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Abstract With almost 40% of the global population suffering from water scarcity, the need to manage water resources is evidently urgent. While water and energy systems are intrinsically linked, the availability of comprehensive, integrated data sets across the domains of water and energy is generally lacking. As a result, estimated indicators representing volumes of water usage per unit of electricity or fuel produced are often required to analyse the water-energy nexus. In this paper, an "ensemble" of indicators is assembled representing water usage spanning different electricity-generation technologies based on previously published works in an attempt to depict the level or lack of detail in current large-scale energy-sector water-usage data. Based on these, the degree in which using such estimates is suitable for reproducing electricity-production water-usage at coarser spatio-temporal scales is assessed. The performance of the ensemble median/min/max as a predictor of water use is evaluated for the period from 1980 to 2015 using additional information about the constituents of the European energy system. Comparing with the reported values for 1980–2015, the median provides a skillful reproduction of historical yearly water use for the EU (EU28) as a whole. A further analysis for 2015 indicates that reasonable agreement is also seen at the country level. Thus, the results suggest that an "ensemble-based approach" has the potential to provide sturdy estimates of yearly water use by energy systems for analyses at both the country and regional levels. Graphical abstract Unlabelled Image Highlights • Electricity plant water withdrawals are estimated using a comprehensive analysis. • Estimates resemble reported levels on spatio-temporal scales of country/year. • The results support perspectives in larger scale water-energy nexus management. • More open source, freely available and detailed data are however urged. [ABSTRACT FROM AUTHOR]

The current transition toward added renewables into the power mix is essential to mitigate climate change effects, but the energy transition has environmental impacts outside the scope of greenhouse gas emissions that also need attention. One such impact is the water-energy dependency nexus, where water dependencies are also seen for non-fossil technologies such as concentrated solar power (CSP), bioenergy and hydropower and mitigation technologies such as carbon capture and storage (CCS). In this light, the selection of power production technologies can potentially affect long-term water resource renewability and dry summer conditions, causing, e.g., power plant shutdowns. In this study, we employ an established and validated scheme of water consumption and withdrawal rates across energy conversion technologies at the European scale to project corresponding water usage rates towards 2050 for EU30 countries. We further use the entire range of global- and regional climate model ensembles for low-, medium- and high-emission scenarios to project trends and robustness estimates of freshwater resources and availability at the distributed level for corresponding countries and years towards 2100. The results show a high sensitivity of water usage rates to the implementation of energy technologies such as CSP and CCS, as well as the decommissioning rates of fossil technologies and some scenarios generally show unaltered or even vastly increasing water consumption and withdrawal rates. Further, the assumptions on using CCS technologies, an evolving field, show a high impact. The assessment of hydro-climatic projections showed some degree of overlaps between decreasing water availabilities and increasing power sector water usage, especially for one power production scenario with a high share of CCS implementation. Further, a vast climate model spread in water availability was seen for both yearly means and summer minima, emphasising the need to include extremes in water management, and the water availability was highly dependent on the emission scenario in some regions. • Future EU water withdrawal and consumption of five energy scenarios was assessed. • Renewable energy is not necessarily compatible with renewable water resources. • The future renewable energy mix can cause significant increases in water usage. • CCS technologies, CSP, bio-energy and geothermal have high water usage rates. • The future water availability is increasingly at risk in some regions and scenarios. [ABSTRACT FROM AUTHOR]

