Environmental and Biological Assessment of Exposure to Benzene in Petroleum Workers

Occupational exposure to benzene was measured in two gasoline marketing terminals and five major refineries in Singapore. A total of 280 workers were monitored over two years. This assessment was carried out with two primary objectives: (1) To find out the extent of occupational exposure to benzene in the petroleum industry in Singapore, (2) To identify suitable biomarkers for monitoring of low levels of benzene exposure. The exposure was measured in five different categories of petroleum and petrochemical workers, i.e., truck drivers, despatch assistant, process operators, oil movements operators and laboratory technicians. The results revealed wide variations in exposure, from 0.01 to 13.6 ppm for personal time weighted average (TWA) exposure over the whole workshift. The exposure of truck drivers appeared to be the highest, with geometric mean (GM) of 1.98 ppm (ranged from 0.25 to 13.6 ppm). The average benzene exposure for process operators was relative low with a GM of 0.04 ppm. Lowest benzene exposure was found in the laboratory technicians, with a GM of 0.02 ppm. As cigarette smoking is known to affect metabolism of benzene, data analyses on the relationships with environmental exposure were conducted only on the 190 nonsmokers. The results showed that urinary trans, trans-muconic acid (ttMA), unmetabolized benzene in urine (UBZ) and benzene in blood (BBZ) were better biomarkers for low level benzene exposure as compared to urinary phenolic metabolites in urine, such as hydroquinone, phenol and catechol.     

An Overview of Data Integration Methods for Regional Assessment

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.