Elsevier

Atmospheric Environment

Volume 224, 1 March 2020, 117323
Atmospheric Environment

Aerosol layers in the free troposphere and their seasonal variations as observed in Wuhan, China

https://doi.org/10.1016/j.atmosenv.2020.117323Get rights and content

Highlights

  • Aerosol layer's geometries and optical characteristics.

  • Aerosol layer's seasonal variations.

  • Monthly free tropospheric AOD.

Abstract

Free-tropospheric aerosol layers and their seasonal variation over Wuhan (30.5°N, 114.4°E), China, are presented based on a 532-nm polarization lidar measurements on 162 days from January through December 2013. Using the aerosol layer selection criterions, a total of 402 free-tropospheric aerosol layer events were identified. The bottom height of the aerosol layers below 2 km accounts for 68% of the total, while approximately 76% of the layer's top height ranges from 1 km to 4 km. Out of the 402 events, 269 (67%) are optically-thin layers with aerosol optical depth (AOD) less than 0.1. The free tropospheric AOD2-7 contribute ~13–31% to the AOD0-7 and the free-tropospheric aerosol layers show considerable moderate variation. The aerosol layers have the maximum mean geometrical thickness of 1.2 km in spring, while the minimum mean thickness is 0.7 km in autumn, and the mean thickness is 0.93 km and 1 km in summer and winter, respectively. The mean backscatter coefficient of aerosol layers during spring, summer, autumn and winter were 1.8 ± 1.4 Mm−1sr−1, 2.3 ± 2 Mm−1sr−1, 2.8 ± 2.7 Mm−1sr−1 and 2.3 ± 2.2 Mm−1sr−1, respectively. Aerosol layers in different seasonal are classified by particle depolarization ratio, there are a large amount of non-spherical particles and mixed particles present in spring, autumn and winter, and the mean particle polarization ratio of aerosol layers during spring, summer, autumn and winter were 0.22, 0.06, 0.15 and 0.14, respectively.

Introduction

Tropospheric aerosols influence Earth's radiation budget, climate and weather directly by scattering and absorbing radiation, indirectly by acting as cloud condensation nuclei (Twomey et al., 1977; Twomey et al., 1984; Albrecht et al., 1989; Charlson et al., 1992; Hansen et al., 1997; Kaufman et al., 2002). The spatial and temporal distribution of tropospheric aerosols and the respective aerosol types are poorly understood and represent large uncertainty sources in our current climate models for the prediction of radiative forcing and future climate change. Therefore, a detailed understanding of the regional geometries and optical properties of aerosols is required (Hsu et al., 2000), contribute to a better understanding of the phenomenon and thus provide local aerosol parameterizations for climate models (Sellegri et al., 2003; Osada, 2003).

The contribution of free tropospheric AOD and their direct effects are underestimated. Most aerosols are concentrated in the planetary boundary layer (PBL), and the tropospheric column AOD is expected to be dominated by the PBL, especially in large cities with dense population and industries. However, some research has shown that the contribution of the free tropospheric AOD to the total column tropospheric AOD is considerable. According to the two-year lidar and photometer measurements in Taipe, China, the contribution of aerosols in the free atmosphere on columnar AOD are approximately 44–50% from February–April and approximately 26–37% in other months (Chen et al., 2009). Results from 9 years (2007–2015) datasets of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) aerosol extinction product shows (Bourgeois et al., 2018), the contribution of aerosols in the free troposphere (FT) to atmospheric AOD may be highly underestimated and could reach a global value of greater than 31%.

As a potentially important climate forcing mechanism, it is difficult to quantify the indirect effect of aerosols in the FT on climate. Three aspects are listed here to describe the influences of aerosol layers transport from other areas. First, the transport aerosol layers significantly contribute to the free tropospheric aerosol loading. This portion can be even as large as 90% of the total free tropospheric aerosol content (Müller et al., 2003). Second, the atmospheric lifetime of aerosols is much longer in the FT than in the PBL (Rosen et al., 1997) and could persist for several weeks (Haywood et al., 2000). Longer resident time means longer acting time and more physical and chemical reactions. Schumet et al. (2018) showed that biomass burning of organic aerosols injected into the free troposphere is more persistent than organic aerosols in the boundary layer. Finally, different aerosol chemical and physical properties have different effects on cloud formation. The particle properties of the PBL are closely linked to local sources, while the tropospheric aerosol layers are transported from other areas and even from continental areas (Ansmann et al., 2005). With the great variability in sources and the process of coagulation, mixing, transport, and removal, the size distribution of the particle diameter ranges from a few nanometres to several micrometres and often shows a complex multimodal shape (Damoah et al., 2004; Müller et al., 2003; Wangdinger et al., 2002).

The PBL and FT are not separated while some transport processes occur between the PBL and FT. The PBL is under the direct influence of the Earth's surface, the height of the PBL changes over time and space from several hundred metres to several thousand metres. The atmosphere above PBL is called the FT. Entrainment effect is an important transport process between the PBL and FT. Under strong convective condition, aerosol-rich air masses mix with clean air masses (via updraft and downdraft) near the PBL top, which yields a transition zone between the PBL and the FT known as the “entrainment zone” (Stull, 1988). Mattis et al. (2008) indicate that the aerosol layers separated from the PBL by geometrical thickness of less than approximately 500 m were caused by the entrainment effect. Another important transport process between the PBL and FT is presented here. Aerosols fall from the atmosphere to the surface by gravity, which is known as dry deposition, and the removal efficiency of dry deposition is governed by the particle size and morphology (Zufall et al., 1998). Gobbi et al. (2007) quantified the impact of Saharan dust on surface air quality in Italy. By monitoring the dust optical thickness in the PBL, Hamonou et al. (1999) identified an isolated case of Saharan dust transport to the European PBL. A similar procedure was performed by Rodríguez et al. (2002) and Gerasopoulos et al. (2006), who showed the significance of the Saharan dust contribution to the PM10 levels in the PBL. For other aerosol types, such as forest fires and volcanic eruptions, these particles are often injected into the free troposphere (Preiβler et al., 2013). In addition, pyroconvection and orographic lifting are two regional processes that can transport aerosols from the surface to the FT (Fromm et al., 2006; Yumimoto et al., 2009; Bourgeois et al., 2015). In general, the aerosols in the FT are highly variable in time and space.

Due to the large differences of sources, processes and weather conditions, the aerosol layers can have distinctive regional characteristics. For example, South African observations showed that higher and thicker layers were observed during the second half of the year, which was partly due to increased biomass burning activity (Giannakaki et al., 2015). The layers characteristics of the dry season and wet season show strong contrasts in Manaus, Brazil. An AOD of less than 0.05 at 532 nm was observed in approximately 50% of all measurement cases during the wet season in the Amazon (Baars et al., 2012). Thus, monitoring aerosols from the ground is performed at many sites worldwide to study the aerosols characteristics under different conditions (relative humidity, temperature, wind, and source). The free-tropospheric aerosol layers were investigated and classified over Évora, Portugal, and the layers were highest in summer with an overall mean layer height of (3.8 ± 1.9) km and lowest in winter at (2.3 ± 0.9) km. The mean contributions of the lofted layer were 17% and 22% at 355 and 532 nm, respectively (Preiβler et al., 2013). The geometrical properties and seasonal variations in aerosol particle pollution in the FT at Leipzig, Germany, have been acquired based on the framework of the German Lidar Network (1997–2000) (Mattis et al., 2008). Winker et al. (2012) presented the global 3-D distribution of aerosols as well as the seasonal and interannual variations characterised by CALIPSO. In addition, the EUCAARI project performed measurements in South Africa, China, India and Brazil (Hänel et al., 2012; Komppula et al., 2012).

