Long-term profiling of aerosol light-extinction, particle mass, cloud condensation nuclei, and ice-nucleating particle concentration over Dushanbe, Tajikistan, in Central Asia

For the first time, continuous vertically resolved long-term aerosol measurements were conducted with a state-of-the-art multiwavelength lidar over a Central Asian site. Such observations are urgently required in efforts to predict future climate and environmental conditions and to support spaceborne remote sensing (ground truth activities). The lidar observations were performed in the framework of the Central Asian Dust Experiment (CADEX) at Dushanbe, Tajikistan, from March 2015 to August 5 2016. An AERONET sun photometer was operated at the lidar field site. During the 18-month campaign, mixtures of continental aerosol pollution and mineral dust were frequently detected from ground to cirrus height level. Regional sources of dust and pollution as well as long-range transport of mineral dust mainly from Middle East and the Saharan deserts determine the aerosol conditions over Tajikistan. In this study, we summarize our findings and present seasonally resolved statistics regarding aerosol layering (main aerosol layer depth, lofted layer occurrence), optical properties (aerosol and dust optical thicknesses 10 at 500-532 nm, vertically resolved light-extinction coefficient at 532 nm), profiles of dust and non-dust mass concentration and dust fraction, and profiles of particle parameters relevant for liquid-water, mixed-phase cloud and cirrus formation such as cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentration. The main aerosol layer over Dushanbe reaches typically 4-5 km height in spring to autumn. Frequently lofted dust-containing aerosol layers were observed at heights from 5-10 km, indicating a sensitive potential of dust to influence cloud ice formation. Typical dust mass fractions were of 15 the order of 60–80%. A considerable fraction is thus anthropogenic pollution and biomass burning smoke. The highest aerosol pollution levels (in the relatively shallow winter boundary layer) occur during the winter months. The seasonal mean 500 nm AOT ranges from 0.15 in winter to 0.36 in summer during the CADEX period (March 2015 to August 2016), DOTs were usually below 0.2, seasonally mean particle extinction coefficients were of the order of 100–500 Mm−1 in the main aerosol layer during the summer half year, and about 100-150 Mm−1 in winter, but mainly caused by anthropogenic haze. Accordingly, the 20 highest dust mass concentrations occur in the summer season (200-600 μg m−3) and the lowest during the winter months (2050 μg m−3) in the main aerosol layer. In winter, the aerosol pollution mass concentrations were 20-50 μg m−3, while during the summer half year (spring to autumn) the mass concentration caused by urban haze and biomass burning smoke decreases to 10-20 μg m−3 in the lower troposphere. The CCN concentration levels are always controlled by aerosol pollution. The INP 1 https://doi.org/10.5194/acp-2019-963 Preprint. Discussion started: 13 December 2019 c © Author(s) 2019. CC BY 4.0 License.

aerosol optical properties and dust mass concentration in combination with vertically resolved dust source identification for representative aerosol scenarios were discussed based on case studies. The final results of this campaign are presented in this article (in Sect. 3). More than 300 individual (day by day) nighttime observations are analyzed and cover well the annual cycle of dust and aerosol pollution layering. As a follow-up project, we recently build a containerized Polly instrument and deployed this new lidar at Dushanbe (June 2019) for long term observations over the next 5-10 years. In addition, we organized the first 5 Central Asian Dust Conference (CADUC 2019, 8-12 April 2019) to emphasize the importance of Central Asian pollution and dust in the global climate system and need for more research in this region (Althausen et al., 2019).
The article is structured as follows: In Sect. 2, we briefly provide technical details to the Polly lidar and the data analysis. The POLIPHON (Polarization Lidar Photometer Networking) data analysis scheme Ansmann, 2016, 2017;Ansmann et al., 2019b) was applied to derive aerosol-type-dependent particle optical properties, dust and non-dust (haze, smoke) mass 10 concentrations profiles, and cloud-process-relevant aerosol parameters such as cloud condensation nucleus (CCN) and icenucleating particle (INP) concentrations. In Sect. 4, the main findings are discussed and summarized. Concluding remarks are given in Sect. 5.

