Urbanization Research Articles

Research and analysis of urban-rural residential carbon emissions in China

Residential carbon emissions are an important component of anthropogenic carbon emissions. a significant increase in residential carbon emissions has become a reality under the global urbanization process. In this context, this paper built a feature combination value model based on NPP-VIIRS nighttime light remote sensing data, and divided urban-rural areas through breakpoint analysis method and reference comparison method. Then, explored the characteristics and differences of residential carbon emissions and per capita residential carbon emissions in nine different levels of cities in 2019 from the perspective of urban-rural areas. The results indicate that the residential carbon emissions and per capita residential carbon emissions shows the spatial distribution characteristics of first tier cities>second tier cities>third tier cities. Among them, the residential carbon emissions in Beijing, Guangzhou, Nanjing, Taiyuan show a distribution pattern of urban>urban-rural fringe>rural. The residential carbon emissions in Shijiazhuang, Wuxi, Xiangyang, Zunyi, Huai’an show a distribution pattern of rural>urban-rural fringe>urban. The per capita residential carbon emissions of urban areas are relatively low, while the per capita residential carbon emissions of rural areas are relatively high, show a distribution pattern of rural>urban-rural fringe >urban. The results can help the Chinese government balance the needs of urban-rural development in different levels of cities, so as to formulate targeted carbon emission reduction policies and achieve low-carbon goals.

Beyond the Idyll: Unveiling the realities of risk perception and neighborhood influence on rural in-migrants in the COVID-19 Era in Dali, China

While the COVID-19 pandemic has intensified counter-urban migration trends globally, with rural areas often portrayed as ideal havens, the post-migration realities and risks faced by rural in-migrants remain understudied. Addressing this research gap, this research investigates the neighborhood factors influencing risk perceptions of rural in-migrants during the COVID-19 pandemic, focusing on four rural destinations in Dali, China. Using a mixed-method approach combining questionnaires, participatory mapping, and regression analysis, we surveyed 234 rural migrants. Our study incorporates objective measurements of neighborhood environments through Participatory GIS. Findings reveal that reduced life quality and economic income are the main perceived risks among rural in-migrants during the pandemic. Neighborhood factors significantly mitigating perceived risks include green spaces, accessible living services, government satisfaction, and strong local community networks. The study also identifies varying vulnerability levels among migrant groups, with migrant workers showing higher risk perceptions than entrepreneurs or unemployed individuals. This research addresses a critical gap in migration studies by examining post-relocation risks faced by rural in-migrants, especially during global crises. It provides empirical evidence on the role of neighborhood environments in mitigating migrants' risk perceptions, offering insights for enhancing rural community resilience. The findings contribute to our understanding of rural in-migration dynamics in the context of the COVID-19 pandemic and beyond, informing strategies for sustainable rural development and migrant integration in the face of future crises.

Fostering resilience and post-traumatic growth in overseas Chinese left-behind children: The role of autonomy, competence, and relatedness.

This study examines the impact of parental migration on the psychological well-being and development of left-behind children (LBCs) in Zhejiang, China, within the broader context of the country's rural transformations and urban migration. It investigates how intellectual and relational engagement (RE), autonomy (AUT), competence (COM), and relatedness (RES) contribute to resilience (REL) and post-traumatic growth (PTG) in these children, reflecting on the shift from viewing parental separation merely as a source of trauma to recognizing its potential to foster significant personal growth. Utilizing a cross-sectional design, the research was conducted in April and May 2023 with 1348 LBCs from a total sample of 4049 students inZhejiang. A two-step random, stratified, cluster-based sampling strategy was employed, and structural equation modeling was used to examine the hypothesized relationships among the constructs. The statistical analysis demonstrated significant positive effects of intellectual engagement (IE), AUT, COM, and RE on both REL and PTG (p<.05 for all). IE strongly correlated with AUT (r=.68, p<.001) and COM (r=.71, p<.001), enhancing REL and facilitating PTG. Additionally, the presence of secure and consistent relationships was identified as crucial for maintaining psychological well-being, with high correlation coefficients (r>.60) underscoring their importance. Notably, REL was found to moderate the relationships among RES, COM, and PTG, highlighting its critical role in the psychological adaptation of left-behind children. The study underscores the importance of nurturing intellectual and REs, AUT, and COM to enhance psychological REL and well-being among LBAs. These elements are crucial for supporting the mental health and developmental needs of children facing the challenges of parental migration. The findings advocate for targeted interventions that can address the unique needs of this vulnerable population, emphasizing the potential for growth and adaptation despite adversities.

