Use of new measurement device to build a high-resolution network in Augsburg city – Smart Air Quality Network-Project

In traditional approach, the air quality in urban environment is monitored by relatively few measuring stations using stationary measuring technology. However, the spatial distribution of air pollutants in cities is very inhomogeneous and depends on various factors. The Smart Air Quality Network project (SAQN) is aimed to set up a dense network of sensor devices for particle mass and number concentration in the city of Augsburg (Germany) as well as conducting of intensive mobile measurements including walking and bike measurements. The main target is to generate real-time data that can be used for several actions and measures in order to reduce pollution levels as well as to inform people about the current levels of air pollutants. Furthermore, the data will be also used for the development and validation of dispersion and land use regression models. For the purpose of this project, a novel measuring device is being developed by GRIMM Aerosol company, so-called “scientific scouts” (autonomous, mobile smart dust measurement devices that are auto-calibrated to a high-quality reference instrument within an intelligent monitoring network). In Phase 1 we already installed 15 scientific scouts at different sampling sites within the Augsburg city. The sampling sites are located in different environments: close to traffic and traffic hotspots, near combustion sources, in the city center and in urban background. In Phase II of this project 35 updated scientific scouts will be installed until summer 2019. The scientific scouts will be able to measure particle mass and number concentrations. The preliminary results suggest good performance of the scientific scouts and their applicability for the purpose of SAQN project. Ongoing calibration will help to improve the performance and efficiency of the low-cost devices. On the other hand, the planned extension of the network in the following months will provide necessary data for the modelling approach

GIS-Based Estimation of Exposure to Particulate Matter and NO(2) in an Urban Area: Stochastic versus Dispersion Modeling

Stochastic modeling was used to predict nitrogen dioxide and fine particles [particles collected with an upper 50% cut point of 2.5 μm aerodynamic diameter (PM(2.5))] levels at 1,669 addresses of the participants of two ongoing birth cohort studies conducted in Munich, Germany. Alternatively, the Gaussian multisource dispersion model IMMIS(net/em) was used to estimate the annual mean values for NO(2) and total suspended particles (TSP) for the 40 measurement sites and for all study subjects. The aim of this study was to compare the measured NO(2) and PM(2.5) levels with the levels predicted by the two modeling approaches (for the 40 measurement sites) and to compare the results of the stochastic and dispersion modeling for all study infants (1,669 sites). NO(2) and PM(2.5) concentrations obtained by the stochastic models were in the same range as the measured concentrations, whereas the NO(2) and TSP levels estimated by dispersion modeling were higher than the measured values. However, the correlation between stochastic- and dispersion-modeled concentrations was strong for both pollutants: At the 40 measurement sites, for NO(2), r = 0.83, and for PM, r = 0.79; at the 1,669 cohort sites, for NO(2), r = 0.83 and for PM, r = 0.79. Both models yield similar results regarding exposure estimate of the study cohort to traffic-related air pollution, when classified into tertiles; that is, 70% of the study subjects were classified into the same category. In conclusion, despite different assumptions and procedures used for the stochastic and dispersion modeling, both models yield similar results regarding exposure estimation of the study cohort to traffic-related air pollutants

Association of lung function with declining ambient air pollution.

Recent studies have found a declining prevalence of respiratory infections in East German children, along with a tremendous improvement of air pollution since 1990. The present study evaluates the effects of improved air quality on lung function. Three consecutive cross-sectional surveys of schoolchildren ages 11-14 years from three communities in East Germany were performed in 1992-1993, 1995-1996, and 1998-1999. Lung function tests were available from 2,493 children. The annual mean of total suspended particulates (TSP) declined from 79 to 25 micro g/m(3), whereas levels for sulfur dioxide declined from 113 to 6 micro g/m(3). Mean forced vital capacity (FVC) and forced expiratory volume in 1 sec (FEV(1)) of the children increased from 1992-1993 to 1998-1999. The adjusted percent change of the geometric mean of FVC was 4.7% for a 50 micro g/m(3) decrease of TSP (p = 0.043) and 4.9% for a decrement of 100 micro g/m(3) SO(2) (p = 0.029). Effects on FEV(1) were smaller and not statistically significant. Our study indicates that a reduction of air pollution in a short time period may improve children's lung function

