• Energy Research
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In this study, we investigated the influence of overall financial development and its components on energy consumption using the panel data of 120 countries and the generalized method of moments (GMM). By dividing the sample into developed and developing countries, we further examined the national differences of the impact of financial development on energy consumption. The empirical results indicate that the overall financial development significantly positively impacts energy consumption from a worldwide perspective, and its two components (financial institution and the financial market) have the same effect. The analysis of national differences indicates that the financial development also positively impacts energy consumption in developing countries but with no obvious effect in developed countries. The results also suggest that financial development cannot be used to restrain the increase in energy consumption from the global perspective, and policymakers in developing countries must balance the relationship between the development of the financial sector and energy consumption.

This study aims to explore the application of fractional order chaotic system (FOCS), based on the T-S fuzzy model, in the design of secure communication (SC) and this SC system’s role in the construction of efficiency evaluation system for dispatching operation of energy saving and power generation under a low carbon economy (LCE). First, the definition of fractional order differential equations and the stability theory of FOCS are discussed. T-S fuzzy control is introduced to analyse the stability of FOCS. Then, based on the adaptive synchronisation theory, the combined FOCS is designed for SC, and the performance of the system constructed here is analysed in a MATLAB environment. Next, an evaluation index system of the dispatching operation effect of energy saving and power generation under LCE is constructed. The confidential communication system constructed here is used to transmit the index data. The particle swarm optimisation (PSO) algorithm is then used to optimise the back propagation neural network (BPNN) model. The BPNN algorithm based on PSO (PSO-BPNN) is obtained, and the evaluation model is constructed. After training this model, it is applied to the evaluation of the dispatching operation effect for energy saving and power generation in 10 provinces in China. The simulation results show that the FOCS based on the T-S fuzzy model can acquire the criterion of system stability. Furthermore, the constructed SC system can effectively undertake the secure transmission of square and sine waves. The performance of the PSO-BPNN model seems to be better than other algorithms. After analysing the data on energy saving and power generation from 10 provinces in China using this model, the comprehensive evaluation value of province 5 is found to be the highest and good (0.802), while that of province 4 is the lowest and general (0.600). Summarising, the FOCS based on T-S fuzzy model constructed here is applied to the design of SC. This can improve the confidentiality of data transmission and reduce the transmission error. Moreover, the BPNN evaluation model based on PSO can effectively achieve the evaluation of the dispatching operation effect of energy saving and power generation under LCE.

Abstract The Chinese government has taken measures to realize energy-savings and emission reductions, such as promoting innovations, adjusting the industrial structure, balancing regional development, and reforming markets. The aim of this paper is to assess the effects of these measures on China's CO2 emissions by using a newly proposed decomposition approach, which identified eight new factors related to the above realistic measures, i.e., energy saving and production technologies, industrial energy and production efficiencies, regional energy and production efficiencies, and pure energy and production efficiencies. The main findings indicate benefits from considerable technological progress in energy-saving and production during 2000–2016 period, and two technological factors contributed the most to emissions abatement and cumulatively reduced 5372.43 Mt and 1291.72 Mt CO2 emissions. The efforts of industrial restructuring promoted energy and production efficiency improvement, which further facilitated emission reduction. In contrast, the pure energy and production efficiency changes cumulatively led to 1080.26 Mt and 1135.85 Mt CO2 emissions growth during the whole sample period, suggesting that severe resource misallocation problems may exist in both the energy market and output market. Additionally, the Chinese government failed to narrow the technology gap between developed regions and underdeveloped regions, further restricting emission reduction.

This dataset currently consists of a single excel file which contains the Scottish Social Accounting Matrix for 2013, with households being disaggregated into quintiles based on their weekly income. The dataset has been used to study the impact of Energy Efficient Scotland programme and associated work that explored how the anticipated impacts may change due to Brexit

The increasing depletion of natural resources, combined with a wider set of pressures on the environment, has, in recent years, highlighted the need for a more efficient use of energy and a development process that involves alternative energy sources. Energy efficiency has received much attention as a solution, implying both monetary and emissions savings. However, the latter may be partially offset by the income and demand effects of the former, both in more efficient sectors and in spreading to the wider economy. This is the problem of rebound effects. Taking Spain as a case study, and introducing an energy-related CGE model that develops the inclusion of renewables, this paper evaluates a combination of efficiency initiatives to deliver both reduced energy use by households and a more sustainable supply of energy. Our findings suggest that a package aimed at improving efficiency in household electricity and petroleum use, combined with a more competitive supply of energy from renewable sources, may be the only way to get reductions in all energy use, and thus benefit the economy. Specifically, we consider how this package may lead to positive economic impacts and associated rebound effects, where the latter are focused on a greener energy supply.

Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results. Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

Abstract Numerous countries have set up strategic petroleum reserves (SPRs) in response to oil disruptions since 1970. While numerous studies model such programs, we found few that evaluate SPRs' historical performance. Thus, we evaluate the U.S. SPR's performance by comparing actual real costs with estimated real benefits. From 1976 to 2014, the real U.S. SPR cost was about $219 billion real (2014$) dollars, whereas the real benefit was only $122 billion. Sensitivity testing suggests such negative net benefits are qualitatively robust. However, if world oil demand is extremely inelastic to oil price or GDP is elastic enough to oil price shocks, the estimated U.S. SPR net benefit is positive. Sensitivity testing around total real costs and benefits range from $380 billion to $80 billion. Limited testing of IEA coordinated drawdowns suggests that total U.S. benefits jump from $122 billion to more than $400 billion putting the SPR strongly in the black. Limited testing of private sector inventory changes was more disappointing and tentatively suggests private activities may at times have offset some of the government drawdowns. With 20-20 hindsight, initial experimentation found that better management could have significantly enhanced the value of the U.S. SPR, especially for the 1990-91 disruption.