Multi-peak accumulation and coarse modes observed from AERONET retrieved aerosol volume size distribution in Beijing

Zhang, Ying; Li, Zhengqiang; Zhang, Yuhuan; Chen, Yu; Cuesta, Juan; Ma, Yanhui

doi:10.1007/s00703-016-0435-3

Cited by 12 publications

(7 citation statements)

References 42 publications

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“…Moreover, the relatively large uncertainties of size distribution in the regions of radius < 0.1 µm and > 7 µm [ Dubovik et al ., ] might also be accumulated and transferred into estimation of aerosol components. In addition, there are multiple modes (three or more) in the observed volume size distribution sometimes [ Li et al ., ; Zhang et al ., ], but the model is still a bimodal lognormal size distribution, which could also enlarge the modeling error if one uses size distribution in the retrieve scheme. Therefore, the use of VF f/c is believed to be beneficial to composition estimation, because it not only provides size information but also avoids the impacts of size distribution uncertainties.…”

Section: Discussionmentioning

confidence: 99%

Estimation of atmospheric aerosol composition from ground‐based remote sensing measurements of Sun‐sky radiometer

Xie

Zhang

et al. 2017

JGR Atmospheres

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Remote sensing provides aerosol loading information, but to address climate and air quality model validation, there are additional needs to acquire aerosol composition information. In this study, a comprehensive aerosol composition model is established to quantify black carbon (BC), brown carbon (BrC), mineral dust (DU), particulate organic matters, ammonium sulfate like (AS), sea salt, and aerosol water uptake. We develop forward modeling of aerosol components, including microphysical parameters (real and imaginary refractive indices, volume fraction ratio of fine to coarse mode, and sphericity) and hygroscopic growth models, and propose an optimization scheme to estimate the components. The uncertainties caused by input parameters are also assessed. Sun‐sky radiometer measurements and meteorological data obtained during a campaign in Huairou, Beijing, are processed to estimate aerosol components, which are further compared with synchronous in situ chemical measurements. The results show generally good consistencies between remotely estimated and measured components (e.g., correlation coefficients for BC, BrC, AS, and PM2.5 lie in about 0.8–0.9). The comparisons between modeled and observed microphysical parameters also show good agreements, with the exception of sphericity, which is likely caused by high uncertainties of this parameter. Sensitivity studies show that BC and BrC are highly sensitive to imaginary refractive index, while DU is strongly correlated to both volume size and sphericity. The performance of composition retrieval is expected to be improved when the sphericity uncertainty is significantly reduced.

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Section: Discussionmentioning

confidence: 99%

Estimation of atmospheric aerosol composition from ground‐based remote sensing measurements of Sun‐sky radiometer

Xie

Zhang

et al. 2017

JGR Atmospheres

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“…In this paper, the sub-mode VSDs and CRIs were retrieved by the aerosol products [24,26] , following by Zhang et al (2016) and Zhang et al (2017). The method developed by Cuesta et al (2008) is employed to separate VSD into a single Log-Normal Modes (LNM).…”

Section: Methodsmentioning

confidence: 99%

“…The method developed by Cuesta et al (2008) is employed to separate VSD into a single Log-Normal Modes (LNM). Each LNM parameters have three parameters: the modal concentration, geometric standard deviation and modal radius [32,33]. The sub-mode VSD can be modeled by the following function:…”

Section: Methodsmentioning

confidence: 99%

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Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China

