Using carcinogenic potency ranking to assign air contaminants to emission classes

[Indoor air guide values for 2-butanone oxime. Communication from the Ad-hoc Working Group on Indoor Guide Values of the Indoor Air Hygiene Commission and the States' Supreme Health Authorities]

The German Working Group on Indoor Guidelines of the Indoor Air Hygiene Committee and of the Supreme State Health Authorities is issuing indoor air guide values to protect public health. No reliable human studies are available for health evaluation of 2-butanone oxime in indoor air. In a well documented chronic inhalation animal study with rats and mice assessed as reliable, degenerative changes in the olfactory epithelium were observed, which led to a dose related increased incidence and severity, especially in mice. Using a benchmark approach the Working Group assessed a BMD10 of 13.8 mg 2-butanone oxime/m(3) for continuous exposure for the endpoint degeneration of the olfactory epithelium. For interspecies differences a reduced factor of 1 was applied due to the same susceptibility of rodents than human for this endpoint. By applying a factor of 10 for interindividual variability, and a factor of 2 to account for the higher respiratory rate of children compared to adults, a health hazard guide value (RW II) of 0.06 mg 2-butanone oxime/m(3) indoor air is obtained. A precautionary guide value of 0.02 mg 2-butanone oxime/m(3) indoor air is recommended.

A scale of risk

This article proposes a conceptual framework for ranking the relative gravity of diverse risks. This framework identifies the moral considerations that should inform the evaluation and comparison of diverse risks. A common definition of risk includes two dimensions: the probability of occurrence and the associated consequences of a set of hazardous scenarios. This article first expands this definition to include a third dimension: the source of a risk. The source of a risk refers to the agents involved in the creation or maintenance of a risk and captures a central moral concern about risks. Then, a scale of risk is proposed to categorize risks along a multidimensional ranking, based on a comparative evaluation of the consequences, probability, and source of a given risk. A risk is ranked higher on the scale the larger the consequences, the greater the probability, and the more morally culpable the source. The information from the proposed comparative evaluation of risks can inform the selection of priorities for risk mitigation.

New methodology for hazardous waste classification using fuzzy set theory Part I. Knowledge acquisition

In the literature on hazardous waste classification, the criteria used are mostly based on physical properties, such as quantity (weight), form (solids, liquid, aqueous or gaseous), the type of processes generating them, or a set of predefined lists. Such classification criteria are inherently inadequate to account for the influence of toxic and hazard characteristics of the constituent chemicals in the wastes, as well as their exposure potency in multimedia environments, terrestrial mammals and other biota. Second, none of these algorithms in the literature has explicitly presented waste classification by examining the contribution of individual constituent components of the composite wastes. In this two-part paper, we propose a new automated algorithm for waste classification that takes into account physicochemical and toxicity effects of the constituent chemicals to humans and ecosystems, in addition, to the exposure potency and waste quantity. In part I, available data on the physicochemical and toxicity properties of individual chemicals in humans and ecosystems, their exposure potency in environmental systems and the effect of waste quantity are described, because they fundamentally contribute to the final waste ranking. Knowledge acquisition in this study was accomplished through the extensive review of published and specialized literature to establish facts necessary for the development of fuzzy rule-bases. Owing to the uncertainty and imprecision of various forms of data (both quantitative and qualitative) essential for waste classification, and the complexity resulting from knowledge incompleteness, the use of fuzzy set theory for the aggregation and computation of waste classification ranking index is proposed. A computer-aided intelligent decision tool is described in part II of this paper and the functionality of the fuzzy waste classification algorithm is illustrated through nine worked examples.