Examining empathy and perspective taking among high-risk and low-risk persistently antisocial and nonantisocial young adults

The present study investigated empathy and perspective taking of three groups: high-risk persistently antisocial, low-risk persistently antisocial and non-antisocial young adults. Antisocial behaviour refers to acts such as thefts, drug dealing, bullying and fighting. In particular, gender and group-related differences of young adults with differing histories of antisocial behaviour (namely, high-risk persistently antisocial, low-risk persistently antisocial and non-antisocial groups) were examined. One hundred and thirty-eight participants, aged 22 to 23 years of age, were interviewed by phone. Participants were drawn from the Australian Temperament Project (ATP) which is a prospective longitudinal study that has tracked pathways of antisocial behaviour and psychosocial adjustment from infancy to young adulthood. An examination of group and gender differences found that high-risk persistently antisocial youth endorsed lower levels of affective empathy, as measured by the empathic concern subscale on the Interpersonal Reactivity Index (IRI), compared to their non-antisocial counterparts. Female participants also reported higher levels of affective empathy than male participants. No gender or group differences were found on the cognitive component of the IRI, as measured by the perspective taking subscale. In particular, this study suggests that both gender and the level of risk for persistently antisocial behaviour were significantly related to differences in empathy in young adulthood. Discussion is focused on the theoretical and practical implications of these findings

Wind power forecasting using historical data and artificial neural networks modeling

One of the main parameters affecting the reliability of the renewable energy sources (RES) system, compared to the local conventional power station, is the ability to forecast the RES availability for a few hours ahead. To this end, the main objective of this work is the prognosis of the mean, maximum and minimum hourly wind power (WP) 8hours ahead. For this purpose, Artificial Neural Networks (ANN) modeling is applied. For the appropriate training of the developed ANN models hourly meteorological data are used. These data have been recorded by a meteorological mast in Tilos Island, Greece. For the evaluation of the developed ANN forecasting models proper statistical evaluation indices are used. According to the results, the coefficient of the determination ranges from 0.285 up to 0.768 (mean hourly WP), from 0.227 up to 0.798 (maximum hourly WP) and from 0.025 up to 0.398 (minimum hourly WP). Furthermore, the proposed forecasting methodology shows that is able to give sufficient and adequate prognosis of WP by a wind turbine in a specific location 8 hours ahead. This will be a useful tool for the operator of a RES system in order to achieve a better monitoring and a better management of the whole system

Public perception of sustainable energy innovation: A case study from Tilos, Greece

Renewable and smart grid technologies play a key role in delivering a sustainable energy future for non-interconnected islands. In this context, societal acceptance of proposed interventions manifests itself as a major determinant of planned transitions. With extant scholarship on public acceptability of sustainable energy technologies focusing on local opposition to wind farms, this paper presents timely survey data from the island of Tilos to provide a better understanding of energy-users’ perceptions vis-à-vis novel smart island proposals. Against stultifying narratives highlighting the lack of community acceptance for local interventions, we uncover: a) the widespread acceptance of sustainable and smart energy solutions, and b) the willingness of a large proportion of locals to play their part, as engaged energy prosumers, in a green energy transition. In turn, these findings form the basis for future academic and technical interventions on the island, and inform broader conclusions on public engagement around energy

Sustainable energy solutions for the Aegean Archipelago Islands: What is the public attitude?

In contributing towards the realisation of plans to transform the Aegean into a “green” archipelago, the internationally acclaimed TILOS research consortium seeks to transfer tacit knowledge of smart micro-grids beyond the island of Tilos. However, research on public acceptability of sustainable energy technologies suggests that local opposition might undermine such plans. In order to minimize the problems of technological transfers it is, thus, imperative to embark on an early-stage exploration of public attitudes towards proposed interventions. In this paper, we draw on survey data from across the Aegean to uncover the widespread acceptability of green energy solutions. Simultaneously, though, we uncover how broad acceptability does not always translate into actual acceptance of the TILOS energy model, especially with respect to solutions that affect the end-user. In turn, we argue that these findings should inform future interventions with the ultimate aim of securing public support to “green” the Aegean

Bringing innovation to market: business models for battery storage

Power systems around the world have undergone significant transitions towards a decentralization and decarbonization with higher requirements on supply security and flexibility. Technology advancement helps to improve energy efficiency and bring down cost, which in turn promote the growth of battery storage internationally. Business models of battery storage remain vague given its early stages of development but it is clear that there is no universal business model for batteries given the breadth of applications. In this study, we review the main components of existing business models and highlight the areas to be strengthened in a novel business model. Business models should be distinguished at different scales (utility-scale; behind-the-meter application; community-island mode operation) addressing different needs (to replace existing system or to add new capacity). A successful business model of a battery storage system needs to take into account electricity system transition, market and regulatory barriers, among others. Last but not least, it is important to consider innovations in other technologies for the design of a business model

