Impact of different geopolitical factors on the energy transition: The role of geopolitical threats, geopolitical acts, and geopolitical risks.

In order to better understand the impact of different geopolitical factors on energy transition, the impact of geopolitical threats (war threats, peace threats, military buildups, nuclear threats and terror threats), geopolitical acts (beginning of war, escalation of war and terror acts), and geopolitical risks on energy transition were systematically investigated. Green technologies, natural resource rents and trade openness were incorporated into the analytical framework, and a dynamic panel threshold model was utilized to explore the impact of geopolitical risks on energy transition across different income levels. To this end, data on geopolitical threats, geopolitical acts, geopolitical risks, energy transitions and other key social economic factors for 38 countries from 2000 to 2022 were collected. The heterogeneity simulation results show that there is a negative correlation between geopolitical threats, geopolitical acts, geopolitical risks and energy transition. Moreover, geopolitical threats have more significant hindrance to the energy transition than geopolitical acts. The results of the nonlinear panel simulation show that there is a double threshold effect of geopolitical risks on energy transition. When geopolitical risk crosses the threshold (0.5197), the coefficient decreases to -0.29, which means that the rising geopolitical risk increases the inhibition on energy transition, and the inhibitory effect is slightly weakened after a certain level. Finally, policy implications are offered.

Revisiting the Environmental Kuznets Curve (EKC) Hypothesis of Carbon Emissions: Exploring the Impact of Geopolitical Risks, Natural Resource Rents, Corrupt Governance, and Energy Intensity.

The global imperative to mitigate carbon emissions for sustainable development has spurred extensive research into economic, social, and energy-related factors. However, prior studies present a complex landscape, yielding mixed conclusions regarding the influence of geopolitical risk, natural resource rents, corrupt governance, and energy intensity. To untangle this ambiguity, we construct a research model grounded in the Environmental Kuznets Curve, employing panel data from 38 countries spanning 2002 to 2020. Employing panel quantile regression models, we directly assess the impact of identified factors. Our findings affirm the alignment between economic growth and carbon emissions, supporting the Environmental Kuznets Curve hypothesis. Notably, increased geopolitical risk and energy intensity correlate with heightened carbon emissions over time, while corruption governance and natural resource rents exhibit a mitigating effect. Additionally, our study explores the indirect impact of these factors using a panel threshold regression model. Results indicate a diminishing influence of economic growth on carbon emissions. Intriguingly, natural resource rents initially curtail, then amplify the connection between economic growth and carbon emissions. Conversely, rising energy intensity magnifies the relationship between economic expansion and carbon emissions.

Geopolitical risk and ecological efficiency: A combination approach based on super-efficiency-DEA and extended-STIRPAT models.

Increased geopolitical risks are impacting the sustainable development of the ecological environment. To better understand the impact of geopolitical risk on ecological sustainability, this study develops a research framework for the impact of geopolitical risk on ecological efficiency. (i) Measuring ecological efficiency by data envelopment analysis. (ii) Examining the relationship between geopolitical risks and ecological efficiency using the extended STIRPAT. (iii) Heterogeneity analysis and mediation test were used to further explore the impact mechanism of geopolitical risks. The research results show that: (i) There are obvious differences in the ecological efficiency of countries with different income levels. The ecological efficiency of countries with higher income levels is generally higher, while the ecological efficiency of countries with lower income levels is lower. (ii) Geopolitical risks reduce ecological efficiency, which is bad for ecosystem sustainability. (iii) The magnitude of the adverse impact of geopolitical risks on ecological efficiency is different among different income groups. The negative impact of geopolitical risk on eco-efficiency is worse in high-income countries than in low-income countries.

Impact of income inequality on carbon emissions: a matter of corruption governance.