Natural hazards in the coastal zone are already a huge problem globally, and the projected frequency and magnitude of high-impact events is expected to increase alongside rising sea levels. At the same time, there is an ever-increasing tendency for the location of urban environments, infrastructure and general assets in the coastal zone. The outcome of these physical and anthropogenic influences are high social and economic costs. Even with a high level of mitigation, adaptation measures are urgently needed to reduce these costs. The physical nature of the optimal adaptation measures depends to a high degree on local conditions and individual subjective perceptions. Further, the optimal temporal timing of their implementation also needs assessment as based on a combination of the projected development of assets, climate change impact on hazardous events and even economy such as discount rates. The Danish COHERENT project (2017-2020) addresses risks in the coastal zone through a cross-disciplinary approach across natural, social and economic sciences as well as long-term adaptation and hazard preparedness. We here present an approach to assess the combined physical impact for selected municipalities within the COHERENT project as well as initial findings. The physical impacts include at its core the combined effect of storm surge induced flooding as well as the simultaneous contribution to flooding from the river catchment with an outlet through central parts of the municipalities. The approach therefore addresses storm surges that arise from extreme winds, their duration and direction as well as extreme precipitation. Additionally the effect of precipitation leading up to the event is also addressed, i.e. the system saturation, as well as potentially direct pluvial flooding. These physical impacts are modelled using existing software components that are dynamically coupled. One of the project outcomes is to create a platform where end-users can directly use these physical model output in conjunction with economic damage assessment to aid in adaptation planning. [ABSTRACT FROM AUTHOR]

Coastal flooding hazard events have increased in frequency and severity in recent decades in Denmark,, and rising sea levels and more extreme storms due to climate change are expected to increase these risks. In the context of the experiences from Danish coastal flooding events during the last decades, we are presenting a methodological framework for integrated assessment of storm surge risks based on a detailed spatial assessment of storm surges, hydrological modeling, damage costs, and societal coping capacities. The perspective is that hazard damages will develop dynamically over time, despite storm surges can be more frequent and severe, adaptation options and human response capacities including physical measures, adaptive learning, and disaster risk management could help to drive down costs. The methodological framework is interdisciplinary and integrates climate physics, hydrology, spatial modelling, economics, and social science perspectives. The framework is applied to the assessment of coastal flooding hazard costs in Denmark including damages in terms of traffic delays, impacts on property prices, psycho-social impacts, and business disruptions. The coping capacities of local societies, which have been- or could be exposed to coastal flooding events are assessed based on insurance based damage cost data and experiences from the operation of emergency management units. The data is based on case studies from flooding risks and experienced events in the Danish city of Aabenraa and Jyllinge.The approach is here to assess the development trends over time in damage costs of specific flooding events over time, and to add information about disaster risk management planning, hazard management, and implemented physical adaptation measures. [ABSTRACT FROM AUTHOR]

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]

Extreme storm surges can cause devastating damage to low-lying coastlines. In this context, analyses of historical storm surge events are fundamental in order to identify local-scale, empirical relationships between complex atmospheric weather patterns and the sea level. These relationships provide valuable knowledge for projections of the present and future damage potential of storms and storm surges. In order to obtain improved storm surge predictions, historical events are reconstructed using hydrodynamical storm surge models, for which it is essential to have an accurate driving meteorological forcing. For the recent past, high-quality operational weather forecasts and reanalysis products overlap in time. This allows for an intercomparison of their ability to reproduce the meteorological forcing mechanisms that may lead to storm surges.The focus of this study is to make recommendations on the use of atmospheric forcing datasets used as input for storm surge modelling of the North Sea – Baltic Sea area. To do so, 10m wind fields produced by the DMI-HIRLAM numerical weather prediction forecast system from the Danish Meteorological Institute are compared with the ERA-Interim based UERRA HARMONIE/V1 regional reanalysis leading up to specific historical storm surge events along Danish coastlines. Three events from the Danish North Sea coast and three events from the Danish Kattegat coasts between the years 2002 and 2013 are assessed. The DMI-HIRLAM model system has undergone stepwise development cycles during this time, while the quality of the UERRA dataset is expected to be more consistent over the study period. Following the analysis, we present recommendations and perspectives for the use of atmospheric forcing data as input for storm surge modelling in the region, based on validation against wind station data. [ABSTRACT FROM AUTHOR]

