Atmospheric microplastic deposition associated with GDP and population growth: Insights from megacities in northern China

Microplastic (MP) pollution is evolving into one of the most pressing environmental concerns worldwide. This study assessed the impact of economic activities on atmospheric MP pollution across 17 megacities in northern China, analyzing the correlation between the deposition flux of atmospheric MPs and variables such as city population, gross domestic product (GDP), and industrial structure. The results have shown that the MP pollution is obviously impacted by human activities related to increased GDP, population, as well as tertiary service sector, in which the MP pollution shows most close relationship with the GDP growth. Polypropylene, polyamide, polyurethane, and polyethylene were identified as the primary components of atmospheric MPs. The average particle size of MPs in atmospheric dustfall is 78.3 µm, and the frequency of MP particles increases as the particle size decreases. The findings highlight the complex relationship between socio-economic development and atmospheric MP accumulation, providing essential insights for the formulation of targeted emission reduction strategies.

Translation elongation factor-1α is pivotal for plant heat tolerance despite its pronounced heat-induced aggregation

The translation elongation factor 1α (EF1α) protein is a highly conserved G protein that is crucial for protein translation in all eukaryotic organisms. EF1α quickly became insoluble at temperatures 42 °C treatment for 2h in vitro, but generally remained soluble in vivo even after being exposed to temperatures as high as 45 °C for an extended period, which suggests that protective mechanisms exist for keeping EF1α soluble in plant cells under heat stress. EF1α had fast in vivo insolubilization when exposed to 45 °C, resulting in about 40% of the protein aggregating after 9 h. Given its established role in protein translation, heat-induced aggregation is most likely to impact the function of the elongation factor. Overexpression of constitutive mutants in both GTP-bound and GDP-bound forms of EF1α resulted in significantly decreased heat tolerance. These findings provide evidence to support the critical role of EF1α, a thermosensitive protein, in the heat tolerance of plants.

Life expectancy and emission trading scheme: a case study in China

Life expectancy can reflect both health benefit and implementation cost of climate policy. Nevertheless, little research has quantified the relation between life expectancy and climate policy in literature. In this paper, we attempt to narrow the research gap by studying how life expectancy is related to the Chinese nationwide emission trading scheme (CNETS). To achieve this research target, a Computable General Equilibrium (CGE) model is employed to simulate the operation of the economic system and the policy shock from emission abatement. The CGE model results show that life expectancy is prolonged by GDP but shortened by emissions, and the GDP impact on life expectancy is larger than the emission impact. Climate policy has dual effects on life expectancy because it relieves both negative emission impacts and positive GDP impacts on lifespan; its net effect on life expectancy is positive. Life expectancy positively impacts GDP, and this impact is moderated by climate policy; specifically, climate policy reinforces the positive impact of life expectancy on GDP. Life expectancy minimally affects carbon emissions during climate policy implementation; in other words, it has minimal impacts on emission abatement. These findings imply that climate policy and life expectancy complement each other; the government could implement climate policy to increase lifespan or prolong life expectancy to facilitate policy implementation.

Exploring the Modifying Role of GDP and Greenness on the Short Effect of Air Pollutants on Respiratory Hospitalization in Beijing

It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p < 0.001), SO2 (p < 0.001), O3 (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.

Estimating sectoral COVID-19 economic losses in the Philippines using nighttime light and electricity consumption data

Introduction

Economic loss estimation is critical for policymakers to craft policies that balance economic and health concerns during pandemic emergencies. However, this task is time-consuming and resource-intensive, posing challenges during emergencies.

Method

To address this, we proposed using electricity consumption (EC) and nighttime lights (NTL) datasets to estimate the total, commercial, and industrial economic losses from COVID-19 lockdowns in the Philippines. Regression models were employed to establish the relationship of GDP with EC and NTL. Then, models using basic statistics and weather data were developed to estimate the counterfactual EC and NTL, from which counterfactual GDP was derived. The difference between the actual and the counterfactual GDP from 2020 to 2021 yielded economic loss.

Results

This paper highlights three findings. First, the regression model results established that models based on EC (adj-R2 ≥ 0.978) were better at explaining GDP than models using NTL (adj-R2 ≥ 0.663); however, combining both EC and NTL improved the prediction (adj-R2 ≥ 0.979). Second, counterfactual EC and NTL could be estimated using models based on statistics and weather data explaining more than 81% of the pre-pandemic values. Last, the estimated total loss amounted to 2.9 trillion PhP in 2020 and 3.2 trillion PhP in 2021. More than two-thirds of the losses were in the commercial sector as it responded to both policies and the COVID-19 case surge. In contrast, the industrial sector was affected primarily by the lockdown implementation.

Discussion

This method allowed monitoring of economic losses resulting from long-term and large-scale hazards such as the COVID-19 pandemic. These findings can serve as empirical evidence for advocating targeted strategies that balance public health and the economy during pandemic scenarios.

Economic activity and suicides: Causal evidence from macroeconomic shocks in England and Wales

The relationship between economic activity and suicides has been the subject of much scrutiny, but the focus in the extant literature has been almost exclusively on estimating associations rather than causal effects. In this paper, using data from England and Wales between January 1, 1997 and December 31, 2017, we propose a plausible set of assumptions to estimate the causal impacts of well-known macroeconomic variables on the daily suicide rate. Our identification strategy relies on scheduled macroeconomic announcements and professional economic forecasts. An important advantage of using these variables to model suicide rates is that they can efficiently capture the elements of 'surprise or shock' via the observed difference between how the economy actually performed and how it was expected to perform. Provided that professional forecasts are unbiased and efficient, the estimated 'surprises or shocks' are 'as good as random', and therefore are exogenous. We employ time series regressions and present robust evidence that these exogenous macroeconomic shocks affect the suicide rate. Overall, our results are consistent with economic theory that shocks that reduce estimated permanent income, and therefore expected lifetime utility, can propel suicide rates. Specifically, at the population level, negative shocks to consumer confidence and house prices accelerate the suicide rate. However, there is evidence of behavioural heterogeneity between sexes, states of the economy, and levels of public trust in government. Negative shocks to the retail price index (RPI) raise the suicide rate for males. Negative shocks to the growth rate in gross domestic product (GDP) raise the population suicide rate when the economy is doing poorly. When public trust in government is low, increases in the unemployment rate increase the suicide rate for females.

Does ICT influence carbon emissions in the context of universal connectivity: a global perspective?

The Connect 2030 initiative, launched by the International Telecommunication Union, is in alignment with the Sustainable Development Goals (SDGs) of the United Nations Agenda 2030. Its main objective is to achieve universal connectivity, a goal that is closely related to environmental issues. This topic currently receives attention from researchers and policymakers. Given these considerations, our study investigates the impact of information and communication technologies on carbon dioxide emissions for a panel of 84 countries spanning the years 2009 to 2020. Using principal component analysis, we construct an ICT index that encompasses international bandwidth, reflecting the universal connectivity, and participation in international data exchanges. The empirical analysis applies the pooled mean group-panel autoregressive distributive lag (PMG-ARDL) approach to estimate both the long-run and short-run coefficients of CO2 emissions' determinants. Our findings show that ICT and renewable energy mitigate CO2 emissions, unlike financial development, GDP, and non-renewable energy, which contribute significantly to emissions for the full sample. These outcomes suggest that promoting ICTs in general and international bandwidth in particular, as part of universal connectivity, improves the quality of the global environment.

