Motivated by a significant impact of price volatility on food security and economic stability in Cameroon, this study aims to understand the factors influencing agricultural product price volatility (APPV) and formulate effective policies for mitigating its negative impact and promoting sustainable economic growth. Specifically, this research used the autoregressive distributed lag-error correction model (ARDL-ECM) to analyse the impact of agricultural productivity, agricultural product imports, population, temperature variation, gross domestic product (GDP) per capita, and government expenditure on APPV based on the annual data from 2000 to 2021. The ARDL-ECM estimation results revealed that agricultural productivity (β=4.901), agricultural product imports (β=1.012), population (β=13.635), and GDP per capita (β=2.794) were positively related to APPV, while temperature variation (β= -0.990) and government expenditure (β= -8.585) were negatively related to APPV in the long term. However, temperature variation had a positive relationship with APPV in the short term. Moreover, the Granger causality test showed that there were bidirectional causality of APPV with agricultural productivity and agricultural product imports, and unidirectional causality of APPV with population, temperature variation, GDP per capita, and government expenditure. The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research, improving access to agricultural inputs, strengthening farmer capacities, implementing climate adaptation measures, and enhancing rural infrastructure. These policies can reduce APPV, improve food security, and promote inclusive economic growth in Cameroon.

Historically, geopolitical risk (GPR) has posed significant challenges to international economic, social, and political frameworks. This study investigated how internal GPR in the selected five Southeast Asian countries (Indonesia, South Korea, Malaysia, the Philippines, and Thailand) influences foreign direct investment (FDI) during 1996-2019. The stationarity of the data was assessed using the Augmented Dickey-Fuller (ADF) unit root test, which shows that the data became stationary after the first difference. The Kao, Pedroni, and Westerlund cointegration tests were employed to examine long-term cointegration among the selected variables (FDI, GPR index (GPRI), gross domestic product (GDP), inflation, interest rate, and trade openness (TOP)). The results indicated that these variables have a long-term cointegration. Consequently, regression analysis using the Pooled Ordinary Least Squares (OLS) regression, fixed effect, random effect, Arellano-Bond dynamic panel-data estimation, and system generalized moment method (GMM) revealed that GPRI and TOP negatively impacted FDI in the selected five Southeast Asian countries. At the same time, GDP, inflation, and interest rate positively influenced FDI in these countries. Because FDI is crucial to shaping a country’s macroeconomic structure, this study recommends that governments and central banks of the selected five Southeast Asian countries should implement policies and strategies to encourage foreign investments.

Poverty remains one of the most pressing global challenges of this era, affecting millions of people across both developing and developed countries. The poverty alleviation resettlement (PAR) is a policy with Chinese characteristics for eradicating poverty. By integrating the Maslow’s Hierarchy of Needs and Amartya Sen’s Capability Approach, this study developed a theoretical framework to analyze the factors influencing the well-being of poverty alleviation migrants (PAMs). A telephone survey conducted between July and August 2022 in Hubei Province, Guizhou Province, Shaanxi Province, and Chongqing Municipality of China yielded 259 valid questionnaires. Using the partial least squares-structural equation modeling (PLS-SEM), this study revealed that financial accessibility, health level, living conditions, and social networks significantly enhanced the well-being of PAMs, with living conditions having the strongest impact on the well-being of PAMs. Furthermore, the factors affecting well-being varied across age groups. Social networks played a more significant role in the elderly group, whereas health level had a greater impact on the young and middle-aged group. These findings deepen the understanding of the PAR and its effects on the well-being of PAMs, offering valuable insights for policy-makers and practitioners to refine poverty alleviation strategies and enhance social welfare.

The intersection of economic development, energy dynamics, environmental policy, and environmental sustainability presents complex challenges for European Union (EU) countries. This study investigated the impact of environmental taxes, hydroelectricity consumption, economic globalization, and gross domestic product (GDP) on the load capacity factor (LCF) in the 10 EU member countries (including Austria, Finland, France, Germany, Italy, Poland, Portugal, Slovakia, Spain, and Sweden) using data from 1995 to 2020. To ensure the reliability and validity of the data, this study applied several advanced econometric tests, including the Pesaran and Yamagata slope heterogeneity test, Pesaran cross-sectional dependence (CSD) test, second-generation unit root test, and Westerlund cointegration test. The data showed important statistical issues such as slope heterogeneity across panels, CSD, mixed-order unit root structures, and long-run associations between variables. To address these issues, we applied an augmented mean group (AMG) model as the main regression approach, and used the pooled mean group-autoregressive distributed lag (PMG-ARDL) method to check the robustness. Specifically, the AMG results indicate that a 1.000% rise in hydroelectricity consumption results in a 0.048% rise in the LCF, while a 1.000% increase in environmental taxes leads to a 0.175% increase in the LCF. Contrary to this, a 1.000% increase in economic globalization results in a 0.370% decrease in the LCF, and a 1.000% increase in GDP leads to a 0.850% decrease in the LCF. Environmental taxes have a more beneficial impact on the environment, and GDP has the most detrimental effect. The findings provide empirical evidence on the role of environmental taxes, hydroelectricity consumption, economic globalization, and GDP in driving the LCF. Additionally, the findings provide valuable information to policy-makers, academicians, and stakeholders shaping energy and environmental policies in the 10 EU member countries.

The social progress index (SPI) measures social and environmental performance beyond traditional economic indicators, providing transparent and actionable insights into the true condition of societies. This study investigates the interdependencies among SPI components and their impact on country-level sustainability performance. Using a Bayesian Belief Network (BBN) approach, the analysis explores the interdependencies among 12 SPI components (including advanced education, basic education, environmental quality, freedom and choice, health, housing, inclusive society, information and communications, nutrition and medical care, rights and voice, safety, and water and sanitation) and their collective influence on sustainability performance. Data from the Sustainable Development Report and SPI datasets, covering 162 countries (including Australia, China, United Arab Emirates, United Kingdom, United States, and so on), were used to assess the relative importance of each SPI component. The key findings indicate that advanced education, inclusive society, and freedom and choice make substantial contributions to high sustainability performance, whereas deficiencies in nutrition and medical care, water and sanitation, and freedom and choice are associated with poor sustainability performance. The results reveal that sustainability performance is shaped by a network of interlinked SPI components, with education and inclusion emerging as key levers for progress. The study emphasizes that targeted improvements in specific SPI components can significantly enhance a country’s overall sustainability performance. Rather than visualizing countries’ progress through composite indicator-based heat maps, this study explores the interdependencies among SPI components and their role in sustainability performance at the global level. The study underscores the importance of a multidimensional policy approach that addresses social and environmental factors to enhance sustainability. The findings contribute to a deeper understanding of how SPI components interact and shape sustainable development.

