Urban Air Pollutants are Significant Risk Factors for Asthma and Pneumonia in Children: The Influence of Location on the Measurement of Pollutants

Background: Air pollution is associated with a substantial burden on human health; however, the most important pollutants may vary with location. Proper monitoring is necessary to determine the effect of these pollutants on respiratory health. Objectives: This study was designed to evaluate the role of outdoor, indoor and personal exposure to combustion-related pollutants NO2 and O-3 on respiratory health of children in a non-affluent urban area of Sao Paulo, Brazil. Methods: Levels of NO2 and O-3 were continuously measured in outdoor and indoor air, as well as personal exposure, for 30 days using passive measurement monitors. Respiratory health was assessed with a Brazilian version of the ISAAC questionnaire. Results: Complete data were available from 64 children, aged 6-10 years. Respiratory morbidity was high, with 43 (67.2%) reporting having had wheezing at any time, 27 (42.2%) wheezing in the last month, 17 (26.6%) asthma at any time and 21(32.8%) pneumonia at any time. Correlations between levels of NO2 and O-3 measured in the three locations evaluated were poor. Levels of NO2 in indoor air and personal exposure to O-3 were independently associated with asthma (both cases P=.02), pneumonia (O-3, P=.02) and wheezing at any time (both cases P<.01). No associations were seen between outdoor NO2 and O-3 and respiratory health. Conclusions: Exposure to higher levels of NO2 and O-3 was associated with increased risk for asthma and pneumonia in children. Nonetheless, the place where the pollutants are measured influences the results. The measurements taken in indoor and personal exposure were the most accurate. (C) 2012 SEPAR. Published by Elsevier Espana, S.L. All rights reserved.

Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries

Background: Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Methods: Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed. Results: Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846), Barnetson (0.850), MMRpro (0.821) and Wijnen (0.807) models did not present significant statistical difference. The Myriad model presented lower AUC (0.704) than the four other models evaluated. Considering thresholds of >= 5%, the models sensitivity varied between 1 (Myriad) and 0.87 (Wijnen) and specificity ranged from 0 (Myriad) to 0.38 (Barnetson). Conclusions: The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.

Impact of urban atmospheric environment on hospital admissions in the elderly

OBJECTIVE: To analyze the impact of intra-urban atmospheric conditions on circulatory and respiratory diseases in elder adults. METHODS: Cross-sectional study based on data from 33,212 hospital admissions in adults over 60 years in the city of Sao Paulo, southeastern Brazil, from 2003 to 2007. The association between atmospheric variables from Congonhas airport and bioclimatic index, Physiological Equivalent Temperature, was analyzed according to the district's socioenvironmental profile. Descriptive statistical analysis and regression models were used. RESULTS: There was an increase in hospital admissions due to circulatory diseases as average and lowest temperatures decreased. The likelihood of being admitted to the hospital increased by 12% with 1 degrees C decrease in the bioclimatic index and with 1 degrees C increase in the highest temperatures in the group with lower socioenvironmental conditions. The risk of admission due to respiratory diseases increased with inadequate air quality in districts with higher socioenvironmental conditions. CONCLUSIONS: The associations between morbidity and climate variables and the comfort index varied in different groups and diseases. Lower and higher temperatures increased the risk of hospital admission in the elderly. Districts with lower socioenvironmental conditions showed greater adverse health impacts.

Tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos

OBJETIVO: Analisar a associação entre indicadores de exposição à poluição por tráfego veicular e mortalidade por doenças do aparelho circulatório em homens adultos. MÉTODOS: Foram analisadas informações sobre vias e volume de tráfego no ano de 2007 fornecidas pela companhia de engenharia de tráfego local. Mortalidade por doenças do aparelho circulatório no ano de 2005 entre homens ≥ 40 anos foram obtidas do registro de mortalidade do Programa de Aprimoramento de Informações de Mortalidade do Município de São Paulo, SP. Dados socioeconômicos do Censo 2000 e informações sobre a localização dos serviços de saúde também foram coletados. A exposição foi avaliada pela densidade de vias e volume de tráfego para cada distrito administrativo. Foi calculada regressão (α = 5%) entre esses indicadores de exposição e as taxas de mortalidade padronizadas, ajustando os modelos para variáveis socioeconômicas, número de serviços de saúde nos distritos e autocorrelação espacial. RESULTADOS: A correlação entre densidade de vias e volume de tráfego foi modesta (r² = 0,28). Os distritos do centro apresentaram os maiores valores de densidade de vias. O modelo de regressão espacial de densidade de vias indicou associação com mortalidade por doenças do aparelho circulatório (p = 0,017). Não se observou associação no modelo de volume de tráfego. Em ambos os modelos – vias e volume de tráfego (veículos leves/pesados) – a variável socioeconômica foi estatisticamente signifi cante. CONCLUSÕES: A associação entre mortalidade por doenças do aparelho circulatório e densidade de vias converge com a literatura e encoraja a realização de mais estudos epidemiológicos em nível individual e com métodos mais acurados de avaliação da exposição.

Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 mu g/m(3), respectively. In Sao Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-a-vis health care costs.

Impact of urban atmospheric environment on hospital admissions in the elderly

OBJECTIVE: To analyze the impact of intra-urban atmospheric conditions on circulatory and respiratory diseases in elder adults. METHODS: Cross-sectional study based on data from 33,212 hospital admissions in adults over 60 years in the city of São Paulo, southeastern Brazil, from 2003 to 2007. The association between atmospheric variables from Congonhas airport and bioclimatic index, Physiological Equivalent Temperature, was analyzed according to the district's socioenvironmental profile. Descriptive statistical analysis and regression models were used. RESULTS: There was an increase in hospital admissions due to circulatory diseases as average and lowest temperatures decreased. The likelihood of being admitted to the hospital increased by 12% with 1ºC decrease in the bioclimatic index and with 1ºC increase in the highest temperatures in the group with lower socioenvironmental conditions. The risk of admission due to respiratory diseases increased with inadequate air quality in districts with higher socioenvironmental conditions. CONCLUSIONS: The associations between morbidity and climate variables and the comfort index varied in different groups and diseases. Lower and higher temperatures increased the risk of hospital admission in the elderly. Districts with lower socioenvironmental conditions showed greater adverse health impacts.

A dynamical system approach to data assimilation in chaotic models

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.

Atmospheric radiative transfer in multiple scattering conditions. Application to NWP models.

High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.

Quantifying and modeling ecosystem services provided by urban greening in cities of the Southern Alps, N Italy

Population growth in urban areas is a world-wide phenomenon. According to a recent United Nations report, over half of the world now lives in cities. Numerous health and environmental issues arise from this unprecedented urbanization. Recent studies have demonstrated the effectiveness of urban green spaces and the role they play in improving both the aesthetics and the quality of life of its residents. In particular, urban green spaces provide ecosystem services such as: urban air quality improvement by removing pollutants that can cause serious health problems, carbon storage, carbon sequestration and climate regulation through shading and evapotranspiration. Furthermore, epidemiological studies with controlled age, sex, marital and socio-economic status, have provided evidence of a positive relationship between green space and the life expectancy of senior citizens. However, there is little information on the role of public green spaces in mid-sized cities in northern Italy. To address this need, a study was conducted to assess the ecosystem services of urban green spaces in the city of Bolzano, South Tyrol, Italy. In particular, we quantified the cooling effect of urban trees and the hourly amount of pollution removed by the urban forest. The information was gathered using field data collected through local hourly air pollution readings, tree inventory and simulation models. During the study we quantified pollution removal for ozone, nitrogen dioxide, carbon monoxide and particulate matter (<10 microns). We estimated the above ground carbon stored and annually sequestered by the urban forest. Results have been compared to transportation CO2 emissions to determine the CO2 offset potential of urban streetscapes. Furthermore, we assessed commonly used methods for estimating carbon stored and sequestered by urban trees in the city of Bolzano. We also quantified ecosystem disservices such as hourly urban forest volatile organic compound emissions.

