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Abstract: Although regulatory agencies formally encourage the integration of all available data in chemical risk assessment, consistent implementation of this practice has been constrained by the lack of a clear, systematic method for doing so. In this paper, we describe a methodology for evaluating, classifying and integrating human and animal data into the risk assessment process that incorporates: (1) a balanced appraisal of human and animal data, (2) relevance to different stages of the risk assessment process, and (3) accommodation for different data quality requirements. The proposed framework offers a flexible, step-wise approach for determining which set of available data best support the chemical risk assessment that involves the rating and relative ranking of human and animal data quality. The evaluation of human data incorporates seven data quality elements, nature and specificity of the lead effect; evaluation of animal data incorporates data quality and relevance to humans. Results of simulations with selected chemicals previously evaluated in a formal risk assessment generally agreed with existing regulatory guidance. Application of the proposed framework across a wider range of chemical agents will improve transparency of the risk assessment process and validity of results, while informing continuous refinements to this evolving methodology. [Copyright &y& Elsevier]

Abstract: This article presents a summary of benzene exposure levels in the shoemaking industry in China reported in the Chinese medical literature between 1978 and 2004. A comprehensive search identified 182 papers reporting such exposure data. These papers could be classified into two categories: benzene poisoning case reports and industrial hygiene surveys. From each paper, the following information was abstracted whenever available: location and year of occurrence, occupation and/or task involved, benzene content in adhesives/solvents, work environment, working conditions, working hours, diagnosis, and air monitoring data of benzene. A total of 333 benzene measurements (88 averages, 116 minimums, 129 maximums) in the shoemaking industry were reported in the 182 papers identified. The data were analyzed in terms of geographical location, time period, type of ownership (state, township, or foreign), type of report (benzene poisoning reports vs. industrial hygiene surveys), and job title (work activity) or process. The reported data covered a wide range; some measurements were in excess of 4500mg/m3. Thirty-five percent of the reported benzene concentrations were below 40mg/m3, which was the national occupational exposure limit (OEL) for benzene between 1979 and 2001. The remaining 65% measurements, which exceeded the national OEL in effect at the time, and were distributed as follows: 40–100mg/m3, 11%; 100–300mg/m3, 21%; 300–500mg/m3, 13%; and 500+mg/m3, 20%. However, only 24% of the reported measurements after 2002 were below 6mg/m3, i.e., Permissible Concentration-Time Weighted Average (PC-TWA) and 10mg/m3, i.e., Permissible Concentration-Short Term Exposure Limit (PC-STEL), the newly amended benzene OELs in effect after May 2002. The data demonstrated that the majority of the facilities in the shoemaking industry reported in the literature were not in compliance of the OEL for benzene in effect at the time. Overall, the data show a clear downward trend of benzene exposure levels over the years, particularly after the introduction of the new lower OEL in 2002. Even though substantially lower when compared to levels in the past, current benzene exposure measurements from the literature review suggest that many facilities in the shoemaking industry in China have benzene concentrations that are still above the new OEL. The reported data, stratified by job, year and survey reason, can be used as part of the information and analysis for developing a job-exposure matrix in retrospective exposure assessment and thus may be part of the information used in developing historical exposure estimates in epidemiologic studies of shoe workers. [Copyright &y& Elsevier]