Health risks associated with exposure to airborne particulate matter (PM) have been shown epidemiologically as well as experimentally, pointing to both respiratory and cardiovascular effects. These health risks are of increasing concern in society, and to protect public health, a clarification of the toxic properties of particles from different sources is of importance. Lately, wear particles generated from traffic have been recognized as a major contributing source to the overall particle load, especially in the Nordic countries where studded tires are used. The aim of this study was to further investigate and compare the ability to induce inflammatory mediators of different traffic-related wear particles collected from an urban street, a subway station, and studded tire−pavement wear. Inflammatory effects were measured as induction of nitric oxide (NO), IL-6, TNF-, arachidonic acid (AA), and lipid peroxidation after exposure of the murine macrophage like cell line RAW 264.7. In addition, the redox potential of the particles was measured in a cell-free system. The results show that all particles tested induce IL-6, TNF-, and NO, and those from the urban street were the most potent ones. In contrast, particles collected from a subway station were most potent to induce lipid peroxidation, AA release, and formation of ROS. Particles from studded tire−pavement wear, generated using a road simulator, were able to induce inflammatory cytokines, NO, lipid peroxidation, and ROS formation. Interestingly, particles generated from pavement containing granite as the main stone material were more potent than those generated from pavement containing quartzite as the main stone material. [ABSTRACT FROM AUTHOR]

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]

Storm surges are among the most destructive natural hazards worldwide. On a global perspective, average yearly global flood losses, considering the world's 136 largest coastal cities, have recently been estimated to approximately USD 6 billion per year [1]. This number is likely to increase dramatically without suitable adaptation measures when accounting for the inherent vulnerability of coastal areas, climate change, socio-economic aspects and local subsidence.Reliable assessments of storm surges impacts under current and future climatic conditions are critical for managing associated risks and for implementing adequate adaptation strategies. Consequently, understanding and considering the uncertainties related not only to the future climate but also to socio-economic change is essential to, e.g., avoid maladaptation. For this aim, fully probabilistic approaches, propagating uncertainty through each step in the modelling chain used to project these impacts, are increasingly applied [2][3]. While it is certainly feasible to implement such a framework using suitable assumptions, it is critically important to recognize the inherent structural uncertainties owing from differences in perception and the numerical representation of uncertainties in each analysis step, often representing different scientific and technical disciplines such as economics vs. hydro-climatic modelling [4]. For example, economic damage functions are typically developed from historical data and thus when used in a future setting an inherent assumption of stationarity is implicitly made. Additional challenges in this domain include discounting and society's and local stakeholders' attitudes to risk, both of which may modify the damage function in ways that conceptually deviate from the representation of uncertainties in climate and hydrological modelling. In this study, we carefully examine the role and potential implications of structural uncertainties along the full impact modelling chain for a location in Western Denmark, where the physical and economic models are in principle linked by stochastic extensions. Thus, we introduce a framework comprised by: (a) a semi-empirical downscaling of global to local sea level rise based on CMIP5 global climate model projections and local sea level observations [5]; (b) a probabilistic description of present and future storm surge heights based on extreme value theory; (c) a simplified flood inundation model; and (d) economic assessment of damages to select assets. Using results from our suite of models, we quantify and compare the relative importance of these sources in a temporal perspective, highlighting the importance of taking uncertainties into account when using storm surge impact assessments for adaptation planning.[1] Hallegatte, S., Green, C., Nicholls, R. J., and Corfee-Morlot, J. (2013). Nature Climate Change, 3(9), 802–806.[2] Thorarinsdottir, T. L., Guttorp, P., Drews, M., Kaspersen, P. S., and de Bruin, K (2017). Water Resour. Res. 53, 8147–8163.[3] Wahl, T., Haigh, I.D., Nicholls, R.J., Arns, A., Dangendorf, S., Hinkel, J., and Slangen, A.B.A. (2017). Nat. Comm. 8, 16075 (2017).[4] Halsnæs, K., Kaspersen, P. S., and Drews, M. (2015). Clim Res 64, 85–98.[5] Guttorp, P., Bolin, D., Januzzi, A., Jones, D., Novak, M., Podschwit, H., Richardson, L., Särkkä, A., Sowder, C., and Zimmerman, A. (2014). Journal of Applied Meteorology and Climatology, 53, 2163–2170. [ABSTRACT FROM AUTHOR]