Search Results (20)

The work presents a comprehensive analysis and costing of sugar beet cultivation in 2020–2022, for individual farms of the Lublin region. About 120 farms were analyzed. Based on this analysis, the criteria for a model farm were determined and adopted for the calculation of sugar beet production costs. ARIMA process modeling was performed, based on which forecasts were determined for several selected parameters. Customs tariffs introduced by the USA have a drastic impact on the economy. The effects of the COVID19 pandemic may also have a significant impact on the current market situation. Forecasting in the current geopolitical situation is very difficult because of the lack of stationarity of parameters. The financial result obtained by growers is mainly influenced by indirect costs absorbing 61.31% of total costs in 2020. In 2021 and 2022, indirect costs were 61.16% and 59.61% of production income, respectively. Among this group of costs, the largest share is accounted for by the costs of sowing services, sugar beet harvesting, and soil liming amounting from 14.27% to 15.92%. During the analyzed period, sugar beet cultivation remained profitable, with a production profitability index of 1.31 in 2020 and 2021, and 1.10 in 2022. The unit cost of production increased every year. In 2020, it was 14.27% and in 2021, it increased to 15.19%. The unit cost of production in 2022 was the highest, at 23.41%. Sugar beet cultivation is one of the profitable activities in agricultural production, but it is characterized by high production costs, which increased during the years analyzed (2020 to 2022), topping out at 90.87% of total revenue. The information and data presented in this study will be used in the development of a farmer-oriented application and will support the creation of an expert system for sugar beet growers. Cost forecasting will enable farmers to plan their production more effectively. Full article

Electric vehicles (EVs) are central to the decarbonisation of transport systems and achievement of the Sustainable Development Goals (such as SDGs 7 and 13, affordable and clean energy and climate action, respectively). This study adopts a hybrid methodological framework, merging panel econometric models with machine learning (ML), to examine the drivers of EV adoption across Africa, China, and the European Union between 2015 and 2023. We analyse the influence of charging station density (CSD), GDP per capita, renewable energy share (RES), urbanisation, and electricity access using both first-difference and fixed-effects models for causal insight and Random Forest, XGBoost, and neural network algorithms for predictive analytics. While CSD emerges as the most significant driver across models, results reveal a paradox—GDP per capita demonstrates a negative relationship with EV adoption in econometric models yet ranks among the top predictive features in ML models. This divergence highlights the limitations of assuming linear causality in high-income settings and underscores the value of combining causal and predictive approaches. SHAP and PCA analyses further illustrate regional disparities, with Africa showing low feasibility scores due to infrastructure and grid limitations. Sub-regional case studies (Kenya, South Africa, Morocco, Nigeria) emphasise the need for tailored, integrated policies that address both energy infrastructure and transport equity. Findings highlight the value of combining interpretable models with predictive algorithms to inform inclusive and region-specific EV transition strategies. Full article

Starting with the debate on the “resource curse”, the main aim of this paper is to evaluate the impact of natural resource rents on income/wealth inequality in the European Union (EU) during the period from 1990 to 2023. Excepting the Gini index, natural resources rents reduced other measures of income and wealth inequality, and the results indicate that growth has a masking mediating effect on the Gini index, but no mediation role of GDP was observed in the case of the top 1% income/wealth share. The income inequality based on the top 1% share significantly increased in Denmark after the discovery of oil and gas relative to the control group composed of Finland and Sweden. Other control variables are considered, and some policy recommendations are proposed to reduce income/wealth inequality. Full article

Owning a home has become a distant, often unattainable dream for many Americans since the 2007–2009 recession. The shortage of homes has decreased affordability, forcing 43 million U.S. households to become renters rather than owners. Racially targeted policies and widespread discrimination, coupled with neoliberal urban renewal policies, have forced communities of color, especially immigrants and the foreign-born, at the greatest disadvantage in homeownership. This paper examines tract-scale disparities in homeownership across major racial/ethnic groups. Using the U.S. Census Office of Management and Budget’s (OMB) 2019 definition of the 13-county-metropolitan statistical area (MSA) of Nashville, Tennessee, as the study area, I use five-year American Community Survey (ACS) (2015–2019) data estimates to examine the spatial disparity in homeownership and its predictors. Nashville MSA is one of the fastest-growing southern gateways, and it is also the largest, most diverse, and most intermixed metropolis in Tennessee. It contains higher than the state’s overall share of foreign-born, and during 2019–2040, its share of immigrants is projected to grow by 40.7%, making it the best-suited laboratory for race/immigrant-focused research on housing. This analysis finds significant differences in race-based mean per-capita income, with Whites ($32,522) and Asians ($32,556) at the top, whereas Blacks ($25,062) and Hispanics ($20,091) are at the lowest. The ratio of race-based per-capita-income-versus-median housing values is the highest for Whites (15.19) and Asians (15.07) and the lowest for Blacks (11.49) and Hispanics (9.27), putting these two groups as the most disadvantaged regarding their affordability. Regression models suggest lower White homeownership in higher diversity tracts among foreign-born-not-citizens (FBNCs), whereas Black and Hispanic homeownerships are higher in tracts with higher diversity among FBNCs. Interestingly, Asian homeownership is high in tracts with high-income Black tracts, pointing toward the increasing significance of class. Full article

