In the recent significant rise in atmospheric CO₂, seawater’s continuous acidification is altering the marine environment’s chemical structure at an unprecedented rate. Due to its potential socioeconomic impact, this subject attracted significant research interest. This study used traditional linear regression, nonlinear regression random forest, and the BP neural network algorithm to establish a prediction model for surface seawater pH based on data of North Pacific sea surface temperature (SST), salinity (SSS), chlorophyll-a concentration (Chl-a), and pressure of carbon dioxide on the sea surface (pCO₂) from 1993 to 2018. According to existing research, three approaches were found to be highly accurate in reconstructing the surface seawater pH of the North Pacific. The highest-performing models were the linear regression model using SSS, Chl-a, and pCO₂, the random forest model using SST and pCO₂, and the BP neural network model using SST, SSS, Chl-a, and pCO₂. The BP neural network model outperformed the linear regression and random forest model when comparing the root mean square error and fitting coefficient of the three best models. In addition, the best BP neural network model had substantially higher seasonal applicability than the best linear regression and the best random forest model, with good fitting effects in all four seasons—spring, summer, autumn, and winter. The process of CO₂ exchange at the sea–air interface was the key factor affecting the pH of the surface seawater, which was found to be negatively correlated with pCO₂ and SST, and positively correlated with SSS and Chl-a. Using the best BP neural network model to reconstruct the surface seawater pH over the North Pacific, it was found that the pH exhibited significant temporal and spatiotemporal variation characteristics. The surface seawater pH value was greater in the winter than the summer, and the pH decline rate over the past 26 years averaged 0.0013 yr⁻¹, with a general decreasing tendency from the northwest to the southeast. The highest value was observed in the tropical western Pacific, while the lowest value was observed in the eastern equatorial region with upwelling, which is consistent with the findings of previous studies. Full article

Land degradation is one of the most important environmental problems worldwide, including in the Arabian Peninsula. In arid climatic conditions (i.e., high temperature, high evaporation, scanty rainfall and high salinity), anthropogenic factors (i.e., grazing, camping, infrastructure development, etc.) are the major causes of land degradation. Therefore, restoration of degraded lands is urgently needed to achieve sustainable development goals. Moreover, countries in the Arabian Peninsula are suffering from a lack of natural freshwater resources. Therefore, using halophytes could be an environmentally and economically viable option to overcome limited availability of fresh water by substituting the demand of portable water for irrigation as well as restoring salt-affected lands. Saline soils are common in the Arabian Peninsula, therefore, exploring the ecological and economic potential of halophytes and incorporating them in restoration projects could be a sustainable option. In this study, an attempt was made to document the uses of Arabian halophytes through a survey of the literature and prioritizing them based on their use value. Out of the 107 species studied, 4 species, namely Arthrocnemum macrostachyum (Moric.) K.Koch., Alhagi graecorum Boiss., Bassia muricata (L.) Asch. and Phragmites australis (Cav.) Trin. Ex Steud., were categorized as high priority followed by 36 species under moderate priority. However, when the priority and life form of species was considered for prioritization, three species, namely Alhagi graecorum, Arundo donax L. and Phragmites australis, ranked at the top in the priority list among perennials and Bassia muricata ranked at the top among annuals. This information could be useful for land restoration specialists to use appropriate halophyte species to achieve for different restoration objectives in salt-affected lands. However, there is a need to develop an active monitoring system that strictly concentrates on the recycling of plants that are used in phytoremediation. Full article

This investigation delves into the effectiveness of employing vegetable-based cutting fluids and nanoparticles in milling AZ31 magnesium alloy, as part of the pursuit of ecologically sustainable manufacturing practices. The study scrutinizes three different cutting environments: (i) dry cutting; (ii) minimum quantity lubrication (MQL) with rice bran oil as the base oil and turmeric oil as an additive; and (iii) MQL with rice bran oil as the base oil, and turmeric oil and kaolinite nanoparticles as additives. Fuzzy logic was implemented to develop the design of experiments and assess the impact of these cutting environments on carbon emissions, surface quality, and microhardness. Upon conducting an analysis of variance (ANOVA), it was determined that all the three input parameters (cutting environment, cutting speed, and feed) greatly affect carbon emissions. The third cutting environment (MQL + bio-oils + kaolinite) generated the lowest carbon emissions (average of 9.21 ppm) and surface roughness value (0.3 um). Confirmatory tests validated that the output parameters predicted using the multiobjective genetic algorithm aligned well with experimental values, thus affirming the algorithm’s robustness. Full article

