Creating a European Hub

Techno-economic evaluation of CO2 transport from a lignite-fired IGCC plant in the Czech Republic

Aim/purpose – This paper aims at determining the role of Poland in the Belt and Road Initiative (BRI) and identifying an alternative course of the trail. However, there are still many variables that can significantly affect the extent of Poland’s participation in BRI. Design/methodology/approach – The paper was based on a literature query and inter- views with six experts of the Polish logistics environment closely connected to the con- cept of the New Silk Road. The interviews and the literature analysis allowed of the authors to define potential scenarios for the course of the New Silk Road. In addition, the SWOT analysis was used to identify the Poland’s role in BRI. Findings – The most important factors that can significantly contribute to Poland’s par- ticipation in BRI are a very convenient geographical location and a strong logistics sec- tor, whereas the main negative factors are the ambivalent attitude of the Polish author i- ties towards the Chinese party and the underdeveloped modern railway infrastructure. The study identified some potential scenarios for the route of the New Silk Road, i.e., Poland as a European hub, transit only, southern road and northern road (ro-ro neigh- bors). The first scenario is the most favorable for Poland – Poland as a European hub. This is due to the current course of the New Silk Road and the location of Poland on the most economically effective transport corridor. Research implications/limitations – The research findings allow for a relatively precise definition of possible scenarios of the BRI Northern Corridor through areas directly related to Poland. The results may contribute to raising knowledge and awareness about BRI, which may provide insights into an academic and social debate on this topic. The upshot is that the results may entail actual activities contributing to increasing the chances of Poland for being a European hub gate for BRI. Originality/value/contribution – Previous publications explored various route alterna- tives of the entire New Silk Road, whereas there was no analysis of the last stage of the transport corridor on which Poland lies. The paper is a response to this research gap. Keywords: Belt and Road Initiative, New Silk Road, Northern Corridor, logistics, inter- national trade. JEL Classification: E27, E61, F15.

Several recent studies pointed out to strong links among the most liquid core European natural gas markets. However, the evidence on the integration of less liquid, peripheral and core European markets is scarce. We address this topic by investigating the dynamics of daily natural gas prices quoted at six European hubs located in Germany, Poland, Czechia, Austria, Italy and Spain. We explore to what extend prices in these hubs are driven by price changes in the most liquid, benchmark European hub (TTF, Netherlands), other energy commodity prices (oil and coal) and local natural gas market fundamentals (whether conditions and gas inventories). We find that natural gas markets are driven by predominantly by changes in the benchmark hub as well as deviations from the law of one price. We also show that other energy commodity prices as well as idiosyncratic factors are important in the least squares regression, but not in a more elaborated GARCH model. These results adds to the discussion on the integration of European natural gas markets.

Background:In the past, two studies found ensembles of human judgement forecasts of COVID-19 to show predictive performance comparable to ensembles of computational models, at least when predicting case incidences. We present a follow-up to a study conducted in Germany and Poland and investigate a novel joint approach to combine human judgement and epidemiological modelling. Methods:From May 24th to August 16th 2021, we elicited weekly one to four week ahead forecasts of cases and deaths from COVID-19 in the UK from a crowd of human forecasters. A median ensemble of all forecasts was submitted to the European Forecast Hub. Participants could use two distinct interfaces: in one, forecasters submitted a predictive distribution directly, in the other forecasters instead submitted a forecast of the effective reproduction number Rt. This was then used to forecast cases and deaths using simulation methods from the EpiNow2 R package. Forecasts were scored using the weighted interval score on the original forecasts, as well as after applying the natural logarithm to both forecasts and observations. Results:The ensemble of human forecasters overall performed comparably to the official European Forecast Hub ensemble on both cases and deaths, although results were sensitive to changes in details of the evaluation. Rt forecasts performed comparably to direct forecasts on cases, but worse on deaths. Self-identified “experts” tended to be better calibrated than “non-experts” for cases, but not for deaths.Conclusions:Human judgement forecasts and computational models can produce forecasts of similar quality for infectious disease such as COVID-19. The results of forecast evaluations can change depending on what metrics are chosen and judgement on what does or doesn't constitute a "good" forecast is dependent on the forecast consumer. Combinations of human and computational forecasts hold potential but present real-world challenges that need to be solved.

