Modelling of occupational respirable crystalline silica exposure for quantitative exposure assessment in community-based case-control studies

We describe an empirical model for exposure to respirable crystalline silica (RCS) to create a quantitative job-exposure matrix (JEM) for community-based studies. Personal measurements of exposure to RCS from Europe and Canada were obtained for exposure modelling. A mixed-effects model was elaborated, with region/country and job titles as random effect terms. The fixed effect terms included year of measurement, measurement strategy (representative or worst-case), sampling duration (minutes) and a priori exposure intensity rating for each job from an independently developed JEM (none, low, high). 23,640 personal RCS exposure measurements, covering a time period from 1976 to 2009, were available for modelling. The model indicated an overall downward time trend in RCS exposure levels of -6% per year. Exposure levels were higher in the UK and Canada, and lower in Northern Europe and Germany. Worst-case sampling was associated with higher reported exposure levels and an increase in sampling duration was associated with lower reported exposure levels. Highest predicted RCS exposure levels in the reference year (1998) were for chimney bricklayers (geometric mean 0.11 mg m(-3)), monument carvers and other stone cutters and carvers (0.10 mg m(-3)). The resulting model enables us to predict time-, job-, and region/country-specific exposure levels of RCS. These predictions will be used in the SYNERGY study, an ongoing pooled multinational community-based case-control study on lung cancer.     

Regression Analysis Model Applied to Biomonitoring Studies

A regression model is proposed for studying the relationship between trace metals concentrations and weights of individuals of Monodonta turbinata (Born), a gastropod mollusc used as a trace metal biomonitor of marine coastal areas. The model herein presented was developed including sites as reference factors and showed very good correlations. The prevision model of contamination gave good results for this kind of pollutants, and it can be used as a tool for monitoring programmes.     

Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon

Fisheries and water resource managers are challenged to maintain stable or increasing populations of Chinook salmon in the face of increasing demand on the water resources and habitats that salmon depend on to complete their life cycle. Alternative management plans are often selected using professional opinion or piecemeal observations in place of integrated quantitative information that could reduce uncertainty in the effects of management plans on population dynamics. We developed a stochastic life cycle simulation model for an endangered population of winter-run Chinook salmon in the Sacramento River, California, USA with the goal of providing managers a tool for more effective decision making and demonstrating the utility of life cycle models for resource management. Sensitivity analysis revealed that the input parameters that influenced variation in salmon escapement were dependent on which age class was examined and their interactions with other inputs (egg mortality, Delta survival, ocean survival). Certain parameters (river migration survival, harvest) that were hypothesized to be important drivers of population dynamics were not identified in sensitivity analysis; however, there was a large amount of uncertainty in the value of these inputs and their error distributions. Thus, the model also was useful in identifying future research directions. Simulation of variation in environmental inputs indicated that escapement was significantly influenced by a 10% change in temperature whereas larger changes in other inputs would be required to influence escapement. The model presented provides an effective demonstration of the utility of life cycle simulation models for decision making and provides fisheries and water managers in the Sacramento system with a quantitative tool to compare the impact of different resource use scenarios.     

Levels and congener profiles of polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans and dioxin-like polychlorinated biphenyls in cow’s milk collected in Campania, Italy

Polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and certain dioxin-like polychlorinated biphenyls (dl-PCBs) are a family of chemically-related lipophilic compounds characterized by similar toxicity. Due to their properties they are universally distributed in the environment and classified as persistent organic pollutants (POPs). From most of studies carried out to evaluate human dietary intake, milk and dairy products result as a major contributors of PCDD/Fs uptake. Of course the main source of milk contamination is animal feeds. Lactating ruminants, cows included, transfer these compounds to the food chain by ingestion of contaminated vegetables or soil. Their resistance to degradation and a high lipophilicity means that PCDD/Fs and dl-PCBs may be accumulated into fat tissues from which they are transferred to milk during lactation period.Seventy-nine cows milk samples, collected in the monitoring plan 2008, were analyzed for PCDD/Fs and dl-PCBs. Eleven milk samples were non-compliant corresponding to five breeding livestock located in Caserta province. The distribution of PCDD/Fs and dl-PCBs congeners in these samples was examined in order to determine the likely sources of dioxins. The results show that the congener profile is characterized by a prevalence of PCDFs in respect of PCDDs, that represents the typical pattern of thermal origin contamination.     

Characterization and identification of trends in average ambient ozone and fine particulate matter levels through trajectory cluster analysis in eastern Canada

In many locations in Eastern Canada, ambient levels of fine particulate matter (PM,25) and surface ozone (O3) depend on airflow direction and synoptic scale meteorological conditions. In this study, a cluster analysis was performed on 10 yr (1994-2003) of back-trajectory data for 11 locations in Eastern Canada, resulting in the identification of 10 unique back-trajectory clusters (or airflows) for each location. The airflows were then used to characterize and identify spatial and temporal trends in the daily maximum 8-hr average O3 (dmax 8-hr O3) and the daily average PM2.5 levels. Results showed that airflows from the southwest passing over Michigan and Southern Ontario were associated, on average, with the highest O3 levels at most locations in Eastern Canada. For PM2.5, the highest levels occurred with airflows from the Eastern Ohio River Valley. At major urban locations in Ontario and Quebec, the warm season mean (May to September) dmax 8-hr O3 and the annual mean PM2.5 were, on average, 12 parts per billion and 7.6 microg/m3 higher, respectively, than airflows from the north. Elevated levels of O3 and PM2.5 also occurred under light airflows, and, on average, the levels under light airflows were higher than their nonlight counterparts. At several locations in Canada, including Toronto, Montreal, Quebec City, and Kejimkujik, the annual warm season mean dmax 8-hr O3 experienced a statistically significant (95% confidence) increasing trend over the 10-yr period. When airflow direction was considered, a number of locations experienced statistically significant upward trends in O3 for airflow from the north and northwest. Several locations also showed significant upward trends associated with airflow from the southwest passing over Michigan and Southwestern Ontario. Although there are no statistically significant downward trends, airflows from the southwest have shown a reduction in O3 levels in Southwestern Ontario in more recent years.     

High concern chemicals in top layer sediments of the northern Adriatic seabed as markers of old waste dumpings

The results are presented of a survey planned to assess the presence of high concern chemicals in sediments collected in a northern sector of the Adriatic sea neighboring the Venice lagoon. For the assessment, persistent marker chemicals were selected from the families of polycyclic aromatic hydrocarbons, polychlorobiphenyls, polychlorodibenzo-p-dioxins (PCDDs), polychlorodibenzofurans (PCDFs), and chlorinated pesticides. Based on the chemical-specific concentrations and PCDD+PCDF profiles determined in the sediments analyzed, dumping zones appear to have existed approximately 5-6km away from lagoon shoreline. Contamination levels exceed the quality criteria established by the pertinent Italian national regulation at many sampling sites, eventually reflecting ("fingerprinting") industrial activities once performed in the industrial settlement of Porto Marghera within the Venice lagoon. In coastal samples, concentration levels appear to be lower than those determined at offshore sampling sites.     

Temperature and discharge variations in natural mineral water springs due to climate variability: a case study in the Piedmont Alps (NW Italy)

Environmental Geochemistry and Health - In the context of global climate change, understanding the relationships between climate and groundwater is increasingly important. This study in the NW Alps...     

Multitechnique diagnostic analysis and 3D surveying prior to the restoration of St. Michael defeating Evil painting by Mattia Preti

Environmental Science and Pollution Research - In this study, a multimethodological analysis involving optical and physical/chemical diagnostic techniques and 3D photogrammetric survey was...