Climate change has amplified the severity of droughts with potentially adverse impacts on agriculture in western Canada. This study assessed meteorological and agricultural drought in the Southern Saskatchewan River Basin (SSRB) using an array of drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), the Self-Calibrated Palmer Drought Severity Index (scPDSI), the Soil Moisture Deficit Index (SMDI), and the Evapotranspiration Deficit Index (ETDI). These indices were evaluated using multiple regional climate model (RCM) projections assuming 1.5, 2.0, and 3.0 °C thresholds of global warming. A modified Soil and Water Assessment Tool (SWAT-M) was used to simulate the soil water content (SWC), actual evapotranspiration (AET), and potential evapotranspiration. The results of a sensitivity analysis using the SUFI-2 method in SWAT-CUP showed that the model performed well with BIAS lower than 10% and NSE and R higher than 0.7, and the range of SWC output closely matched the observed SWC. According to the RCM projections, the annual precipitation increases for all three global temperature thresholds while the annual mean temperature increases at a greater rate than the rise in global mean temperature. The projected PDSI and the SPEI suggest that drought duration and severity will exceed historical values while SPI will remain largely unchanged. Furthermore, severe drought conditions (SMDI < 2.0) are more frequent under the 3.0 °C global temperature scenario. The mean ETDI was historically 0.58 while the projected value is 0.2, 0.1, and −0.2 for the first to third scenarios, respectively. Simulated values, spatial maps, and heat maps of SMDI and ETDI illustrated that Canesm2.CRCM5 projects the driest conditions among all the RCMs. Agricultural drought indices, which incorporate SWC data, show more significant effects than meteorological drought indices. The increasing dryness will potentially impact agricultural crop production, particularly under the third scenario (3 °C) in the SSRB. Full article

Energy transition has a prominent role in 21st-century urban agendas. Worldwide, cities pursue the local implementation of international, national and regional agendas aiming at a sustainable energy transition. Landscape integration, multifunctionality and community participation are three of the key concepts here. These concepts are interpreted differently across the different spatial levels. The object of this paper is to analyse the application of the three sustainability concepts at the regional, local and site levels for the city of Amsterdam, the Netherlands. The results show that the degree of implementation of the concepts depends on what factors are considered important at each spatial level. At the regional and local levels, landscape integration with regards to social factors such as finances and co-ownership drive successful implementation, thanks to the organisation of effective participatory processes. At the site level, landscape integration and multifunctionality with regards to spatial factors such as the ecological, recreational and historical landscape factors drive successful implementation through effective landscape design activities. However, the sustainability of the energy transition implementation process is affected by a lack of social-ecological systems thinking. Participation processes—if present—focus either on social or spatial factors but fail to interconnect them. The regional and local levels that currently demonstrate major abstraction and separation of social and spatial factors would benefit from effective exchange with the site level. At that scale, design activities are the arena to combine and reconcile social and spatial factors. Full article

Taking advantage of the growing production of organic waste for its conversion to waste-to-energy (WtE) also contributes to mitigating the problems associated with its final disposal, which is a global trend of increasing application. This work presents an innovative approach for the identification and prioritization of WtE alternatives available from the use of food waste (FW) present in the municipal solid waste (MSW) of a Colombian municipality with source separation and selective collection: (i) a systematic literature review, which allows one to identify WtE alternatives; (ii) the prospective MIC-MAC method (Matrice d’Impacts Croisés Multiplication Appliqués à un Classement) allowed the selection of criteria and sub criteria; (iii) the analytical hierarchical process (AHP) and the technique of order of preference by similarity to the ideal solution (TOPSIS), allowed a ranking of selected alternatives considering the technical, environmental, and social aspects. The WtE technologies identified were anaerobic digestion, gasification, incineration, biogas recovery from landfills, and pyrolysis; this last was excluded due to its greater application potential with substrates such as plastic waste. The six sub-criteria identified and prioritized were social acceptability (36%), greenhouse gas emissions mitigated (16.17%), MSW reduction (15.83%), energy production (13.80%), technological maturity (12.95%), and electrical energy conversion efficiency (5.25%), with the decreasing order of preferences of anaerobic digestion (78.2%), gasification (47.5%), incineration (27.4%), and biogas recovery from landfills (6.6%); the latter was the least desirable alternative (lower social acceptance and CO₂ tons mitigated in relation to the other options). The innovative nature of this study is the identification and consideration of the comprehensive management of this type of waste of a large number of criteria (120 environmental, 52 social, and 59 technical) and the validation of the results through a sensitivity analysis, which allowed us to confirm for this study, that anaerobic digestion is the most favorable technology for the treatment and energy use of FW. Full article