In this study, we investigate the estimates of the convenience yield implied in European natural gas hub trading. In addition to the net convenience yield, we provide two option/based approaches, which connect to the economic idea of the convenience yield as being the benefits from holding the physical commodity. In particular, we approximate the convenience yield via lookback and Asian options. Our empirical results are consistent with the intuition conveyed by the theory of storage. We conclude that the choice of an adequate approximation method should depend on the market under investigation, in particular, on the existence of market frictions such as short/sale constraints or restricted storage access. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

BackgroundRecurring COVID-19 waves highlight the need for tools able to quantify transmission risk, and identify geographical areas at risk of outbreaks. Local outbreak risk depends on complex immunity patterns resulting from previous infections, vaccination, waning and immune escape, alongside other factors (population density, social contact patterns). Immunity patterns are spatially and demographically heterogeneous, and are challenging to capture in country-level forecast models.MethodsWe used a spatiotemporal regression model to forecast subnational case and death counts and applied it to three EU countries as test cases: France, Czechia, and Italy. Cases in local regions arise from importations or local transmission. Our model produces age-stratified forecasts given age-stratified data, and links reported case counts to routinely collected covariates (e.g. test number, vaccine coverage). We assessed the predictive performance of our model up to four weeks ahead using proper scoring rules and compared it to the European COVID-19 Forecast Hub ensemble model. Using simulations, we evaluated the impact of variations in transmission on the forecasts. We developed an open-source RShiny App to visualise the forecasts and scenarios.ResultsAt a national level, the median relative difference between our median weekly case forecasts and the data up to four weeks ahead was 25% (IQR: 12–50%) over the prediction period. The accuracy decreased as the forecast horizon increased (on average 24% increase in the median ranked probability score per added week), while the accuracy of death forecasts was more stable. Beyond two weeks, the model generated a narrow range of likely transmission dynamics. The median national case forecasts showed similar accuracy to forecasts from the European COVID-19 Forecast Hub ensemble model, but the prediction interval was narrower in our model. Generating forecasts under alternative transmission scenarios was therefore key to capturing the range of possible short-term transmission dynamics.DiscussionOur model captures changes in local COVID-19 outbreak dynamics, and enables quantification of short-term transmission risk at a subnational level. The outputs of the model improve our ability to identify areas where outbreaks are most likely, and are available to a wide range of public health professionals through the Shiny App we developed.

In the past, two studies found ensembles of human judgement forecasts of COVID-19 to show predictive performance comparable to ensembles of computational models, at least when predicting case incidences. We present a follow-up to a study conducted in Germany and Poland and investigate a novel joint approach to combine human judgement and epidemiological modelling. From May 24th to August 16th 2021, we elicited weekly one to four week ahead forecasts of cases and deaths from COVID-19 in the UK from a crowd of human forecasters. A median ensemble of all forecasts was submitted to the European Forecast Hub. Participants could use two distinct interfaces: in one, forecasters submitted a predictive distribution directly, in the other forecasters instead submitted a forecast of the effective reproduction number R t. This was then used to forecast cases and deaths using simulation methods from the EpiNow2 R package. Forecasts were scored using the weighted interval score on the original forecasts, as well as after applying the natural logarithm to both forecasts and observations. The ensemble of human forecasters overall performed comparably to the official European Forecast Hub ensemble on both cases and deaths, although results were sensitive to changes in details of the evaluation. R t forecasts performed comparably to direct forecasts on cases, but worse on deaths. Self-identified "experts" tended to be better calibrated than "non-experts" for cases, but not for deaths. Human judgement forecasts and computational models can produce forecasts of similar quality for infectious disease such as COVID-19. The results of forecast evaluations can change depending on what metrics are chosen and judgement on what does or doesn't constitute a "good" forecast is dependent on the forecast consumer. Combinations of human and computational forecasts hold potential but present real-world challenges that need to be solved.

