153 research outputs found
Modeling organic aerosol over Europe in summer conditions with the VBS-GECKO parameterization: sensitivity to secondary organic compound properties and IVOC emissions [Dataset]
No full text<p>This dataset is composed of simulation outputs of the CHIMERE model that were used to evaluate the VBS-GECKO SOA parameterization as described in the study :</p>
<p>Lannuque, V., Couvidat, F., Camredon, M., Aumont, B., and Bessagnet, B. : Modelling organic aerosol over Europe in summer conditions with the VBS-GECKO parameterization: sensitivity to secondary organic compound properties and IVOC emissions, Atmos. Chem. Phys., <em>to be submitted soon</em>.<br>
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<strong>Please cite the original ACP article when using these data in a publication.</strong></p>
<p><br>
The paper also contains more information about how these data were obtained.</p>
<p>The dataset is composed of 34 netcdf files. The 17 "daily" files gather the daily averages and the 17 "profile" files present the average day profiles.</p>
<p>Victor Lannuque</p>
Modeling organic aerosols during MILAGRO: importance of biogenic secondary organic aerosols
No full textThe meso-scale chemistry-transport model CHIMERE is used to assess our understanding of major sources and formation processes leading to a fairly large amount of organic aerosols - OA, including primary OA (POA) and secondary OA (SOA) - observed in Mexico City during the MILAGRO field project (March 2006). Chemical analyses of submicron aerosols from aerosol mass spectrometers (AMS) indicate that organic particles found in the Mexico City basin contain a large fraction of oxygenated organic species (OOA) which have strong correspondence with SOA, and that their production actively continues downwind of the city. The SOA formation is modeled here by the one-step oxidation of anthropogenic (i.e. aromatics, alkanes), biogenic (i.e. monoterpenes and isoprene), and biomass-burning SOA precursors and their partitioning into both organic and aqueous phases. Conservative assumptions are made for uncertain parameters to maximize the amount of SOA produced by the model. The near-surface model evaluation shows that predicted OA correlates reasonably well with measurements during the campaign, however it remains a factor of 2 lower than the measured total OA. Fairly good agreement is found between predicted and observed POA within the city suggesting that anthropogenic and biomass burning emissions are reasonably captured. Consistent with previous studies in Mexico City, large discrepancies are encountered for SOA, with a factor of 2-10 model underestimate. When only anthropogenic SOA precursors were considered, the model was able to reproduce within a factor of two the sharp increase in OOA concentrations during the late morning at both urban and near-urban locations but the discrepancy increases rapidly later in the day, consistent with previous results, and is especially obvious when the column-integrated SOA mass is considered instead of the surface concentration. The increase in the missing SOA mass in the afternoon coincides with the sharp drop in POA suggesting a tendency of the model to excessively evaporate the freshly formed SOA. Predicted SOA concentrations in our base case were extremely low when photochemistry was not active, especially overnight, as the SOA formed in the previous day was mostly quickly advected away from the basin. These nighttime discrepancies were not significantly reduced when greatly enhanced partitioning to the aerosol phase was assumed. Model sensitivity results suggest that observed nighttime OOA concentrations are strongly influenced by a regional background SOA (∼1.5 μg/m3) of biogenic origin which is transported from the coastal mountain ranges into the Mexico City basin. The presence of biogenic SOA in Mexico City was confirmed by SOA tracer-derived estimates that have reported 1.14 (±0.22) μg/m3 of biogenic SOA at TO, and 1.35 (=0.24) μg/m3 at Tl, which are of the same order as the model. Consistent with other recent studies, we find that biogenic SOA does not appear to be underestimated significantly by traditional models, in strong contrast to what is observed for anthropogenic pollution. The relative contribution of biogenic SOA to predicted monthly mean SOA levels (traditional approach) is estimated to be more than 30% within the city and up to 65% at the regional scale which may help explain the significant amount of modern carbon in the aerosols inside the city during low biomass burning periods. The anthropogenic emissions of isoprene and its nighttime oxidation by NO3 were also found to enhance the SOA mean concentrations within the city by an additional 15%. Our results confirm the large underestimation of the SOA production by traditional models in polluted regions (estimated as 10-20 tons within the Mexico City metropolitan area during the daily peak), and emphasize for the first time the role of biogenic precursors in this region, indicating that they cannot be neglected in urban modeling studies
