A Spatial Analysis of the Potentials for Offshore Wind Farm Locations in the North Sea Region:Challenges and Opportunities

Over the last decade, the accelerated transition towards cleaner means of producing energy has been clearly prioritised by the European Union through large-scale planned deployment of wind farms in the North Sea. From a spatial planning perspective, this has not been a straight-forward process, due to substantial spatial conflicts with the traditional users of the sea, especially with fisheries and protected areas. In this article, we examine the availability of offshore space for wind farm deployment, from a transnational perspective, while taking into account different options for the management of the maritime area through four scenarios. We applied a mixed-method approach, combining expert knowledge and document analysis with the spatial visualisation of existing and future maritime spatial claims. Our calculations clearly indicate a low availability of suitable locations for offshore wind in the proximity of the shore and in shallow waters, even when considering its multi-use with fisheries and protected areas. However, the areas within 100 km from shore and with a water depth above -120 m attract greater opportunities for both single use (only offshore wind farms) and multi-use (mainly with fisheries), from an integrated planning perspective. On the other hand, the decrease of energy targets combined with sectoral planning result in clear limitations to suitable areas for offshore wind farms, indicating the necessity to consider areas with a water depth below -120 m and further than 100 km from shore. Therefore, despite the increased costs of maintenance and design adaptation, the multi-use of space can be a solution for more sustainable, stakeholder-engaged and cost-effective options in the energy deployment process. This paper identifies potential pathways, as well as challenges and opportunities for future offshore space management with the aim of achieving the 2050 renewable energy targets

The development of a new crop growth model SwitchFor for yield mapping of switchgrass

ACKNOWLEDGMENTS This study was supported by the Chinese Scholarship Council (CSC) and partially supported by the National Key Project of Intergovernmental Cooperation in International Scientific and Technological Innovation (2018YFE0112400 to S.C.). A.H. was funded by was funded by the ADVENT project funded by the UK Natural Environment Research Council (NE/M019691/1) and ADVANCES funded by the UK Natural Environment Research Council (NE/M019691/1), EPSRC funded UKERC-4 and the BBSRC funded PCB4GGR project (BB/V011553/1). We would like to Bingchen Xu, from Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, China, for providing field trail data of the switchgrass on the Loess Plateau. We also acknowledge the data support from the Loess Plateau Data Center, National Earth System Science Data Sharing Infrastructure, and National Science and Technology Infrastructure of China (http://loess.geodata.cn).Peer reviewedPublisher PD

How does the interplay between resource availability, intersectoral competition and reliability affect a low-carbon power generation mix in Brazil for 2050?

Increasing penetration of solar and wind energy can reduce the reliability of power generation systems. This can be mitigated by e.g.; low-carbon dispatchable hydropower and baseload biomass power plants. However, long-term supply potential for those sources is often uncertain, and biomass can also be used for biofuel production. The purpose of this study is to assess the interplay between uncertain supply potential of biomass and hydropower, intersectoral competition and reliability on a low carbon power system for 2050, with Brazil as case study, using a soft-link between an energy model and a power system model. Hydropower acts as a balancing agent for solar and wind energy, even under lower hydropower supply potential. When less biomass is available, low carbon transportation is met more with electric cars instead of ethanol cars, leading to an increase in electric load for charging their batteries. The charging strategy determines whether peak load increases substantially; after commuting, or lowers; in off-peak hours. This shows the importance of using a soft-link between the high temporal resolution power system model to assess the reliability, and a least cost-optimization model to assess the interplay between resource availability and intersectoral competition of low-carbon power systems

Сюжетна структурованість новел-легенд Петра Могили

The article deals with the legends by -etro Mohyla in general narrative theory context

Projecting socio-economic impacts of bioenergy:Current status and limitations of ex-ante quantification methods

The socio-economic effects of bio-energy are not unequivocally positive, although it is one of the main arguments for supporting its expansion. An ex-ante quantification of the impacts is necessary for transparently presenting the benefits and burdens of bioenergy before they occur, and for minimising unwanted outcomes. In this article, the status, limitations, and possibilities for improvements in ex-ante quantitative research methods for investigating socio-economic impacts of bioenergy are mapped. For this, a literature review to identify relevant indicators, analyse the latest quantitative ex-ante research methods, and to assess their ability and suitability to measure these indicators was performed. The spatial aggregation of existing analyses was specifically considered because quantitative information on different spatial scales shows the geographic distribution of the effects. From the 236 indicators of socio-economic impacts spread over twelve impact categories that were found in this review, it becomes evident that there are clear differences in the ex-ante quantification of these indicators. The review shows that some impact categories receive more attention in ex-ante quantification studies, such as project-level economic feasibility and national-level macroeconomic impacts, while other relevant indicators have not been ex-ante quantified, such as community impacts and public acceptance. Moreover, a key blind spot regarding food security impacts was identified in the aggregation level at which food security impacts are quantified, which does not match the level at which the impacts occur. The review also shows that much more can be done in terms of ex-ante quantification of these impacts. Specifically, spatial disaggregation of models and model collaboration can extend the scope of socio-economic analyses. This is demonstrated for food security impacts, which shows the potential for future household-level analysis of food security impacts on all four pillars of food security

The development of a new crop growth model SwitchFor for yield mapping of switchgrass

Switchgrass is a promising energy crop has the potential to mitigate global warming and energy security, improve local ecology and generate profit. Its quantitative traits, such as biomass productivity and environmental adaptability, are determined by genotype-by-environment interaction (GEI) or response of genotypes grown across different target environments. To simulate the yield of switchgrass outside its original habitat, a genotype-specific growth model, SwitchFor that captures GEI was developed by parameterising the MiscanFor model. Input parameters were used to describe genotype-specific characteristics under different soil and climate conditions, which enables the model to predict the yield in a wide range of environmental and climate conditions. The model was validated using global field trail data and applied to estimate the switchgrass yield potentials on the marginal land of the Loess Plateau in China. The results suggest that upland and lowland switchgrass have significant differences in the spatial distribution of the adaptation zone and site-specific biomass yield. The area of the adaption zone of upland switchgrass was 4.5 times of the lowland ecotype's. The yield difference between upland and lowland ecotypes ranges from 0 to 34 Mg ha−1. The weighted average yield of the lowland ecotype (20 Mg ha−1) is significantly higher than the upland type (5 Mg ha−1). The optimal yield map, generated by comparing the yield of upland and lowland ecotypes based on 1 km2 grid locations, illustrates that the total yield potential of the optimal switchgrass is 61.6–106.4 Tg on the marginal land of the Loess Plateau, which is approximately twice that of the individual ecotypes. Compared with the existing models, the accuracy of the yield prediction of switchgrass is significantly improved by using the SwitchFor model. This spatially explicit and cultivar-specific model provides valuable information on land management and crop breeding and a robust and extendable framework for yield mapping of other cultivars

Geospatial analysis of the energy yield and environmental footprint of different photovoltaic module technologies

The majority of currently installed photovoltaic (PV) systems are based on mono- and polycrystalline silicon PV modules. Manufacturers of competing technologies often argue that due to the characteristics of their PV technologies, PV systems based on their modules are able to achieve higher annual energy yield, due to a smaller effect of temperature on module performance and/or a better performance at low light intensities. While these benefits have been confirmed in local studies many times, there is still limited insight as to the locations at which a particular technology actually performs best. In this study we have analysed the performance of a large set of PV modules, based on irradiance time series that were taken from satellite measurements. Using these data, and combining it with a PV performance model, we have made a geospatial analysis of the energy yield of different types of PV modules. We aim to make the energy yield of the investigated modules spatially explicit, allowing PV system installers to choose the best module type for every location investigated. Our results show that there is large geographical variety in the performance of PV modules, in terms of energy yield but also in terms of relative performance or performance ratio. While some technologies clearly exhibit a decrease in performance ratio at locations where they operate at higher temperatures, for some technologies this effect is much smaller. As a result of the variation in performance, the environmental footprint of.13V modules also shows large geographical variations. However, even at low irradiance locations the environmental footprint of PV modules in general is much lower compared to that of fossil fuel based electricity generation. (C) 2017 Elsevier Ltd. All rights reserved

Evaluating the suitability of marginal land for a perennial energy crop on the Loess Plateau of China

Abstract With a large marginal land area, the Loess Plateau in China holds great potential for biomass production and environmental improvement. Identifying suitable locations for biomass production on marginal land is important for decision‐makers from the viewpoint of land‐use planning. However, there is limited information on the suitability of marginal land within the Loess Plateau for biomass production. Therefore, this study aims to evaluate the suitability of the promising perennial energy crop switchgrass (Panicum virgatum L.) on marginal land across the Loess Plateau. A fuzzy logical model was developed and validated based on field trials on the Loess Plateau and applied to the marginal land of this region, owing to its ability of dealing with the continuous nature of soil, landscape variations, and uncertainties of the input data. This study identified that approximately 12.8–20.8 Mha of the Loess Plateau as available marginal land, of which 2.8–4.7 Mha is theoretically suitable for switchgrass cultivation. These parts of the total marginal land are mainly distributed in northeast and southwest of the Loess Plateau. The potential yield of switchgrass ranges between 44 and 77 Tg. This study showed that switchgrass can grow on a large proportion of the marginal land of the Loess Plateau and therefore offers great potential for biomass provision. The spatial suitability maps produced in this study provide information to farmers and policymakers to enable a more sustainable development of biomass production on the Loess Plateau. In addition, the fuzzy‐theory‐based model developed in this study provided a good framework for evaluating the suitability of marginal land