HELIOS/SICRIT/mass spectrometry for analysis of aerosols in engine exhaust

Current legislations typically characterize systems of aerosols, such as from vehicle exhaust, primarily by number concentration and size distributions. While potential health threats have a dependence on the particle size, the chemical composition of particles, including the volatile and semi-volatile components adsorbed onto nonvolatile particle cores present at roadside and urban settings, is important in understanding the impact of exhaust particles on health. To date, the only tools suitable for an online in-depth chemical aerosol characterization are aerosol mass spectrometers, which are typically composed of complex and cost intensive instrumentation. We present a new analytical system, which combines a novel inexpensive infrared-radiation-based evaporation system (HELIOS) with a commercially available highly efficient atmospheric ionization source (SICRIT) connected to a rather low-price ion-trap mass spectrometer. Our inexpensive, robust and mobile aerosol characterization HELIOS/SICRIT/Mass Spectrometry system enables highly sensitive chemical analysis of particle-associated volatile substances. We validate the HELIOS/SICRIT/Mass Spectrometry system in laboratory experiments with coated particles generated under controlled conditions, and show that the system is capable of identification of combustion-generated polycyclic aromatic hydrocarbons and relative quantification of individual chemical species adsorbed on particle surfaces. We then employ our system to analyze real-world vehicle engine exhaust aerosol and show through time-resolved measurements with high time resolution (<10 s) that the chemical composition of the particles changes during different parts of an engine test cycle.acceptedVersionPeer reviewe

Avlägsnande av vätesulfid från en luftström med användning av UV-ljus

Volatile sulfur compounds are cause of concern because, when present in high concentrations, they constitute a danger for health because of their strong toxicity. Furthermore, for low concentrations, they are often a cause of complaint, because of their low odor threshold. In this context, the purpose of this Thesis is to evaluate a new technology for the abatement of sulfur-based malodorous compounds. The investigated technology consists in the use of ozone generating low-pressure UV mercury lamps, operating at room temperature. Hydrogen sulfide is often found in industrial processes, (e.g. WWTPs (Wastewater Treatment Plants), leather production, sewage treatment, garbage disposal, etc). Moreover, it presents both a very high toxicity a low odor threshold. Thus, due to its high representativeness of the case, hydrogen sulfide was chosen as reference compound for the purposes of this project. In order to evaluate a wide range of cases, several experiments using different residence times, humidity contents and inlet concentrations of the pollutant were conducted. The obtained results show that this technology generally presents discrete conversion efficiencies, although not suffcient to be used as freestanding process. For this reason, a pretreatment is revealed to be necessary. The best conversion efficiency was obtained for low flow rates and high moisture content. At the end of the project, as side-study, a possible pretreatment using an adsorbent bed constituted by granular ferric oxide was evaluated.

Global Air Pollution Data for Health Risk Assessments in Lombardy, Italy

Air pollution figures among the top 10 of the Disability Adjusted Life Years (DALY) risk factors. Poor air quality particularly impacts the urban population. In 2021, in Europe, 91% of it was exposed to pollutants' concentrations above the 2021 World Health Organization (WHO) air quality guidelines (WHO, 2021a). For this reason, performing a health risk assessment due to the exposure to air pollution is important to support policy makers and to guide the implementation of mitigation measures. Several data sources of surface air pollution concentration are available today, especially for high-income countries. However, each of them brings strengths and weaknesses in terms of spatiotemporal resolution and coverage. Moreover, data are lacking in many regions of the world. With this study, we present an evaluation of the performance of the European Centre for Medium-Range Weather Forecast (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) global reanalysis dataset (EAC4), with coarse resolution and worldwide availability, with those of the ECMWF-CAMS European Reanalysis, with higher resolution. This is done in sight of an application of these data to perform a health risk assessment due to a long-term exposure to NO2, PM2.5 and O3. Data aggregates are put in relation to the Fraction of Settled Area (FSA) of the World Settlement Footprint and diurnal variability of the species' concentrations. The geographical area of this study is the highly urbanized Lombardy region in northern Italy. However, the results are discussed with respect to global applicability

Das Bioklimatische Informationssystem BioClis

Umweltstressoren wie Luftschadstoffe, Hitze oder Kälte können die menschliche Gesundheit auf vielfältige Weise beeinträchtigen. Der Klimawandel und die Zunahme von Extrema stellen den menschlichen Organismus vor neue Herausforderungen. Um die Auswirkungen von Klimawandel und Umweltstressoren auf die Gesundheit bewerten und gezielt Anpassungsmaßnahmen planen zu können, ist eine Quantifizierungs- und Informationsstrategie erforderlich. Hierzu wurde BioClis entwickelt (www.alpendac.eu/bioclis). Mit BioClis wurde ein Werkzeug geschaffen, das der Bayerischen Regierung und Bevölkerung die flächenhafte Bewertung des aggregierten Gesundheitsrisikos durch Hitze- und Kältestress, sowie Luftschadstoffe ermöglicht. Als webbasiertes Informationssystem liefert BioClis tagesaktuelle, flächendeckende und farbcodierte Analysen und Vorhersagen, die als Service der Umweltforschungsstation Schneefernerhaus (UFS) angeboten werden. Kern ist ein Umweltdatenprozessor, der auf den informationstechnologischen Entwicklungen der AlpEnDAC Plattform aufbaut und verschiedenste Datenquellen aus epidemiologischen Erhebungen, in-situ Messungen, Satelliten und numerischen Modellen integriert. Hier werden zwei Gesundheitsindizes, der aggregierte Risikoindex ARI und der universelle thermische Klimaindex UTCI, übersichtlich dargestellt. Zwei Gesundheitsindizes, der ARI-Gesamtrisikoindex und der UTCI-Index für das universelle thermische Klima, werden hier klar angezeigt, zusammen mit Informationen zur Konzentration der Hauptschadstoffe (Ozon, NO2 und PM10) und die wichtigsten meteorologischen Variablen

