The structure of the fire fighting foam surfactant Forafac®1157 and its biological and photolytic transformation products

For several decades, perfluorooctane sulfonate (PFOS) has widely been used as a fluorinated surfactant in aqueous film forming foams used as hydrocarbon fuel fire extinguishers. Due to concerns regarding its environmental persistence and toxicological effects, PFOS has recently been replaced by novel fluorinated surfactants such as Forafac®1157, developed by the DuPont company. The major component of Forafac®1157 is a 6:2 fluorotelomer sulfonamide alkylbetaine (6:2 FTAB), and a link between the trade name and the exact chemical structure is presented here to the scientific community for the first time. In the present work, the structure of the 6:2 FTAB was elucidated by ¹H, ¹³C and ¹⁹F nuclear magnetic resonance spectroscopy and high-resolution mass spectrometry. Moreover, its major metabolites from blue mussel (Mytilus edulis) and turbot (Scophthalmus maximus) and its photolytic transformation products were identified. Contrary to what has earlier been observed for PFOS, the 6:2 FTAB was extensively metabolized by blue mussel and turbot exposed to Forafac®1157. The major metabolite was a deacetylated betaine species, from which mono- and di-demethylated metabolites also were formed. Another abundant metabolite was the 6:2 fluorotelomer sulfonamide. In another experiment, Forafac®1157 was subjected to UV-light induced photolysis. The experimental conditions aimed to simulate Arctic conditions and the deacetylated species was again the primary transformation product of 6:2 FTAB. A 6:2 fluorotelomer sulfonamide was also formed along with a non-identified transformation product. The environmental presence of most of the metabolites and transformation products was qualitatively demonstrated by analysis of soil samples taken in close proximity to an airport fire training facility.     

Learning from accidents – What more do we need to know?

A model of experience feedback (the CHAIN model) that emphasizes the whole chain from initial reporting to preventive measures is used to identify important research needs in the field of learning from accidents. Based on the model, six quality criteria for experience feedback after an accident or incident are presented. Research on experience feedback from accidents is reviewed. The overall conclusion is that the discipline of experience feedback has not been sufficiently self-reflective. The process of experience feedback can and should be applied to experience feedback itself, but that is rarely done. Evaluation studies are needed that provide hard (evidence-based) information about the effects of various methodologies and organizational structures. Four types of studies are particularly important for the development of evidence-based accident investigation practices: (1) studies of the effects and the efficiency of different accident investigation methods, (2) studies of the dissemination of conclusions from accident investigation, (3) follow-up studies of the extent to which accident investigation reports give rise to actual preventive measures, and (4) studies of the integration of experience feedback systems into overall systems of risk management.     

Appraisal of measurement methods, chemical composition and sources of fine atmospheric particles over six different areas of Northern Belgium

Daily and seasonal variation in the total elemental, organic carbon (OC) and elemental carbon (EC) content and mass of PM_2.5 were studied at industrial, urban, suburban and agricultural/rural areas. Continuous (optical Dustscan, standard tapered element oscillating micro-balance (TEOM), TEOM with filter dynamics measurement system), semi-continuous (Partisol filter-sampling) and non-continuous (Dekati-impactor sampling and gravimetry) methods of PM_2.5 mass monitoring were critically evaluated. The average elemental fraction accounted for 2-6% of the PM_2.5 mass measured by gravimetry. Metals, like K, Mn, Fe, Cu, Zn and Pb were strongly inter-correlated, also frequently with non-metallic elements (P, S, Cl and/or Br) and EC/OC. A high OC/EC ratio (2-9) was generally observed. The total carbon content of PM_2.5 ranged between 3 and 77% (averages: 12-32%), peaking near industrial/heavy trafficked sites. Principal component analysis identified heavy oil burning, ferrous/non-ferrous industry and vehicular emissions as the main sources of metal pollution.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

Grading of Parameters for Urban Tree Inventories by City Officials, Arborists, and Academics Using the Delphi Method

Tree inventories are expensive to conduct and update, so every inventory carried out must be maximized. However, increasing the number of constituent parameters increases the cost of performing and updating the inventory, illustrating the need for careful parameter selection. This article reports the results of a systematic expert rating of tree inventories aiming to quantify the relative importance of each parameter. Using the Delphi method, panels comprising city officials, arborists, and academics rated a total of 148 parameters. The total mean score, the top ranking parameters, which can serve as a guide for decision-making at practical level and for standardization of tree inventories, were: Scientific name of the tree species and genera, Vitality, Coordinates, Hazard class, and Identification number. The study also examined whether the different responsibilities and usage of urban tree databases among organizations and people engaged in urban tree inventories affected their prioritization. The results revealed noticeable dissimilarities in the ranking of parameters between the panels, underlining the need for collaboration between the research community and those commissioning, administrating, and conducting inventories. Only by applying such a transdisciplinary approach to parameter selection can urban tree inventories be strengthened and made more relevant.     