The Paris Agreement recognized the significant role of forests in climate change mitigating and adapting. It also emphasized the importance of the Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanism as a vital tool for achieving the goal of limiting global warming to 1.5 °C above pre-industrial levels. This study aims to assess the REDD+ readiness of Bhutan, India, Myanmar, and Nepal in preparation for effectively implementing REDD+ at the national level. A total of 57 indicators across five categories were used to evaluate readiness: overall readiness, technical readiness, institutional readiness, financing readiness, and strategy and safeguard readiness. The indicator-based questionnaire was administered to government officials, NGOs, private sectors, and academics. The results showed that Nepal was slightly more advanced in overall readiness, owing in part to the longer readiness period of the World Bank-supported Terai Arc ER-P. India scored highly in technical readiness and has several sub-national programmes for REDD+ implementation. Bhutan had strong ratings for strategy and safeguard readiness but lower scores for institutional and financing readiness. Myanmar had consistent ratings across readiness areas, but a lower score for technical readiness. However, political and governance situations pose significant challenges to the effective implementation of REDD+ in Myanmar. Full article

Several kinds of research from both global and local perspectives have discussed social entrepreneurship and inclusive development. Accordingly, this article aims to highlight the key contributors (authors, institutions, countries, journals) and knowledge structure (co-authorship analysis and cooccurrence-of-keyword analysis) of this research domain. Utilizing the bibliographic data of 300 articles extracted from the Scopus database, we primarily employed Biblioshiny software, resulting in 673 authors from 69 different countries and 496 different institutions. Furthermore, the yearly publication of the 300 documents rose from 1 in 1996 to 24 in 2022, with an average age of 6.08 years and a citation rate of 13.79 yearly. Remarkably, the number of publications on this subject accelerated in 2014. According to the study’s findings, the most productive country in line with research publishing is the USA. The most productive institution has been recognized as the Amrita School of Engineering. The most active author is reported to be Kadol N. The most prolific journal is Entrepreneurship and Regional Development. In addition to this, the top three most frequent terms are ‘social development’, ‘economic development’ and ‘entrepreneur. ‘Social entrepreneurship’, ‘social and economic effects’, ‘sustainable development’ and ‘social development’ are the latest keywords in this field that predict future trends. Taken collectively, this review is an expedient resource for gaining a thorough grasp of the state of the art and prospective routes for future research. Full article

Marine development and eco-environmental management have received increasing attention over the past two decades, however, no effective universal approach has been established to achieve marine development without destroying marine ecosystems. This study discusses the integrated ocean management (IOM) for meeting the sustainable development goal (SDG14) through the following four aspects: the marine eco-environment foundation, market mechanism, management support, and space consideration. Our findings highlight how to enhance the coastal and marine areas management efficiency to achieve ecological and socioeconomic values for sustainable development through the benign interaction of marine ecosystem and socioeconomic systems. The presented case study examines the IOM framework for achieving SDG14 in the Bohai Sea. Furthermore, content analysis and semi-structured interviews were conducted. The framework is theoretically and empirically explored in light of the Bohai Sea’s management, focusing on the role of the government and incentive. Further, issues preventing effective IOM are highlighted and a framework for optimizing the IOM implementation to better balance the interests of various industries is suggested. When implementing the IOM framework, each region should fully play to its own advantages and push forward with some focused aspects first. The long-term effect of the Bohai Sea’s management may need time to be verified, and the role of the market mechanism and multi-interest coordination mechanism need more special attention for the Bohai Sea in the future. Full article