Growing climate change concerns have intensified the focus on agribusiness sustainability, driving an urgent energy transition to improve production efficiency and mitigate environmental harm. The complex interplay between energy efficiency and energy consumption highlights the essential role of strategic energy policies in ensuring sustainable development. This study used the Double-Log regression model with bootstrap resampling to examine the rebound effect in the energy transition of agribusiness focusing on five Latin American countries including Brazil, Argentina, Uruguay, Colombia, and Mexico based on the agricultural sector data during 2010-2022. The findings revealed that the rebound effect significantly influences energy transition, with varying degrees of impact across agricultural sectors. This study identified partial rebound effect across all five countries, with elasticity coefficient varying from 9.63% (Colombia’s coffee sector) to 89.12% (Brazil’s livestock sector). In Brazil’s sugarcane sector, non-renewable energy, agricultural employment, and irrigation efficiency were identified as key factors influencing energy consumption, while in livestock sector, energy consumption was affected by CH₄ emissions, income and well-being of farmers, water consumption, and water conservation practices. In Mexico’s livestock sector, CH₄ emissions, non-renewable energy, and water conservation practices were the key factors affecting energy consumption. In Argentina’s sugarcane sector, pesticides, NO₂ emissions, renewable energy, and agricultural employment were the key factors affecting energy consumption, while renewable energy, income and well-being of farmers, and water consumption were the key factors affecting energy consumption in livestock sector. In Uruguay’s livestock sector, non-renewable energy, income and well-being of farmers, and irrigation efficiency were the key factors affecting energy consumption. In Colombia’ coffee sector, NO₂ emissions and irrigation efficiency were identified as key factors influencing energy consumption. Finally, this study reinforces the importance of aligning energy transition with Sustainable Development Goals (SDGs), ensuring that energy efficiency gains do not inadvertently increase energy consumption or environmental degradation.

Water resources are vital for all living beings and should be managed properly to ensure the safety and well-being of humankind. Surface water bodies are constantly faced with serious contamination risks generated primarily by human activities and urbanization. The problem of waste littering and dumping in developing countries like Nigeria is increasingly affecting environmental resources such as air and water. Several studies have revealed alarming levels of heavy metals that exceed the World Health Organization (WHO) standards. Plastic waste represents a substantial portion of litter, affecting water quality. Pollution results in the depletion of aquatic ecosystems and an increase in water-related diseases. This review aims to assess the impact of waste littering and dumping on surface water quality in Nigeria. In this review, the findings of various studies on surface water bodies in Nigeria, particularly those under the influence of urbanization and waste disposal, were compiled. This review compared numerous physical and chemical parameters like pH, dissolved oxygen, and heavy metals, and microbiological properties such as total coliforms. The water quality index (WQI) was also computed in these studies to ascertain the suitability of the water samples for human consumption. Review results showed that numerous water bodies in Nigeria have significantly diverse water quality levels, with some samples meeting or exceeding the WHO guidelines for microbiological, chemical, and physical characteristics. Notably, levels of heavy metals, turbidity, and pH frequently exceeded permissible limits, pointing to contamination from agricultural and industrial sources. The WQI results for multiple locations revealed that the majority of surface water sources were classified as “bad” to “very bad”, meaning they were unfit for human consumption. The results emphasized the critical need for immediate action to prevent further harm and deterioration of surface water bodies in Nigeria. Recommendations include strengthening waste management policies, promoting recycling initiatives, fostering collaborations among stakeholders, developing littering penalties and enforcing fines to curb the challenge, and raising educational awareness from the primary level. This review emphasizes the need for proactive measures to protect the environment and surface water quality in Nigeria.

Mangrove ecosystems support biodiversity, protect coastal areas, and provide sustainable livelihoods. However, they face significant threats from deforestation and unsustainable land use practices. This study examines the viability of the payments for ecosystem services (PES) programs in promoting sustainable mangrove tourism in Tongke-Tongke Village, Sinjai District, South Sulawesi Province, Indonesia. We collected data through household surveys, semi-structured stakeholder interviews, and tourist questionnaires to evaluate the economic value of mangrove tourism and tourists’ willingness to pay (WTP) for conservation. Analytical methods included quantitative descriptive analysis, thematic analysis, travel cost analysis, and contingent valuation method. The results indicated strong community support, with 70.00% of respondents acknowledging sustainable mangrove tourism’s economic, environmental, and cultural benefits. Economic estimates revealed that mangrove tourism generated 943.00 USD/(hm²•a), while tourists’ WTP for conservation ranged from 0.21 to 0.56 USD/(person•month), contributing approximately 11.39 USD/(hm²•a). Despite challenges such as inadequate infrastructure, socioeconomic disparities, and land privatization, this study advocates for integrating the PES programs, enhancing governance frameworks, and fostering local community engagement to ensure equitable benefit distribution and maximize the potential of mangrove tourism. These strategies aim to bolster conservation efforts, improve local livelihoods, and strengthen the resilience of mangrove ecosystems.

As urbanization accelerates, rural regions in China are experiencing transformative changes. This study examines the transformation mechanism of modern agricultural villages in the loess hilly and gully regions, using Zhaojiawa Village in Shannxi Province of China as a case study. In this study, we explored the village’s evolution amid China’s rural revitalization efforts, highlighting the transition from a traditional agricultural village to a modern agricultural village in the context of rapid urbanization. This study employed actor-network theory (ANT) to investigate the complex interactions among diverse actors that drive rural transformation. ANT interlinks spatial relationships with intricate social networks. We utilized Google Earth remote sensing images in 2015 and 2021 and interview data to construct ANT. Three key dimensions of rural transformation are identified: economic structure transformation, social relationship reorganization, and spatial layout reconstruction. The transformation mechanism in Zhaojiawa Village is underpinned by a network of diverse actors, both human and non-human, aligned around two pivotal stages of agricultural village development (i.e., construction stage and development stage). In the initial construction stage, the Suide County government led a complex actor network to enhance rural living and production spaces. In the development stage, the village committee emerged as a central actor, with increased participation from villagers and external enterprises, facilitating the creation of a multifunctional space. The evolving goals and roles of these key actors contributed to the reconfiguration of the actor network, promoting rural transformation. These insights are applicable to other ecologically vulnerable and economically challenged rural areas in the loess hilly and gully regions, suggesting that collaboration among stakeholders can effectively facilitate the transition to specialized and integrated industries, thereby fostering rural revitalization.

The rapid acceleration of global warming and intensifying human activities have exacerbated the fragility and climate sensitivity of ecosystems worldwide, particularly in arid regions. Vegetation, a key component of ecosystems, is critical in enhancing the ecological environment. The Ertix River Basin (ERB) is a transboundary watershed that spans multiple countries, mostly in arid regions. However, research on the fractional vegetation coverage (FVC) and its driving factors in the ERB remains limited. Investigating the spatiotemporal changes in the FVC and its relationship with various factors in the ERB can offer scientific support for optimizing regional vegetation restoration policies and promoting the coordinated development of human-environment interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) MYD13Q1 V6 data were obtained via the Google Earth Engine platform, and methods including the pixel dichotomy method, Theil-Sen median trend analysis, and Mann‒Kendall test were employed to examine the spatiotemporal dynamics of the FVC in the ERB from 2003 to 2023, with future trend forecast using the Hurst index. The impacts of natural and socioeconomic factors on the FVC were evaluated through the partial least squares-structural equation model (PLS-SEM). The results indicated that the FVC in the ERB showed a slight degradation trend with an average annual decrease of 0.046% during 2003-2023, with significant changes occurring in 2004, 2010, and 2019. Spatially, 53.380% of the study area was degraded, and the change in the FVC increased gradually from southeast to northwest. The FVC in 63.000% of the study area was highly stable and displayed long-term persistence; and the direct impact of natural factors (path coefficient of 0.617) on the FVC was significantly higher than that of socioeconomic factors (0.167). Among the natural factors, precipitation (0.999) was the most significant. This study reveals the significant impacts of natural and socioeconomic factors on vegetation dynamics in arid regions, and provides a scientific basis for transnational ecological conservation.

