Due to demographic change, there is an increasing demand for professional care services, whereby this demand cannot be met by available caregivers. To enable adequate care by relieving informal and formal care, the independence of people with chronic diseases has to be preserved for as long as possible. Assistance approaches can be used that support promoting physical activity, which is a main predictor of independence. One challenge is to design and test such approaches without affecting the people in focus. In this paper, we propose a design for a randomized trial to enable the use of an age simulation suit to generate reference data of people with health impairments with young and healthy participants. Therefore, we focus on situations of increased physical activity.

Laboratory landslide experiments enable the observation of specific properties of these natural hazards. However, these observations are limited by traditional techniques: frequently used high-speed video analysis and wired sensors (e.g. displacement). These techniques lead to the drawback that either only the surface and 2D profiles can be observed or wires confine the motion behaviour. In contrast, an unconfined observation of the total spatiotemporal dynamics of landslides is needed for an adequate understanding of these natural hazards. The present study introduces an autonomous and wireless probe to characterize motion features of single clasts within laboratory-scale landslides. The Smartstone probe is based on an inertial measurement unit (IMU) and records acceleration and rotation at a sampling rate of 100 Hz. The recording ranges are ±16 g (accelerometer) and ±2000∘ s−1 (gyroscope). The plastic tube housing is 55 mm long with a diameter of 10 mm. The probe is controlled, and data are read out via active radio frequency identification (active RFID) technology. Due to this technique, the probe works under low-power conditions, enabling the use of small button cell batteries and minimizing its size. Using the Smartstone probe, the motion of single clasts (gravel size, median particle diameter d50 of 42 mm) within approx. 520 kg of a uniformly graded pebble material was observed in a laboratory experiment. Single pebbles were equipped with probes and placed embedded and superficially in or on the material. In a first analysis step, the data of one pebble are interpreted qualitatively, allowing for the determination of different transport modes, such as translation, rotation and saltation. In a second step, the motion is quantified by means of derived movement characteristics: the analysed pebble moves mainly in the vertical direction during the first motion phase with a maximal vertical velocity of approx. 1.7 m s−1. A strong acceleration peak of approx. 36 m s−2 is interpreted as a pronounced hit and leads to a complex rotational-motion pattern. In a third step, displacement is derived and amounts to approx. 1.0 m in the vertical direction. The deviation compared to laser distance measurements was approx. −10 %. Furthermore, a full 3D spatiotemporal trajectory of the pebble is reconstructed and visualized supporting the interpretations. Finally, it is demonstrated that multiple pebbles can be analysed simultaneously within one experiment. Compared to other observation methods Smartstone probes allow for the quantification of internal movement characteristics and, consequently, a motion sampling in landslide experiments.

The study analyzes the long-term trends (1998–2019) of concentrations of the air pollutants ozone (O3) and nitrogen oxides (NOx) as well as meteorological conditions at forest sites in German midrange mountains to evaluate changes in O3 uptake conditions for trees over time at a plot scale. O3 concentrations did not show significant trends over the course of 22 years, unlike NO2 and NO, whose concentrations decreased significantly since the end of the 1990s. Temporal analyses of meteorological parameters found increasing global radiation at all sites and decreasing precipitation, vapor pressure deficit (VPD), and wind speed at most sites (temperature did not show any trend). A principal component analysis revealed strong correlations between O3 concentrations and global radiation, VPD, and temperature. Examination of the atmospheric water balance, a key parameter for O3 uptake, identified some unusually hot and dry years (2003, 2011, 2018, and 2019). With the help of a soil water model, periods of plant water stress were detected. These periods were often in synchrony with periods of elevated daytime O3 concentrations and usually occurred in mid and late summer, but occasionally also in spring and early summer. This suggests that drought protects forests against O3 uptake and that, in humid years with moderate O3 concentrations, the O3 flux was higher than in dry years with higher O3 concentrations.

Soil degradation due to erosion is a significant worldwide problem at different spatial (from pedon to watershed) and temporal scales. All stages and factors in the erosion process must be detected and evaluated to reduce this environmental issue and protect existing fertile soils and natural ecosystems. Laboratory studies using rainfall simulators allow single factors and interactive effects to be investigated under controlled conditions during extreme rainfall events. In this study, three main factors (rainfall intensity, inclination, and rainfall duration) were assessed to obtain empirical data for modeling water erosion during single rainfall events. Each factor was divided into three levels (− 1, 0, + 1), which were applied in different combinations using a rainfall simulator on beds (6 × 1 m) filled with soil from a study plot located in the arid Sistan region, Iran. The rainfall duration levels tested were 3, 5, and 7 min, the rainfall intensity levels were 30, 60, and 90 mm/h, and the inclination levels were 5, 15, and 25%. The results showed that the highest rainfall intensity tested (90 mm/h) for the longest duration (7 min) caused the highest runoff (62 mm3/s) and soil loss (1580 g/m2/h). Based on the empirical results, a quadratic function was the best mathematical model (R2 = 0.90) for predicting runoff (Q) and soil loss. Single-factor analysis revealed that rainfall intensity was more influential for runoff production than changes in time and inclination, while rainfall duration was the most influential single factor for soil loss. Modeling and three-dimensional depictions of the data revealed that sediment production was high and runoff production lower at the beginning of the experiment, but this trend was reversed over time as the soil became saturated. These results indicate that avoiding the initial stage of erosion is critical, so all soil protection measures should be taken to reduce the impact at this stage. The final stages of erosion appeared too complicated to be modeled, because different factors showed differing effects on erosion.

Climate change is expected to cause mountain species to shift their ranges to higher elevations. Due to the decreasing amounts of habitats with increasing elevation, such shifts are likely to increase their extinction risk. Heterogeneous mountain topography, however, may reduce this risk by providing microclimatic conditions that can buffer macroclimatic warming or provide nearby refugia. As aspect strongly influences the local microclimate, we here assess whether shifts from warm south-exposed aspects to cool north-exposed aspects in response to climate change can compensate for an upward shift into cooler elevations.