Atmospheric composition forecasting in Europe
No full textInternational audienceThe atmospheric composition is a societal issue and, following new European directives, its forecast is now recommended to quantify the air quality. It concerns both gaseous and particles species, identified as potential problems for health. In Europe, numerical systems providing daily air quality forecasts are numerous and, mostly, operated by universities. Following recent European research projects (GEMS, PROMOTE), an organization of the air quality forecast is currently under development. But for the moment, many platforms exist, each of them with strengths and weaknesses. This overview paper presents all existing systems in Europe and try to identify the main remaining gaps in the air quality forecast knowledge. As modeling systems are now able to reasonably forecast gaseous species, and in a lesser extent aerosols, the future directions would concern the use of these systems with ensemble approaches and satellite data assimilation. If numerous improvements were recently done on emissions and chemistry knowledge, improvements are still needed especially concerning meteorology, which remains a weak point of forecast systems. Future directions will also concern the use of these forecast tools to better understand and quantify the air pollution impact on health
Quatre essais sur l'entrepreneuriat numérique : développement de nouvelles entreprises et d'écosystèmes
No full textDans le domaine d'étude de l'Entrepreneuriat Numérique (EN), les perspectives systémiques et microéconomiques sont deux dimensions analytiques complémentaires mais distinctes.Au niveau systémique, la numérisation a transformé les paysages entrepreneuriaux, donnant naissance à des Ecosystèmes Entrepreneuriaux (EE) distincts de leur version numérique, les Ecosystèmes Entrepreneuriaux Digitaux (DEE). Cependant, de telles perspectives, bien que cruciales pour comprendre le développement des EE encastrés dans des dynamiques plus large, éclipsent parfois l'approche de l'entrepreneuriat centrée sur l'individu. En effet, au niveau de l'analyse des caractéristiques micro-comportementales des individus, des facteurs comme la formation universitaire et les compétences jouent un rôle important dans le succès des firmes. Dès lors, cette thèse propose quatre essais qui discutent des dimensions à la fois systémiques et micro de l'EN pour en comprendre la mécanique sous-jacente.A travers une perspective systémique, le premier essai propose une analyse de la structuration de la littérature des DEE et met en lumière le lien entre les réseaux de co-auteur et le contenu sémantique qui la façonne. En utilisant des méthodologies issues de la scientométrie, ce chapitre complète les études qualitatives antérieures. Un des résultats importants de cette étude est que le domaine scientifique des DEE se caractérise par une riche gamme de thématiques et de disciplines, bien qu'avec une intégration limitée, car largement ancrée sur un ensemble restreint de contributions reliant ces différents domaines d'autorité. Le deuxième essai, considérant les EE comme des entités au sein de marchés régionaux et mondiaux plus larges, explore l'IoT Valley, un EE spécialisé la technologie IoT LPWAN, entre 2009 et 2019. Ce chapitre met en application la méthodologie dite de l'analyse des événements historiques (HEA), et montre que l'évolution et le développement des EE peut être le résultat d'un mélange de dynamisme entrepreneurial local, de contextes régionaux et phénomènes mondiaux tels qu'une bataille de standards ou la platformisation des marchés.Abordant les aspects micro de l'EN, le troisième essai se penche sur la relation entre la diversité organisationnelle et la performance des entreprises. En examinant l'impact de la diversité des compétences de trois échelons organisationnels (équipes de direction, équipes de management de niveau intermédiaire et des travailleurs opérationnel) sur la croissance utilisateur d'entreprises numériques, nous constatons une corrélation positive entre la diversité fonctionnelle et l'expansion de ces entreprises. Cependant, la force de cette relation varie selon la phase de financement de l'entreprise, ouvrant ainsi la voie à de potentielles nouvelles directions de recherche. Enfin, le quatrième et dernier essai se tourne vers l'application de la théorie du signal aux études entrepreneuriales, suggérant que le niveau et la diversité