Developing a dynamic correction mechanism for aethalometer results of actual urban aerosols

2021 
Abstract The aethalometer (AE) is usually used to monitor light-absorbing aerosols. However, since the AE must first collect particles on a filter tape and then detect the optical changes caused by the filter/particle system, the primary data reported by the AE are not in-situ absorption coefficients (binsitu), but light attenuation coefficients (bATN). The shadow effect, multiple scattering effect, and particle-scattering effect combine to generate artifacts. The intent of the present study was to develop a new correction methodology that could dynamically translate bATN into binsitu. A photoacoustic extinctiometer (PAX), which is usually accepted as a reference instrument for binsitu measurement, was concomitantly operated with an AE situated in wintertime Beijing, China. (i) During the observation period, the AE collected 303 consecutive quartz spots (n = 1, 2, 3..0.303) laden with particles. Each spot had a series of consecutive attenuation readings (ATNn,i(λ), i = 1, 2, 3....) dependent on the ambient black carbon (BC) concentrations. Based on the 11-spot moving average of the compensation factors, fmoving,n(λ), a dynamic shadow effect correction coefficient was devised (Eq. (10) ). (ii) The bATNn,i for each of seven wavelengths could be calculated from ATNn,i(λ), and the absorption Angstrom exponent αn,i was derived by considering the relationship between bATN,n,i(λ) and λ. (iii) Meanwhile, the PAX continuously recorded binsitu,n,i. The composite scattering correction coefficient, CCn,i(λ), could be calculated as Eq. (11) . (iv) A liner relationship was discovered between the CC(λ) and α. At 880 nm, for example, the relationship was CC(λ) = 1.79α + 2.63 (r2 = 0.90). (v) Apparently, the two key parameters, Rn,i[fmoving,n(λ)] and CCn,i(λ), are both derivable from the AE measurement data, which allows the translation from bATN,n,i to binsitu,n,i (Eq. (5) ) from the AE alone, independent of other instruments. Applying the dynamic correction algorithm to the data from a different time period revealed that bcor,n,i agreed well with binsitu,n,i, directly supporting our correction algorithm. Future studies are proposed to address the ways in which the methodology is temporally or regionally dependent, and whether the aerosols from sources or affected by dust advection also fall within the scope of this correction algorithm.
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