Remittances are essential to the sustainability of economies in mountainous regions that face massive labour migration due to limited income generation and employment opportunities. In 2021, the share of remittances in GDP in the top 10 mountainous economies in the world was over 20%. Nonetheless, most are characterised by relatively lower GDP per capita and high poverty levels. Drawing a comparison with other mountainous areas, Phuthaditjhaba, an emerging mountainous city of South Africa on the border with Lesotho, faces similar out-migration and inferior socio-economic parameters. A global systematic literature review on the impact of remittances on livelihoods, specifically targeting mountainous areas, is missing. We, therefore, interrogate the role that remittances can play in Phuthaditjhaba. To inform our intended research, we seek to draw lessons from evidence on how migration and remittances affect mountainous communities globally. Accordingly, we carry out a systematic literature review (SLR) based on an updated Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA) 2020 statement supported by bibliometric (co-word) analysis (BA) in VOSViewer. We collected data from the Scopus and Dimensions websites and drew 165 publications, of which only 88 were included after exclusion and inclusion assessments. The PRISMA results show that Mountain Research and Development, Russell King, and Nepal are the most productive and cited journal, the most productive and cited author, and the most researched country, respectively. The bibliometric analysis on keyword co-occurrences revealed that women, agriculture, labour migration, land management, forest, and poverty are the research hotspots. In light of these findings, we proffer important recommendations for future researchers and policymakers and identify thematic research areas for Phuthaditjhaba. Full article

Although China has been successful in reducing national income inequality over the past decade, regional income inequality shows a fluctuating trend. The pre-tax income shares of the top 10% and 1% have grown since 1978 and reached about 40% and 15% of the total income share in 2015. Meanwhile, the pre-tax income shares of the bottom 50% have been falling, having dropped from one-quarter of the total income share to less than that of the top 1% in 2015. With this background, this study investigated the trends of income inequality from 2000 to 2020 in west, central, northeast, and east regions in China and analysed their influence factors. Income data from 271 prefecture-level cities in mainland China between 2010 and 2019 were used to calculate the Theil index in each province and region. The analysis was segregated based on urban and rural areas in four regions: east, northeast, central, and west. The Theil index indicated that the income inequality of different regions in China showed a declining trend in rural areas, and a declining and then increasing trend in urban areas. Furthermore, local economic development has a positive impact on income inequality, whereas the urbanization rate and fiscal spending rate have negative impacts on income inequality. Full article

It is well known that vaccination is the best clinical approach for successfully controlling COVID-19 infection. Understanding the disparities in COVID-19 vaccination apprehension among parents in different societies is crucial for effectively implementing COVID-19 vaccination programs. This observational cross-sectional study was carried out in the Riyadh region of Saudi Arabia between February and April 2022. The validated questionnaire was shared with parents who had children between the ages of five and eleven years. The collected data were analyzed using descriptive and inferential statistical methods. Multinomial regression analysis was conducted to determine the factors significantly affecting vaccine-use decisions. Of the 699 participants, 83% of the mothers were between the ages of 35 and 44 years, 67% were university educated, and only 14% were healthcare workers. A large proportion of parents, with an age range of 18–34 years (p = 0.001), and those with a higher income group (p = 0.014), demonstrated significant vaccine hesitancy. Further, parents who received one or two vaccination doses were significantly (p = 0.02) more hesitant than those who received more than two doses of the vaccine. Furthermore, a significantly (p = 0.002) high percentage of parents who follow the Ministry of Health (MOH) guidelines for personal preventive measures were hesitant about their children’s vaccination. Concerns about side effects (31.4%) and a lack of safety data (31.2%) on the COVID-19 vaccines were the two most significant reasons for parents to develop vaccine hesitancy. Social media (24.3%), poor perceived immunity (16.3 %), and news articles (15.5%) were the top three contributors to this hesitancy. Vaccinated parents were 8.21 times more likely to be vaccination-hesitant than non-vaccinated parents. Additionally, parents with less education and a COVID-19-positive child at home increased the odds of vaccine hesitancy by 1.66 and 1.48 times, respectively. Overall, one-third of the parents were not prepared to vaccinate their children, and one-quarter of the respondents had not decided about vaccination. This study shows that parents in Riyadh are generally reluctant to vaccinate their children against COVID-19. As social media is a primary source of information for parents, public health professionals should utilize the platform to encourage parents to support vaccine acceptance. Full article

