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Poorly implemented energy subsidies are economically costly to taxpayers and damage the environment. This report aims at providing the emerging lessons form a representative sample of case studies in 20 developing countries that could help policy makers to address implementation challenges, including overcoming political economy and affordability constraints. The sample has selected on the basis of a number of criteria, including the country’s level of development (and consumption), developing country region, energy security and the fuel it subsidies (petroleum fuel, electricity, natural gas). The case studies were supported by data collection related to direct budgetary subsidies, fuel and electricity tariffs, and household survey data.The analysis provides strong evidence of the success of reforms in reducing the associated fiscal burden. For the sample of countries, the average energy subsidy recorded in the budget was reduced from 1.8% in 2004 to 1.3%GDP in 2010. The reduction of subsidies is particularly remarkable for net energy importers. Pass-through of international fuel prices was also notable in the case of electricity generated by fossil fuel. For the sample of countries, the average end-user electricity tariff increased by 50%, from USD 6 cents in 2002 to USD 9 cents per kWh in 2010.In spite of the relatively price inelastic demand for gasoline and diesel, fossil fuel consumption in the road sector (per unit of GDP) declined in the 20 countries examined from 53 (44) in 2002 to about 23 kt oil equivalent per million of GDP in 2008 in the case of gasoline (Diesel). The most notable decline in consumption was recorded in the low and lower middle income countries. This reflects the much higher rate of growth in GDP in this group of countries and underlines the opportunities to influence future consumption behavior rather than modifying the existing consumption patterns, overcoming inertia and vested interests. Similar trends are recorded for power consumption.While there is no one-size-fits-all model for subsidy reform, implementation of compensatory social policies and an effective communication strategy, before the changes are introduced, reduces helped with the implementation of reforms.

Climate change is recognised as one of the key challenges humankind is facing. The Information and Communication Technology (ICT) sector including data centres generates up to 2% of the global CO2 emissions, a number on par to the aviation sector contribution, and data centres are estimated to have the fastest growing carbon footprint from across the whole ICT sector, mainly due to technological advances such as the cloud computing and the rapid growth of the use of Internet services. There are no recent estimations of the total energy consumption of the European data centre and of their energy efficiency. The aim of this paper is to evaluate, analyse and present the current trends in energy consumption and efficiency in data centres in the European Union using the data submitted by companies participating in the European Code of Conduct for Data Centre Energy Efficiency programme, a voluntary initiative created in 2008 in response to the increasing energy consumption in data centres and the need to reduce the related environmental, economic and energy supply security impacts. The analysis shows that the average Power Usage Effectiveness (PUE) of the facilities participating in the programme is declining year after year. This confirms that voluntary approaches could be effective in addressing climate and energy issue.

The article reviews the existing methods of increasing the energy efficiency of electric transport by analyzing and studying the methods of increasing the energy storage resource. It is grouped according to methods, approaches, and solutions. The most effective methods and ways of their implementation are identified. General methods of increasing energy efficiency, methods of increasing recuperation during braking, methods of energy-efficient energy consumption, the use of energy-saving technologies, and improving the energy efficiency of the traction drive are considered. The purpose of this work is to identify the main operating factors on the basis of a critical review of existing methods for assessing the technical condition of batteries and experimental results on the degradation of lithium-ion batteries. Using the great experience of the research group in the field of modeling, diagnostics, and forecasting of life of electric cars, as well as their intellectual management, the new theoretical and practical methods of integrated assessment of the parameters of the traction battery and state of charge, which are operated in the heavy forced regenerative regimes of electric traction, are created and proposed. A great role is played by the construction of the transport model. The development is based on physical laws that passengers and vehicle owners are unaware of. For each model there is a different area of application, and what is suitable for one object may not be suitable for another. The overview shows that there is no one-size-fits-all way to improve energy efficiency. It is necessary to make a choice among several proposed models after a thorough feasibility study.

Deploying green energy is, directly and indirectly, related to energy- and environment-related sustainable development goals (SDGs). This study uses the stochastic impact by regression on the population, affluence, and technology (STIRPAT) model to examine the relationship between CO2 emissions, energy efficiency, green energy index (GEI), and green finance in the top ten economies that support green finance. The results show that green bonds are a suitable method to promote green energy projects and reduce CO2 emissions significantly. At the same time, there is no causal linkage between these variables in the short term. Therefore, to achieve sustainable economic growth for environmental issues, governments should implement supportive policies with a long-term approach to boost private participation in the investment of green energy projects. This policy may be applicable during and in the post the COVID-19 era when green projects have more difficulties accessing finance.

The household sector is one of the most energy-intensive sectors in Europe, and thus a focal point for reducing greenhouse gas emissions associated with energy consumption. Energy efficiency is considered a key measure to reduce household energy consumption, but several factors could lead to an underinvestment in energy efficiency. This is the so-called energy efficiency gap or paradox. The factors in question are grouped under market failures (including informational failures), behavioural failures and other factors. Various policies can be used to address these failures and promote the adoption of energy-efficient technologies, including energy standards and codes, economic incentives and information instruments. This paper reviews the empirical evidence to date on energy efficiency policies and discusses their effectiveness. On the one hand, command and control instruments seem to be effective policies, but they have to overcome several barriers. In the case of price instruments, subsidies and taxes do not seem to be effective while rebates present mixed results as they sometimes are effective and in other cases, they could present significant shortcomings. Finally, the effectiveness of informational policies is not always ensured as they depend on the country, sector and product category. Information feedback tools also seem to be effective as they work as a constant reminder of energy-efficient behaviour. Some limitations of energy efficiency policies are also identified, such as the difficulties of implementing codes and standards given that a minimum level need to be achieved, differences in the effectiveness of rebate programmes and non-conclusive results in regard to the effectiveness of monetary energy efficiency labels.

