Berre-les-Alpes, France
Berre-les-Alpes, France

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Petit J.-E.,Air Lorraine | Amodeo T.,INERIS | Meleux F.,INERIS | Bessagnet B.,INERIS | And 9 more authors.
Atmospheric Environment | Year: 2017

During March 2015, a severe and large-scale particulate matter (PM) pollution episode occurred in France. Measurements in near real-time of the major chemical composition at four different urban background sites across the country (Paris, Creil, Metz and Lyon) allowed the investigation of spatiotemporal variabilities during this episode. A climatology approach showed that all sites experienced clear unusual rain shortage, a pattern that is also found on a longer timescale, highlighting the role of synoptic conditions over Wester-Europe. This episode is characterized by a strong predominance of secondary pollution, and more particularly of ammonium nitrate, which accounted for more than 50% of submicron aerosols at all sites during the most intense period of the episode. Pollution advection is illustrated by similar variabilities in Paris and Creil (distant of around 100 km), as well as trajectory analyses applied on nitrate and sulphate. Local sources, especially wood burning, are however found to contribute to local/regional sub-episodes, notably in Metz. Finally, simulated concentrations from Chemistry-Transport model CHIMERE were compared to observed ones. Results highlighted different patterns depending on the chemical components and the measuring site, reinforcing the need of such exercises over other pollution episodes and sites. © 2017 Elsevier Ltd


Jacquemin B.,French Institute of Health and Medical Research | Jacquemin B.,University Paris - Sud | Lepeule J.,French Institute of Health and Medical Research | Lepeule J.,Joseph Fourier University | And 28 more authors.
Environmental Health Perspectives | Year: 2013

Background: Errors in address geocodes may affect estimates of the effects of air pollution on health. Objective: We investigated the impact of four geocoding techniques on the association between urban air pollution estimated with a fine-scale (10 m × 10 m) dispersion model and lung function in adults. Methods: We measured forced expiratory volume in 1 sec (FEV1) and forced vital capacity (FVC) in 354 adult residents of Grenoble, France, who were participants in two well-characterized studies, the Epidemiological Study on the Genetics and Environment on Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Home addresses were geocoded using individual building matching as the reference approach and three spatial interpolation approaches. We used a dispersion model to estimate mean PM10 and nitrogen dioxide concentrations at each participant's address during the 12 months preceding their lung function measurements. Associations between exposures and lung function parameters were adjusted for individual confounders and same-day exposure to air pollutants. The geocoding techniques were compared with regard to geographical distances between coordinates, exposure estimates, and associations between the estimated exposures and health effects. Results: Median distances between coordinates estimated using the building matching and the three interpolation techniques were 26.4, 27.9, and 35.6 m. Compared with exposure estimates based on building matching, PM10 concentrations based on the three interpolation techniques tended to be overestimated. When building matching was used to estimate exposures, a one-interquartile range increase in PM10 (3.0 μg/m3) was associated with a 3.72-point decrease in FVC% predicted (95% CI: -0.56, -6.88) and a 3.86-point decrease in FEV1% predicted (95% CI: -0.14, -3.24). The magnitude of associations decreased when other geocoding approaches were used [e.g., for FVC% predicted -2.81 (95% CI: -0.26, -5.35) using NavTEQ, or 2.08 (95% CI -4.63, 0.47, p = 0.11) using Google Maps]. Conclusions: Our findings suggest that the choice of geocoding technique may influence estimated health effects when air pollution exposures are estimated using a fine-scale exposure model.


