Derivation of PM₁₀ mass concentration from advanced satellite retrieval products based on a semi-empirical physical approach

Highlights

• Volume-to-extinction ratio is alternative value to microphysical parameter.

• Volume-to-extinction ratio is suitable for different aerosol types.

• Volume-to-extinction ratio can be directly used for satellite data.

• Particle effective density can be estimated from satellite refractive index data.

• PM₁₀ results are well tested by using POLDER/GRASP products.

Abstract

PM₁₀ remote sensing is of great significance in the atmospheric environment studies. Contrary to intuitive perception, deriving PM₁₀ is more difficult than PM_2.5 from satellite measurements. This is because although the major satellite parameter Aerosol Optical Depth (AOD) contain contribution of all suspended particles, it is much more sensitive to fine particles than coarse particles. To address this challenge, a physically based remote sensing method for PM₁₀ is developed using two new semi-empirical physical models: the model of columnar volume-to-extinction ratio (VE₁₀) and the model of particle effective density. VE₁₀ is a key parameter bridging the non-linear relationship between aerosol extinction and volume concentration. A semi- empirical VE₁₀ model is developed based on the fine mode fraction (FMF), and the mean relative error of VE₁₀ modeling is 14.5%. Similarly, the particle effective density depends on the ratio of mass to volume. The particle effective density is effectively characterized by refractive index of matter, with the theoretical error of 13.8%. Both semi-empirical physical models are applied to the derivation of PM₁₀, by using aerosol retrieval products of POLarization and Directionality of the Earth's Reflectances (POLDER) produced by the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm. As a validation, PM₁₀ mass concentration is estimated over China from Jan. to Oct. in 2013. A fairly good correlation and consistency are achieved by inter-comparison with in-situ PM₁₀ measurements.

Introduction

PM₁₀ (particulate matter with an aerodynamic diameter less than 10 μm), the inhalable particles, acting as a transmission vector for viruses (Schuit et al., 2020; Yan et al., 2018), has adverse health effects (Dobaradaran et al., 2016; Jeong, 2013; Khaniabadi et al., 2017; Nourmoradi et al., 2015; Wang et al., 2009). Hence, monitoring of PM₁₀ is of great significance. However, due to the weak extinction of coarse particles to sunlight, remote sensing of PM₁₀ from satellites is more challenging than PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm). Generally, the PM₁₀ is estimated using ground-based measurements. In-situ monitoring can provide accurate day and night PM₁₀ measurements. In China, in-situ stations are mainly located in eastern cities. It has limited spatial coverage and spatial representation. Moreover, the selection of the appropriate monitoring locations is also critical. Commonly, the PM₁₀ is monitored based on the tapered element oscillating microbalance (TEOM) technique or with beta attenuation monitors. Instrument calibration and manual operation at different stations may probably reduce the comparability of data. Satellite remote sensing technique is a useful tool, which can complement the lack of in-situ PM₁₀ measurements, especially over ocean, the regions between land and ocean, and the Northwestern China. In addition, high-resolution remote sensing results have large spatial coverage and spatial representation, which can provide scientific basis for site selection on the ground. Of course, it also depends on the development and improvement of satellite sensors and inversion approaches. Moreover, the missing data during the period without in-situ stations can be reconstructed based on satellite historical observation.

In these regards, the satellite observations with large spatial coverage can represent an extension to existing ground networks. Currently, there are mainly three methods of determining PM₁₀ from satellite remote sensing data. One is the mathematical statistical method, which is of high accuracy (Lee et al., 2010; Li et al., 2005; Liu et al., 2005; Seo et al., 2015; Wu et al., 2016; Guo et al., 2017), but somewhat lacking of clear physical mechanism. The second one is the chemical transport model method, which cannot operate without an accurate emission inventory or metrological field (Boys et al., 2014; Geng et al., 2015; Van Donkelaar et al., 2014; Van Donkelaar et al., 2010). The third one is the semi-empirical physical approach. For semi-empirical physical approach, the relationship between each variable and PM is clearly expressed through reasonable physical assumptions (Lin et al., 2015; Yan et al., 2017; Zhang and Li, 2015). Easy and fast operation is the premier advantage of this method. There is an obvious nonlinear relationship between PM and satellite-derived aerosol optical depth (AOD), hence the aerosol mass extinction efficiency and the effective radius are two important factors characterizing this nonlinear relationship (Koelemeijer et al., 2006; Van Donkelaar et al., 2006; Wang et al., 2010). However, to determine above two aerosol properties is usually difficult in practice. In these regards, the Volume-to-Extinction Ratio (VE₁₀) that adequately characterize the nonlinear relationship between extinction and volume can be used as an alternative to mass extinction efficiency and effective radius in capturing relationship between PM and AOD.

Many sensors currently can offer AOD products of high accuracy. However, few fine mode fraction (FMF) products are available from satellite remote sensing (Jethva et al., 2010; Kleidman et al., 2005; Levy et al., 2010; Levy et al., 2007). This is due to the down looking satellite measurements of surface reflected radiance are not very sensitive to particle size. The GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm derives an extended set of aerosol parameters benefiting from multi-angular polarimetry POLDER/PARASOL measurements (Dubovik et al., 2011, Dubovik et al., 2014). A solid quality of retrieved aerosol characteristics can be obtained by PARASOL/GRASP products (Chen et al., 2020). In this study, we use the POLDER/GRASP aerosol products including AOD, fine mode AOD, and the real part of the refractive index data at 490 nm, which are public available at GRASP-Open website (https://www.grasp-open.com/). Previous study by Wei et al. (2020a) indicated a high quality of POLDER/GRASP aerosol products (e.g. AOD, FMF, fine mode AOD, etc.) over China. In this study, we firstly design the sensitivity tests to investigate the impact of cutting diameter on VE₁₀. Then, the VE₁₀ model is established and tested based on data from Aerosol Robotic Network (AERONET). The extinction-volume conversion, vertical correction, humidity correction and weighting are applied based on the semi-empirical physical approach. The PM₁₀ remote sensing method is developed and the results are compared with the in-situ measurements over China from Jan. to Oct. in 2013. Finally, we discuss the error sources of derived PM₁₀ and provide both the theoretical and expected error estimations of the method.