Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSEu, with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSEu accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSEu are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSEu tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSEu was in the range 25% - 34%.JRC.C.5-Air and Climat

Atmospheric impacts of harbor and industrial activities on fine particles (PM2.5) in Marseille

Les particules fines (PM2.5) suscitent de plus en plus l’intérêt des pouvoirs publics en raison de leurs effets néfastes sur la qualité de l’air et la santé humaine. La mise en place des politiques de réductions efficaces des émissions requière une connaissance détaillée des contributions des principales sources aux concentrations ambiantes en PM. Ainsi, cette thèse a pour objectifs de caractériser la composition chimique des PM2.5, et de quantifier leurs sources d’émissions à Marseille. Pour se faire, une campagne de mesure d’un an (2011-2012) a été conduite sur le site de fond urbain de « Cinq avenues ». La spéciation chimique complète des filtres collectés a été réalisée, et 3 modèles-récepteurs ont été utilisés: CMB (Chemical Mass Balance), PMF (Positive Matrix Factorization), et ME-2 (Multilinear Engine). Bien que basés sur des concepts sensiblement différents, l’exercice d’intercomparaison des sorties de ces modèles a montré globalement un bon accord pour l’estimation des contributions de la combustion de biomasse (entre 23 et 33% en moyenne annuelle) et du trafic véhiculaire (14-26%). En revanche, des différences significatives sont observées pour la source industrielle (1-18%) et le sulfate d’ammonium (12-30%). Cette étude a mis en évidence une contribution importante de la matière organique (OM) qui représente en moyenne 42% des PM2.5. Quant à la quantification des sources, l’un des résultats marquants est la mise en évidence de deux types d’aérosols de combustion de biomasse, dont l’un provient très probablement du brûlage à l’air libre de déchets verts. Ce dernier peut même être considéré comme un contributeur majeur des PM2.5 à l’automne et en début d’hiver.Fine particulate matter (PM2.5) has received considerable attention due to its impact on human health and air quality. Therefore, effective plans for human health protection require a detailed knowledge of the most relevant PM emission sources and their contributions to the ambient PM levels. Thus, this thesis aims to characterize the chemical composition of PM2.5 collected in Marseille area, and quantify the impacts of the main emission sources. To meet these objectives, a one-year monitoring campaign was conducted at the urban background site of “Cinq avenues” during the period of 2011-2012. A detailed chemical characterization of the collected PM2.5 filters was performed, and 3 receptor models were applied to this database: CMB (Chemical Mass Balance), PMF (Positive Matrix Factorization), and ME-2 (Multilinear Engine). Although based on significantly different concepts, the intercomparison exercise of the output data of the used models has generally showed a good agreement in estimating the source contributions of biomass burning (representing between 23 and 33% on annual average) and vehicular traffic (between 14 and 26%). In contrast, significant differences were observed for the industrial (1-18%) and ammonium sulfate (12-30%) sources. This study highlighted the significant contribution of organic matter (OM), which represents 42% of the PM2.5 mass, on average. Regarding the source apportionment results, one of the most striking findings is the identification of two types of biomass burning aerosol, one of which probably comes from open burning of green waste. The latter can even be considered a major contributor to the PM2.5 mass during fall and early winte

Evaluation of discharge instructions among hospitalized Lebanese patients

Background: Hospital readmissions are considered as the primary indicator of insufficient quality of care and are responsible of increasing annual medical costs by billions of dollars. Different factors tend to reduce readmissions, particularly instructions at discharge. Objectives: Our study objective was to evaluate discharge instructions given to hospitalized Lebanese patients and associated factors. Methods: Two hundred patients, aged between 21 and 79 years and admitted to the emergency department, were recruited from a Lebanese university hospital. Discharge instructions were evaluated by a face-to-face interview to fill a questionnaire with the patients immediately after their final contact with the physician or nurse in charge. We mainly focused on medications instructions and created two scores related to “instructions given” and “instructions appropriate” to later conduct bivariate analysis. Results: We found that discharge instructions were not completely given to all our study population. The degree of appropriateness fluctuated between 25% and 100%. The instructor in charge of giving discharge instructions had its significant influence on medication instructions given (p=0.014). In addition, the instructor and his experience influenced the degree of “appropriate instructions”. In fact, our study showed that despite being capable of giving good medication advice, nurses’ instructions were significantly less effective in comparison with physicians, fellows and residents. However, nurses gave 52% of the instructions, which questions the quality of those instructions. Conclusions: In conclusion, our observational study showed that in a Lebanese university hospital, patients’ understanding of discharge instructions is poor. Careful attention should be drawn to other hospitals as well and interventions should be considered to improve instructions quality and limit later complications and readmissions. The intervention of clinical pharmacists and their medication-related advice might be crucial in order to improve instructions’ quality

