No abstract

While many authors have described the adverse health effects of poor air quality and meteorological extremes, there remain inconsistencies on a regional scale as well as uncertainty about the single and joint effects of atmospheric predictors. In this context, we investigated the short-term impacts of weather and air quality on moderate extreme cancer-related mortality events for the urban area of Augsburg, Southern Germany, during the period 2000–2017. First, single effects were uncovered by applying a case-crossover routine. The overall impact was assessed by performing a Mann–Whitney U testing scheme. We then compared the results of this procedure to extreme noncancer-related mortality events. In a second step, we found periods with contemporaneous significant predictors and carried out an in-depth analysis of these joint-effect periods. We were interested in the atmospheric processes leading to the emergence of significant conditions. Hence, we applied the Principal Component Analysis to large-scale synoptic conditions during these periods. The results demonstrate a strong linkage between high-mortality events in cancer patients and significantly above-average levels of nitrogen dioxide (NO2) and particulate matter (PM2.5) during the late winter through spring period. These were mainly linked to northerly to easterly weak airflow under stable, high-pressure conditions. Especially in winter and spring, this can result in low temperatures and a ground-level increase and the accumulation of air pollution from heating and traffic as well as eastern lateral advection of polluted air. Additionally, above-average temperatures were shown to occur on the days before mortality events from mid-summer through fall, which was also caused by high-pressure conditions with weak wind flow and intense solar radiation. Our approach can be used to analyse medical data with epidemiological as well as climatological methods while providing a more vivid representation of the underlying atmospheric processes.

Planetary Health connects human health with the natural and anthropogenic systems on which it depends. Planetary Health education has been growing in a wide range of health-related disciplines, yet not been widely implemented in health-related university curricula. This cross-sectional study focused on students' knowledge of and interest in Planetary Health education in order to assess the relevance of Planetary Health and Planetary Health topics for university students and their fields of study. We surveyed 1,303 students enrolled in health-related programmes in Bavaria, Germany. Data was collected on students' previous knowledge of and interest in Planetary Health, as well as the relevance of different Planetary Health topics and students' willingness to select a Planetary Health elective within their study programmes. Descriptive statistics were calculated. The majority of participants (73.8%) had not yet heard of Planetary Health but were interested in learning more about this field (90.7%). Most participants considered Planetary Health as relevant to their field (81.6%) and would likely choose a Planetary Health elective (81.9%). Participants were most interested in topics about general associations between climate and health as well as its connections with mental health and (micro) plastics. There is an urgent need and high student interest to implement a Planetary Health module in health-related study programmes in order to move this topic more into focus for the next generation of students.

In the present study the role of soil moisture (SM) in a statistical downscaling framework for precipitation in the EuroMediterranean domain is assessed. Different settings of the statistical downscaling models, differing in terms of the predictor variables used, are compared to quantify the influence of SM on the downscaling results. Results indicate an improvement of the skill of the statistical models when using SM information. This improvement is only moderate when averaged over the whole Euro-Mediterranean domain, but for specific regions the gain in performance is substantial. Regional projections of precipitation under the RCP4.5 and RCP8.5 scenario are considerably modified when SM is used as additional predictor in comparison with results based on atmospheric predictors alone.

This study investigates the projected precipitation changes of the 21st century in the Mediterranean area with a model ensemble of all available CMIP3 and CMIP5 data based on four different scenarios. The large spread of simulated precipitation change signals underlines the need of an evaluation of the individual general circulation models in order to give higher weights to better and lower weights to worse performing models. The models' spread comprises part of the internal climate variability, but is also due to the differing skills of the circulation models. The uncertainty resulting from the latter is the aim of our weighting approach. Each weight is based on the skill to simulate key predictor variables in context of large and medium scale atmospheric circulation patterns within a statistical downscaling framework for the Mediterranean precipitation. Therefore, geopotential heights, sea level pressure, atmospheric layer thickness, horizontal wind components and humidity data at several atmospheric levels are considered. The novelty of this metric consists in avoiding the use of the precipitation data by itself for the weighting process, as state‐of‐the‐art models still have major deficits in simulating precipitation. The application of the weights on the downscaled precipitation changes leads to more reliable and precise change signals in some Mediterranean sub‐regions and seasons. The model weights differ between sub‐regions and seasons, however, a clear sequence from better to worse models for the representation of precipitation in the Mediterranean area becomes apparent.