Policymakers and environmental scientists have proposed numerous measures toward achieving a sustainable environment. Some of these measures include the efficient use of energy and a clean energy transition. This study empirically investigates the role of non-renewable energy efficiency and renewable energy utilization in driving environmental sustainability in India over the period from 1965 to 2018. Using the approach of the Dynamic Autoregressive Distributed Lag (DyARDL) simulations, the empirical evidence shows that non-renewable energy efficiency and renewable energy utilization promote environmental sustainability through an increase in the load capacity factor. The effects of financial development and trade impede environmental sustainability through a decrease in the load capacity factor. The results further show that the relationship between income and load capacity factor is characterized by an inverted U-shape. This suggests that the load capability curve (LCC) hypothesis is not valid for India. Given the overall findings of this study, it is suggested that policymakers should promote energy efficiency and renewable energy technologies as the ultimate policy measure to mitigate the accumulation of CO2 emissions and other significant climatic changes in India.

The purpose of the study is to test the role of green bond financing on energy efficiency investment and economic growth. To achieve the study objective, fuzzy decision-making modeling technique is applied. The results revealed that bank loans are now the main source of financing for energy efficiency projects. Project-based financing might be replaced with Energy Performance Contracts (EPC) warranting energy efficiency investment. Moreover, green banks invest both public and private funds in energy efficiency promoting economic growth. The usage of green bonds for financing environmentally beneficial projects or companies is limitless. Providing for screening energy efficiency investment proposals with small payback hurdle rates might have large opportunity costs. Green bonds can be used to remove the financing barriers for green finance and sustainability tool. On this, study provides policy implications to key stakeholders; if suggested policy suggestions implemented successfully, these would help to enhance scope of green bond financing to uplift energy efficiency financing and green growth successfully.

This study delves into the multifaceted landscape of energy efficiency management with the objective of rationalizing the utilization of energy resources. The article considers a methodical approach to the study of the level of energy intensity of economic activity, covering levels of management, from the macro level to the level of an individual enterprise. In general, it is advisable to supplement the proposed approach with existing methods that extend the content to the results of energy efficiency research. Using the Life Cycle Assessment (LCA) method and other methodologies, we explore various dimensions of energy resource utilization and the scale of energy efficiency management across different stages of the lifecycle. Additionally, the study introduces levels of energy efficiency management developed by the authors, providing a structured framework for optimizing energy use. Through rigorous analysis, we evaluate the environmental impacts, energy consumption patterns, and efficiency levels associated with diverse energy management strategies. Our findings illuminate key areas for improvement and optimization in energy utilization practices, offering insight beneficial for policymakers, industry stakeholders, and environmental advocates alike. By leveraging the comprehensive framework of LCA alongside the developed levels of energy efficiency management, this research contributes to a nuanced understanding of energy efficiency management, thereby facilitating informed decision-making towards sustainable energy utilization pathways. Examining the example of building the life cycle of gas production and highlighting the main stages of its transformation from a raw resource to a finished product for consumption allows for the consideration of the entire chain of creation of the added value of this energy resource and enables control of the level of its influence on the results of the activities of economic units involved in this chain, as well as the consequences of their impact on the environment. This allows us to conclude that the approach discussed in the article can be used both for researching the energy efficiency of individual enterprises, as well as their associations, industries, and the economy in general.

Despite strong political efforts in Europe, industrial small- and medium-sized enterprises (SMEs) seem to neglect adopting practices for energy efficiency. By taking a cultural perspective, this study investigated what drives the establishment of energy efficiency and corresponding practices in SMEs. Based on 10 ethnographic case studies and a quantitative survey among 500 manufacturing SMEs, the results indicate the importance of everyday employee behavior in achieving energy savings. The studied enterprises value behavior-related measures as similarly important as technical measures. Raising awareness for energy issues within the organization, therefore, constitutes an essential leadership task that is oftentimes perceived as challenging and frustrating. It was concluded that the embedding of energy efficiency in corporate strategy, the use of a broad spectrum of different practices, and the empowerment and involvement of employees serve as major drivers in establishing energy efficiency within SMEs. Moreover, the findings reveal institutional influences on shaping the meanings of energy efficiency for the SMEs by raising attention for energy efficiency in the enterprises and making energy efficiency decisions more likely. The main contribution of the paper is to offer an alternative perspective on energy efficiency in SMEs beyond the mere adoption of energy-efficient technology.

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy efficiency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most effective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy efficiency at a very early design stage. On the other hand,efficient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, artificial intelligence (AI) in general and machine learning (ML) techniques in specific terms have been proposed for forecasting of building energy consumption and performance. This paper provides a substantial review on the four main ML approaches including artificial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance.