BESTGRID Process: Going Beyond Existing Practices of Stakeholders’ Participation in Electricity Transmission Projects

The goals of climate change mitigation and energy security policies are key drivers for the EU energy transition towards low-carbon energy generation. Even though alternative technologies, including renewable energy, are well advanced, the current state of electricity grids is one of the bottlenecks for its further deployment. Inhabitants of communities affected by planned infrastructure are protesting against further projects to deploy electricity grids in many European countries. The innovative BESTGRID process brings together organized stakeholders from civil society, academia and the energy sector to understand the nature of concerns about these projects and to test various actions to address the concerns. The major research questions addressed by this work are: What are the main stakeholder concerns about the deployment of electricity transmission grids in Europe? What are successful actions to address these concerns? Which level of participation can be achieved in electricity transmission infrastructure project siting in Europe? We address these research questions through a variety of methods, which allow us to gain a systemic look and the holistic understanding of the problem. We analyse five real-world pilot projects which are under planning or construction in Germany (SuedLink and Bertikow-Pasewalk connections), UK (NEMO Link connection) and Belgium (Stevin and Waterloo-Braine l’Alleud connections). We collect empirical data through extensive dialogue with stakeholders, by observation of public and stakeholders information events on-site, by conducting interviews with key stakeholders, and by conducting an on-site survey of all communities where public information events were organized. We mapped participation in each project according to the methodology developed by Arnstein and finally analyzed how concerns about the planned power lines changed before and after actions and policy interventions, which were developed and tested in BESTGRID

Assessment of management effect on grasslands characteristics in an area of the Apennines (North Italy)

In many regions of Europe, semi-natural grasslands not properly utilized face different threats, concerning changes in botanical composition and structural evolution, which can lead to a reduction of the qualitative value of forage biomass or, in the mid-long term, forest recovery. The present paper assesses various semi-natural grasslands within a mountain public property located in Tuscany (North Apennines, Italy) subjected to different types of utilization. Some of them are managed through cattle grazing during summer, whereas some others are only periodically mowed and utilization is performed only by wildlife occurring in the area. The paper analyses the importance of resource management and its impact on botanical composition and on qualitative value of forage production. Data collection of studied areas was conducted by means of vegetation assessment performed with a fast procedure that simplifies the botanical composition sampling. Results show the relevance of some environmental factors on grasslands evolution and on their composition (such as altitude and slope) and the importance of management on grassland quality and on level of shrub encroachment

Social challenges of electricity transmission: grid Deployment in Germany, the United Kingdom, and Belgium

The European Union needs to decarbonize its energy generation to reach its goals of climate change mitigation and energy security policies. In 2011, the European Commission published a road map to reduce greenhouse gases (GHG) by at least 80% by 2050. The road map foresees five pathways, and, across all of them, renewable energy generation plays a significantly stronger role today. The deployment of renewable energy sources (RES)to generate electricity is one possible option to decarbonize energy generation. The goals of the European energy security policy require restructuring energy generation toward a greater share of lowcarbon energy generation. In October 2014, EU leaders agreed on the 2030 policy framework for climate and energy, which settles the GHG reduction target of 40% compared to 1990, as well as an increase of the share of renewable energy to at least 27% of EU energy consumption by 2030

Can the BestGrid process improve stakeholder involvement in electricity transmission projects?

The European Union has set ambitious targets for deployment of renewable energy sources to reach goal of climate change mitigation and energy security policies. However, the current state of electricity transmission infrastructure is a major bottleneck for further scaling up of renewable energy in the EU. Several thousands of kilometers of new lines have to be constructed and upgraded to accommodate growing volumes of intermittent renewable electricity. In many countries, construction of electricity transmission projects has been delayed for several years due to concerns of local stakeholders. The innovative BESTGRID approach, reported here, brings together transmission system operators (TSOs) and non-governmental organizations (NGOs) to discuss and understand the nature of stakeholder concerns. This paper has three objectives: (1) to understand stakeholder concerns about the deployment of electricity transmission grids in four pilot projects according to five guiding principles: need, transparency, engagement, environment, and impacts on human health as well as benefits; (2) to understand how these principles can be addressed to provide a basis for better decision-making outcomes; and (3) to evaluate the BESTGRID process based on feedback received from stakeholders and the level of participation achieved according to the ladder of Arnstein. This paper goes beyond a discussion of "measures to mitigate opposition" to understand how dialogue between TSOs and the public -represented mainly by NGOs and policy-makers- might lead to a better decision-making process and more sustainable electricity transmission infrastructure deployment

T2 lesion location really matters: a 10 year follow-up study in primary progressive multiple sclerosis

Objectives: Prediction of long term clinical outcome in patients with primary progressive multiple sclerosis (PPMS) using imaging has important clinical implications, but remains challenging. We aimed to determine whether spatial location of T2 and T1 brain lesions predicts clinical progression during a 10-year follow-up in PPMS. Methods: Lesion probability maps of the T2 and T1 brain lesions were generated using the baseline scans of 80 patients with PPMS who were clinically assessed at baseline and then after 1, 2, 5 and 10 years. For each patient, the time (in years) taken before bilateral support was required to walk (time to event (TTE)) was used as a measure of progression rate. The probability of each voxel being ‘lesional’ was correlated with TTE, adjusting for age, gender, disease duration, centre and spinal cord cross sectional area, using a multiple linear regression model. To identify the best, independent predictor of progression, a Cox regression model was used. Results: A significant correlation between a shorter TTE and a higher probability of a voxel being lesional on T2 scans was found in the bilateral corticospinal tract and superior longitudinal fasciculus, and in the right inferior fronto-occipital fasciculus (p<0.05). The best predictor of progression rate was the T2 lesion load measured along the right inferior fronto-occipital fasciculus (p=0.016, hazard ratio 1.00652, 95% CI 1.00121 to 1.01186). Conclusion: Our results suggest that the location of T2 brain lesions in the motor and associative tracts is an important contributor to the progression of disability in PPMS, and is independent of spinal cord involvement

magnetization transfer imaging demonstrates a distributed pattern of microstructural changes of the cerebral cortex in amyotrophic lateral sclerosis

BACKGROUND AND PURPOSE: To date, damage of the cerebral cortex neurons in ALS was investigated by using conventional MR imaging and proton MR spectroscopy. We explored the capability of MTI to map the microstructural changes in cerebral motor and extramotor cortices of patients with ALS. MATERIALS AND METHODS: Twenty patients with ALS and 17 age-matched healthy controls were enrolled. A high-resolution 3D SPGR sequence with and without MT saturation pulses was obtained on a 1.5T scanner to compute MTR values. Using the FMRIB Software Library tools, we automatically computed the MTR of the cerebral cortex GM in 48 regions of the entire cerebral cortex derived from the standard Harvard-Oxford cortical atlas. RESULTS: The MTR values were significantly lower in patients with ALS than in healthy controls in the primary motor cortex (precentral gyrus), nonprimary motor areas (superior and middle frontal gyri and superior parietal lobe), and some extramotor areas (frontal pole, planum temporale, and planum polare). No correlation was found between regional MTR values and the severity of clinical deficits or disease duration. CONCLUSIONS: MTI analysis can detect the distributed pattern of microstructural changes of the GM in the cerebral cortex of patients with ALS with involvement of both the motor and extramotor areas

Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding

White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factors and neurodegenerative diseases affect lesion load and spatial distribution. At the individual level, WMH vary in contrast, amount and distribution in different white matter regions. In this work, we aimed to improve BIANCA, the FSL tool for WMH segmentation, in order to better deal with these sources of variability. We worked on two stages of BIANCA by improving the lesion probability map estimation (classification stage) and making the lesion probability map thresholding stage automated and adaptive to local lesion probabilities. Firstly, in order to take into account the effect of population-level factors, we included population-level lesion probabilities, modelled with respect to a parametric factor (e.g. age), in the classification stage. Secondly, we tested BIANCA performance when using four alternative classifiers commonly used in the literature with respect to K-nearest neighbour algorithm (currently used for lesion probability map estimation in BIANCA). Finally, we propose LOCally Adaptive Threshold Estimation (LOCATE), a supervised method for determining optimal local thresholds to apply to the estimated lesion probability map, as an alternative option to global thresholding (i.e. applying the same threshold to the entire lesion probability map). For these experiments we used data from a neurodegenerative cohort, a vascular cohort and the cohorts available publicly as a part of a segmentation challenge. We observed that including population-level parametric lesion probabilities with respect to age and using alternative machine learning techniques provided negligible improvement. However, LOCATE provided a substantial improvement in the lesion segmentation performance, when compared to the global thresholding. It allowed to detect more deep lesions and provided better segmentation of periventricular lesion boundaries, despite the differences in the lesion spatial distribution and load across datasets. We further validated LOCATE on a cohort of CADASIL (Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy) patients, a genetic form of cerebral small vessel disease, and healthy controls, showing that LOCATE adapts well to wide variations in lesion load and spatial distribution