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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.

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.

The study assessed the effects of firewood usage on rural women health in Ogun State. Samples of 128 respondents were randomly selected from four local government areas of Ogun State. Data were collected with the aid of structured questionnaire. Percentages were used for data analysis. Majority of the respondents were married (91%) with a mean age of 50 years. Most of the respondents (86.7%) used firewood for cooking, the preference of the utilization of firewood over other alternatives was due to non-availability of other sources (40%) and availability of firewood (33%). Some perceived health effects on the respondents were discomfort caused by the smoke from the firewood (𝑥 ̅ = 2.81) and eyes irritation (= 2.53). The study recommended alternative energy sources that are with lesser health hazards be made readily available at subsidized rate in the rural areas since this was the major attractive driving force for the use of firewood.

Abstract Building energy performance is often inadequate given design goals. While different types of assessment methods exist, they either do not consider design goals and/or are not general enough to integrate new and innovative energy concepts. Furthermore, existing assessment methods focus mostly on the building and system level while ignoring more detailed data. With the availability and affordability of more detailed measured data, the increased number of measured data points requires a structure to organize these data. This paper presents the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured data and simulated data representing design goals. The EPCM is based on an interlinked building object hierarchy that structures the detailed performance data from a spatial and mechanical perspective. This research is developed and tested on multiple case studies that provide real-life context and more generality compared to single case studies.

Abstract The main hindrances to the large-scale development of renewable-energy projects are the lack of bankability and the inability to align investments and investors with suitable financial instruments or robust policy measures. To illustrate a bankable project, this paper presents a research-based case study on the installation of solar photovoltaic panels on the rooftops of 195 trains of the Indian Railways. Detailed information on the annual running hours, exposure to sunlight, efficiency of solar photovoltaic generation and electrical power demands of each rail coach is considered to conduct a quantitative measure of the tentative amount of fossil fuel savings. The purpose is to provide insight into the types of renewable-energy projects that can be highly attractive to financial institutions and promoters due to their lucrative internal return on investment. As seen in this case study, there are annual savings in diesel of 12 323 088 litres and a CO2 reduction of 32 755 tonnes, with return on investment of 1.3 years. Furthermore, this study conducts a comprehensive analysis of the limitations of existing renewable-energy project financing mechanisms in India. Subsequently, three policy measures are recommended to develop a robust financial mechanism that can effectively meet the needs of investors and investors. These measures include increasing equity injection through a buy-and-hold strategy, providing direct tax benefits to promoters and financing through real-estate investment trusts. The findings are highly relevant to address the challenges associated with bridging the financial gap between access to finance and capital investment in the renewable-energy sector, especially for Asian countries.

AbstractClimate change poses new and unique challenges that threaten lives and livelihoods. Given the increasing risks and looming uncertainty of climate change, increasing attention has been directed towards adaptation, or the strategies that enable humanity to persist and thrive through climate change the best it can. Though climate change is a global problem often discussed at the national scale, urban areas are increasingly seen as having a distinct role, and distinctive motivation and capacity, for adaptation. The 12 articles in this special issue explore ways of understanding and addressing climate change impacts on urban areas. Together they reveal young but rapidly growing scholarship on how to measure, and then overcome, challenges of climate change. Two key themes emerge in this issue: 1) that we must identify and then overcome current barriers to urban adaptation and 2) frameworks/metrics are necessary to identify and track adaptation progress in urban settings. Both of these themes point to the power of indicators and other quantitative information to inform priorities and illuminate the pathway forward for adaptation. As climate change is an entirely new challenge, careful measurement that enables investment by private and public parties is necessary to provide efficient outcomes that benefit the greatest number of people.

AbstractBioenergy projects can lead to direct and indirect land use change (LUC), which can substantially affect greenhouse gas balances with both beneficial and adverse outcomes for bioenergy's contribution to climate change mitigation. The causes behind LUC are multiple, complex, interlinked, and change over time. This makes quantification uncertain and sensitive to many factors that can develop in different directions—including land use productivity, trade patterns, prices and elasticities, and use of by‐products associated with biofuels production. Quantifications reported so far vary substantially and do not support the ranking of bioenergy options with regard to LUC and associated emissions. There are however several options for mitigating these emissions, which can be implemented despite the uncertainties. Long‐rotation forest management is associated with carbon emissions and sequestration that are not in temporal balance with each other and this leads to mitigation trade‐offs between biomass extraction for energy use and the alternative to leave the biomass in the forest. Bioenergy's contribution to climate change mitigation needs to reflect a balance between near‐term targets and the long‐term objective to hold the increase in global temperature below 2°C (Copenhagen Accord). Although emissions from LUC can be significant in some circumstances, the reality of such emissions is not sufficient reason to exclude bioenergy from the list of worthwhile technologies for climate change mitigation. Policy measures to minimize the negative impacts of LUC should be based on a holistic perspective recognizing the multiple drivers and effects of LUC.This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.