The role of environmental diplomacy and economic factors on environmental degradation

In recent years, rising carbon dioxide (CO2) emissions and other negative environmental effects of human activity have raised concerns about the planet's future. Rapid industrialization, urbanization, and economic activity have shown a surge in CO2 emissions, contributing to global warming and climate change. The main purpose of this study is to examine the impact of such as gross domestic product, gross domestic product square, foreign direct investment, environmental diplomacy, environmental diplomacy security, and renewable energy consumption on environmental degradation. This study provides a new perspective on environmental diplomacy in OECD countries using panel data econometric methodologies from 1991 to 2020. It contributes to our understanding of the role of environmental and economic factors in reducing CO2 emissions. The panel data is also analyzed by CD, CIPS, FMOLS, DOLS, and PMG-ARDL tests. However, as per the findings of this research, all the factors significantly impact environmental degradation (Co2 emission). Finding data to either confirm or deny the efficacy of the Environmental Kuznets Curve theory within the framework of OECD countries is possible through this approach. This policy framework attempts to solve the issues at the connection of environmental diplomacy and economic concerns by emphasizing cooperation and sustainability and incorporating environmental considerations into economic decision-making processes in OECD countries.

Capital flight from BRICS nations: Does every cloud have a silver lining?

This study investigates the potential determinants of capital flight from BRICS countries. We use the residual method to estimate capital flight and employ GMM testing approach. We find a surge in the volume of capital flight from BRICS especially in the aftermath of global financial crisis. The empirical results suggest that, past values of the capital flight, real GDP growth rates, exchange rate depreciation, unemployment rate, business confidence index and financial stability indicator as significant factors causing resident capital outflows from BRICS nations. These findings call for an effective policy framework by the fiscal and monetary authorities.

The dynamics of Escherichia coli FtsZ dimer

The E. coli FtsZ dimer was studied to gain insights into FtsZ protofilament formation. In the simulation study of the M. janaschii dimer it was found that the monomer-monomer contacts in the GDP bound dimer is lower which results in the high curvature of the GDP bound protofilaments. In this study, the E. coli FtsZ dimer was simulated. The initial structure was obtained from our previous study in which we had simulated the E. coli FtsZ monomer with its C-terminal IDR (Intrinsically Disordered Region). The M. janaschii FtsZ dimer subunit contacts were used as the starting configuration. Simulations of the dimer were performed with GTP and with GDP. It is found that the central helix H5 closes by about 15 degrees in the simulation with GTP than in the simulation with GDP. The C-terminal IDR and the C-terminal domain region between SC2 and HC2 are found to have much high flexibility and hence exhibit domain motion.Communicated by Ramaswamy H. Sarma.

Forecasting the transportation energy demand with the help of optimization artificial neural network using an improved red fox optimizer (IRFO)

Transportation energy demand has a significant impact on worldwide energy consumption and greenhouse gas emissions. Accurate transportation energy demand predictions can help policymakers develop and implement successful energy policies and strategies. In this study, a novel approach to predict transportation energy demand using the Artificial Neural Network (ANN) based on the Improved Red Fox Optimizer (IRFO) has been suggested. The proposed method utilizes the ANN model to solve the complex nonlinear relationships between transportation energy demand and its effective parameters including Gross Domestic Product (GDP), population, and vehicle numbers. Also, the IRFO algorithm was utilized to modify the ANN model's parameters to improve the prediction accuracy. The experimental findings demonstrate the ANN-IRFO model performs better than the other method in terms of accuracy and effectiveness. It predicts the growth of GDP, population, and vehicles number by 5.5 %, 4.8 %, and 4.2 %, respectively. The findings demonstrate that the suggested method can provide accurate forecasts for transportation energy demand, which can help decision-makers to make informed decisions and policies regarding energy management and sustainability.

Multi-locus genome-wide association studies reveal the genetic architecture of Fusarium head blight resistance in durum wheat

Durum wheat is more susceptible to Fusarium head blight (FHB) than other types or classes of wheat. The disease is one of the most devastating in wheat; it reduces yield and end-use quality and contaminates the grain with fungal mycotoxins such as deoxynivalenol (DON). A panel of 265 Canadian and European durum wheat cultivars, as well as breeding and experimental lines, were tested in artificially inoculated field environments (2019-2022, inclusive) and two greenhouse trials (2019 and 2020). The trials were assessed for FHB severity and incidence, visual rating index, Fusarium-damaged kernels, DON accumulation, anthesis or heading date, maturity date, and plant height. In addition, yellow pigment and protein content were analyzed for the 2020 field season. To capture loci underlying FHB resistance and related traits, GWAS was performed using single-locus and several multi-locus models, employing 13,504 SNPs. Thirty-one QTL significantly associated with one or more FHB-related traits were identified, of which nine were consistent across environments and associated with multiple FHB-related traits. Although many of the QTL were identified in regions previously reported to affect FHB, the QTL QFhb-3B.2, associated with FHB severity, incidence, and DON accumulation, appears to be novel. We developed KASP markers for six FHB-associated QTL that were consistently detected across multiple environments and validated them on the Global Durum Panel (GDP). Analysis of allelic diversity and the frequencies of these revealed that the lines in the GDP harbor between zero and six resistance alleles. This study provides a comprehensive assessment of the genetic basis of FHB resistance and DON accumulation in durum wheat. Accessions with multiple favorable alleles were identified and will be useful genetic resources to improve FHB resistance in durum breeding programs through marker-assisted recurrent selection and gene stacking.

A bibliometric analysis of publication output in selected South American countries

Research output provides an insight into the development of the scientific capability of a country. Budget allocation for research and development (R&D) is directly proportional to the research output of a country. Bibliometric analysis of South American countries has not been done in many studies. The purpose of this paper was to analyse research outputs from South American countries on various metrics. An analysis was done for a period of 11 years from 2010 to 2020. The analysis revealed that Brazil with highest percentage of research spend has lowest Field Weighted Citation Impact (FWCI). This contrasts with Uruguay, whose FWCI is high despite comparatively lower spend on R&D and lower publication output. Although Argentina has the highest percentage of researchers per million population (1202), it has the least papers per researchers (0.3 per year) among the countries studied. A huge disparity in terms of percentage of research spent, research output, papers per researcher, and output with national and international co-authorship was observed.

Biospheric values as predictor of climate change risk perception: A multinational investigation

Climate change is one of the big challenges of our time. A better understanding of how individuals form their evaluation of the risk related to climate change seems to be key to win broad support for climate change mitigation efforts. Extant research indicates that biospheric values (BV) are an important antecedent of individuals' perception of the risk and consequences related to climate change. However, risk perception scholars have only recently started to study how BV relate to individuals' climate change risk perception (CCRP) and much is still to be learned about this relationship. The present study contributes to this growing literature by studying the BV-CCRP relationship in a multinational context. The results suggest that the BV - CCRP relationship varies in strength between different countries. These differences can be explained in part by societies' cultural leanings (i.e., individualism vs. collectivism) and societies' wealth. The present research adds to our understanding of why individuals in different countries perceive climate change related risk differently and how this perception is shaped differently by biospheric values in different countries. In this way, the findings help to build a more nuanced theory of how CCRP are formed. The presented results also have implications for policymakers and NGOs who wish to increase individuals' engagement with climate change and its consequences in different populations. In particular, the findings suggests that it might be necessary to use different strategies in different societies to achieve a greater awareness of climate change related risks.

Analyzing the influencing factors of collaborative innovation and industrial structure upgrading on the economy: reflection on the economic dilemma of enterprises

The present study has investigated the impact of enterprises, collaborative innovation, industrial structure, inflation, and entrepreneurship in 27 provinces of China. The study used annual time series data from 2003 to 2019. This study adopts the CC-EMG and AMG tests to estimate the long-term association between the variables. The study applied one-step system GMM, two-step system GMM, Cup-FM, and Cup-BC regression estimations to calculate robust and reliable outcomes. The findings show that collaborative innovation, industrial structure, and entrepreneurship positively impact economic growth, whereas enterprises and inflation negatively impact economic growth. The estimated results also provide important policy implications for the selected and the other emerging economies in designing an appropriate way forward to economic development.

