Elsevier

Atmospheric Environment

Volume 226, 1 April 2020, 117403
Atmospheric Environment

An improved parameterization scheme for size-resolved particle activation ratio and its application on comparison study of particle hygroscopicity measurements between HTDMA and DMA-CCNC

https://doi.org/10.1016/j.atmosenv.2020.117403Get rights and content

Highlights

  • A new parameterization scheme for SPAR considering the contribution of the nearly-hydrophobic particles is proposed.

  • The fitting parameters using the improved scheme were up to 20% lowered for hygroscopic particles.

  • The derived aerosol hygroscopicity using the improved scheme agrees better with aerosol hygroscopicity derived from HTDMA.

Abstract

Size-resolved Particle Activation Ratio (SPAR), defined as the size-dependence of CCN activity of aerosol particles, is generally parameterized by a scheme that neglects the contribution of nearly-hydrophobic particles. In this paper, it was found that nearly-hydrophobic particles can contribute up to 20% to the CCN activity for large particles and the estimation of particle hygroscopicity would be significantly biased using the original parameterization scheme. An improved parameterization scheme considering the contribution of nearly-hydrophobic particles was proposed and applied on measurements conducted at a rural site in the North China Plain during summer 2013. For hygroscopic particles in range of 50–70 nm diameter, which might be dominated by organic compounds, their number fraction (fn) and midpoint activation diameter (Da) fitted with the improved scheme were up to 20% lower than the parameters fitted with the original scheme. Both parameterization schemes of SPAR were further applied in a comparison study of aerosol hygroscopicity measurements between Cloud Condensation Nuclei (CCN) Counter coupled with Differential Mobility Analyzer (DMA-CCNC) and Hygroscopicity Tandem Differential Mobility Analyzer (HTDMA) during the Xianghe Campaign. Applying the improved scheme, the correlations of derived fn for hygroscopic particles between measurements of DMA-CCNC and HTDMA were improved (R increased by up to 0.2 with the uncertainty of the regression to be about 10%). In addition, for particles smaller than 100 nm, the size-dependence of hygroscopicity parameter and the diurnal cycle of fn derived using the improved scheme, based on the DMA-CCNC measurements were more consistent with those derived with the HTDMA measurements. These results highlight the importance of considering nearly-hydrophobic particles in SPAR curves fitting and in the calculation of aerosol hygroscopicity based on DMA-CCNC measurements.

Introduction

Cloud condensation nuclei (CCN) are aerosol particles that can form cloud droplets under supersaturated conditions and play critical roles in cloud microphysics and aerosol indirect radiative effects (Pruppacher and Klett, 1978, Seinfeld and Pandis, 2006, Twomey, 1967, Zhao et al., 2006). CCN activity of particles that are determined by particle size and particle chemical composition (Köhler, 1936; Petters and Kreidenweis, 2007) is highly size-dependent. Therefore, size-resolved particle activation ratio (SPAR) is introduced to quantify the size-dependent CCN activity of particles, which can be measured by a CCN Counter coupled with a Differential Mobility Analyzer (DMA-CCNC, Roberts and Nenes, 2005; Deng et al., 2011). SPAR can be used to calculate CCN number concentration from particle number size distribution (Deng et al., 2013; Juranyi et al., 2010; Rose et al., 2010), and to estimate aerosol hygroscopicity and mixing state (e.g., Good et al., 2010; Su et al., 2010; Rose et al., 2011; Padro et al., 2012; Lance et al., 2013).

Simple sigmoidal functions with three parameters are usually used to fit SPAR curves. These fitting parameters can be understood as the number fraction of CCNs to total particles (fn), the midpoint activation diameter (Da) of the CCNs and the standard deviation of the CCNs, respectively (Rose et al., 2008; Gunthe et al., 2011; Padro et al., 2012; Deng et al., 2013), and are helpful in the study of aerosol hygroscopicity and mixing state (Rose et al., 2011; Kawana et al., 2016; Mei et al., 2013; Ogawa et al., 2016). There are three kinds of fitting formulas with different mathematical forms (Rose et al., 2008; Meng et al., 2014; Padro et al., 2012; Deng et al., 2013), which have been shown to be consistent in fitting SPAR curves and in calculating CCN number concentrations (Tao et al., 2018). All those existing parameterization schemes are based on the assumption that nearly-hydrophobic (NH) particles contribute negligibly to cloud activation. However, in the North China Plain and some other regions, NH particles were found to contribute up to 20% to the CCN activity, which is not negligible (Zhang et al., 2014; Irwin et al., 2010; Juranyi et al., 2013; Kawana et al., 2017; Müller et al., 2017). In this case, applying existing parameterization schemes may lead to significant deviations of calculated Da and the corresponding aerosol hygroscopicity.

