Top Read Articles

Published in last 1 year |

In last 2 years |

In last 3 years |

All

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Relationship between drought and soil erosion based on the normalized differential water index (NDWI) and revised universal soil loss equation (RUSLE) model Muhammad RENDANA, Wan Mohd Razi IDRIS, Febrinasti ALIA, Supli Effendi RAHIM, Muhammad YAMIN, Muhammad IZZUDIN Regional Sustainability    2024, 5 (4): 100183-.   DOI: 10.1016/j.regsus.2024.100183 Abstract （45）   HTML （5）    PDF （1408KB）（18）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Climate change vulnerability assessment in the new urban planning process in Tanzania Issa NYASHILU, Robert KIUNSI, Alphonce KYESSI Regional Sustainability    2024, 5 (3): 100155-.   DOI: 10.1016/j.regsus.2024.100155 Abstract （41）   HTML （10）    PDF （330KB）（12）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Cost and benefit analysis of Climate-Smart Agriculture interventions in the dryland farming systems of northern Ghana Felix KPENEKUU, Philip ANTWI-AGYEI, Fred NIMOH, Andrew DOUGILL, Albert BANUNLE, Jonathan ATTA-AIDOO, Frank BAFFOUR-ATA, Thomas Peprah AGYEKUM, Godfred ADDAI, Lawrence GUODAAR Regional Sustainability    2025, 6 (1): 100196-.   DOI: 10.1016/j.regsus.2025.100196 Abstract （40）   HTML （9）    PDF （611KB）（11）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China SONG Boyi, ZHANG Shihang, LU Yongxing, GUO Hao, GUO Xing, WANG Mingming, ZHANG Yuanming, ZHOU Xiaobing, ZHUANG Weiwei Regional Sustainability    2024, 5 (3): 100162-.   DOI: 10.1016/j.regsus.2024.100162 Abstract （38）   HTML （6）    PDF （653KB）（12）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Preserving environmental quality of ecotourism sites through community participation in Purulia District of West Bengal, India Piyall CHATTERJEE, Soumyendra Kishore DATTA Regional Sustainability    2024, 5 (3): 100163-.   DOI: 10.1016/j.regsus.2024.100163 Abstract （38）   HTML （5）    PDF （440KB）（4）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Impact of geopolitical risk, GDP, inflation, interest rate, and trade openness on foreign direct investment: Evidence from five Southeast Asian countries Md. Shaddam HOSSAIN, Liton Chandra VOUMIK, Tahsin Tabassum AHMED, Mehnaz Binta ALAM, Zabin TASMIM Regional Sustainability    2024, 5 (4): 100177-.   DOI: 10.1016/j.regsus.2024.100177 Abstract （36）   HTML （2）    PDF （524KB）（12）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Employment and development levels in rural areas of the Russian Federation Guzel SALIMOVA, Gulnara NIGMATULLINA, Gamir HABIROV, Alisa ABLEEVA, Rasul GUSMANOV Regional Sustainability    2024, 5 (3): 100164-.   DOI: 10.1016/j.regsus.2024.100164 Abstract （35）   HTML （3）    PDF （547KB）（6）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Green transformation paths of resource-based cities in China from the configuration perspective GONG Qunxi Regional Sustainability    2024, 5 (3): 100158-.   DOI: 10.1016/j.regsus.2024.100158 Abstract （33）   HTML （6）    PDF （575KB）（9）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin, China JI Xiaomei, NIE Zhilei, WANG Kaiyong, XU Mingxian, FANG Yuhao Regional Sustainability    2024, 5 (3): 100159-.   DOI: 10.1016/j.regsus.2024.100159 Abstract （33）   HTML （4）    PDF （531KB）（15）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Assessing the impact of climate change on agricultural production in central Afghanistan Homayoon RAOUFI, Hamidreza JAFARI, Wakil Ahmad SARHADI, Esmail SALEHI Regional Sustainability    2024, 5 (3): 100156-.   DOI: 10.1016/j.regsus.2024.100156 Abstract （32）   HTML （2）    PDF （702KB）（5）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District, Ghana Frank BAFFOUR-ATA, Louisa BOAKYE, Moses Tilatob GADO, Ellen BOAKYE-YIADOM, Sylvia Cecilia MENSAH, Senyo Michael KWAKU KUMFO, Kofi Prempeh OSEI OWUSU, Emmanuel CARR, Emmanuel DZIKUNU, Patrick DAVIES Regional Sustainability    2024, 5 (3): 100157-.   DOI: 10.1016/j.regsus.2024.100157 Abstract （31）   HTML （3）    PDF （565KB）（5）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Encouraging circular economy and sustainable environmental practices by addressing waste management and biomass energy production Nazim Forid ISLAM, Bhoirob GOGOI, Rimon SAIKIA, Balal YOUSAF, Mahesh NARAYAN, Hemen SARMA Regional Sustainability    2024, 5 (4): 100174-.   DOI: 10.1016/j.regsus.2024.100174 Abstract （29）   HTML （5）    PDF （942KB）（5）       Knowledge map    Save The current linear economy assumes abundant, easily accessible, and cost-effective natural resources. However, this assumption is unsustainable, especially considering the world’s current trajectory exceeding the Earth’s ecological limits. In contrast, circular economy (CE) reduces wastes and improves resource efficiency, making them a more sustainable alternative to the dominant linear model. Biomass energy generated from agricultural leftovers, forestry wastes, and municipal trash provides a renewable substitute for fossil fuels. This reduces greenhouse gas emissions and improves energy security. Proper waste management, including trash reduction, recycling, and innovative waste-to-energy technology, reduces the burden on landfills and incineration and creates renewable energy from materials that would otherwise go to waste. Although integrating these techniques is consistent with the CE’s resource efficiency and waste minimization principles, it requires addressing environmental, technical, and socioeconomic challenges. Given the pressing global issues, transitioning to a CE and implementing sustainable environmental practices are crucial to mitigate the current waste management crisis. The aim of this study is to emphasize the viability of biomass as a source of sustainable energy, the necessity of comprehensive strategies that prioritize ecological sustainability, community involvement, and innovation to achieve a circular principle based future, and the potential obstacles to the implementation of sustainable environmental practices. This study will aid in implementing CE practices to accomplish the Sustainable Development Goals (SDGs) by reducing greenhouse gas emissions and landfill loads. Beyond environmental benefits, it can also bring economic, social, and health improvements. Furthermore, this study will assist societies in addressing global issues, such as resource scarcity, pollution, and climate change, as well as transitioning to a more sustainable and resilient future. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Understanding factors affecting non-participants’ interest in community-supported agriculture Maula Fadhilata RAHMATIKA, Agus SUMAN, Wildan SYAFITRI, Sri MULJANINGSIH Regional Sustainability    2024, 5 (3): 100160-.   DOI: 10.1016/j.regsus.2024.100160 Abstract （28）   HTML （2）    PDF （409KB）（5）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