Lidar is a powerful tool for obtaining the geometries and optical properties of free tropospheric aerosols, and lidar is conducive to long-term observations. Lidar networks have been established to detect aerosols over wide areas, such as the Asian Dust Network (Sugimoto et al., 2008), the European Aerosol Research Lidar Network (Bösenberg et al., 2001, 2003) (EARLINET), the National Institute for Environmental Studies (NIES) Lidar Network (Sugimoto et al., 2006), and the National Aeronautics and Space Administration's (NASA's) Micro-pulse Lidar Network (Welton et al., 2001).

In this study, we focus on the geometrical characteristics and optical properties of aerosol layers and their seasonal variations. Polarization lidar was implemented at our site (30.5°N, 114.4°E, 70 m above sea level) located in the central zone of Wuhan. Wuhan is an industrialized megacity in central China and has a resident population of ~10.2 million. Wuhan is crossed by the Yangtze River and hosts more than one hundred lakes, and Wuhan has a humid subtropical climate with abundant rainfall. The local aerosol sources mainly come from traffic, various industrial activities, and cooking emissions (Van Donkelaar et al., 2010; Ma et al., 2014).

In section 2, the technical aspects of the lidar and data analysis method are described, including the method of determining the PBL height, cloud height and aerosol layer boundaries. In section 3, the statistical analysis of the geometries and optical properties of aerosol layers as well as the monthly free tropospheric AOD and seasonal variations are presented and discussed. In section 4, the discussion and conclusions are presented.

Section snippets

Polarization lidar and its retrieving method

The polarization lidar system located at Wuhan University has a two-channel configuration. The lidar transmitter uses a Nd:YAG laser to produce an emission of 120 mJ per pulse at 532 nm with a repetition rate of 20 Hz. The output laser beam passes through a Brewster polarizer to increase the polarization purity (up to 10000:1). The receiver consists of a Cassegrain telescope with a diameter of 300 mm and a field of view of 1 mrad. After passing through an interference filter (0.3 nm bandwidth),

Results and discussion

One year of lidar data (from 2013) is used for the statistical analysis of the geometries and optical properties of the aerosol layers as well as seasonal variations and contribution of free tropospheric AOD.

Summary and conclusions

Approximately 2760 h data were obtained during ground-based lidar observations at Wuhan, China, in 2013. The geometrical characteristics of the aerosol layer (bottom, top height and thickness) and the optical characteristics (AOD, δp, and mean backscatter coefficient) are statistically analysed. Approximately 68% of the layer's bottom height are below 2 km, while 76% of the layer's top height ranges from 1 km to 4 km. In addition, 61% of the layer's thickness are less than 1 km. Most layers are

CRediT authorship contribution statement

Junyi Shao: Data curation, Methodology, Writing - original draft. Fan Yi: Writing - review & editing. Zhenping Yin: Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research is funded by the National Natural Science Foundation of China through grants 41927804 .The authors gratefully acknowledge the NOAA Air Resources Laboratory for the HYSPLIT transport and dispersion model used in this publication and the University of Wyoming for providing the radiosonde data.

References (80)

  • J. Bösenberg

    EARLINET: a European aerosol research lidar network to establish an aerosol climatology

    For. Rep.

    (2003)
  • Q. Bourgeois et al.

    Aerosol transport over the andes from the Amazon Basin to the remote Pacific ocean: a multiyear CALIOP assessment

    J. Geophys. Res.

    (2015)
  • Q. Bourgeois et al.

    How much of the global aerosol optical depth is found in the boundary layer and free troposphere?

    Atmos. Chem. Phys.

    (2018)
  • I.M. Brooks

    Finding boundary layer top: application of a wavelet covariance transform to lidar backscatter profiles

    J. Atmos. Ocean. Technol.

    (2003)
  • R.J. Charlson et al.

    Climate forcing by anthropogenic aerosols

    Science

    (1992)
  • R. Damoah et al.

    Around the world in 17 days— hemispheric-scale transport of forest fire smoke from Russia in May 2003

    Atmos. Chem. Phys.

