# Spatiotemporal Variation in Absorption Aerosol Optical Depth over China
## 1 Introduction  
Aerosols are tiny water droplets and particulates in the air. They are considered an important factor affecting global climate change, radiation balance, the cloud formation process and human health [1, 2, 3]. Aerosol optical depth (AOD) is the elementary optical parameter of aerosols [4]. As the non-scattering part of the AOD, the absorption aerosol optical depth (AAOD), on behalf of aerosol column optical absorption, is an importantparameter for assessing radiative forcing and atmospheric heating [5; 6; 7]. The Angstrom exponent (AE) provides information about the aerosol dominance size in the atmospheric vertical column. As an indispensable part of the AE, the absorption Angstrom exponent (AAE) is another key parameter, and it can be applied to reveal the spectral dependence of aerosol absorption [8]. Additionally, the AAE can be used to infer the main particle types in absorbent aerosols, for example mineral dust, BC, and brown carbon (BrC), as the absorption wavelength dependence is an intrinsic property closely interrelated with aerosol composition. BC and BrC chiefly come from incomplete anthropogenic combustion and biomass burning, and dust is predominantly derived from natural wind erosion, sometimes from landscape changes or soil disturbance [1; 9]. The AAE value of pure BC is near 1 theoretically, while the presence of dust or BrC increases the AAE value because of its enhanced absorption of ultraviolet/near-ultraviolet wavelengths [10]. The AAE depends on the emitting source and the mixing state of the absorption aerosol [11; 12; 13; 14]. To understand the effect of absorptive aerosols on the environment profoundly, it is necessary to analyze the AAOD and AAE. Remote sensing techniques including ground and satellite networks play the vital role in aerosol monitoring and characterization, as well as allowing a deeper understanding of the optical properties of atmospheric aerosols. Currently, the way to measure aerosol absorption characteristics routinely and globally is radiation measurements, e.g., the Aerosol Robotic Network (AERONET) based on ground observation [15; 16; 17; 18; 19], and the Ozone Monitoring Instrument (OMI) based on satellite remote observation [20; 21; 22; 23; 24; 25; 26; 27]. Nonetheless, AERONET is unable to determine the regional-scale AAOD variation trends with relatively finite monitoring stations and a narrow monitoring range while the OMI may misetimate or lose data for some days such as for excessive rain. [PERSON] et al. developed a method for classifying dust and non-dust aerosol types and determined the contributions of BC-related absorption to the non-dust AAOD from AERONET observations [16]. [PERSON] et al. compared the variations in black carbon AAOD and dust AAOD in China [17]. [PERSON] et al. inverted the AAOD of black carbon from AERONET observations over the world from 2000 to 2018 [18]. [PERSON] et al. utilized AAOD, single-scattering albedo (SSA), and the AAE from the AERONET data to distinguish the respective proportion of BC, dust, and organic matter in the entire AAOD, and pointed out that the AAE between 325 and 1000 nm is about 1.45 for biomass burning, whereas it is 2.3 for Saharan dust aerosols [19]. The OMI utilizes the greater sensitivity of radiation measured at the top of the atmosphere in the near ultraviolet region to different loads and aerosol types, and derives extinction AOD and AAOD using inversion programs generated by the near-ultraviolet aerosol inversion algorithm at three shortwave lengths of 354, 388 and 500 nm [20; 21]. [PERSON] et al. used the OMI aerosol index and AAOD to evaluate the NASA MERRA aerosol reanalysis [22]. [PERSON] et al. reduced the uncertainties of BC emissions by assimilating the OMI observation results of AAOD with the chemistry model of the Goddard Earth Observing System [23]. Their research group also discussed what factors have controlled the AAOD growth trend in the USA during the past decade [24]. [PERSON] et al.