Water-soluble organic compounds in air particulate matter analyzed by HPLC-DAD-MS and HPLC-MS/MS: abundance, sources and transformation of carboxylic acids, nitrophenols and nitrated proteins

Wasserlösliche organische Verbindungen (WSOCs) sind Hauptbestandteile atmosphärischer Aerosole, die bis zu ~ 50% und mehr der organischen Aerosolfraktion ausmachen. Sie können die optischen Eigenschaften sowie die Hygroskopizität von Aerosolpartikeln und damit deren Auswirkungen auf das Klima beeinflussen. Darüber hinaus können sie zur Toxizität und Allergenität atmosphärischer Aerosole beitragen.In dieser Studie wurde Hochleistungsflüssigchromatographie gekoppelt mit optischen Diodenarraydetektion und Massenspektrometrie (HPLC-DAD-MS und HPLC-MS/MS) angewandt, um WSOCs zu analysieren, die für verschiedene Aerosolquellen und -prozesse charakteristisch sind. Niedermolekulare Carbonsäuren und Nitrophenole wurden als Indikatoren für die Verbrennung fossiler Brennstoffe und die Entstehung sowie Alterung sekundärer organischer Aerosole (SOA) aus biogenen Vorläufern untersucht. Protein-Makromoleküle wurden mit Blick auf den Einfluss von Luftverschmutzung und Nitrierungsreaktionen auf die Allergenität primärer biologischer Aerosolpartikel – wie Pollen und Pilzsporen – untersucht.rnFilterproben von Grob- und Feinstaubwurden über ein Jahr hinweg gesammelt und auf folgende WSOCs untersucht: die Pinen-Oxidationsprodukte Pinsäure, Pinonsäure und 3-Methyl-1,2,3-Butantricarbonsäure (3-MBTCA) sowie eine Vielzahl anderer Dicarbonsäuren und Nitrophenole. Saisonale Schwankungen und andere charakteristische Merkmale werden mit Blick auf Aerosolquellen und -senken im Vergleich zu Daten anderen Studien und Regionen diskutiert. Die Verhätlnisse von Adipinsäure und Phthalsäure zu Azelainsäure deuten darauf hin, dass die untersuchten Aerosolproben hauptsächlich durch biogene Quellen beeinflusst werden. Eine ausgeprägte Arrhenius-artige Korrelation wurde zwischen der 3-MBTCA-¬Konzentration und der inversen Temperatur beobachtet (R2 = 0.79, Ea = 126±10 kJ mol-1, Temperaturbereich 275–300 K). Modellrechnungen zeigen, dass die Temperaturabhängigkeit auf eine Steigerung der photochemischen Produktionsraten von 3-MBTCA durch erhöhte OH-Radikal-Konzentrationen bei erhöhten Temperaturen zurückgeführt werden kann. Im Vergleich zur chemischen Reaktionskinetik scheint der Einfluss von Gas-Partikel-Partitionierungseffekten nur eine untergeordnete Rolle zu spielen. Die Ergebnisse zeigen, dass die OH-initiierte Oxidation von Pinosäure der geschwindigkeitsbestimmende Schritt der Bildung von 3-MBTCA ist. 3-MBTCA erscheint somit als Indikator für die chemische Alterung von biogener sekundärer organischer Aerosole (SOA) durch OH-Radikale geeignet. Eine Arrhenius-artige Temperaturabhängigkeit wurde auch für Pinäure beobachtet und kann durch die Temperaturabhängigkeit der biogenen Pinen-Emissionen als geschwindigkeitsbestimmender Schritt der Pinsäure-Bildung erklärt werden (R2 = 0.60, Ea = 84±9 kJ mol-1).rn rnFür die Untersuchung von Proteinnitrierungreaktionen wurde nitrierte Protein¬standards durch Flüssigphasenreaktion von Rinderserumalbumin (BSA) und Ovalbumin (OVA) mit Tetranitromethan (TNM) synthetisiert.Proteinnitrierung erfolgt vorrangig an den Resten der aromatischen Aminosäure Tyrosin auf, und mittels UV-Vis-Photometrie wurde der Proteinnnitrierungsgrad (ND) bestimmt. Dieser ist definiert als Verhältnis der mittleren Anzahl von Nitrotyrosinresten zur Tyrosinrest-Gesamtzahl in den Proteinmolekülen. BSA und OVA zeigten verschiedene Relationen zwischen ND und TNM/Tyrosin-Verhältnis im Reaktionsgemisch, was vermutlich auf Unterschiede in den Löslichkeiten und den molekularen Strukturen der beiden Proteine zurück zu führen ist.rnDie Nitrierung von BSA und OVA durch Exposition mit einem Gasgemisch aus Stickstoffdioxid (NO2) und Ozon (O3) wurde mit einer neu entwickelten HPLC-DAD-¬Analysemethode untersucht. Diese einfache und robuste Methode erlaubt die Bestimmung des ND ohne Hydrolyse oder Verdau der untersuchten Proteine und ernöglicht somit eine effiziente Untersuchung der Kinetik von Protein¬nitrierungs-Reaktionen. Für eine detaillierte Produktstudien wurden die nitrierten Proteine enzymatisch verdaut, und die erhaltenen Oligopeptide wurden mittels HPLC-MS/MS und Datenbankabgleich mit hoher Sequenzübereinstimmung analysiert. Die Nitrierungsgrade individueller Nitrotyrosin-Reste (NDY) korrelierten gut mit dem Gesamt-Proteinnitrierungsgrad (ND), und unterschiedliche Verhältnisse von NDY zu ND geben Aufschluss über die Regioselektivität der Reaktion. Die Nitrierungmuster von BSA und OVA nach Beahndlung mit TNM deuten darauf hin, dass die Nachbarschaft eines negativ geladenen Aminosäurerestes die Tyrosinnitrierung fördert. Die Behandlung von BSA durch NO2 und O3 führte zu anderend Nitrierungemustern als die Behandlung mit TNM, was darauf hindeutet, dass die Regioselektivität der Nitrierung vom Nitrierungsmittel abhängt. Es zeigt sich jedoch, dass Tyrosinreste in Loop-Strukturen bevorzugt und unabhängig vom Reagens nitriert werden.Die Methoden und Ergebnisse dieser Studie bilden eine Grundlage für weitere, detaillierte Untersuchungen der Reaktionskinetik sowie der Produkte und Mechanismen von Proteinnitrierungreaktionen. Sie sollen helfen, die Zusammenhänge zwischen verkehrsbedingten Luftschadstoffen wie Stickoxiden und Ozon und der Allergenität von Luftstaub aufzuklären.rn