Does higher education promote sustainable development? Role of green technology and financial performance

How do digitalizing businesses help them achieve sustainable growth? This research examines the mediating function of green technology innovation in answering this question by defining sustainable development performance in terms of corporations' financial and environmental success. The educational system in China is examined to see how much of an impact it has on eco-innovation, as well as the relationship between green technology and innovation. The IFE test was utilized to determine whether or not the associations between variables such as GDP per capita, urbanization, green technology, higher education, and carbon dioxide emissions will continue to exist between 2004 and 2020 in China. The data for this analysis came from 30 of China's provinces. The findings of both the short-term and long-term CS-ARDL estimations demonstrated a positive link between eco-innovation and GDP per capita, green technology, higher education, and CO2 emissions. On the other hand, a negative correlation was found between urbanization and eco-innovation. The next topic covered in the research was how the effects of green technology might be seen in areas such as GDP per capita, higher education, and carbon dioxide emissions. The findings might provide valuable knowledge that developing economies can use to construct a feasible, sustainable path.

Analysis and prediction of the incidence and prevalence trends of gonorrhea in China

To understand the epidemiological trend of gonorrhea in China from 2004 to 2021, predict the prevalence of the disease, and provide basic theory and data support for monitoring and managing gonorrhea. Gonorrhea incidence data in China from 2004 to 2021 were collected through the China Public Health Science Data Center and National Administration of Disease Prevention and Control, and the incidence and epidemiological characteristics were analyzed. Statistical analysis was performed using Joinpoint and autoregressive integrated moving average (ARIMA) models. A linear correlation model was used to analyze the correlation between gross domestic product (GDP) and the incidence rate. From 2004 to 2021, a total of 2,289,435 cases of gonorrhea were reported in China, with an average reported incidence rate of 9.46/100,000 people and a downward followed by an upward trend. Individuals with gonorrhea were primarily 20-30 y of age, with 1,034,847 cases (53.38%) from 2004 to 2018. The trend of increasing incidence was most obvious in the 10-20 age group (5,811 cases in 2004 to 12,752 cases in 2018, AAPC = 6.1, P < .001). The incidence of gonorrhea in China was negatively correlated with GDP from 2004 to 2021 (r = -0.547, P = .019). The correlation coefficient between the average incidence growth rate of each region from 2012 to 2018 and the average growth rate of regional GDP was 0.673 (P < .01). The root mean square error (RMSE) of the ARIMA model was 4.89%, showing powerful performance. There would be 97,910 gonorrhea cases in 2023 as predicted by the model.

Green financial investment and its influence on economic and environmental sustainability: does privatization matter?

Green financial investment and privatization have been widely used as policy tools to promote economic growth and efficiency in many countries. However, their effects on environmental sustainability have been less explored. This study utilizes autoregressive distributed lag (ARDL) and quantile autoregressive distributed lag (QARDL) techniques to explore the effects of green financial investment and privatization on economic and environmental performance in China. Using data from 1995 to 2021, we analyze the impact of green financial investment and privatization on economic performance, measured by GDP per capita, and environmental performance, measured by CO2 emissions based on green finance and privatization theories. Our findings reveal that green financial investment has a beneficial effect on both economic and environmental performance. On the other hand, privatization has a positive impact on long-term economic performance, while also having negative consequences on environmental performance. These findings can inform evidence-based policies and strategies that promote both economic and environmental performance.

Economic factors underlying biodiversity loss

Contemporary economic thinking does not acknowledge that the human economy is embedded in Nature; it instead treats humanity as a customer that draws on Nature. In this paper, we present a grammar for economic reasoning that is not built on that error. The grammar is based on a comparison between our demand for Nature's maintenance and regulating services and her ability to supply them on a sustainable basis. The comparison is then used to show that for measuring economic well-being, national statistical offices should estimate an inclusive measure of their economies' wealth and its distribution, not GDP and its distribution. The concept of 'inclusive wealth' is then used to identify policy instruments that ought to be used to manage such global public goods as the open seas and tropical rainforests. Trade liberalization without heed paid to the fate of local ecosystems from which primary products are drawn and exported by developing countries leads to a transfer of inclusive wealth from there to rich importing countries. Humanity's embeddedness in Nature has far-reaching implications for the way we should view human activities-in households, communities, nations and the world. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Exploring the Factors Behind Regional Differences in Physical Fitness of Geological University Students

The intention of this study is to investigate the distribution of physical fitness of the geographical students. The indicators among freshmen at a Chinese geological university and compare their fitness levels with students from other types of institutions. The research revealed that students at higher latitudes exhibited greater physical strength but were less athletic than those at lower latitudes. Spatial dependence on physical fitness was more pronounced in males than in females, particularly for indicators characterizing athletic capacity. Influencing factors such as PM10, air temperature, rainfall, eggs consumption, grain consumption, and GDP which were identified as the major climate, dietary structure, and economic level were examined. Revised：PM10, air temperature and eggs consumption, factors influencing the spatial distribution of male physical fitness across the country. Rainfall, grains consumption and GDP, factors influencing the spatial distribution of female physical fitness across the country. respectively. These factors were found to affect males (42.43%) more than females (25.33%). These findings highlight the significance of regional differences in students' physical fitness levels, with students in geological universities demonstrating better overall physical fitness compared to their counterparts at other schools. Consequently, it is essential to develop tailored physical education strategies for students in various regions, taking into account local economic, climatic, and dietary factors. This study offers a greater explanation of physical fitness disparities between the Chinese university students as well as provides insights for designing effective physical education programs.

Comparison of vaccination and booster rates and their impact on excess mortality during the COVID-19 pandemic in European countries

Aim

To evaluate the effect of vaccination/booster administration dynamics on the reduction of excess mortality during COVID-19 infection waves in European countries.

Methods

We selected twenty-nine countries from the OurWorldInData project database according to their population size of more than one million and the availability of information on dominant SARS-CoV-2 variants during COVID-19 infection waves. After selection, we categorized countries according to their "faster" or "slower" vaccination rates. The first category included countries that reached 60% of vaccinated residents by October 2021 and 70% by January 2022. The second or "slower" category included all other countries. In the first or "faster" category, two groups, "boosters faster'' and "boosters slower" were created. Pearson correlation analysis, linear regression, and chi-square test for categorical data were used to identify the association between vaccination rate and excess mortality. We chose time intervals corresponding to the dominance of viral variants: Wuhan, Alpha, Delta, and Omicron BA.1/2.

Results and discussion

The "faster" countries, as opposed to the "slower" ones, did better in protecting their residents from mortality during all periods of the SARS-CoV-2 pandemic and even before vaccination. Perhaps higher GDP per capita contributed to their better performance throughout the pandemic. During mass vaccination, when the Delta variant prevailed, the contrast in mortality rates between the "faster" and "slower" categories was strongest. The average excess mortality in the "slower" countries was nearly 5 times higher than in the "faster" countries, and the odds ratio (OR) was 4.9 (95% CI 4.4 to 5.4). Slower booster rates were associated with significantly higher mortality during periods dominated by Omicron BA.1 and BA.2, with an OR of 2.6 (CI 95%. 2.1 to 3.3). Among the European countries we analyzed, Denmark, Norway, and Ireland did best, with a pandemic mortality rate of 0.1% of the population or less. By comparison, Bulgaria, Serbia, and Russia had a much higher mortality rate of up to 1% of the population.