Cyrys J.,Helmholtz Center for Environmental Research | Cyrys J.,University of Augsburg | Eeftens M.,University Utrecht | Heinrich J.,Helmholtz Center for Environmental Research | And 59 more authors.
Atmospheric Environment | Year: 2012

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects of exposure to air pollution on human health in Europe. This paper documents the spatial variation of measured NO2 and NOx concentrations between and within 36 ESCAPE study areas across Europe.In all study areas NO2 and NOx were measured using standardized methods between October 2008 and April 2011. On average, 41 sites were selected per study area, including regional and urban background as well as street sites. The measurements were conducted in three different seasons, using Ogawa badges. Average concentrations for each site were calculated after adjustment for temporal variation using data obtained from a routine monitor background site.Substantial spatial variability was found in NO2 and NOx concentrations between and within study areas; 40% of the overall NO2 variance was attributable to the variability between study areas and 60% to variability within study areas. The corresponding values for NOx were 30% and 70%. The within-area spatial variability was mostly determined by differences between street and urban background concentrations. The street/urban background concentration ratio for NO2 varied between 1.09 and 3.16 across areas. The highest median concentrations were observed in Southern Europe, the lowest in Northern Europe.In conclusion, we found significant contrasts in annual average NO2 and NOx concentrations between and especially within 36 study areas across Europe. Epidemiological long-term studies should therefore consider different approaches for better characterization of the intra-urban contrasts, either by increasing of the number of monitors or by modelling. © 2012 Elsevier Ltd.


Golly B.,University of Savoy | Brulfert G.,Air Rhone Alpes | Berlioux G.,SGL CARBON S.A.S | Jaffrezo J.-L.,French National Center for Scientific Research | Besombes J.-L.,University of Savoy
Science of the Total Environment | Year: 2015

This work focuses on emissions from industrial sources that are still poorly understood in Europe, especially the "carbon industry". The study is based on two intensive sampling campaigns performed in a graphite material production plant for 2weeks in July 2013 and November 2013 in alpine valleys. The chemical characterization of PM10 was conducted at three sampling sites (outdoor and indoor sites) located inside one industrial area, which is considered as the highest emissions source of polycyclic aromatic hydrocarbons (PAHs) in the Arve valley. The identification of specific tracers among metals and trace elements is commonly used to characterize industrial emissions. In our study, original enrichment factors relative to the "rural exposed background" have been calculated, and the metallic fraction was not affected by this industrial source. In contrast, the organic fraction of PM10 has a number of features, providing a complete organic source profile and referred to as the "carbon industry". In particular, polycyclic aromatic sulfur heterocycles (PASH) have been largely detected from fugitive emissions with rather large concentrations. The average concentrations of benzo(b)naphtho(2,1-d)thiophene (BNT(2,1)) reached 2.35-6.56ng·m-3 and 60.5-376ng·m-3 for outdoor and indoor sites, respectively. The use of this reference profile in the chemical mass balance model (CMB) applied to samples collected in two sites near industrial areas shows that this source had an average contribution of 6% of the organic matter (OM) mass during the sampling period during the winter of 2013. © 2015 Elsevier B.V.


PubMed | SGL CARBON S.A.S, French National Center for Scientific Research, University of Savoy and Air Rhone Alpes
Type: | Journal: The Science of the total environment | Year: 2015

This work focuses on emissions from industrial sources that are still poorly understood in Europe, especially the carbon industry. The study is based on two intensive sampling campaigns performed in a graphite material production plant for 2weeks in July 2013 and November 2013 in alpine valleys. The chemical characterization of PM10 was conducted at three sampling sites (outdoor and indoor sites) located inside one industrial area, which is considered as the highest emissions source of polycyclic aromatic hydrocarbons (PAHs) in the Arve valley. The identification of specific tracers among metals and trace elements is commonly used to characterize industrial emissions. In our study, original enrichment factors relative to the rural exposed background have been calculated, and the metallic fraction was not affected by this industrial source. In contrast, the organic fraction of PM10 has a number of features, providing a complete organic source profile and referred to as the carbon industry. In particular, polycyclic aromatic sulfur heterocycles (PASH) have been largely detected from fugitive emissions with rather large concentrations. The average concentrations of benzo(b)naphtho(2,1-d)thiophene (BNT(2,1)) reached 2.35-6.56ngm(-3) and 60.5-376ngm(-3) for outdoor and indoor sites, respectively. The use of this reference profile in the chemical mass balance model (CMB) applied to samples collected in two sites near industrial areas shows that this source had an average contribution of 6% of the organic matter (OM) mass during the sampling period during the winter of 2013.


