Aerosol Optical and Microphysical Properties of Four  Typical Sites of SONET in China Based on Remote  Sensing Measurements

Xie, Yisong; Li, Zhengqiang; Li, Donghui; Xu, Hua; Li, Kaitao

doi:10.3390/rs70809928

Cited by 35 publications

(19 citation statements)

References 75 publications

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“…Indeed, the fraction of coarse particles in Hongkong is higher than its counterpart in the continental background site of Qiandaohu during September. Similar observations also exist in other coastal sites, such as Zhoushan in the YRD [17].…”

Section: Aerosol Optical Properties In Eastern Chinasupporting

confidence: 66%

How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?

et al. 2017

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Abstract:The rapid changes of aerosol sources in eastern China during recent decades could bring considerable uncertainties for satellite retrieval algorithms that assume little spatiotemporal variation in aerosol single scattering properties (such as single scattering albedo (SSA) and the size distribution for fine-mode and coarse mode aerosols) in East Asia. Here, using ground-based observations in six AERONET sites, we characterize typical aerosol optical properties (including their spatiotemporal variation) in eastern China, and evaluate their impacts on Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol retrieval bias. Both the SSA and fine-mode particle sizes increase from northern to southern China in winter, reflecting the effect of relative humidity on particle size. The SSA is~0.95 in summer regardless of the AEROENT stations in eastern China, but decreases to 0.85 in polluted winter in northern China. The dominance of larger and highly scattering fine-mode particles in summer also leads to the weakest phase function in the backscattering direction. By focusing on the analysis of high aerosol optical depth (AOD) (>0.4) conditions, we find that the overestimation of the AOD in Dark Target (DT) retrieval is prevalent throughout the whole year, with the bias decreasing from northern China, characterized by a mixture of fine and coarse (dust) particles, to southern China, which is dominated by fine particles. In contrast, Deep Blue (DB) retrieval tends to overestimate the AOD only in fall and winter, and underestimates it in spring and summer. While the retrievals from both the DT and DB algorithms show a reasonable estimation of the fine-mode fraction of AOD, the retrieval bias cannot be attributed to the bias in the prescribed SSA alone, and is more due to the bias in the prescribed scattering phase function (or aerosol size distribution) in both algorithms. In addition, a large yearly change in aerosol single scattering properties leads to correspondingly obvious variations in the time series of MODIS AOD bias. Our results reveal that the aerosol single scattering properties in the MODIS algorithm are insufficient to describe a large variation of aerosol properties in eastern China (especially change of particle size), and can be further improved by using newer AERONET data.

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Section: Aerosol Optical Properties In Eastern Chinasupporting

confidence: 66%

How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?

et al. 2017

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“…For the Beijing site, the average AOD for 440 nm, 675 nm, 870 nm and 1020 nm in spring, summer, autumn, winter and annual average values are summarized in Table 3 and shown in Figure 1a. In intra-annual aspect, summer usually has the highest average AOD as reported in some previous studies [50][51][52], followed by spring, autumn and winter. The largest seasonal averaged AOD in 440 nm is 1.33 compared to previous report of 0.93 [53].…”

Section: Aerosol Optic Depth (Aod) Trendsmentioning

confidence: 63%

“…Small α to around 0 usually means that the aerosol particles are mainly large with dust particles, while large α to around 2 means aerosol particles are mostly fine mode. α < 0.6 indicates the dust aerosol [17,50,56]. 2) in 2014 for the Beijing site (Xianghe site), suggesting that during the past 10 years, fine mode aerosol loading at both the Beijing and Xianghe sites has been increasing gradually.…”

Section: åNgström Exponent (α)mentioning

confidence: 99%

Analysis of Aerosol Properties in Beijing Based on Ground-Based Sun Photometer and Air Quality Monitoring Observations from 2005 to 2014

et al. 2016

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Aerosol particles are the major contributor to the deterioration of air quality in China's capital, Beijing. Using ground-based sun photometer observations from 2005 to 2014, the long-term variations in optical properties and microphysical properties of aerosol in and around Beijing were investigated in this study. The results indicated little inter-annual variations in aerosol optic depth (AOD) but an increase in the fine mode AODs both in and outside Beijing. Furthermore, the single scattering albedo in urban Beijing is larger, while observations at the site that is southeast of Beijing suggested that the aerosol there has become more absorbing. The intra-annual aspects were as follow: The largest AOD and high amount of fine mode aerosols are observed in the summer. However, the result of air pollution index (API) that mainly affected by the dry density of near-surface aerosol indicated that the air quality has been improving since 2006. Winter and spring were the most polluted seasons considering only the API values. The inconsistency between AOD and API suggested that fine aerosol particles may have a more important role in the deterioration of air quality and that neglecting particulate matter with aerodynamic diameter less than 2.5 µm (PM 2.5 ) in the calculation of API might not be appropriate in air quality evaluation. Through analysis of the aerosol properties in high API days, the results suggested that the fine mode aerosol, especially PM 2.5 has become a major contributor to the aerosol pollution in Beijing.

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“…In addition, under extremely wet conditions when AS and fine SS grow to coarse mode, their nonspherical fractions are assumed to be equal to coarse SS. Since SPH relates to volume fraction of nonspherical particles [ Xie et al ., ], this study utilizes SPH as a constraint for nonspherical component retrievals. To simplify the forward model, SPH of components (except for AS and fine SS) are considered to be constant under varying RH.…”

Section: Methodsmentioning

confidence: 99%

“…In this study aerosol components are derived from aerosol microphysical properties retrieved from groundbased remote sensing measurements. The polarized Sun-sky radiometer (CE-318DP) provides direct solar irradiance measurements from ultraviolet to infrared wavelengths and sky radiance measurements at multiple angles and wavelengths in the almucantar and solar principal plane geometries [Holben et al, 1998;Xie et al, 2015;Ma et al, 2016]. In this study, we use the retrieval algorithm of Dubovik et al [2006] to acquire the microphysical properties, which is also employed by AERONET.…”

Section: Sun-sky Radiometer Measurements and Productsmentioning

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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Aerosol Optical and Microphysical Properties of Four Typical Sites of SONET in China Based on Remote Sensing Measurements

Cited by 35 publications

References 75 publications

How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?

How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?

Analysis of Aerosol Properties in Beijing Based on Ground-Based Sun Photometer and Air Quality Monitoring Observations from 2005 to 2014

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

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