This study investigates the nexus of income inequality, economic growth, and CO₂ emissions based on the environmental Kuznets curve (EKC) hypothesis for 38 OECD countries during 1990–2015. The indices of income inequality include the Gini coefficient and the top income share. The main objective of this study is to re-examine the effects of income inequality and economic growth on CO₂ emissions based on the Environmental Kuznets Curve (EKC) hypothesis. The panel analysis for OECD countries is examined using country fixed effects and Granger causality including pre-tests for unit root, cointegration, and stationarity. The main findings of this study are as follows. First, the effects of economic growth on CO₂ emissions have an inverted U-shaped relationship, and the effects of income inequality on CO₂ emission also have an inverted U-shaped relationship. Second, the Gini coefficient and the top income share represented by the income inequality index are well-defined tools for analyzing the relationship between income inequality and environmental degradation. Third, the increase in trade dependency and renewable energy consumption has contributed to the decrease in CO₂ emissions, but the increase in energy use has led to an increase in CO₂ emissions. Finally, economic growth and income inequality have Granger causality for CO₂ emissions, and economic growth bi-directionally causes Granger causality for income inequality. Therefore, this study suggests that resolving income inequality is crucial and another important environmental policy that affects CO₂ emissions. Full article

The dramatic lack of diversity within science, technology, engineering, and mathematics (STEM) higher-education graduates is a serious issue facing the future of the STEM workforce. Colleges and universities are attempting to fix this disparity through targeted intervention programs aimed at increasing the persistence and retention of low-income, first-generation, and underrepresented (UR) students in STEM. A comprehensive synthesis of adopted strategies and analysis of their effectiveness is lacking. We conducted a systematic multiple-studies review, considering 31 empirical articles published between 2005 and 2020 that shared the outcomes of intentional intervention programs in place across the United States. We uncovered essential characteristics of successful programs and highlighted the top 10 critical program components to consider. These can be used to guide the development and execution of future programs’ support systems and interventions. This is a relatively new area of research, with most programs just in the earliest stages of implementation. It is essential to continue to follow the data on the outcomes of these programs, particularly their longitudinal impacts on the diversification of the STEM workforce, to be able to implement effective evidence-based practices. Full article

Future wind power developments may be located in complex topographic and harsh environments; forests are one type of complex terrain that offers untapped potential for wind energy. A detailed analysis of the unsteady interaction between wind turbines and the distinct boundary layers from those terrains is necessary to ensure optimized design, operation, and life span of wind turbines and wind farms. Here, laboratory experiments were carried to explore the interaction between the wake of a horizontal-axis model wind turbine and the boundary layer flow over forest-like canopies and the modulation of forest density in the turbulent exchange. The case of the turbine in a canonical boundary layer is included for selected comparison. The experiments were performed in a wind tunnel fully covered with tree models of height $H/z_{hub}\approx 0.36$, where $z_{hub}$ is the turbine hub height, which were placed in a staggered pattern sharing streamwise and transverse spacing of $\mathsf{\Delta }x/d_c=1.3$ and 2.7, where $d_c$ is the mean crown diameter of the trees. Particle image velocimetry is used to characterize the incoming flow and three fields of view in the turbine wake within $x/d_T\in (2,7)$ and covering the vertical extent of the wake. The results show a significant modulation of the forest-like canopies on the wake statistics relative to a case without forest canopies. Forest density did not induce dominant effects on the bulk features of the wake; however, a faster flow recovery, particularly in the intermediate wake, occurred with the case with less dense forest. Decomposition of the kinematic shear stress using a hyperbolic hole in the quadrant analysis reveals a substantial effect sufficiently away from the canopy top with sweep-dominated events that differentiate from ejection-dominated observed in canonical boundary layers. The comparatively high background turbulence induced by the forest reduced the modulation of the rotor in the wake; the quadrant fraction distribution in the intermediate wake exhibited similar features of the associated incoming flow. Full article