Urban air pollution exposure: an assessment exploiting world settlement footprint and land use data

The majority of the population in Europe that is exposed to air pollution levels exceeding the WHO limit values lives in metropolitan areas. There are already several studies that assess the linkage between air pollution and adverse effects on health. With the technology at our disposition, today, we can identify air pollution hotspots. The assessment of the pollution situation alone represents, however, only one component of the whole picture. In order to be able to build a scale that identifies the most critical regions in higher need of intervention, also the probability of exposure and the number of people exposed to defined pollution concentrations must be considered. For this purpose, we can benefit from satellite-derived data products of settlement extent, population density and land use. To improve the health risk assessment, novel data sets have been synergistically exploited for the first time. In this work a method is proposed to perform an assessment of the increased health risk within urban areas in Europe due to the exposure to PM2.5 and to calculate the health burden index HBI: a useful parameter for the assessment of health risk that provides a measure of the impact of air pollution and enables to perform comparisons between different cities. This is a first approach showing the potential of this easily scalable tool that can be of support in the decision-making process and in the research on air pollution/health relationship. Further work is required for the verification and tuning of the initial hypotheses by means of validation with real-life data

Mapping Function from Dynamics: Future Challenges for Network-Based Models of Protein Structures

International audienceProteins fulfill complex and diverse biological functions through the controlled atomic motions of their structures (functional dynamics). The protein composition is given by its amino-acid sequence, which was assumed to encode the function. However, the discovery of functional sequence variants proved that the functional encoding does not come down to the sequence, otherwise a change in the sequence would mean a change of function. Likewise, the discovery that function is fulfilled by a set of structures and not by a unique structure showed that the functional encoding does not come down to the structure either. That leaves us with the possibility that a set of atomic motions, achievable by different sequences and different structures, encodes a specific function. Thanks to the exponential growth in annual depositions in the Protein Data Bank of protein tridimensional structures at atomic resolutions, network models using the Cartesian coordinates of atoms of a protein structure as input have been used over 20 years to investigate protein features. Combining networks with experimental measures or with Molecular Dynamics (MD) simulations and using typical or ad-hoc network measures is well suited to decipher the link between protein dynamics and function. One perspective is to consider static structures alone as alternatives to address the question and find network measures relevant to dynamics that can be subsequently used for mining and classification of dynamic sequence changes functionally robust, adaptable or faulty. This way the set of dynamics that fulfill a function over a diversity of sequences and structures will be determined

Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility

Abstract Background The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities. Methods In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level. Results The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO2 and O3. For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric. Conclusions This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health

In proteins, the structural responses of a position to mutation rely on the Goldilocks principle: not too many links, not too few

International audienceA disease has distinct genetic and molecular hallmarks such as sequence variants that are likely to produce the alternative protein structures accountable for individual responses to drugs and disease development. Thus, to set up customized therapies, the structural influences of amino acids on one another need to be tracked down. Using network-based models and classical analysis of amino acid and atomic packing in protein structures, the influence of first shell neighbors on the structural fate of a position upon mutation, is revisited. Regardless of the type and position in a structure, amino acids satisfy on average over their neighbors, a low and similar number of atomic interactions, the average called the neighborhood watch (Nw). The structural tolerance of a position to mutation depends on the modulation of the composition and/or proximity of neighbors to maintain the same Nw, before and after mutation, at every position. Changes, upon mutation of the number of atomic interactions at the level of individual pairs (wij) are structurally tolerated but influence structural dynamics. Robust, fragile and rescue interactions can be identified with Nw and wij, offering a framework to classify sequence variants according to position-dependent structural changes

Regional mobility patterns and exposure to environmental stressors: effects on the health risk assessments due to air pollution

Urban environments are often characterized by high levels of air pollution, representing a significant risk to human health. This study presents a methodology for conducting a retrospective and indirect health risk assessment in urban areas, due to the long-term exposure to particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3). Specifically, the risk of all-causes mortality is investigated. For this purpose, relative risk values from the World Health Organization were used. The methodology combines various data sources that are available over a large geographical scale. They include: satellite-based settlement data, model-based air pollution data, land use information, demographic data, and regional-scale mobility patterns. By incorporating these factors, the study examines the impact of population mobility on the population exposure and daily variations in pollutant levels on health risks. As a results two health metrics are derived: The Health Risk Increase (HRI) and the Health Burden (HB). The results from the study show that neglecting the mobility patterns and the diurnal cycles of pollutants can lead to an underestimation of the health risk. This methodology tries to fill the data gap encountered when information on personal exposure are needed at population level. The incorporation of satellite and model data makes it scalable and easy tunable to perform a health risk assessment also in remote regions, where local sensors are limited, for example by using globally available pollution datasets. This methodology can be extended to cover the additional environmental stressors, like heat/cold stress, and health endpoints. and Additional studies are required to assess the uncertainty in the exposure when using these medium to- low resolution data