Investigations on the effect of chlorine in lubricating oil and the presence of a diesel oxidation catalyst on PCDD/F releases from an internal combustion engine

This paper reports on an intensive study into releases of polychlorinated dibenzo-p-dioxins (PCDD), polychlorinated furans (PCDF) and polychlorinated biphenyls (PCB) from a diesel engine and the analysis of PCDD/F and PCB in crankcase lubricating oil. Experimental conditions were set and carefully controlled in order to maximize the possible impact of, and our ability to measure the effect of, changes in the levels of chlorine in the lubricant. Emissions to air were measured using modified EPA methods following the principles of the European EN 1948 standards. A series of 40 experimental runs were completed using three reference lubricants formulated to have three levels of chlorine present as a residual component (at levels of 12, 131 and 259 mg kg(-1) or ppm). The engine was run with and without the diesel oxidation catalyst. All lubricants were realistic oils and the use of unrealistic additives or doping of components - particularly chlorine - in the fuel and lubricant was carefully avoided. Analysis of fuel and lubricant (before and after testing) samples required strenuous attention to achieve acceptable recoveries and showed non-detectable levels of PCB and PCDD/F at a detection limit of around 1.5 ng I-TEQ kg(-1) (ppt), indistinguishable from the laboratory blank. The testing demonstrated the need for extreme care to be taken in developing measurement methods that are sufficiently sensitive for measuring chlorine content of fluids and PCDD/F in oils, the latter being particularly challenging. Mean emissions of PCDD/F with the diesel oxidation catalyst in place were 23 pg I-TEQ l(-1) of fuel and with the diesel oxidation catalyst removed 97 pg I-TEQ l(-1) of fuel. The results of this testing showed that the emissions of PCDD/F were greatly reduced by the presence of a diesel oxidation catalyst in the exhaust, a finding that has not been explicitly tested in previous work. They also show that emissions from the engine were not controlled by the level of chlorine in the lubricant and that emissions did not change in response to a much greater step change in the total chlorine entering the combustion chamber due to a change in the level of chlorine in the fuel. Emissions when the engine was configured with a diesel oxidation catalyst showed a consistent pattern that appears to be unique in the experience of the authors.     

Implications of climate change for the stomatal flux of ozone: a case study for winter wheat

Climate change factors such as elevated CO2 concentrations, warming and changes in precipitation affect the stomatal flux of ozone (O3) into leaves directly or indirectly by altering the stomatal conductance, atmospheric O3 concentrations, frequency and extent of pollution episodes and length of the growing season. Results of a case study for winter wheat indicate that in a future climate the exceedance of the flux-based critical level of O3 might be reduced across Europe, even when taking into account an increase in tropospheric background O3 concentration. In contrast, the exceedance of the concentration-based critical level of O3 will increase with the projected increase in tropospheric background O3 concentration. The influence of climate change should be considered when predicting the future effects of O3 on vegetation. There is a clear need for multi-factorial, open-air experiments to provide more realistic information for O3 flux-effect modelling in a future climate.     

Representing uncertainty in climate change scenarios: a Monte-Carlo approach

Climate change impact assessment is subject to a range of uncertainties due to both incomplete and unknowable knowledge. This paper presents an approach to quantifying some of these uncertainties within a probabilistic framework. A hierarchical impact model is developed that addresses uncertainty about future greenhouse gas emissions, the climate sensitivity, and limitations and unpredictability in general circulation models. The hierarchical model is used in Bayesian Monte-Carlo simulations to define posterior probability distributions for changes in seasonal-mean temperature and precipitation over the United Kingdom that are conditional on prior distributions for the model parameters. The application of this approach to an impact model is demonstrated using a hydrological example. This revised version was published online in July 2006 with corrections to the Cover Date.     

