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Damage costs from coastal flooding are high and are expected to increase further due to rising sea levels. The associated risks suggest a need for developing methodologies and models to assess damage costs in coastal areas as a basis for decision-making on climate change adaptation. The accuracy of damage cost estimates is critical in cost-effective decision-making on adaptation measures, reflecting climate hazards, flood levels, and associated damage costs. However, detailed models require extended work compared to simpler models due to demands on input data, including land use, damage costs, and adaptation options and costs. In the paper, varying levels of resolution, damage costs and flood models are assessed for coastal flooding risks for two Danish urban areas. Two damage cost models are used: a detailed, context-specific model using local high-resolution land use- and flood damage cost data and a less detailed model with lower-resolution land use data and damage costs based on generic European cost curves. Two flood models are used for the assessment using the detailed damage cost model based on a dynamic and a static flood approach, respectively. For the coarser model, only a static flood model is used. Significant differences are identified between the modelling approaches: The flood area varies up to a factor of ten for static floods due to the digital elevation map (DEM) model alone and a factor of 17 when changing both the DEM and using a dynamic flood. Corresponding factors for resulting damage costs are four and five, respectively.

In support of West Africa's potential energy transition under climate change, an international team of scientists and a wide range of local stakeholders in Ghana and Burkina Faso jointly assessed different mitigation and adaptation pathways for energy and water supply and demand, including their implications for achieving SDGs, in a transdisciplinary approach. They iteratively co-developed a range of future scenarios based on i) stakeholder knowledge and priorities, ii) countries' national plans, and iii) simulations with a set of complementary energy and water models. Unlike current national plans, the more ambitious scenarios indicate that the projected rapid increase in electricity demand could be met almost entirely from renewables, but that a diversification beyond hydropower will be necessary. Phasing out fossil fuels would bring West African countries's energy policies in line with Paris Agreement targets and generate additional socio-economic and environmental co-benefits.

Increasing renewable sources in the energy mix is essential to mitigate climate change, not least in countries where the energy demand is likely to rise over the coming decades to reduce or even skip durations of time where fossils dominate. For Africa, solar photovoltaic (PV) and inland wind energy, combined with hydropower, provide significant and untapped potentials, whereas trends and robustness measures need further investigation. This study aims to gain insight into distributed trends in solar PV and wind energy potentials over Africa. This study employs relevant metrics, including relative change, model agreement, robustness, bias, and absolute levels for every available model combination and two climate scenarios, with energy planning purposes in mind. The study finds that regional climate models were the primary control of spatio-temporal patterns over their driving global climate model. Solar PV potentials show more coherence between models, a lower bias and general high potentials in most African regions than wind potentials. Favourable locations for inland wind energy include mainly the regions of greater Sahara and the Horn region. For wind and solar potentials combined, scattered locations within Sahara stand out as the most favourable across scenarios and periods. The analysis of minimum energy potentials shows stable conditions despite low potentials in certain regions. The results demonstrate a potential for solar and wind power in most of the African regions and highlight why solar and wind power or synergies of energy mix should be considered for local energy planning and storage solutions.

Data centres (DCs) are large electricity consumers, estimated to account for around 1% of worldwide electricity usage. They release excess heat (EH) during the operation, which can be recovered in district heating (DH) networks. DCs are expected to satisfy the rising demand for digital services.The electricity usage for cooling and available EH from the operation of DCs depends on the air temperature that changes with geographical location. The changes are not uniform and global warming pathways will influence them. Here lays the contribution of the present article. We use an existing thermodynamic model of a hyper-scale DC for different locations in Ukraine to analyse the electricity usage for cooling and EH availability for two climate scenarios (RCP2.6 and RCP 4.5) in 2010–2050.The results show that the electricity consumption for cooling and available EH can vary greatly within Ukraine. The electricity consumption for cooling is over two times higher in the hottest compared to the coldest location in the country, while the emitted EH is around 80% higher on average. The global climate pathway has a minor influence — the electricity use for cooling and EH availability are 4% higher in RCP4.5 than in RCP2.6. Finally, one hyper-scale DC of 150 MW could cover the demand for space heating and domestic hot water for roughly 100 thousand people. This assessment is an important input to consider when developing plans to rebuild Ukraine.