Conclusion

Thus, slow vaccination and booster administration was a major factor contributing to an order of magnitude higher excess mortality in "slower" European countries compared to more rapidly immunized countries.

Measuring the impact of the digital economy in developing countries: A systematic review and meta- analysis

The digital economy, driven by Information and Communication Technology (ICT), has emerged as a significant contributor to economies worldwide. However, accurately defining and measuring its impact on national economies remains a complex endeavor. This paper explores the definition, measurement, role, and impacts of the digital economy across various economies. It also examines the involvement of governments and telecommunication regulators in assessing the digital economy and identifies future directions for developing countries. A systematic literature review utilizing the PRISMA Model is employed to investigate the factors and indices used to measure the digital economy. The findings highlight ongoing efforts to harmonize the definition and metrics; nonetheless, challenges persist due to the scarcity of appropriate datasets and variations in country-specific definitions. Additionally, the effectiveness of existing digital economy indices and toolkits in assessing the level of digitalization in developing countries is evaluated. The paper concludes that despite ongoing efforts to bridge the gaps, the concept of the digital economy remains defined and measured differently, necessitating a new definition that accounts for various contextual peculiarities. Furthermore, a roadmap is proposed to develop a toolkit that ensures comprehensive measurement, thus preventing an underestimation of the digital economy's contribution to the Gross Domestic Product (GDP) in developing countries. The paper underscores the need for international and multi-stakeholder dialogue to establish a common understanding of the digital economy's definition and measurement. Developing countries, such as Nigeria, are urged to develop or adopt new metrics tailored to their unique circumstances, facilitating an accurate and efficient quantification of the digital economy's impact on crucial indicators like GDP. Improved statistical data collection and recording methodologies are recommended for both governments and the private sector. Moreover, the paper advocates for the establishment of a Digital Economy Advisory Board (DEAB) in developing countries to maximize the benefits of the ongoing global transition to the digital economy.

Cancer trends and risk factors in China over the past 30 years (1990-2019)

Objective: We retrospectively studied cancer mortality and incidence in China from 1990 to 2019, investigated the cancer trends and risk factors, and analyzed the effects of Gross Domestic Product (GDP) on cancer mortality and incidence. Methods: Data was obtained in "Our world in data" in October 2022 to explore mortality rates of different cancers and their trends and the roles of cancer risk factors, including GDP, air pollution, etc. Results: Over the past 30 years, cancer had been China's second leading cause of death. Tracheal, bronchial, and lung cancers, with an annual growth rate of 6.5%, were the most frequently diagnosed cancers. The burden of different cancers changed as the mortality rate of cancer changed. The age-standardized cancer mortality rate had decreased by 19.0%; cancer deaths in all age groups had increased. While the number of cancer deaths in the elderly aged ≥70 did not increase distinctively, its percentage increased by 52.1% and 1.7% annually. The percentage of patients with new-onset cancer increased by 240% and 8.6% annually. For every USD 1,000 increase in GDP, cancer deaths decreased by 2.3/100,000. Tobacco, meat, and alcohol consumption and BMI had increased and were not conducive to the future control of cancer. Conclusions: We summarized the incidence and mortality of major cancers and their trends in China over the past 30 years and analyzed the effects of GDP and the roles of cancer risk factors. Overall GDP growth and effective control of air pollution reduced cancer mortality, while population aging, smoking, alcohol consumption, BMI increasing, and meat consumption brought challenges for cancer control.

Links between renewable and non-renewable energy consumption, economic growth, and climate change, evidence from five emerging Asian countries

One of the greatest challenges facing humanity in the current millennium is the need to mitigate climate change, and one of the most viable options to overcome this challenge is to invest in renewable energy. The study dynamically examines the links between renewable energy consumption, non-renewable energy consumption, climate change, and economic growth in five emerging Asian countries during the period 1975-2020. Variables selected in the model have long-term cointegration, as explored by the Pedroni cointegration test and the Westerlund cointegration test. The long-term estimated parameters of the augmented mean group (AMG) method show that renewable energy consumption significantly reduces climate change, while non-renewable energy consumption significantly promotes climate change. The results also show that GDP, investment in transport infrastructure, and urbanization can significantly contribute to climate change in selected emerging Asian countries. Moreover, the results validate the inverted U-shaped EKC hypothesis for emerging Asian economies. Country-specific analysis results using AMG estimates shows that renewable energy consumption reduces climate change in selected emerging Asian countries. Non-renewable energy consumption and investment in transport infrastructure have had significant progressive impacts on climate change in all countries. Urbanization contributes significantly to climate change, with the exception of Japan, which does not have any significant impact on climate change. GDP contributes significantly to climate change in all countries; however, GDP2 has significant adverse effects on climate change in India, China, Japan, and Korea, validating the inverted U-shaped EKC assumption for all countries except Bangladesh. Moreover, the Dumitrescu and Hurlin causality test confirmed a pairwise causal relationship between non-renewable energy consumption and GDP, supporting the feedback hypothesis. The results suggest that the best option for climate change mitigation in selected emerging Asian countries is to transition from non-renewable to renewable energy sources.

Impact of economic variables on CO2 emissions in belt and road and OECD countries

The rebirth of the Belt and Road Initiative (BRI) programme have necessitated the study as it has a vast potential to promote economic growth, yet, marred with numerous energy use and ecological concerns. The article is the first to comparatively examine the impact of economic variables on consumption-based CO₂ emissions in the BRI and the Organisation for Economic Co-operation and Development (OECD) countries by testing the Environmental Kuznets Curve (EKC) and the Pollution Haven Hypothesis (PHH). The Common Correlated Effects Mean Group (CCEMG) estimates the results. Income (GDP) and GDP² positively and negatively impact CO₂ emissions in the three panels, validating the EKC. Foreign direct investment (FDI) significantly affects CO₂ emissions for the global and BRI panels, supporting the PHH. However, the PHH is refuted for the OECD panel as the impact of FDI on CO₂ emissions is negative and statistically significant. GDP and GDP² decline by 0.029% and 0.0446%, respectively, for BRI countries, compared to OECD countries. It is recommended that BRI countries enact new and stringent environmental laws and use more tidal energy, solar energy, wind power, bioenergy, and hydropower instead of fossil fuels, for the sustainable attainment of higher economic growth, devoid of pollution.

Dynamic connectedness between green energy and carbon risk during Russia-Ukraine conflict: new evidence from a wavelet analysis

The study explores the inter-relations between green and renewable energy and carbon risk. Key market participants with varying time horizons include traders, authorities, and other financial entities. This research examines these relationships and frequency dimensions from February 7, 2017, to June 13, 2022, using novel multivariate wavelet analysis approaches, such as partial wavelet coherency and partial wavelet gain. The multiple coherencies between green bond, clean energy, and carbon emission futures imply that these regions were situated at low frequencies (relating to approximately 124-day frequency) and run from the beginning of 2017 to the beginning of 2018, in the first half of 2020, and from the beginning of 2022 to the end of the sample. The relationship between the solar energy index, envitec biogas, biofuels, geothermal energy, and carbon emission futures, is significant in the low-frequency band starting from early 2020 to middle 2022 and in the high-frequency band starting from early 2022 to middle 2022. Our research demonstrates the partial coherencies between these indicators during the Russia-Ukraine conflict. The partial coherency between the S&P green bond index and carbon risk suggests that carbon risk pushes anti-phase connectedness. The partial phase difference S&P global clean energy index and carbon emission futures (from early April 2022 to the end of April 2022) recommend that indicators are in-phase with carbon risk pushing and the phase (from early May 2022 to middle June 2022), suggesting that carbon emission futures are in-phase with S&P global clean energy index pushing.