Determinants of spatiotemporal changes of land use carbon emissions for counties in Shaanxi Province, China.

In China, urban sprawl and developed land expansion challenge the country's "carbon peak" and "carbon neutrality" goals. Counties as the basic governance units arecrucial for effective carbon reduction policies. This study examines land use carbon emissions (LUCE) in Shaanxi Province at the county level, essential for China's low-carbon strategy. Analyzing data from 107 counties between 2000 and 2020, we found that developed land, though increasing, is the primary carbon source with a slowing growth rate. The Conversion of Cropland to Forests and Grasslands national policy mitigated the impact on carbon absorption. Carbon emissions displayed positive autocorrelation and spatial heterogeneity, varying across the region. Using the Spatial Durbin Error Model, we linked county-level emissions to GDP per capita, population, urbanization rate, and research and development expenditure for direct and indirect influence. These factors correlate with fossil fuel use and high-quality industrial development. Promoting public transits and reducing private car use are vital for achieving local and regional low-carbon goals.

Measuring Changes in Temperature Rates due to Urban Expansion in Selected Municipalities of Baghdad using GIS Technology

The expansion of building blocks at the expense of agricultural land is one of the main problems causing climate change within the urban area of a city. The research came to determine these indicators, as a study was conducted on the expansion of the building blocks in three municipalities in the city of Baghdad for a period of four decades extended in the form of time cycles for the period (1981-2021) and using ArcMap GIS 10.7 technology. Then, the impact of this expansion on temperature rates was evaluated, as they are the most important climatic elements due to their significant effect on the rest of the elements. The results showed a clear, direct relationship between the increase in urban expansion rates and the corresponding rise in temperature rates, which results in urban heat islands. The results for the last time cycle showed high expansion rates for the municipalities of Al-Kadhimiya, Al-Shaala, and New Baghdad (62.2, 82.4, and 92.1), respectively, and were offset by high-temperature rates (25.2, 25.49, and 25.67) for the same municipalities, respectively, as the highest rates were recorded in the New Baghdad municipality, followed by the municipality of Al-Shaala, in second place, then the municipality of Al-Kadhimiya, with the lowest rates due to its location on the Tigris River.

Evaluation of urban low-carbon development efficiency: evidence from 30 cities in China

With the acceleration of global urbanization, the issues faced by urban development are becoming increasingly apparent. Some countries and regions have placed less emphasis on low-carbon emissions in the development process and prioritized urban development. However, blindly pursuing rapid urbanization has led to excessive urban carbon emissions, which outweigh the gains. Therefore, based on panel data from 30 cities in China from 2010 to 2019, this study combines the super-efficiency slacks-based measure (SBM) model and the Malmquist index, taking urban carbon emissions as undesirable outputs, to evaluate urban development efficiency. Through a multidimensional comparative analysis, this study reveals the developmental challenges encountered by various cities. The results show that: statically, the overall urbanization progress of these 30 cities is commendable, but significant fluctuations are observed in the development trend. The mean super-efficiency of cities in the eastern coastal areas is relatively high, whereas other regions exhibit instances of ineffective mean super-efficiency. Dynamically, there are few periods of efficiency improvement during 2010–2019, and there is an imbalance in the sources of efficiency improvement. Shanghai and Hangzhou exhibit the best continuous dynamic improvement status, with small fluctuations in dynamic efficiency, whereas Guiyang has the worst dynamic efficiency improvement status, indicating poor urban development. This study underscores the urgent need for a balanced approach to urban development that incorporates low-carbon initiatives to ensure sustainable progress and mitigate adverse environmental impacts.

