Carbon-neutral power system enabled e-kerosene production in Brazil in 2050

Rich in renewable resources, extensive acreage, and bioenergy expertise, Brazil, however, has no established strategies for sustainable aviation fuels, particularly e-kerosene. We extend the lens from the often-studied economic feasibility of individual e-kerosene supply chains to a system-wide perspective. Employing energy system analyses, we examine the integration of e-kerosene production into Brazil’s national energy supplies. We introduce PyPSA-Brazil, an open-source energy system optimisation model grounded in public data. This model integrates e-kerosene production and offers granular spatial resolution, enabling federal-level informed decisions on infrastructure locations and enhancing transparency in Brazilian energy supply scenarios. Our findings indicate that incorporating e-kerosene production can bolster system efficiency as Brazil targets a carbon-neutral electricity supply by 2050. The share of e-kerosene in meeting kerosene demand fluctuates between 2.7 and 51.1%, with production costs varying from 113.3 to 227.3 €/MWh. These costs are influenced by factors such as biokerosene costs, carbon pricing, and export aspirations. Our findings are relevant for Brazilian policymakers championing aviation sustainability and offer a framework for other countries envisioning carbon-neutral e-kerosene production and export

Highly efficient triazine/carbazole-based host material for green phosphorescent organic light-emitting diodes with low efficiency roll-off

Two novel triazin/carbazole-based host materials were designed and synthesized, which demonstrated outstanding EL performance with maximum CE, PE and EQE of 69.3 cd A−1, 54.2 lm W−1 and 21.9%, respectively.</p

Carbon-neutral power system enabled e-kerosene production in Brazil in 2050

Rich in renewable resources, extensive acreage, and bioenergy expertise, Brazil, however, has no established strategies for sustainable aviation fuels, particularly e‑kerosene. We extend the lens from the often‑studied economic feasibility of individual e‑kerosene supply chains to a system‑wide perspective. Employing energy system analyses, we examine the integration of e‑kerosene production into Brazil’s national energy supplies. We introduce PyPSA‑Brazil, an open‑source energy system optimisation model grounded in public data. This model integrates e‑kerosene production and offers granular spatial resolution, enabling federal‑level informed decisions on infrastructure locations and enhancing transparency in Brazilian energy supply scenarios. Our findings indicate that incorporating e‑kerosene production can bolster system efficiency as Brazil targets a carbon‑neutral electricity supply by 2050. The share of e‑kerosene in meeting kerosene demand fluctuates between 2.7 and 51.1%, with production costs varying from 113.3 to 227.3 €/MWh. These costs are influenced by factors such as biokerosene costs, carbon pricing, and export aspirations. Our findings are relevant for Brazilian policymakers championing aviation sustainability and offer a framework for other countries envisioning carbon‑neutral e‑kerosene production and export

Downscaling ERA5 wind speed data: a machine learning approach considering topographic influences

Energy system modeling and analysis can provide comprehensive guidelines to integrate renewable energy sources into the energy system. Modeling renewable energy potential, such as wind energy, typically involves the use of wind speed time series in the modeling process. One of the most widely utilized datasets in this regard is ERA5, which provides global meteorological information. Despite its broad coverage, the coarse spatial resolution of ERA5 data presents challenges in examining local-scale effects on energy systems, such as battery storage for small-scale wind farms or community energy systems. In this study, we introduce a robust statistical downscaling approach that utilizes a machine learning approach to improve the resolution of ERA5 wind speed data from around 31 km × 31 km to 1 km × 1 km. To ensure optimal results, a comprehensive preprocessing step is performed to classify regions into three classes based on the quality of ERA5 wind speed estimates. Subsequently, a regression method is applied to each class to downscale the ERA5 wind speed time series by considering the relationship between ERA5 data, observations from weather stations, and topographic metrics. Our results indicate that this approach significantly improves the performance of ERA5 wind speed data in complex terrain. To ensure the effectiveness and robustness of our approach, we also perform thorough evaluations by comparing our results with the reference dataset COSMO-REA6 and validating with independent datasets

Executive Compensation and the Split Share Structure Reform in China

AcceptedArticle"This is an Accepted Manuscript of an article published by Taylor & Francis in European Journal of Finance on 08 Jul 2013, available online: http://wwww.tandfonline.com/10.1080/1351847X.2013.802250."The split share structure reform in China enables state shareholders of listed firms to trade their restricted shares. This renders the wealth of state shareholders more strongly related to share price movements. We predict that this reform will create remuneration arrangements that strengthen the relationship between Chinese firms’ executive pay and stock market performance. We confirm this prediction by showing that there is such an effect among state-controlled firms, and especially those where the dominant shareholders have a greater incentive to improve share return performance. Our results indicate that this reform strengthens the accountability of executives to external monitoring by the stock market, and therefore benefits minority shareholders in China

Ecological strategies of Hyphantria cunea (Lepidoptera: Arctiidae) response to different larval densities

Population density is an essential factor affecting the life history traits of insects and their trade-off relationships, as increasing density intensifies intraspecific competition. It decreases the average resources available to individuals within a population, affecting their morphology, physiology, behavior, and fitness. The fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Arctiidae), has been an invasive pest of forest trees, ornamental plants, and fruit trees in China for many years. The larvae have a typical aggregation habit before the fourth instar and keep spitting silk to gather the damaged leaves into silk webs. However, the fitness of H. cunea in response to population density remains unclear. In this study, the critical biological parameters, food utilization, and population parameters of H. cunea in response to different rearing densities were investigated. The results showed that under high population density, H. cunea larvae showed better performance, with faster development, higher survival rates, and shorter generation time, but pupal weight and female fecundity decreased as population density increased. In contrast, for larvae raised in low density, the developmental period was prolonged, and mortality was increased, while higher food utilization, greater body size, and female fecundity were observed. Both males and females had similar development strategies in response to the density, but females may be more resistant to crowding than males. In conclusion, H. cunea could adopt different ecological strategies against the stress of density. High population densities result in shorter generation cycles and higher survival rates. Conversely, the low-density generation period becomes longer but with greater fecundity. The results may help determine the possible outbreak mechanism and develop effective population monitoring and forecasting measures for H. cunea