Agricultural production (especially intensive rice production) is a primary income source for over 2.0×10⁷ people in the Vietnamese Mekong River Delta. However, adverse climate change impacts, socio-economic change, and high dependence on farm inputs for intensive production constrain the longer-term sustainability of rice systems. Government and agribusiness actors are encouraging more farmers to grow non-rice crops and supporting the upscaling of alternative crops to paddy rice. We used a qualitative approach to investigate the value chain characteristics, as well as constraints and opportunities of alternative crops via two case studies (baby corn and honeydew melon) in An Giang and Hau Giang provinces, Vietnam. Data collection involved focus group discussions with local farmers and interviews with farmers and industry experts. Thematic analysis was used to compile the findings, and the results were validated with local government staff. The baby corn value chain featured on-going and stable market demand (including value-addition) and better vertical coordination (e.g., written contracts and financial support). The honeydew melon value chain featured positive relationships between farmers and traders despite less-developed vertical coordination. There are opportunities for value chain engagement through product quality certification, value-addition, and accessing high-value domestic and export markets. However, farmers require crop-specific and generic support from private and public sectors. Increased labour requirements and limited access to finance and credit limit value chain participation. Upscaling and marketing alternative crops can enhance farmer profitability and support non-farming agricultural business establishment, economic growth, and community development. Efficient value chains will be critical to ensure the adoption of alternative crops and development of crop-specific agribusiness models. These findings can inform policy-makers and change facilitators in designing targeted interventions to support the adoption of alternative crops in the study area as well as in Vietnam and globally.

As the impact of climate change intensifies, climate migration (climate change-induced migration) has become a pressing global issue that requires effective adaptation strategies to lessen its effects. Therefore, this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor. We collected sample data through face-to-face interviews in Khorramabad City, Iran from February to May in 2023. Using the Structural Equation Modeling (SEM), we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration. The findings showed that while climate change adaptation strategies can boost community resilience, their success is closely tied to levels of food insecurity. About 78.72% of the surveyed households experienced certain levels of food insecurity, increasing the risk of displacement due to climate-related disasters. Climate change adaptation strategies including economic strategies, irrigation management strategies, organic-oriented strategies, sustainable development-oriented strategies, and crop variety management strategies played a significant role in reducing climate migration. Moreover, we found that climate change adaptation strategies not only impact food security, but also shape migration decisions. This research underscores the importance of an integrated approach that links climate change adaptation strategies, climate migration, and food insecurity. This study emphasizes the importance of food security for formulating sustainable adaptation strategies.

There is a gradual increase in the proportion of renewable energy sources. Green hydrogen has the potential to become one of the major energy carriers in the future. The Russian Federation, in partnership with countries in the Asia-Pacific region and especially China, has the potential to play a significant role in green hydrogen market. This study assessed the potential of developing green hydrogen energy based on wind power in the Far Eastern Federal District (FEFD) of the Russian Federation. Empirical wind speed data were collected from 20 meteorological stations in 4 regions (Sakhalinskaya Oblast’, Primorskiy Krai, Khabarovskiy Krai, and Amurskaya Oblast’) of the FEFD. The Weibull distribution was used to predict the potential of green hydrogen production. Five different methods (Empirical Method of Justus (EMJ), Empirical Method of Lysen (EML), Maximum Likelihood Method (MLE), Power Density Method (PDM), and Median and Quartiles Method (MQM)) were used to determine the parameters (scape factor and scale factor) of the Weibull distribution. We calculated the total electricity generation potential based on the technical specifications of the three wind turbines: Senvion 6150 onshore, H165-4.0 MW, and Vestas V150-4.2 MW. The results showed that Vladivostok, Pogibi, Ilyinskiy, Yuzhno-Kuril’sk, Severo-Kuril’sk, Kholmsk, and Okha stations had the higher potential of green hydrogen production, of which Vladivostok exhibited the highest potential of green hydrogen production using the wind turbine of H165-4.0 MW, up to 2.56×10⁵ kg/a. In terms of economic analysis, the levelized cost of hydrogen (LCOH) values of lower than 4.00 USD/kg were obtained at Yuzhno-Kuril’sk, Ilyinskiy, Pogibi, and Vladivostok stations using the wind turbine of H165-4.0 MW, with the values of 3.54, 3.50, 3.24, and 2.55 USD/kg, respectively. This study concluded that the FEFD possesses significant potential in the production of green hydrogen and, with appropriate investment, has the potential to become a significant hub for green hydrogen trading in the Asia-Pacific region.

Desertification poses a significant ecological threat to global sustainability, notably within arid regions such as the Tarim Basin surrounding the extensive Taklimakan Desert in Northwest China. This study used the Google Earth Engine (GEE) platform and Random Forest (RF) to analyze multi-temporal Landsat images to reveal desertification dynamics in the Tarim Basin spanning from 1990 to 2020. The results showed that land use types of the Tarim Basin were classified into three types: artificial oases, natural oases, and desertified land. To robustly quantify the spatiotemporal dynamics of land use, we introduced the Desertification Change Index (DCI), a novel metric specifically designed to measure the transformation sensitivity of land use types. Our analysis demonstrated that from 1990 to 2020, artificial oases showed a continuous increasing trend, while desertified land decreased significantly. Natural oases decreased during 1990-2000, then continued to grow, and showed a decreasing trend again after 2015. Moreover, natural oases have mainly been converted into desertified land and artificial oases. Artificial oases were mainly converted into natural oases, and most of desertified land was converted into natural oases. Regions with significant oasis expansion (DCI=2) were mostly concentrated within the influence radius of artificial oases. In contrast, regions with significant oasis degradation (DCI= -2) were generally farther from artificial oases. Finally, this study found that the changes in land use types of the Tarim Basin are mainly driven by human activities, which play a dual role—mitigating desertification by controlling oasis expansion and exacerbating desertification through unsustainable resource utilization. Ultimately, this research provides essential insights for policy-makers and land managers aiming to devise adaptive and sustainable desertification control measures in the Tarim Basin and similarly arid regions globally.