Fallah Shorshani M.,ParisTech National School of Bridges and Roads | Fallah Shorshani M.,IFSTTAR Institute Francais des science et Technologies des Transports | Seigneur C.,ParisTech National School of Bridges and Roads | Polo Rehn L.,French National Center for Scientific Research | And 6 more authors.
Transportation Research Part D: Transport and Environment | Year: 2015

Atmospheric pollutant dispersion near sources is typically simulated by Gaussian models because of their efficient compromise between reasonable accuracy and manageable computational time. However, the standard Gaussian dispersion formula applies downwind of a source under advective conditions with a well-defined wind direction and cannot calculate air pollutant concentrations under calm conditions with fluctuating wind direction and/or upwind of the emission source. Attempts have been made to address atmospheric dispersion under such conditions. This work evaluates the performance of standard and modified Gaussian plume models using measurements of NO2, PM10, PM2.5, five inorganic ions and seven metals conducted near a freeway in Grenoble, France, during 11-27 September 2011. The formulation for calm conditions significantly improves model performance. However, it appears that atmospheric dispersion due to vehicle-induced turbulence is still underestimated. Furthermore, model performance is poor for particulate species unless road dust resuspension by traffic is explicitly taken into account. © 2014 Elsevier Ltd.


Soulhac L.,École Centrale Lyon | Lamaison G.,École Centrale Lyon | Cierco F.-X.,Compagnie Nationale du Rhone | Ben Salem N.,Air Rhone Alpes | And 4 more authors.
Atmospheric Environment | Year: 2016

SIRANERISK is an operational model for the simulation of the dispersion of unsteady atmospheric releases of pollutant within and above an urban area. SIRANERISK is built on the same principles as the SIRANE model, and couples a street network model for the pollutant transfers within the urban canopy with a Gaussian puff model for the transfers above it. The performance of the model are here analysed by a detailed comparisons with wind-tunnel experiments. These experiments concern the dispersion of steady and unsteady pollutant releases within and above obstacle arrays with varying geometrical configurations, representing different topologies of idealised urban districts. The overall good agreement between numerical and experimental data demonstrates the reliability of SIRANERISK as an operational tool for the assessment of risk analysis and for the management of crises due to the accidental release of harmful airborne pollutants within a built environment. © 2016 Elsevier Ltd.


Morelli X.,French Institute of Health and Medical Research | Rieux C.,Air Rhone Alpes | Cyrys J.,Helmholtz Center for Environmental Research | Forsberg B.,Umeå University | Slama R.,French Institute of Health and Medical Research
Environmental Research | Year: 2016

Risk assessment studies often ignore within-city variations of air pollutants. Our objective was to quantify the risk associated with fine particulate matter (PM2.5) exposure in 2 urban areas using fine-scale air pollution modeling and to characterize how this risk varied according to social deprivation. In Grenoble and Lyon areas (0.4 and 1.2 million inhabitants, respectively) in 2012, PM2.5 exposure was estimated on a 10×10 m grid by coupling a dispersion model to population density. Outcomes were mortality, lung cancer and term low birth weight incidences. Cases attributable to air pollution were estimated overall and stratifying areas according to the European Deprivation Index (EDI), taking 10 μg/m3 yearly average as reference (counterfactual) level. Estimations were repeated assuming spatial homogeneity of air pollutants within urban area. Median PM2.5 levels were 18.1 and 19.6 μg/m3 in Grenoble and Lyon urban areas, respectively, corresponding to 114 (5.1% of total, 95% confidence interval, CI, 3.2-7.0%) and 491 non-accidental deaths (6.0% of total, 95% CI 3.7-8.3%) attributable to long-term exposure to PM2.5, respectively. Attributable term low birth weight cases represented 23.6% of total cases (9.0-37.1%) in Grenoble and 27.6% of cases (10.7-42.6%) in Lyon. In Grenoble, 6.8% of incident lung cancer cases were attributable to air pollution (95% CI 3.1-10.1%). Risk was lower by 8 to 20% when estimating exposure through background stations. Risk was highest in neighborhoods with intermediate to higher social deprivation. Risk assessment studies relying on background stations to estimate air pollution levels may underestimate the attributable risk. © 2016 Elsevier Inc.


