Retrieval Of Aerosol Chemical Composition From Ground

Aerosol chemical components are key factors influencing the aerosol radiative properties. In the field of climate change research, it is still difficult to evaluate aerosol radiative forcing accurately. The main reason is the difficulty in accurately determining the radiative properties of aerosols. Additionally, in the field of atmospheric correction for the satellite remotely sensed imageries, the unsuitable selection of atmospheric aerosol mode will result in low accuracy of quantitative remote sensing retrievals. Hence, in order to better understand the aerosol radiative characteristics, more and more research institutions and scholars are committed to explore the physical and chemical properties of atmospheric aerosols. Recently, some researches have started to give their attention to study aerosol physical and chemical properties based on Aerosol Robotics Network (AERONET), a network of more than500surface sun-sky radiometers (or sun photometers) located throughout the world, providing a long term view and an extensive spatial coverage. In addition, AERONET provides high-precision calibration for each instrument and mature inversion products related to aerosol properties, which makes it possible to access to the information of atmospheric aerosol chemical composition in different regions over the world. Compared to the in-situ chemical sampling method, estimate of the content of aerosol chemical components through the sun-sky radiometer measurements has the superiorities of automatically acquiring the aerosol information within the entire atmosphere in real-time and without direct contact to the aerosol.In this study, according to the aerosol optical properties, we firstly simplify the aerosol as a mixture of five components. They are three absorbing components like Black Carbon (BC), Brown Carbon (BrC), and dust (DU); one scattering (non-absorbing) component of ammonium sulfate (AS) as well as water, which is responsible for aerosol hygroscopic characteristics. Then, we present a method to retrieve columnar contents of these five chemical components simultaneously from spectral refractive indices and spectral single scattering albedo (SSA) obtained from the sun-sky radiometer measurements. This method is a succession of several previous studies, but has advantages in providing simultaneous determination of BC, BrC, and DU. We then implement this method to investigate the column-integrated aerosol composition over Jing-Jin-Tang region, China using the sun-sky radiometer measurements. In the last part, we validate the retrieved BC concentrations with the in-situ measurements.The main results and conclusions of the research are presented as follows:(1) According to the published literatures, the spectral variation characteristics of imaginary refractive indices (k) of BC, BrC, and DU are examined to find out the reason why the current researches did not choose BrC and DU simultaneously as the end-members in the retrieval. The SSA spectra of BC, BrC, and DU are investigated based on the measurements from typical AERONET sites of desert dust, biomass and urban/industrial. We find that the difficulty in distinguishing BrC and DU based on k spectra can be solved by examining the shape of the SSA spectra. The shape of DU SSA from675-1020nm follows an increasing (or neutral) pattern, while for BrC it follows a deceasing pattern. This provides the basis that in addition to the spectral refractive index, SSA spectra can also be added into the inversion algorithm, and accordingly three major absorbing aerosols of BC, BrC and DU can be considered simultaneously as the end-members in the retrieval.(2) According to the definition of the SSA, a physical model associating SSA with the content and the inherent physical properties of aerosol components is established combined with the Mie theory, which provides the foundation to retrieve aerosol chemical composition from the parameters of aerosol properties.(3) Based on the sun-sky radiometer measurements, inversion experiments using different inversion algorithms are carried out. Results show that the calculated aerosol property parameters with the five-component inversion model proposed in this research match the observed ones from the sun-sky radiometer best. Especially, when the aerosols are influenced by dust or coal burning emissions, the five-component inversion model can fully reproduce the aerosol’s enhanced absorption at440nm. However, the three-component (BC, AS, and AW) inversion model works worst and can not explain the enhanced absorption characteristics of aerosols at440nm. The performance of the four-component inversion model (BC, DU, AS, and AW) is in between the five-component and three-component inversion model. (4) The five-component inversion model is applied to investigate the aerosol chemical composition under different weather conditions, i.e., the clear day in Summer with the fine particles dominated in the aerosol, the hazy and clear days in winter with the coarse particles comparable to the fine particles, and the dusty day with the coarse particles dominated in the aerosol. It turns out that the retrieved results for each case is reasonable, which indicates that the five-component inversion algorithm proposed here is applicable for various mixing ratios of the coarse particles to the fine particles in the aerosol.(5) Based on the sun-sky radiometer measurements obtained from Apr.,2011to Mar.,2012, the spatiotemporal variations of the columnar content of the five aerosol chemical components over Jing-Jin-Tang region are explored using the five-component inversion algorithm. The results show that there exist apparent seasonal variation trends for BC, BrC, DU, and AW, as a result of the seasonal changes of the aerosol emission sources as well as weather conditions such as relative humidity. BC is generally higher in winter and lower in spring. BrC peaks form November to the following March, and reaches to the minimum in summer and in September of autumn. DU dominates in spring and winter, followed by autumn, and is minimum summer. AW peaks in summer, followed by autumn and is minimum in spring. Xinglong, as the atmospheric background site, is different in aerosol chemical composition compared to the other two sites of Beijing and Xianghe in this region. Moreover, due to similar climatic characteristics and aerosol emission sources, the aerosol chemical compositions show relatively high similarity between Xianghe and Beijing.(6) Based on the sun-sky radiometer measurements obtained from2001-2012over Beijing, the change trends in the contents of aerosol chemical components in the past12years are investigated using the five-component inversion algorithm. The results showed that the content of BC is decreased gradually, caused by energy-saving emission reduction measures being taken by the government to the prepare for the2008Olympic Games. The volume fraction of BC is over2%before2008, but less than2%after2008. The content of BrC is decreasing before2006and2007, but increasing afterwards. For the other three components, i.e. DU, AS and AW, the contents are basically in a steady state in the past12years. The yearly averaged content of DU is about30%in volume fraction, AS is mainly in the vicinity of40%, and AW is about25-30%.(7) According to the inversion results of aerosol chemical composition over Beijing during2001-2012, the preliminary atmospheric aerosol mode is establishment. For Beijing, the soot, dust and water-soluble type particles account for2%,39%and59% respectively in the dry aerosol. This result is comparable with other published results related to Beijing’s atmospheric aerosol mode, indicating that a reasonable and credible atmospheric aerosol mode can be obtained from ground-based remote sensing data using the aerosol chemical composition inversion algorithm.(8) Consistent temporal variation trends and good correlations are found between retrieved BC mass concentration and in-situ measurements. The large relative errors of the retrieved BC mass concentration exist when the actual BC mass concentration is lower(<2μg/m3). As the actual BC mass concentration increases, the relative error is decreased following an e exponential function (R2=0.74). The relative error of the retrieved BC mass concentration is basically less than45%and can even reach to1%when the actual BC mass concentration is above2μg/m3.