Examining the dynamics between economic development, tourism, renewable energy and life expectancy in the Nordic economies.

As the world struggles with pressing issues like climate change and sustainable development, affecting health outcomes and environmental quality, the Nordic regionsare at the forefront of major global challenges. This paper investigates the role of human capital, renewable energy use, tourism, natural resources, and economic growth in shaping life in the Nordic region i.e., Denmark, Norway, Sweden, Finland, and Iceland).Utilizing panel data spanning from 1990 to 2020, the Driscoll and Kraay standard error (DSK) technique is employed to analyze this intricate interplay. The study reveals that in the Nordic context, sustainable economic growth, bolstered by investments in human capital and the widespread acceptance of renewable energy sources, has been positively associated with increased life expectancies. Furthermore, prudent management of natural resources has helped mitigate adverse health effects related to depletion, maintaining environmental and public health standards. The thriving tourism industry has also been shown to influence lifespan in this region positively. On the contrary, the empirical finding contended that an adverse correlation exists between carbon emissions and LEX. This research underscores the importance of a comprehensive and balanced approach that considers economic development, sustainable development, and public health in pursuing longer and healthier lives, providing valuable insights for policymakers and regions seeking to replicate these positive outcomes.The findings of this study are both conceptually reliable and empirically robust, providing important insights for the formulation of environmental and health policy.

Carbon pricing policies and renewable energy development: Analysis based on cross-country panel data.

While studies have theoretically discussed the impact of carbon pricing on renewable energy, the practical implementation and effectiveness of these policies remain uncertain. This study empirically examines the role of carbon emissions trading and carbon tax in global renewable energy development using panel data from 196 countries and regions and employing the staggered difference-in-differences (DID) model and Bacon decomposition method. The results suggest that: (1) From the perspective of policy shocks, carbon trading has increased non-hydro renewable electricity generation by 73.32%, while carbon tax has increased it by 31.79%. This indicates that the overall impact of carbon trading on renewable energy is greater than that of carbon tax. However, the elasticity coefficients of renewable energy to carbon trading prices and carbon tax rates are 0.1801 and 0.1845, respectively, suggesting a slightly greater marginal effect of carbon tax on renewable energy compared to carbon trading. (2) Both carbon tax and carbon trading have mitigated the growth of fossil electricity and encouraged public investment in renewable energy, thereby fostering its development. (3) The influence of carbon pricing on renewable energy varies by income level; notably, the implementation of these policies in high-income countries has diminished their promotional effect on renewable energy. (4) The contribution of technological innovation to renewable energy development is smaller than that of policies including carbon trading and carbon tax, indicating that renewable energy development during the sample period was predominantly driven by policy measures. The findings indicate that the application of carbon pricing policies should be further promoted to accelerate the energy mix transition.

Decoding worldwide efficiency: Linking government spending, corruption, gender inequality, and renewable energy practices.

Countries have become increasingly concerned about the impact of their activities and their alignment with sustainable development goals. Consequently, it is necessary to examine their performance efficiency in a unified manner, accounting for economic, environmental, and social variables. A country's performance efficiency is defined as the ratio of observed output to frontier output, given the country's productive resources. In this paper, we use the frontier technique of Data envelopment analysis (DEA) to estimate the frontier output. The objective of this study is to assess the performance efficiency of 111 worldwide countries and to examine whether gender inequality, the share of renewable energy consumption, the government control of corruption and government expenditure on education could explain differences in performance. We employed the non-parametric DEA model using three inputs (capital, labor, and primary energy consumption) and one output (GDP). We also considered an additional output (CO2 emissions); however, the results were identical to the one output model because CO2 emissions and primary energy consumption are highly correlated (0.96). We find that there is a negative impact of gender inequality, a positive impact of the share of renewable energy consumption and government control of corruption on performance efficiency. Our results also indicate that reducing CO2 emissions required transitioning towards renewable energy and using the energy efficiently. However, we did not find a positive relationship between government expenditures on education and country efficiency.

Impact of crop rotation and tillage operations on mitigating greenhouse gas emissions and evaluation of sustainability index in rice- wheat-green gram cropping system of north Bihar.

