Distillated kerosene may get contaminated with trace metals from different sources, such as from the crude oil itself, transporting pipes, and storage tanks. If these contaminants are not removed or deactivated, they will not only have a negative impact on the combustion properties, but also oxidize and contribute to the formation of filter clogging gums. At elevated temperatures, trace metals can corrode the turbine and produce deposits on the turbine components. Routine monitoring of kerosene fuels is therefore essential for high quality fuel production.
Kerosene Analysis for Trace Metals
Analyzing kerosene by ICP-OES after ASTM D7111
Kerosene, distillate oil, and gas oils containing approximately 6 to 18 carbon atoms are liquid. They are produced in the middle of fractional distillation and are called middle distillates, compared to lighter distillates (i.e., naphtha) and heavier distillates (i.e., lubricating oils). Middle distillate fuels are used for jet fuels, household, and other applications. This page provides information about the analysis of kerosene by ICP-OES after ASTM D7111.
Why analysis of kerosene for trace metals is important
ASTM D7111: Analysis of kerosene using ICP-OES
ASTM Standard Test Method D7111 can be used to measure trace metal contaminants in kerosene and other middle distillates fuel. Although the method is not developed for the purpose of analyzing samples containing particulates, particulates less than 1µm can be carried to the plasma and included in the quantitation. Because sample introduction transports volatile samples more efficiently than nonvolatile samples, the method also overestimates for the samples that are sufficiently volatile.
To overcome the above problems, use an organic sample introduction kit to minimize the detection inaccuracy. In addition, when performing ICP-OES for any trace elemental analysis, wavelength selection for different analytes to reduce spectral interferences is always a challenge for the operators. Powerful system software that provides fast and intuitive selection of wavelengths and interference corrections simplifies the analysis workload and overcomes analytical bias.
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