Assessing the Status of Electricity Generation in the Non-Interconnected Islands of the Aegean Sea Region

Assessment of the electricity generation status for Non-Interconnected Islands (NIIs) of the Aegean Sea region, excluding the electricity systems of Crete and Rhodes, is undertaken in the current study. The authors focus on the long-term analysis of thermal power generation characteristics and also on the challenges so far limiting the contribution of Renewable Energy Sources (RES) in covering the electricity needs of the specific area. According to the present analysis, due to the existing technical limitations, the annual RES shares in the electricity balance of NIIs of the Aegean Sea have since 2010 stagnated in the range of 15% to 18%. Moreover, the performance of thermal power stations for all 30 NII systems is evaluated on the basis of their utilization factor, associated fuel consumption and electricity production costs. The vast majority of these stations is characterized by low capacity factors in combination with high specific fuel consumption and high operational expenses that in the case of smaller scale island regions could even exceed 600€/MWh. At the same time, the authors discuss on the alternatives and encourage further investigation of novel, intelligent energy solutions, such as the smart microgrid and battery-based hybrid power station that are currently developed on the island of Tilos under the implementation of the TILOS Horizon 2020 program

Life cycle greenhouse gas emissions from power generation in China's provinces in 2020

Carbon intensity of power generation is an important indicator to show the direct competitiveness of electricity against the combustion of fossil fuels. In this study, we estimate the carbon intensities of power generation in China's provinces. Most provinces are likely to have a carbon intensity per unit of power generation between 500 and 700 g CO2/kWh in 2020, which justifies the progress of electrification from the power generation perspective. With the growing share of low carbon power generation, most provinces show trends of decline in carbon intensity between 2015 and 2020. However, some provinces are expected to see increase in carbon intensity due to increasing share of coal power generation in their power mixes. Coal is still a major growth contributor in most provinces, despite significant growths of low carbon energy sources. Furthermore, renewable energy sources can help reduce the carbon intensity of power generation, but a better coordination among provinces is required, alongside with strong government support and direction

Assessment of electrical vehicles as a successful driver for reducing CO2 emissions in China

This paper analyses the impacts of the gasoline vehicle replacement programme with EVs at different penetration rates on petroleum and electricity sectors and their CO2 emissions. The study utilises a top-down- type Environmental Input-Output (EI-O) model. Our results show that the replacement of gasoline cars with EVs causes greater impacts on total gasoline production than on total electricity generation. For example, at 5%, 20%, 50%, 70% and 100% gasoline vehicle replacement with EVs, the total gasoline production decreases by 1.66%, 6.65%, 16.62%, 23.27% and 33.24% in policy scenario 1, while the total electricity production only increases by 0.71%, 2.82%, 7.05%, 9.87% and 14.10%. Our study confirms that the gasoline vehicle replacement with EVs, powered by 80% coal, has no effect on overall emissions. The CO2 emissions reduction in the petroleum sector is offset by the increase in CO2 emissions in the electricity sector, leaving the national CO 2 emissions unchanged. By decarbonising the electricity sector, i.e. using 30% less coal in electricity generation mix, the total CO2 emissions will be reduced by 28% (from 10,953 to 7,870 Mt CO 2 ) on the national level. The gasoline vehicle replacement programme with EVs, powered by 50% coal-based electricity, helps reduce CO2 emissions in petroleum sector and contributes zero or a very small proportion of additional CO2 emissions to the electricity sector (policy scenario 2 and 3). We argue that EVs can contribute to a reduction of petroleum dependence, air quality improvement and CO2 emission reduction only when their introduction is accompanied by aggressive electricity sector decarbonisation

On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. Drawing on previous work where a global database of energy resource economic potentials was constructed, this work uses cost distributions of non-renewable resources in order to evaluate global flows of energy commodities. A mathematical framework is given to calculate endogenous flows of energy resources given an exogenous commodity price path. This framework can be used in reverse in order to calculate an exogenous marginal cost of production of energy carriers given an exogenous carrier demand. Using rigid price inelastic assumptions independent of the economy, these two approaches generate limiting scenarios that depict extreme use of natural resources. This is useful to characterise the current state and possible uses of remaining non-renewable resources such as fossil fuels and natural uranium. The theory is however designed for use within economic or technology models that allow technology substitutions. In this work, it is implemented in the global power sector model FTT:Power. Policy implications are given.Comment: 18 pages, 7 figures, 8 pages of supplementary informatio

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network