Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming.

BACKGROUND: Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe. METHODS: We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability. RESULTS: In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49% (95%CI: 3.82-7.19) and 0.81% (95%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 °C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45% (95%CI: -0.02-1.06) at 3 °C, 1.53% (95%CI: 0.96-2.06) at 4 °C, and 2.88% (95%CI: 1.60-4.10) at 5 °C, compared to today's warming level of 1 °C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 °C versus 1 °C of GMT rise. CONCLUSIONS: Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany's most populated cities.

Future sea level rise constrained by observations and long-term commitment.

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections.

The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework.

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.

Constraints and potentials of future irrigation water availability on agricultural production under climate change.

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

Multimodel assessment of water scarcity under climate change.

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m(3) per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

Multisectoral climate impact hotspots in a warming world.

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

Greenhouse-gas emission targets for limiting global warming to 2 degrees C.

More than 100 countries have adopted a global warming limit of 2 degrees C or below (relative to pre-industrial levels) as a guiding principle for mitigation efforts to reduce climate change risks, impacts and damages. However, the greenhouse gas (GHG) emissions corresponding to a specified maximum warming are poorly known owing to uncertainties in the carbon cycle and the climate response. Here we provide a comprehensive probabilistic analysis aimed at quantifying GHG emission budgets for the 2000-50 period that would limit warming throughout the twenty-first century to below 2 degrees C, based on a combination of published distributions of climate system properties and observational constraints. We show that, for the chosen class of emission scenarios, both cumulative emissions up to 2050 and emission levels in 2050 are robust indicators of the probability that twenty-first century warming will not exceed 2 degrees C relative to pre-industrial temperatures. Limiting cumulative CO(2) emissions over 2000-50 to 1,000 Gt CO(2) yields a 25% probability of warming exceeding 2 degrees C-and a limit of 1,440 Gt CO(2) yields a 50% probability-given a representative estimate of the distribution of climate system properties. As known 2000-06 CO(2) emissions were approximately 234 Gt CO(2), less than half the proven economically recoverable oil, gas and coal reserves can still be emitted up to 2050 to achieve such a goal. Recent G8 Communiqués envisage halved global GHG emissions by 2050, for which we estimate a 12-45% probability of exceeding 2 degrees C-assuming 1990 as emission base year and a range of published climate sensitivity distributions. Emissions levels in 2020 are a less robust indicator, but for the scenarios considered, the probability of exceeding 2 degrees C rises to 53-87% if global GHG emissions are still more than 25% above 2000 levels in 2020.

Contribution of climate change to the spatial expansion of West Nile virus in Europe.

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land-use and human population changes. To this end, we trained ecological niche models to predict the risk of local WNV circulation leading to human cases to then unravel the isolated effect of climate change by comparing factual simulations to a counterfactual based on the same environmental changes but a counterfactual climate where long-term trends have been removed. Our findings demonstrate a notable increase in the area ecologically suitable for WNV circulation during the period 1901-2019, whereas this area remains largely unchanged in a no-climate-change counterfactual. We show that the drastic increase in the human population at risk of exposure is partly due to historical changes in population density, but that climate change has also been a critical driver behind the heightened risk of WNV circulation in Europe.

Human displacements, fatalities, and economic damages linked to remotely observed floods.

We present a new open source dataset FLODIS that links estimates of flood-induced human displacements, fatalities, and economic damages to flooded areas observed through remote sensing. The dataset connects displacement data from the Internal Displacement Monitoring Centre (IDMC), as well as data on fatalities and damages from the Emergency Events Database (EM-DAT), with the Global Flood Database (GFD), a satellite-based inventory of historic flood footprints. It thereby provides a spatially explicit estimate of the flood hazard underlying each individual disaster event. FLODIS contains two datasets with event-specific information for 335 human displacement events and 695 mortality/damage events that occurred around the world between 2000 and 2018. Additionally, we provide estimates of affected population, GDP, and critical infrastructure, as well as socio-economic indicators; and we provide geocoding for displacement events ascribed to other types of disasters, such as tropical cyclones, so that they may be linked to corresponding hazard estimates in future work. FLODIS facilitates integrated flood risk analysis, allowing, for example, for detailed assessments of local flood-damage and displacement vulnerability.

Better insurance could effectively mitigate the increase in economic growth losses from U.S. hurricanes under global warming.