Widespread introduced species dominate the urban tree assemblage on the endemic-rich tropical island of São Tomé.

The Afrotropics are experiencing some of the fastest urbanisation rates on the planet but the impact of city growth on their rich and unique biodiversity remains understudied, especially compared to natural baselines. Little is also known about how introduced species influence β-diversity in these contexts, and how patterns coincide with native ranges of species. Here we investigated how tree assemblages of the endemic-rich Afrotropical island of São Tomé differed between urban, rural and natural zones. These were primarily characterised by urban greenspaces, shade plantations, and old-growth forests, respectively. Based on 81 transects, we assessed biodiversity metrics of endemic, native and introduced species. Tree abundance and species richness were highest in the natural zone, where the composition was most different from the urban zone. The tree community of the rural zone was the most uneven and had the least variation among transects, representing the lowest β-diversity. The urban zone was dominated by introduced species (57.7%), while the natural zone hosted almost exclusively native species (93.3%), including many endemics (26.1%). The biogeographic realms that species originated from were particularly diverse in the urban zone, with few species from the Afrotropics. In contrast to native and endemic trees, introduced trees were clearly associated with urban and rural expansion, as they were much more abundant and species-rich in these zones than in the natural zone, facilitating biotic homogenisation. These findings highlight how urban and rural environments are affecting the native tree flora of São Tomé, and the need for conservation measures geared towards globally threatened and endemic tree species. Importantly, these require the protection of natural forests, despite the rising land demands for settlements and agriculture. Ultimately, such action to conserve endemic trees will contribute to global efforts to prevent further biodiversity declines.

Evaluation of Mortality Rate Disparities for Cardiac Arrest Between Urban and Rural Cohorts in the United States Using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Database.

Introduction The United States includes diverse geographic areas with distinct urban and rural settings. Urban areas served with higher health services and the rural regions with restricted facilities. This disparity results in higher rural mortality rates. Thus, the study uses the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database to assess the disparities in cardiac arrest mortality rates in urban versus rural areas. Methods This is a retrospective study to assess trends in overall mortality rates for urban versus rural areas in the United States between 1999 and 2020, using the CDC WONDER data for cardiac arrest (ICD-10 CODE I46), extracted on May 25, 2024. Urban/rural classification was based on the Metropolitan 2013 scheme. Statistical analysis was done via RStudio v.4.3.3 and included measures of central tendency, mortality rates per 100,000, and plotting of temporal trends. Results Between 1999 and 2020, the total number of deaths due to cardiac arrest in rural and urban areas was 103,115 and 262,505, respectively. Among the age groups, infants <1 year and elderly >85 years showed a high mortality rate in rural areas compared to urban areas.Gender analysis revealed both males (3.3 per 100,000) and females (3.52 per 100,000) had a high rural mortality rate, compared to urban rates of 1.51 and 1.54 per 100,000, respectively. Racial analysis showed that American Indian or Alaska Native and Asian or Pacific Islander populations had higher mortality in rural areas, with rates of 1.1 and 1.81 per 100,000, respectively, compared to the urban rates of 0.34 and 0.8 per 100,000. Conclusion Trends in mortality rate showed a general decline over time but the gap between urban and rural mortality persists, highlighting the need for continued efforts in rural areas.