Etat des lieux sur les connaissances apportées par les études expérimentales des sources de particules fines en France

Le projet SOURCES avait pour premier objectif de réaliser une synthèse des études scientifiques permettant l’identification et la quantification des sources de particules dans l’air ambiant (PM10 et PM2,5) en France. L’accent a été porté principalement sur l’impact des sources anthropiques en milieu urbain au cours des dix dernières années et/ou sur les résultats obtenus par la mise en oeuvre d’outils statistiques de traitement de données expérimentales. Ces méthodologies incluent, notamment, la détermination très étendue des constituants de la matière particulaire via la détermination d’une grande diversité de traceurs spécifiques, suivie de l’utilisation d’outils statistiques. La plupart des études récentes se basent sur les approches de type Positive Matrix Factorization (PMF), présentant l’avantage de ne pas dépendre des hypothèses de départ concernant le nombre et la nature des sources à quantifier. La comparaison de résultats issus de différentes études basées sur une même approche contient une part d’incertitude liée aux inhomogénéités de traitement de données. Ainsi, le deuxième objectif de SOURCES était de proposer une ré-analyse homogène de jeux de données nationaux acquis au cours de ces dernières années. De 8 à 11 profils chimiques ont été identifiés sur chaque site grâce à la présence des traceurs spécifiques les caractérisant, dont 9 sont communément retrouvés sur la majorité des sites. Ces derniers correspondent à la combustion de la biomasse, aux émissions primaires liées au trafic routier, à deux facteurs riches en aérosols inorganiques secondaires (nitrate et sulfate d’ammonium), à des particules biogéniques primaires et secondaires, aux sels marins frais ou processés, et aux poussières minérales. Deux facteurs supplémentaires, correspondant aux émissions industrielles (rejets primaires et/ou composés issus des résidus de la combustion de fioul lourd) ont été résolus sur un nombre réduit de sites. Ce travail d’harmonisation constitue la première étude de type modèle-récepteur harmonisée et multi-sites des sources de particules en suspension (PM). Cet apport méthodologique de SOURCES représente un pilier important dans le domaine d’études des sources de PM et pourra servir à la communauté scientifique, notamment dans le cadre des activités du Centre commun de recherche de la Commission européenne (Joint Research Center) et du comité européen de normalisation. De plus, cette méthode pourra être utilisée dans les futures études PMF à large échelle spatiale permettant ainsi, d’améliorer la comparabilité des résultats (profils chimiques, par exemple) entre les différents sites et différentes régions

Sources contribution to the oxidative potential of PM₁₀ at 15 French sites.

International audienc

Source apportionment of oxidative potential of atmospheric particulate matter : method & application at 15 sites in France

Atmospheric ambient PM has already been shown to be linked to diverse health outcome such as asthma, cardiovascular disease and increase cancer risk. However, epidemiological studies focus only on PM mass despite the fact that the PM present a wide span of size, shape, chemical composition and so reactivity. The oxidative potential (OP) of PM has been proposed as a new proxy for air quality in order to better estimate the the population exposition since it integrates the different PM characteristic and is a closely linked to the inflammatory response of the body to the oxidative stress induced by PM, and so to different health outcomes. However, long time series of OP measurement are still poorly documented in the literature and no standardized assays has emerged. Moreover, very scars source apportionment of OP has been conducted yet

Harmonized PM source apportionment on a large set of various French sites using constrained Positive Matrix Factorization

