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According to the renewable energy directive 2009/28/EC, the European Union Member States should increase by 2020 the use of renewable energy to 20% of gross final energy consumption and to reach a mandatory share of 10% renewable energy in the transport sector. This study aims to quantify the impact of 2020 bioenergy targets on the land use in the EU, based on the projections of the National Renewable Action Plans in four scenarios: Scenario 1. Bioenergy targets according to NREAPs; Scenario 2. Bioenergy targets according to NREAPs, no second generation biofuels; Scenario 3. Bioenergy targets according to NREAPs, reduced import of biofuels and bioliquids; Scenario 4. Bioenergy targets according to NREAPs, high imports of biofuels and bioliquids. This study also considers the credit for co-products generated from biofuel production. The analysis reveals that the land used in the EU for bioenergy would range between 13.5 Mha and 25.2 Mha in 2020. This represent between 12.2% and 22.5% of the total arable land used and 7.3% and 13.5% of the Utilised Agricultural Area (UAA). In the NREAPS scenario, about 17.4 Mha would be used for bioenergy production, representing 15.7% of arable land and 9.4% of UAA. The increased demand from biofuels would lead to an increased generation of co-products, replacing conventional fodder for animal feed. Considering the co-products, the land used for bioenergy would range between 8.8 Mha and 15.0 Mha in 2020 in the various scenarios. This represent between 7.9% and 13.3% of the total arable land used in the EU and 4.7% and 8.0% of the UAA. In the NREAPS scenario, when co-products are considered, about 10.3 Mha would be used for biofuels, bioliquids and bioenergy production, representing 9.3% of arable land and 5.6% of agricultural land. This study further provides detailed data on the impact on land use in each Member State.

Microalgae have tremendous potential for producing liquid renewable fuel. Many methods for converting microalgae to biofuel have been proposed; however, an economical and energetically feasible route for algal fuel production is yet to be found. This paper presents a review on the comparison of the most promising conversion pathways of microalgae to liquid fuel: hydrothermal liquefaction (HTL), wet extraction and non-destructive extraction. The comparison is based on important assessment parameters of product quality and yield, nutrient recovery, GHG emissions, energy and the cost associated with the production of fuel from microalgae, in order to better understand the pros and cons of each method. It was found that the HTL pathway produces more oil than the wet extraction pathway; however, higher concentrations of unwanted components are present in the HTL oil produced. Less nutrients (N and P) can be recovered in HTL compared to wet extraction. HTL consumes more fossil energy and generates higher GHG emissions than wet extraction, while the production cost of fuel from HTL pathway is lower than wet extraction pathway. There is considerable uncertainty in the comparison of the energy consumption and economics of the HTL pathway and the wet extraction pathway due to different scenarios analysed in the assessment studies. To be able to appropriately compare methodologies, the conversion methods should be analysed from growth to upgradation of oil utilising sufficiently similar assumptions and scenarios. Based on the data in available literature, wet oil extraction is the more appropriate system for biofuel production than HTL. However, the potential of alternative extraction/conversion technologies, such as, non-destructive extraction, need to be further assessed.

The influence of ethanol on the degradation kinetics of linear alkyl benzene sulfonate (LAS) and organic matter was investigated using batch experiments with different initial LAS concentrations (8.3 mg L-1 to 66.9 mg L-1) and biomass immobilized on sand. Data were fitted with a substrate inhibition model. Concentrations of 2.4 mg LAS L-1 and 18.9 mg LAS L-1 (without and with ethanol) provided the maximum LAS utilization rate by the biomass (Sbm). For LAS degradation, ethanol addition favored a lower decrease in the specific substrate utilization rate (robs), even at the LAS concentration usually reported as inhibitory (> 14.4 mg L-1). For organic matter degradation, robs was higher with ethanol. Higher biomass differentiation was observed at higher LAS concentrations. With ethanol, microbial selection occurred at LAS concentrations near Sbm. At higher LAS concentrations, the dominance and diversity values did not change significantly with ethanol, whereas without ethanol, their behaviors were irregular.

This paper reports the real-time behavior of the leakage current flowing on glass-type insulator strings of a 230-kV substation tower during washing. Monitoring of two insulator strings in the tower is achieved by use of a pair of optical-fiber sensors that detect samples of the leakage current waveforms and transmit those samples to a processing module via an optical link. It is observed that leakage current during washing may reach high peak levels, and the effectiveness of the washing can be inferred by the degree of leakage current after drying of the insulator strings. Direct monitoring of the leakage current can thus be used as an important guideline for proper washing procedures during this type of intervention as well as for determining the effectiveness of the procedure.

