Biomass burning is a significant source of particulate matter (PM) in ambient air. To date, the evaluation of the distinct contributions of both, wood burning, used for residential heating, and green waste burning, on the PM concentration levels is difficult and rarely achieved. Such discrimination is of major concern for air quality policy-makers in order to implement efficient actions to reduce air pollution. The main objective of the research project SODEMASS (bioMASS burning SOurces DEconvolution) is to identify specific organic molecular markers and/or chemical patterns of both biomass burning sources that can be further used in PM source apportionment studies. Several experiments have been performed in “real” conditions in a large combustion chamber facility (1000 m3) to simulate the ambient air dilution conditions. Different wood combustion appliances, such as a residential wood stove and a fireplace, under different output conditions (nominal vs reduced) and wood log moisture content (mix of species including beech, oak and hornbeam), have been tested. The green waste burning experiments have been carried out using two kinds of burning material such as grass mowing with tree leaves and hedge trimming with branches. Smoke temperature, O2, NOx, CO, CO2, non-volatile PM concentrations, were monitored continuously by using automatic sensors or analyzers and about 50 PM samples (on quartz fiber filters) have been collected after dilution (dilution factor about 500-1000). Filter samples have been characterized using both, targeted (EC/OC, levoglucosan and its isomers, PAHs, methoxyphenols, alkanes, polyols) and non-targeted (high resolution mass spectrometry analyses) approaches. Preliminary targeted results showed the predominance of higher molecular weight alkanes with odd carbon numbers (C27, C29, C31) in the case of green waste burning versus open or closed fires. Results obtained showed that levoglucosan/mannosan ratios for green waste burning ( 17). For the non-target screening approach, which is not commonly used in the atmospheric chemistry, a description of the analytical development will be presented. Thanks to the chemical fingerprints obtained from GC/Q-TOF-MS and LC/Q-TOF-MS analyses and statistical data analysis, chemical pattern of each biomass burning source will be highlighted and will complete the information already provided by the targeted results to better discriminate both sources.
Abstract Background At a regional or continental scale, the characterization of environmental health inequities (EHI) expresses the idea that populations are not equal in the face of pollution. It implies an analysis be conducted in order to identify and manage the areas at risk of overexposure where an increasing risk to human health is suspected. The development of methods is a prerequisite for implementing public health activities aimed at protecting populations. Methods This paper presents the methodological framework developed by INERIS (French National Institute for Industrial Environment and Risks) to identify a common framework for a structured and operationalized assessment of human exposure. An integrated exposure assessment approach has been developed to integrate the multiplicity of exposure pathways from various sources, through a series of models enabling the final exposure of a population to be defined. Results Measured data from environmental networks reflecting the actual contamination of the environment are used to gauge the population’s exposure. Sophisticated methods of spatial analysis are applied to include additional information and take benefit of spatial and inter-variable correlation to improve data representativeness and characterize the associated uncertainty. Integrated approaches bring together all the information available for assessing the source-to-human-dose continuum using a Geographic Information System, multimedia exposure and toxicokinetic model. Discussion One of the objectives of the integrated approach was to demonstrate the feasibility of building complex realistic exposure scenarios satisfying the needs of stakeholders and the accuracy of the modelling predictions at a fine spatial-temporal resolution. A case study is presented to provide a specific application of the proposed framework and how the results could be used to identify an overexposed population. Conclusion This framework could be used for many purposes, such as mapping EHI, identifying vulnerable populations and providing determinants of exposure to manage and plan remedial actions and to assess the spatial relationships between health and the environment to identify factors that influence the variability of disease patterns.
Abstract Background This study aims to describe and test a tiered approach for assessing compliance to Environmental Quality standards (EQSs) for priority substances in biota in line with the European Water Framework Directive. This approach is based on caged gammarids and trophic magnification factors (TMFs) at the first tier, with fish analyzed at the second tier at sites predicted to exceed the EQS at the first tier. A dataset was implemented by monitoring perfluorooctane sulfonate (PFOS) in caged gammarids exposed at 15 sites in French rivers, and in fish muscle and rest-of-body from the same sites. Isotopic ratios (δ 13 C and δ 15 N) were also measured in gammarids and fish. Two scenarios were developed to compare measured PFOS concentrations in fish against predicted concentrations based on measures in caged gammarids and TMFs. Scenario (1) compared measured PFOS concentrations in fish fillets with predicted PFOS concentrations based on measured concentrations in caged gammarids and δ 15 N. Scenario (2) tested whether or not EQS exceedance was correctly predicted based on measured concentrations in caged gammarids and trophic levels (TLs) from wild fish and gammarid populations. Results δ 13 C and δ 15 N variations showed that caged gammarids used local food resources during exposure in the field. PFOS concentrations in gammarids were fairly variable through time at each site. In fish, concentrations ranged from < 1 to 250 ng g −1 (wet weight). After adjustment to the TL at which the EQS is set, 12 sites were above the EQS for PFOS. In scenario (1), predicted concentrations were almost correct at 7 sites out of 15. Most incorrect predictions were overestimations that were slightly improved by applying a lower (neutral) TMF. In scenario (2) we tested several variants for parameters involved in the predictions. The most efficient combination yielded two wrong predictions out of 15. This result was obtained with a higher (more conservative) TMF value, mean concentrations in gammarids from several field exposures during a year, and a TL for gammarids at the median of the distribution in French rivers. Conclusion The proposed tiered approach was thus efficient. However, the number of sites was relatively limited, and the dataset was biased towards EQS exceedance. The tiered approach warrants further validation.