Simulation of the migration and transformation of petroleum pollutants in the soils of the Loess plateau: a case study in the Maling oil field of northwestern China

We developed a coupled water–oil simulation model to simulate the migration and transformation of petroleum-derived contaminants in the soil of the Xifeng oil field. To do so, we used the HYDRUS-2D model, which simulates the diffusion, adsorption or desorption, and microbial degradation of petroleum-derived hydrocarbons in the soil–water system. The saturated soil hydraulic conductivity of petroleum-derived pollutants was 0.05 cm?day^?1, which is about 1 to 2 % of the soil moisture permeability coefficient. Our numerical simulation results show that spilled crude oil was mainly concentrated in the surface horizons of the soil. The organic pollutant concentration tended to be highest nearest to the pollution source. The pollutant migration was generally concentrated within the top 20 to 30 cm of the soil, with the maximum concentration in the top 5 cm of the soil. With passing time, the pollutant accumulation increased and the adsorption and degradation functions reached a dynamic balance with the input rate at depths greater than 30 cm below the soil surface. The oil-derived pollutants totaled 50 to 100 mg?kg^?1 under the dynamic balance condition, which occurred after 20 to 30 years. The petroleum-derived pollutant concentration in the loess soil was inversely correlated with the horizontal distance from the oil well, and the concentration decreased greatly at a distance greater than 40 m from the well.     

The response of two ecologically important Antarctic invertebrates (Sterechinus neumayeri and Parborlasia corrugatus) to reduced seawater pH: effects on fertilisation and embryonic development

Ocean acidification, or the lowering of seawater pH, is caused by sequestration of atmospheric CO₂ into the oceans. This study investigated the effects of present-day pH 8.0, predicted ocean surface pH for the years 2100 and 2300 (pH 7.7 and pH 7.3, respectively) and an extreme pH (pH 7.0) on fertilisation and embryogenesis in the Antarctic nemertean worm Parborlasia corrugatus and sea urchin Sterechinus neumayeri. Fertilisation success was not affected by pH in P. corrugatus across a range of sperm concentrations. Fertilisation success in S. neumayeri declined significantly in pH 7.0 and 7.3 seawater, but only at a low sperm concentration. Seawater pH had no effect on the rate of egg cleavage in S. neumayeri, or the proportion of abnormal embryos 1-day post-fertilisation. P. corrugatus embryogenesis was also relatively robust to pH changes, with a significant effect detected only when the seawater pH was decreased to 7.0. While fertilisation and early cell division were relatively robust, later development through to the gastrula was sensitive to pH. In S. neumayeri, an effect of pH on development was evident by the gastrula stage, while there were significantly more abnormal P. corrugatus embryos in pH 7.0 up to the blastula stage, and in pH 7.0 and pH 7.3 at the coeloblastula stage. Our results are similar to the observations on other marine invertebrate species where fertilisation and early embryonic development are generally robust to lowered seawater pH, while the older coeloblastula and gastrula stages are more responsive. We also found no evidence to suggest that Antarctic species are more adversely affected by lower seawater pH compared with the findings for non-Antarctic counterparts. We conclude that in the two species we examined, near-future decreases in pH (decreases of ≈0.3–0.5 pH units) may not have a significant effect on fertilisation and early embryogenesis, while predicted longer term decreases (decreases of ≈0.7–0.77 pH units) could reduce fertilisation success in S. neumayeri if sperm concentrations are low and may increase abnormalities in P. corrugatus during later embryogenesis.     

Mathematical problem definition for ecological restoration planning

Ecological restoration is an increasingly important tool for managing and improving highly degraded or altered environments. Faced with a large number of sites or ecosystems to restore, and a diverse array of restoration approaches, investments in ecological restoration must be prioritized. Nevertheless, there are relatively few examples of the systematic prioritization of restoration actions. The development of a general theory for ecological restoration that is sufficiently sophisticated and robust to account for the inherent complexity of restoration planning, and yet is flexible and adaptable to ensure applicability to a diverse array of restoration problems is needed. In this paper we draw on principles from systematic conservation planning to explicitly formulate the ‘restoration prioritization problem’. We develop a generalized theory for static and dynamic restoration planning problems, and illustrate how the basic problem formulation can be expanded to allow for many factors characteristic of restoration problems, including spatial dependencies, the possibility of restoration failure, and the choice of multiple restoration techniques. We illustrate the applicability of our generic problem definition by applying it to a case study - restoration prioritization on The Irvine Ranch Natural Landmark in Southern California. Through this case study we illustrate how the definition of the general restoration problem can be extended to account for the specific constraints and considerations of an on-the-ground restoration problem.     