Issue/problem A key barrier to implementing artificial intelligence (AI) in healthcare is the lack of robust and secure infrastructure for developing, testing, and validating innovative AI-based solutions. Without structured environments, it is difficult to translate AI advances into clinical practice, especially in areas such as breast cancer diagnostics. This infrastructure gap hinders the creation of clinically relevant and safe AI tools, particularly in resource-limited settings, and risks the deployment of poorly validated or non-compliant solutions. Description of the problem To address this, the Croatian Institute of Public Health (CIPH) participated in the organization of an innovation challenge within the AI4Health.Cro European Digital Innovation Hub. The challenge targeted breast cancer diagnostics, tasking teams with developing AI models for BI-RADS prediction and lesion localization, ensuring model interpretability, and designing a user interface for clinical use. The project leveraged real, anonymized mammography data and was structured in two phases: initial model development with open data, followed by refinement within a Secure Processing Environment (SPE). The initiative included clear protocols for data security, anonymization, and compliance with GDPR, and fostered collaboration among multiple institutions. Results Approximately 2 terabytes of mammographic images and reports were processed within the SPE. Radiologists contributed annotations to enhance dataset quality for model development. Fourteen teams created AI model prototypes, achieving promising preliminary results. Lessons The project demonstrated that secure, interoperable infrastructure and clear data governance are essential for responsible AI innovation in healthcare. Structured, multi-institutional collaboration and early clinical involvement proved critical for developing trustworthy, clinically relevant AI tools. Key messages • Robust infrastructure enables secure data handling and reliable computing, ensuring safe, effective AI innovation that advances healthcare diagnostics and improves patient outcomes. • Cross-sector partnerships between healthcare, academia and tech innovators, coupled with secure data protocols, drive responsible AI innovation and real-world clinical integration.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a scientific mission that collects high spatio‐temporal resolution (∼70 m, 1–5 days average revisit time) thermal images since its launch on 29 June 2018. As a predecessor of future missions, one of the main objectives of ECOSTRESS is to retrieve and understand the spatio‐temporal variations in terrestrial evapotranspiration (ET) and its responses to soil water availability and atmospheric aridity. In the European ECOSTRESS Hub (EEH), by taking advantage of land surface temperature (LST) retrievals, we generated ECOSTRESS ET products over Europe and Africa using three models with different structures and parameterization schemes, namely Surface Energy Balance System (SEBS) and Two Source Energy Balance (TSEB) parametric models, as well as the non‐parametric Surface Temperature Initiated Closure (STIC) model. A comprehensive evaluation of the EEH ET products was conducted with respect to flux measurements from 19 eddy covariance sites in Europe over six different biomes with diverse aridity levels. Results revealed comparable performances of STIC and SEBS (RMSE of ∼70 W m−2). However, the relatively complex TSEB model produced a higher RMSE of ∼90 W m−2. Comparison between STIC ET estimates and the operational ECOSTRESS ET product from NASA PT‐JPL model showed a larger RMSE (around 50 W m−2 higher) for the PT‐JPL ET estimates. Substantial overestimation (>80 W m−2) in PT‐JPL ET estimates was evident over shrublands and savannas, presumably due to weak constraint of LST in the model. Overall, the EEH supports ET retrieval for the future high‐resolution thermal missions.

In the absence of a systematic approach to epidemiological modeling in Slovenia, various isolated mathematical epidemiological models emerged shortly after the outbreak of the COVID-19 epidemic. We present an epidemiological model adapted to the COVID-19 situation in Slovenia. The standard SEIR model was extended to distinguish between age groups, symptomatic or asymptomatic disease progression, and vaccinated or unvaccinated populations. Evaluation of the model forecasts for 2021 showed the expected behavior of epidemiological modeling: our model adequately predicts the situation up to 4 weeks in advance; the changes in epidemiologic dynamics due to the emergence of a new viral variant in the population or the introduction of new interventions cannot be predicted by the model, but when the new situation is incorporated into the model, the forecasts are again reliable. Comparison with ensemble forecasts for 2022 within the European Covid-19 Forecast Hub showed better performance of our model, which can be explained by a model architecture better adapted to the situation in Slovenia, in particular a refined structure for vaccination, and better parameter tuning enabled by the more comprehensive data for Slovenia. Our model proved to be flexible, agile, and, despite the limitations of its compartmental structure, heterogeneous enough to provide reasonable and prompt short-term forecasts and possible scenarios for various public health strategies. The model has been fully operational on a daily basis since April 2020, served as one of the models for decision-making during the COVID-19 epidemic in Slovenia, and is part of the European Covid-19 Forecast Hub.

This article responds to the call for more empirical knowledge about transnational environmental crime. It does so by analysing the case of illegal transports of electronic waste (e-waste) in a European trade hub. Given the complexity and global nature of transnational environmental crime, it is difficult to determine which actors are involved. In this regard, a local research setting allows the actors involved in illegal transports of e-waste to be identified. This research tries to determine whether these actors and their roles can be considered legal or illegal and illustrates the legal-illegal interfaces in e-waste flows. Moreover, this case study analyses the push, pull and facilitating factors and therefore looks at what motivations and opportunities shape the flows of e-waste in locations of origin, transit and destination. The results show that the social organisation and emergence of transnational environmental crime is on a thin line between legal and illegal which needs to be contextualised within the global reality of the locations of origin, transit and destination.

