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WOS: 000463342600001 In this research, we aim at exploring the influence of renewables on industrial production (Ip) in the US by following continuous wavelet coherence and partial continuous wavelet coherence analyses. To this end, we observed the co-movements between, biofuels and Ip, solar and Ip, wind and Ip, geothermal and Ip, wood and Ip, and, waste and Ip in the US for the monthly period from January 1989 to November 2016. The primary motivations behind this research are twofold. Firstly, it attempts to reach the co-movements, if exists, between renewables' consumption and industrial production by following time domain and frequency domain analyses. Secondly, it aims at observing the potential co-movements between renewable energy sources (geothermal, solar, wind, biofuels, wood, and, waste) and Ip by adding some control variables (fossil fuels, total biomass etc.) into the wavelet models to understand clearly the responses of the industrial production to the impulses in renewables in both short term and long term periods. The paper hence eventually reveals significant effects of geothermal, wind, solar, biofuels, wood, and, waste on US industrial production in short term cycles and long term cycles. Thereby, following this paper's results of continuous wavelet analyses which depict the impact of renewables on US economy at 1-3-year frequency and 3-8-year frequency for the time period from January 1989 to November 2016, one might provide policy makers with relevant current and future efficient renewables' energy policy for the US and other countries which have similar structures with the US.

Alternative marine fuels are accepted and used as an important solution for preventing ship-related air-borne pollutants. Studies of international organizations such as IMO on these fuels are increasing and gaining importance. However, assessing the environmental performances of these fuels, which generally produce much less pollutants than fossil fuels during operation, a life cycle perspective will provide a comprehensive understanding of which one is more environmentally efficient. In this study; biogas, dimethyl ether, ethanol, liquefied natural gas, liquefied petroleum gas, methanol, ammonia, and biodiesel were determined as alternative fuels and their environmental damages during life cycle were evaluated in life cycle perspective. SimaPro V9.0.0.49 and ReCiPe 2008 V1.09 were used for the assessment. The results focused on the effects on human health, ecosystem, resource utilization, emission inventory, and social costs. Thus, a complete evaluation was achieved for all alternative fuels considering not only the operating conditions but also the production process. Biogas was found as the best fuel in the short, medium, and long term; methanol, ammonia, and biodiesel group performed worst. While biogas causes 0.9 tons of CO2 production, methanol, ammonia, and biodiesels produce 1.5, 4.8, and 1.6 (average) tons of CO2, respectively. Despite the doubts on production, transfer, and storage, biogas was also identified as the most sustainable type of fuel.

This paper first reviews the potential causality from biomass energy to CO2 emissions and economic development within relevant literature. Later, the paper examines statistically the impacts of biomass energy consumption on CO2 emissions and GDP in the US. To this end, paper observes environmental and economic implications of biomass fuel usage throughout energy literature and launches asymmetric causality test to confirm/disconfirm the literature output. The findings of the tests indicate that biomass energy consumption per capita mitigates CO2 emissions per capita and increases GDP per capita. Eventually, upon its output, this research asserts that biomass energy consumption can be an efficient policy tool for environmentally sustainable development in the US, and, that, hence, biomass production technologies and biomass consumption need to be promoted in other countries as well as in the US. On the other hand, analyses underline the fact that policy makers should consider as well some potential constraints of biomass energy usage such as land use constraints and carbon leakage from biomass production. Therefore, although this paper explores the remedial impact of biomass on environment and growth, one may suggest also that further possible works consider the effects of biomass sources in detail to minimize the some worsening influence of biomass usage on climate change.

The sewage sludge creates as a result of wastewater treatment and has high water content, contains pathogens, heavy metals, micro-pollutants, etc., and also include organics that have a high calorific value, nitrogen and phosphor; therefore, it is necessary to select sustainable methods in its treatment/disposal. As for sustainable sludge management, not only current technologies, but also several other criteria such as legal regulations and problem-solving need to be taken into account. This study summarized the current situation for the management of domestic sewage sludge in Turkey and compared the methods of anaerobic digestion, incineration, gasification, pyrolysis and supercritical water gasification (SCWG), which are used/can be used in Turkey, with one another on the basis of four different criteria. As a result of the SWOT-FAHP (fuzzy analytic hierarchy process) analysis performed, it was observed that supercritical water gasification, which is one of the five methods considered, and problem-solving criterion, which is one of the four criteria considered, had the highest weight values. According to the results obtained via comparison of criteria, it was determined that the availability of current technology had less importance than problem-solving criterion in the selection of an appropriate method. The reasons why the method of supercritical water gasification had a high weight value even though it had certain disadvantages can be listed as follows: it ensures treatment with a high yield, does not require pre-treatment, has a shorter reaction time and creates a higher amount of beneficial by-products as compared with harmful emissions. Furthermore, this study also touched upon the obstacles to overcome for the development of SCWG and brought recommendations.