Carbon emissions have become a critical concern in the global effort to combat climate change, with each country or region contributing differently based on its economic structures, energy sources, and industrial activities. The factors influencing carbon emissions vary across countries and sectors. This study examined the factors influencing CO₂ emissions in the 7 South American countries including Argentina, Brazil, Chile, Colombia, Ecuador, Peru, and Venezuela. We used the Seemingly Unrelated Regression (SUR) model to analyse the relationship of CO₂ emissions with gross domestic product (GDP), renewable energy use, urbanization, industrialization, international tourism, agricultural productivity, and forest area based on data from 2000 to 2022. According to the SUR model, we found that GDP and industrialization had a moderate positive effect on CO₂ emissions, whereas renewable energy use had a moderate negative effect on CO₂ emissions. International tourism generally had a positive impact on CO₂ emissions, while forest area tended to decrease CO₂ emissions. Different variables had different effects on CO₂ emissions in the 7 South American countries. In Argentina and Venezuela, GDP, international tourism, and agricultural productivity significantly affected CO₂ emissions. In Colombia, GDP and international tourism had a negative impact on CO₂ emissions. In Brazil, CO₂ emissions were primarily driven by GDP, while in Chile, Ecuador, and Peru, international tourism had a negative effect on CO₂ emissions. Overall, this study highlights the importance of country-specific strategies for reducing CO₂ emissions and emphasizes the varying roles of these driving factors in shaping environmental quality in the 7 South American countries.

Road transport plays a crucial role in facilitating mobility and the movement of goods, particularly in the Extended Bangkok Metropolitan Region (EBMR), Thailand. This area is undergoing rapid industrialization and urbanization, resulting in significant energy consumption and greenhouse gas (GHG) emissions. This study examined the relationships among individual socioeconomic factors, travel characteristics, and energy consumption characteristics and their impacts on GHG emissions from road transport. The path analysis technique was applied to identify the key driving factors and their causal relationships. The data were collected through 1600 questionnaire surveys with road drivers in representative areas of the EBMR from December 2022 to May 2023. The results revealed that individual socioeconomic factors significantly influenced GHG emissions from road transport. Among the drivers, factors such as income, age, education, and driving experience indirectly influenced travel characteristics and energy consumption characteristics, impacting GHG emissions. Similarly, individual socioeconomic factors affected the travel characteristics of tourists and personal travelers. Driving experience was a crucial factor for public road transport and freight vehicle drivers, influencing travel characteristics and contributing to GHG emissions. These findings highlight the importance of key policy recommendations, such as promoting the adoption of electric vehicles, optimizing public transport, incentivizing low-emission tourism, and modernizing freight transport with clean technologies, to enhance efficiency, reduce emissions, and support regional sustainability. This study provides policy-makers with insights into the key factors influencing GHG emissions across different driving factors, revealing how individual socioeconomic factors impact travel characteristics and energy consumption characteristics. The findings will inform the development of targeted emission reduction strategies and sustainable transport policies.

The rapid urbanization and increasing challenges are faced by cities globally, including climate change, population growth, and resource constraints. Sustainable smart city (also referred to as “smart sustainable city”) can offer innovative solutions by integrating advanced technologies to build smarter, greener, and more livable urban environments with significant benefits. Using the Web of Science (WoS) database, this study examined: (i) the mainstream approaches and current research trends in the literature of sustainable smart city; (ii) the extent to which the research of sustainable smart city aligns with Sustainable Development Goals (SDGs); (iii) the current topics and collaboration patterns in sustainable smart city research; and (iv) the potential opportunities for future research on the sustainable smart city field. The findings indicated that research on sustainable smart city began in 2010 and gained significant momentum in 2013, with China leading, followed by Italy and Spain. Moreover, 59.00% of the selected publications on the research of sustainable smart city focus on SDG 11 (Sustainable Cities and Communities). Bibliometric analysis outcome revealed that artificial intelligence (AI), big data, machine learning, and deep learning are emerging research fields. The terms smart city, smart cities, and sustainability emerged as the top three co-occurring keywords with the highest link strength, followed by frequently co-occurring keywords such as AI, innovation, big data, urban governance, resilience, machine learning, and Internet of Things (IoT). The clustering results indicated that current studies explored the theoretical foundation, challenges, and future prospects of sustainable smart city, with an emphasis on sustainability. To further support urban sustainability and the attainment of SDGs, the future research of sustainable smart city should explore the application and implications of AI and big data on urban development including cybersecurity and governance challenges.

Climate change poses substantial challenges to agricultural productivity and sustainability, particularly in Mediterranean and Sub-Saharan Africa regions. Local smallholder farmers’ adaptation strategies to climate change are crucial for mitigating these impacts. Therefore, this study investigated the socioeconomic factors influencing smallholder farmers’ perceptions and adaptation strategies to climate change in four countries (Morocco, Egypt, Italy, and Senegal) of Mediterranean and Sub-Saharan Africa regions using a binary logistic regression (BLR) model. The results indicated that educational level, farming experience, agricultural income, farm size, participation in agricultural workshops, and training in Good Agricultural Practices (GAPs) significantly impacted smallholder farmers’ perceptions and adaptation strategies to climate change (such as smallholder farmers adopting drought-tolerant crops). Higher educational level was linked to the greater possibility of smallholder farmers adopting drought-tolerant crops in Italy and Egypt, while gaps in rural education limited the possibility of smallholder farmers adopting drought-tolerant crops in Morocco and Senegal. Farming experience and agricultural income also enhanced the possibility of smallholder farmers adopting drought-tolerant crops, with notable variations across countries due to systemic barriers such as limited infrastructure in Senegal. Larger farm size and participation in agricultural workshops further improved the possibility of smallholder farmers adopting drought-tolerant crops, particularly in Morocco and Egypt. The findings highlighted the importance of tailored interventions and policy measures to support smallholder farmers in effectively responding to the challenges of climate change under diverse agricultural contexts. By understanding the specific needs and circumstances of smallholder farmers in these countries, policymakers can develop more effective adaptation strategies to enhance agricultural resilience and sustainability under the context of climate change.

The use of renewable energy is an important way to achieve sustainable agricultural and economic development. However, there are differences in access to renewable energy between the Global North and Global South. This study utilised an autoregressive distributed lag-error correction model and the data spanning from 1991 to 2021 to comparatively analyse the dynamic relationship among renewable energy consumption, the value of agricultural production, gross domestic product (GDP), economic diversification index, urban population, the total water extraction for agricultural withdrawal, and trade balance in the Netherlands and South Africa. In the short run, renewable energy consumption was increased by the value of agricultural production but decreased by GDP in South Africa. In the long run, renewable energy consumption and GDP increased the value of agricultural production, while the value of agricultural production also increased GDP in South Africa. However, in the Netherlands, there was no short- and long-run relationship between renewable energy consumption and agricultural and economic development. The results revealed that there was a short- and long-run relationship in South Africa. Moreover, in the Netherlands, the adjustment speed was -1.46 for renewable energy consumption with an error correction of 0.68 a (8.22 months). In South Africa, the adjustment speed was -1.28 for renewable energy consumption with an error correction of 0.78 a (9.38 months). Therefore, compared to South Africa, renewable energy consumption in the Netherlands takes less time to return to balance after a shock. These findings signify different trajectories on sectoral and economic transition initiatives spurred using renewable energy between the Netherlands and South Africa. Policy relating to initiatives such as “agro-energy communities” in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.

