Balancing environmental and industry sustainability: A case study of the US gold mining industry

Mandatory insurance requirements and/or mitigation fees (royalties) for mining companies may help reduce environmental risk exposure for the federal government. Mining is examined since the Environmental Protection Agency (EPA) Toxic Release Inventory reveals that this sector produces more hazardous waste than any other industrial sector. Although uncommon, environmental expense can exceed hundreds of millions of dollars per development. Of particular concern is the potential for mines to become unfunded Superfund sites. Monte Carlo simulation of risk exposure is used to establish a plausible range of unfunded federal liabilities associated with cyanide-leach gold mining. A model is developed to assess these costs and their impact on both the federal budget and corporate profitability (i.e., industry sustainability), particularly if such costs are borne by offending firms.     

Using diatom indices for water quality assessment in a subtropical river, China

Diatoms have been regularly used as bioindicators to assess water quality of surface waters. However, diatom-based indices developed for a specific geographic region may not be appropriate elsewhere. We sampled benthic diatom assemblages in the upper Han River, a subtropical river in China, to evaluate applicability of 14 diatom-based indices used worldwide for water quality assessment. A total of 194 taxa from 31 genera were identified in the dry season and 139 taxa from 23 genera in the wet season. During the dry season, significant relationships were found for all but one of the diatom-based indices (Index Diatom Artois–Picardie) with one or more physical and chemical variables including nutrients and ion concentrations in river waters. The Biological Diatom Index (IBD) and diatom-based eutrophication/pollution index (EPI-D) were strongly related to trophic status and ionic content, while Watanabe’s Index was related to organic pollution and conductivity. Yet, the diatom indices showed weak relationships with physical and chemical variables during the wet season. It suggests that diatom-based indices developed in Europe can be applied with confidence as bioindicators of water quality in subtropical rivers of China, at least during base-flow conditions.     

Levels and trends of HBCD and BDEs in the European and Asian environments, with some information for other BFRs

In this paper, we review recent data for brominated flame retardants (particularly BDEs, HBCD and TBBP-A) in samples from the European and Asian environments, including recent temporal trend studies. Research is active and we cite over 100 studies published during 2005-2007. Environmental compartments studied comprise the atmosphere, indoor and outdoor air, sewage sludges, soils and sediments and a variety of biological samples and food chains. Findings include that the lack of reference materials for use in analytical quality control and method validation identified earlier has been addressed, and certified concentrations are now available for a number of BDE congeners in six pre-existing and one new reference materials. BDE209 was certified in three samples of indoor dust. The analysis of BDE209 remains problematic, but suitable methods for its determination are available and need to be applied. The contamination of indoor environments with BFRs has been recognised as representing a significant uptake pathway, particularly via dust. Additional data for TBBP-A are needed from areas, where it is produced and used, primarily Asia, as the worst-case scenario. As a reactive flame retardant it is less likely to leach from finished products. Also, issues regarding the importance of e-waste recycling as a source of BFRs to the local populations and the local environment require urgent study, certainly in China and possibly elsewhere. Generally, trends show a levelling in concentrations of BDEs and increases in concentrations of HBCD wherever determined and BDE209 in Asia.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Concentrations of organophosphate esters and brominated flame retardants in German indoor dust samples

While it is known that the ingestion of indoor dust contributes substantially to human exposure to the recently restricted polybrominated diphenyl ethers (PBDEs), the situation for one class of potential replacements, i.e. organophosphate esters (OPEs), used in a variety of applications including as flame retardants has yet to be fully characterised. In this study, surface dust from twelve different cars from various locations throughout Germany were analysed for eight OPEs, decabromodiphenyl ethane (DBDPE), and eight PBDEs. In five cars, tris-(1,3-dichloro-2-propyl) phosphate (TDCPP) was the dominant compound with concentrations up to 620 μg g(-1) dust. High concentrations of tri-cresyl phosphate (TCP) (up to 150 μg g(-1)) were also detected in two samples of car dust. Dust from ten offices in the same building in Ludwigsburg, Germany was also analysed. In these samples, tri (2-butoxyethyl) phosphate (TBEP) predominated with an average concentration of 7.0 μg g(-1) dust, followed by tris (1-chloro-2-propyl) phosphate (TCPP) at 3.0 μg g(-1) and triphenyl phosphate (TPhP) at 2.5 μg g(-1) dust. Although caution must be exercised given the relatively small database reported here; this study provides evidence that cars and offices from Germany are significantly more contaminated with OPEs than PBDEs. Average concentrations of ΣOPEs were ten times higher in car than in office dust. This is the first study to provide data on a wide range of OPE concentrations in German indoor dust samples.     

