A shaking extraction method for petroleum hydrocarbons in soil was developed and compared to Soxhlet extraction. Soxhlet extraction is an EPA-approved method for volatile and semivolatile organic contaminants from solid materials, but it has many disadvantages including long extraction periods and potential loss of volatile compounds. When field-moist soils are used, variability in subsamples is higher, and the extraction of hydrocarbons with a nonpolar solvent may be less efficient. A shaking method was designed to fill the need for simpler and more efficient extraction of petroleum hydrocarbons from soil. A systematic study of extraction conditions was performed for various soil types, soil weights, solvents, extraction times, and extraction cycles. The results were compared to those for Soxhlet extraction. Shaking 1 g of soil with a sequence of three 10-mL aliquots of dichloromethane or acetone was found to be equivalent to Soxhlet extraction for total petroleum hydrocarbons and polycyclic aromatic hydrocarbons. Shaking with acetone was more consistent than all other methods for the extraction of specific compounds from aged, contaminated soil. The shaking method appears to be applicable to a wide range of soil types and petroleum contaminants but should be compared to Soxhlet extraction for new conditions.

Abstract. We demonstrate both analytically and numerically that the existing methods for measuring tail dependence in copulas may sometimes underestimate the extent of extreme co-movements of dependent risks and, therefore, may not always comply with the new paradigm of prudent risk management. This phenomenon holds in the context of both symmetric and asymmetric copulas with and without singularities. As a remedy, we

Mathematics and Economics 46(2), 308 -316], the structure in this paper is absolutely continuous with respect to the corresponding Lebesgue measure. The distribution is of importance to actuaries through its connections to the popular frailty models, as well as because of the capacity to describe dependent heavy-tailed risks. The genesis of the new distribution is linked to a number of existing probability models, and useful characteristic results are proved. Expressions for, e.g., the decumulative distribution and probability density functions, (joint) moments and regressions are developed.The distributions of minima and maxima, as well as, some weighted risk measures are employed to exemplify possible applications of the distribution in insurance.

No abstract

No abstract

Abstract. Tail dependence refers to clustering of extreme events. In the context of financial risk management, the clustering of high-severity risks has a devastating effect on the well-being of firms and is thus of pivotal importance in risk analysis.

No abstract

No abstract