Trends in health and health inequality during the Japanese economic stagnation: Implications for a healthy planet

Introduction

Human health and wellbeing may depend on economic growth, the implication being that policymakers need to choose between population health and the health of ecosystems. Over two decades of low economic growth, Japan's life expectancy grew. Here we assess the temporal changes of subjective health and health inequality during the long-term low economic growth period.

Methods

Eight triennial cross-sectional nationally representative surveys in Japan over the period of economic stagnation from 1992 to 2013 were used (n = 625,262). Health is defined positively as wellbeing, and negatively as poor health, based on self-rated health. We used Slope and Relative Indices of Inequality to model inequalities in self-rated health based on household income. Temporal changes in health and health inequalities over time were examined separately for children/adolescents, working-age adults, young-old and old-old.

Results

At the end of the period of economic stagnation (2013), compared to the beginning (1992), the overall prevalence of wellbeing declined slightly in all age groups. However, poor health was stable or declined in the young-old and old-old, respectively, and increased only in working-age adults (Prevalence ratio: 1.14, 95% CI 1.08, 1.20, <0.001). Over time, inequality in wellbeing and poor self-rated health were observed in adults but less consistently for children, but the inequalities did not widen in any age group between the start and end of the stagnation period.

Conclusions

Although this study was a case study of one country, Japan, and inference to other countries cannot be made with certainty, the findings provide evidence that low economic growth over two decades did not inevitably translate to unfavourable population health. Japanese health inequalities according to income were stable during the study period. Therefore, this study highlighted the possibility that for high-income countries, low economic growth may be compatible with good population health.

Environment and natural resources degradation under COVID-19 crises: Recovery post pandemic

Environmental stability improved during the covid 19 pandemic when production and industrial activities, and natural resources depletion processes stopped during the lockdown environment worldwide; however, based on the judgment of COP26 and the recent COP27, environmental degradation increased in the world in post-pandemic; therefore, policymakers and researchers re-focused their attention on the determinants of CO2 in economies. Hence, this study investigates the nexus of natural resource rents, including oil rents, mineral rents, and coal rents, on the carbon emissions of upper-middle-income economies from 1984 to 2021. The study included economic growth and renewable energy as additional determinants. We have presented detailed time series methods that aid in examining the modeled variables characteristics in the current research, i.e., ADF and ADF-GLS for a unit root in the data variables and considering their stationarity, Johansen cointegration for long-term cointegration among variables, FMOLS, DOLS and CCR for the long run elasticities between dependent and independent variables and Granger causality test in our range of methods. Robustness checks analysis is done through a non-parametric approach by quantile regression and robust regression analysis. Our results exhibit that two natural resource rents that are oil rents and coal rents, have adverse impacts on carbon emissions, and both are positive and significant. In contrast, mineral rents have no statistical significance and role in the carbon emissions of upper-middle-income economies. Moreover, economic growth and renewable energy also positively and significantly impact carbon emissions. Granger causality analysis exerts that natural resources rents, except for mineral rents, economic growth, and renewable energy, all granger causes CO2 emissions, and the feedback is also true. The relevant findings are suitable for policymakers in upper-middle-income economies to ensure environmental sustainability in upper-middle-income economies.

Impact of green technological innovations on environmental quality for Turkey: evidence from the novel dynamic ARDL simulation model

The contribution of this research is to provide empirical evidence that investing in green technology innovation (GTI) can reduce the ecological footprint in Turkey, which can lead to sustainable economic growth and environmental quality. The research also highlights the importance of controlling energy consumption, GDP, trade openness, and urbanization, as these variables have a positive or negative effect on ecological footprint. The findings of this research can be useful for the Turkish government, policymakers, and environmentalists to promote the implementation of GTI and eco-friendly resources, which can reduce the impact of climate change and contribute to economic prosperity. Overall, this research provides important information for decision-makers to adopt policies that prioritize green innovation and environmental protection in Turkey.

Economic development, weak ties, and depression: Evidence from China

OBJECTIVES

Weak ties are becoming mainstream in daily relationships and play an essential role in the improvement of individuals' mental health. Despite growing concerns on depression, inclusion of weak ties is limited. To address the gap, this study empirically shed light on the role of weak ties on individual depression in the context of economic development.

METHOD

A cross-sectional study was conducted based on 2018 China Health and Retirement Longitudinal Study (CHARLS) with a sample of 16,545 individuals. A moderated mediation model is constructed to evaluate the impact of economic development (GDP) on the degrees of depression, the mediating effect of weak ties, and the moderating effect of residents' residence types (living in urban or rural areas).

RESULTS

Economic development exerts a significant direct impact on depression (β=-1.027, p<0.001). Weak ties are significantly negatively correlated with depression (β=-0.574, p<0.001), and act as a mediator between economic development and local individual depression. In addition, the residence type plays a moderating role between economic development and weak ties (β=0.193, p<0.001). That is, living in urban areas would introduce the higher the level of weak ties.

CONCLUSIONS

Higher economic development is largely conducive to alleviating the degrees of depression, weak ties play a mediating role in economic development and depression, and residence types have a positive moderating effect on the economic development and weak ties.

Algal mediated intervention for the retrieval of emerging pollutants from aqueous media

Water is a crucial elemental contributor for all sectors; however, the agricultural sector alone accounts for 70% of the world's total water withdrawal. The anthropogenic activity from various industries including agriculture, textiles, plastics, leather, and defence has resulted in the release of contaminants into water systems, resulting harm to the ecosystem and biotic community. Algae-based organic pollutant removal uses several methods, such as biosorption, bioaccumulation, biotransformation, and biodegradation. The adsorption of methylene blue by algal species Chlamydomonas sp. showed a maximum adsorption capacity of 2744.5 mg/g with 96.13% removal efficiency; on the other hand, Isochrysis galbana demonstrated a maximum of 707 µg/g nonylphenol accumulation in the cell with 77% removal efficiency indicating the potential of algal systems as efficient retrieval system for organic contaminants. This paper is a compilation of detailed information about biosorption, bioaccumulation, biotransformation, biodegradation, and their mechanism, along with the genetic alteration of algal biomass. Where the genetic engineering and mutations on algae can be advantageously utilized for the enhancement of removal efficiency without any secondary toxicity.

The transition journey of EU vs. NON-EU countries for waste management

This study aims to identify macroeconomic indicators that can be used as predictors of waste management on the European continent. The study was conducted taking in account the intensification of urbanizations, the increase of standard of leaving that fuels to consumerism phenomenon, and imposed challenges for waste management. The research focuses on the interval from 2010 to 2020 for 37 European countries grouped according to EU15/EU28/non-EU and EU/non-EU members. As macroeconomic indicators, human development index (HDI), GDP/capita. GNI/capita, general government expenditure with environment protection, people at risk of poverty or social exclusion, population by educational attainment level, sex, and age (%)-less than primary, primary and lower secondary education (levels 0-2) were used. A multilinear regression model with collinearity diagnosis was applied to find out the direction and intensity of the contribution of independent variables and to hierarchy the predictors of waste management.. For multiple comparison between and inside of each grouping of countries, statistical inference methods were used: one-way ANOVA with Bonferroni post hoc test multiple comparisons and independent samples Kruskal-Wallis test with Dunn's post hoc test. The main conclusions of the study are that EU15 countries have the highest average values for most indicators of waste management, comparative with EU28 and with non-EU countries, followed by a group of EU28 countries. For indicators of recycling rate of packaging waste by type of packaging-metallic and recycling rate of e-waste, the non-EU countries have the highest values of mean compared with the EU15 and EU28 groups of countries. This can be explained by the high level of development of the some non-euro area countries (Iceland, Norway, Switzerland, Liechtenstein) that have intense concerns about waste recycling and have the necessary financial strength to carry out complex environmental protection programs.