Arable land is the natural resource of food production, plays a key role in safe guarding people’s livelihood, maintaining social stability, and ecological balance. In the context of the great challenge of rapid loss of arable land and rapid growth of food demand due to rapid socio-economic development, scientific forecasting of arable land demand and supply, can clarify the conservation pressure of regional arable land, provide a reference for formulating effective arable land policies, and ensuring regional food security and sustainable development. Therefore, with the help of system dynamics model and Gray-Markov model, this study predicts and analyzes the balance of arable land supply and demand in China, and reached the following conclusions. (1) During the projection period, with the continuous development of living standards and agricultural technology, both per capita food demand and food production show an upward trend. However, the combined effects of changes in diet structure and grain yields on changes in arable land demand are smaller than those brought about by population changes. Therefore, the trend of arable land demand is similar to that of population change, and the arable land demand in China reaches a peak of 112.78 million hm² in 2026. (2) The amount of arable land possession is always greater than the amount of arable land replenishment, and the arable land supply area shows a continuous decreasing trend, and the arable land supply in China is 127.16 million hm² in 2035. (3) China’s supply holdings are all able to meet the demand of China’s arable land, but combined with existing studies, it is insufficient to meet the demand of crop rotation fallow between 2023 and 2030, which is not conducive to sustainable development. In the future, arable land protection policies should be comprehensively improved and strictly implemented to ensure national food security and achieve sustainable use of arable land. Full article

International student mobility is an important dimension of internationalisation in higher education, involving a high percentage of students in certain subject areas. A literature review revealed the absence of studies deepening our knowledge of this group of students in specific contexts and stages. Thus, this survey study was undertaken to gather data on the profiles and academic and professional careers of a sample of students. Specific differences in their intrinsic and extrinsic motives for their choice of degree subject were found. A total of 314 students from 14 Master’s degree programmes at two public universities responded, 42.4% of whom were international students. The data showed differences in reasons for choice between international and Spanish-native students when enroling in a Master’s degree programme. The foreign students had diverse motivations, in many cases related to each other, with no predominance of extrinsic or intrinsic motives. This suggests that, when students are deciding to study abroad, universities should consider the importance of offering guidance to these students at the stage prior to accessing the Master’s degree. Full article

This research was conducted to forecast the uniaxial compressive strength (UCS) of rocks via the random forest, artificial neural network, Gaussian process regression, support vector machine, K-nearest neighbor, adaptive neuro-fuzzy inference system, simple regression, and multiple linear regression approaches. For this purpose, geo-mechanical and petrographic characteristics of sedimentary rocks in southern Iran were measured. The effect of petrography on geo-mechanical characteristics was assessed. The carbonate and sandstone samples were classified as mudstone to grainstone and calc-litharenite, respectively. Due to the shallow depth of the studied mines and the low amount of quartz minerals in the samples, the rock bursting phenomenon does not occur in these mines. To develop UCS predictor models, porosity, point load index, water absorption, P-wave velocity, and density were considered as inputs. Using variance accounted for, mean absolute percentage error, root-mean-square-error, determination coefficient (R²), and performance index (PI), the efficiency of the methods was evaluated. Analysis of model criteria using multiple linear regression allowed for the development of a user-friendly equation, which proved to have adequate accuracy. All intelligent methods (with R² > 90%) had excellent accuracy for estimating UCS. The percentage difference of the average of all six intelligent methods with the measured value was equal to +0.28%. By comparing the methods, the accuracy of the support vector machine with radial basis function in predicting UCS was (R² = 0.99 and PI = 1.92) and outperformed all the other methods investigated. Full article

Soil is a composite material of great interest to civil engineers. When the quality of such composite soils is poor, ground improvement techniques must be adopted to withstand the design load of superstructure. Existing soil stabilizers include lime and cement; however, their environmental safety and sustainable use during stabilization have been receiving increasing attention in recent years. This study investigated the use of granite sand (GS) and calcium lignosulphonate (CLS) as sustainable stabilizers that could be blended with clayey soils. The considered dosages of GS were 30%, 40% and 50%, and those of the CLS were 0.25%, 0.5%, 1% and 1.5%. Direct shear and consolidation tests were performed on the GS–CLS blended soil samples that were cured for 7 and 14 days. The amended stabilizers improved the shear parameters and consolidation characteristics at an optimum dosage of 30% GS and 0.5% CLS. Maximum improvements of 84% and 163% were observed in the cohesion and angles of internal friction, respectively. A significant change was also observed in the consolidation characteristics, making them practically applicable. The soil hydraulic conductivity was reduced by 14%, and the coefficient of consolidation increased by 203% for 30% GS and 05% CLS. Carbon footprint analyses were performed on the soil composition that would be best-suited for a typical homogenous earthen dam section. The results showed that the use of GS and CLS together reduced the carbon emissions by 6.57 and 7.7 times, compared to traditional stabilizers, such as cement and lime. Full article