des compétences approuvés en ligne des équipes de start-ups numériques peut attirer les investisseurs à investir dans leur entreprise. De fait, en analysant les données de 439 start-ups, cette recherche montre que les investisseurs privilégient les équipes mettant en avant soit des compétences très approfondies, soit diversifiées, mais rarement les deux à la fois. L'une des originalités de ce chapitre concerne l'utilisation de LinkedIn pour recueillir les compétences des équipes de start-ups.In fine, cette thèse montre à quel point il est crucial d'aborder l'EN à la fois par sa nature systémique et par les micro-caractéristiques idiosyncrasiques des individus et des firmes. En essence, cette thèse met en lumière les interactions nuancées de divers facteurs dans la formation du récit entrepreneurial. Une telle vue permet d'ouvrir la voie à des discussions académiques enrichissantes et à des applications pratiques mieux informées dans le domaine des entreprises numériques.In the field of Digital Entrepreneurship (DE) studies, systemic and microeconomic perspectives are two complementary yet distinct analytical dimensions.At the systemic level, digitization has transformed entrepreneurial landscapes, giving rise to distinct Entrepreneurial Ecosystems (EE) in their digital form, known as Digital Entrepreneurial Ecosystems (DEE). However, such perspectives, while crucial for understanding the development of EEs embedded within broader dynamics, sometimes overshadow the individual-centered approach to entrepreneurship. Indeed, in the analysis of micro-behavioral characteristics of individuals, factors such as educational background and skills play a significant role in firm success. Therefore, this thesis presents four essays that discuss both systemic and micro dimensions of DE to understand the underlying mechanics.From a systemic perspective, the first essay provides an analysis of the structure of DEE literature and highlights the connection between co-author networks and the semantic content shaping it. Using scientometric methodologies, this chapter complements previous qualitative studies. One significant finding of this study is that the scientific domain of DEE is characterized by a rich array of themes and disciplines, albeit with limited integration, largely centered on a restricted set of contributions connecting these various domains of authority. The second essay, considering EEs as entities within broader regional and global markets, explores the IoT Valley, a specialized EE in IoT LPWAN technology, between 2009 and 2019. This chapter applies the Historical Event Analysis (HEA) methodology and demonstrates that the evolution and development of EEs can result from a mixture of local entrepreneurial dynamism, regional contexts, and global phenomena such as standard battles or market platformization.Addressing the micro aspects of DE, the third essay examines the relationship between organizational diversity and firm performance. By examining the impact of diversity in skills across three organizational levels (top management teams, mid-level management teams, and operational workers) on the user growth of digital firms, a positive correlation between functional diversity and the expansion of these companies is observed. However, the strength of this relationship varies according to the firm's funding stage, thus paving the way for potential new research directions. Finally, the fourth and final essay turns to the application of signal theory in entrepreneurial studies, suggesting that the level and diversity of online-endorsed skills of digital start-up teams can attract investors to invest in their companies. Analyzing data from 439 start-ups, this research demonstrates that investors prefer teams that emphasize either highly specialized skills or diversified skills but rarely both simultaneously. One of the unique aspects of this chapter is the use of LinkedIn to gather the skills of startup teams.In conclusion, this thesis highlights the importance of approaching DE through both its systemic nature and the idiosyncrasic micro-characteristics of individuals and firms. In essence, this thesis sheds light on the nuanced interactions of various factors in shaping the entrepreneurial narrative. Such a view opens the door to enriching academic discussions and better-informed practical applications in the field of digital Entrepreneurship
Four essays on digital entrepreneurship : new ventures and ecosystems development