Does tourism have an impact on carbon emissions in Asia? An application of fresh panel methodology

This research investigates the effects of tourism, GDP per capita, renewable energy, energy intensity, urbanization, and population on the environment in 40 Asian countries. Data from 1995 to 2019 are used in this analysis. Slope heterogeneity (SH), cross-sectional dependency (CSD), and the combination of level and first differenced stationary are all addressed using a new cross-sectionally autoregressive distributed lag (CS-ARDL) model in this work. Using Westerlund's cointegration method, these variables can be connected throughout time. To validate the findings, both augmented mean groups (AMG) and Common correlated effect mean groups (CCEMG) were utilized. The study results indicate that tourism helps slow the degradation of the natural environment. CO2 emissions increase as a result of variables such as population growth, energy use, and economic development. Only tourism and renewable energy can help cut CO2 emissions. As a consequence, CS-ARDL results are supported by results from AMG and CCEMG tests. Policymakers may be encouraged countries to adopt renewable energy and foster the expansion of the sustainable tourism industry.

Which Factors Influence the Immensely Fluctuating CRT Implantation Rates in Europe? A Mixed Methods Approach Using Qualitative Content Analysis Based on Expert Interviews

(1) Background: Cardiac resynchronisation therapy (CRT) is nowadays an indispensable treatment option for heart failure. Although the indication is subject to clear cross-national guidelines by the European Society of Cardiology (ESC), there is immense variation in the number of implantations per 100,000 inhabitants in Europe, especially in German-speaking countries (Germany, Austria and Switzerland). The aim of the present study was to identify possible factors for these differences using a qualitative research approach. (2) Methods: Semi-standardized interviews were conducted with 11 experts in the field of CRT therapy (3 experts from Germany, 4 from Austria and 4 from Switzerland) using a pre-prepared interview template and analysed according to Mayring's qualitative content analysis. (3) Results: The main factors identified were the costs of purchasing the devices and the financing systems of the respective healthcare systems, although cost pressure still seems to play a subordinate role in the German-speaking countries. Moreover, "lack of implementation of ESC guidelines", "insufficient training" and "lack of medical infrastructure" could be excluded as potential reasons. (4) Conclusions: Economic factors, but not a lack of adherence to ESC guidelines, seem to have a major influence on the fluctuating implantation figures in German-speaking countries, according to the unanimous assessment of renowned experts.

Evaluating the role of renewable energy and technology innovations in lowering CO2 emission: a wavelet coherence approach

Environmental sustainability is one of the most critical issues that require efficient environmental and economic policies in modern times. Advancements in renewables and green technologies contribute significantly to sustained long-term development without affecting environmental quality. Several studies focus on the association of carbon dioxide emissions (CO₂e) with economic variables. However, they ignored the impact of technological innovations and renewable energy consumption on CO₂e in developed countries. Therefore, this study examines the relationship between CO₂e, energy consumption, gross domestic product (GDP), renewable energy consumption, and technology innovations in G-7 countries by employing cross-sectionally augmented autoregressive distributed (CS-ARDL) lag and wavelet coherence techniques during 1990-2020. The results depict that GDP and renewable energy consumption are inversely related to CO₂e. A 1% increase in CO₂e will decrease GDP and renewable energy consumption by 0.459 and 0.172% in the long run and by 0.471 and 0.183% in the short run in G7 countries. Technology innovations negatively impact CO₂e in the short run while positively influencing it in the long run. Considering the advancements in green technologies in different energy-dependent and manufacturing sectors is crucial for a sustainable environment in the long run. Such initiatives ensure the effective use of energy sources by limiting CO₂e in the atmosphere. Moreover, the dynamic common correlated effects mean group model confirms the reliability and effectiveness of the CS-ARDL. The wavelet coherence approach revealed a causality relation between CO2e and technology innovation in Italy, Japan, the UK, and the USA during the study period.

Goals of sustainable infrastructure, industry, and innovation: a review and future agenda for research

Sustainable Development Goal 9 targets (SDG 9 targets) are mainly tracked through the indicators of penetration of internet and mobile broadband subscription, logistic performance index, quality and ranking of the universities, investment in research and development initiatives, industrial reforms and emission control, and connectivity to rural areas. The attainment of many of these targets and tracking of indicators is confronted by challenges of poor awareness, funding issues, distorted policies, and implementation failures. This systematic review on achievements, challenges, and future scope in attaining SDG 9 consolidates the literature from the Web of Science, related to SDG 9 and indicators, since 2017; develops bibliometric patterns; conducts thematic analysis by focusing the leading indicators of SDG 9; and develops agenda for future research. The major limitations of this study include focusing on selected indicators and limited literature availability. This review recommends policymakers, researchers, and administrators to focus on promising themes such as tackling the digital divide and ensuring digital justice and digital equality; clean fuel and technology adoption; enhancing internet and mobile broadband subscription with reduced negative impacts, logistic sector reforms; industrial policy reforms and technology integration; improving the quality and sustainability of universities; and increasing funding and support for research and development initiatives and improving the rural connectivity.

Determinants of Public Health Personnel Spending in Spain

Public health is funded with government funds gathered from tax revenues, whether national, provincial or municipal. The health system therefore suffers during economic crisis periods, whether due to disinvestment, loss of purchasing power among health care personnel or the decrease in the number of professionals. This worsens the situation, as it is necessary to cover the needs of an increasingly elderly population and with a longer life expectancy at birth. The present study intends to show a model which explains the determination of the "Public Health Personnel Expenditure" in Spain for a determined period. A multiple linear regression model was applied to the period including the years 1980-2021. Macroeconomic and demographic variables were analyzed to explain the dependent variable. Variation in health personnel expenditure: "We included those variables which presented a high or very high correlation above r > 0.6. The variables which explain the behavior of Variation in health personnel expenditure". It was a determining factor in the present study to consider that the variables with the greatest repercussions on health policy were mainly macroeconomic variables rather than demographic variables, with the only significant demographic variable that had a specific weight lower than macroeconomic variables being "Birth Rate". In this sense, the contribution made to the scientific literature is to establish an explanatory model so that public policy managers and states in particular can consider it in their public spending policies, bearing in mind that health expenditures in a Beveridge-style health system, as Spain has, are paid with funds drawn from tax revenues.

Effect of tubulin self-association on GTP hydrolysis and nucleotide exchange reactions

We investigated how the self-association of isolated tubulin dimers affects the rate of GTP hydrolysis and the equilibrium of nucleotide exchange. Both reactions are relevant for microtubule (MT) dynamics. We used HPLC to determine the concentrations of GDP and GTP and thereby the GTPase activity of SEC-eluted tubulin dimers in assembly buffer solution, free of glycerol and tubulin aggregates. When GTP hydrolysis was negligible, the nucleotide exchange mechanism was studied by determining the concentrations of tubulin-free and tubulin-bound GTP and GDP. We observed no GTP hydrolysis below the critical conditions for MT assembly (either below the critical tubulin concentration and/or at low temperature), despite the assembly of tubulin 1D curved oligomers and single-rings, showing that their assembly did not involve GTP hydrolysis. Under conditions enabling spontaneous slow MT assembly, a slow pseudo-first-order GTP hydrolysis kinetics was detected, limited by the rate of MT assembly. Cryo-TEM images showed that GTP-tubulin 1D oligomers were curved also at 36 °C. Nucleotide exchange depended on the total tubulin concentration and the molar ratio between tubulin-free GDP and GTP. We used a thermodynamic model of isodesmic tubulin self-association, terminated by the formation of tubulin single-rings to determine the molar fractions of dimers with exposed and buried nucleotide exchangeable sites (E-sites). Our analysis shows that the GDP to GTP exchange reaction equilibrium constant was an order-of-magnitude larger for tubulin dimers with exposed E-sites than for assembled dimers with buried E-sites. This conclusion may have implications on the dynamics at the tip of the MT plus end.

