Modelling the photooxidation of ULP,E5 and E10 in the CSIRO smog chamber

The photooxidation of fuel vapour was investigated in a smog chamber and simulated using three chemical mechanisms, the Master Chemical Mechanism (MCMv3.1), SAPRC-99 and the Carbon Bond chemical mechanism (CB05). Three varieties of fuel were used, unleaded petrol (ULP) and two ULP-ethanol blends which contained 5% and 10% ethanol (E5, E10). The fuel vapours were introduced into the chamber using two methods, by injecting the vapours from wholly evaporated fuel directly, and by injecting the headspace vapour from fuel equilibrated at 38 °C. The chamber experiments were simulated using the selected mechanisms and comparisons made with collected experimental data.The SAPRC-99 mechanism reproduced Δ(O₃–NO) more accurately for almost all fuel types and injection modes, with negligible model error for both injection modes. The average model error for MCM simulations was ?16% and for CB05 the average model error was ?34%. The predictions for the CB05 mechanism varied depending on injection mode, the Δ(O₃–NO) model error for wholly evaporated experiments was ?44%, compared to ?24% for headspace vapour experiments. The difference in aromatic content between experiments of different injection modes was likely to be the cause of the difference in model error for CB05. The model error for all headspace experiments was dependent upon the initial carbon monoxide concentrations.The results for Δ(O₃–NO) were matched by the prediction of other key products, with formaldehyde predicted to within 20% by both SAPRC and the MCM. The addition of ethanol to the base SAPRC mechanism altered the predictions of Δ(O₃–NO) by less than 2%. Changes observed in the concentrations of formaldehyde and acetaldehyde were consistent with the expected yields from ethanol oxidation.     

Evaluation of artificial neural networks for fine particulate pollution (PM10 and PM2.5) forecasting

Multi-layer perceptron (MLP) artificial neural network (ANN) models are compared with traditional multiple regression (MLR) models for daily maximum and average O3 and particulate matter (PM10 and PM2.5) forecasting. MLP particulate forecasting models show little if any improvement over MLR models and exhibit less skill than do O3 forecasting models. Meteorological variables (precipitation, wind, and temperature), persistence, and co-pollutant data are shown to be useful PM predictors. If MLP approaches are adopted for PM forecasting, training methods that improve extreme value prediction are recommended.     

Implications of research on endocrine disruption for the environmental risk assessment, regulation and monitoring of chemicals in the European Union

We assess the implications which research on endocrine disrupting chemicals (EDCs) has for the regulation of synthetic substances and for the protection of the environment, particularly under the forthcoming European Union (EU) REACH legislation. EDCs present regulatory problems inter alia because they can act additively at concentrations which are individually harmless, and they may have non-classical dose (concentration)-response relationships at low exposure levels. Furthermore, current in vivo testing routines were not specifically designed to assess the endocrine disrupting properties of chemicals, whilst in silico and in vitro methods have only limited applicability and availability for this purpose. We need to ensure that the assessment approaches specified in the draft REACH legislation and Technical Guidance are able to evaluate EDCs efficiently. However, it must also be recognised that environmental monitoring procedures in Europe will need to be improved to detect EDCs that have evaded identification, and where appropriate, control, under REACH.     

Effects of temperature on mineralisation of petroleum in contaminated Antarctic terrestrial sediments

Although petroleum contamination has been identified at many Antarctic research stations, and is recognized as posing a significant threat to the Antarctic environment, full-scale in situ remediation has not yet been used in Antarctica. This is partly because it has been assumed that temperatures are too low for effective biodegradation. To test this, the effects of temperature on the hydrocarbon mineralisation rate in Antarctic terrestrial sediments were quantified. 14C-labelled octadecane was added to nutrient amended microcosms that were incubated over a range of temperatures between -2 and 42 degrees C. We found a positive correlation between temperature and mineralisation rate, with the fastest rates occurring in samples incubated at the highest temperatures. At temperatures below or near the freezing point of water there was a virtual absence of mineralisation. High temperatures (37 and 42 degrees C) and the temperatures just above the freezing point of water (4 degrees C) showed an initial mineralisation lag period, then a sharp increase in the mineralisation rate before a protracted plateau phase. Mineralisation at temperatures between 10 and 28 degrees C had no initial lag phase. The high rate of mineralisation at 37 and 42 degrees C was surprising, as most continental Antarctic microorganisms described thus far have an optimal temperature for growth of between 20 and 30 degrees C and a maximal growth temperature <37 degrees C. The main implications for bioremediation in Antarctica from this study are that a high-temperature treatment would yield the most rapid biodegradation of the contaminant. However, in situ biodegradation using nutrients and other amendments is still possible at soil temperatures that occur naturally in summer at the Antarctic site we studies (Casey Station 66 degrees 17(') S, 110 degrees 32(') E), although treatment times could be excessively long.     