As the world grapples with increasing environmental challenges, innovative technologies are essential for promoting sustainability and accountability. This study examined the impact of environmental performance indices (EPIs) on the growth and investment trends of blockchain-based sustainability-focused companies in 15 countries (Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Italy, Norway, Poland, Sweden, Spain, Switzerland, the United Kingdom, and the United States) from Europe and America during 2010-2022. This study used the negative binomial regression model to assess the relationship between EPIs and blockchain-based sustainability-focused companies based on the data from the CrunchBase and EarthData. Results indicated that in ecosystem vitality, national terrestrial biome protection efforts were negatively correlated the formation of blockchain-based sustainability-focused companies, while global terrestrial biome protection efforts and marine protected areas had a positive impact on the formation of these companies and the number of funding rounds. In environmental health, PM_2.5 exposure had a positive impact on the number of funding rounds. Conversely, pollutants such as sulfur dioxide (SO₂) and ocean plastics deterred the formation of blockchain-based sustainability-focused companies and reduced the number of funding rounds. In climate change performance, adjusted emission growth rate for carbon dioxide (CO₂), adjusted emission growth rate for F-gases, and adjusted emission growth rate for black carbon had a significantly positive impact on the formation of blockchain-based sustainability-focused companies. Conversely, adjusted emission growth rate for Nitrous Oxide (N₂O) and projected greenhouse gas emissions in 2050 negatively affected the formation of these companies. These findings highlight the dual role of EPIs as driving factors and barriers in the development and investment of blockchain-based sustainability-focused companies in countries from Europe and America.

Land use conflicts (LUCs), as a spatial manifestation of the conflicts in the human-land relationships, have a profound impact on regional sustainable development. For China’s metropolitan junction areas (MJAs), the existence of “administrative district economies” has made the issue of LUCs more prominent. Based on a case study of the central Chengdu-Chongqing region, we conducted an exploratory spatial data analysis of the evolutionary process of regional LUCs. Furthermore, structural equation modeling was utilized to analyze the dynamic mechanism of LUCs in MJAs, with a particular emphasis on exploring the influences of administrative boundary. The results showed that from 2010 to 2020, LUCs in the central Chengdu-Chongqing region continued to worsen, and the spatial process conflict and spatial structure conflict indices increased by more than 30.0%. The intensification of LUCs in the central Chengdu-Chongqing region from 2010 to 2020 was mainly the result of the deterioration of conflicts in evaluation units with low conflict levels. LUCs in China’s metropolitan areas generally presented a circular gradient distribution, weakening from the core to the periphery, but there were some strong isolated conflict zones in the outer regions. LUCs in China’s MJAs were the result of interactions among multiple factors, e.g., natural environment, socio-economic development, policy and institutional processes, and administrative boundary effects. Administrative boundary affected the flow of socio-economic elements, changing the supply-and-demand competition of stakeholders for land resources, consequently exerting an indirect influence on LUCs. This study advances the theory of the dynamic mechanism of LUCs, and provides theoretical support for the governance of these conflicts in transboundary areas.

There is a need for more focus in understanding the economic benefits of Climate-Smart Agriculture (CSA) interventions, particularly in sub-Saharan Africa, where extreme climate events are significantly affecting agriculture and rural livelihoods. This study used the Net Present Value (NPV), Internal Rate of Return (IRR), Benefit-Cost Ratio (BCR), and payback period to evaluate the economic viability of the adopted CSA interventions in the three villages (Doggoh, Jeffiri, and Wulling) of the dryland farming systems of northern Ghana, where CSA interventions were mostly practiced. Data were collected from 161 farm households by the questionnaire survey. The results showed that CSA interventions including livestock-crop integration, mixed cropping, crop rotation, nutrient integration, and tie ridging enhanced crop yield and the household income of smallholder farmers. The five CSA interventions selected by smallholders were in the following order of priority: livestock-crop integration (BCR=2.87), mixed cropping (BCR=2.54), crop rotation (BCR=2.24), nutrient integration (BCR=1.98), and tie ridging (BCR=1.42). Results further showed that livestock-crop integration was the most profitable CSA intervention even under a pessimistic assumption with a long payback period of 5.00 a. Moreover, this study indicated that the implementation of CSA interventions, on average, was relatively profitable and had a nominal financial risk for smallholder farmers. Understanding the economic viability of CSA interventions will help in decision-making process toward selecting the right CSA interventions for resilience development.

Urbanization in small- and medium-sized cities has often been overlooked in urban studies. Research on urbanization has predominantly focused on large metropolitan cities; however, urbanization in small- and medium-sized cities also contributes to the acceleration of urban sprawl. Urban growth boundary (UGB) is an ecological approach designed to limit urban development. This study aimed to analyze environmental protection priority zones by combining ecological quality and sensitivity indices to identify the areas suitable for UGB implementation. Tegal City and its surrounding areas (including Tegal and Brebes regencies) of Indonesia were selected as the study area. The ecological quality index was calculated using the normalized difference vegetation index, humidity index, land surface temperature, and normalized difference bare soil index. These indices were subsequently subjected to principal component analysis (PCA) to extract orthogonal factors, which were summed to derive the final index value. In parallel, we mapped and evaluated ecological sensitivity based on spatial planning policies and regulations. The results revealed that ecological quality in Tegal and Brebes regencies was predominantly categorized as good and very good ecological quality, whereas Tegal City exhibited moderate and poor ecological quality. Additionally, over 45.00% of the area in Tegal and Brebes regencies demonstrated very high ecological sensitivity. Consequently, more than 50.00% of the area in Tegal and Brebes regencies, along with 27.00% of Tegal City, were classified as ecological constraint zone, making them potential regions for UGB development. The UGB is expected to curtail urban expansion, promote compact city planning, and preserve ecosystem services to achieve urban sustainability. This study implies that planning small- and medium-sized cities is important to prevent urban sprawl and maintain environmental health. Designing UGB to limit urban expansion should be enhanced by better knowledge about its ecological functions in supporting urban sustainability.

Human well-being and livelihoods depend on natural ecosystem services (ESs). Following the increment of population, ESs have been deteriorated over time. Ultimately, land use/land cover (LULC) changes have a profound impact on the change of ecosystem. The primary goal of this study is to determine the impacts of LULC changes on ecosystem service values (ESVs) in the upper Gilgel Abbay watershed, Ethiopia. Changes in LULC types were studied using three Landsat images representing 1986, 2003, and 2021. The Landsat images were classified using a supervised image classification technique in Earth Resources Data Analysis System (ERDAS) Imagine 2014. We classified ESs in this study into four categories (including provisioning, regulating, supporting, and cultural services) based on global ES classification scheme. The adjusted ESV coefficient benefit approach was employed to measure the impacts of LULC changes on ESVs. Five LULC types were identified in this study, including cultivated land, forest, shrubland, grassland, and water body. The result revealed that the area of cultivated land accounted for 64.50%, 71.50%, and 61.50% of the total area in 1986, 2003, and 2021, respectively. The percentage of the total area covered by forest was 9.50%, 5.90%, and 14.80% in 1986, 2003, and 2021, respectively. Result revealed that the total ESV decreased from 7.42×10⁷ to 6.44×10⁷ USD between 1986 and 2003. This is due to the expansion of cultivated land at the expense of forest and shrubland. However, the total ESV increased from 6.44×10⁷ to 7.76×10⁷ USD during 2003-2021, because of the increment of forest and shrubland. The expansion of cultivated land and the reductions of forest and shrubland reduced most individual ESs during 1986-2003. Nevertheless, the increase in forest and shrubland at the expense of cultivated land enhanced many ESs during 2003-2021. Therefore, the findings suggest that appropriate land use practices should be scaled-up to sustainably maintain ESs.

