Search

Municipal solid (MSW) waste composting may have negative effects on the public health. Researches have discovered that MSW produce air emissions of volatile organic compounds (VOCs) whose commercial kinds include components such as paints and coatings, aerosols, cosmetics and cleaning agents. Sufficient exposure to these VOCs may lead to health risks. In a related development, the US EPA's Total Exposure Assessment Methodolody reports that US residents usually are exposed to VOCs. In addition, indoor concentrations of VOCs are higher because of the VOCs in commercial prodcts used and stored in side homes.

Abstract: Implementation of probabilistic analyses in exposure assessment can provide valuable insight into the risks of those at the extremes of population distributions, including more vulnerable or sensitive subgroups. Incorporation of these analyses into current regulatory methods for occupational pesticide exposure is enabled by the exposure data sets and associated data currently used in the risk assessment approach of the Environmental Protection Agency (EPA). Monte Carlo simulations were performed on exposure measurements from the Agricultural Handler Exposure Database and the Pesticide Handler Exposure Database along with data from the Exposure Factors Handbook and other sources to calculate exposure rates for three different neurotoxic compounds (azinphos methyl, acetamiprid, emamectin benzoate) across four pesticide‐handling scenarios. Probabilistic estimates of doses were compared with the no observable effect levels used in the EPA occupational risk assessments. Some percentage of workers were predicted to exceed the level of concern for all three compounds: 54% for azinphos methyl, 5% for acetamiprid, and 20% for emamectin benzoate. This finding has implications for pesticide risk assessment and offers an alternative procedure that may be more protective of those at the extremes of exposure than the current approach. [ABSTRACT FROM AUTHOR]

The application of quantitative microbial risk assessments (QMRAs) to understand and mitigate risks associated with norovirus is increasingly common as there is a high frequency of outbreaks worldwide. A key component of QMRA is the dose-response analysis, which is the mathematical characterization of the association between dose and outcome. For Norovirus, multiple dose-response models are available that assume either a disaggregated or an aggregated intake dose. This work reviewed the dose-response models currently used in QMRA, and compared predicted risks from waterborne exposures (recreational and drinking) using all available dose-response models. The results found that the majority of published QMRAs of norovirus use the 1 F1 hypergeometric dose-response model with α = 0.04, β = 0.055. This dose-response model predicted relatively high risk estimates compared to other dose-response models for doses in the range of 1-1,000 genomic equivalent copies. The difference in predicted risk among dose-response models was largest for small doses, which has implications for drinking water QMRAs where the concentration of norovirus is low. Based on the review, a set of best practices was proposed to encourage the careful consideration and reporting of important assumptions in the selection and use of dose-response models in QMRA of norovirus. Finally, in the absence of one best norovirus dose-response model, multiple models should be used to provide a range of predicted outcomes for probability of infection. [ABSTRACT FROM AUTHOR]