Analysis of influential factors for the relationship between PM<sub>2.5</sub> and AOD in Beijing

Abstract

Abstract. The relationship between aerosol optical depth (AOD) and PM 2.5 is often investigated in order to obtain surface PM 2.5 from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD-PM 2.5 regressions. Using both ground and satellite observations in Beijing from 2011 to 2015, this study analyzes the influential factors including the aerosol type, relative humidity (RH), planetary boundary layer height (PBLH), wind speed and direction, and the vertical structure of aerosol distribution. The ratio of PM 2.5 to AOD, which is defined as η, and the square of their correlation coefficient (R 2 ) have been examined. It shows that η varies from 54.32 to 183.14, 87.32 to 104.79, 95.13 to 163.52, and 1.23 to 235.08 µg m −3 with aerosol type in spring, summer, fall, and winter, respectively. η is smaller for scattering-dominant aerosols than for absorbing-dominant aerosols, and smaller for coarse-mode aerosols than for fine-mode aerosols. Both RH and PBLH affect the η value significantly. The higher the RH, the smaller the η, and the higher the PBLH, the smaller the η. For AOD and PM 2.5 data with the correction of RH and PBLH compared to those without, R 2 of monthly averaged PM 2.5 and AOD at 14:00 LT increases from 0.63 to 0.76, and R 2 of multi-year averaged PM 2.5 and AOD by time of day increases from 0.01 to 0.93, 0.24 to 0.84, 0.85 to 0.91, and 0.84 to 0.93 in four seasons respectively. Wind direction is a key factor for the transport and spatial-temporal distribution of aerosols originated from different sources with distinctive physicochemical characteristics. Similar to the variation in AOD and PM 2.5 , η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM 2.5 concentrations to AOD decreases with surface wind speed. The vertical structure of aerosol exhibits a remarkable change with seasons, with most particles concentrated within about 500 m in summer and within 150 m in winter. Compared to the AOD of the whole atmosphere, AOD below 500 m has a better correlation with PM 2.5 , for which R 2 is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD-PM 2.5 relationships.

Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China

“…The proportion of strongly absorbing coarse-mode particles -mainly dust (Group VII) -was only ∼ 1.04 % of the total particle count at Hangzhou, while at the other sites the percent abundances were < 1 %, and the FMF for these particles was ∼ 0.50-0.63 at all sites. These patterns show that the YRD region is different from regions in northern China, including Beijing, where dust particles contribute significantly to the coarse-mode absorption (Zheng et al, 2017). The percentage of weakly absorbing coarse-mode particles (Group VIII) at all sites was < 0.54 %, which shows that this aerosol type was rare.…”

“…Thus, it is advantageous to categorize aerosols as absorbing or non-absorbing based on ground-based optical parameters, including SSA, fine-mode fraction of AOD, and EAE etc. In this study, we used the SSA, FMF and EAE values to classify the fine-mode and coarse-mode particles from each site into eight groups of particles following the method of Zheng et al (2017). The eight types of particles were (I) highly absorbing fine-mode particles (AE > the ChunAn rural site, the percentage of Type I particles was only ∼ 0.16 % (FMF ∼ 0.91).…”

Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning

“…The data set has been successfully used in previous air quality studies (cf. Chen et al, ; Stafoggia et al, ; Zheng et al, ). To capture regional transport of particles, ERA‐Interim reanalysis wind components (m/s) in east‐west and north‐south direction (10 m height) are used.…”

“…To capture regional transport of particles, ERA‐Interim reanalysis wind components (m/s) in east‐west and north‐south direction (10 m height) are used. Wind direction and speed can influence both particle concentrations (Beloconi et al, ; Chudnovsky et al, ; Li et al, ) and the relationship between AOD and PM10 (Stirnberg et al, ; Zheng et al, ). Wind direction and speed are included as instantaneous values and as the mean of precedent days (72 hr).…”

The Effects of PM2.5 Concentrations and Relative Humidity on Atmospheric Visibility in Beijing

“…In addition, the RH correction based on the aerosol hygroscopic growth factor is widely adopted in retrieving satellite‐observed aerosol optical depth to determine surface PM 2.5 concentrations (Q. He et al, ; J. Guo et al, ; Kong et al, ; J. Lin & Li, ; Ma et al, ; C. Zheng, Zhao, et al, ). Moreover, the visibility may display either an exponential or power law relationship with the PM 2.5 concentrations at the same location, depending on the conditions of wind speed, wind direction, and precipitation intensity (J. Wang et al, ).…”