Green transformation is an unavoidable choice for resource-based cities (RBCs) that face resource depletion and environmental pollution. Existing research has focused primarily on specific RBCs, making it challenging to apply green transformation strategies universally across cities. The fuzzy set qualitative comparative analysis (fsQCA) is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome. Thus, to address this gap, in this study, we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China. By incorporating the element of time, this study explored the dynamic evolution of solutions in 2013, 2016, and 2019. The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency (GTE), and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs. Green transformation paths of RBCs exhibit the same destination through different paths. Additionally, the combination of system environment elements and system structure elements is both complementary and alternative. Differences in RBCs have led to various factor combinations and development paths, but there are some similarities in the key elements of the factor combinations at different stages. Economic environment, government support, and technological innovation are key factors that universally enhance the GTE in RBCs. These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.

Green spaces in urban and suburban areas play a significant role in helping settlements adapt to climate change. The design, quantity, quality, and location of green spaces influence their ability to provide benefits to people and enhance the quality of life. Private green spaces, if adequately managed, can enhance the environmental quality. This study, based on a questionnaire survey and the Motivation/Attitude-Driven Behaviour (MADB) model, investigated how the attitudes and behaviours of residents shape private green spaces in 12 settlements of the 4 city regions (Cluj region, Nitra region, Kecskemét region, and Győr region) in 3 Central European countries (Hungary, Slovakia, and Romania). The results showed that beautiful natural environment, abundance of green spaces, beautiful settlement and streetscape, and village atmosphere were mentioned most often, along with good quality of life, with a mention rate of over 70.00% in the four city regions. Convenience also played a significant role in the management of green spaces, showing that convenience factors (less work, less waste, and cheaper management) more important for those who live in settlements nearer to the cities. The importance of biodiversity and ecology was positively correlated with socio-economic status such as education and financial situation. However, the importance of the utility of green spaces was less prevalent among original villagers and settlers. Moreover, we found that the percentage of green spaces of settlers is slightly higher than that of original villagers. The results of factor analysis revealed that socio-economic status can influence respondents’ attitudes towards green spaces. It suggests to increase ecological awareness of residents, especially for new settlers, and promote good management techniques for green spaces. This study can improve the awareness of urban planners about the importance of green spaces in suburban areas.

Indigenous people around the Kerinci Seblat National Park (KSNP), Indonesia, have a high dependence on forest resources as their main source of livelihood. This study addressed the vulnerability of Rejang indigenous people around the KSNP to climate change. The popular livelihood vulnerability index (LVI) model was adapted by adding and modifying subcomponents suitable for the study area. Primary data were collected through household surveys in two communities: Embong and Topos. In total, 146 samples were selected for this study using stratified random sampling. The results showed that Embong was more vulnerable to climate change than Topos. Embong exhibited a higher level of vulnerability to the effects of socio-demographic profile, social network, health, and natural disasters and climate variability, whereas Topos was more vulnerable to livelihood strategy, food, and water. Furthermore, Embong was more exposed to natural disasters and climate variability than Topos, but it demonstrated higher adaptive capacity and lower sensitivity than Topos. Nevertheless, socio-demographic profile influenced adaptive capacity in both communities. Sensitivity was influenced most by health in Embong, and sensitivity was influenced most by food in Topos. Although the vulnerability levels were not high in the two communities, several subcomponents must be specifically considered. Overall, this study can help the government make informed decisions to enhance adaptive capacity of the KSNP to climate change.

The economic potential induced by environmental changes in the Arctic region garnered substantial interest, which positions Arctic trade as a crucial indicator in forecasting the impacts of climate change on the global economy. Nevertheless, attention devoted to the evolving dynamics of trade in the Arctic region remains scarce. In this study, we constructed export trade network in the Arctic region (including Denmark, Finland, Sweden, Norway, Iceland, the Canadian Arctic, the Russian Arctic, Alaska State of the USA, and Greenland) from 1990 to 2019 and analyzed its topology and evolutionary characteristics through complex network theory. We used a structural entropy index based on the distribution of the number of trading partners and the degree of trade concentration to assess export diversity, while we also utilized a revealed comparative advantage index to evaluate product export competitiveness using the share of trade volume of each type of product. The results indicate that the total export trade in the Arctic region increased by 53.4% during 1990-2019, with the most significant growth observed in the exports of chemical products and mineral fuels. The increasing complexity of trade network in the Arctic region resulted in the region’s export destinations no longer being concentrated on a few major countries and regions. The proportion of exports from the Arctic region to Europe decreased by 13.5%, while the proportion of exports from the Arctic region to Asia and North America increased by 6.8% and 3.1%, respectively. The Arctic region exhibited clear distinctions in the range of flows of different products, and its export trade was becoming increasingly diversified. Although differences in comparative advantages between products within individual countries or regions have narrowed, substantial gaps persist. The findings of this study can enhance the comprehensive understanding of the significance and function of Arctic trade activities within the global economy, providing a scientific basis for addressing the associated challenges and opportunities in the context of climate change.

The importance of valuing environmental resources, especially in ecotourism sites, has become increasingly important over the last two decades. Ecotourism is now considered as an important source of livelihood of local stakeholders in backward regions. Therefore, the preservation of ecotourism sites through community participation seems very important to maintain continued flow of tourists. This study aimed at recognizing the importance of community participation for the preservation of ecotourism sites. For this, this study executed a survey based on non-probability sampling in two ecotourism sites (Garpanchkot and Baranti) covering 100 respondents in Purulia District, West Bengal of India. The central issue of this study was to assess the tendency of community participation for the conservation of ecotourism sites and find the optimum condition for offering participatory labour time. This study showed that the participation of young people is high, and the majority of respondents are aware of the importance in protecting ecotourism sites. Because respondents were too poor to offer money, the contingent valuation method (CVM) was used to elicit their willingness to pay (WTP) participatory labour time for the conservation of ecotourism sites. Respondents’ age, income, education level, caste, and their perceived environmental quality had significant relationship with their WTP participatory labour time by applying the ordinary least square (OLS) model. It was found that the mean WTP participatory labour time of each respondent in a month is approximately 3.64 h. The significance of this study is that community participation can improve the sense of belonging, trust, and credibility of ecotourism sites, making them more appreciative of the value and protection of these sites.