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

Origin and variability of PM10 and atmospheric radiotracers at the WMO-GAW station of Mt. Cimone (1998-2011) and in the central Po Valley

Particulate matter is one of the main atmospheric pollutants, with a great chemical-environmental relevance. Improving knowledge of the sources of particulate matter and of their apportionment is needed to handle and fulfill the legislation regarding this pollutant, to support further development of air policy as well as air pollution management. Various instruments have been used to understand the sources of particulate matter and atmospheric radiotracers at the site of Mt. Cimone (44.18° N, 10.7° E, 2165 m asl), hosting a global WMO-GAW station. Thanks to its characteristics, this location is suitable investigate the regional and long-range transport of polluted air masses on the background Southern-Europe free-troposphere. In particular, PM10 data sampled at the station in the period 1998-2011 were analyzed in the framework of the main meteorological and territorial features. A receptor model based on back trajectories was applied to study the source regions of particulate matter. Simultaneous measurements of atmospheric radionuclides Pb-210 and Be-7 acquired together with PM10 have also been analysed to acquire a better understanding of vertical and horizontal transports able to affect atmospheric composition. Seasonal variations of atmospheric radiotracers have been studied both analysing the long-term time series acquired at the measurement site as well as by means of a state-of-the-art global 3-D chemistry and transport model. Advection patterns characterizing the circulation at the site have been identified by means of clusters of back-trajectories. Finally, the results of a source apportionment study of particulate matter carried on in a midsize town of the Po Valley (actually recognised as one of the most polluted European regions) are reported. An approach exploiting different techniques, and in particular different kinds of models, successfully achieved a characterization of the processes/sources of particulate matter at the two sites, and of atmospheric radiotracers at the site of Mt. Cimone.