This paper considers a revisited Environmental Kuznets Curve (EKC) hypothesis with potential impact of renewable energy consumption on environmental quality. To this end, paper aims at investigating the validity of the EKC hypothesis employing the dependent variable of CO2 emissions and regressors of GDP, quadratic GDP and renewable energy consumption. This paper, hence, analyzes this revisited EKC hypothesis to observe if (i) there exists an inverted-U shaped relationship between environmental quality (in terms of CO2 emissions), per capita income and per capita income squared and (ii) there exists a negative causality from renewables to CO2 emissions within EKC model. Paper employs a panel data set of 17 OECD countries over the period 1977–2010 and launches panel FMOLS and panel DOLS estimations. The findings support the EKC hypothesis for the panel and indicate that GDP per capita and GDP per capita squared have the impacts on CO2 emissions positively and negatively, respectively, and that renewable energy consumption yields negative impact on CO2 emissions. Another remark of this paper is that the validity of EKC does not depend on income level of individual countries of panel in which EKC hypothesis holds. Eventually, paper argues that if countries carry out (i) policies, i.e., for fair and easy access to the electricity from renewable sources and (ii) policies to increase renewables supply through i.e. improved renewable energy technologies, they will be able to contribute to combating global warming problem as they increase their GDP’s.

One may observe that there exist many seminal papers in energy literature to investigate intensively the energy consumption–growth nexus. The majority of these papers employ time series and/or panel data methodologies to explore, if exists, the impact of energy and/or renewable energy usage on economic growth. While time series or panel data methodologies, on the other hand, can capture time and/or cross sectional dimensions of variables, they are not able to observe frequency dimension of the related variables. This paper, thus, aims at considering both time series and frequency properties of relevant data through wavelet coherence methodology to follow the possible influences of US renewable energy consumption on the US economy in both the short run and the long run cycles. This paper, hence, considers short run and long run co-movements between renewables consumption and industrial production through wavelet coherence and wavelet partial coherence analyses. Wavelet analyses are able to capture the co-movements in time and frequency domains. Hence, wavelet analyses are able to observe structural breaks within transitory and permanent cycles through time in analyzing the dependency between two variables. This paper specifically launches continuous wavelet transform methodology since it is more selective with time parameters in comparison with discrete wavelet transform function. Employing the US monthly data of renewables and industrial production with the controlled variables of coal consumption, natural gas consumption and petroleum consumption, this paper observes, first, continuous wavelet coherency analyses and, later, considers continuous wavelet partial coherence analyses with phase differences. In conclusion, paper yields that renewables consumption has positive significant impacts on industrial production, hence, on economic growth, in both lower and higher frequencies in the US.

The purpose of this paper is to reveal the long run dynamics of biomass energy consumption and GDP growth through homogeneous and heterogeneous variance structures for G7 countries. It covers annual data from 1980 to 2009. Panel unit root analyses, panel cointegration analyses, conventional OLS and dynamic OLS analyses are run throughout homogeneous and heterogeneous variance structures of the panel data to examine the relationship. The findings show that the long run elasticities of panel real GDP data in terms of panel capital stock, panel human capital index and panel biomass consumption are significant and positive. The results confirmed the growth hypothesis in which biomass energy consumption have positive effects on economic growth of G7 countries. As a policy implication, energy policies which improve the biomass energy infrastructure and biomass supply are the appropriate options for G7 countries since biomass energy consumption increases the economic growth. (C) 2015 Elsevier Ltd. All rights reserved.

