subjected to interpolation using ordinary kriging. This procedure yielded two distinct maps: one illustrating bearing capacity and the other depicting the substratum. The bearing capacity of the soil in the study zone is rated as moderate, fluctuating between two and four bars. The depth of the foundation remains relatively shallow, ranging from 0.8 m to 4.5 m. The outcomes are highly promising, affirming that the soil in Casablanca boasts commendable geotechnical attributes capable of enduring substantial loads and stresses. Consequently, redirecting future urban planning in the region toward vertical expansion seems judicious, safeguarding Casablanca’s remaining green spaces and the small agricultural belt. The results of this work help to better plan the urban development of the city of Casablanca in a smarter way, thus preserving space, agriculture, and the environment while promoting sustainability. In addition, the databases and maps created through this paper aim for a balanced financial management of city expenditures in urban planning. Full article

Access to clean and safe drinking water is a fundamental human right. Despite global efforts, including the UN’s “Water for Life” program, a significant portion of the population in developing countries, including Somaliland, continues to rely on unimproved water sources. These unimproved sources contribute to poor health outcomes, particularly for children. This study aimed to investigate the factors associated with the use of unimproved drinking water sources in Somaliland by employing supervised machine learning models to predict patterns and determinants based on data from the 2020 Somaliland Demographic and Health Survey (SHDS). Secondary data from SHDS 2020 were used, encompassing 8384 households across Somaliland. A multilevel logistic regression model was applied to analyze the individual- and community-level factors influencing the use of unimproved water sources. In addition, machine learning models, including logistic regression, decision tree, random forest, support vector machine (SVM), and K-nearest neighbor (KNN), were compared in terms of accuracy, sensitivity, specificity, and other metrics using cross-validation techniques. This study uses supervised machine learning models to analyze unimproved drinking water sources in Somaliland, providing data-driven insights into the complex determinants of water access. This enhances predictive accuracy and informs targeted interventions, offering a robust framework for addressing water-related public health issues in Somaliland. The analysis identified key determinants of unimproved water source usage, including socioeconomic status, education, region, and household characteristics. The random forest model performed the best with an accuracy of 93.57% and an area under the curve (AUC) score of 98%. Decision tree and KNN also exhibited strong performance, while SVM had the lowest predictive accuracy. This study highlights the role of socioeconomic and community factors in determining access to clean drinking water in Somali Land. Factors such as age, education, gender, household wealth, media access, urban or rural residence, poverty level, and literacy level significantly influenced access. Local policies and resource availability also contribute to variations in access. These findings suggest that targeted interventions aimed at improving education, infrastructure, and community water management practices can significantly reduce reliance on unimproved water sources and improve the overall public health. Full article

Recycling’s value in conserving scarce resources, avoiding environmental damage to the land, and reducing energy consumption is well known. This research aims to develop a composite that uses recycled reinforcement that was formed through an in situ method to build confidence in the usage of recycled materials. Thus, in connection with defense and aerospace industry applications, aluminum composite alloys receive more interest due to their light weight and high strength with improved mechanical properties; therefore, this research focuses on the fabrication of in situ-developed recycled TiC (r-TiC)-reinforced AlZnMgCu composites, i.e., new recycled materials. Experiments were conducted to determine the synthesized composites’ microstructural, mechanical, tribological, and corrosion properties. The microstructural study showed that r-TiC was distributed uniformly along the grain boundaries until the addition of 12% r-TiC. However, the accumulation of reinforcements began at 14% r-TiC addition and became more aggregated with subsequent increases in the percentage addition of r-TiC. The mechanical and tribological tests showed that the composite with 14% r-TiC was superior to all other compositions, with 60% improved mechanical qualities and the lowest wear rate of 0.0007 mm3/m. Composites containing 2% r-TiC showed the best corrosion resistance, an increase of 22% over AlZnMgCu, without reinforcement. Full article