The use of multiple tracers for tracking wastewater discharges in freshwater systems

The assessment of potential impacts of wastewater effluent discharges in freshwater systems requires an understanding of the likely degrees of dilution and potential zones of influence. In this study, four tracers commonly present in wastewater effluents were monitored to compare their relative effectiveness in determining areas in freshwater systems that are likely to be impacted by effluent discharges. The four tracers selected were the human pharmaceutical carbamazepine, anthropogenic gadolinium, fluorescent-dissolved organic matter (fDOM), and electrical conductivity (EC). The four tracers were monitored longitudinally in two distinct freshwater systems receiving wastewater effluents, where one site had a high level of effluent dilution (effluent <1 % of total flow) and the other site had a low level of effluent dilution (effluent ～50 % of total flow). At both sites, the selected tracers exhibited a similar pattern of response intensity downstream of discharge points relative to undiluted wastewater effluent, although a number of anomalies were noted between the tracers. Both EC and fDOM are non-specific to human influences, and both had a high background response, relative to the highly sensitive carbamazepine and anthropogenic gadolinium responses, although the ease of measuring EC and fDOM would make them more adaptable in highly variable systems. However, the greater sensitivity and selectivity of carbamazepine and gadolinium would make their combination with EC and fDOM as tracers of wastewater effluent discharges highly desirable to overcome potential limitations of individual tracers.     

Advantages of Geographically Weighted Regression for Modeling Benthic Substrate in Two Greater Yellowstone Ecosystem Streams

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m² cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r ². For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r ² values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.     

Does vehicle colour influence crash risk?

An often asked question regarding vehicle safety is whether vehicle colour has an influence on crash risk and if so, what is the differential in risk between the various colours of vehicles available. The major objective of this study was to assess the relationship between vehicle colour and crash risk through the analysis of real crash outcomes described in Police reported crash data. The study employed induced exposure methods utilising single vehicle crashes as the comparison crash type. It estimated the crash risk associated with each vehicle colour relative to a reference colour which was chosen to be white. Results of the analysis identified a clear statistically significant relationship between vehicle colour and crash risk. Compared to white vehicles, a number of colours were associated with higher crash risk. These colours were black, blue, grey, green, red and silver. The association between vehicle colour and crash risk was strongest during daylight hours where relative crash risks were higher for the colours listed compared to white by up to around 10%. No colour had a statistically significantly lower crash risk than white although crash risks for a number of other colours were not statistically significantly different from white.     

A review of medical error taxonomies: A human factors perspective

Although a large number of medical error taxonomies have been published, there is little evidence to suggest that these taxonomies have been systematically compared. This paper describes a study comparing 26 medical error taxonomies using a human factors perspective. The taxonomies were examined to determine if they classified systemic factors of medical errors and if they utilized theoretical error concepts in their classifications. Scope of classification was also examined. It was found that two-thirds of the taxonomies classified systemic factors of medical errors and only a third utilized theoretical error concepts. Medical error taxonomies based on theoretical error concepts were more likely to be generic in applicability and also more likely to classify systemic factors and psychological error mechanisms of medical errors. In addition to terminology, the medical error taxonomies also varied in terms of domain-specificity, granularity, and developmental process. Different medical error taxonomies provide different information; how these differences affect medical error management needs to be investigated.