Toxicity of methyl tert-butyl ether to marine organisms: ambient water quality criteria calculation

In response to increasing concerns over the detection of methyl tert-butyl ether (MTBE) in groundwater and surface water and its potential effects in aquatic ecosystems, industry and the United States Environmental Protection Agency (USEPA) began to collaborate in 1997 to develop aquatic toxicity databases sufficient to derive ambient water quality criteria for MTBE consistent with USEPA requirements. Acute toxicity data for seven marine species, chronic toxicity data for an invertebrate, and plant toxicity data were developed to complete the saltwater database. The species tested were Cyprinodon variegatus, Gasterosteus aculeatus, Callinectes sapidus, Mytilus galloprovincialis, Palaemonetes pugio, Rhepoxynius abronius, Americamysis bahia, and Skeletonema costatum. The toxicity tests were conducted in accordance with USEPA and American Society for Testing and Materials testing procedures and Good Laboratory Practice guidelines. Data developed from this study were consistent with existing data and showed that MTBE has low acute and chronic toxicity to the marine species tested. Based upon measured MTBE concentrations, acute effects were found to range from 166 mg MTBE/l for the grass shrimp to 1950 mg MTBE/l for marine mussel. The no-observed effect concentration for the reproduction and growth of mysids was 26 mg MTBE/l during the life cycle test. The toxicity of MTBE to saltwater organisms is comparable to its toxicity to the freshwater species tested. Reported MTBE concentrations in coastal waters are several orders of magnitude lower than concentrations observed to cause effects in marine organisms.     

A study on the behaviour of pesticides and their transformation products in the Scheldt estuary using liquid chromatography-electrospray tandem mass spectrometry

Off-line solid-phase extraction (SPE) combined with liquid chromatography-electrospray tandem mass spectrometry (LC-ESI-MS-MS) was used to study the estuarine behaviour of the polar pesticides, atrazine, chloridazon, diuron and metolachlor, and their transformation products (TPs), hydroxyatrazine (HA), desisopropylatrazine (DIA), desethylatrazine (DEA), 3,4-dichlorophenylmethylurea (DPMU) and monuron. The compounds were identified by comparing their LC retention times and product-ion spectra with those of standard solutions. In all but one case the detection limits of the method were sufficient to determine the compounds of interest over the entire salinity range in the estuary. The concentrations of the dissolved pesticides ranged from 70 ng l-1 for chloridazon to 1350 ng l-1 for diuron. The levels of TPs were 3-8% of the levels of their parent pesticide. The mixing plots of polar pesticides and their TPs indicated that TPs, which are present in fresh river water, are conservatively transported to the sea and that no additional amounts of TPs are formed during their transport through the estuary. The one exception was HA, of which approximately 10% of the amount transported to the North Sea is formed in the lower part of the estuary by photochemical oxidation of atrazine. The latter was concluded from the ratios of each analyte over the sum total of the parent pesticide and all TPs along the salinity gradient, which proved to be a useful tool for identifying such estuarine transformations.     

The city as a refuge for insect pollinators

Research on urban insect pollinators is changing views on the biological value and ecological importance of cities. The abundance and diversity of native bee species in urban landscapes that are absent in nearby rural lands evidence the biological value and ecological importance of cities and have implications for biodiversity conservation. Lagging behind this revised image of the city are urban conservation programs that historically have invested in education and outreach rather than programs designed to achieve high‐priority species conservation results. We synthesized research on urban bee species diversity and abundance to determine how urban conservation could be repositioned to better align with new views on the ecological importance of urban landscapes. Due to insect pollinators’ relatively small functional requirements—habitat range, life cycle, and nesting behavior—relative to larger mammals, we argue that pollinators put high‐priority and high‐impact urban conservation within reach. In a rapidly urbanizing world, transforming how environmental managers view the city can improve citizen engagement and contribute to the development of more sustainable urbanization.     

A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

Working Life Across Cultures: “Work Life 2000: Quality in Work” and Occupational Health Education in Developing Countries

The article reflects on the changing world of work, and the challenges presented to both occupational health and occupational health education. We draw on the 63 preparatory workshops and the international conference in the “Work Life 2000: Quality in Work” program, an initiative of the Swedish Presidency of the European Union. The International Commission on Occupational Health is introduced, with particular concentration on a current practical project initiated by the Department of Health in South Africa, intended to lead to a set of projects, networking for occupational health education in developing countries. The practical initiatives cast light on a new set of issues that arise when occupational health and safety crosses cultural barriers, and previously separate comparative cases are linked.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

Modelling Change in Ground Vegetation Response to Acid and Nitrogen Pollution, Climate Change and Forest Management at in Sweden 1500–2100 a.d.

The ForSAFE model, designed for modelling biogeochemical cycles (water, acidity, base cation, nitrogen and carbon) in terrestrial ecosystems, was modified with a vegetation response module (VEG), incorporating the effects of: nitrogen pollution, acidification, soil moisture, temperature, wind chill exposure, light and shading by trees, grazing by animals, competition between plants, above ground for light and below ground for water and nutrients. The model calculates the response of number ground vegetation plant groups. The integrated model was tested and validated at integrated level II forest monitoring sites across Sweden, four have been shown here, and used to assess the effect of acidification and nitrogen pollution in relation to factors such as climate change, forest management and changing grazing pressure. The response functions have been derived from single-factor experiments and integrated through the model structure for use on whole systems. The tests with the model suggest that the ground vegetation composition is reasonably well predicted, that much research remains before the model is fully tested and operational, and that the model may serve as a tool for assessing impacts of climate change, acid rain and forest management on plant biodiversity in forested areas.