French National Institute for Industrial Environment and Risks

Verneuil-en-Halatte, France

French National Institute for Industrial Environment and Risks

Verneuil-en-Halatte, France
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Saib M.-S.,French National Institute for Industrial Environment and Risks | Caudeville J.,French National Institute for Industrial Environment and Risks | Beauchamp M.,French National Institute for Industrial Environment and Risks | Carre F.,French National Institute for Industrial Environment and Risks | And 3 more authors.
Environmental Health: A Global Access Science Source | Year: 2015

Background: Reducing health inequalities involves the identification and characterization of social and exposure factors and the way they accumulate in a given area. The areas of accumulation then allow for prioritization of interventions. The present study aims to build spatial composite indicators based on the aggregation of environmental, social and health indicators and their inter-relationships. Method: Preliminary work was carried out firstly to homogenize spatial coverage, and secondly to study spatial variation of environmental (EI), socioeconomic (SI) and health (HI) indicators. The aggregation of the different indicators was performed using several methodologies for which results and decision-makers' usability were compared. Results: Four methodologies were tested: 1) A simple summation of normalized HI, EI and SI indicators (IC), 2) the sum of the normalized HI, EI and SI indicators weighted by the first principal component of a Principal Component Analysis (IC PCA), 3) the sum of normalized and weighted indicators of the first principal component of Local Principal Component Analysis (IC LPCA), and 4) the sum of normalized and weighted indicators of the first principal component of a Geographically Weighted Principal Component Analysis (IC GWPCA). Conclusion: The GWPCA is particularly adapted to taking into account the spatial heterogeneity and the spatial autocorrelation between SI, EI and HI. This approach invalidates the basic assumptions of many standard statistical analyses. Where socioeconomic indicators present high deprivation and where they are associated with potential modifiable health determinants, decision-makers can prioritize these areas for reducing inequalities by controlling the socioeconomic and health determinants. © 2015 Saib et al.


PubMed | Regional Observatory of Health and Social Issues in Picardie, French National Institute for Industrial Environment and Risks and University hospital of Amiens
Type: | Journal: Environmental health : a global access science source | Year: 2015

Reducing health inequalities involves the identification and characterization of social and exposure factors and the way they accumulate in a given area. The areas of accumulation then allow for prioritization of interventions. The present study aims to build spatial composite indicators based on the aggregation of environmental, social and health indicators and their inter-relationships.Preliminary work was carried out firstly to homogenize spatial coverage, and secondly to study spatial variation of environmental (EI), socioeconomic (SI) and health (HI) indicators. The aggregation of the different indicators was performed using several methodologies for which results and decision-makers usability were compared.Four methodologies were tested: 1) A simple summation of normalized HI, EI and SI indicators (IC), 2) the sum of the normalized HI, EI and SI indicators weighted by the first principal component of a Principal Component Analysis (IC PCA), 3) the sum of normalized and weighted indicators of the first principal component of Local Principal Component Analysis (IC LPCA), and 4) the sum of normalized and weighted indicators of the first principal component of a Geographically Weighted Principal Component Analysis (IC GWPCA).The GWPCA is particularly adapted to taking into account the spatial heterogeneity and the spatial autocorrelation between SI, EI and HI. This approach invalidates the basic assumptions of many standard statistical analyses. Where socioeconomic indicators present high deprivation and where they are associated with potential modifiable health determinants, decision-makers can prioritize these areas for reducing inequalities by controlling the socioeconomic and health determinants.


Saib M.-S.,French National Institute for Industrial Environment and Risks | Saib M.-S.,University of Picardie Jules Verne | Caudeville J.,French National Institute for Industrial Environment and Risks | Carre F.,French National Institute for Industrial Environment and Risks | And 3 more authors.
International Journal of Environmental Research and Public Health | Year: 2014

Spatial health inequalities have often been analyzed in terms of socioeconomic and environmental factors. The present study aimed to evaluate spatial relationships between spatial data collected at different spatial scales. The approach was illustrated using health outcomes (mortality attributable to cancer) initially aggregated to the county level, district socioeconomic covariates, and exposure data modeled on a regular grid. Geographically weighted regression (GWR) was used to quantify spatial relationships. The strongest associations were found when low deprivation was associated with lower lip, oral cavity and pharynx cancer mortality and when low environmental pollution was associated with low pleural cancer mortality. However, applying this approach to other areas or to other causes of death or with other indicators requires continuous exploratory analysis to assess the role of the modifiable areal unit problem (MAUP) and downscaling the health data on the study of the relationship, which will allow decision-makers to develop interventions where they are most needed. © 2014 by the authors; licensee MDPI, Basel, Switzerland.


Lafortune S.,French National Institute for Industrial Environment and Risks | Adelise F.,French National Institute for Industrial Environment and Risks | Lahaiea F.,French National Institute for Industrial Environment and Risks | Beaufils B.,French National Institute for Industrial Environment and Risks | And 6 more authors.
Energy Procedia | Year: 2014

INERIS has monitored a CO2 injection test performed in a coal seam. Both passive seismic monitoring and gas monitoring have been performed prior, during and after the injection test. Gas migration was not monitored in coal because leakage occurred during the injection. Nevertheless, passive seismic monitoring and continuous gas monitoring proved here to be valuable tools to observe gas migration and the behaviour of the rock during the injection test. They also helped to understand the discrepancies between observations and predictions, which can be useful to draw recommendations for future tests. © 2014 The Authors. Published by Elsevier Ltd.


Lafortune S.,French National Institute for Industrial Environment and Risks | Adelise F.,French National Institute for Industrial Environment and Risks | Rhenals Garrido D.R.,French National Institute for Industrial Environment and Risks | Pokryszka Z.,French National Institute for Industrial Environment and Risks
Energy Procedia | Year: 2014

Oil and gas production from shale formations stimulated by hydraulic fracturing (or "fracking") is an abundant source of domestically available energy for the United States of America. Today, shale formations are mostly fracked using fresh water or brine which induces large volumes of water to manage. The use of CO2 is an alternative fracking option and appears to have several benefits, as (1) it does not require water but carbon dioxide; as (2) injection of carbon dioxide could enhance the gas recovery; and as (3) carbon dioxide could be adsorbed onto the shale surface to be permanently stored in the formation. We performed adsorption experiments to assess the quantity of carbon dioxide that could be adsorbed onto shale. © 2014 The Authors. Published by Elsevier Ltd.


Lafortune S.,French national institute for industrial environment and risks | Pokryszka Z.,French national institute for industrial environment and risks | Bentivegna G.,French national institute for industrial environment and risks | Farret .R.,French national institute for industrial environment and risks
Energy Procedia | Year: 2013

Involved in several research projects funded by France and European Union on carbon capture and storage, INERIS has worked for many years on the design, building, testing and field-deployment of gas monitoring devices in soil and subsurface on industrial sites. INERIS has developed a strong experience using self-designed devices dedicated to the characterization of CO2 storages and analogues of natural or anthropogenic CO2-leaking systems. INERIS focuses on the monitoring of gas flux at surface and on the monitoring of gas migration in the subsurface using gas monitoring wells. After many years of worldwide research done by many researchers and industrials it's now time to adopt a "monitoring -ready" approach. That means to be ready to challenge industrial and stakeholders' expectations for efficient, field-deployable and cheap solutions to perform efficient gas monitoring in the soil and the subsurface. We will here discuss the way INERIS performs surface and subsurface gas measurements (1) to achieve baseline studies on storage sites before injection starts, (2) to ensure monitoring in injection and post-injection phases and(3) to characterize leaking processes that impact surface and urban areas.

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