The use of satellites to cover remote areas is a promising approach for increasing communication availability and reliability. The satellite resources, however, can be quite costly, and developing ways to optimize their usage is of great interest. Optimizing spectral efficiency while keeping the transmission error rate above a certain threshold represents one of the crucial aspects of resource optimization. This paper provides a novel strategy for adaptive coding and modulation (ACM) employment in land mobile satellite networks. The proposed solution incorporates machine learning techniques to predict channel state information and subsequently increase the overall spectral efficiency of the network. The Digital Video Broadcasting Satellite Second Generation (DVB-S2X) satellite protocol is considered as the use case, and by using the developed channel simulator, this paper performs an evaluation of the proposed machine learning solutions for channels with various characteristics, with a total of 90 different observed channels. The results show that a convolutional neural network with a modified loss function consistently achieves an improvement (over 100% in some scenarios) of spectral efficiency compared to the state-of-the-art ACM implementation while keeping the transmission error rate under 0.01 for single channel evaluation. When observing two channels, an improvement of more than 300% compared to the outdated information spectral efficiency was obtained in multiple scenarios, showing the effectiveness of the proposed approach and allowing optimization of the handover strategy in satellite networks that allow user-centric handover executions. Full article

The integrated use of remote sensing and machine learning stands out as a powerful and well-established approach for dealing with various environmental monitoring tasks, including deforestation detection. In this paper, we present a tunable, data-driven methodology for assessing deforestation in the Amazon biome, with a particular focus on protected conservation reserves. In contrast to most existing works from the specialized literature that typically target vast forest regions or privately used lands, our investigation concentrates on evaluating deforestation in particular, legally protected areas, including indigenous lands. By integrating the open data and resources available through the Google Earth Engine, our framework is designed to be adaptable, employing either anomaly detection methods or artificial neural networks for classifying deforestation patterns. A comprehensive analysis of the classifiers’ accuracy, generalization capabilities, and practical usage is provided, with a numerical assessment based on a case study in the Amazon rainforest regions of São Félix do Xingu and the Kayapó indigenous reserve. Full article

This paper explores the application of The World Avatar (TWA) dynamic knowledge graph to connect isolated data and assess the impact of rising sea levels in Singapore. Current sea level rise vulnerability assessment tools are often regional, narrow in scope (e.g., economic or cultural aspects only), and are inadequate in representing complex non-geospatial data consistently. We apply TWA to conduct a multi-perspective impact assessment of sea level rise in Singapore, evaluating vulnerable buildings, road networks, land plots, cultural sites, and populations. We introduce OntoSeaLevel, an ontology to describe sea level rise scenarios, and its impact on broader elements defined in other ontologies such as buildings (OntoBuiltEnv ontology), road networks (OpenStreetMap ontology), and land plots (Ontoplot and Ontozoning ontology). We deploy computational agents to synthesise data from government, industry, and other publicly accessible sources, enriching buildings with metadata such as property usage, estimated construction cost, number of floors, and gross floor area. An agent is applied to identify and instantiate the impacted sites using OntoSeaLevel. These sites include vulnerable buildings, land plots, cultural sites, and populations at risk. We showcase these sea level rise vulnerable elements in a unified visualisation, demonstrating TWA’s potential as a planning tool against sea level rise through vulnerability assessment, resource allocation, and integrated spatial planning. Full article

Determining the spatiotemporal deployment strategy for dockless shared bicycles in urban blocks has always been a focal point for city managers and planners. Extensive research has delved into the usage patterns in terms of time and space, deduced travel purposes, and scrutinized the relationship between trips and the built environment. The elements of the built environment are significantly correlated with the starting and ending points of dockless shared bicycle trips, leading to a scarcity of shared bicycles in areas that are more frequently used as starting points and an abundance of idle bicycles in areas that serve as endpoints. This paper posits that the idle state of shared bicycles is as important as their usage. Utilizing a case study of Xinjiekou Central District in Nanjing, China, we propose a framework for analyzing the temporal and spatial usage and idleness of shared bicycles. We also discuss the impact of various factors, such as proximity to transit stations, land use, and road accessibility, on the different usage and idle states of dockless shared bicycles. The findings reveal that the public transportation system has a similar influence on both the utilization and idleness of dockless shared bicycles, indicating that areas with a dense concentration of transportation services experience greater demand for shared bicycles as both origins and destinations. The influence of other factors on the usage and idleness of dockless shared bicycles varies significantly, resulting in either a shortage or surplus of these bicycles. Consequently, based on the findings regarding the use and idleness of dockless shared bicycles, we formulate a redistribution and zone-based management strategy for shared bicycles. This paper offers new insights into the spatiotemporal distribution and utilization of shared bicycles under the influence of different built environments, contributing to the further optimization of dockless shared bicycle resource allocation. Full article