Human Exposure to Malathion during a Possible Vector-Control Intervention against West Nile Virus. I: Methodological Framework for Exposure Assessment

The arrival of West Nile Virus in North America prompted public health authorities to develop intervention plans in order to prevent the propagation of this mosquito-transmitted pathogen. The last-resort measure proposed by the Government of Quebec (Canada) is the large-scale application of insecticides by aerial or ground Ultra Low Volume (ULV) treatment. This article presents an assessment of the exposure to malathion and its metabolite, malaoxon, for a population where an eventual application of malathion would occur. Each exposure pathway is detailed by describing the equation and every conservative assumption. This methodological framework was then used with the aim of assessing the toxicological risk based on a probabilistic approach (see companion article, this issue). In the current study, a daily absorbed dose of the mixture of malathion and malaoxon was estimated in terms of “malathion equivalent dose.” Each exposure pathway following a single event of ground or aerial ULV spraying of malathion was investigated for the population, classified into five age groups. Dermal exposure to dislodgeable residues on turf, foliage, and hard surfaces was estimated to be the most important source of exposure compared to any other pathways; it accounts for 63% to 98% of the estimated cumulative absorbed doses. The hand-to-mouth behavior of toddlers may also contribute considerably to their “malathion-equivalent” exposure (i.e., approximately 15% of the cumulative dose). Otherwise, the current study shows that ground ULV spraying is the type of treatment that may induce lower exposure, because the predicted concentration of malathion on turf and foliar surfaces is less than the one predicted for aerial ULV spraying.     

Analysis and Portrayal of Uncertainty in a Food-Web Exposure Model

The results of quantitative risk assessments are key factors in a risk manager's decision of the necessity to implement actions to reduce risk. The extent of the uncertainty in the assessment will play a large part in the degree of confidence a risk manager has in the reported significance and probability of a given risk. The two main sources of uncertainty in such risk assessments are variability and incertitude. In this paper we use two methods, a second-order two-dimensional Monte Carlo analysis and probability bounds analysis, to investigate the impact of both types of uncertainty on the results of a food-web exposure model. We demonstrate how the full extent of uncertainty in a risk estimate can be fully portrayed in a way that is useful to risk managers. We show that probability bounds analysis is a useful tool for identifying the parameters that contribute the most to uncertainty in a risk estimate and how it can be used to complement established practices in risk assessment. We conclude by promoting the use of probability analysis in conjunction with Monte Carlo analyses as a method for checking how plausible Monte Carlo results are in the full context of uncertainty.     

Risk assessment of land ecology on a regional scale: Application of the relative risk model to the mining city of Daye,China

The ecological risk assessment of land ecosystems plays a vital role in land environment protection and management in China. To identify the ecological impairment in land ecosystems, risk assessment of regional land ecology was conducted in Daye, a traditional mining city in Central China, using the relative risk model (RRM). The study area was divided into six sub-regions; and the sources, stressors, habitats, and end points of the impairment were identified. A conceptual model was built to represent the ecological interactions among risk components. Results showed the following: (1) The traditional iron–coal mining sub-region and the mineral processing sub-region exhibited high risk. (2) Mining was the largest risk source, followed by solid waste piling and urbanization. (3) Disappearance of habitats was the greatest risk stressor, followed by the accumulation of pollutants and heavy metals. (4) Among the eight identified habitats, the lake habitat was the most likely to be affected. (5) Health threats, soil contamination, and landscape aesthetic dysfunctions appeared to be the end points under the largest risk pressure. Finally, Monte Carlo analysis was used to evaluate the effects of uncertainty on risk model predictions. Our assessment model was proven to be generally valid for regional land ecology risk assessment.