GOAL, SCOPE, AND BACKGROUND: Diesel exhaust is believed to consist of thousands of organic constituents and is a major cause of urban pollution. We recently reported that a systematic separation procedure involving successive solvent extractions, followed by repeated column chromatography, resulted in the isolation of vasodilatory active nitrophenols. These findings indicated that the estimation of the amount of nitrophenols in the environment is important to evaluate their effect on human health. The isolation procedure, however, involved successive solvent extractions followed by tedious, repeated chromatography, resulting in poor fractionation and in a significant loss of accuracy and reliability. Therefore, it was crucial to develop an alternative, efficient, and reliable analytical method. Here, we describe a facile and efficient acid-base extraction procedure for the analysis of nitrophenols. MATERIALS AND METHODS: Diesel exhaust particles (DEP) were collected from the exhaust of a 4JB1-type engine (ISUZU Automobile Co., Tokyo, Japan). Gas chromatography-mass spectrometry (GC-MS) analysis was performed with a GCMS-QP2010 instrument (Shimadzu, Kyoto, Japan). RESULTS: A solution of DEP in 1-butanol was extracted with aqueous NaOH to afford a nitrophenol-rich oily extract. The resulting oil was methylated with trimethylsilyldiazomethane and subsequently subjected to GC-MS analysis, revealing that 4-nitrophenol, 3-methyl-4-nitrophenol, 2-methyl-4-nitrophenol, and 4-nitro-3-phenylphenol were present in significantly higher concentrations than those reported previously. DISCUSSION: Simple acid-base extraction followed by the direct analysis of the resulting extract by GC-MS gave only broad peaks of nitrophenols with a poor detection limit, while the GC-MS analysis of the sample pretreated with (trimethylsilyl)diazomethane gave satisfactorily clear chromatograms with sharp peaks and with a significantly lowered detection limit (0.5 ng/ml, approximately 100 times). CONCLUSION: The present method involving an acid-base extraction, in situ derivatization, and GC-MS analysis has shown to be a simple, efficient, and reliable method for the isolation and identification of the chemical substances in DEP. 相似文献
Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method, identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.
