China’s Belt and Road Initiative (BRI) hopes to deliver trillions of dollars in infrastructure financing to Asia, Europe, and Africa. If the initiative follows Chinese practices to date for infrastructure financing, which often entail lending to sovereign borrowers, then BRI raises the risk of debt distress in some borrower countries. This paper assesses the likelihood of debt problems in the 68 countries identified as potential BRI borrowers. We conclude that eight countries are at particular risk of debt distress based on an identified pipeline of project lending associated with BRI.
Because this indebtedness also suggests a higher concentration in debt owed to official and quasi-official Chinese creditors, we examine Chinese policies and practices related to sustainable financing and the management of debt problems in borrower countries. Based on this evidence, we offer recommendations to improve Chinese policy in these areas. The recommendations are offered to Chinese policymakers directly, as well as to BRI’s bilateral and multilateral partners, including the IMF and World Bank.
Mangrove forests are vital to coastal protection, biodiversity support, and climate regulation. In the Niger Delta, these ecosystems are increasingly threatened by oil spill incidents linked to intensive petroleum activities. This study investigates the extent of mangrove degradation between 1986 and 2022 in the lower Niger Delta, specifically the region between the San Bartolomeo and Imo Rivers, using remote sensing and machine learning. Landsat 5 TM (1986) and Landsat 8 OLI (2022) imagery were classified using the Support Vector Machine (SVM) algorithm. Classification accuracy was high, with overall accuracies of 98% (1986) and 99% (2022) and Kappa coefficients of 0.97 and 0.98. Healthy mangrove cover declined from 2804.37 km2 (58%) to 2509.18 km2 (52%), while degraded mangroves increased from 72.03 km2 (1%) to 327.35 km2 (7%), reflecting a 354.46% rise. Water bodies expanded by 101.17 km2 (5.61%), potentially due to dredging, erosion, and sea-level rise. Built-up areas declined from 131.85 km2 to 61.14 km2, possibly reflecting socio-environmental displacement. Statistical analyses, including Chi-square (χ2 = 1091.33, p < 0.001) and Kendall’s Tau (τ = 1, p < 0.001), showed strong correlations between oil spills and mangrove degradation. From 2012 to 2022, over 21,914 barrels of oil were spilled, with only 38% recovered. Although paired t-tests and ANOVA results indicated no statistically significant changes at broad scales, localized ecological shifts remain severe. These findings highlight the urgent need for integrated environmental policies and restoration efforts to mitigate mangrove loss and enhance sustainability in the Niger Delta.
The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.
Support through the corporate tax system is a very specific form of funding to promote the functioning of team sports. The basic idea of the mechanism is that profit-oriented companies can donate a larger part of their corporate tax to sports organisations. The scheme has been in operation in Hungary since 2011. Its introduction and fine-tuning required several legislative changes and EU approval. Its importance is reflected in the increase in the number of sports organisations in the respective sports. While funding is available to many sports organisations, in some cases it is quite concentrated. In our empirical research we sought to find out how the degree of concentration has changed over time. The degree of concentration has an impact on how balanced the competition is. One of the key values for sports services is the requirement of an uncertain output. The data reveal that over time the distribution has become more evenly balanced across all sport operators. The amount of funding for sports organisations has started to converge. According to these figures, there are several sports organisations with equivalent subsidies participating in the competition system. However, the majority of clubs with the highest subsidies tend to be the same from year to year. The allocation of grants is determined by the sports federation of the given sport according to the submitted applications. Decision-makers should pay particular attention to maintaining the balance of competition over a long period of time. To this end, the list of sporting organisations with the highest subsidies should be continuously assessed and revised.
The holding of soccer events has an important impact on modern urban activities, which is conducive to the economic development, social harmony, cultural integration and regional integration of cities. However, massive energy is consumed during the event preparation and infrastructure construction, resulting in an increase in the city’s carbon emissions. For the sustainable development of cities, it is important to explore the theoretical mechanism and practical effectiveness of the relationship between soccer events and urban carbon emissions, and to adopt appropriate policy management measures to control carbon emissions of soccer events. With the development of green technology, digitalization, and public transportation, the preparation and management methods of soccer events are diversified, and the possibility of carbon reduction of the event is further increased. This paper selects 17 cities in China from 2011 to 2019 and explores the complex impact of soccer events on urban carbon emissions by using green technology innovation, digitalization level and public transportation as threshold variables. The results show that: (1) Hosting soccer events increases carbon emissions with an impact coefficient of 0.021; (2) There is a negative single-threshold effect of green innovation technology, digitalization level and public transportation on the impact of soccer events on carbon emissions, with the impact coefficients of soccer events decreasing by 0.008, 0.01 and 0.06, respectively, when the threshold variable crosses the threshold. These findings will enhance the attention of city managers to the management of carbon emissions from soccer events and provide guidance for reducing carbon emissions from soccer events through green technology innovation, digital means and optimization of public transportation.
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