Global warming is likely to increase the proportion of intense hurricanes in the North Atlantic. Here, we analyze how this may affect economic growth. To this end, we introduce an event-based macroeconomic growth model that temporally resolves how growth depends on the heterogeneity of hurricane shocks. For the United States, we find that economic growth losses scale superlinearly with shock heterogeneity. We explain this by a disproportional increase of indirect losses with the magnitude of direct damage, which can lead to an incomplete recovery of the economy between consecutive intense landfall events. On the basis of two different methods to estimate the future frequency increase of intense hurricanes, we project annual growth losses to increase between 10 and 146% in a 2°C world compared to the period 1980-2014. Our modeling suggests that higher insurance coverage can compensate for this climate change-induced increase in growth losses.

Climate change and international migration: Exploring the macroeconomic channel.

International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries. On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades. Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape. Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration. As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal. Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income. Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change. We illustrate these different possibilities, and the corresponding effects of 3°C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.

Climate signals in river flood damages emerge under sound regional disaggregation.

Climate change affects precipitation patterns. Here, we investigate whether its signals are already detectable in reported river flood damages. We develop an empirical model to reconstruct observed damages and quantify the contributions of climate and socio-economic drivers to observed trends. We show that, on the level of nine world regions, trends in damages are dominated by increasing exposure and modulated by changes in vulnerability, while climate-induced trends are comparably small and mostly statistically insignificant, with the exception of South & Sub-Saharan Africa and Eastern Asia. However, when disaggregating the world regions into subregions based on river-basins with homogenous historical discharge trends, climate contributions to damages become statistically significant globally, in Asia and Latin America. In most regions, we find monotonous climate-induced damage trends but more years of observations would be needed to distinguish between the impacts of anthropogenic climate forcing and multidecadal oscillations.

Intergenerational inequities in exposure to climate extremes.

Young generations are severely threatened by climate change.

Influence of statin treatment on coronary atherosclerosis visualised using multidetector computed tomography.

OBJECTIVE: Coronary angiography using multidetector computed tomography (MDCT) allows non-invasive assessment of non-calcified, calcified and mixed plaques. Progression of coronary plaques may be influenced by statins. METHODS: Sixty-three consecutive patients underwent MDCT as a follow-up to their original CT angiography in a retrospective longitudinal study. MDCT was performed by using a voxel size of 0.5 × 0.35 × 0.35 mm(3) at two time points 25 ± 3 months apart. Non-calcified, calcified and mixed coronary plaque components were analysed by using volumetric measurement. The influence of statin, low-density lipoprotein (LDL) and risk factors was assessed by using a linear random intercept model for plaque growth. RESULTS: The volumes of non-calcified, calcified and mixed coronary plaques significantly (P < 0.001) increased from baseline (medians/interquartile ranges = 21/15-39, 7/3-20 and 36/16-69 mm(3)) to follow-up (29/17-44, 13/6-29 and 41/20-75 mm(3)). Statins significantly slowed the growth of non-calcified plaques (statin coefficient ß = -0.0036, P = 0.01) but did not significantly affect the growth rate of mixed or calcified plaques. The effect of statin treatment on non-calcified plaques remained significant after adjusting for LDL levels and cardiac risk factors. CONCLUSION: Quantification using MDCT shows that progression of non-calcified coronary plaques may be slowed by statins.

Relevance of intracranial hypertension for cerebral metabolism in aneurysmal subarachnoid hemorrhage. Clinical article.

OBJECT: Intracranial hypertension, defined as intracranial pressure (ICP) >/= 20 mm Hg, is a complication typically associated with head injury. Its impact on cerebral metabolism, ICP therapy, and outcome has rarely been studied in patients with aneurysmal subarachnoid hemorrhage (aSAH); such an assessment is the authors' goal in the present study. METHODS: Cerebral metabolism was prospectively studied in 182 patients with aSAH. The database was retrospectively analyzed with respect to ICP. Patients were classified into 2 groups based on ICP. There were 164 with low ICP (<20 mm Hg) and 18 with high ICP (>or=20 mm Hg, measured>6 hours/day). Cerebral microdialysis parameters of energy metabolism, glycerol, and glutamate levels were analyzed hourly from the brain parenchyma of interest for 7 days. The 12-month outcome in these patients was evaluated. RESULTS: In the high ICP group, extended ICP therapy including decompressive craniectomy was necessary in 7 patients (39%). Cerebral glycerol levels and the lactate/pyruvate ratio were pathologically increased on Days 1-7 after aSAH (p<0.001). The excitotoxic neurotransmitter glutamate and glycerol, a marker of membrane degradation, further increased on Days 5-7, probably reflecting the development of secondary brain damage. An ICP>or=20 mm Hg was shown to have a significant influence on the 12-month Glasgow Outcome Scale (GOS) score (p=0.001) and was a strong predictor of mortality (OR=24.6; p<0.001). Glutamate (p=0.012), the lactate/pyruvate ratio as a marker of anaerobic metabolism (p=0.028), age (p<0.001), and Fisher grade (p=0.001) also influenced the GOS score at 12 months. CONCLUSIONS: The authors confirmed the relevance of intracranial hypertension as a severe complication in patients with aSAH. Because high ICP is associated with a severely deranged cerebral metabolism and poor outcome, future studies focusing on metabolism-guided, optimized ICP therapy could help minimize secondary brain damage and improve prognosis in patients with aSAH.

