Optimizing renewable-based energy supply options for power generation in Ethiopia.

Ethiopia unveiled homegrown economic reform agenda aimed to achieve a lower-middle status by 2030 and sustain its economic growth to achieve medium-middle and higher-middle status by 2040 and 2050 respectively. In this study, we evaluated the optimal renewable energy mix for power generation and associated investment costs for the country to progressively achieve upper-middle-income countries by 2050. Two economic scenarios: business as usual and Ethiopia's homegrown reform agenda scenario were considered. The study used an Open Source energy Modeling System. The model results suggest: if projected power demand increases as anticipated in the homegrown reform agenda scenario, Ethiopia requires to expand the installed power capacity to 31.22GW, 112.45GW and 334.27GW to cover the current unmet and achieve lower, medium and higher middle-income status by 2030, 2040 and 2050 respectively. The Ethiopian energy mix continues to be dominated by hydropower and starts gradually shifting to solar and wind energy development towards 2050 as a least-cost energy supply option. The results also indicate Ethiopia needs to invest about 70 billion US$ on power plant investments for the period 2021-2030 to achieve the lower-middle-income electricity per capita consumption target by 2030 and staggering cumulative investment in the order of 750 billion US$ from 2031 to 2050 inclusive to achieve upper-middle-income electricity consumption rates by 2050. Ethiopia has enough renewable energy potential to achieve its economic target. Investment and financial sourcing remain a priority challenge. The findings could be useful in supporting decision-making concerning socio-economic development and investment pathways in the country.

The Energy Efficiency and Public Health in the ASEAN Plus Three Cooperation.

This study pays more attention to the energy consumption saving, environmental pollution, and health efficiency improvement. We employ the Slack-based measure of Dynamic network Data Envelopment Analysis (DEA) model (DNSBM) to assess the impact of forestry area on annual and overall energy and health efficiency in 2 intertemporal stages, and also put forward on direction and magnitude to be improved respect to the slack variables. For the empirical study, this study employs the 13 countries in the Association of Southeast Asian Nations Plus Three Cooperation (hereinafter referred to as APT) during 2011-2015. From the empirical evidence, it is not easy to raise gross domestic product while reducing energy consumption and PM2.5 emissions to improve energy efficiency. What makes people neglect is the impact of reduced forestry area on health efficiency. Optimistically, all economies are able to adopt measures from policy and technical perspectives, for instance, appropriately adjust energy-related policies, energetically develop innovative energy technologies, and preserve forestry areas, to create a harmonious atmosphere featuring economic development, environmental conservation, and national health and well-being.

Per capita income, trade openness, urbanization, energy consumption, and CO2 emissions: an empirical study on the SAARC Region.

The developing world in general is facing so many crucial problems including global warming in recent years. Global warming has multiple consequences on each segment of the society and therefore, its root causes are important to identify. The present study examines the impact of per capita income, trade openness, urbanization, and energy consumption on CO2 emissions. Countries located in South Asian Association for Regional Cooperation (SAARC) are considered in the study. The selection of the SAARC region is motivated by the diverse nature of its members and further lack of available empirical literature on the same relationship. Annual data from 1980 to 2016 are analyzed using appropriate panel data techniques. The results revealed the presence of environmental Kuznets curve (EKC) in the SAARC region. Further, the introduction of cubic function into the model indicated that the shape of the EKC is N shaped. Besides, trade openness has negative while urbanization and energy consumption have impacted CO2 emissions positively. Moreover, the causality exercise explored a bidirectional causality between urbanization, energy consumption, per capita income, and CO2 emissions. Similarly, energy consumption, per capita GDP, and urbanization are also bidirectionally related. Further, a unidirectional causality running from CO2 emissions, urbanization, and energy consumption to trade openness is detected. Lastly, a unidirectional causality is witnessed from per capita income to energy consumption.

Identification and analysis of driving factors of CO2 emissions from economic growth in Pakistan.

This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO2 emissions over the period 1990-2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved.

Decoupling effect and forecasting of economic growth and energy structure under the peak constraint of carbon emissions in China.

The decoupling effect between economic growth and energy structure was quantitatively analyzed from 1999 to 2014 across China. The results showed it existed weak decoupling effects in most regions. Based on the analysis of the influence of energy structure on carbon intensity, using scenario simulation methods and Markov chain modeling, the carbon intensity was predicted for China in 2020. The impact of energy structure adjustment on the carbon intensity to meet China's carbon target by 18 possible scenarios are calculated. Furthermore, the peak value of carbon emissions was also calculated in 2030. The results showed that the carbon intensity predicted for China in 2020 can be achieved regardless of whether the energy structure was adjusted or not when energy saving and carbon reduction policies maintained with economic growth at 6-7%. Moreover, given fixed energy structure growth, for each 1% of economic growth, the carbon intensity will decrease by about 3.5%. Given fixed economic growth, the decrease of energy intensity will be greater if the control of energy consumption is stronger. The effect of energy structure adjustment on the decreasing of carbon intensity will be 4% higher under constraints than without constraints. On average, the contribution of energy structure adjustment to achieving the carbon intensity target was calculated as 4% higher than that with constraints. In addition, given relatively fixed economic growth at 6-7%, the peak value of carbon emission in 2030 was calculated as 13.209 billion tons with constraints and 14.38 billion tons without constraints.

