Risk assessment for Puccinia psidii becoming established in South Africa

Puccinia psidii, the causal agent of myrtle rust, was first recorded from Latin America more than 100 years ago. It occurs on many native species of Myrtaceae in Latin America and also infects non-native plantation-grown Eucalyptus species in the region. The pathogen has gradually spread to new areas including Australia and most recently South Africa. The aim of this study was to consider the susceptibility of selected Eucalyptus genotypes, particularly those of interest to South African forestry, to infection by P. psidii. In addition, risk maps were compiled based on suitable climatic conditions and the occurrence of potential susceptible tree species. This made it possible to identify the season when P. psidii would be most likely to infect and to define the geographic areas where the rust disease would be most likely to establish in South Africa. As expected, variation in susceptibility was observed between eucalypt genotypes tested. Importantly, species commonly planted in South Africa show good potential for yielding disease-tolerant material for future planting. Myrtle rust is predicted to be more common in spring and summer. Coastal areas, as well as areas in South Africa with subtropical climates, are more conducive to outbreaks of the pathogen.

Bioavailability and toxicity of chemicals in inland waters : the importance of prevailing water chemistry and implications for risk assessment

Physicochemical characterization of freshwater samples from Finland, Sweden, the Netherlands, and Spain revealed that water hardness and pH decreased and the quantity and quality of humic substances changed considerably in this geographical series from south to north. Since the ambient water chemistry may affect the availability of chemicals, the total aqueous concentration of a chemical may be insufficient to predict the bioconcentration, subsequent biological response, and thus risk. In addition, organisms could be affected directly by water quality characteristics. In this context the main objective of this thesis was to investigate the bioavailability of selected ecotoxicologically relevant chemicals (cadmium, benzo(a)pyrene, and pyrene) in various European surface waters and to show the importance of certain water chemistry characteristics in interpreting the bioavailability and toxicity results. The bioavailability of cadmium to Daphnia magna was examined in very soft humic lake water. Humic substances as natural ligands decreased the free and bioavailable proportion of cadmium in soft lake water. As a consequence the uptake rate and the acute toxicity decreased compared with the humic-free reference. When the hardness of humic lake water was artificially elevated, the acute toxicity of cadmium decreased, although the proportion of free cadmium increased. The decreased bioavailability of cadmium in hard water was a result of effective competition for uptake by the hardness cations, especially calcium ions. The protective role of humic substances and water hardness against cadmium toxicity was also observed in Lumbriculus variegatus, although D. magna was more sensitive to cadmium. The bioavailability of two polycyclic aromatic hydrocarbons (PAHs), pyrene and benzo(a)pyrene, was studied in European surface waters of varying water chemistry. Humic substances acted as complexing ligands with both PAHs, but the bioavailability of the more lipophilic benzo(a)pyrene to D. magna was affected more by humic substances than that of pyrene. In addition, not only the quantity of humic substances, but also their quality affected the bioavailability of benzo(a)pyrene. Nevertheless, the humic substances played a protective role in the photo-enhanced toxicity of pyrene under UV-B radiation. Water hardness had no effect on pyrene toxicity. Results indicate that the typical physicochemical characteristics of boreal freshwaters should be considered carefully in local and regional risk assessment of chemicals concerning the Fennoscandian region.

Risk assessment for airborne infectious diseases between natural ventilation and split-system air conditioner in a university classroom

Indoor air quality is a critical factor in the classroom due to high people concentration in a unique space. Indoor air pollutant might increase the chance of both long and short-term health problems among students and staff, reduce the productivity of teachers and degrade the student’s learning environment and comfort. Adequate air distribution strategies may reduce risk of infection in classroom. So, the purpose of air distribution systems in a classroom is not only to maximize conditions for thermal comfort, but also to remove indoor contaminants. Natural ventilation has the potential to play a significant role in achieving improvements in IAQ. The present study compares the risk of airborne infection between Natural Ventilation (opening windows and doors) and a Split-System Air Conditioner in a university classroom. The Wells-Riley model was used to predict the risk of indoor airborne transmission of infectious diseases such as influenza, measles and tuberculosis. For each case, the air exchange rate was measured using a CO2 tracer gas technique. It was found that opening windows and doors provided an air exchange rate of 2.3 air changes/hour (ACH), while with the Split System it was 0.6 ACH. The risk of airborne infection ranged between 4.24 to 30.86 % when using the Natural Ventilation and between 8.99 to 43.19% when using the Split System. The difference of airborne infection risk between the Split System and the Natural Ventilation ranged from 47 to 56%. Opening windows and doors maximize Natural Ventilation so that the risk of airborne contagion is much lower than with Split System.

Human health risk assessment of heavy metals in urban stormwater

Toxic chemical pollutants such as heavy metals (HMs) are commonly present in urban stormwater. These pollutants can pose a significant risk to human health and hence a significant barrier for urban stormwater reuse. The primary aim of this study was to develop an approach for quantitatively assessing the risk to human health due to the presence of HMs in stormwater. This approach will lead to informed decision making in relation to risk management of urban stormwater reuse, enabling efficient implementation of appropriate treatment strategies. In this study, risks to human health from heavy metals were assessed as hazard index (HI) and quantified as a function of traffic and land use related parameters. Traffic and land use are the primary factors influencing heavy metal loads in the urban environment. The risks posed by heavy metals associated with total solids and fine solids (<150µm) were considered to represent the maximum and minimum risk levels, respectively. The study outcomes confirmed that Cr, Mn and Pb pose the highest risks, although these elements are generally present in low concentrations. The study also found that even though the presence of a single heavy metal does not pose a significant risk, the presence of multiple heavy metals could be detrimental to human health. These findings suggest that stormwater guidelines should consider the combined risk from multiple heavy metals rather than the threshold concentration of an individual species. Furthermore, it was found that risk to human health from heavy metals in stormwater is significantly influenced by traffic volume and the risk associated with stormwater from industrial areas is generally higher than that from commercial and residential areas.

An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions

This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.