Zhang

et al. 2019

Atmosphere

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Chengdu is a typical basin city of Southwest China with rare observations of remote sensing measurements. To assess the climate change and establish a region aerosol model, a deeper understanding of the separated volume size distribution (VSD) and complex refractive index (CRI) is required. In this study, we employed the sub-mode VSD and CRI in Chengdu based on the three years observation data to investigate the sub-mode characteristics and climate effects. The annual average fraction of the fine-mode aerosol optical depth (AOD f ) is 92%, which has the same monthly tendency as the total AOD. But the coarse-mode aerosol optical depth (AOD c ) has little variation in different months. There are four distinguishing modes of VSD in Chengdu; the median radii are 0.17 µm ± 0.05, 0.31 µm ± 0.12, 1.62 µm ± 0.45, 3.25 µm ± 0.99, respectively. The multi-year average and seasonal variations of fine-and coarse-mode VSD and CRI are also analyzed to characterize aerosols over this region. The fine-mode single scattering albedos (SSAs) are higher than the coarse-mode ones, which suggests that the coarse-mode aerosols have a stronger absorbing effect on solar light than the small-size aerosol particles in Chengdu.is conducive to the formation of aerosol particulates, which has made Chengdu become one of the regions in China with serious haze pollution [7][8][9][10]. The special topography and climate in Sichuan basin leads to a kind of wet, rainy and cloudy weather condition [11]. Therefore, it is difficult to obtain a large number of measurements through optical remote sensing observations in Chengdu. Sampling method of atmospheric particulates is one kind of Chengdu air pollution study [7,9,10,12], which fails to acquire the aerosol's larger-scale spatial characteristics. The spatial characteristics of aerosols can be obtained by remote sensing, one kind of non-contact method [13][14][15]. For instance, some studies analyzed the spatial-temporal distribution of aerosol optical depth (AOD) in Sichuan basin using satellite remote sensing [16,17]. Besides, aerosol optical parameters obtained by the ground-based remote sensing observation were statistically analyzed in this area [18][19][20][21].Although the above-mentioned research studies focus on the total-column aerosol properties by remote sensing methods, it still remains a big challenge to obtain the characteristics of sub-mode aerosol (fine-and coarse-mode) in Chengdu. The fine-and coarse-mode particles are related to the different sources and compositions. Fine-mode aerosols are mainly dominated by anthropogenic emissions and are related to the fog or low-altitude cloud dissipated events [22,23]. Coarse-mode particles are determined by the sea salt, dust and other natural sources. Therefore, the knowledge of aerosol sub-mode properties plays a role in the research on regional climate and the improvement of the aerosol model used in the satellite retrieval algorithms.In this study, the sub-mode volume size distribution (VSD) and complex refractive index (CRI) in Chengdu a...

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“…The results may be correct for areas that have few occurrences of heavy particulate matter pollution, as aerosol retrieval is likely to be successful. However, for areas such as Beijing that have frequent particulate matter pollution episodes, MODIS retrieval is highly possible to fail, while AERONET-which is aimed directly at the sun-could produce sufficiently accurate results [31,32]. As MODIS AOD products-including 3 km DT, 10 km DT, and 10 km DB-have been widely used to estimate the surface PM 2.5 concentrations over various situations [33,34], it raises a question of what the representativeness of different MODIS AOD products under different air quality conditions is.…”

Section: Introductionmentioning

confidence: 99%

Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing

2017

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Abstract:The newly released MODIS Collection 6 aerosol products have been widely used to evaluate fine particulate matter with a 10 km Dark Target aerosol optic depth (DT AOD) product, a new 3 km DT AOD product and an enhanced Deep Blue (DB) AOD product. However, the representativeness of MODIS AOD products under different air quality conditions remains unclear. In this study, we obtained all three types of MODIS Terra AOD from 2001 to 2015 and Aqua AOD from 2003 to 2015 for the Beijing region to study the performance of the different AOD products (Collection 6) under different air quality situations. The validation of three MODIS AOD products suggests that DB AOD has the highest accuracy with an expected error (EE) envelope (containing at least 67% of the matchups on a scatter plot) of 0.05 + 0.15τ, followed by 10 km DT AOD (0.08 + 0.2τ) and 3 km DT AOD (0.35 + 0.15τ), specifically for Beijing. Near-surface PM 2.5 concentrations during the passage of MODIS from 2013 to 2015 were also obtained to categorize air quality as unpolluted, moderately, and heavily polluted, as well as to analyze the performance of the different AOD products under different air quality conditions. Very few MODIS 3 km DT retrievals appeared on heavily polluted days, making it almost impossible to play an effective role in air quality applications in Beijing. While the DB AOD allowed for considerable retrievals under all air quality conditions, it had a coarse spatial resolution. These results demonstrate that the MODIS 3 km DT AOD product may not be the appropriate proxy to be used in the satellite retrieval of surface PM 2.5 , especially for those areas with frequent haze-fog events like Beijing.

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Multi-peak accumulation and coarse modes observed from AERONET retrieved aerosol volume size distribution in Beijing

Cited by 12 publications

References 42 publications

Estimation of atmospheric aerosol composition from ground‐based remote sensing measurements of Sun‐sky radiometer

Estimation of atmospheric aerosol composition from ground‐based remote sensing measurements of Sun‐sky radiometer

Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China

Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing

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