Corruption is often linked with income inequality and its impact on carbon emissions. This study investigates the moderating effect of corruption governance on the relationship between income inequality and carbon emissions. Panel data for 62 countries from 2012 to 2020 were used. We employed a threshold panel regression approach, considering income inequality as the explanatory variable and carbon dioxide emissions as the dependent variable, with corruption governance as the threshold variable. Our findings suggest that enhancing the level of corruption governance can mitigate the CO2 emissions driven by income inequality. Specifically, we found a shift in the impact on CO2 emissions when corruption governance crosses a certain threshold. This study provides insights into how improving corruption governance can help in managing the environmental effects of income inequality.

Does artificial intelligence (AI) reduce ecological footprint? The role of globalization.

This article explores the impact of artificial intelligence (AI) on global ecological footprints, which has important implications for global sustainability in the digital age. Using the comprehensive evaluation index of AI constructed by the entropy method and the dataset at the global national level, we find that from 2010 to 2019, the overall level of global AI shows an upward trend, in which the growth rate of AI in developed countries is more pronounced and exhibits a stable growth trend, while the growth rate of AI in developing countries displays a trend of instability. The research results show that AI has a significant inhibitory effect on ecological footprints. This conclusion holds even after endogeneity and robustness tests. In addition, under the effect of globalization, the impact of AI on ecological footprints shows nonlinear characteristics. As globalization deepens, the marginal effect of AI in reducing the ecological footprint shows an increasing trend. These findings emphasize the important role of AI in environmental governance and provide a new and comprehensive perspective for policymakers. Therefore, the government should continue to support the research and application of AI, promote the cross-industry integration of AI, and play a positive role in the process of globalization to promote global sustainable development.

Prolonged war reverses carbon emissions from an early decline to a late increase - Evidence from Syria.

Given that war can have a serious impact on the climate, this article is aimed to discuss the impact of warfare on carbon emissions by examining changes in CO2 before and during the war in Syria based on the kaya constant equation and the LMDI decomposition method. In the decade before the war, population was the largest contributor, making up 32.64% of the total 51.02% increase in carbon emissions. The only factor that offsetting carbon emissions was energy intensity, making a 22.30% curbing effect. In the early stage of the war, carbon emissions decreased by 56.38%, in which per capita GDP contributed 37.55% of the total CO2 decline. Carbon intensive of energy was the only factor promoting the carbon increase with a 4.67% contribution. In the late war, carbon emissions start to resume slow increase with energy intensity and economy turning negative to positive. It can be speculated that the impact of the war on CO2 emissions: (i) in the first years of the war, CO2 would drop significantly at the cost of significant population decline and economic recession, the least desirable and the worst way to reduce carbon emissions. (ii) if evolves into a prolonged war, it would reverse carbon emissions from decline to increase, although the population and the economy are both falling. This research, therefore contends that once war is triggered, there is no other solution to prevent this worst-case scenario of Population Decline - Economic Recession - Increased Carbon Emissions from happening, unless the war is stopped immediately.

Do industrial robots reduce carbon intensity? The role of natural resource rents and corruption control.

Although the research on the impact of robotics on carbon emissions is increasing, there are still relatively few studies on the impact of robots on carbon intensity from the perspective of natural resources and corruption. In order to fill in the research gaps, panel data from 66 countries between 1993 and 2018 are collected, and linear and nonlinear panel regression approaches are developed. Natural resource rent and corruption control are used as threshold variables, robot penetration is used as explanatory variables, and carbon emission intensity is the explained variable. The results of the linear model show that robot penetration is negatively correlated with carbon emission intensity, which means that robot penetration reduces carbon emission intensity. The results of the nonlinear model show that when natural resource rents and corruption control are used as thresholds, the relationship between robot penetration and carbon emission intensity presents a U shape and an inverted U shape, respectively. Specifically, the threshold for natural resource rents is 4.7%. When the natural resource rent is lower than this threshold, the robot penetration rate reduces the carbon emission intensity, but when the natural resource rent is higher than this threshold, the robot penetration rate increases the carbon emission intensity. The threshold value of corruption control is -0.4349. When the corruption control is lower than this threshold, the robot penetration rate increases the carbon emission intensity. If the corruption control is higher than this threshold, the robot reduces the carbon emission intensity. Finally, policy recommendations for better use of robotics to reduce carbon emission intensity are put forward from the perspective of natural resource rent and corruption control.