Ultrafine particles and platelet activation in patients with coronary heart disease – results from a prospective panel study

BACKGROUND: Epidemiological studies on health effects of air pollution have consistently shown adverse cardiovascular effects. Toxicological studies have provided evidence for thrombogenic effects of particles. A prospective panel study in a susceptible population was conducted in Erfurt, Germany, to study the effects of daily changes in ambient particles on various blood cells and soluble CD40ligand (sCD40L, also known as CD154), a marker for platelet activation that can cause increased coagulation and inflammation. Blood cells and plasma sCD40L levels were repeatedly measured in 57 male patients with coronary heart disease (CHD) during winter 2000/2001. Fixed effects linear regression models were applied, adjusting for trend, weekday and meteorological parameters. Hourly data on ultrafine particles (UFP, number concentration of particles from 0.01 to 0.1 μm), mass concentration of particles less than 10 and 2.5 μm in diameter (PM(10), PM(2.5)), accumulation mode particle counts (AP, 0.1–1.0 μm), elemental and organic carbon, gaseous pollutants and meteorological data were collected at central monitoring sites. RESULTS: An immediate increase in plasma sCD40L was found in association with UFP and AP (% change from geometric mean: 7.1; CI: [0.1, 14.5] and 6.9; CI: [0.5, 13.8], respectively). Platelet counts decreased in association with UFP showing an immediate, a three days delayed (lag 3) and a 5-day average response (% change from the mean: -1.8; CI: [-3.4,-0.2]; -2.4; CI: [-4.5,-0.3] and -2.2; CI: [-4.0,-0.3] respectively). CONCLUSION: The increased plasma sCD40L levels support the hypothesis that higher levels of ambient air pollution lead to an inflammatory response in patients with CHD thus providing a possible explanation for the observed association between air pollution and cardiovascular morbidity and mortality in susceptible parts of the population

Verbrennungsprodukte und Gesundheit: Ruß und Größenverteilung ultrafeiner und feiner Partikel in der Außenluft in Leipzig und Dresden und Gesundheit: Abschlussbericht

Die Publikation dokumentiert die Ergebnisse der epidemiologischen Studie zu gesundheitlichen Auswirkungen von ultrafeinen und feinen Partikeln und Ruß. Wie sich ultrafeine Partikel auf die Gesundheit auswirken, ist bisher noch nicht ausreichend untersucht. Mit der Auswertung der langen Messreihen von Dresden, Leipzig und Augsburg leistet die Studie deshalb einen Beitrag zum besseren Verständnis der Folgen von Luftschadstoffen auf die menschliche Gesundheit. Die Analysen zeigten erhöhte Risiken sowohl für respiratorische Mortalität als auch für die Hospitalisierung zu unterschiedlichen Zeitpunkten nach der Exposition mit ultrafeinen Partikeln. Dabei stieg das Risiko beispielsweise in der kalten Jahreshälfte stärker an. Die Veröffentlichung richtet sich an Vertreter von Fachbehörden und Forschungseinrichtungen, aber auch an die interessierte Öffentlichkeit. Redaktionsschluss: 05.01.202

A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota

Statistical analysis of microbial genomic data within epidemiological cohort studies holds the promise to assess the influence of environmental exposures on both the host and the host-associated microbiome. However, the observational character of prospective cohort data and the intricate characteristics of microbiome data make it challenging to discover causal associations between environment and microbiome. Here, we introduce a causal inference framework based on the Rubin Causal Model that can help scientists to investigate such environment-host microbiome relationships, to capitalize on existing, possibly powerful, test statistics, and test plausible sharp null hypotheses. Using data from the German KORA cohort study, we illustrate our framework by designing two hypothetical randomized experiments with interventions of (i) air pollution reduction and (ii) smoking prevention. We study the effects of these interventions on the human gut microbiome by testing shifts in microbial diversity, changes in individual microbial abundances, and microbial network wiring between groups of matched subjects via randomization-based inference. In the smoking prevention scenario, we identify a small interconnected group of taxa worth further scrutiny, including Christensenellaceae and Ruminococcaceae genera, that have been previously associated with blood metabolite changes. These findings demonstrate that our framework may uncover potentially causal links between environmental exposure and the gut microbiome from observational data. We anticipate the present statistical framework to be a good starting point for further discoveries on the role of the gut microbiome in environmental health