In September 2022, the European Hub for Planetary Health (EHPH) was established with the aim of coordinating a movement to promote leadership across multidisciplinary communities in Europe towards a synergistic approach to planetary health. www.planetaryhealth.eu The vision of the Policy Engagement Working Group (PEWG) of the EHPH is that Planetary Health should be the central mindset of everyday life for all people, for the purpose of safeguarding a liveable planet for future generations. It is necessary to apply scientific insights to promote Planetary Health-based policies whilst being mindful of the social and economic pressures on populations to ensure that such policies are actionable. The mission of the Policy Engagement Working Group is to build bridges between researchers and policy makers in Europe (on local, regional, national, and EU levels), to promote Planetary Health as a central line of thought for policy making. The PEWG aims to be an interface between views and insights of the members of the Planetary Health European Hub and governments, academia, and other relevant actors in European policy, to move the evidence-base for Planetary Health higher on the political agenda so it is integrated into policies, strategies, and policy agendas. We want to support enhanced policy coherence and vertical coordination in support of Planetary Health and sustainability at international, national, regional, and local levels. The priorities of the Policy Engagement Working Group include knowledge translation; awareness raising by dissemination of information and signposting to reliable sources that can be for the benefit of policy makers and the public on the concept of Planetary Health; policy dissemination and analysis; policy advice and advocacy to European health services and governments; capacity building and development of operational methodologies for national, regional and local Planetary Health Operations.

Theatre on Tour: Amsterdam’s <i>Schouwburg</i> as a European Hub

The First European Planetary Health Congress, held from 5 to 7 July 2023 at ARTIS in Amsterdam, represented a significant milestone in the global movement of Planetary Health. The event brought together 121 attendees from academia and the private sector dedicated to addressing the impact of human disruptions to natural systems on the well-being of life on Earth. Co-organized by Natura Artis Magistra (ARTIS) and the European Hub of the Planetary Health Alliance (PHA), the Congress featured five workshops: The Future of Planetary Health Cities, Impact through Synergy, Planetary Health Education, Movement Building, and Food and Microbes. Oral presentations addressed the theme of how human health and the health of human civilization depend on the natural environment, including subthemes on Earth, Water, and Food. Additionally, the subtheme of Humans reflected on how humanity can thrive within Planetary Boundaries and how to imagine a prosperous future for all life on Earth. The First European Planetary Health Congress offered a platform for fostering sustainable, just, and equitable societies within ecological limits. Accordingly, ARTIS and the European Hub aim to shape a hopeful future for generations to come.

Women in Global Health (WGH) is a global movement with the largest network of women and allies working to challenge power and privilege for gender equity in health. It has grown to include over 50,000 supporters in 90 countries and has 41 official chapters. The WGH European network is an established hub of the global WGH movement focusing on gender equality in Europe Some of the WGH European Chapters have been engaged in the work with Ukrainian migrants.The workshop will start with a brief introduction to the WGH network and European hub. Following these opening remarks, the session will review the ongoing conflict in Ukraine through a gender equity lens, exploring what the crisis has taught us and how these experiences can help improve gender equity interventions in the future. The session will focus on two topics. 1) exploring the daily realities of women living in the conflict situation in Ukraine and 2) the situation of Ukrainian female refugees in European Member States. We will hear personal stories and accounts from Ukrainian women themselves and from professionals working with them both in-country and in European Member States. The inputs will be moderated in an interview style by one of the WGH European Chapter leads. The interviews will be followed by an interactive section where discussions will be facilitated with the audience in small groups. These discussions will centre on the accounts heard in the session and draw on any personal experience audience members may have of working with women in/from conflict situations, in Ukraine or elsewhere. In the plenary, we will then ask the small for feedback on their conversations. with the aim of discussing what the WGH movement can learn from these experiences with respect to applying them to interventions in gender equity in migrant health in the future. A final input from a female health leader will reflect on the session content and summarise its conclusions. Key messages • Gender equity can bring about transformative change in times of crisis. • Gender equity is not merely the ethical way to advance, but an operational necessity in time of crisis. Speakers/Panelists Sabine Ludwig Charité - Universitätsmedizin Berlin, Berlin, Germany Halyna Skipalska Ukrainian Foundation for Public Health, Kyiv, Ukraine Paloma Cuchi WHO, Poland