Extreme sea levels and coastal flooding can cause devastating socio-economic damages and even loss of lives. Robust and timely risk mitigation requires knowledge of recurrence frequencies, but such estimates are riddled with uncertainties, especially regarding high-impact, low-probability events. In the North Sea–Baltic Sea region, considerable inter- and intra-decadal variability mean that the risks of present-day, wind-driven extreme sea levels are not fully determined. This knowledge gap is becoming more urgent for decision-makers and stakeholders since mitigation of the impacts of current and future flooding hazards, e.g. by coastal adaptation schemes, ideally requires detailed knowledge on the current and future storm-surge regime.In the present study, we investigate the wind-driven sea-level responses across the entirety of the complex Danish coastlines. We use an idealised framework to map the ranges of critical wind directions systematically by applying an advanced oceanographic model for storm surges driven by synthetic wind fields. We find that the modelled extreme water levels increase linear-to-quadratically with increased wind speed. This increase shows no signs of levelling off even for static winds of 40ms−1, although this finding is dependent on the wind stress parameterisation, which becomes uncertain for such strong wind forcing. The magnitudes of the resulting extreme water levels are highest in the Wadden Sea region in the southeastern North Sea. Still, when taking local sea-level variability into account, the most extreme incidents are undoubtedly generated in the western Baltic Sea.Hereafter, and based on the same synthetic wind fields, we investigate a complementary methodology’s potential to generalise the synthetic modelling results. For this purpose, site-specific relations between the dynamic wind forcing (i.e. wind speed and wind direction), parameters defining the local conditions and extreme sea levels are determined based on the dynamic model simulations that are generalised using a novel empirical–statistical method. The approach is tested for the North- and Baltic Seas and performs reasonably well for the highly complex coastlines around Denmark.We propose that our method could pave the way for improved operational and physically-based impact assessments based on full, large-scale regional climate model projections as a complement to select sets of coupled ocean projections.

A flipped classroom, also known as flipped learning, is a teaching method in which students watch online lectures at home, followed by group work in the classroom. This study aimed to evaluate the efficacy of a flipped classroom vs. traditional lectures in a statistics and epidemiology course at Oslo Metropolitan University. The study used a pragmatic randomized controlled trial design in which one group of students received traditional lectures, while another group received flipped classroom teaching. Each participating student had previous experience with both teaching methods. No difference was found in exam grades between the two groups, but the students preferred the flipped classroom significantly (p = .008). Students who received instruction in the flipped classroom preferred this method to a higher degree than those who received traditional lectures (p = .018).

Climate change and increased coastal urbanization are causing low-lying coastlines to become increasingly susceptible to the threat of extreme water levels and coastal flooding. Robust decision-making on adaptation in the coastal zone, based on reliable ocean-modelling tools, is therefore crucially contingent on accurate assessments of current and future storm surge hazards. This accuracy relies considerably on the quality of the wind forcing used in the ocean models. In this paper, we use a high-resolution, regional 3D ocean model (HBM) covering the North Sea and Baltic Sea to simulate extreme water levels during three extreme storm surge events with different dynamics and patterns, in order to assess their impacts along Denmark's coastlines, which are of varying levels of complexity. We demonstrate that the model is able to reproduce the observed extreme high-water levels accurately, indicating that the system is well suited for producing simulations of present and future projections of extreme storm surges with high resulting impacts and damage potentials. Additionally, we quantify the level at which acknowledged deficiencies in the otherwise most suitable atmospheric forcing data set influence the results of the storm surge simulations. We found that reducing the temporal resolution of the forcing data – that is, replacing two out of every six time stamps with linearly interpolated values – is preferable to using the original forcing data set when recurring noise is present in these time stamps. As a result, for given storm surge events, and depending on the stage reached in the storm's evolution, mean absolute errors can be reduced by 4.5 cm. This emphasizes the importance of considering such model fluctuations when coupling high-resolution atmosphere and ocean models. [Display omitted] • 3D ocean model HBM skillfully reproduces extreme water levels along Danish coastlines. • Performance improves when two out of every six forcing time stamps are removed. • Slightly reduced temporal resolution tops higher resolution but noisy data. • Based on these results, we find the HBM model validated for future projection runs. [ABSTRACT FROM AUTHOR]

