• Energy Research
• 11. Sustainability close
• GB close
• NL close

PurposeThe purpose of this paper is to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value‐added chain of biomass and bioenergy and comparing them accordingly.Design/methodology/approachA tri‐dimensional approach (sustainability issues; technical biomass conversion routes; physical trade flows) was developed for testing the coverage of various sustainability dimensions in different phases of the value‐added chain with the chosen certification schemes and sustainability principles.FindingsUsing the tri‐dimensional approach, a comparison of the chosen schemes and principles demonstrated that the application of existing schemes and the development of new ones have placed a major emphasis on the primary production of biomass. Economic and social dimensions related to biofuels and bioenergy processing and trade were either emphasised less or they were covered inadequately. In view of this, the schemes sometimes seem to ignore that the utilisation of renewable energy as such guarantee no positive or neutral climate impact and may not be economically sustainable, especially when bioenergy can often be more expensive than energy generated from fossil energy sources.Originality/valueThe analysis showed that the tri‐dimensional model is an applicable framework that could facilitate policy makers to formulate policies that comprehensively take into consideration the various sustainability dimensions throughout the entire value‐added chain, now and in the future. It can be applied to the future outlining and completion of certification schemes and sustainability principles for biomass and bioenergy, as well as in the testing of their applicability in the implementation.

With the fast growth of the global economy, energy supply and demand have a strong impact on social, economic, and environmental aspects. As a consequence, this has pushed the decision-makers to formulate objectives, guiding economic policies toward sustainable goals. The process is known as Sustainable Development Goals (SDGs) that have been proposed by the United Nations. This being said, the energy sector is a vital domain with a vast potential for improvments in terms of technologies and ligistalations. Solar energy is among the most efficient solutions proposed to reduce the economic and environmental footprints of energy. In this frame, the current paper aims to localize solar energy within SDGs and analyze the contribution of the solar energy towards the achievement of the SDGs. Moreover, the current work highlights the contributions of Mohammed bin Rashid Al Maktoum (MBR) Solar Park in the United Arab Emirates to achieving the SDGs. Indeed, the MBR Solar Park concept offers valuable insights of environmental impacts by deploying clean and affordable energy sources in place of conventional fossil fuel power plants that are still heavily used in the region. The MBR Solar Park operation has already mitigated 6.5 million tonnes of carbon dioxide equivalent and this number will likely rise when all phases are installed and operational. Moreover, it has been shown that MBR Solar Park achieve several SDGs such SDG 8: decent work and economic growth, SDG 9: industry, innovation and infrastructure, SDG 11: sustainable cities and communities, and SDG 15: life on land.

Wind power is an important potential source of electricity/energy generation, which also reduce the greenhouse gas emissions. Turkey is one of the largest markets in the wind energy production sector across the world. With the growing energy demand and for sustainability, the production is increasingly moving towards offshore wind farms. This study briefly reviews the offshore wind farms across the world and evaluates three alternatives for selecting the best site for an offshore wind farm based on 4 main and 15 sub-criteria in the Black Sea region of Turkey. The integrated distance measures and intuitionistic fuzzy sets based on multi-criteria decision-making are employed for that purpose. The ranking for the alternatives results with Inebolu, Amasra, Karasu, repectively in that order from the best to the worst option.

The European Geosciences Union (EGU) brings together geoscientists from all over the world covering all disciplines of the Earth, planetary and space sciences. This geoscientific interdisciplinarity is needed to tackle the challenges of the future. One major challenge for humankind is to provide adequate and reliable supplies of affordable energy and other resources in efficient and environmentally sustainable ways. This Energy Procedia issue provides an overview of the contributions of the Division on Energy, Resources & the Environment (ERE) at the EGU General Assembly 2017.

The Colombian agricultural sector has the capacity and ambition to reduce its land use and GHG emissions through sustainable intensification of livestock production. However, an appraisal of the impact of achieving such goal on the availability of land to produce bioenergy crops remains lacking. Moreover, previous assessments of the role bioenergy in Colombia have mostly focused on residues, in isolation of land use policies.To address this gap, we propose a hybrid statistical land balancing and suitability allocation approach to estimate long term projections of the cost–supply potential of bioenergy crops and residues. Regionalized to the departmental level, this approach could provide higher resolution than global assessments, while avoiding the complexity of spatially explicit methods. We investigated three scenarios covering the uncertainty of socioeconomic drivers and agricultural and livestock productivity factors.Our results suggest that pursuing progressive land use policies (SSP1 scenario) could release up to 14 Mha of land by 2050, which could be available to produce perennial bioenergy crops. The cumulative potential of crops in SSP1 could reach up to 2,200 PJ, where about half of this potential could be attained at 7 $ GJ -1 or less. Potential supply centers could be identified in Orinoquia, Andean, and Caribbean regions for energy crops and the Pacific region for residues. Our findings indicate that there could be an opportunity to create synergy between the low carbon development strategies of the land use and energy sectors in Colombia.

The basins of the Indus and Ganges rivers cover 2.20 million km2 and are inhabited by more than a billion people. The region is under extreme pressures of population and poverty, unregulated utilization of the resources and low levels of productivity. The needs are: (1) development policies that are regionally differentiated to ensure resource sustainability and high productivity; (2) immediate development and implementation of policies for sound groundwater management and energy use; (3) improvement of the fragile food security and to broaden its base; and (4) policy changes to address land fragmentation and improved infrastructure. Meeting these needs will help to improve productivity, reduce rural poverty and improve overall human development.

Abstract Urban planners, local authorities, and energy policymakers often develop strategic sustainable energy plans for the urban building stock in order to minimize overall energy consumption and emissions. Planning at such scales could be informed by building stock modeling using existing building data and Geographic Information System-based mapping. However, implementing these processes involves several issues, namely, data availability, data inconsistency, data scalability, data integration, geocoding, and data privacy. This research addresses the aforementioned information challenges by proposing a generalized integrated methodology that implements bottom-up, data-driven, and spatial modeling approaches for multi-scale Geographic Information System mapping of building energy modeling. This study uses the Irish building stock to map building energy performance at multiple scales. The generalized data-driven methodology uses approximately 650,000 Irish Energy Performance Certificates buildings data to predict more than 2 million buildings’ energy performance. In this case, the approach delivers a prediction accuracy of 88% using deep learning algorithms. These prediction results are then used for spatial modeling at multiple scales from the individual building level to a national level. Furthermore, these maps are coupled with available spatial resources (social, economic, or environmental data) for energy planning, analysis, and support decision-making. The modeling results identify clusters of buildings that have a significant potential for energy savings within any specific region. Geographic Information System-based modeling aids stakeholders in identifying priority areas for implementing energy efficiency measures. Furthermore, the stakeholders could target local communities for retrofit campaigns, which would enhance the implementation of sustainable energy policy decisions.

Daylighting in urban streets in the tropics is affected by obstructions in the real street conditions. This paper proposes a method of estimating daylight in urban streets under overcast, partly cloudy and clear sky conditions. The concept of the daylight factor forms the basis of this paper with some assumptions to simplify the method. The calculated values proposed method were compared with the measured values from the survey in Bangkok. The results of the comparisons showed a high level of similarity. The calculation of the daylight factor or the absolute illuminance in streets could thus be obtained from the method described in this paper.