Evolution and driving factors of ocean carbon emission efficiency: A novel perspective on regional differences.

Existing studies on carbon emission efficiency seldom discuss ocean carbon emission efficiency, and few studies on ocean carbon emission efficiency hardly discuss its regional differences. To fill this research gap, this paper innovatively measures and evaluates the ocean carbon emission efficiency of 11 Chinese coastal provinces from 2001 to 2019 using the super-efficiency SBM-GML model, and empirically analyzes the dynamic link between ocean carbon emission efficiency, trade openness and financial development by constructing a PVAR model based on an endogeneity perspective. Meanwhile, another major innovation of this study is to divide China's 11 coastal provinces into two coastal areas, north and south, with the Huaihe River as the boundary, in order to investigate the regional heterogeneity of ocean carbon emission efficiency and its influencing factors. The results show that (i) China's average ocean carbon emission efficiency has improved significantly, which is mainly due to the driving effect of technological progress. (ii) China's ocean carbon emission efficiency generally presents a spatial pattern that is higher in the south and lower in the north. Technological progress is the main source of the improvement in ocean carbon emission efficiency in the two regions. (iii) Significant regional heterogeneity exists in the impact of trade openness and financial development on ocean carbon emission efficiency, that is, trade openness and financial development both promote and hinder ocean carbon emission efficiency in the southern region than in the northern region. Finally, targeted policy recommendations are proposed.

Could the digital economy increase renewable energy and reduce carbon emissions? Empirical research on EKC in 67 countries.

The digital economy is considered important to achieve carbon peaking and carbon neutrality. This paper explores the impact of the digital economy on carbon emissions and renewable energy development using panel data for 67 countries from 2005-2019. The results show that there is an inverted U-shaped relationship between the digital economy and carbon emissions, which is consistent with the Environmental Kuznets Curve (EKC) hypothesis, and a U-shaped relationship with renewable energy consumption, which is consistent with the Renewable energy Kuznets Curve (RKC) hypothesis. Compared with gross domestic product (GDP), the digital economy is more likely to accelerate the process of energy transition and carbon reduction, which is a key factor for carbon peaking. In addition, it is also found that the turning point of the RKC precedes the EKC, which means that the RKC reaching its turning point is a prerequisite for the corresponding EKC to reach its peak.Therefore, the digital economy should be accelerated to push RKC to cross the turning point as soon as possible, thereby accelerating EKC to cross the turning point.

Does renewable energy consumption improve environmental efficiency in 121 countries? A matter of income inequality.

Renewable energy is a key component of the Sustainable Development Goals (SDGs) set by the United Nations, and is an important factor in facilitating the energy transition and carbon neutrality of countries. This study aims to examine the interaction between renewable energy consumption and carbon efficiency to achieve the goal of carbon reduction for environmental sustainability. This study measures the carbon efficiency globally and countries in each income group through the data envelopment analysis method. Then, this study empirically analyzes the impact of renewable energy consumption on carbon efficiency by controlling for heterogeneity, cross-sectional dependence and generalized moments estimation. The results show that (1) carbon efficiency enhances with the increase of income level, and the global carbon efficiency improvement is mainly due to the change of technological progress. (2) There is a weak improvement in scale efficiency in LI and LMI, dragged down by the decline in pure technical efficiency, which is the opposite of countries at higher income levels. (3) Renewable energy consumption has a positive effect on the improvement of carbon efficiency at all income levels, and there is a two-way causal relationship between renewable energy consumption and carbon efficiency. The effect of renewable energy on carbon efficiency is most significant in countries with middle income levels. Policy makers in each country should promote the renewable energy development to achieve energy transition and reduce carbon emissions. In addition, this study emphasizes that countries should consider the interaction between the renewable energy consumption and income level in ensuring sustainable development.