Cross-sectional data show Global North countries export higher quality products at a point in time. Product-level panel data can address if countries improve their export quality over time. The literature has addressed this practically relevant panel question only in small samples over the short term. We addressed it for a large sample, over the long run, focusing on the hitherto overlooked endogeneity between export quality and factor accumulation and the role of export composition. We utilized a two-tiered panel: the panel of countries and the panel of products each country trades. We found some evidence that middle-income countries often upgrade export quality within the same product, but that high- and low-income countries do this less often. Our results appear to support product cycle theory: some countries climb the value ladder, others are competed off from the ladder’s top, and new countries enter markets. Technology appears to be a potential basis for consolidating trade competitiveness over time, as skill accumulation becomes more widespread across countries and loses significance as an explanatory variable. Our results provide some explanation of why Global North countries might resist sharing technology. This research is timely with deadlocked multilateral trade negotiations and looming trade wars. It attempts to contribute to an evidence-based guide to trade policy. Full article

Macadamia is an essential commodity crop in Malawi. The nuts are a lucrative commodity and are used for household consumption, income generation among farming families and as a foreign exchange earning crop at country-level. Macadamia production in Malawi has increased significantly in recent years. Malawi is the seventh top producer of macadamia nuts valued at £23.5 million, with a global market share of 3%. In 2018, the country was the fourth-largest exporter of macadamia nuts that were valued at £18.2 million. The majority (90%) of this crop was grown by large commercial estates with smallholder’s production only contributing about 10% of the total crop production. However, the smallholder sector is vital for the future growth of the macadamia sector in the country. Further, Malawian smallholders consider macadamia production as a low-input crop with large returns per unit area (£10.7 kg⁻¹ ha⁻¹), and it thus a lucrative commodity with high potential for poverty reduction and wealth creation among these farming families. This paper, therefore, explores: (i) the historical and current trends in macadamia nut production in Malawi; (ii) analyses the country’s macadamia value chain focusing on smallholder farmer contributions; and (iii) discusses the constraints of smallholder macadamia production in Malawi for informed policymaking. We conclude that the synthesis of the Malawian macadamia sub-sector provides an understanding of the vital contributions of macadamia to Malawi’s economic growth and improvement of livelihoods. Full article

As the market share of electric vehicles increases, the intermittent load on the electricity grid due to charging will increase. This can be counteracted by Vehicle-to-Grid (V2G) which utilises dormant electric vehicles to feed power into the grid, generating income for the vehicle owner while relieving load across the grid. However, increased battery use through V2G can negatively affect battery health. In this work, a computational model of an electric vehicle with battery degradation is used to investigate the relationship of these effects. The analysis was conducted at the top level of detail, only considering the battery pack of the vehicle. The findings of this investigation show that the cost relating to battery degradation is smaller than the potential profit available from Vehicle-to-Grid over a three-year period. However, the benefit does not seem to be enough to justify the upfront investment requirement, and further financial incentives, such as net billing, may be required to make V2G economically viable. Future development within this field is vital for the success of the electric vehicle within the automotive markets, and for the transition to a renewable energy grid. Full article

The rapid urbanization and growing population aging have become salient features in China. Understanding their impacts on household emissions is crucial for designing mitigation policies for household carbon emissions. By integrating Chinese older household survey data with an unconditional quantile regression model, this paper examines the heterogeneous impacts of household characteristics on indirect carbon emissions of older Chinese households. There are three main findings: (1) The effects of urbanization on emissions at different quantiles of carbon emissions appear to be inverted U-shaped, which means that the rise of urbanization level increases carbon emissions more at the middle than at the bottom or the top, and helps to alleviate carbon emission inequality, (2) though carbon emissions rise with the increase of income, there is a clear urban-rural divide in the effects of income on carbon emissions, and (3) the rise in the share of well-educated people contributes to the increase in carbon emissions. The higher the degree of education is, the larger the impact is. These findings contribute to understanding the determinants of carbon emissions and are helpful for policymakers to design targeted policies in reducing carbon emissions from the consumption-side. Full article

The awareness of self-consumption of grid-connected roof-top solar photovoltaic (PV) owners in a community and the advancement in information and communication technologies (ICT) led to the development of a novel peer-to-peer energy trading mechanism for next-generation power systems. In the peer-to-peer (P2P) energy trading landscape, the prosumers and consumers self-organize and trade energy among themselves. In recent years, the large penetration of distributed energy resources, as well as the advancement of technologies in the fields of protection, power electronics, and storage devices, led to the use of direct current (DC) home appliances by the end-users, i.e., consumers in a community. In this paper, the operational costs of an individual household and community when operated with alternating current (AC) and DC home appliances are calculated using bill sharing and the mid-market rate method for various degrees of PV penetration. The bill sharing method shares the operational cost and income among all the peers in proportion to the amount of energy they consume/generate. The mid-market rate method calculates the P2P internal price at the median of the import and export price based on the relationship between total generation and demand. In terms of operational cost, both producers and consumers benefit fairly when the mid-market rate method is used when the households in a community are operated with DC home appliances. Full article