Abstract Adsorbent-based carbon capture is only feasible if adsorption-desorption cycles are both fully regenerating and efficient. This work proposes a regenerative pH swing process and a pH swing regenerative adsorbent that are inspired by natural CO2 conversion by carbonic anhydrase biocatalysts found in mammalian red blood cells. The main objective is to develop, test and analyze a synthetic pH Swing Adsorption (pHSA) system as well as a pHSA compatible solid adsorbent to capture CO2 from a simulated ambient air gas stream. The lead developed adsorbent is a carbon black co-activated with potassium carbonate and nitrogenous copolymer that is impregnated with immobilized bovine carbonic anhydrase and thereby deemed “BCA/KN-CB”. BCA/KN-CB has preliminarily demonstrated both competitive CO2 adsorption capacity and limited regenerative ability under experimental pHSA conditions. In addition, BCA-based adsorbents achieved higher adsorption capacities than non-BCA adsorbent counterparts. The BCA/KN-CB adsorbent displayed both large point of zero charge (PZC) swings and regenerative stability. The proposed pHSA system requires essentially zero energy expenditure to achieve intended environments for capture and regeneration. With 1 kg of adsorbent, pHSA has the ability to capture 1 kg CO2 in less than 4 h of cycling. The tested pHSA adsorbent can also capture more than 96% of total CO2 in a given raw gas stream flowing through the capture chamber. This proof-of-concept study of a pH swing adsorption/biocatalytic adsorbent system suggests the potential to effectively operate under ambient conditions and exhibit advantageous operational efficiencies to other high-profile CO2 capture systems.

Abstract In this work, energy analysis is carried out to account for inputs and outputs of energy and GHG emissions associated with the biodiesel production system. Jojoba oil is obtained by cultivation of the jojoba plant, harvesting of seeds followed by extraction of oil, which is then converted to biodiesel by the process of transesterification. Energy efficiency is expressed in terms of the net energy balance (NEB) and the net energy ratio (NER). The use of the byproducts (husk, cake or meal, waste residues and glycerin) are also included as a part of the system boundary. The results show that the NEB and NER values are calculated at 46724.1 MJ/ha (28.9 MJ/L biodiesel produced) and 2.16, respectively. At the same time, the total amount of GHG emissions are estimated at 2.28 kg-CO2eq/L biodiesel produced (66.0 g CO2eq/MJ biodiesel produced). Nevertheless, if manure is used as fertilizer for jojoba plant cultivation, the primary energy input will fall by 9.52% (to 22.49 MJ/L of biodiesel).

Abstract Flow-accelerated corrosion (FAC) is a degradation mechanism that affects carbon steel piping in power plants. The failures and degradation due to FAC have necessitated numerous replacements in many power plants. Several computer codes around the world were developed as part of a systematic program or process to control FAC in power plant utilities. The typical plant model requires the input of the flow parameters, piping configuration and the plant water chemistry. The results on FAC rate are considered the key to proper selection of components for inspection. The lack of information on the effect of the upstream components located in the proximity limited the accuracy of the FAC prediction tools and hence will affect the accuracy in identifying potential inspection locations. In the present study 211 inspection data for 90° carbon steel elbows from several nuclear power plants were used to determine the effect of the proximity between two components on the FAC wear rate. The effect of the velocity as well as the distance between the elbows and the upstream components is discussed in the present analysis. Based on the analyzed trends obtained from the inspection data, significant increase in the wear rate of approximately 70% on average is identified to be due to the proximity.

Short term load forecasting plays an increasingly important role in Smart Grid. Short term load forecasting is also an important part of enterprise power system management. Providing accurate load time series data for a certain period of time in the future can enable enterprises to ensure the smooth operation of production while making a reasonable power plan, reducing power consumption and basic electricity charges, thus reducing the production cost of enterprises. In addition, lower electricity consumption means lower carbon dioxide emissions, which has far-reaching implications for sustainable development strategies. This paper presents a short-term load forecasting method based on time series. The model divides the time series data into four parts: trend item, period item, holiday item and error item. In the experiment part, this paper provides a set of preprocessing method flow. Aiming at the problem that the sampling rate of the current smart grid data is not constant, a data smoothing algorithm is proposed.

The main objective of this paper is to illustrate the current state of the art of the newborn smart gas grid concept. We provide a detailed discussion of the envisaged features of the smart gas grid, giving attention to both the related academic literature and to the ongoing world-wide projects. In doing so, we also discuss the potentialities of rethinking the smart grid paradigm from the perspective of a whole energy system, that both encompasses the electrical and the gas grid, and identify some critical key aspects that must be handled while developing the new smart energy paradigm.