Does environmental regulation improve marine carbon efficiency? The role of marine industrial structure.

With the continuous increase of marine development, intensive economic activities have reduced the marine carbon efficiency and seriously damaged the marine ecological environment, which needs reasonable environmental regulations to guide. This study aims to examine the interactions between marine environmental regulation and carbon efficiency to achieve the goal of carbon emission reduction for the sustainability of marine ecosystem. This study empirically analyzes the heterogeneous effects and mediating effects of China's marine environmental policies on marine carbon efficiency using the mediating effects model and generalized moments estimation. The results show that there is a "U" shaped relationship between marine environmental regulation and marine carbon efficiency in China, marine environmental regulation can indirectly promote marine carbon efficiency through the transmission mechanism of resource allocation efficiency and structural optimization of marine industries. In addition, China's marine environmental regulation policies have regional heterogeneous effects on marine carbon efficiency. This study provides a new perspective for optimizing marine carbon efficiency and sustainable development of marine ecosystem.

Exploring the role of nuclear energy in the energy transition: A comparative perspective of the effects of coal, oil, natural gas, renewable energy, and nuclear power on economic growth and carbon emissions.

Nuclear power has received renewed attention during the energy transition in recent years. This study is aimed to explore whether nuclear energy can promote economic growth without increasing carbon emissions. In order to have a more comprehensive understanding of the relationship between nuclear energy, economic growth, and carbon emissions, this study also discusses the impact of coal, oil, natural gas, and renewable energy on economic growth and carbon emissions. The second-generation panel unit root test, panel cointegration test, panel fully modified ordinary least squares, and Heterogeneous Dumitrescu and Hurlin causality test were used to estimate the long-term elasticity and causality among variables. Results based on panel data from 24 countries with nuclear energy from 2001 to 2020 show that both nuclear energy and renewable energy can curb carbon emissions. Especially in Canada, Finland, Russia, Slovenia, South Korea, and The United Kingdom, nuclear energy reduces carbon emissions more significantly than renewable energy. Meanwhile, there is a positive relationship between increased nuclear energy, increased renewable energy, and economic growth, which means that nuclear energy and renewable energy could increase economic growth as well. There is a positive relationship between increased oil, increased natural gas, and economic growth, while there is a negative relationship between the increase in coal and economic growth. Meanwhile, there is a positive relationship between increased oil, increased coal, and increased carbon emissions, while the positive relationship between increased natural gas and increased carbon emissions is not significant. Thus, in the 22 countries with nuclear power, increased coal consumption does not drive economic growth but increases carbon emissions. Increased oil consumption increases economic growth, but it increases carbon emissions. Increased natural gas consumption boosts economic growth but adds little to carbon emissions. In the authors' view, nuclear power and renewable energy are all options for these nuclear-power countries to pursue economic growth without increasing carbon emissions. Moreover, nuclear power has a better effect on curbing carbon emissions in some countries than renewable energy. Therefore, under the premise of safety, nuclear power should be seriously considered and re-developed.

Financing Constraints and Firm's Productivity Under the COVID-19 Epidemic Shock: Evidence of A-Shared Chinese Companies.

Focusing on the financing barriers to firm productivity improvement under the influence of external shocks, we empirically analyze the data of A-share listed companies from 2007-2018 to determine the impact of financing constraints on total factor productivity (TFP) in the context of COVID-19 pandemic and the paths of factor use efficiency and R&D innovation efficiency on this impact using ordinary least-squares (OLS) method. We find that financing constraints are an important factor inhibiting the TFP of firms. This inhibitory effect is more serious in small-scale firms, non-state firms, and non-energy firms. Further investigation shows that the inhibitory effect of financing constraints on firms' TFP is more pronounced when firms are located in the Yangtze River Delta city cluster, the Pearl River Delta city cluster, non-port cities, and provincial capitals. The mechanism test finds that improving the efficiency of capital use and labor use can alleviate the suppressive effect of financing constraints on TFP. The alleviating impact is more significant when capital use efficiency is improved. However, increasing the efficiency of R&D innovation further strengthens the inhibitory effect of financing constraints, and this effect is more pronounced under positive external shocks.

