Amplification of black carbon light absorption induced by atmospheric aging: temporal variation at seasonal and diel scales in urban Guangzhou

Abstract

<p><strong>Abstract.</strong> Black carbon (BC) is an important climate forcer in the atmosphere. Amplification of light absorption can occur by coatings on BC aerosols, an effect that remains one of the major sources of uncertainties for accessing the radiative forcing of BC. In this study, the absorption enhancement factor (E<sub>abs</sub>) was quantified by the minimum R squared (MRS) method using elemental carbon (EC) as the tracer. Two field campaigns were conducted in urban Guangzhou at the Jinan university super site during both wet season (July 31–September 10, 2017) and dry season (November 15, 2017–January 15, 2018) to explore the temporal dynamics of BC optical properties. The average concentration of EC was 1.94 ± 0.93 and 2.81 ± 2.01 μgC m<sup>−3</sup> in the wet and dry seasons, respectively. Mass absorption efficiency at 520 nm by primary aerosols (MAE<sub>p520</sub>) determined by MRS exhibit a strong seasonality (8.6 m<sup>2</sup>g<sup>−1</sup> in the wet season and 16.8 m<sup>2</sup>g<sup>−1</sup> in the dry season). E<sub>abs520</sub> was higher in the wet season (1.51 ± 0.50) and lower in the dry season (1.29 ± 0.28). Absorption Ångström exponent (AAE<sub>470-660</sub>) in the dry season (1.46 ± 0.12) were higher than that in the wet season (1.37 ± 0.10). Collective evidence showed that the active biomass burning (BB) in dry season effectively altered optical properties of BC, leading to elevated MAE, MAE<sub>p</sub> and AAE in dry season comparing to those in wet season. Diurnal E<sub>abs520</sub> was positively correlated with AAE<sub>470-660</sub> (<i>R</i><sup>2</sup> = 0.71) and negatively correlated with the AE33 aerosol loading compensation parameter (<i>k</i>) (<i>R</i><sup>2</sup> = 0.74) in the wet season, but these correlations were significantly weaker in the dry season, which may be related to the impact of BB. This result suggests that lensing effect was dominating the AAE diurnal variability during the wet season. The effect of secondary processing on Eabs diurnal dynamic were also investigated. The E<sub>abs520</sub> exhibit a clear dependency on secondary organic carbon to organic carbon ratio (SOC/OC). E<sub>abs520</sub> correlated well with nitrate, implying that gas-particle partitioning of semi-volatile compounds may potentially play an important role in steering the diurnal fluctuation of E<sub>abs520</sub>. In dry season, the diurnal variability of E<sub>abs520</sub> was associated with photochemical aging as evidenced by the good correlation (<i>R</i><sup>2</sup> = 0.69) between oxidant concentrations (O<sub>x</sub>=O<sub>3</sub>+NO<sub>2</sub>) and E<sub>abs520</sub>.</p>

Mass absorption cross-section and absorption enhancement from long term black and elemental carbon measurements: A rural background station in Central Europe

“…The light absorption enhancement ( E abs _ λ ) can be calculated by dividing the total B abs_λ or MAC eBC_λ by their primary fractions (B abs_pri_λ and MAC pri_λ ) as in Eq. (4) ( Sun et al, 2020 ; Wu et al, 2018 ): where B abs_pri λ and MAC pri λ are the primary or reference B abs and MAC, respectively, measured at wavelength λ for freshly emitted BC particles. In this study, the E abs _ λ was calculated as the ratio between MAC λ and MAC pri_λ according to Eq.…”

“…The MRS method estimates the primary ratios (e.g., [OC/EC] pri , MAE pri ) by investigating the inherent independence between a primary pollutant (e.g., EC) and a secondary component (e.g., SOC, B abs_aging ) during atmospheric aging ( Sun et al, 2020 ; Wu et al, 2018 ; Wu and Yu, 2016 ). A description of the MRS method has been detailed in Wu et al (2018) , and a computer program was built in Igor Pro (WaveMetrics, Inc. Lake Oswego, OR, USA) for its easy application ( Wu, 2017a ).…”

“…Inversely, B abs_aging , due to the coating of particles formed during atmospheric transport and its variability, depends on the coating thickness, independently of the EC mass. As a result, the minimum R 2 (between EC and B abs_aging ) would correspond to the best MAC pri of the dataset representing the overall MAC pri from different primary emission sources instead of MAC pri from a single primary source as for ([OC/EC] pri ) in the EC tracer method ( Wu et al, 2018 ; Sun et al, 2020 ).

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“…One approach is to adopt the reference MAC pri based on the literature, but these values are variable depending on the location, sources, and measurement period, and may not be representative of MAC pri for a given site. Another approach is to determine MAC pri based on a correlation analysis of the concurrent measurements of both MAC BC and BC particle mixing state with a single-particle soot photometer (SP2) or soot particle aerosol mass spectrometer (SP-AMS) ( Cappa et al, 2019 ; Sun et al, 2020 ; Yuan et al, 2020 ).…”

“…The TD-PAS, SP2, and SP-AMS methods have the advantage of providing high time resolution data, but the high cost of these systems reduces their worldwide field deployment, particularly for long-term measurements ( Sun et al, 2020 ; Wu et al, 2018 ). Wu et al (2018) recently developed an alternative new statistical approach.…”