The Langat River Basin in Malaysia is vulnerable to soil erosion risks because of its exposure to intensive land use activities and its topography, which primarily consists of steep slopes and mountainous areas. Furthermore, climate change frequently exposes this basin to drought, which negatively affects soil and water conservation. However, recent studies have rarely shown how soil reacts to drought, such as soil erosion. Therefore, the purpose of this study is to evaluate the relationship between drought and soil erosion in the Langat River Basin. We analyzed drought indices using Landsat 8 satellite images in November 2021, and created the normalized differential water index (NDWI) via Landsat 8 data to produce a drought map. We used the revised universal soil loss equation (RUSLE) model to predict soil erosion. We verified an association between the NDWI and soil erosion data using a correlation analysis. The results revealed that the southern and northern regions of the study area experienced drought events. We predicted an average annual soil erosion of approximately 58.11 t/(hm²•a). Analysis of the association between the NDWI and soil erosion revealed a strong positive correlation, with a Pearson correlation coefficient of 0.86. We assumed that the slope length and steepness factor was the primary contributor to soil erosion in the study area. As a result, these findings can help authorities plan effective measures to reduce the impacts of drought and soil erosion in the future.

The development of agro-industrial complex is important for ensuring national food security and national health. The development of rural areas is subject to the development of agriculture and local infrastructure, as well as the availability of various services. This study selected 15 indicators in 2021 to analyze the employment and development levels in rural areas of 71 regions of the Russian Federation using the analytical grouping method. The results indicated that 20 regions (Group 1) had the highest percentage of rural population (33.10%). The percentage of population engaged in agriculture had the highest value (12.40%) in 31 regions (Group 2). Moreover, 20 regions (Group 3) had the highest investments in fixed assets at the expense of municipal budget (11.80 USD/person). Increasing the investments in fixed assets carried out from the budget of the municipality can improve the employment level in rural areas. Then, we used cluster analysis to divide 14 regions of the Volga Federal District in the Russian Federation into 3 clusters. Cluster 1 covered Kirov Region and Republic of Mari El; Cluster 2 included Ulyanovsk Region, Saratov Region, Nizhny Novgorod Region, Perm Territory, Orenburg Region, Chuvash Region, and Republic of Mordovia; and Cluster 3 contained Republic of Tatarstan, Samara Region, Udmurtian Republic, Penza Region, and Republic of Bashkortostan. Results indicated that the 2 regions of Cluster 1 need to increase the availability of resources and natural gas and improve the investment attractiveness of rural areas. The 7 regions of Cluster 2 needed to develop infrastructure, public services, and agricultural production. We found the highest employment level in rural areas, the largest investments in fixed assets at the expense of municipal budget, the largest residential building area per 10,000 persons, and the largest individual residential building area in the 5 regions of Cluster 3. This study makes it possible to draw up a comprehensive regional development program and proves the need for the development of rural areas, which is especially important for the sustainable development of the Russian Federation.

Community-supported agriculture (CSA) has emerged as a viable solution for addressing the agricultural challenges faced by countries like Indonesia. This study uses the well-established unified theory of acceptance and use of technology (UTAUT2) model to examine the interest in CSA of potential customers in Indonesia. A standardized questionnaire was distributed to 1200 respondents, and the data were analyzed using structural equation model-partial least square (SEM-PLS) in SmartPLS 4.0 software. The results capture potential CSA consumer interest and will help to improve CSA development strategies in Indonesia. The model explains 44.4% of customers’ intentions, and identifies performance expectancy as the decisive factor in customers’ willingness to participate in CSA. Performance expectancy (0.292), hedonic motivation (0.262), social influence (0.259), and facilitating conditions (0.086) positively influence customers’ interest in participating in a CSA program. The adoption of CSA programs by both farmers and customers could be increased by implementing regulations that provide tax incentives and subsidies, offering training on sustainable farming practices, facilitating the establishment of distribution channels, and establishing guidelines for fair price and quality standards. This study shows the high potential for the implementation of CSA in Indonesia. It could also be used as a foundation for the development of new policies regarding sustainable agriculture markets in Indonesia.

The tourism industry is economically very important. According to the World Travel Tourism Council, in 2019, the tourism industry accounted for a quarter of all new jobs created worldwide, 10.3% of all jobs, and 9.6×10¹² USD of the global gross domestic product. This study aimed to calculate the tourism efficiency index for different Latin American countries from 2010 to 2021 using data envelopment analysis, which analyzes the relationships between input variables (including the number of employees in the tourism industry and the number of hotel-type establishments) and output variables (including tourism expenditures in other countries and public social expenditures in recreation and culture per capita). Additionally, this study aimed to identify the countries with greater tourism development and the factors that may affect the development of the tourism industry through the stochastic frontier production function. The results of the tourism efficiency index for Central America (including Costa Rica, Dominica, El Salvador, Honduras, Mexico, and Panama) and South America (including Argentina, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, and Uruguay) exhibited different trends. However, after the global health crisis, the tourism industry recovered, showing new opportunities to promote sustainability. The results of the stochastic frontier production function demonstrated that countries with higher levels of inbound and outbound tourism, contribution of tourism to the economy, natural resources, and literacy rate exhibited more efficient tourism industry, whereas countries with higher pollution levels exhibited less efficient tourism industry. The findings of this study could allow us to formulate suitable public policies to promote tourism, maintain natural resources, and diversify these sectors with more inclusive programmes that can facilitate growth and benefit vulnerable communities.

The drylands of China cover approximately 6.6×10⁶ km² and are home to approximately 5.8×10⁸ people, providing important ecosystem services for human survival and development. However, dryland ecosystems are extremely fragile and sensitive to external environmental changes. Land use and land cover (LULC) changes significantly impact soil structure and function, thus affecting the soil multifunctionality (SMF). However, the effect of LULC changes on the SMF in the drylands of China has rarely been reported. In this study, we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center. We explored the drivers of the SMF changes under different LULC types (including forest, grassland, shrubland, and desert) and used structural equation modeling to explore the main driver of the SMF changes. The results showed that the SMF under the four LULC types decreased in the following descending order: forest, grassland, shrubland, and desert. The main driver of the SMF changes under different LULC types was mean annual temperature (MAT). In addition to MAT, pH in forest, soil moisture (SM) and soil biodiversity index in grassland, SM in shrubland, and aridity index in desert are crucial factors for the SMF changes. Therefore, the SMF in the drylands of China is regulated mainly by MAT and pH, and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes. The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Despite a growing body of literature on smart specialization, the role of public authorities and innovation intermediaries, particularly in developing regions, remains understudied. This research examines one of the first attempts to apply the smart specialization framework to the development of an innovation strategy outside Europe, specifically in the Pernambuco State, Brazil. We focus on two priority areas (clothing and high-tech automotive components) identified by the state government as key targets for pilot policy experimentation and use different methods, such as social network analysis and content analysis, to interview strategic innovation actors for studying the promotion of innovation and regional development in Pernambuco. Findings highlight how regional governance, collaboration, and trust are shaped by public authorities and innovation intermediaries. The study identifies three key challenges in implementing smart specialization strategy in developing regions: i.e., achieving effective decentralization, cultivating an innovation culture, and establishing participatory governance mechanisms. The public sector actors act as crucial knowledge brokers and policy intermediaries, facilitating the linkages and partnerships necessary to overcome these challenges.