Assessing links between energy consumption, freight transport, and economic growth: evidence from dynamic simultaneous equation models.

We investigate this study to examine the relationship between economic growth, freight transport, and energy consumption for 63 developing countries over the period of 1990-2016. In order to make the panel data analysis more homogeneous, we apply the income level of countries to divide the global panel into three sub-panels, namely, lower-middle income countries (LMIC), upper-middle income countries (UMIC), and high-income countries (HIC). Using the generalized method of moments (GMM), the results prove evidence of bidirectional causal relationship between economic growth and freight transport for all selected panels and between economic growth and energy consumption for the high- and upper-middle income panels. For the lower-middle income panel, the causality is unidirectional running from energy consumption to economic growth. Also, the results indicate that the relationship between freight transport and energy use is bidirectional for the high-income countries and unidirectional from freight transport to energy consumption for the upper-middle and lower-middle income countries. Empirical evidence demonstrates the importance of energy for economic activity and rejects the neo-classical assumption that energy is neutral for growth. An important policy recommendation is that there is need of advancements in vehicle technology which can reduce energy intensity from transport sector and improve the energy efficiency in transport activity which in turn allows a greater positive role of transport in global economic activity.

The nexus between energy consumption and financial development: estimating the role of globalization in Next-11 countries.

In the modern era of globalization, the economic activities expand with the passage of time. This expansion may increase demand for energy both in developing and developed countries. Therefore, this study assesses the impact of financial development on energy consumption incorporating the role of globalization in Next-11 countries. A group of panel estimation techniques is used to analyze the panel data and time series data for the time 1990-2014. The empirical results of the study suggest that financial development stimulates energy consumption. Also, globalization increases demand for energy consumption, although the single country analysis suggests that the effect of globalization on energy demand is heterogeneous among N-11 countries. Furthermore, feedback hypothesis is confirmed between financial development and energy consumption. Also, bidirectional causality is found between economic growth and energy consumption. The findings urge for the attention of policymaker in emerging countries to develop a strategy to reduce the consequences of energy consumption by controlling resource transfer through globalization to the host country and by adopting energy conversation policies.

Linear and non-linear impact of Internet usage and financial deepening on electricity consumption for Turkey: empirical evidence from asymmetric causality.

This study investigates the relationship between Internet usage, financial development, economic growth, capital and electricity consumption using quarterly data from 1993Q1 to 2014Q4. The integration order of the series is analysed using the structural break unit root test. The ARDL bounds test for cointegration in addition to the Bayer-Hanck (2013) combined cointegration test is applied to analyse the existence of cointegration among the variables. The study found strong evidence of a long-run relationship between the variables. The long-run results under the ARDL framework confirm the existence of an inverted U-shaped relationship between financial development and electricity consumption, not only in the long-run, but also in the short-run. The study also confirms the existence of a U-shaped relationship between Internet usage and electricity consumption; however, the effect is insignificant. Additionally, the influence of trade, capital and economic growth is examined in both the long run and short run (ARDL-ECM). Finally, the results of asymmetric causality suggest a positive shock in electricity consumption that has a positive causal impact on Internet usage. The authors recommend that the Turkish Government should direct financial institutions to moderate the investment in the ICT sector by advancing credits at lower cost for purchasing energy-efficient technologies. In doing so, the Turkish Government can increase productivity in order to achieve sustainable growth, while simultaneously reducing emissions to improve environmental quality.

A multi-paradigm framework to assess the impacts of climate change on end-use energy demand.

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.

Surpassing the current limitations of biohydrogen production systems: The case for a novel hybrid approach.

The steadily increase of global energy requirements has brought about a general agreement on the need for novel renewable and environmentally friendly energy sources and carriers. Among the alternatives to a fossil fuel-based economy, hydrogen gas is considered a game-changer. Certain methods of hydrogen production can utilize various low-priced industrial and agricultural wastes as substrate, thus coupling organic waste treatment with renewable energy generation. Among these approaches, different biological strategies have been investigated and successfully implemented in laboratory-scale systems. Although promising, several key aspects need further investigation in order to push these technologies towards large-scale industrial implementation. Some of the major scientific and technical bottlenecks will be discussed, along with possible solutions, including a thorough exploration of novel research combining microbial dark fermentation and algal photoheterotrophic degradation systems, integrated with wastewater treatment and metabolic by-products usage.

Testing the relationships between energy consumption, CO2 emissions, and economic growth in 24 African countries: a panel ARDL approach.

This study complements existing literature by examining the nexus between energy consumption (EC), CO2 emissions (CE), and economic growth (GDP; gross domestic product) in 24 African countries using a panel autoregressive distributed lag (ARDL) approach. The following findings are established. First, there is a long-run relationship between EC, CE, and GDP. Second, a long-term effect from CE to GDP and EC is apparent, with reciprocal paths. Third, the error correction mechanisms are consistently stable. However, in cases of disequilibrium, only EC can be significantly adjusted to its long-run relationship. Fourth, there is a long-run causality running from GDP and CE to EC. Fifth, we find causality running from either CE or both CE and EC to GDP, and inverse causal paths are observable. Causality from EC to GDP is not strong, which supports the conservative hypothesis. Sixth, the causal direction from EC to GDP remains unobservable in the short term. By contrast, the opposite path is observable. There are also no short-run causalities from GDP, or EC, or EC, and GDP to EC. Policy implications are discussed.