Elemental composition of sediments in Lake Jinzai, Japan: Assessment of sources and pollution

Bottom sediments from Lake Jinzai in southwest Japan were analyzed to determine their chemical compositions and to assess the potential for ecological harm by comparison with sediment quality guidelines. The pollution status of lake sediments was evaluated by employing contamination factor (CF), pollution load index (PLI), and geoaccumulation index (I(geo)), focusing on a suite of elements in lakebed and core sediments. Elevated concentrations of As, Pb, Zn, Cu, TOC, N, and P were present in several layers of the upper core and other surface sediments. The elevated metal concentrations are likely related to the fine-grained nature of the sediments, reducing bottom conditions produced by abundant organic matter, and possibly minor non-point anthropogenic sources. Moreover, correlations between the concentrations of trace metals and organic carbon, nitrogen, phosphorus, and iron, suggest that these elements play a role in controlling abundances. Calculated CF, PLI, and I(geo) indicate that the sediments are strongly polluted with respect to As, moderately to strongly polluted with Zn, and moderately polluted with Pb and Cu. Metal concentrations exceed the New York State Department of Environmental Conservation (NYSDEC) lowest effect level and the Canadian Council of Ministers of the Environment (CCME) interim sediment quality guidelines that indicate moderate impact on aquatic organisms in the study area.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

Quantifying the effects of trampling and habitat edges on forest understory vegetation – A field experiment

We investigated the effects of human trampling on boreal forest understory vegetation on, and off paths from suburban forest edges towards the interiors and on the likelihood of trampling-aided dispersal into the forests for three years by carrying out a trampling experiment. We showed that the vegetation was highly sensitive to trampling. Even low levels of trampling considerably decreased covers of the most abundant species on the paths. Cover decreased between 10 and 30% on paths which had been trampled 35 times, and at least by 50% on those trampled 70–270 times. On-path vegetation cover decreased similarly at forest edges and in the interiors. However, some open habitat plant species that occurred outside the forest patches and at forest edges dispersed into the forests, possibly through the action of trampling. A higher cover percentage of an open habitat species at the forest edge line increased its probability to disperse into the forest interior. The vegetation community on, next to, and away from lightly trampled paths remained the same throughout the trampling experiment. For heavily trampled paths, the community changed drastically on the paths, but stayed relatively similar next to and away from the paths. As boreal vegetation is highly sensitive to the effects of trampling, overall ease of access throughout the forest floor should be restricted to avoid the excessive creation of spontaneous paths. To minimize the effects of trampling, recreational use could be guided to the maintained path network in heavily used areas.     

EXAMINING LAND USE INFLUENCES ON STREAM HABITATS AND MACROINVERTEBRATES: A GIS APPROACH1

ABSTRACT: Geographic Information Systems (GIS) were used to assess the relationships between land use patterns and the physical habitat and macroinvertebrate fauna of streams within similar sized watersheds. Eleven second or third order watersheds ranging from highly urbanized to heavily forested were selected along Lake Superior's North Shore. Land use patterns within the watersheds were quantified using readily available digital land use/land cover information, with a minimum mapping resolution of 16 ha. Physical habitat features, describing substrate characteristics and stream morphology, were characterized at sample points within each stream. Principle component and correlation analyses were used to identify relationships between macroinvertebrates and stream physical habitat, and between habitat and land use patterns. Substrate characteristics and presence of coarse woody debris were found to have the strongest correlations with macreinvertebrate assemblage richness and composition. Agricultural and urban land use was correlated with substrate characteristics. Algal abundance, associated with macroinvertebrate compositional differences, was correlated with housing density and non-forest land covers. The use of readily available spatial data, even at this relatively coarse scale, provides a means to detect the primary relationships between land use and stream habitat quality; finer-resolution GIS databases are needed to assess more subtle influences, such as those due to riparian conditions.