Ultrafine particles (UFP; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. At the same time, little is known about the immission situation at typical urban sites such as high-traffic roads, residential areas with a high amount of solid fuels for home heating or commercial and industrial areas due to missing legal requirements for measurements of UFP. Therefore, UFP were measured and evaluated in the (sub-)urban background as well as on spots influenced by these various anthropogenic local sources in the city of Augsburg, Germany, for the year 2017. In particular, the spatial and temporal correlations of the UFP concentrations between the seven measurement sites, the quantification and valuation of the contribution of local emitters with regard to their diurnal, weekly and seasonal variations and the influence of meteorological conditions on the formation and dispersion of UFP were investigated. Our analysis results demonstrate that urban UFP concentrations show a pronounced temporal and spatial variability. The mean concentration level of UFP varies between below 8,000 ultrafine particles/cm3 at the suburban background site and above 16,700 ultrafine particles/cm3 at the measurement station located next to a busy street canyon. At this particularly traffic-exposed measurement station, maximum concentrations of over 50,000 ultrafine particles/cm3 were measured. The additional UFP load caused by intensive traffic volume during evening rush hour in connection with the unfavourable exchange processes in the street canyon can be quantified to concentrations of 14,000 ultrafine particles/cm3 on average (compared to the immission situation of the urban background). An aggravating effect is brought about by inversion weather conditions in connection with air-polluted easterly winds, low wind speeds, lack of precipitation and very low mixing layer heights, such as over Augsburg at the end of January 2017, and cause peak concentrations of UFP.

Background/Objectives: Meteorological factors seem to influence stroke incidence, however, the complex association between weather and stroke remains unclear. Possible explanations from the literature do not categorize into subdivisions of ischemic strokes, only have small patient numbers, or refer to a selection of isolated weather elements without investigating weather changes and more. Method: In this exploratory trial, almost 18,000 stroke cases from a single stroke center in Southern Germany were analyzed from 2006 to 2015 and classified into the main subgroups of strokes and subdivisions of ischemic stroke etiologies applying the Trial of Org 10172 in Acute Stroke Treatment classification. For each stroke event, the air mass classification was determined from a subset of 7 air mass categories. Relative excess morbidities were derived for the 7 different air mass categories, taking into account the day of the event and up to 2 and 5 days preceding the stroke event. Results: Statistically significant findings (α ≤0.1) reveal that dry tropical air masses were associated with a lower/higher risk for hemorrhagic (HEM)/macroangiopathic strokes (MAS), respectively. Dry polar air masses were associated with a higher risk for intracerebral bleedings and lower risk for ischemic stroke subtypes. Moist air masses were associated with a reduced incidence of MAS. A strong temperature increase 5 days prior to the event was associated with a lower risk of HEM strokes. Temperature increases were associated with lower risks for MAS and cardio-embolic strokes. Significant temperature decreases were associated with a higher risk of MAS. Conclusions: Temperature effects were dependent on both air masses and temperature changes within 5 days prior to the event and were associated with statistically relevant changes in stroke incidence. Decisive factors such as etiology, age, sex, and risk factors were also taken into account.

Background: The main purpose of this paper is to contribute to the improvement in the present knowledge concerning regional carbon dioxide (CO 2) and methane (CH 4) exchange as an essential step towards reducing the uncertainties along with bottom-up estimations of their global budget by identifying the characteristic spatial and temporal scales of the regional greenhouse gas fluxes. To this end, we propose a stepwise statistical top-down methodology for examining the relationship between synoptic-scale atmospheric transport patterns and mole fractions of the climate gases to finally receive a characterisation of the sampling sites with regard to the key processes driving the CO 2 or CH 4 concentration levels. Results: The results of this study presented in this paper give detailed insights into the emission structures underlying the measurement time series by means of origin-related examinations of the Alpine CO 2 and CH 4 budgets. The time series of both climate gases from the atmospheric measurements carried out at the four high-alpine observatories Schneefernerhaus, Jungfraujoch, Sonnblick and Plateau Rosa form the basis for the characterisation of the regional CO 2 as well as CH 4 budget of the Alpine region as the focus area of the Central European study region. For the investigation area so outlined, the project identifies source and relative sink regions with influence on the Alpine climate gas measurements as well as their temporal variations. The therefore required combination of the measurements with the synoptic situation prevailing at the respective measuring time which carries the information about the origin of the analysed air masses is derived by means of a trajectory-based receptor model. The back trajectory receptor model is set up to decipher with high spatial resolution the most relevant source and sink areas, whereby the Alpine region is identified as a significant relative sink for CO 2 as well as for CH 4 concentrations all year long, whereas major European emitters show their impact during different seasons. Conclusions: The reliable results achieved with this approach in connection with the encouraging model-internal uncertainty assessments and external plausibility checks lend credence to our model and its strength to illustrate dependably spatial-temporal variations of the relevant emitters and absorbers of different climate gases (CO 2 and CH 4) in high spatial resolution.