Investigating the Uncertainties in the Simple Mass Balance Equation for Acidity Critical Loads for Terrestrial Ecosystems in the United Kingdom

The Simple Mass Balance (SMB)equation has been developed and used as one ofthe principal methods for calculating criticalloads of acidity for forest ecosystems. Criticalloads have formed the basis for informing policyrelated to the control and abatement of emissionsof acidifying pollutants. The SMB equationrelies on a variety of assumptions and dataderived from a variety of sources. Each of thesecomponent constituents has a potential source oferror depending on the method(s) used for theirderivation and the value(s) assigned. The resultis the possibility of generating a range ofcritical load values for a single ecosystem. This paper summarises the SMB equation, examinesthe uncertainties in deriving input values andreviews other works on the key assumptions.     

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Over recent years, technical developments resulting in the feasibility of fetal cardiovascular magnetic resonance (CMR) have provided a new diagnostic tool for studying the human fetal heart and circulation. During the same period, we have witnessed the arrival of several minimally invasive fetal cardiac interventions (FCI) as a possible form of treatment in selected congenital heart diseases (CHDs). The role of fetal CMR in the planning and monitoring of FCI is not yet clear. Indeed, high-quality fetal CMR is not available or routinely offered at most centers caring for patients with prenatally detected CHD. However, in theory, fetal CMR could have much to offer in the setting of FCI by providing complementary anatomic and physiologic information relating to the specific intervention under consideration. Similarly, fetal CMR may be useful as an alternative imaging modality when ultrasound is hampered by technical limitations, for example, in the setting of oligohydramnios and in late gestation. In this review, we summarize current experience of the use of fetal CMR in the diagnosis and monitoring of fetuses with cardiopathies in the setting of a range of invasive in utero cardiac and vascular interventions and medical treatments and speculate about future directions for this versatile imaging medium.     

Flood management: prediction of microbial contamination in large-scale floods in urban environments

With a changing climate and increased urbanisation, the occurrence and the impact of flooding is expected to increase significantly. Floods can bring pathogens into homes and cause lingering damp and microbial growth in buildings, with the level of growth and persistence dependent on the volume and chemical and biological content of the flood water, the properties of the contaminating microbes, and the surrounding environmental conditions, including the restoration time and methods, the heat and moisture transport properties of the envelope design, and the ability of the construction material to sustain the microbial growth. The public health risk will depend on the interaction of these complex processes and the vulnerability and susceptibility of occupants in the affected areas. After the 2007 floods in the UK, the Pitt review noted that there is lack of relevant scientific evidence and consistency with regard to the management and treatment of flooded homes, which not only put the local population at risk but also caused unnecessary delays in the restoration effort. Understanding the drying behaviour of flooded buildings in the UK building stock under different scenarios, and the ability of microbial contaminants to grow, persist, and produce toxins within these buildings can help inform recovery efforts. To contribute to future flood management, this paper proposes the use of building simulations and biological models to predict the risk of microbial contamination in typical UK buildings. We review the state of the art with regard to biological contamination following flooding, relevant building simulation, simulation-linked microbial modelling, and current practical considerations in flood remediation. Using the city of London as an example, a methodology is proposed that uses GIS as a platform to integrate drying models and microbial risk models with the local building stock and flood models. The integrated tool will help local governments, health authorities, insurance companies and residents to better understand, prepare for and manage a large-scale flood in urban environments.