A multiscale and multiperspective quantifying framework for spatial patterns and influencing mechanisms of geographical indications

Geographical indications (GIs) embody distinctive regional elements characterized by widespread spatial distribution, serving as vital agricultural intellectual properties and significant tourism assets. This case study introduces a multiscale and multi-perspective quantification framework for Shandong Province, focusing on spatial agglomeration, association, and heterogeneity. This approach quantitatively explores GIs’ spatial patterns and influencing mechanisms, analyzing both at the monomer and regional scales, considering static and dynamic perspectives. Leveraging methods such as kernel density analysis, Moran’s I index, Geary’s C index, Internet hot word analysis, and Geodetector, the coastal municipalities, prosperous urban areas, and zones with high-quality arable soils were identified as spatial agglomeration areas for GIs. The study revealed a strong correlation between the spatial distribution pattern of socioeconomic factors and GIs’ spatial density from a static perspective. However, diminished spatial autocorrelation was observed for GIs’ public perception from a dynamic standpoint, indicating a reduced influence of Internet connectivity. The spatial heterogeneity in GIs is determined by multiple interconnected factors, displaying an enhancement effect between any two influencing factors. Among the 15 influencing factors analyzed, urbanization rate; gross value of agricultural, forestry, animal husbandry, and fishery production; and per capita gross domestic product significantly contribute to spatial heterogeneity effects at both urbanization rate, gross value of agriculture, forestry, animal husbandry, fishery production, and per capita gross domestic product significantly contributed to spatial heterogeneity effects at regional and monomer scales. The results suggest that GIs are likely to flourish with regional economic growth. The analytical framework and quantification methods support exploring and sustainably utilizing GIs, improving output quality, and modernizing GIs’ production, ultimately contributing to regional agriculture’s high-quality and sustainable development.

Rural migrants in urban centers: Sources of vulnerability or agents of adaptive capacity?

Research on climate migration is increasingly analyzing not only the role of climate as a migration driver but also migration's adaptive and maladaptive outcomes. However, despite broad recognition that climate-related migration is overwhelmingly rural-to-urban, migration's effects on the vulnerability and adaptive capacity of the receiving urban destinations, many of which struggle to adapt to climate change, have received scant attention. To begin addressing this gap, this study examines how urban planners and policymakers in flood-prone Dar es Salaam, Tanzania's main migration destination and Africa's fastest-growing metropolis, perceive these effects. To this end, we utilize semi-structured interviews to examine three interrelated dimensions: migration's effects on flooding, the potential responses to ameliorate its adverse effects, and migrants' capabilities and the ways the city can harness those capabilities to reduce flooding.The results show that most planners and policymakers view migration as mainly exacerbating flooding yet also perceive migrants as possessing the potential to contribute to urban adaptation. This potential encompasses aspects recognizing migrants' agency, such as adaptation knowledge and planning skills, alongside ‘physical-economic’ elements linked with the use of migrants as labor for maintaining drainage channels and their contribution to enlarging the city's tax base, which may assist in funding flood-prevention infrastructure. However, the results also point to Dar es Salaam's inaction to exploit this potential, accompanied by a perceived lack of responsibility for advancing adaptation. We conclude by highlighting the importance of adopting a proactive approach to mapping and harnessing migrants' capabilities, ultimately contingent on cities' willingness to assume this responsibility.

Carbon emissions from global impervious surface expansion between 1985 and 2020

Impervious surface expansion (ISE) refers to the phenomenon that natural surfaces are covered by artificial materials, such as cement, asphalt, bricks, etc., usually due to human activities. Over recent decades, the rapid growth of the global population, economic development, and continuous urbanization have contributed to extensive ISE, which caused significant losses in terrestrial ecosystem carbon pools. A global assessment effort is lacking because of limited comprehensive data on carbon pools and uncertainties surrounding the extent of ISE. In this study, we aimed to quantify the carbon emissions resulting from global ISE between 1985 and 2020, following the method provided by the Intergovernmental Panel on Climate Change (IPCC) Guidelines. We first divided global land into 87 fine geographical zones by overlaying continental boundary information with an ecological zone map. Then, multiple time-series impervious surface data products, land cover dynamic monitoring product, global biomass data, and topsoil organic carbon (TSOC) information were integrated to build a lookup table (LUT) of biomass and TSOC density for these fine geographical zones. Last, we employed the IPCC method to estimate carbon emissions from ISE between 1985 and 2020. Our findings indicated a global ISE encompassing a total area of 58.12 Mha, with cropland encroachment accounting for 67.30 %. Over the past 35 years, cumulative committed carbon emissions from global ISE reached 1.14 ± 0.38 PgC, with TSOC representing 54.55 % and biomass carbon contributing 45.45 %.

