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Experimental Assessment of Emission Factors from Fires in the Built Environment Including Scaling Effects
No full textInternational audienceConcern for the health of the natural environment is growing as human population grows. Recently, renewed attention has been given to the environmental impact of fires and the fire implications of sustainability choices made in the built environment. To properly understand the environmental impact of fires, however, it is crucial that we can estimate fire emissions. This paper explores the concept of fire emissions and emission factors and investigates the potential to use small scale testing to develop emission factors for fire emissions. The findings show that there is a potential to use dynamic tests such as the cone calorimeter (CC, ISO 5660) and fire propagation apparatus (FPA, ISO 12136) to develop emission factors to estimate larger scale fire emissions, at least for CO and CO2 emissions. While there is a spread of data from between the CC or FPA and the medium scale tests, this is of the same order or less than the spread between the two small scale tests. The spread in emission factor values from the various tests is smaller for CO2 than for CO and greatest for small CO-emission factors (< 10 g/kg). More work is needed to similarly characterise a broad range of species
Évaluation des effets sur le neurodéveloppement de l’exposition prénatale et postnatale aux produits phytopharmaceutiques. Présentation du projet NEUROPHYTO
No full textInternational audiencePrenatal and neonatal periods are windows of vulnerability to environmental chemical contaminants. A growing number of epidemiological and toxicological studies suggest that exposure to pesticides during these periods may impact the health of children at birth as well as their development, with potential delayed adverse effects.The NEUROPHYTO project is a new research project that aims to evaluate the exposure to pesticides of French children from prenatal period to early childhood and to study the possible effects of these exposures on their motor and neuropsychological development. New exposure data will be generated: levels of 140 pesticides and metabolites will be measured in biological samples (urine and hair) of 200 children from the national cohort Elfe (French longitudinal study of children). The levels of active substance(s) in the brain will be estimated using a mathematical model and then related to early neurodevelopmental effects. Two approaches will be used to better identify and characterize these links. The first strategy will rely on epidemiological methods and the second will be based on the understanding of the neurotoxicity mechanisms of the substances. Finally, a child-specific risk analysis will provide support to public policies by targeted evidence during pre- and post-natal windows of vulnerability.Les périodes prénatale et néonatale constituent des fenêtres de sensibilité vis-à-vis des contaminants chimiques de l’environnement. Un nombre croissant d’études épidémiologiques et toxicologiques suggère que l’exposition aux pesticides pendant ces périodes pourrait impacter la santé des enfants à la naissance ainsi que leur développement, avec des retentissements possibles tout au long de la vie.Le projet NEUROPHYTO est un nouveau projet de recherche qui vise à évaluer les expositions aux produits phytosanitaires d’enfants français lors de la période prénatale à la petite enfance et à étudier les effets possibles de ces expositions sur leur développement moteur et neuropsychologique. De nouvelles données d’exposition seront produites : les concentrations de 140 pesticides et métabolites seront mesurés dans les échantillons biologiques (urine et cheveux) de 200 enfants de la cohorte nationale Elfe (Etude longitudinale française depuis l’enfance). Les concentrations de substance(s) active(s) dans le cerveau seront estimées par modélisation puis mis en relation avec des effets neurodéveloppementaux précoces. Deux approches seront mises en œuvre afin de mieux identifier et caractériser ces liens : l’une épidémiologique et l’autre basée sur la compréhension des mécanismes de neurotoxicité des substances. Enfin, une analyse spécifique des risques pour les enfants permettra d’appuyer les politiques publiques en apportant des éléments ciblés sur les fenêtres de sensibilité pré et postnatales
Étude de la composition chimique des PM1 et des sources de l’aérosol organique sur différents sites français à partir de jeux de données pluriannuels à haute résolution temporelle
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Aerosol complex refractive index retrieval in the Paris urban area and its forested surroundings during the ACROSS field campaign: variability and constraint for direct radiative effect estimation in regional models