Nous nous concentrons sur les obstacles liés au financement qui entravent l'amélioration de la productivité des entreprises lorsqu'il y a des chocs externes, et nous analysons de façon empirique l'impact des contraintes de financement sur la productivité globale des facteurs des entreprises dans le contexte de la COVID-19, ainsi que les voies permettant l'efficacité d'utilisation des facteurs et l'efficacité de l'innovation en R&D sur cet impact. Pour ce faire, nous utilisons la méthode des moindres carrés ordinaires en nous basant sur les données de sociétés cotées en bourse de 2007 à 2018. Nous constatons que les contraintes de financement représentent un facteur important qui inhibe la productivité globale des facteurs des entreprises. Cet effet inhibiteur est plus prononcé au sein des petites entreprises, des entreprises non gouvernementales et des entreprises non énergétiques. Une autre étude révèle que l'effet inhibiteur des contraintes de financement sur la productivité globale des facteurs des entreprises est plus prononcé lorsque les entreprises sont situées dans le groupe de villes du delta du fleuve Yangtze, dans le groupe de villes du delta de la rivière des Perles, dans les villes non portuaires et dans les capitales provinciales. Le test du mécanisme révèle que l'amélioration de l'efficacité de l'utilisation du capital et de la main-d'œuvre des entreprises peut atténuer l'effet suppressif des contraintes de financement sur la productivité globale des facteurs. L'impact d'atténuation est plus important lorsque l'efficacité d'utilisation du capital est améliorée. Cependant, l'augmentation de l'efficacité de l'innovation en R&D renforce encore l'effet inhibiteur des contraintes de financement, et il est plus prononcé en cas de chocs externes positifs.

Revisiting the environmental kuznets curve hypothesis in 208 counties: The roles of trade openness, human capital, renewable energy and natural resource rent.

Achieving carbon neutral requires a comprehensive understanding of the effect of different key factors on carbon emissions. To this end, this study investigates the effect of trade openness, human capital, renewable energy and natural resource rent on carbon emissions within the framework of the environmental Kuznets curve (EKC) hypothesis. Second-generation econometric tests, Generalized Method of Moments and Fully Modified Ordinary Least Squares estimator were developed based on the aggregated dataset of 208 countries from 1990 to 2018. The results show that (i) the EKC hypothesis is validated when the effects of trade openness, human capital, renewable energy consumption, and natural resource rents are considered. The relationship between income level and carbon emissions shows an "inverted U-shaped" curve at the global level. Besides, the real GDP per capita corresponding to the EKC turning point is 19,203$. (ii) Renewable energy consumption and human capital have heterogeneous effects on carbon emissions in before- and after-EKC turning points. Specifically, renewable energy consumption has a better emission reduction effect for countries before the EKC turning point, with effects of -0.4334 and -0.1598, respectively; human capital has a better emission reduction effect for countries after the EKC turning point, with effects of -0.6311 and -0.3398, respectively.(iii) the mitigation effect of trade openness on carbon emissions is only effective in countries with weak decoupling after EKC turning points, with a mitigating effect of -0.0615. However, natural resource rents increase carbon emissions in most countries.

Does income inequality reshape the environmental Kuznets curve (EKC) hypothesis? A nonlinear panel data analysis.