The role of rural-urban migration on child survival in Kenya.

Migration in many developing countries is mostly motivated by the need to improve the well-being of individuals or household members. The aim of this study, therefore, was to establish the role of rural-urban migration on child survival in Kenya. Using a sample of 156,977 children pooled from six Demographic and Health Surveys conducted in Kenya between 1989 and 2014 we compared child survival for five sets of paired migration statuses using odds ratios. The results of the odds ratio for the composite analysis show that children born to rural non-migrants, rural-to-urban migrants and urban-to-rural migrants were 31 percent, 15 percent and 33 percent respectively more likely to die compared to those born to urban non-migrants. Children born to rural-to-urban migrants were 12 percent less likely to die compared to those born to rural non-migrant women while survival chances were similar for children born to urban-to-rural migrants and rural non-migrants. When odd ratios are decomposed by socioeconomic and health characteristics, the results suggest that most of the rural-to-urban migrants face adaptability challenges in urban region. From these results, we conclude that migration can affect child survival through the socioeconomic and environmental adaptability capability of the migrant households. Policies on child survival should therefore aim at bridging the socioeconomic gaps between migrant groups. Specifically, the progressive development policies at both national and devolved governance should aim at reducing the geographical socioeconomic disparities. Keywords: Migration, Child survival, Rural region, Urban region, Odds ratio

Spatiotemporal characteristics and multi-scenario simulation of land use change and ecological security in the mountainous areas: Implications for supporting sustainable land management and ecological planning

The acceleration of global urbanization has intensified land use activities, which threaten the ecological environment and hinder the achievement of sustainable socioeconomic development goals. With the background of continuous land use expansion, the reasonable management of land use and ecological protection has increasingly become an important issue. This study constructs an ecological security (ES) index to evaluate the ES pattern, and employs the Future Land-Use Simulation (FLUS) model for multi-scenario simulation of land use patterns in mountainous areas. The results showed that from 2000 to 2020, cultivated land and grassland showed a sharp decrease, with areas of −128.64 and −228.18 km² respectively, while forest land, urban land, and other construction land increased, with areas of 116.12, 31.21, and 120.69 km² respectively. Over time, the mountainous areas mainly exhibited low and moderate ES patterns. Furthermore, for 2020–2030, under the natural development scenario, cultivated land, forest land, and grassland will show a decrease, while urban and other construction land will show a sharp increase. In contrast, under the ecological protection scenario, ecological land will show significant increase, and the patch expansion of urban construction land will be smaller. These results confirm the positive contribution of ES protection effects to improving the land use development, and support insightful guidance for formulating policies on ecological management in mountainous areas.

Urban sprawl, urban form, and urban land use pattern: examining urban planning response to the causes and effects of urban sprawl in Kumasi, Ghana

ABSTRACT Unplanned urbanization continues to threaten the sustainability of cities in the global south. This study seeks to assess the urban planning response to the effects of sprawl on the urban form and land use pattern of Kumasi. The study relied on geospatial techniques to determine changes in land use patterns, landforms, and sprawl. A qualitative research approach was used to examine urban planning response to the causes and effects of urban sprawl in Kumasi. The results of this study show that the higher the urbanization rate, the more the built-up area increases, causing a significant loss of natural assets such as farmlands. In terms of shape, the research showed that the Greater Kumasi Metropolis has shifted from the historically monocentric city structure to a polycentric city. The city currently has multiple centers or subcentres for commercial, cultural, and social activities. In spite of all the threats posed by urban sprawl on the metropolis, there no clear policy intervention put in place to address the adverse effects of sprawl in the Greater Kumasi Metropolis. The researchers recommend that city authorities should adopt the compact city approach to control the high rate of sprawl to promote densification.