In recent years, the atmosphere has been exposed to a substantial increase in concentration of the trace gases. In 2012, energy-related CO 2 emissions reached a record of 31.6 gigatonnes which corresponds to 1.4% comparing to 2011. According to the International Energy Agency (IEA), an energy revolution is needed to achieve a 50% reduction of global CO 2 emissions relative to current levels by 2050. In this revolution, energy efficiency, energy storage, new transport technologies, nuclear energy and CO 2 capture and storage should play a crucial role. Furthermore, renewable energy technologies comprise a large potential for emission reductions which takes second place after energy efficiency improvements. Until 2035, renewable energy will also have greater impact than other potential alternatives including both CO 2 capture and storage or nuclear energy. For this reason, renewable energy industries, markets, and policy frameworks are developed rapidly in recent years, and they will play a substantial role in the world׳s future. This paper presents an overview of renewable electric power capacity worldwide and discusses the current status, technologies, industry and recent developments of renewable energy sources (RESs) in detail. In addition, the top countries in terms of total installed renewable electric power capacity are also identified.

Biomass is one of the major sources of renewable energy in the World. This paper aims at observing primary biomass energy supply in some EU countries within periods1971-2009 and 1982-2009. Following related two panel data sets for biomass in EU, this work employs linear models and nonlinear threshold autoregression (TAR) models to test linearity against nonlinearity and nonstationarity against stationarity. If nonlinearity is found, then, the next step is to search transition variable and threshold value of the panel data sets. This paper eventually has the purpose to reveal if EU countries converge in the production of biomass in a linear form or nonlinear form. Findings show that panel of Austria, Denmark, Finland, France and Portugal follows nonlinear process and reaches partial convergence in per million primary solid biomass energy supply. However, the involvement of Belgium, Greece, Norway, Poland and Sweden to the panel yields linearity and divergence. One may suggest policy makers of EU and/or OECD, upon conclusion of this paper, to revise their energy policies to stimulate both production and consumption of biomass energy source. (C) 2012 Elsevier Ltd. All rights reserved.

The source of carbon dioxide (CO2) emissions has been of great interest to researcher(s) and/or policy maker(s) within ongoing efforts to diminish the emissions in the world due to CO2's serious adverse environmental effect. This paper investigates the possible existence of long run relationship between CO2 emissions and biomass consumption in US for the period January 1990-September 2011. To this end, paper first seeks for effect of biomass on CO2 through energy literature and later follows cointegration analyses with structural breaks to reveal parameter estimates of long run equilibrium of CO2 with fossil fuel consumption and biomass consumption. Eventually this paper explores that structural breaks are important to understand the course of CO2 and that, as expected, fossil fuel and biomass effect CO2 positively and negatively, respectively. Alternative cointegration analyses with regime shifts confirm negative impact of biomass and positive impact of fossil fuel on CO2, as well. (c) 2012 Elsevier Ltd. All rights reserved.

The main objective of the present study is to apply the artificial neural network (ANN) methodology, linear regression (LR) and nonlinear regression (NLR) models to estimate the electricity consumptions of the residential and industrial sectors in Turkey. Installed capacity, gross electricity generation, population and total subscribership were selected as independent variables. Two different scenarios (powerful and poor) were proposed for prediction of the future electricity consumption. Obtained results of the LR, NLR and ANN models were also compared with each other as well as the projection of the Ministry of Energy and Natural Resources (MENR) and the results in literature. Results of the comparison showed that the performance values of the ANN method are better than the performance values of the LR and NLR models. According to the poor scenario and ANN model, Turkey's residential and industrial sector electricity consumptions will increase to value of 140.64 TWh and 124.85 TWh by 2015, respectively.

Wind power, as a renewable source of energy, produces no emissions and is an excellent alternative in environmental terms to conventional electricity production based on fuels such as oil, coal or natural gas. At present, the vast majority of wind power is generated from onshore wind farms. However, their growth is limited by the lack of inexpensive land near major population centers and the visual pollution caused by large wind turbines. Comparing with onshore wind power, offshore winds tend to flow at higher speeds than onshore winds, thus it allows turbines to produce more electricity. Estimates predict a huge increase in wind energy development over the next 20 years. Much of this development will be offshore wind energy. This implies that great investment will be done in offshore wind farms over the next decades. For this reason, offshore wind farms promise to become an important source of energy in the near future. In this study, history, current status, investment cost, employment, industry and installation of offshore wind energy in Europe are investigated in detail, and also compared to its onshore counterpart.