Particulate matter (PM) is one of the most studied atmospheric pollutants due to their adverse effects on human health and the increased risk of morbidity and mortality (Pope et al., 2009). In order to reduce the health risks and to build effective PM abatement strategies, a detailed knowledge about the predominant sources of PM and a reliable source identification and quantification of their contribution to the PM ambient levels are strongly needed. Multivariate receptor models such as Positive Matrix Factorization (PMF) are very useful and have long been used worldwide for PM source apportionment (Viana et al., 2008; Belis et al., 2013). PMF notably uses a weighted least-squares fit and quantitatively determine source fingerprints and their contributions to the total PM mass, providing both factor profiles and the mass contributed by the factors. However, in many cases, it happens to be tricky to separate two factors that co-vary due to similar seasonal variation, obscuring the physical sense of the extracted factors. To address such issues of source collinearities, extra specific constraints are incorporated to the model (i.e., constrained PMF, that can be performed using for instance the ME-2 software developed by Paatero (1999)), allowing for a better source separation and cleaner profiles that are more consistently interpretable. The main objectives of the present work conducted within the framework of the SOURCES project was to perform a harmonized PM source apportionment on a large number of sites (up to 18) of different typologies (urban background, industrial, traffic, rural and/or Alpine sites) distributed all over France and previously investigated with annual or multiannual studies (2012-2015). For that purpose, and to improve the source apportionment results, a constrained version of PMF (US-EPA PMF v5.0) receptor model was applied to the PM chemical datasets in a harmonized way for all sites. PM samples collected at these sites were extensively characterized and generally analyzed for the contents of OC/EC, anions/cations, major and trace elements (such as Cu, Ni, Pb, Rb, Sb, V, Zn, Al, Ca, K, Mg, Na, Ti, etc.,), and several organic molecular markers (including oxalate, MSA, levoglucosan, polyols, etc.,)..

Source apportionment of atmospheric particulate matter (PM10) using a constrained USEPA-PMF5.0 model on different urban environments in France

Particulate matter (PM) is one of the most studied atmospheric pollutant in urban areas due to particles adverse effects on human health (Pope et al., 2009). Intrinsic properties of PM (e.g. chemical composition and morphology) are directly linked to their origins. A harmonized and comprehensive apportionment study of PM sources in urban environments is extremely required to connect source contributions with PM concentration levels and then develop effective PM abatement strategies. Multivariate receptor models such as Positive Matrix Factorization (PMF) are very useful and have been used worldwide for PM source apportionment (Viana et al., 2008). PMF uses a weighted least-squares fit and quantitatively determines source fingerprints (factors) and their contributions to the total PM mass. However, in many cases, it could be tricky to separate two factors that co-vary due to similar seasonal variations, making unclear the physical sense of the extracted factors. To address such issues of source collinearities, additional specific constraints are incorporated into the model (i.e. constrained PMF) based on user’s external knowledge allowing better apportionment results. In this work and within the framework of the SOURCES project, a harmonized source apportionment approach has been implemented and applied for the determination of PM10 sources on a large number of sites (up to 20) of different typologies (e.g. urban background, industrial, traffic, rural and/or alpine sites) distributed all over France and previously investigated with annual or multiannual studies (2012-2016). A constrained PMF approach (using US-EPA PMF5.0 software) was applied to the comprehensive PM-offline chemical datasets (i.e. carbonaceous fraction, major ions, metals/trace elements, specific organic markers) in a harmonized way for all the investigated sites. Different types of specific chemical constraints from well-characterized sources were defined based on external knowledge and were imposed to some species in the PMF factor profiles. As an example, the contributions of the levoglucosan and mannosan, specific tracers of the biomass burning emissions, were pulled up maximally in the biomass burning factor profile resolved at Port de Bouc site (Figure 1) and were set to zero in all other resolved PMF factors (e.g. vehicular emissions, biogenic emissions, etc,…). The different source categories contributing to ambient PM concentration levels were chemically characterized and quantified. Chemical profiles of the resolved common sources have been compared and give first time indication on the spatial variabilities of the source compositions, and their applicability as forcing factors in a fully constrained PMF. The presentation will address the main points achieved with this program