How enabling factors determine unmet healthcare needs? A panel data approach for countries

Health service need refers to the essential care required to achieve optimal health outcomes within resource constraints. When necessary services to address identified health issues are not received, unmet needs arise. This research focuses on the determinants of unmet healthcare needs across the 34 countries within the European region from 2011 to 2019, focusing on Andersen's Behavioral Model's enabling factors. We employed a static and robust panel regression model using Stata 14.0 software. Key determinants analyzed include GDP per capita, urbanization rate, and physicians per capita. Findings reveal that lower GDP per capita and lower urbanization rates are significantly correlated with higher levels of unmet healthcare needs, highlighting income level and geographical accessibility as critical factors. Additionally, a higher number of physicians per capita is associated with reduced unmet healthcare needs, indicating the importance of healthcare resources in addressing healthcare access gaps. These findings underscore the importance of targeted healthcare policies that address income level, improve healthcare accessibility, and enhance healthcare resource allocation to reduce unmet healthcare needs effectively. These findings equip policymakers and administrators with empirically grounded insights to comprehend the factors contributing to unmet healthcare needs and to develop policies aimed at addressing this challenge.

Urbanization alters the relative importance of local and landscape factors affecting plant communities in the Tokyo megacity.

Plant communities are impacted by local factors (related to environmental filtering) and landscape factors (related to dispersal limitation). While many studies have shown that the relative importance of these factors in understanding plant community dynamics due to urbanization, little is known about how they are altered by urbanization-a significant threat to biodiversity. This study evaluates the relative importance of local environmental (local factors), landscape, and spatial (landscape factors) variables that influence plant communities in 34 urban green spaces comprising two different habitats (forests and grasslands) along the urban-rural gradients in the Tokyo megacity, Japan. To continuously assess the relative importance of each factor along the urban-rural gradients, we extracted 1000 landscapes within a certain range that contained several sites. Subsequently, the relative importance of each factor and urbanization rate (proportion of artificial built-up area) were estimated for each landscape. Our study found that the relative importance of both local and landscape factors decreased, while that of local factor for native species in forest habitats and that of landscape factors for native species in grassland habitats increased. Collectively, these findings suggest that city size and habitat characteristics must be considered when predicting changes in plant communities caused by urbanization.

The Rural-Urban Intermarriage and Female Identity Formation in Contemporary China

This article analyzes the marital experiences of rural-urban female migrants in contemporary China through qualitative semi-structured interviews. It argues that these women have gained more autonomy and higher status within their families through intermarriage. Despite these improvements, they continue to face significant prejudices and pressures from family members and society. The empirical research reveals that female migrants often struggle with managing relationships with their elders. Additionally, differences in economic income and the division of domestic labor lead to conflicts over household finances between female migrants and their partners. The study found that female migrants are under multiple pressures from their partners and parents-in-law, often choosing to compromise in domestic conflicts. Overall, the autonomy that female migrants exhibit in intermarriages highlights a significant transformation in their self-determination and self-identification.