The COVID-19 pandemic has further increased income inequality. This work is aimed to explore the impact of income inequality on the environmental Kuznets curve (EKC) hypothesis. To this end, income inequality is set as the threshold variable, economic growth is set as the explanatory variable, while carbon emission is set as the explained variable, and the threshold panel model is developed using the data of 56 countries. The empirical results show that income inequality has changed the relationship between economic growth and carbon emissions from an inverted U-shaped to an N-shaped, which means that income inequality redefines the environmental Kuznets curve and increases the complexity of the decoupling of economic growth and carbon emissions. Specifically, economic growth significantly increases carbon emissions during periods of low income inequality, however, as income inequality increases, economic growth in turn suppresses carbon emissions. In the period of high income inequality, economic growth inhibits the increase of carbon emissions. However, with the increase of income inequality, the impact of economic growth on carbon emission changes from inhibiting to promoting. Panel regressions for robustness tests show that this phenomenon is more pronounced in high-income countries. We therefore contend that the excessive income inequality is bad for the win-win goal of economic growth without carbon emission growth, and the income distribution policy should be included in the carbon neutral strategy.

Uncovering the impact of income inequality and population aging on carbon emission efficiency: An empirical analysis of 139 countries.

Income inequality and carbon emission efficiency are the primary issues that need to be addressed to achieve UN sustainable development goals. However, research on the relationship between income inequality and carbon emission efficiency has not received enough attention. To more comprehensively understand how income inequality affects carbon emission efficiency, and how aging and economic growth affect the relationship between income inequality and carbon emissions efficiency, fixed effect regression estimation and threshold effect regression estimation approaches are developed based on panel data of 139 countries from 1998 to 2018. The results show that: (i) there is an inhibitory effect of income inequality on the improvement of carbon emission efficiency; (ii) under the influence of aging, there is a U-shaped relationship between income inequality and carbon emission efficiency, that is, income inequality has an inhibitory effect on the improvement of carbon emission efficiency before promoting it; (iii) along with the rapid economic growth, the inhibitory effect of income inequality on carbon emission efficiency increases, that is, there is an inverted U-shaped relationship between income inequality and carbon emission efficiency. Finally, we combine the changes in spatial and temporal distributions to propose corresponding policy recommendations.

Revisiting renewable energy and economic growth-Does trade openness a matter?

A significant obstacle to the scaling of renewable energy is the concern that increased consumption of renewable energy could have a negative impact on economic growth, due to the higher cost of renewable energy compared to fossil energy. To examine how exactly renewable energy consumption impacts economic growth, this study uses a non-linear panel threshold model with trade openness, financial development, and per capita income as threshold variables, to analyze the long-term non-linear relationship between renewable energy consumption and economic growth in 28 European Union countries from 2007 to 2017. The results show that (i) renewable energy consumption has significant threshold effect on economic growth. First, the effect of renewable energy consumption on economic growth is positive and significant if and only if it surpasses a certain threshold of trade openness. Second, a moderate financial development interval makes the consumption of renewable energy have a positive effect on economic growth, and if it is too low or too high, it will have a negative effect. Third, as for income level, the promoting effect of renewable energy consumption on economic growth is showing a "stepwise growth" feature, which means, when the income level surpasses its threshold value, the positive effect is strengthened. (ii) The results of the fixed-effects model show that, overall, renewable energy consumption promotes economic growth. (iii) The changes in the number of countries in different threshold intervals indicate that the positive impact of renewable energy consumption on economic growth in the EU is increasing.

Impact of the COVID-19 pandemic on research on marine plastic pollution - A bibliometric-based assessment.

Fighting the COVID-19 pandemic has led to a dramatic increase in plastic waste, which has had a huge impact on the environment, including the marine environment. This work aims to evaluate the pattern of national research cooperation, research hotspots, and research evolution before and during the epidemic by systematically reviewing the publications on marine plastic pollution during 2015-2019 (before the pandemic) 2020-2022 (during the pandemic) using the systematic literature review and latent semantic analysis. The results show (i) Compared to pre-pandemic, publications on marine pollution during the COVID-19 pandemic declined briefly and then increased sharply. (ii) Compared with before the pandemic, the national cooperation model has changed during the pandemic, and four major research centers have been formed: Central European countries centered on Italy; Nordic countries centered on United Kingdom; South Korea, India and other developing countries in Asia and Africa and a Pacific Rim country centered on United States and China. (iii) The knowledge map of keyword clustering does not change significantly before and during the COVID-19: ecosystem, spatial distribution, environmental governance and biodegradation. However, there are differences in the sub-category research of the four types of keywords. (iv) The impact of marine plastic on organisms and the governance of marine plastic pollution have become a branch of knowledge that have evolved rapidly during the pandemic. The governance of marine plastic pollution and microplastics are expected to become an important research direction.