Source apportionment of atmospheric particulate matter (PM) using a constrained US-EPA-PMF5.0 model at different urban environments in France

Particulate matter (PM) is one of the most studied atmospheric pollutant in urban areas due to their adverse effects on human health (Pope et al., 2009). Intrinsic properties of PM (e.g. chemical composition and morphology) are directly linked to their origins. Therefore, a harmonized and comprehensive apportionment study of PM sources in urban environments is extremely required to connect source contributions with PM concentration levels and then develop effective PM abatement strategies. Multivariate receptor models such as Positive Matrix Factorization (PMF) are very useful and have been used worldwide for PM source apportionment (Viana et al., 2008). PMF uses a weighted least-squares fit and quantitatively determines source fingerprints (factors) and their contributions to the total PM mass. However, in many cases, it could be tricky to separate two factors that co-vary due to similar seasonal variations, making unclear the physical sense of the extracted factors. To address such issues of source collinearities, additional specific constraints are incorporated into the model (i.e. constrained PMF) based on user’s external knowledge allowing better apportionment results. In this work and within the framework of the SOURCES project, a harmonized source apportionment approach has been implemented and applied for the determination of PM sources on a large number of sites (up to 20) of different typologies (e.g. urban background, industrial, traffic, rural and/or alpine sites) distributed all over France and previously investigated with annual or multiannual studies (2012-2016). A constrained PMF approach (using US-EPA PMF5.0 software) was applied to the comprehensive PM-offline chemical datasets (i.e. carbonaceous fraction, major ions, metals/trace elements, specific organic markers) in a harmonized way for all the investigated sites. Different types of specific chemical constraints from well-characterized sources were defined based on external knowledge and were imposed to some species in the PMF factor profiles. As an example, the contributions of the levoglucosan, a specific tracer of the biomass burning emissions, were pulled up maximally in the biomass burning factor profiles and were set to zero in all other resolved factors (e.g. vehicular emissions, biogenic emissions, etc,. . . ). The different source categories contributing to ambient PM concentration levels were chemically characterized and quantified. Chemical profiles of the resolved common sources have been exploited and compared allowing us to get extra knowledge on the spatial variabilities of the source compositions. The presentation will address the main points achieved with this program

Factors related to autonomy among Lebanese women: a web-based cross-sectional study

International audienceBackground: Autonomy involves making independent decisions and creating lasting and equitable power relationships within families. Many factors, dependent on both the woman and her partner, can influence self-dependence, and subsequent decision-making, exerting a protective or triggering effect on its development. Therefore, the primary objective of the study was to assess autonomy in a sample of Lebanese women. The secondary objective was to evaluate the association between socioeconomic status, psychological factors, and autonomy. Methods: A web based cross-sectional online study was conducted between June 8 and August 1, 2020. The questionnaire developed on Google Forms was distributed through social media and WhatsApp groups, using the snowball technique. The Women's Autonomy Index (WAI) was created using three items adapted from a previous study. In addition, the Composite Abuse Scale Revised-Short Form (CASR-SF) was used to assess three domains of abuse: physical, sexual, and psychological. The Perceived stress scale short version to measure stress perception, the Lebanese Anxiety Scale to measure anxiety and the Patient Health Questionnaire (PHQ-9) to assess depression. The Statistical Package for the Social Sciences (SPSS) software version 25 was used for data analysis. Linear regressions were performed, taking the Women's Autonomy Index as the dependent variable. Results: The sample consisted of 369 Lebanese women. University education level (beta = 1.263), alcohol consumption (beta = 0.586), intermediate income level (beta = 0.702), high income (beta = 0.911), employment (beta = 0.559), and older age (beta = 0.033) were significantly associated with higher WAI. Living in South Lebanon (beta = − 0.668) and being Druze (beta = − 323) were associated with lower WAI. Significantly higher mean scores of anxiety and perceived stress were found among women with low autonomy. Conclusion: In Lebanon, the autonomy of women depends on several personal and partner-related characteristics (education, socioeconomic status, age), in addition to the cultural (geographic and religious) environment. Furthermore, low autonomy is associated with higher perceived stress and anxiety and probable depression and domestic abuse