Cerebral microdialysis for detection of bacterial meningitis in aneurysmal subarachnoid hemorrhage patients: a cohort study.

INTRODUCTION: Bacterial meningitis (BM) is a severe complication in patients with aneurysmal subarachnoid haemorrhage (SAH). Clinical signs of meningitis are often masked by SAH-related symptoms, and routine cerebrospinal fluid (CSF) analysis fails to indicate BM. Microdialysis (MD) is a technique for monitoring cerebral metabolism in patients with SAH. A cohort study was performed to investigate the value of MD for the diagnosis of BM. METHODS: Retrospectively, 167 patients with SAH in an ongoing investigation on cerebral metabolism monitored by MD were analysed for the presence of BM and related MD changes. Diagnosis of BM was based on microbiological CSF culture or clinical symptoms responding to antibiotic treatment, combined with an increased CSF cell count and/or fever. Levels of MD parameters before and after diagnosis of BM were analysed and compared with the spontaneous course in controls. RESULTS: BM developed in 20 patients, of which 12 underwent MD monitoring at the time of diagnosis. A control group was formed using 147 patients with SAH not developing meningitis. On the day BM was diagnosed, cerebral glucose was lower compared with the value three days before (p = 0.012), and the extent of decrease was significantly higher than in controls (p = 0.044). A decrease in cerebral glucose by 1 mmol/L combined with the presence of fever >or= 38 degrees C indicated BM with a sensitivity of 69% and a specificity of 80%. CSF chemistry failed to indicate BM, but the cell count increased during the days before diagnosis (p < 0.05). CONCLUSIONS: A decrease in MD glucose combined with the presence of fever detected BM with acceptable sensitivity and specificity, while CSF chemistry failed to indicate BM. In patients with SAH where CSF cell count is not available or helpful, MD might serve as an adjunct criterion for early diagnosis of BM.

The German version of the Anorectic Behavior Observation Scale (ABOS).

OBJECTIVE: To assess the performance of the German version of the Anorectic Behavior Observation Scale (ABOS) as a parent-report screening instrument for eating disorders (ED) in their children. METHODS: Parents of 101 ED female patients (80 with Anorexia Nervosa; 21 with Bulimia Nervosa) and of 121 age- and socioeconomic status (SES)-matched female controls completed the ABOS. RESULTS: Confirmatory factor analysis supported the original three-factor structure model of the ABOS. Cronbach's alpha coefficients indicated good internal consistency for the three factors and the total score in the total sample. The best cut-off point (100% sensitivity and specificity) in the German version was >or=23. CONCLUSION: The ABOS may be a useful additional instrument for assessing ED.

Comparison of body size estimation in adolescents with different types of eating disorders.

OBJECTIVE: To examine differences in body size estimation in adolescents with different types of eating disorders. METHOD: A total of 129 patients with eating disorders (M(age) = 16.0 +/- 1.8) and 354 healthy control participants (CP) (M(age) = 15.2 +/- 2.1) completed the EDI-2 and were asked to estimate the circumference of selected body parts by using string (BID-CA). RESULTS: CP showed an average overestimation of 8-16%, depending on the estimated body part. Eating disorder patients overestimated their body parts on average by about 30%. Thigh and waist estimations were the best variables for discriminating between patients with eating disorders and CP. No significant differences were found between bulimia nervosa and anorexia nervosa patients. CONCLUSIONS: Body image distortion plays an important role in both anorexia nervosa and bulimia nervosa. The BID-CA is well suited to discriminate between healthy and disordered overestimation of body parts.

State-of-the-art global models underestimate impacts from climate extremes.

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.