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Saint-Clément-de-la-Place, France

Bobbia M.,Air Normand | Misiti M.,CNRS Mathematics Laboratory | Misiti Y.,CNRS Mathematics Laboratory | Poggi J.-M.,CNRS Mathematics Laboratory | And 2 more authors.
Atmospheric Pollution Research | Year: 2015

We consider hourly PM10 measurements from 22 monitoring stations located in Basse–Normandie and Haute–Normandie regions (France) and also in the neighboring regions. All considered monitoring stations are either urban background stations or rural ones. The paper focuses on the statistical detection of outliers of the hourly PM10 concentrations from a spatial point of view. The general strategy uses a jackknife type approach and is based on the comparison of the actual measurement with some robust spatial prediction. Two spatial predictions are considered: the first one is based on the median of the concentrations of the closest neighboring stations which directly consider weighted concentrations while the second one is based on kriging increments, instead of more traditional pseudo–innovations. The two methods are applied to the PM10 monitoring network in Normandy and are fully implemented by Air Normand (the official association for air quality monitoring in Haute–Normandie) in the Measurements Quality Control process. Some numerical results are provided on recent data from January 1, 2013 to May 31, 2013 to illustrate and compare the two methods. © Author(s) 2015. Source


Bobbia M.,Air Normand | Jollois F.-X.,University of Paris Descartes | Poggi J.-M.,University Paris - Sud | Poggi J.-M.,University of Paris Descartes | Portier B.,INSA Rouen
Environmetrics | Year: 2011

The problem is to quantify local and background contributions to PM10 concentrations in Haute-Normandie region. We use measures of pollution variables on a network of 11 monitoring sites, completed by meteorological variables, during 2004-2009. Random forests (RFs), a recent statistical method, are used to put in evidence the marginal effects of explanatory variables, and to classify parameters of influence on PM10 pollution in different situations: roadside, urban background, industrial, and rural. The local pollution is the most important source and is marked by the classic tracers NO and NO2 as urban activity pollution, and SO2 as industrial one. The entire process of statistical quantification of local and background contributions, without neither direct information nor measurements about sources, can be divided in three main steps. The first one is to classify the explanatory variables (pollutants and meteorological parameters) into five groups: pollutants from urban activity, pollutants from industrial activity, and three groups of meteorological variables. The second step is to handle the specificity of a rural and coastal station for which there is a priori no local pollution sources, to use it as a marker of the background pollution. The final step consists of quantifying the local and background contributions to the PM10 pollution, using only markers of urban and industrial activities and PM10 background. As a synthetic conclusion, it appears as often seen in publications about other geographical locations, that the local part contributes half of the total pollution. © 2011 John Wiley & Sons, Ltd. Source


Harrou F.,Texas A&M University at Qatar | Fillatre L.,University of Nice Sophia Antipolis | Bobbia M.,Air Normand | Nikiforov I.,CNRS Risk Management Science and Technology
Proceedings of the IEEE Conference on Decision and Control | Year: 2013

Monitoring ozone concentrations is an essential requirement due to the adverse environmental and health effects of abnormal ozone pollution. The objective of this paper is twofold: first, to model ground level ozone concentrations, and second, to detect abnormal ozone measurements. Towards this end, a multidimensional Seasonal AutoRegressive Moving Average with eXogenous variable (SARMAX) model has been developed to describe ground level ozone concentrations. The database used to fit the models consists of two data sets collected from Upper Normandy region, France, via the network of air quality monitoring stations. A good description of the ambient ozone pollution may be a tool for facilitating detection of abnormalities in ozone measurements. The overarching goal of this paper is to detect abnormal pollution measurements caused by air pollution anomalies or malfunctioning sensors in the framework of regional ozone surveillance network. The proposed Constrained Generalized Likelihood Ratio (CGLR) anomaly detection scheme is successfully applied to collected data. The detection results of the proposed method are compared to that declared by Air Normand air monitoring association. © 2013 IEEE. Source


Michelot N.,Ministry in Charge of the Ecology | Marchand C.,INERIS | Ramalho O.,CSTB | Delmas V.,Air Normand | Carrega M.,Ministry in Charge of the Ecology
HVAC and R Research | Year: 2013

Indoor air quality monitoring in public premises, especially those hosting vulnerable populations such as children, was introduced in the second French national environment and health action plan and then regulated by the first "Grenelle Environnement" law, on August 3, 2009. A national pilot monitoring survey of indoor air quality in 310 French schools and day-care centers was performed in two phases from 2009 to 2011. This article is dedicated to the results of the first phase (2009 to 2010, in 160 schools and day-care centers), and another article is in preparation about the whole survey results. Formaldehyde, benzene, and air stuffiness were the targeted compounds. They were measured for 1-2 weeks during heating and non-heating seasons in each investigated building. The results of the first phase are presented in this article. They show, referring to the management values suggested by the French committee for public health, that air quality is acceptable in most establishments tested. Nonetheless, a few cases required additional investigations or corrective measures. Furthermore, the air stuffiness (based on carbon dioxide measurements) was found to be very high in 16% of the classrooms (up to 25% in elementary schools). In 47% of the elementary schools, at least one classroom had very high air stuffiness. The mayors and school principals were informed and provided with means to identify the main sources of pollution and to implement remediation actions. The outcomes of this research have led to another step toward mandatory indoor air quality monitoring of public premises in France. France is the first country to implement a routine and mandatory assessment of air quality in public buildings accommodating vulnerable people. © 2013 Taylor and Francis Group, LLC. Source


Perdriel S.,CAIRN Developpement | Moussafir J.,ARIA Technologies | Derognat C.,ARIA Technologies | Cortinovis J.,Air Normand
HARMO 2010 - Proceedings of the 13th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes | Year: 2010

The industrial zone of Le Havre in the River Seine Estuary (France) is characterized by the presence of several major sources of SO2 emissions, with several refineries and a large power plant. The air quality in the area is under the supervision of the AIR NORMAND Air Quality Management Board, which operates an extended network of automatic stations. There were a large number of SO2 episodes during year 2007 when observed concentrations were above regulatory limits: this situation has driven the Regional Authority for Industry Research and Environment (DREAL) to undertake the detailed numerical simulation of all episodes, in order to determine with precision the emission reductions that had to be imposed to comply with EU regulations. The simulation of all the 77 episodes observed during year 2007 was performed, with a very high spatial resolution (down to 100m) and a time step of 15mn for averaged SO2 concentrations, using full 3D simulation tools. The SO2 emissions from all the main stacks of the "Top 3" industrial sources were defined on an hourly basis. A sequence of nested mesoscale meteorological models (MM5 + NSWIFT) was used to represent the flow over the Seine Estuary, and a 3D Lagrangian Dispersion model (SPRAY) was used to simulate the time dependent SO2 concentration distributions. The paper presents the comparisons between model results and measurements and the model evaluation conclusions, and focuses on the difficulties of high-resolution micro-meteorological modelling in weak winds and stable conditions in an Estuary situation, with topographic and sea breeze effects. A subset of the episodes for which the quality of the results was fairly good was selected and the results of the simulations for these cases have been actually applied to the computation of optimal emission reductions. Source

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