PubMed | Air Rhone Alpes, Grenoble University Hospital Center and French Institute of Health and Medical Research
Type: | Journal: Environment international | Year: 2015

Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity and indoor air pollution levels. We recruited 40 pregnant women in the Grenoble urban area, France, who carried a Global Positioning System (GPS) during up to 3 weeks; in a subgroup, indoor measurements of fine particles (PM2.5) were conducted at home (n=9) and personal exposure to nitrogen dioxide (NO2) was assessed using passive air samplers (n=10). Outdoor concentrations of NO2, and PM2.5 were estimated from a dispersion model with a fine spatial resolution. Women spent on average 16 h per day at home. Considering only outdoor levels, for estimates at the home address, the correlation between the estimate using the nearest background air monitoring station and the estimate from the dispersion model was high (r=0.93) for PM2.5 and moderate (r=0.67) for NO2. The model incorporating clean GPS data was less correlated with the estimate relying on raw GPS data (r=0.77) than the model ignoring space-time activity (r=0.93). PM2.5 outdoor levels were not to moderately correlated with estimates from the model incorporating indoor measurements and space-time activity (r=-0.10 to 0.47), while NO2 personal levels were not correlated with outdoor levels (r=-0.42 to 0.03). In this urban area, accounting for space-time activity little influenced exposure estimates; in a subgroup of subjects (n=9), incorporating indoor pollution levels seemed to strongly modify them.


PubMed | Air Rhone Alpes, Umeå University, French Institute of Health and Medical Research and Helmholtz Center for Environmental Research
Type: | Journal: Environmental research | Year: 2016

Risk assessment studies often ignore within-city variations of air pollutants. Our objective was to quantify the risk associated with fine particulate matter (PM2.5) exposure in 2 urban areas using fine-scale air pollution modeling and to characterize how this risk varied according to social deprivation. In Grenoble and Lyon areas (0.4 and 1.2 million inhabitants, respectively) in 2012, PM2.5 exposure was estimated on a 1010m grid by coupling a dispersion model to population density. Outcomes were mortality, lung cancer and term low birth weight incidences. Cases attributable to air pollution were estimated overall and stratifying areas according to the European Deprivation Index (EDI), taking 10g/m(3) yearly average as reference (counterfactual) level. Estimations were repeated assuming spatial homogeneity of air pollutants within urban area. Median PM2.5 levels were 18.1 and 19.6g/m(3) in Grenoble and Lyon urban areas, respectively, corresponding to 114 (5.1% of total, 95% confidence interval, CI, 3.2-7.0%) and 491 non-accidental deaths (6.0% of total, 95% CI 3.7-8.3%) attributable to long-term exposure to PM2.5, respectively. Attributable term low birth weight cases represented 23.6% of total cases (9.0-37.1%) in Grenoble and 27.6% of cases (10.7-42.6%) in Lyon. In Grenoble, 6.8% of incident lung cancer cases were attributable to air pollution (95% CI 3.1-10.1%). Risk was lower by 8 to 20% when estimating exposure through background stations. Risk was highest in neighborhoods with intermediate to higher social deprivation. Risk assessment studies relying on background stations to estimate air pollution levels may underestimate the attributable risk.

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