Current status, trends, and predictions in the burden of gallbladder and biliary tract cancer in China from 1990 to 2019.

BACKGROUND: Gallbladder and biliary tract cancer (GBTC) has greatly damaged the health of patients and is accompanied by a dismal prognosis. The worldwide distribution of GBTC shows extensive variance and the updated data in China is lacking. This study was to determine the current status, trends, and predictions in the burden of GBTC over the past 30 years in China. METHODS: This was a descriptive, epidemiological, secondary analysis of the Global Burden of Disease, Injuries, and Risk Factor Study 2019 data. Data including incidence, prevalence, mortality, and disability-adjusted life years (DALYs) of GBTC in China by year, age, and sex were assessed. Joinpoint regression analysis was conducted to evaluate trends of disease burden due to GBTC from 1990 to 2019. Nordpred age-period-cohort analysis was applied for the projection of mortality and incidence due to GBTC from 2019 to 2044. RESULTS: Nationally, there were 38,634 (95% uncertainty interval [UI]: 27,350-46,512) new cases and 47,278 (95% UI: 32,889-57,229) patients due to GBTC, causing 34,462 (95% UI: 25,220-41,231) deaths, and 763,584 (95% UI: 566,755-920,493) DALYs in 2019. Both cases and rates of burden owing to GBTC were heavier among males and at old age. From 1990 to 2019, the age-standardized rates of incidence, prevalence, mortality, and DALYs of GBTC generally increased from 1990 to 2019, with average annual percentage change at 0.8% (95% confidential interval [CI]: 0.6-1.0%), 1.3% (95% CI: 1.1-1.5%), 0.4% (95% CI: 0.2-0.6%), and 0.2% (95% CI: 0.1-0.4%), respectively. Even though the age-standardized incidence rate and age-standardized mortality rate in both sexes were predicted to decline gradually from 2019 to 2044, the number of new cases and deaths were expected to grow steadily. CONCLUSIONS: GBTC is becoming a major health burden in China, particularly among males and older individuals. Given the aging population and increasing burden, effective strategies and measurements are urged to prevent or reduce the number of new cases and deaths of GBTC.

Adaptive-weight water quality assessment and human health risk analysis for river water in Hong Kong.

The water quality of Hong Kong's four water control zones (Tolo Harbour and Channel, Port Shelter, Victoria Harbour, and Junk Bay) is of vital importance and has attracted much attention. This study aims to more objectively and comprehensively assess the water quality and its health impact based on the four-year monitoring data of 21 parameters collected from four zones. First, physicochemical characteristics of the water system were investigated based on multivariate statistical approaches, including Kruskal-Wallis test, hierarchical cluster analysis, and Mann-Kendall test. Then, water quality levels over space and time and the element sources were analyzed using adaptive-weight water quality index (AWQI) method, and factor analysis, respectively. Finally, the potential harm of trace elements for humankind was identified based on the health risk assessment model. The results revealed that (1) the values of more than half of the water quality parameters exhibited significant interannual changes, and the values of all parameters distinctly varied over space; (2) The water quality status in four water control zones showed a steady and long-term improvement trend from 2016 to 2019; (3) The sources of pollution elements impacting water quality status were related to the comprehensive influence of human activities and natural processes; (4) The carcinogenic risks of all trace elements were negligible or acceptable, while Mn and As may cause noncarcinogenic harm to humankind.