No full textDans le domaine d'étude de l'Entrepreneuriat Numérique (EN), les perspectives systémiques et microéconomiques sont deux dimensions analytiques complémentaires mais distinctes.Au niveau systémique, la numérisation a transformé les paysages entrepreneuriaux, donnant naissance à des Ecosystèmes Entrepreneuriaux (EE) distincts de leur version numérique, les Ecosystèmes Entrepreneuriaux Digitaux (DEE). Cependant, de telles perspectives, bien que cruciales pour comprendre le développement des EE encastrés dans des dynamiques plus large, éclipsent parfois l'approche de l'entrepreneuriat centrée sur l'individu. En effet, au niveau de l'analyse des caractéristiques micro-comportementales des individus, des facteurs comme la formation universitaire et les compétences jouent un rôle important dans le succès des firmes. Dès lors, cette thèse propose quatre essais qui discutent des dimensions à la fois systémiques et micro de l'EN pour en comprendre la mécanique sous-jacente.A travers une perspective systémique, le premier essai propose une analyse de la structuration de la littérature des DEE et met en lumière le lien entre les réseaux de co-auteur et le contenu sémantique qui la façonne. En utilisant des méthodologies issues de la scientométrie, ce chapitre complète les études qualitatives antérieures. Un des résultats importants de cette étude est que le domaine scientifique des DEE se caractérise par une riche gamme de thématiques et de disciplines, bien qu'avec une intégration limitée, car largement ancrée sur un ensemble restreint de contributions reliant ces différents domaines d'autorité. Le deuxième essai, considérant les EE comme des entités au sein de marchés régionaux et mondiaux plus larges, explore l'IoT Valley, un EE spécialisé la technologie IoT LPWAN, entre 2009 et 2019. Ce chapitre met en application la méthodologie dite de l'analyse des événements historiques (HEA), et montre que l'évolution et le développement des EE peut être le résultat d'un mélange de dynamisme entrepreneurial local, de contextes régionaux et phénomènes mondiaux tels qu'une bataille de standards ou la platformisation des marchés.Abordant les aspects micro de l'EN, le troisième essai se penche sur la relation entre la diversité organisationnelle et la performance des entreprises. En examinant l'impact de la diversité des compétences de trois échelons organisationnels (équipes de direction, équipes de management de niveau intermédiaire et des travailleurs opérationnel) sur la croissance utilisateur d'entreprises numériques, nous constatons une corrélation positive entre la diversité fonctionnelle et l'expansion de ces entreprises. Cependant, la force de cette relation varie selon la phase de financement de l'entreprise, ouvrant ainsi la voie à de potentielles nouvelles directions de recherche. Enfin, le quatrième et dernier essai se tourne vers l'application de la théorie du signal aux études entrepreneuriales, suggérant que le niveau et la diversité des compétences approuvés en ligne des équipes de start-ups numériques peut attirer les investisseurs à investir dans leur entreprise. De fait, en analysant les données de 439 start-ups, cette recherche montre que les investisseurs privilégient les équipes mettant en avant soit des compétences très approfondies, soit diversifiées, mais rarement les deux à la fois. L'une des originalités de ce chapitre concerne l'utilisation de LinkedIn pour recueillir les compétences des équipes de start-ups.In fine, cette thèse montre à quel point il est crucial d'aborder l'EN à la fois par sa nature systémique et par les micro-caractéristiques idiosyncrasiques des individus et des firmes. En essence, cette thèse met en lumière les interactions nuancées de divers facteurs dans la formation du récit entrepreneurial. Une telle vue permet d'ouvrir la voie à des discussions académiques enrichissantes et à des applications pratiques mieux informées dans le domaine des entreprises numériques.In the field of Digital Entrepreneurship (DE) studies, systemic and microeconomic perspectives are two complementary yet distinct analytical dimensions.At the systemic level, digitization has transformed entrepreneurial landscapes, giving rise to distinct Entrepreneurial Ecosystems (EE) in their digital form, known as Digital Entrepreneurial Ecosystems (DEE). However, such perspectives, while crucial for understanding the development of EEs embedded within broader dynamics, sometimes overshadow the individual-centered approach to entrepreneurship. Indeed, in the analysis of micro-behavioral characteristics of individuals, factors such as educational background and skills play a significant role in firm success. Therefore, this thesis presents four essays that discuss both systemic and micro dimensions of DE to understand the underlying mechanics.From a systemic perspective, the first essay provides an analysis of the structure of DEE literature and highlights the connection between co-author networks and the semantic content shaping it. Using scientometric methodologies, this