Synergistic assessment of air pollution and carbon emissions from the economic perspective in China

The synergistic evaluation integrating air quality, human health, climate impact, and socioeconomic development is significant for green and low-carbon transition. Here, we quantified the contribution of pollutant emissions in 30 provinces (source) to PM_2.5 concentration and related premature mortality in each 20 km grid (receptor) of China in 2020 by an integrated model for the first time. Further, we established a cross-province contribution matrix of health impact intensity (HII, PM_2.5-related deaths per GDP). According to HII and CEI (carbon emission intensity, defined as CO₂ emission per GDP) levels, 30 provinces were divided into 4 regions including LL, HL, LH and HH. In order to assess the synergy in air pollution and carbon emission, we established an index system consisting of ISEC-AC (index for synergistic assessment) and its two sub index: IHI (index for HII assessment), and ICE (index for CEI assessment). Results showed that the ISEC-AC was more easily influenced by IHI as the variance of IHI was much higher than that of ICE. Influenced by various factors, e.g., economic structure, population density, pollution transport, ISEC-AC exhibited substantial spatial heterogeneity. In general, the ISEC-AC of southeast provinces was higher than that of central and western, indicating the environmental and climate impact per GDP was relatively lower in southeast China. For provinces, ISEC-AC of SH and GD were ~ 16 times higher than NX. For regions, due to low carbon emission intensity and health impact intensity, ISEC-AC of LL was the highest with 176; followed by HL (128), LH (126) and HH (77). Further, we figured out the main control problems and then put forward targeted synergetic control suggestions for air pollution and carbon emission from the perspective of energy structure, industry structure and industry layout, which can provide insights into future green and low-carbon policy making in China and other countries.

The health consequences of civil wars: evidence from Afghanistan

This study examines the effects of long-run civil wars on healthcare, which is an important component of human capital development and their causality nexus in Afghanistan using the MVAR (modified vector autoregressive) approach and the Granger non-causality model covering data period 2002Q3-2020Q4. The primary results support a significant long-run relationship between variables, while the results of the MVAR model indicate the per capita cost of war, per capita GDP, and age dependency ratio have significantly positive impacts on per capita health expenditures, whereas child mortality rate and crude death rate have negative impacts. The results of the Granger non-causality approach demonstrate that there is a statistically significant bidirectional causality nexus between per capita health expenditure, per capita cost of war, per capita GDP, child mortality rate, crude death rate, and age dependency ratio, while it also supports the existence of strong and significant interconnectivity and multidimensionality between per capita cost of war and per capita health expenditure, with a significantly strong feedback response from the control variables. Important policy implications sourced from the key findings are also discussed.

Renewable energy, industrial upgradation, and import-export quality: green finance and CO2 emission reduction nexus

There has been a steady decline in carbon dioxide emissions in the world's 19 most industrialized nations even as GDP has increased. These nations' efforts to reduce emissions of carbon dioxide, therefore, to reduction of CO₂ and development of renewable energy are the objective of this research. With the years 1995-2019 as a point of reference, we have selected gross domestic product, GDP, RE, industrial upgrading, and import and export as our independent variables. A panel nonlinear autoregressive distributed lag (NARDL) method is utilized to investigate the links between carbon dioxide emission and these independent variables. For the purpose of determining the direction of causation, the panel heterogeneous causality test is used. RE and standards of export and import were shown to be contributing variables in the decrease of carbon dioxide emissions. The environmental Kuznets curve hypothesis was validated by the estimated findings. Increased carbon dioxide emissions are countered by the positive impulses of technological progress, such as R&D development spending and standards of import and export index. Industrial upgrading and emissions of carbon dioxide, gross domestic product and RE, and industrial upgrading and emissions of carbon dioxide, all have a bidirectional causal link. In particular, a one-way causality between gross domestic product and emissions of carbon dioxide, standards of imports and exports, and industrial upgrading, and industrial upgrading and standards of imports and exports is demonstrated. Following the results, policy suggestions are put out.

Resiliency of healthcare expenditure to income shock: Evidence from dynamic heterogeneous panels

Using the World Bank data over the period of 1960-2019, this study aims at estimating the resiliency of health expenditures against gross domestic product (GDP). Long-run and short-run elasticities are calculated using the type of panel time series methods that are exclusively designed for dynamic heterogeneous panels: Mean Group, Pooled Mean Group, and Dynamic Fixed Effects estimators. These methods permit better estimations of elasticity with considerable heterogeneity across the 177 countries included in this study. Along with a standard elasticity estimation, this study estimates country-specific long-run and short-run elasticities along with error correction components. The study finds that the long-run elasticity of income is very close to unity, but short-run coefficients are insignificant for most nations. In addition, most countries revert to long-run equilibrium reasonably quickly if there is shock as the error correction coefficients are negative and, in many cases, very close to one. While for most developed countries, the short-run elasticities are lower in comparison with the short-run elasticities of developing countries indicating that many developing countries may face a larger decrease in health expenditure with the forecasted decline in income due to impending economic recession. Therefore, although this study is not directly intended to capture the post-COVID-19 effects, the study estimates may project the potential responses in health expenditure across countries due to potential income shocks.

Analysis and improvement of sports industry development and public health strategy under low-carbon economic structure

With the continuous development of society, various industries are rising and developing rapidly. Against this background, the energy crisis has come quietly. Therefore, to improve the quality of life of residents and promote the comprehensive and sustainable development of society, it is essential to enhance the development of the sports industry and formulate public health strategies under the background of a low carbon economy (LCE). Based on this, to promote the low-carbon development of the sports industry and optimize the formulation of social public health strategies, firstly, this paper introduces the low-carbon economic structure and its role in society. Then, it discusses the development of the sports industry and the necessity of perfecting public health strategy. Finally, based on LCE's development background, the sports industry's development situation in the whole society and M enterprises is analyzed, and suggestions are put forward to improve the public health strategy. The research results show that the current development prospect of the sports industry is extensive, and the added value of the sports industry will be 1,124.81 billion yuan in 2020, up by 11.6% year-on-year, accounting for 1.14% of Gross Domestic Product (GDP). Although industrial development declined in 2021, the added value of the sports industry accounts for an increasing proportion of GDP yearly, which shows that the sports industry is playing an increasingly important role in economic growth. And through the analysis of the development of M enterprise sports industry as a whole and in different directions, this paper shows that enterprises should reasonably control the development of various industries to provide impetus for the overall development of enterprises. The innovation of this paper lies in the innovative use of the sports industry as the primary research object, and its development under LCE is studied. This paper not only supports the sustainable development of sports industry in the future, but also contributes to improving public health strategy.