Kuala Lumpur of Malaysia, as a tropical city, has experienced a notable decline in its critical urban green infrastructure (UGI) due to rapid urbanization and haphazard development. The decrease of UGI, especially natural forest and artificial forest, may reduce the diversity of ecosystem services and the ability of Kuala Lumpur to build resilience in the future. This study analyzed land use and land cover (LULC) and UGI changes in Kuala Lumpur based on Landsat satellite images in 1990, 2005, and 2021and employed the overall accuracy and Kappa coefficient to assess classification accuracy. LULC was categorized into six main types: natural forest, artificial forest, grassland, water body, bare ground, and built-up area. Satellite images in 1990, 2005, and 2021 showed the remarkable overall accuracy values of 91.06%, 96.67%, and 98.28%, respectively, along with the significant Kappa coefficient values of 0.8997, 0.9626, and 0.9512, respectively. Then, this study utilized Cellular Automata and Markov Chain model to analyze the transition of different LULC types during 1990-2005 and 1990-2021 and predict LULC types in 2050. The results showed that natural forest decreased from 15.22% to 8.20% and artificial forest reduced from 18.51% to 15.16% during 1990-2021. Reductions in natural forest and artificial forest led to alterations in urban surface water dynamics, increasing the risk of urban floods. However, grassland showed a significant increase from 7.80% to 24.30% during 1990-2021. Meanwhile, bare ground increased from 27.16% to 31.56% and built-up area increased from 30.45% to 39.90% during 1990-2005. In 2021, built-up area decreased to 35.10% and bare ground decreased to 13.08%, indicating a consistent dominance of built-up area in the central parts of Kuala Lumpur. This study highlights the importance of integrating past, current, and future LULC changes to improve urban ecosystem services in the city.

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment. Industrialization and urbanization promote social-economic development, but they also have generated a series of environmental and ecological issues in this basin. Previous researches have evaluated urban resilience at the national, regional, urban agglomeration, city, and prefecture levels, but not at the watershed level. To address this research gap and elevate the Yellow River Basin’s urban resilience level, we constructed an urban resilience evaluation index system from five dimensions: industrial resilience, social resilience, environmental resilience, technological resilience, and organizational resilience. The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin. The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010, 2015, and 2020. Furthermore, the grey correlation analysis method was utilized to explore the influencing factors of these differences. The results of this study are as follows: (1) the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010-2015, and significant spatial distribution differences were observed, with a higher resilience level in the eastern region and a low-medium resilience level in the western region; (2) the differences in urban resilience were noticeable, with industrial resilience and social resilience being relatively highly developed, whereas organizational resilience and environmental resilience were relatively weak; and (3) the correlation ranking of resilience influencing factors was as follows: science and technology level>administrative power>openness>market forces. This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

Smallholder farmers in Ahafo Ano North District, Ghana, face multiple climatic and non-climatic issues. This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions (FGDs) with 10 respondents. The Mann-Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022. The relative importance index (RII) value was used to rank the climatic and non-climatic factors perceived by respondents. The socioeconomic characteristics affecting smallholder farmers’ perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model. Results showed that mean annual rainfall decreased (P>0.05) but mean annual temperature significantly increased (P<0.05) from 2002 to 2022 in the district. The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature (RII=0.498), erratic rainfall (RII=0.485), and increased windstorms (RII=0.475). The critical non-climatic factors were high cost of farm inputs (RII=0.485), high cost of healthcare (RII=0.435), and poor condition of roads to farms (RII=0.415). Smallholder farmers’ perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics (P<0.05). This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors. Therefore, to enhance the resilience of smallholder farmers to climate change, it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

Afghanistan has faced extreme climatic crises such as drought, rising temperature, and scarce precipitation, and these crises will likely worsen in the future. Reduction in crop yield can affect food security in Afghanistan, where the majority of population and economy are completely dependent on agriculture. This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference (1990-2020) and future (2025-2100) periods. Climate data (1990-2020) were collected from four meteorological stations and three local organizations, and wheat yield data (1990-2020) were acquired from the United States Agriculture Department. Data during the reference period (1990-2020) were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG). Furthermore, the auto-regression model was used for trend analysis. The results showed that an increase in the average annual temperature of 2.15°C, 2.89°C, and 4.13°C will lead to a reduction in the wheat yield of 9.14%, 10.20%, and 12.00% under Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5 during the future period (2025-2100), respectively. Moreover, an increase in the annual maximum temperature of 1.79°C, 2.48°C, and 3.74°C also causes a significant reduction in the wheat yield of 2.60%, 3.60%, and 10.50% under RCP2.6, RCP4.5, and RCP8.5, respectively. Furthermore, an increase in the annual minimum temperature of 2.98°C, 2.23°C, and 4.30°C can result in an increase in the wheat yield of 6.50%, 4.80%, and 9.30% under RCP2.6, RCP4.5, and RCP8.5, respectively. According to the SDSM, the decrease of the average monthly precipitation of 4.34%, 4.10%, and 5.13% results in a decrease in the wheat yield of 2.60%, 2.36%, and 3.18% under RCP2.6, RCP4.5, and RCP8.5, respectively. This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.

Climate change vulnerability assessment is an essential tool for identifying regions that are most susceptible to the impacts of climate change and designing effective adaptation actions that can reduce vulnerability and enhance long-term resilience of these regions. This study explored a framework for climate change vulnerability assessment in the new urban planning process in Jangwani Ward, Tanzania. Specifically, taking flood as an example, this study highlighted the steps and methods for climate change vulnerability assessment in the new urban planning process. In the study area, 95 households were selected and interviewed through purposeful sampling. Additionally, 10 respondents (4 females and 6 males) were interviewed for Focus Group Discussion (FGD), and 3 respondents (1 female and 2 males) were selected for Key Informant Interviews (KII) at the Ministry of Lands, Housing and Human Settlements Development. This study indicated that climate change vulnerability assessment framework involves the assessment of climatic hazards, risk elements, and adaptive capacity, and the determination of vulnerability levels. The average hazard risk rating of flood was 2.3. Socioeconomic and livelihood activities and physical infrastructures both had the average risk element rating of 3.0, and ecosystems had the average risk element rating of 2.9. Adaptive capacity ratings of knowledge, technology, economy or finance, and institution were 1.6, 1.9, 1.4, and 2.2, respectively. The vulnerability levels of socioeconomic and livelihood activities and physical infrastructure were very high (4.0). Ecosystems had a high vulnerability level (3.8) to flood. The very high vulnerability level of socioeconomic and livelihood activities was driven by high exposure and sensitivity to risk elements and low adaptive capacity. The study recommends adoption of the new urban planning process including preparation, planning, implementation, and monitoring-evaluation-review phases that integrates climate change vulnerability assessment in all phases.