chapter complements previous qualitative studies. One significant finding of this study is that the scientific domain of DEE is characterized by a rich array of themes and disciplines, albeit with limited integration, largely centered on a restricted set of contributions connecting these various domains of authority. The second essay, considering EEs as entities within broader regional and global markets, explores the IoT Valley, a specialized EE in IoT LPWAN technology, between 2009 and 2019. This chapter applies the Historical Event Analysis (HEA) methodology and demonstrates that the evolution and development of EEs can result from a mixture of local entrepreneurial dynamism, regional contexts, and global phenomena such as standard battles or market platformization.Addressing the micro aspects of DE, the third essay examines the relationship between organizational diversity and firm performance. By examining the impact of diversity in skills across three organizational levels (top management teams, mid-level management teams, and operational workers) on the user growth of digital firms, a positive correlation between functional diversity and the expansion of these companies is observed. However, the strength of this relationship varies according to the firm's funding stage, thus paving the way for potential new research directions. Finally, the fourth and final essay turns to the application of signal theory in entrepreneurial studies, suggesting that the level and diversity of online-endorsed skills of digital start-up teams can attract investors to invest in their companies. Analyzing data from 439 start-ups, this research demonstrates that investors prefer teams that emphasize either highly specialized skills or diversified skills but rarely both simultaneously. One of the unique aspects of this chapter is the use of LinkedIn to gather the skills of startup teams.In conclusion, this thesis highlights the importance of approaching DE through both its systemic nature and the idiosyncrasic micro-characteristics of individuals and firms. In essence, this thesis sheds light on the nuanced interactions of various factors in shaping the entrepreneurial narrative. Such a view opens the door to enriching academic discussions and better-informed practical applications in the field of digital Entrepreneurship
POMI: A Model Intercomparison exercise over the Po valley
No full textA collaborative research project for air pollution reduction was set up in 2006 between the Joint Research Centre of the European Commission (JRC) and the Authorities of the Lombardy Region in Italy. Among other research activities the PO valley Model Intercomparison exercise (POMI) has been carried out in order to explore the changes in air-quality in response to changes in emissions. The starting point was the evaluation of the simulated particulate matter and ozone against observations for the year 2005 of the six participating Chemical Transport Models’ (CTM). As models were run with the same configuration in terms of spatial resolution, boundary condition, emissions and meteorology, the differences presented in the models’ results should only be related to their formulation.
As described in the paper much effort has been put to improve the accuracy of emissions and meteorology. Nevertheless none of the models using the proposed meteorology succeeded to fulfill the performance criteria set in the 2008 Air Quality Directive and in the literature for particulate matter, while also for ozone the results are not very satisfying. Possible explanations for this common behavior and a discussion of the differences among models’ results are presented.JRC.H.2 - Air and Climat
Long-term health impact assessment of total PM2.5 in Europe during the 1990–2015 period
No full textSeveral datasets of PM2.5 concentrations over Europe during the 1990–2015 period, were used to calculate health impacts from chronic exposure to total particle matter below 2.5 μm (i.e. PM2.5). The datasets used in the analysis include the European Topic Centre on Air Pollution and Climate Change Mitigation (ETC/ACM), the Copernicus Atmospheric Monitoring Service (CAMS), the Global Burden of Disease (GBD), the World Health Organization (WHO) as well as the EURODELTA-Trends (EDT) multi-model reanalysis developed specifically for Europe. The exposure to ambient PM2.5 concentrations was calculated as population weighted annual average PM2.5 concentrations by country. The calculated exposure to PM2.5 was later used as input in the health impact assessment (HIA) Alpha-RiskPoll (ARP) tool to retrieve the total number of premature deaths. Our results indicate a substantial reduction in the number of premature deaths from PM2.5 exposure in Europe over the 1990–2010 