• Energy Research
• 13. Climate action close
• 11. Sustainability close
• 15. Life on land close

Abstract Pollution control strategies currently in use by electric power systems are reviewed and a new minimum emission dispatch (MED) method is developed. This new method minimizes overall emission levels at an increased cost in large-scale power systems while simultaneously accommodating local pollution level requirements, as well as economic constraints.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.

Abstract In this paper, the prevention of negative technogenic impact on the environment of oil sludge by using it as a secondary resource is considered. Oil sludge from various objects of oil fields in Kazakhstan (Mangystau region) has been studied. The possibilities of using oil (after its separation from oil sludge by bioremidiation) as a partial substitute for bitumen base in the production of modified bitumen are considered. The main physical and mechanical characteristics of modified bitumen are determined. The results confirm that the modified bitumen prepared with oil sludge and oil separated by bioremiation method meets the requirements for polymer-bitumen binder to Kazakhstan standards and is suitable for the production of modified bitumen in its physico-chemical characteristics.

This paper discussed the biomass growth and consumption processes in grazed pasture ecosystems from a theoretical point of view, simulated the dynamics of these two processes with mathematical models, and analyzed the mechanism of ecological balance in pasture ecosystems from the perspective of these two processes. With the proposed biomass growth and consumption models, the dynamics of cumulative biomass consumption during one production cycle was simulated, and the optimal grazing strategies of pastures were proposed. The results could be valuable for pasture grazing management in practice.

Abstract As a burgeoning theoretical framework, energy justice has been mostly focused on the energy transition in Western countries, where socio-political settings are largely featured by liberalism and democracy, leaving an obvious gap in its application in other socio-political contexts. As a major energy consumer and a leader of the global low-carbon transition, China is characterized by a distinctive socio-political regime. An array of grand strategies to transform its coal-dominant energy structure have been initiated to ameliorate deteriorating environmental crises in particular and materialize a low-carbon transition in general. Based on extensive evidence, this article incorporates the energy justice framework into the analysis of an ongoing energy transition project in rural Northern China. It contributes to the related research in three dimensions. First, empirically, it demonstrates that the coal-to-gas heating transition project has been swamped with social injustices; the absence of measures to address these would lead this mega-project to profound failure. Second, theoretically, it illustrates that the concerns of justice are even more paramount in an authoritarian context where policy processes are characterized by strong political-administrative intervention and the pursuit of efficiency at all cost. In light of this, it stresses the indispensable role of restorative justice as a core tenet in achieving energy justice in authoritarian socio-political contexts, such as China. Third, this study advocates expanding the evaluation parameters of authoritarian environmentalism to include social consequences.

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.

Progressive urban density affects city centers especially and results in growing congestion, lack of parking spaces, and increasing environmental costs of transportation, causing increased air pollutant emissions and noise. These phenomena reduce the attractiveness of the city and result in a degradation of the quality of life for its residents. In light of these phenomena, there is a clear need for intelligent management of urban space using new technologies that would be complementary to existing intelligent transportation systems. Expanding information resources obtained from mobile cameras will have a positive impact on increasing the efficiency of transportation management and use of limited space in city centers. It will also have an impact on reducing external transport costs and increasing the quality of logistics services provided in the city. The main aim of the paper is to develop a concept of a transport management system in cities using mobile vision systems mounted on unmanned aerial vehicles. The model will concern the cases of lane occupation by freight vehicles and the analysis of parking spaces in the city in order to improve their management. The results of the developed model will contribute to the automation of the parking space management process and increase the efficiency of the use of city parking space resources.