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Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

This chapter uses data on Intended Nationally Determined Contributions (INDCs) to examine the nature of climate change mitigation and adaptation actions being pursued in African countries and assesses the extent to which preferred mitigation and adaptation priorities advance the cause of sustainable development on the continent. The prospective synergies between mitigation and adaptation approaches and sustainable development are assessed. Also, the pathways through which resource constraints and institutional and policy environment affect Africa’s ability to mitigate and adapt to climate change are examined, as well as the degree to which these constraints are being addressed. It is argued that Africa’s ability to benefit from sustainable development synergies embedded in the mitigation and adaptation strategies in the INDCs will be greatly limited by institutional and policy environment that hinders funding, capacity building, and technological innovation systems development. The slow pace of efforts to address these impediments further erodes confidence that climate adaptation in Africa will be effective at sufficiently contributing to a reduction in climate change risks to the continent.

Abstract With the rapid rise of installed nuclear power in China, meeting the increasing demands on natural uranium and rationally treating the vast spent fuel are essential issues for the sustainable development of Chinese nuclear power industry. This paper discusses four most potential nuclear fuel cycle modes in China and analyzes the natural uranium requirements under these different fuel cycle modes first based on three development patterns (low-, medium-, and high-speed) of installed nuclear power capacity. Then, an optimization model including natural uranium requirements, spent fuel final disposal amounts and total cost of electricity generation is constructed and optimization problem under two scenarios of reprocessing capacity are solved and results discussed. The annual and cumulative natural uranium requirements under these two scenarios are also calculated. Finally some conclusions are put forward based on the analyses.

The macroalgal industry is expanding, and the quest for novel ingredients to improve and develop innovative products is crucial. Consumers are increasingly looking for natural-derived ingredients in cosmetic products that have been proven to be effective and safe. Macroalgae-derived compounds have growing popularity in skincare products as they are natural, abundant, biocompatible, and renewable. Due to their high biomass yields, rapid growth rates, and cultivation process, they are gaining widespread recognition as potentially sustainable resources better suited for biorefinery processes. This review demonstrates macroalgae metabolites and their industrial applications in moisturizers, anti-aging, skin whitening, hair, and oral care products. These chemicals can be obtained in combination with energy products to increase the value of macroalgae from an industrial perspective with a zero-waste approach by linking multiple refineries. The key challenges, bottlenecks, and future perspectives in the operation and outlook of macroalgal biorefineries were also discussed.

We describe the background and an analytical framework for a mathematical optimization model for home energy management systems (HEMS) to manage electricity demand on the smart grid by efficiently shifting electricity loads of households from peak times to off-peak times. We illustrate the flexibility of the model by modularizing various available technologies such as plug-in electric vehicles, battery storage, and automatic windows. First, the analysis shows that the end-user can accrue economic benefits by shifting consumer loads away from higher-priced periods. Specifically, we assessed the most likely sources of value to be derived from demand response technologies. Therefore, wide adoption of such modeling could create significant cost savings for consumers. Second, the findings are promising for the further development of more intelligent HEMS in the residential sector. Third, we formulated a smart grid valuation framework that is helpful for interpreting the model's results concerning the efficiency of current smart appliances and their respective prices. Finally, we explain the model's benefits, the major concerns when the model is applied in the real world, and the possible future areas that can be explored.

Abstract The transition of energy structure to renewable energy is a social and systematic engineering that requires complex regional power interconnection as a support. Thus, an assessment of the economic viability of infrastructure investments for supporting such transmission expansion is crucial. This study presents a multi-regional power system optimization model to evaluate the potential economic benefits of infrastructure investments for the national inter-regional electricity network in China under various scenarios in the context of low-carbon transformation. Key factors influencing economic benefits are analyzed specifically and regulation barriers associated with inter-regional electricity trade are given particular attention. The results show that approximately 140 Giga Watt (GW) of infrastructure construction for the inter-regional electricity trade network is economically viable during the planning horizon. These new interconnections would lead to 250–440 billion RMB of economic benefits. Regional electricity trade barriers caused by imperfect market mechanisms have a negative impact on the economic benefits of transmission infrastructure investments, although they promote scale and utilization efficiency in the power sector of electricity-importing regions. Improving the national grid coordination mechanism to break the grid isolation between the State Grid Corporation of China and the China Southern Power Grid is crucial, because a large number of transmission lines connecting these two national-level power grids are economically viable.

Abstract In modern developed economies, one of the primary objectives is to manage the transition from polluting to cleaner technologies as efficiently as possible. By now, in the current empirical literature, one can identify technological spillovers from environmental innovations as a major driver of this process. Specific energy policy aspects connected with industry behaviour have yet to be explored. The aim of this paper is to investigate energy efficiency via environmental innovation and the resulting degree of resilience and adaptation of both developed and developing countries. The work applies the non-parametric DEA (Data Envelopment Analysis) framework and Tobit analysis. For this scope, it is built a panel dataset made of some 5000 observations based on energy policy and sustainable development variables for 136 OECD and non-OECD countries. The results show that knowledge spillovers from environmental innovations reduce inefficiency and therefore strengthen the resilience of economies that decide and manage to invest adequately in the transition to more sustainable technologies. Besides, OECD countries improve their energy efficiency scores over time, whilst non-OECD countries do not. This implies that sustainable technologies transition is made more efficient by environmental innovation but the process is fostered by disposing of a resilient economic system – hence, vulnerability can affect the transition. These hypotheses lead to important economic, social and environmental implications for energy policy modelling.

About 11 years ago, the U.S. Department of Energy (DOE) funded the Pacific Northwest National Laboratory (PNNL) to conduct one of the first field demonstrations of what later was called a transactive system. Transactive systems have since become important tools in the DOE?s research efforts to modernize the U.S. electric power grid and conserve energy in U.S. buildings. The DOE currently funds fundamental and applied research to advance transactive system technologies, including their simulation, standardization, theoretical principles, valuation, demonstration, and automation. This article will discuss the historical and current DOE research and development activities in this topic area, including a recent PNNL report concerning the valuation of transactive systems.

Identifying the drivers of carbon dioxide emissions in the manufacturing industry is vital for developing effective environmental policies. This study adopts provincial panel data from 2000 to 2013 and uses nonparametric additive regression models to analyze the drivers of CO2 emissions in the industry. The results show that the nonlinear effect of economic growth on CO2 emissions supports the Environmental Kuznets Curve (EKC) hypothesis. Energy structure has an inverted “U-shape” effect owing to massive coal consumption in the early stages and the optimization of energy structure in the later stage. The inverted “U-shaped” impact of industrialization may be due to the priority development of heavy industry in the early stages and the optimization of industrial structure in the later stages. The impact of urbanization also exhibits an inverted “U-shaped” pattern because of mass consumption of steel and cement products in the early stages and the advancement in clean energy technologies at the later stages. However, specific energy consumption has a positive “U-shaped” impact because of the difference in the speed of technological progress at different times. Thus, the differential effects of these indicators at different times should be taken into consideration when discussing reduction of CO2 emissions in China's manufacturing industry.