As the largest carbon emitter in the world, China aims to reach its peak carbon emissions goal by the year 2030, while the construction industry makes a significant contribution to carbon emissions, directly affecting the country’s commitment to meet its target. The present paper investigates the dynamic characteristics of carbon emissions released by China’s construction industry under single- and multiple-scenario settings with altering economic growth rates, optimizing energy structures, adjusting industrial structures, and modifying carbon emission policy factors. The research results show that the total carbon emissions generally present a steady increase from the year 2000 and will reach 12,880.40 million tons (MT) by 2030 under a scenario without any intervention. Indirect carbon emissions released from associated industries account for over 96% of the total carbon emissions, while direct carbon emissions make a minor contribution to the total. Single and comprehensive scenarios have positive effects on reducing emissions; it was also observed that only under energy structure scenario III and comprehensive scenario III could carbon emissions released from the construction sector reach a peak value by 2030. The effects of emissions reductions as a result of single policies can be presented in the following order: energy structure, economic growth, carbon emissions policy factor, and industrial structure. All of the emissions reduction effects of multiple scenarios are superior to the single scenarios. The research results provide a basis and guidance for policymakers to adopt the correct steps to fulfill China’s aim of achieving peak carbon emissions by the projected date. Full article

An emergy analysis is used to assess the sustainability of urban agglomerations’ eco-economic systems, which are generally measured by emergy–value sustainability indicators using a combination of several system indicators. However, this assessment approach is not applicable to economically developed high-density urban agglomerations. The application of the traditional entropy value evaluation method needs to be expanded to further strengthen the sustainability of the complex eco-economic–social relationships in megacity cluster regions. In this study, taking the Guangdong–Hong Kong–Macau Greater Bay Area (GBA) as a case study, we study a new evaluation method for evaluating the sustainable development capacity of cities. This method is based on the entropy power method and is used to construct the evaluation system of all indicators of the social–economic–natural subsystems of the eco-economic system, and it couples the development degree with the coordination degree. (1) This study shows that the new method is applicable for the sustainability assessment of high-density megacity clusters and is more accurate and comprehensive. The sustainability rankings are provided for Zhaoqing, Jiangmen, Huizhou, Guangzhou, Macau, Foshan, Zhongshan, Dongguan, Zhuhai, and Shenzhen. Hong Kong is the most representative, with a high sustainability index, but has the lowest level of coordination and a clear incoherence within the system. (2) The current emergy structure of the GBA city cluster is extremely unreasonable. The GBA city cluster is a resource-consuming city with a common characteristic of a low level of coordinated development. Although urban clusters have some potential in terms of renewable emergy and resources, the recycling rate of waste is low, and the consumption rate of nonrenewable resources is high. The effective use of land resources has become an important factor in the bottlenecking of sustainable development, and all other cities face such problems, except Zhaoqing, Jiangmen, and Huizhou. (3) The GBA city cluster can be divided into three categories according to the new method. Category 1 mainly includes Hong Kong, Shenzhen, Dongguan, and Zhuhai, which have coordinated development degrees ranging between 0.0 and 0.135 and the highest emergy density (ED) values but are extremely dependent on external emergy. They have high levels of emergy use per capita (EUC), high living standards, and high quality of life. The effective use of land resources severely restricts sustainable economic development, resulting in extreme ecological and environmental carrying pressure. Category 2 includes Guangzhou, Macau, Foshan, and Zhongshan, whose coordinated development degrees range from 0.143 to 0.179. The sustainable development capacity of these cities is at the middle level amongst the whole GBA. Their main emergy characteristics are emergy flow and subsystem evaluation indices that are between category 1 and category 3, but each has its own characteristics. The category 3 cities include Zhaoqing, Jiangmen, and Huizhou, whose coordinated development degrees are between 0.192 and 0.369. These cities are characterized by relatively low ED and EUC values, living standards, and quality, but their land resources have certain potential. These cities have a high emergy self-sufficiency rate (ESR) and natural environmental support capacity, but their environmental loading ratio (ELR) is still much higher than the national average. In terms of the economic development and innovation development levels, these cities are ranked as category 1 > category 2 > category 3. In terms of the ecological and environmental conditions and blue–green space protection, these cities are ranked as category 1 < category 2 < category 3. The results of this study can provide cities in the GBA with more scientific and consistent directions for the coordinated development of their ecological–economic–social systems to provide sustainable development decision-making services for megacity cluster systems. Full article