Semen quality as a potential susceptibility indicator to SARS-CoV-2 insults in polluted areas

Environmental Science and Pollution Research - The epidemic of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has impacted worldwide with its infectious spread and mortality...     

The Cl-initiated oxidation of CH3C(O)OCH=CH2, CH3C(O)OCH2CH=CH2, and CH2=CHC(O)O(CH2)3CH3 in the troposphere

Background, aim, and scope  

Unsaturated esters are emitted to the atmosphere from biogenic and anthropogenic sources, including those from the polymer industry. Little information exists concerning the atmospheric degradation of unsaturated esters, which are mainly initiated by OH radicals. Limited information is available on the degradation of alkenes by Cl atoms and almost no data exists for the reactions of unsaturated esters with Cl atoms. This data is necessary to assess the impact of such reactions in maritime environments where, under circumstances, OH radical- and Cl atom-initiated oxidation of the compounds can be important. Rate coefficients for the reactions of chlorine atoms with vinyl acetate, allyl acetate, and n-butyl acrylate have been determined at 298 ± 3 K and atmospheric pressure. The kinetic data have been used in combination with that for structurally similar compounds to infer the kinetic contributions from the possible reaction channels to the overall reaction rate.     

Test of a behavior-based individual-based model: response of shorebird mortality to habitat loss.

In behavior-based individual-based models (IBMs), demographic functions are emergent properties of the model and are not built into the model structure itself, as is the case with the more widely used demography-based IBMs. Our behavior-based IBM represents the physiology and behavioral decision making of individual animals and, from that, predicts how many survive the winter nonbreeding season, an important component of fitness. This paper provides the first test of such a model by predicting the change in winter mortality of a charadriid shorebird following removal of intertidal feeding habitat, the main effect of which was to increase bird density. After adjusting one calibration parameter to the level required to replicate the observed mortality rate before habitat loss, the model predicted that mortality would increase by 3.65%, which compares well with the observed increase of 3.17%. The implication that mortality was density-dependent was confirmed by predicting mortality over a range of bird densities. Further simulations showed that the density dependence was due to an increase in both interference and depletion competition as bird density increased. Other simulations suggested that an additional area of mudflat, equivalent to only 10% of the area that had been lost, would be needed by way of mitigation to return mortality to its original level. Being situated at a high shore level with the flow of water in and out impeded by inlet pipes, the mitigating mudflat would be accessible to birds when all mudflats in the estuary were covered at high tide, thus providing the birds with extra feeding time and not just a small replacement mudflat. Apart from providing the first, and confidence-raising, test of a behavior-based IBM, the results suggest (1) that the chosen calibration procedure was effective; (2) that where no new fieldwork is required, and despite being parameter rich, a behavior-based IBM can be parameterized quickly (few weeks), and thus cheaply, because so many of the parameter values can be obtained from the literature and are embedded in the model; and (3) that behavior-based IBMs can be used to explore system behavior (e.g., the role of depletion competition and interference competition in density-dependent mortality).     

Functional traits and the growth-mortality trade-off in tropical trees

A trade-off between growth and mortality rates characterizes tree species in closed canopy forests. This trade-off is maintained by inherent differences among species and spatial variation in light availability caused by canopy-opening disturbances. We evaluated conditions under which the trade-off is expressed and relationships with four key functional traits for 103 tree species from Barro Colorado Island, Panama. The trade-off is strongest for saplings for growth rates of the fastest growing individuals and mortality rates of the slowest growing individuals (r2 = 0.69), intermediate for saplings for average growth rates and overall mortality rates (r2 = 0.46), and much weaker for large trees (r2 < or = 0.10). This parallels likely levels of spatial variation in light availability, which is greatest for fast- vs. slow-growing saplings and least for large trees with foliage in the forest canopy. Inherent attributes of species contributing to the trade-off include abilities to disperse, acquire resources, grow rapidly, and tolerate shade and other stresses. There is growing interest in the possibility that functional traits might provide insight into such ecological differences and a growing consensus that seed mass (SM), leaf mass per area (LMA), wood density (WD), and maximum height (H(max)) are key traits among forest trees. Seed mass, LMA, WD, and H(max) are predicted to be small for light-demanding species with rapid growth and mortality and large for shade-tolerant species with slow growth and mortality. Six of these trait-demographic rate predictions were realized for saplings; however, with the exception of WD, the relationships were weak (r2 < 0.1 for three and r2 < 0.2 for five of the six remaining relationships). The four traits together explained 43-44% of interspecific variation in species positions on the growth-mortality trade-off; however, WD alone accounted for > 80% of the explained variation and, after WD was included, LMA and H(max) made insignificant contributions. Virtually the full range of values of SM, LMA, and H(max) occurred at all positions on the growth-mortality trade-off. Although WD provides a promising start, a successful trait-based ecology of tropical forest trees will require consideration of additional traits.