period, between nearly 30 and 50%. Putting all the data-sets together, even if they do not cover the whole period, a decrease of even around 60% is observed between 1990 and 2015. For the countries included in this study, the estimated number of premature deaths from PM2.5 in 1990 was found to be around 960 000 (median of all the available datasets), whereas in 2015 it was found to be around 445 000. However, the variability in the estimated premature deaths from the different PM2.5 datasets was found to be large during the early 90s (around a factor of 2). For the latest years of the investigated period (2005 onwards), where a relatively flat trend in the PM2.5 exposure was observed, the differences between the different datasets were smaller. Even though our results indicate a reduction in the number of premature deaths from chronic exposure to PM2.5, the numbers remain considerable in 2015, underlining the need to continue improving air quality in the future
Évolution de la qualité de l’air en europe sur dix ans : première évaluation multimodèle
No full textInternational audienceIn order to assess the efficiency of air quality mitigation measures, an investigation of the decadal evolution of air quality over Europe was performed in the framework of the European research project CityZen. Significant downward trends of anthropogenic emissions were reported over the past decade, and these efforts lead to a decrease of NO2 levels observed at background sites throughout Europe. On the contrary, the ozone trend is insignificant or increasing at most sites (as a result of less efficient NOx titration). To identify the factors influencing this trend, INERIS coordinated an ambitious decadal numerical experiment involving six modelling teams implementing a variety of state-of-the-art models. The models were found to capture well the decreasing trend of NO2 on average over Europe despite degraded performances in selected countries attributed to shortcomings in the emission inventories. A complementary experiment using constant emissions over the past decade demonstrated that the lack of significant ozone trend can be largely attributed to the large interannual variability that exceeds the trend that would be attributed to mitigation measures.Dans une logique d’appui aux décideurs dans l’évaluation de l’efficacité des politiques environnementales, l’INERIS s’intéresse aux tendances historiques de la qualité de l’air. Par la mise en oeuvre d’objectifs ambitieux de réduction des émissions de polluants anthropiques, celles-ci ont baissé significativement depuis vingt ans. Il est donc légitime de chercher à quantifier l’efficacité de telles réductions en termes de réduction des concentrations atmosphériques de polluants et de l’exposition des populations. À l’échelle de l’Europe, les émissions d’oxydes d’azote (NOx) issues d’activités humaines ont été presque divisées par deux depuis 1990 [B]. L’exposition aux effets néfastes du NO2 pour la santé a donc été réduite, mais paradoxalement, l’impact sur les polluants secondaires tels que l’ozone est moins clair. Le principal facteur limitant l’efficacité des mesures de gestion de la qualité de l’air est la variabilité météorologique. Les niveaux de pollution observés pendant une année donnée dépendent des substances émises (soit les polluants ciblés, soit leurs précurseurs), mais aussi de la météorologie correspondante qui peut faciliter - ou non - l’occurrence d’épisodes de pollution intenses. La variabilité météorologique interannuelle masque la réelle tendance à long terme, qui peut être attribuée aux mesures de gestion
A simple and fast method to downscale chemistry transport model output fields from the regional to the urban/district scale.
No full textFor policy applications, the need to improve the resolution of environmental variables is crucial. Air pollution assessment indeed requires the use of air pollutant concentration fields at a high resolution, to better evaluate the exposure of citizens. We propose a fast proxy-based downscaling strategy, to downscale air quality modelling results using the fraction of the pollutant concentration influenced by precursor emissions in a given cell. The approach combines in an additive way (i) a classically interpolated background pollutant fraction, with (ii) a proxy-based concentration derived from the emissions. The proxy-based pollutant fraction is spread over the high resolution mesh into the surrounding cells with a Gaussian approach to account for diffusion effects. The evaluation of our approach against observations shows its relevance to create reliable air pollution concentration fields at a higher resolution, starting from a coarse resolution modelling results
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