Aerosol layers in the free troposphere and their seasonal variations as observed in Wuhan, China
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, , 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)
- et al.
Columnar optical properties of tropospheric aerosol by combined lidar and sunphotometer measurements at taipei, China
Atmos. Environ.
(2009) - et al.
Origin and variability of particulate matter (PM10) mass concentrations over the Eastern Mediterranean
Atmos. Environ.
(2006) - et al.
Estimating theimpact of Saharan dust on the year 2001 PM10 record of Rome, Italy
Atmos. Environ.
(2007) - et al.
Nabro aerosol evolution observed jointly by lidars at a mid-latitude site and CALIPSO
Atmos. Environ.
(2016) Aerosols, cloud microphysics, and fractional cloudiness
Science
(1989)- et al.
Ice formation in Saharan dust over central Europe observed with temperature/humidity/aerosol Raman lidar
J. Geophys. Res.: Atmosphere
(2005) - et al.
Continuous monitoring of the boundary-layer top with lidar
Atmos. Chem. Phys.
(2008) - et al.
Aerosol profiling with lidar in the amazon basin during the wet and dry season
J. Geophys. Res. Atmos.
(2012) - et al.
Calculation of the calibration constant of polarization lidar and its dependency on atmospheric temperature
Optic Express
(2002) - et al.
EARLINET: a European aerosol research lidar network
Adv. Laser Rem. Sens.
(2001)
EARLINET: a European aerosol research lidar network to establish an aerosol climatology
For. Rep.
Aerosol transport over the andes from the Amazon Basin to the remote Pacific ocean: a multiyear CALIOP assessment
J. Geophys. Res.
How much of the global aerosol optical depth is found in the boundary layer and free troposphere?
Atmos. Chem. Phys.
Finding boundary layer top: application of a wavelet covariance transform to lidar backscatter profiles
J. Atmos. Ocean. Technol.
Climate forcing by anthropogenic aerosols
Science
Around the world in 17 days— hemispheric-scale transport of forest fire smoke from Russia in May 2003
Atmos. Chem. Phys.
An objective method for deriving atmospheric structure from airborne lidar observations
J. Atmos. Ocean. Technol.
Description of the HYSPLIT_4 modeling system
Tech. Memo. ERL ARL-224
Practical model for the calculation of multiply scattered lidar returns
Appl. Optic.
Surface-based remote sensing of the mixing-layer height–a review
Meteorol. Z.
Analysis of atmospheric lidar observations: some comments
Appl. Optic.
Lidar determination of the entrainment zone thickness at the top of the unstable marine atmospheric boundary layer
Boundary-Layer Meteorol.
About the effects of polarising optics on lidar signals and the Delta 90 calibration
Atmos. Meas. Tech.
Depolarization ratio profiling at several wavelengths in pure Saharan dust during
SAMUM 2006, Tellus B
Violent pyro-convective storm devastates Australia's capital and pollutes the stratosphere
Geophys. Res. Lett.
One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa
Atmos. Chem. Phys.
Automatic determination of the planetary boundary layer height using lidar: one‐year analysis over southeastern Spain
J. Geophys. Res.: Atmosphere
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.
Characterization of the vertical structure of Saharan dust export to the Mediterranean basin
J. Geophys. Res.
One‐year aerosol profiling with EUCAARI Raman lidar at Shangdianzi GAW station: Beijing plume and seasonal variations
J. Geophys. Res.: Atmosphere
Radiative forcing and climate response
J. Geophys. Res.
Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: a review
Rev. Geophys.
Dust aerosols detected using a ground-based polarization lidar and CALIPSO over Wuhan (30.5 N, 114.4 E), China
Adv. Meteorol.
Determination of radiative forcing of Saharan dust using combined TOMS and ERBE data
J. Geophys. Res. Atmos.
Sensitivity of a lidar inversion algorithm to parameters relating atmospheric backscatter and extinction
Appl. Optic.
Micropulse lidar-derived aerosol optical depth climatology at ARM sites worldwide
J. Geophys. Res.: Atmosphere
A satellite view of aerosols in the climate system
Nature
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.
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
Cited by (11)
Enhancement in free-tropospheric aerosol loading over India
2022, Atmospheric EnvironmentCitation Excerpt :Globally, free-tropospheric contribution to total columnar aerosol abundance is reported to be ∼31% (62%) in day time (night time) (Bourgeois et al., 2018). However, effects of free-tropospheric aerosols in Earth's climate system are reported to be underestimated (Shao et al., 2020). Presence of continental aerosols, such as smoke and dust particles, are reported in the free-tropospheric altitudes over several regions (Bourgeois et al., 2018; Padmakumari et al., 2013).
Horizontally oriented ice crystals observed by the synergy of zenith- and slant-pointed polarization lidar over Wuhan (30.5°N, 114.4°E), China
2021, Journal of Quantitative Spectroscopy and Radiative TransferCitation Excerpt :The gain ratio between two polarized channels is obtained based on the Δ90° method given by Freudenthaler et al. [23]; the relative error of volume polarization ratio δ (aerosol + molecular) is less than 5%. The lidar system has been routinely operated since October 2010 and is widely used for aerosol observations [24–26]. Especially, process-level ice formation in the local atmosphere [27], ice virga falling out of their parent cloud [28], and dust-related heterogeneous nucleation of midlevel clouds [29] were studied by using this polarization lidar.
Asian dust impacts on heterogeneous ice formation at Wuhan based on polarization lidar measurements
2021, Atmospheric EnvironmentCitation Excerpt :Dust particles are advected from Gobi desert in the north and Taklamakan desert in the northwest (see Fig. 1), and are transported by cold fronts or by westerly winds (Tsai et al., 2008). Anthropogenic aerosol are either produced locally or transported from industrial cities nearby (Shao et al., 2020). Biogenic aerosol, especially pollen, could also have some contributions, considering of the vast surrounded farmland and forest.
Investigating the relationship between aerosol and cloud optical properties inferred from the MODIS sensor in recent decades over East China
2020, Atmospheric EnvironmentCitation Excerpt :Further, the decreasing tendencies in AOD and AE during summer was observed in the northern parts of the study domain (over the western Shandong province), denotes the dominance of coarse-mode particles due to dust aerosols coming from the deserts (Taklimakan and Mongolia), with the prominence of sea salt aerosols from the East and South of China Sea. These results are consistent, and agreement with the previous investigations observed over entire China (Luo et al., 2014; Kang et al., 2016; Hu et al., 2018; Shao et al., 2020). The spatial (Fig. 6) and temporal (Fig. 7 and Table 3) distributions of different cloud parameters (COT, CF, CER, CTT, and CTP) over East China were analyzed using the long-term (2000–2017) MODIS Terra satellite data.