Abstract Background Stroke incidence rates have fallen in high-income countries over the last several decades, but findings regarding the trend over recent years have been mixed. The aim of the study was to describe and model temporal trends in incidence of stroke by age and sex between 2010 and 2015 in Norway, and to generate incidence projections towards year 2040. Methods All recorded strokes in Norway between 2010 and 2015 were extracted from the National Patient Registry and the National Cause of Death Registry. We report incidence by age, sex, and year; in raw numbers, per 100,000 person-years, by WHO and European standard populations; and generated statistical models by stroke type, age, sex, and year; and projected stroke incidence toward year 2040. Results The data covered 30.1 million person-years at risk, 53431 unique individuals hospitalized with a primary stroke diagnosis, and 6315 additional individuals registered as dead due to stroke. From 2010 to 2015, individuals suffering stroke per 100,000 person-years dropped from 239 to 195 (208 to 177 excluding immediate deaths). The decline was driven by ischemic strokes, with a statistically non-significant time trend for hemorrhagic stroke. Conclusions The age-dependent incidence of ischemic strokes in Norway is declining rapidly, and more than compensates for the growth and ageing of the population. Comparisons with historic incidence statistics show that the reduction in incidence rates has accelerated over the last two decades.

Abstract Background Hip fracture patients are frail and have a high mortality. We investigated whether the introduction of fast track care reduced the 30-day mortality after hip fractures. Methods Fast track hip fracture care was established at our institution in October 2013. Data from the Norwegian Hip Fracture Register and electronic hospital records were merged for 2230 hip fracture patients operated in our department from January 2012 through December 2015. 1090 of these patients were operated before (conventional treatment group) and 1140 patients were operated after the introduction of fast track care (fast track group). Data were analysed by univariate analysis and binary logistic regression. Results Mortality did not differ significantly between the conventional treatment group and the fast track group at 30 days (7.9% vs. 6.5%), 90 days (13.5% vs. 12.5%) and one year (22.8% vs. 22.8%). Median admission time and time to surgery were significantly shorter in the fast track group than in the conventional treatment group (1.1 h vs. 3.9 h and 23.6 h vs. 25.7 h, both p

Water plays a quintessential role in the lives of individuals and communities. In recent decades, population growth, migration from rural to urban areas, industrialization, and climate change have increasingly jeopardized the sustainability of cities, especially in developing countries, including Iran. The purpose of this study is to assess recent and future perspectives for urban water security in Iran. To do so, the paper extends previous water security studies within the region by collecting data on urban water security from a cohort of cities rather than a single location. To assess the state of water security in the recent past, from 2013 to 2019, we introduce a dedicated framework comprised of five dimensions and twelve indicators. In estimating future water resources for Iran in the period up to 2100, ensemble-based hydro-climatic regional climate model projections for RCPs 4.5 and 8.5 were analyzed in time and space. The results show that four of the five dimensions of present-day urban water security, including accessibility, availability, water health and sanitation, and the economic value of water, all demonstrate general improvements in water-related urban infrastructure, whereas the environmental indicator depicts a decreasing trend. Future projected trends for Iran's hydro-climate show a general decline in its net availability from already scarce conditions and also increased variability due to climate change. In general, the study indicates both advances in Iran's urban water security recently and severe implications for future water availability in certain regions and periods in the decades to come. The study also advises policymakers to seek to mitigate the water crisis in so far, as also enforced by climate change, by increasing the appropriate infrastructure and using new technologies in the water and wastewater industry. [Display omitted] • A new and recent data set on urban water security indicators in Iran was analyzed. • Twelve indicators formed the novel and combined urban water security index. • Four out of five water security dimensions showed progress during 2013–2019. • The urban water environment dimension showed a declining trend. • Projected future water recourses in Iran is under increasing pressure towards 2100. [ABSTRACT FROM AUTHOR]

Climate change causes transformations to the conditions of existing agricultural practices appointing farmers to continuously evaluate their agricultural strategies, e.g., towards optimising revenue. In this light, this paper presents a framework for applying Bayesian updating to simulate decision-making, reaction patterns and updating of beliefs among farmers in a developing country, when faced with the complexity of adapting agricultural systems to climate change. We apply the approach to a case study from Ghana, where farmers seek to decide on the most profitable of three agricultural systems (dryland crops, irrigated crops and livestock) by a continuous updating of beliefs relative to realised trajectories of climate (change), represented by projections of temperature and precipitation. The climate data is based on combinations of output from three global/regional climate model combinations and two future scenarios (RCP4.5 and RCP8.5) representing moderate and unsubstantial greenhouse gas reduction policies, respectively. The results indicate that the climate scenario (input) holds a significant influence on the development of beliefs, net revenues and thereby optimal farming practices. Further, despite uncertainties in the underlying net revenue functions, the study shows that when the beliefs of the farmer (decision-maker) opposes the development of the realised climate, the Bayesian methodology allows for simulating an adjustment of such beliefs, when improved information becomes available. The framework can, therefore, help facilitating the optimal choice between agricultural systems considering the influence of climate change.