    (2004)
  • K.J. Davis et al.

    An objective method for deriving atmospheric structure from airborne lidar observations

    J. Atmos. Ocean. Technol.

    (2000)
  • R.R. Draxler

    Description of the HYSPLIT_4 modeling system

    Tech. Memo. ERL ARL-224

    (1997)
  • R.R. Draxler et al.
    (2003)
  • E.W. Eloranta

    Practical model for the calculation of multiply scattered lidar returns

    Appl. Optic.

    (1998)
  • S. Emeis et al.

    Surface-based remote sensing of the mixing-layer height–a review

    Meteorol. Z.

    (2008)
  • F.G. Fernald

    Analysis of atmospheric lidar observations: some comments

    Appl. Optic.

    (1984)
  • C. Flamant et al.

    Lidar determination of the entrainment zone thickness at the top of the unstable marine atmospheric boundary layer

    Boundary-Layer Meteorol.

    (1997)
  • V. Freudenthaler

    About the effects of polarising optics on lidar signals and the Delta 90 calibration

    Atmos. Meas. Tech.

    (2016)
  • V. Freudenthaler et al.

    Depolarization ratio profiling at several wavelengths in pure Saharan dust during

    SAMUM 2006, Tellus B

    (2009)
  • M. Fromm et al.

    Violent pyro-convective storm devastates Australia's capital and pollutes the stratosphere

    Geophys. Res. Lett.

    (2006)
  • E. Giannakaki et al.

    One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa

    Atmos. Chem. Phys.

    (2015)
  • M.J. Granados‐Muñoz et al.

    Automatic determination of the planetary boundary layer height using lidar: one‐year analysis over southeastern Spain

    J. Geophys. Res.: Atmosphere

    (2012)
  • S. Groß et al.

    Characterization of saharan dust, marine aerosols and mixtures of biomass-burning aerosols and dust by means of multi-wavelength depolarization and Raman lidar measurements during samum 2

    Tellus Ser. B Chem. Phys. Meteorol.

    (2011)
  • E. Hamonou et al.

    Characterization of the vertical structure of Saharan dust export to the Mediterranean basin

    J. Geophys. Res.

    (1999)
  • A. Hänel et al.

    One‐year aerosol profiling with EUCAARI Raman lidar at Shangdianzi GAW station: Beijing plume and seasonal variations

    J. Geophys. Res.: Atmosphere

    (2012)
  • J. Hansen et al.

    Radiative forcing and climate response

    J. Geophys. Res.

    (1997)
  • J. Haywood et al.

    Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: a review

    Rev. Geophys.

    (2000)
  • Y. He et al.

    Dust aerosols detected using a ground-based polarization lidar and CALIPSO over Wuhan (30.5 N, 114.4 E), China

    Adv. Meteorol.

    (2015)
  • N.C. Hsu et al.

    Determination of radiative forcing of Saharan dust using combined TOMS and ERBE data

    J. Geophys. Res. Atmos.

    (2000)
  • H.G. Hughes et al.

    Sensitivity of a lidar inversion algorithm to parameters relating atmospheric backscatter and extinction

    Appl. Optic.

    (1985)
  • D.N. Kafle et al.

    Micropulse lidar-derived aerosol optical depth climatology at ARM sites worldwide

    J. Geophys. Res.: Atmosphere

    (2013)
  • Y.J. Kaufman et al.

    A satellite view of aerosols in the climate system

    Nature

    (2002)
  • M. Komppula et al.

    One year of Raman-lidar measurements in Gual Pahari EUCAARI site close to New Delhi in India–Seasonal characteristics of the aerosol vertical structure

    Atmos. Chem. Phys.

    (2012)
  • W. Kong et al.

    Convective boundary layer evolution from lidar backscatter and its relationship with surface aerosol concentration at a location of a central China megacity

    J. Geophys. Res.: Atmosphere

    (2015)
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