Kinetic modeling and experiments on gas uptake and chemical transformation of organic aerosol in the atmosphere

Aerosolpartikel beeinflussen das Klima durch Streuung und Absorption von Strahlung sowie als Nukleations-Kerne für Wolkentröpfchen und Eiskristalle. Darüber hinaus haben Aerosole einen starken Einfluss auf die Luftverschmutzung und die öffentliche Gesundheit. Gas-Partikel-Wechselwirkunge sind wichtige Prozesse, weil sie die physikalischen und chemischen Eigenschaften von Aerosolen wie Toxizität, Reaktivität, Hygroskopizität und optische Eigenschaften beeinflussen. Durch einen Mangel an experimentellen Daten und universellen Modellformalismen sind jedoch die Mechanismen und die Kinetik der Gasaufnahme und der chemischen Transformation organischer Aerosolpartikel unzureichend erfasst. Sowohl die chemische Transformation als auch die negativen gesundheitlichen Auswirkungen von toxischen und allergenen Aerosolpartikeln, wie Ruß, polyzyklische aromatische Kohlenwasserstoffe (PAK) und Proteine, sind bislang nicht gut verstanden.rn Kinetische Fluss-Modelle für Aerosoloberflächen- und Partikelbulk-Chemie wurden auf Basis des Pöschl-Rudich-Ammann-Formalismus für Gas-Partikel-Wechselwirkungen entwickelt. Zunächst wurde das kinetische Doppelschicht-Oberflächenmodell K2-SURF entwickelt, welches den Abbau von PAK auf Aerosolpartikeln in Gegenwart von Ozon, Stickstoffdioxid, Wasserdampf, Hydroxyl- und Nitrat-Radikalen beschreibt. Kompetitive Adsorption und chemische Transformation der Oberfläche führen zu einer stark nicht-linearen Abhängigkeit der Ozon-Aufnahme bezüglich Gaszusammensetzung. Unter atmosphärischen Bedingungen reicht die chemische Lebensdauer von PAK von wenigen Minuten auf Ruß, über mehrere Stunden auf organischen und anorganischen Feststoffen bis hin zu Tagen auf flüssigen Partikeln. rn Anschließend wurde das kinetische Mehrschichtenmodell KM-SUB entwickelt um die chemische Transformation organischer Aerosolpartikel zu beschreiben. KM-SUB ist in der Lage, Transportprozesse und chemische Reaktionen an der Oberfläche und im Bulk von Aerosol-partikeln explizit aufzulösen. Es erforder im Gegensatz zu früheren Modellen keine vereinfachenden Annahmen über stationäre Zustände und radiale Durchmischung. In Kombination mit Literaturdaten und neuen experimentellen Ergebnissen wurde KM-SUB eingesetzt, um die Effekte von Grenzflächen- und Bulk-Transportprozessen auf die Ozonolyse und Nitrierung von Protein-Makromolekülen, Ölsäure, und verwandten organischen Ver¬bin-dungen aufzuklären. Die in dieser Studie entwickelten kinetischen Modelle sollen als Basis für die Entwicklung eines detaillierten Mechanismus für Aerosolchemie dienen sowie für das Herleiten von vereinfachten, jedoch realistischen Parametrisierungen für großskalige globale Atmosphären- und Klima-Modelle. rn Die in dieser Studie durchgeführten Experimente und Modellrechnungen liefern Beweise für die Bildung langlebiger reaktiver Sauerstoff-Intermediate (ROI) in der heterogenen Reaktion von Ozon mit Aerosolpartikeln. Die chemische Lebensdauer dieser Zwischenformen beträgt mehr als 100 s, deutlich länger als die Oberflächen-Verweilzeit von molekularem O3 (~10-9 s). Die ROIs erklären scheinbare Diskrepanzen zwischen früheren quantenmechanischen Berechnungen und kinetischen Experimenten. Sie spielen eine Schlüsselrolle in der chemischen Transformation sowie in den negativen Gesundheitseffekten von toxischen und allergenen Feinstaubkomponenten, wie Ruß, PAK und Proteine. ROIs sind vermutlich auch an der Zersetzung von Ozon auf mineralischem Staub und an der Bildung sowie am Wachstum von sekundären organischen Aerosolen beteiligt. Darüber hinaus bilden ROIs eine Verbindung zwischen atmosphärischen und biosphärischen Mehrphasenprozessen (chemische und biologische Alterung).rn Organische Verbindungen können als amorpher Feststoff oder in einem halbfesten Zustand vorliegen, der die Geschwindigkeit von heterogenen Reaktionenen und Mehrphasenprozessen in Aerosolen beeinflusst. Strömungsrohr-Experimente zeigen, dass die Ozonaufnahme und die oxidative Alterung von amorphen Proteinen durch Bulk-Diffusion kinetisch limitiert sind. Die reaktive Gasaufnahme zeigt eine deutliche Zunahme mit zunehmender Luftfeuchte, was durch eine Verringerung der Viskosität zu erklären ist, bedingt durch einen Phasenübergang der amorphen organischen Matrix von einem glasartigen zu einem halbfesten Zustand (feuchtigkeitsinduzierter Phasenübergang). Die chemische Lebensdauer reaktiver Verbindungen in organischen Partikeln kann von Sekunden bis zu Tagen ansteigen, da die Diffusionsrate in der halbfesten Phase bei niedriger Temperatur oder geringer Luftfeuchte um Größenordnungen absinken kann. Die Ergebnisse dieser Studie zeigen wie halbfeste Phasen die Auswirkung organischeer Aerosole auf Luftqualität, Gesundheit und Klima beeinflussen können. rn