The hygroscopicity parameter of ambient aerosol particles can be derived from DMA-CCNC, Hygroscopicity Tandem Differential Mobility Analyzer (HTDMA, Swietlicki et al., 2008), humidified nephelometer (Titos et al., 2016; Kuang et al., 2017) and aerosol chemical composition measurements (Liu et al., 2014; Zhang et al., 2014; Wang et al., 2020). Among them, only HTDMA, DMA-CCNC and Single Particle Aerosol Mass Spectrometer (SPAMS) can provide size-resolved aerosol hygroscopicity as well as the probability density of aerosol hygroscopicity at a specific particle size, which is used to derive parameters of hygroscopic particles in this study. Compared to the limited applications of SPAMS in the study of aerosol hygroscopicity, field campaigns with HTDMA or DMA-CCNC measurements are more common. Widespread attention has been paid to the comparison of the measurements between these two instruments in order to improve the understanding of physical and chemical processes related to particle hygroscopicity (Wex et al., 2009; Dusek et al., 2011; Hodas et al., 2016; Liu et al., 2018; and reference therein). In the recent decade, studies comparing measurements of HTDMA and DMA-CCNC were conducted all around the world. While a few studies reported good agreements (Juranyi et al., 2010; Juranyi et al., 2013; Kawana et al., 2017), the majority of the studies found large differences (higher than 50%) in particle hygroscopicity measured by the two instruments, despite significant correlations (Irwin et al., 2010, 2011; Lance et al., 2013; Wu et al., 2013; Whitehead et al., 2014; Cerully et al., 2011; Hong et al., 2014; Bougiatioti et al., 2016; Kawana et al., 2017; Müller et al., 2017). The discrepancy of aerosol hygroscopicity measured by DMA-CCNC and HTDMA may have resulted from variations in aerosol hygroscopicity due to organic compounds (Hodas et al., 2016; Ruehl et al., 2016; Ovadnevaite et al., 2017; Liu et al., 2018; Wex et al., 2009; Dusek et al., 2011; Pajunoja et al., 2015), but may also come from uncertainties in the measurements (Duplissy et al., 2011; Irwin et al., 2010; Topping and McFiggans, 2012; Dusek et al., 2011; Whitehead et al., 2014) or in the calculation of aerosol hygroscopicity (Petters et al., 2007; Wang et al., 2017). As the parameterization scheme for SPAR can affect the aerosol hygroscopicity calculated based on DMA-CCNC measurements, it is necessary to evaluate how the assumption neglecting nearly-hydrophobic particles influences the comparison between the aerosol hygroscopicities measured by DMA-CCNC and HTDMA.

In this study, an improved parameterization scheme for fitting measured SPAR curves was proposed to account for influences of nearly-hydrophobic particles on SPAR and its performance is compared to that of the original parameterization scheme based on DMA-CCNC measurements in the North China Plain. Furthermore, these two parameterization schemes were applied in a comparison study of aerosol hygroscopicity measurements between HTDMA and DMA-CCNC. The influences of applying the improved scheme rather than the original scheme on the derived parameters (fn, Da and hygroscopicity parameter κ) were discussed, including their size-dependences and diurnal cycles.

Section snippets

Site

Measurements of aerosol microphysical properties were conducted at a regional atmospheric observatory at Xianghe station (39.75° N, 116.96° E; 36 m a.s.l.) for two weeks in the summer of 2013. The observatory is surrounded by residential areas and farmlands. It is about 50 km southeast from Beijing and 70 km west from Tianjin in the NCP, with a small village nearby and about 5 km west to the city center of Xianghe county. During this campaign, comprehensive aerosol microphysical properties were

Performance of the parameterization scheme considering contribution of NH particles on SPAR

The measured SPAR curves and the corresponding fitting curves using the original scheme and the new scheme at three SSs are shown in Fig. 3. The SPAR curves for high supersaturation cases reveal two obvious stages of increase with particle diameter. Taking the SPAR curve at 0.8% as an example, a rapid SPAR increase can be observed within the diameter range of 30–60 nm, which slowed down when diameter reached above 60 nm. Such a phenomenon has been often observed in SPAR measurements at higher

Conclusions

Size-resolved Particle Activation Ratio (SPAR) curves, which are determined by aerosol hygroscopicity and mixing state, are essential for NCCN calculation and can provide information on aerosol hygroscopicity. A parameterization scheme with three parameters has been generally used for simplified quantification of SPAR curves, which was based on the assumption that NH particles contribute little to CCN activity. In North China Plain, it was found that the contribution of NH particles could not

CRediT authorship contribution statement

Jiangchuan Tao: Conceptualization, Methodology, Software, Data curation, Validation, Formal analysis, Investigation, Writing - original draft, Visualization, Project administration, Funding acquisition. Ye Kuang: Conceptualization, Methodology, Validation, Writing - review & editing. Nan Ma: Conceptualization, Methodology, Software, Data curation, Investigation, Writing - review & editing, Project administration, Funding acquisition. Yijia Zheng: Formal analysis, Writing - review & editing. A.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work is supported by the National Natural Science Foundation of China (41805110 and 41590872) and the National Key R&D Program of China (2016YFC020000: Task 5).

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