Environment, education, and economy nexus: evidence from selected EU countries

Among the most fundamental problems today are environmental problems. As people earn higher incomes as a result of getting a good education, their sensitivity to environmental problems increases. As the income level of both the consumers who have received quality education and the producers who make conscious production increases, their demand for environmental quality and their sensitivity to environmental problems will also increase so it is thought that educational expenditures and policies can affect the number and cost of environmental problems. On the other hand, economic activities comprehensively consume natural resources and impact the ecological quality adversely. Therefore, GDP and the educational expenditures variables are used in the model. The aim of this study is to analyze the relationship between environment, education, and economy during the period of 1998-2017 from selected EU countries (Austria, Italy, the Netherlands, Norway, Poland, Portugal, Romania, and Slovakia). As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-run relationship between the variables was determined at the level of 1%. According to the results of the Dumitrescu-Hurlin causality test, a unidirectional causality relationship from educational expenditures to ecological footprint at the level of 5%, a unidirectional causality relationship from ecological footprint to renewable energy at the level of 1%, and a bidirectional causality relationship at the level of 1% between ecological footprint and GDP were determined. According to the results of Granger causality test based on the VEC model, a unidirectional causality relationship from ecological footprint to educational expenditures at the level of 5%, and bidirectional causality relationship between ecological footprint and renewable energy (from ecological footprint to renewable energy at the level of 10%; from renewable energy to ecological footprint at the level of 1%) were determined. Based on the findings, it can be concluded that economic and educational policy makers should be aware that they have important consequences on environment.

Understanding the relationships between health spending, treatable mortality and economic productivity in OECD countries

Introduction

Population health is one of the highest priorities for countries, which can translate into increased economic prosperity. This encourages research on health in an economic context.

Methods

The objective was to assess the relationships between health spending, treatable respiratory mortality, and gross domestic product (GDP) in countries of the Organization for Economic Co-operation and Development (OECD). The research was conducted with respect to health systems (tax-based, insurance-based) and gender differentiation of the productive population (aged 25-64 years). Descriptive analysis, regression analysis, and cluster analysis were used to achieve the main objective. The data covered the period from 1994 to 2016.

Results

The results of the regression analysis revealed negative relationships between health spending and treatable respiratory mortality in countries with a tax-based health system for male and female working-age populations, as well as in countries with an insurance-based health system for male population. This means that higher health spending was associated with lower treatable respiratory mortality. Also, lower treatable mortality was associated with higher GDP, especially in the male productive population from countries with an insurance-based health system. In this study, countries with a tax-based health system were characterized by higher health spending, lower rates of treatable mortality from respiratory system diseases, and higher GDP compared to countries with an insurance-based health system. Males reported a higher mortality rate than females. Among the countries with a tax-based health system, the United Kingdom and Latvia showed less positive outcomes, while Italy and Iceland were the countries with the most positive outcomes. Among the countries with an insurance-based health system, Hungary and Slovakia reported poor outcomes, while France, Switzerland and Luxembourg were characterized by very positive outcomes. The United States showed a high mortality rate despite its high economic outcomes, i.e., health spending and GDP.

Discussion

Health care financing in particular is one of the instruments of health policy. It seems that the leaders of countries should ensure a sufficient level of health financing, as higher health spending can contribute to lower mortality rates in a country. This may translate into higher productivity. Especially countries with underfunded health systems should increase their health spending.

Impact assessment of the EU import ban on Indonesian palm oil: Using environmental extended multi-scale MRIO

Under the Renewable Energy Directive (RED) II, the EU will phase out the use of palm oil for biodiesel feedstock. Environmental concerns are the main reasons for the EU to implement this initiative. This study analyzes the economic and environmental impact of EU import ban to Indonesia at provincial level, using 2 scenarios (a direct and direct-indirect import ban). The analysis is performed using a global-subnational Multi-Regional Input-Output (MRIO) with environmental extensions. This study shows that a direct (combined) import ban of palm oil by the EU will reduce Indonesia's GDP by -0.2 % (-0.26 %) and employment by -0.12 % (-0.54 %) from baseline. At provincial level, Riau, North Sumatra, Lampung, Central Kalimantan and South Kalimantan experience the highest impact on their domestic product (more than -0.5 %). Under a direct import ban, job losses mostly happen in outside Java (96.26 %) and in the oilseeds sector (75.21 %). Low and middle skilled jobs decline more than high skilled jobs and count for 95 % of the total loss. This study also shows that a direct (combined) import ban reduces national GHG emissions by -0.19 % (-0.24 %) and total land use by -0.48 % (-0.6 %). Potential carbon sequestration can be 34.55 (42.27) million tons C equivalent to 149.74 (182.67) million tons CO₂e under assumption a full rewilding from the reduction of land use in oilseed. Our study shows that an EU import ban on Indonesian palm oil has relatively small economic and environmental impacts at national and provincial level. Yet, this policy can create potential carbon sequestration that can absorb CO₂ by vegetation and soil.

Spatiotemporal distribution characteristics of PM2.5 concentration in China from 2000 to 2018 and its impact on population

PM2.5 is an important indicator reflecting changes in air quality. In recent years, affected by climate change and human activities, the problem of environmental pollution has become more and more prominent. In this study, the PM2.5 data from 2000 to 2018 obtained by satellite remote sensing inversion algorithm were selected to analyze the temporal and spatial distribution of PM2.5 in China. The results show that the areas with higher PM2.5 concentrations were mainly in the North China, the Sichuan Basin, and the Tarim Basin. The areas with a significant increase in PM2.5 were mainly in the Northeast China, while the areas with a significant decrease were mainly in the Sichuan Basin and southeastern Gansu. The change of PM2.5 in southern China was not significantly correlated with the change of population and economy, while PM2.5 in Northeast China increases with the increase of population and economy. In 2000, 2005, 2010, and 2015, the proportion of the population polluted by PM2.5 was 8.65%, 7.2%, 22.99%, and 9.75%, respectively. The year with the highest percentage (37.63%) of population when air quality reached EXCELLENT was 2015. When the PM2.5 spatial cluster number was six, it can better reflect the PM2.5 spatial distribution state. The places with large changes in PM2.5 spatial clustering were mainly in the Northeast China, Sichuan Basin, and Tarim Basin, which were also areas with large changes in PM2.5. This study provides an important reference for atmospheric environmental monitoring and protection.

Services as a Determinant of Botswana's Economic Sustainability

In 2015, the services sector contributed about 58 percent to the gross domestic product (GDP) in Sub-Saharan Africa (SSA), which was a significant increase from the 47.6 percent observed in 2005, and a shift from the mining, agriculture, and manufacturing sector. This increase calls to support services as the catalyst for sustained economic development as indicated by the structural transformation and modernization theories. The main objective of this paper was to examine the relationship between and the impact of services on the economic development in Botswana and make recommendations on how Botswana can apply well-directed policies to improve its services sector and diversify its impact on other sectors and GDP, making it less reliant on mining which is vulnerable to price volatilities. The paper applied econometric modeling and results of the Autoregressive-Distributed Lag (ARDL) Bounds test for cointegration indicate that services and other industries services, agriculture, industry, mining, and investment impact GDP over the short and long run. These variables impacted GDP and converged to equilibrium at the speed of 46.89 percent, with a percent change in services in the short and long run impacting GDP by 0.328 and 0.241 percentages, respectively, and the outcome of the Wald test indicated causality from services to GDP growth. The services sectors have contributed over 40 percent to the country's GDP from 1995 to the present, though the sectors have not gone without challenges with limitations such as limited infrastructure development; poverty and inequality; unemployment of over 20 percent; disease, which has dampened productivity; and lack of proper governance and accountability, which has created a habitat for an increase in cases of corruption in state and private entities. The findings of the study with the lessons learned from other studies with similar findings recommend that the government of Botswana should formulate suitable policies and strategies for services diversification. This is by expanding the market for the sector in areas such as tourism that were impacted by the COVID-19 pandemic, escalating investments by instituting strategies to attract and grow domestic and foreign investments, and improve on management of institutions and resources.