No full textInternational audienceThe complex refractive index (CRI) is one of the key parameter driving aerosol spectral opticalproperties and direct radiative effects (DRE). Its value and spectral variation under differentconditions, such as anthropogenic− and biogenic−dominated environments andanthropogenic−biogenic mixing situations, remains not fully understood. As a consequence,oversimplified representations of aerosol optical properties are generally used in climate models.Therefore, measurements of aerosol CRI in different environments and their inclusion in modelsare needed. The field observations from the ACROSS campaign, performed in June-July 2022 in theIle de France region, are used in this study to deepen the knowledge of aerosol optical properties,aiming to improve the aerosol representation in the CHIMERE model and provide the bestconstraint for DRE simulations. Measurements obtained both at the Paris city center and theRambouilllet rural forest sites during ACROSS are considered, in order to explore the CRI variabilityfrom anthropogenic−dominated to biogenic−dominated environments, includinganthropogenic−biogenic mixing situations. The CRI retrievals at seven different wavelengths,performed by combining the Mie theory with optical and size distribution measurements, arerepresentative of different atmospheric conditions, aerosol loadings as well as type and chemicalcompositions. In fact, the June-July 2022 period was characterized by highly diversified weatherconditions: 1) two strong heatwaves, promoting SOA build-up and favoring the export of the Parispollution plume towards the forest site; 2) Saharan dust events transported from the upperatmosphere to the ground; 3) biomass burning episode; 4) periods with reduced anthropogenicinfluence. The CRI retrievals under these different conditions and their link to particulate chemicalcomposition is investigated. Hence, the CRI dataset presented here constitutes a unique datasetfrom which models can benefit to validate and constrain simulations and DRE estimations, underboth urban and biogenic emissions influence. These data, in conjunction with those from theaircraft observations during ACROSS, are used to initialize and perform sensitivity studies on theaerosol DRE, using the CHIMERE−WRF coupled model, the OPTSIM model for the aerosol opticalproperties and the Rapid Radiative Transfer Model for GCMs (RRTMG
Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques
No full textInternational audienceModel output statistics (MOS) approaches relying on machine learning algorithms were applied to downscale regional air quality forecasts produced by CAMS (Copernicus Atmosphere Monitoring Service) at hundreds of monitoring sites across Europe. Besides the CAMS forecast, the predictors in the MOS typically include meteorological variables but also ancillary data. We explored first a “local” approach where specific models are trained at each site. An alternative “global” approach where a single model is trained with data from the whole geographical domain was also investigated. In both cases, local predictors are used for a given station in predictive mode. Because of its global nature, the latter approach can capture a variety of meteorological situations within a very short training period and is thereby more suited to cope with operational constraints in relation to the training of the MOS (frequent upgrades of the modelling system, addition of new monitoring sites). Both approaches have been implemented using a variety of machine learning algorithms: random forest, gradient boosting, and standard and regularized multi-linear models. The quality of the MOS predictions is evaluated in this work for four key pollutants, namely particulate matter (PM10 and PM2.5), ozone (O3) and nitrogen dioxide (NO2), according to scores based on the predictive errors and on the detection of pollution peaks (exceedances of the regulatory thresholds). Both the local and the global approaches significantly improve the performances of the raw ensemble forecast. The most important result of this study is that the global approach competes with and can even outperform the local approach in some cases. This global approach gives the best RMSE scores when relying on a random forest model for the prediction of daily mean, daily max and hourly concentrations. By contrast, it is the gradient boosting model which is better suited for the detection of exceedances of the European Union regulated threshold values for O3 and PM10
Post-Mining Multi-Hazard Assessment for Sustainable Development
No full textInternational audienceToday, most mines (coal, iron, and others) in Europe are already closed due to economic, environmental, and societal issues. Therefore, post-mining risk assessment and management remain crucial for mining authorities, policymakers, and planners. In the post-mining period, several hazards are likely to affect the surface areas in the closed mining sites. The impact of closed mines can lead to potentially damaging changes in surface and/or underground water flow, as well as the development of surface instabilities that can affect people or infrastructure, sometimes dangerously. The assessment of the different hazards must consider the interaction between the mining hazards and other risks (natural and technological). Thus, land use planning, particularly the rehabilitation of former mining sites, requires better tools to apprehend the multiplicity of hazards and their constraints. The paper presents a methodology considering the interactions between hazards around closed mines. After recalling the advantages of this multi-hazard analysis, the work consisted of, almost exhaustively, describing the three prominent families of hazards: mining, natural, and technological. Then, the possible interactions between hazards were described according to their nature (trigger or aggravating), their category (technical or regulatory), and their typology (dependent or independent). Finally, an attempt was proposed to evaluate the type and intensity of interactions between hazards. The multi-hazard assessment methodology was applied to a coal mine and showed the complexity and the utility of such a risk assessment analysis to improve risk management in closed mines