Impact of Public Health Emergencies on the Willingness of Rural Migrant Workers to Return Home: Evidence from China

In 2022, under the combined influence of the COVID-19 pandemic and the economic downturn. The employment landscape is grim, particularly for rural migrant workers, who are under immense pressure to secure employment. This study used structural equation modeling and bootstrapping methods to identify the influencing factors of migrant workers’ willingness to return home during public health emergencies and the potential multiple causal relationships, based on 2879 questionnaires on the employment status of migrant workers who are from Chongqing in 2022. The result of this study will be used as a reference by policymakers to formulate employment policies. The results show that: (1) Public health emergencies have no discernible direct impact on people’s willingness to return home. However, they have a significant positive effect on hometown belongings and a significant negative effect on income level and employment stability. These effects are ranked in order of influence: sense of belonging to hometown &gt; income level &gt; employment stability. (2) The willingness to return home is significantly impacted negatively by employment stability and income level, but it is significantly positively impacted by hometown belonging, with employment stability having the biggest impact. (3) There is a substantial inverse relation between income level and sense of belonging to hometown; the higher the income level, the stronger the capacity to withstand outside threats, and the greater the propensity to remain employed. (4) Three pathways exist by which public health emergencies affect migrant workers’ willingness to return home: “PHE→ES→HI”, “PHE→IL→HI”, and “PHE→ES→IL→HI”. (5) Income level and employment stability have multiple chain’mediating effects between public health emergencies and the willingness to return home, while only income level plays a partial mediating role between employment stability and the willingness to return hometown.

Carbon emission prediction of 275 cities in China considering artificial intelligence effects and feature interaction: A heterogeneous deep learning modeling framework

High technology and artificial intelligence (AI) are crucial for achieving urban Dual Carbon Goals. This study proposes a heterogeneous deep learning framework with analysis and prediction phases to explore AI technology's impact on urban carbon emissions. In the analysis phase, fixed effect models address differences in AI development and time heterogeneity among cities. In the prediction phase, an Attention Deep & Cross Network (ADCN) model leveraging feature interactions is proposed to enhance prediction precision and robustness. The Shapley Additive Explanations (SHAP) method quantifies each feature's contribution to ADCN's predictions, elucidating factors' impacts on carbon emissions. This study investigates AI development levels and other variables across 275 Chinese cities to test model performance and uncover the AI-carbon emissions relationship. Results show that fixed effects models significantly improve prediction accuracy, with ADCN outperforming statistical and machine learning models (RMSE: 646.262, MAE: 474.818, R²: 0.993). SHAP analysis reveals that AI technology level (11.85 %), smart city (12.35 %), energy consumption (11.60 %), population (9.38 %), urbanization rate (8.89 %), and GDP (8.40 %) significantly influence carbon emissions. Especially, the interaction between AI technology and smart city or intelligent manufacturing proportion increases their carbon reduction by 1.059 × 1021 or 4.992 × 1019 tons. AI technology moderates the impact of increasing energy consumption and urbanization, reducing their potential emissions by 20 % and 1 %. The framework offers high accuracy and scalability, providing valuable insights for strategy development.

Conceptualizing climate-induced migration in Africa

Climate change has detrimental effects on the livelihoods of Africans, given their dependency on agriculture and subsistence farming. As such, when the environment is no longer conducive due to climate change challenges, migration is opted to seek better, more supportive living conditions. The study aimed to understand migration trends in the African region and to identify sustainable development strategies to mitigate migration by employing a bibliometric and systematic literature review. This systematic literature review of 16 studies conceptualized climate-induced mobility in African countries with evidence on how climate change has influenced migration decisions for most dwellers in vulnerable African areas. The results revealed a rural-urban migration as farming workers searched for other ways to secure livelihoods. Migration to other countries was also identified, especially in countries like the United States, France and the United Kingdom. However, the results also revealed that those who remained in rural areas would opt for other livelihood activities such as businesses. It was also observed that climate-induced migration is growing in Africa, particularly in Ghana, Uganda, Tanzania and Ethiopia. Therefore, to mitigate climate issues and manage migration, strategies are required to support communities affected by climate-induced problems.This study recommends that governments and policymakers should consider strategies like climate development finance, capacitating communities depending on natural resources, conservation agriculture and innovative technology to help stabilize the economies in areas affected by climate change and to improve human security.