Week #3 Progress

More data analysis is happening this week. This time I derived quantitative information from our data set, i.e. I tried to figure out exactly how much organic and inorganic species exists in each sample. A quick way to do so is to perform integration on the high-resolution time series plot for the sample set. Let me take the following time series plot for CALE sample set as an example. Notice that the green trace represents the amount of organics detected by the mass spectrometer at that time. If we integrate through the time series for one injection, i.e. calculate the area under one peak, we are able to obtain the number for the amount of organics (Org) present in that one injection of sample. A program file was written for Igor to perform the calculation.

hr_t_series

Still, it’s not sufficient for us to derive the accurate concentration of organics in each sample, since there was always unknown amount of organic mass lost during each injection. Notice the traces represent HI and I. The iodine species were not present in the original sample, but were added into the sample for calibration and quantification purpose. Such species are called internal standards by analytical chemists. We know the exact concentration of internal standards ([IS], in this case [I] + [HI]) we put into each sample. Through integration step, we can also know the amount of internal standards (IS), and moreover, the ratio of amount of organics over internal standards in each sample injection ([Org]/[IS]). In this way, we can calculate the concentration of organics in each sample through a simple multiplication ([Org] = [Org]/[IS] * [IS]).

quant.

Those numbers can give us some rough estimation of the concentration of organic aerosols in urban air, though we need more information considering the sampling procedure to calculate the exact number. One of my focus for the following week would be explore the original field data of the samples and try to have a better understanding of the aerosol concentration.

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