In North Bihar (NB), the conventional rice-wheat cropping system has led to soil, water, and environmental degradation, alongside low profitability, threatening sustainability. To address these concerns, a thorough field research was conducted over the course of three years to assess different methods of tillage and crop establishment in a rice, wheat, and greengram cycle. The experiment involved five scenarios with different combinations of crop rotation, tillage techniques, seeding procedures, fertilizer use, and irrigation strategies. Uncertainty analysis showed no significant change in mean and variance estimation among seven scenario replications at 5% significance level. Compared to traditional farming (SN-1), managing DSR-rice (SN-5) increased profitability by 17.56%, improved energy use efficiency (EUE) by 32.16%, and reduced irrigation by 24.76% and global warming potential (GWP) by 23.46%. Similarly, substituting zero tillage wheat (ZTW) SN-5 resulted in comparable profitability gains (18.25%) and significant improvements in irrigation (10 %), EUE (+48.65%), and GWP (-20 %) compared to SN-1. Green gram ZT also showed increased profitability (17.35%), with notable improvements in EUE (+38.31%) and GWP (-12.92%) compared to SN-1. Principal component and correlation analyses revealed relationships between total energy inputs, yields, economic returns, and sustainability indices, highlighting the benefits of crop rotation and tillage practices in optimizing resource use. The study suggests that compared to conventional systems, significant improvements in productivity, profitability, energy-use efficiency, and environmental mitigation can be achieved with Crop Rotation and Tillage Operations techniques.

A Low-Carbon and Economic Dispatch Strategy for a Multi-Microgrid Based on a Meteorological Classification to Handle the Uncertainty of Wind Power.

In a modern power system, reducing carbon emissions has become a significant goal in mitigating the impact of global warming. Therefore, renewable energy sources, particularly wind-power generation, have been extensively implemented in the system. Despite the advantages of wind power, its uncertainty and randomness lead to critical security, stability, and economic issues in the power system. Recently, multi-microgrid systems (MMGSs) have been considered as a suitable wind-power deployment candidate. Although wind power can be efficiently utilized by MMGSs, uncertainty and randomness still have a significant impact on the dispatching and operation of the system. Therefore, to address the wind power uncertainty issue and achieve an optimal dispatching strategy for MMGSs, this paper presents an adjustable robust optimization (ARO) model based on meteorological clustering. Firstly, the maximum relevance minimum redundancy (MRMR) method and the CURE clustering algorithm are employed for meteorological classification in order to better identify wind patterns. Secondly, a conditional generative adversarial network (CGAN) is adopted to enrich the wind-power datasets with different meteorological patterns, resulting in the construction of ambiguity sets. Thirdly, the uncertainty sets that are finally employed by the ARO framework to establish a two-stage cooperative dispatching model for MMGS can be derived from the ambiguity sets. Additionally, stepped carbon trading is introduced to control the carbon emissions of MMGSs. Finally, the alternative direction method of multipliers (ADMM) and the column and constraint generation (C&CG) algorithm are adopted to achieve a decentralized solution for the dispatching model of MMGSs. Case studies indicate that the presented model has a great performance in improving the wind-power description accuracy, increasing cost efficiency, and reducing system carbon emissions. However, the case studies also report that the approach consumes a relative long running time. Therefore, in future research, the solution algorithm will be further improved for the purpose of raising the efficiency of the solution.

Microbiology challenges and opportunities in the circular economy.

Our knowledge and understanding of micro-organisms have led to the development of safe food, clean water, novel foods, antibiotics, vaccines, healthier plants, animals and soils, and more, which feeds into the United Nations Sustainable Development Goals (UN SDGs). The circular economy can contribute to the UN SDGs and micro-organisms are central to circular nutrient cycles. The circular economy as described by the Ellen MacArthur foundation has two halves, i.e. technical and biological. On the technical side, non-biological resources enter manufacturing paths where resource efficiency, renewable energy and design extend the life of materials so that they are more easily reused and recycled. Biological resources exist on the other half of the circular economy. These are used to manufacture products such as bioplastics and paper. The conservation of nature's stocks, resource efficiency and recycling of materials are key facets of the biological half of the circular economy. Microbes play a critical role in both the biological and technical parts of the circular economy. Microbes are key to a functioning circular economy, where natural resources, including biological wastes, are converted by microbes into products of value and use for society, e.g. biogas, bioethanol, bioplastics, building block chemicals and compost for healthy soils. In more recent times, microbes have also been seen as part of the tool kit in the technical side of the circular economy, where microbial enzymes can degrade plastics and microbes can convert those monomers to value-added products.