Higher incidences of asthma during thunderstorms can pose a serious health risk. In this study, we estimate the thunderstorm asthma risk using statistical methods, with special focus on Bavaria, Southern Germany. In this approach, a dataset of asthma-related emergency cases for the study region is combined with meteorological variables and aeroallergen data to identify statistical relationships between the occurrence of asthma (predictand) and different environmental parameters (set of predictors). On the one hand, the results provide evidence for a weak but significant relationship between atmospheric stability indices and asthma emergencies in the region, but also show that currently thunderstorm asthma is not a major concern in Bavaria due to overall low incidences. As thunderstorm asthma can have severe consequences for allergic patients, the presented approach can be important for the development of emergency strategies in regions affected by thunderstorm asthma and under present and future climate change conditions.
<p class="western"><span lang="en-GB">A network of low-cost air quality sensors for monitoring NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB">- and O</span><sub><span lang="en-GB">3</span></sub><span lang="en-GB">-concentrations has been installed at an urban high traffic site in the city of Munich (Bavaria, South Germany). NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB">-measurements conducted over a period of several seasons are used to analyse the effectiveness of novel air filtering systems that have been installed alongside the street section.</span></p> <p class="western"><span lang="en-GB">Estimates of hourly mean NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB">-concentrations at the network sites are determined by applying several calibration methods (linear and non-linear models) that were fitted, validated and compared based on data gathered during two periods where all sensors were co-located at an on site official reference station.</span></p> <p class="western"><span lang="en-GB">Resulting NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB">-estimates at the low-cost network sites are further analysed with respect to spatiotemporal variations in NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB">-concentrations. Thereby the effects of local scale variations in the urban environment, varying traffic loads, changing synoptic weather types and different operating conditions of the air filtering systems are considered.</span></p> <p class="western"><span lang="en-GB">The contribution presents </span><span lang="en-GB">and discusses different approaches for the calibration of the low-cost NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB"> measurements and shows preliminary results of the analyses of spatiotemporal NO</span><sub><span lang="en-GB">2</span></sub><span lang="en-GB"> variations in a high traffic urban environment under special consideration of the effectiveness of novel air filtering systems.</span></p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.