What are the underlying causes and dynamics of land use conflicts in metropolitan junction areas? A case study of the central Chengdu- Chongqing region in China TIAN Junfeng, WANG Binyan, QIU Cheng, WANG Shijun Regional Sustainability    2024, 5 (3): 100161-.   DOI: 10.1016/j.regsus.2024.100161 Abstract （28）   HTML （5）    PDF （2088KB）（5）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Sustainable smart city and Sustainable Development Goals (SDGs): A review Z. R. M. Abdullah KAISER, Apu DEB Regional Sustainability    2025, 6 (1): 100193-.   DOI: 10.1016/j.regsus.2025.100193 Abstract （28）   HTML （4）    PDF （3150KB）（33）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Green hydrogen production from wind energy in Far Eastern Federal District (FEFD), the Russian Federation Mihail DEMIDIONOV Regional Sustainability    2025, 6 (1): 100199-.   DOI: 10.1016/j.regsus.2025.100199 Abstract （27）   HTML （2）    PDF （1184KB）（5）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Evolutionary characteristics of export trade network in the Arctic region MA Xing, QIANG Wenli, WANG Shijin, LIU Jiayi, Arunima MALIK, LI Mengyu, WANG Xiang Regional Sustainability    2024, 5 (4): 100176-.   DOI: 10.1016/j.regsus.2024.100176 Abstract （26）   HTML （2）    PDF （2262KB）（4）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Qualitative assessment of the impact of waste littering and dumping on surface water quality in Nigeria Gloria FAYOMI, Ednah ONYARI, Onyeka NKWONTA Regional Sustainability    2025, 6 (1): 100194-.   DOI: 10.1016/j.regsus.2025.100194 Abstract （22）   HTML （3）    PDF （824KB）（8）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Driving factors of CO2 emissions in South American countries: An application of Seemingly Unrelated Regression model Gadir BAYRAMLI, Turan KARIMLI Regional Sustainability    2024, 5 (4): 100182-.   DOI: 10.1016/j.regsus.2024.100182 Abstract （16）   HTML （1）    PDF （795KB）（2）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

Select

Smart specialization, public authorities, and innovation intermediaries in developing regions Hugo PINTO, Manuel LARANJA, Elvira UYARRA Regional Sustainability    2024, 5 (4): 100175-.   DOI: 10.1016/j.regsus.2024.100175 Abstract （16）   HTML （2）    PDF （678KB）（6）       Knowledge map    Save 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. Table and Figures | Reference | Related Articles | Metrics | Comments（0）