A New Prediction Model for Slope Stability Analysis

The instability of river bank can result in considerable human and land losses. The Po river is the most important in Italy, characterized by main banks of significant and constantly increasing height. This study presents multilayer perceptron of artificial neural network (ANN) to construct prediction models for the stability analysis of river banks along the Po River, under various river and groundwater boundary conditions. For this aim, a number of networks of threshold logic unit are tested using different combinations of the input parameters. Factor of safety (FS), as an index of slope stability, is formulated in terms of several influencing geometrical and geotechnical parameters. In order to obtain a comprehensive geotechnical database, several cone penetration tests from the study site have been interpreted. The proposed models are developed upon stability analyses using finite element code over different representative sections of river embankments. For the validity verification, the ANN models are employed to predict the FS values of a part of the database beyond the calibration data domain. The results indicate that the proposed ANN models are effective tools for evaluating the slope stability. The ANN models notably outperform the derived multiple linear regression models.

Nanotoxicology: a perspective and discussion of whether or not in vitro testing is a valid alternative

Despite the many proposed advantages related to nanotechnology, there are increasing concerns as to the potential adverse human health and environmental effects that the production of, and subsequent exposure to nanoparticles (NPs) might pose. In regard to human health, these concerns are founded upon the plethora of knowledge gained from research relating to the effects observed following exposure to environmental air pollution. It is known that increased exposure to environmental air pollution can cause reduced respiratory health, as well as exacerbate pre-existing conditions such as cardiovascular disease and chronic obstructive pulmonary disease. Such disease states have also been associated with exposure to the NP component contained within environmental air pollution, raising concerns as to the effects of NP exposure. It is not only exposure to accidentally produced NPs however, which should be approached with caution. Over the past decades, NPs have been specifically engineered for a wide range of consumer, industrial and technological applications. Due to the inevitable exposure of NPs to humans, owing to their use in such applications, it is therefore imperative that an understanding of how NPs interact with the human body is gained. In vivo research poses a beneficial model for gaining immediate and direct knowledge of human exposure to such xenobiotics. This research outlook however, has numerous limitations. Increased research using in vitro models has therefore been performed, as these models provide an inexpensive and high-throughput alternative to in vivo research strategies. Despite such advantages, there are also various restrictions in regard to in vitro research. Therefore, the aim of this review, in addition to providing a short perspective upon the field of nanotoxicology, is to discuss (1) the advantages and disadvantages of in vitro research and (2) how in vitro research may provide essential information pertaining to the human health risks posed by NP exposure.