Abstract

Abstract. The relationship between aerosol optical depth (AOD) and PM2.5 is often investigated in order to obtain surface PM2.5 from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD–PM2.5 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 PM2.5 to AOD, which is defined as η, and the square of their correlation coefficient (R2) 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 PM2.5 data with the correction of RH and PBLH compared to those without, R2 of monthly averaged PM2.5 and AOD at 14:00 LT increases from 0.63 to 0.76, and R2 of multi-year averaged PM2.5 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 PM2.5, η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM2.5 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 PM2.5, for which R2 is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD–PM2.5 relationships.

Highlights

  • Atmospheric aerosol, known as particulate matter, can influence the Earth’s climate system by directly and indirectly modifying the incoming solar radiation and outgoing longwave radiation

  • The data used in this study include surface PM2.5 concentrations and aerosol optical depth (AOD), satellite-based AOD from the ModerateResolution Imaging Spectroradiometer (MODIS), satellitebased aerosol profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and meteorology data from China Meteorological Administration (CMA)

  • The AODdry obtained here could be somehow overestimated compared to its true value. It shows a much better positive relationship in the temporal variation in monthly average AODdry and PM2.5_column, with R2 as 0.76. This result indicates that the corrections for planetary boundary layer height (PBLH) and relative humidity (RH) are essential for the improvement of the retrieval accuracy of PM2.5 from AOD

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Summary

Introduction

Atmospheric aerosol, known as particulate matter, can influence the Earth’s climate system by directly and indirectly modifying the incoming solar radiation and outgoing longwave radiation. Systematic studies about the influential factors to the relationship between PM2.5 and AOD have not been carried out, which are necessary for future derivation of accurate PM2.5 from satellite AOD observations. Using both satellite and surface observation of aerosol properties and meteorology variables in Beijing from 2011 to 2015, this study analyzes the influential factors to AOD–PM2.5 relationship, which include aerosol type, RH, PBLH, wind speed, and the vertical structure of aerosol distribution.

Data and method
Meteorological data
AERONET measurements
CALIPSO profile products
MODIS aerosol product
Method
Aerosol classification method
Analysis and results
Effect of RH and PBLH
Aerosol type
Vertical distribution of aerosol
Findings
Summary
Full Text
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