Impact of climate change on the collapse of shallow mines – feedback from France
No full textInternational audienceFor many years, Ineris has been conducting research on the impact of climate changeon the stability of abandoned mines. In this context, work has been initiated to reference cases ofshallow mine collapses. So far, 480 cases have been identified and described. Preliminary analysisof the information gathered shows that 50% of the cases correspond relate to chalk mines, 32% tolimestone mines, and 16% to gypsum mines. Two case studies presented in the paper were alsoanalyzed in more detail. Complexity of the water-rock interaction and the importance of studyingmore precisely the various parameters impacted and their relationships are highlighted. Therefore, achalk mine located in Seine-et-Marne (France) was instrumented to monitor the evolution of thestructure over time and analyze the different causes of degradation. The objectives are to betterunderstand the behavior of these structures to be able to detect precursor signs to these collapses
Multi-hazard analysis of abandoned coal-mines
No full textInternational audienceNowadays, most coal mines in Europe are already closed or are in a state of liquidation. However, the problem concerning the abandoned coal mines and their influence on the environment is still a central objective of the mining industry and coal regions in transition. After the end of the exploitation, numerous disturbances can occur. Mines operators, local authorities and decision makers face multi-hazard and multi-risks related to mine closure. Land and especially planning for a proper old mining site rehabilitation require better tools to apprehend the multiplicity of hazards and constraints. The objective to improve risk assessment by creating a new methodology to treat a global and multi-hazard related to abandoned coalmines instead of each hazard separately and study the interaction between the hazards related to post-mining areas. The mining hazards concern: ground movement, hydrologic hazards, self-heating, soil and water pollution. One hazard can trigger another one. Different tools such as a global matrix, fault tree, etc. for identifying the hazard interaction. The hazard interaction matrix was built, figure 1 shows a tentative view of interactions that phenomena in the columns (source phenomenon) may have with phenomena in the rows (target phenomenon). Figure 1 also shows indicative interactions between source phenomena and target phenomena according to 4 levels of interactions: No known case of interaction between phenomena (white colour), Low (yellow), Medium (green) and High (red). The final adopted interactions are based on the feedback and the deep discussion between experts. This approach will help the mining actors to improve and design the mitigation measures facing the multi-hazard impact and consequences
European feedback on post-mining seismicity
No full textInternational audienceFollowing the Paris Agreement adopted in 2015, Europe has committed to reducing its greenhouse gas emissions. In this context, the abandonment of coal as an energy source, both in terms of consumption and production, will lead to the closure of many mines in the years to come. Mine closure guidelines to manage residual mining risks already exist in European countries. However, they do not include post-mining seismic risk management due to a lack of sufficient studies and knowledge on this subject. After mining closure, the flooding of the mining works leads to hydromechanical loading of the underground and, in the longer term, to diffusion and an increase in the pore pressure. These conditions can lead, in certain situations, to the reactivation of tectonic faults, which may cause seismic events strong enough to be felt on the surface or even produce damage. Events of lower magnitudes, usually attributed to the remobilization of old mining works, are referred to as postmining seismic hazards. The European RFCS PostMinQuake project, which started in 2020, aims to study this hazard at five mining basins located in France, Germany, Poland and the Czech Republic, known to have experienced significant seismicity during their operation. This analysis, based on the feedback of the partners of the project, aims to frame an inventory of the five studied mining basins, which all encounter post-mining seismicity problem today. Three basins out of five show events with local magnitudes of the order of 3 to 3.5, which took place between nine and thirteen years after the closure of the mines. Even though the magnitudes of these earthquakes are small to moderate, they are felt on the surface as they occur at shallow depths. In all of the considered countries, a national seismological network exists, however, none of them is fully dedicated to post-mining seismic monitoring. These networks generally consist of a sparse mesh of stations, which does not allow the detection of events of magnitude less than 1 and the location of events have high spatial uncertainties. France is not an exception, but it relies on microseismic monitoring to detect early signs of instability at the level of mining structures and to anticipate the possible appearance of surface disorders. Out of the five basins that are studied, the Gardanne basin, which has been monitored since 2008, is the most documented case study of post-mining seismicity. This article also shows the difficulty in identifying the key conditions and factors that can lead to the remobilization of faults