CADEX lidar data analysis
During the 18-month CADEX campaign, a Polly-type multiwavelength polarization/Raman lidar En-15 gelmann et al., 2016;Hofer et al., 2017) was operated in Dushanbe, Tajikistan. The Dushanbe lidar station is part of PollyNET, a network of permanent or campaign-based Polly lidar stations (Baars et al., 2016) and is the first outpost of the European Aerosol Research Lidar Network (EARLINET) (Pappalardo et al., 2014). The polarization Raman lidar permits us to measure height profiles of the particle backscatter coefficient at the laser wavelengths of 355, 532 and 1064 nm wavelength, particle extinction coefficients at 355 and 532 nm by means of 387 and 607 nm nitrogen Raman signal profiling, the particle linear 20 depolarization ratio at 355 and 532 nm by means of additional cross-polarized lidar return detection at 355 and 532 nm, and of the water-vapor-to-dry-air mixing ratio by using the Raman lidar return signals at 407 nm (water vapor channel) and 387 nm nitrogen Raman channel (e.g., Mattis et al., 2004;Baars et al., 2012;Engelmann et al., 2016;Hofer et al., 2017;Dai et al., 2018). Technical details of the lidar system are described in Engelmann et al. (2016). The specifically used Polly, the field site and the CADEX measurement campaign including ancillary instrumentation are described in Hofer et al. (2017). 25 The lidar observations were manually analyzed. During the 18-month CADEX campaign (535 days), the Polly lidar acquired data at 487 days for at least a 3 h time period. To achieve a representative coverage of aerosol conditions, profiles were calculated on a day-by-day basis for each night at which the application of the Raman lidar methods was possible, i.e., when low clouds and fog was absent. For the most favorable measurement period, the collected signal profiles were averaged, typically over 60-180 minutes, and corrected for background noise and system-dependent effects, such as the incomplete 30 overlap between laser beam and receiver field-of-view in the lowermost 1.5 km above the lidar (Hofer et al., 2017). Raman lidar profiles of the particle extinction coefficient and extinction-to-backscatter ratio (lidar ratio) at 355 and 532 nm could be obtained for 276 nights.
The 532 nm particle backscatter coefficient and linear depolarization-ratio profiles are input in the POLIPHON (polarization lidar photometer networking) data analysis to derive height profiles of dust mass concentration, dust mass fraction, INPrelevant aerosol parameters, and of CCN and INP concentrations Ansmann, 2016, 2017). The POLIPHON methodology could be applied to 328 nighttime observations. The technique was recently discussed with focus on desert dust by Ansmann et al. (2019b). A case study from Dushanbe was shown in that article to provide an overview about the potential 5 of the POLIPHON method. Thus, only a brief description is given here.
In a first step, dust and non-dust optical and associated microphysical properties are separated based on typical particle linear depolarization ratio values (Müller et al., 2007;Tesche et al., 2009) for dust (0.31) and non-dust (≤0.05). In Central Asia, the non-dust aerosol component covers contributions of anthropogenic haze and biomass burning smoke. The separated backscatter profiles are converted into dust and aerosol-pollution extinction profiles by using typical lidar ratio values for Central Asian, 10 Middle East, and eastern Saharan dust of (30-40 sr 40 sr) and for Central Asian aerosol pollution (40-50 sr 50 sr) (Hofer et al., 2017). The lidar-ratio observations will be presented in a follow-up article.
The dust and non-dust extinction profiles are then directly converted to number, volume and surface-area concentration profiles by means of the conversion factors listed in Table 2. In this article, we mainly concentrate on the retrieval of height profiles of dust mass concentrations and cloud-relevant dust properties (CCN and INP concentration). The required dust conversion 15 factors and parameters are derived from extended Aerosol Robotic Network (AERONET) observations at Dushanbe (Ansmann et al., 2019b). For the non-dust extinction-to-volume conversion, we used typical fine-mode conversion factors as presented by Mamouri and Ansmann (2017) for Central Europe (Leipzig, Germany). Similarly, we used Leipzig conversion parameters to obtain estimates for the non-dust CCN concentrations for Dushanbe, but assumed aerosol pollution background conditions, i.e., a factor of 2 less fine-mode particles for a given non-dust extinction coefficient then in highly polluted Central Europe 20 (Haarig et al., 2019a). Volume concentration profiles are converted to mass concentration profiles by using generic densities of dust (2.6 g cm −3 ) and non-dust (1.5 g cm −3 ) . To finally estimate INP concentrations for the most relevant ice nucleation modes (immersion freezing, deposition nucleation) (Mamouri and Ansmann, 2016), parameterizations are applied with dust particle number concentration n 250,d (considering particles with radius larger than 250 nm only) as input to obtain immersion-freezing INP concentrations (DeMott et al., 2015) and dust particle surface-area concentration s d as input 25 to obtain deposition-nucleation INP concentrations (Ullrich et al., 2017). In the latter retrieval, the ice super saturation level during the ice crystal nucleation process is required and a typical value of 1.15 (115% relative humidity over ice) is assumed.
Dust CCN concentrations are estimated from profiles of number concentration of dust particles with a radius larger than 100 nm n 100,d (Ansmann et al., 2019b;Lv et al., 2018). In the estimation of the aerosol-pollution-related CCN concentration, the dry activation radius is assumed to be 50 nm. The respective conversion parameter C n60,c in Tab. 2 with index 60 considers that 30 particles at ambient aerosol conditions are usually slightly larger than dry particles. The conversion factor C n60,c assumes that hygroscopic haze particles with radius >60 nm (at ambient conditions) are representing dry haze particles with dry radius of > 50 nm. For the n 100,d and n 50,c conversions, the exponents b d and b c are used (Tab. 2) The Dushanbe lidar site was collocated with an AERONET sun photometer station (AERONET, 2019;Holben et al., 1998) which is operated since 2010 (Abdullaev et al., 2012). The sun photometer provides AOT at 8 wavelengths and further particle optical and microphyical properties retrieved from the column-integrated daytime measurement (Hofer et al., 2017).
As auxiliary meteorological observations we used GDAS (Global Data Assimilation System) temperature and pressure profiles from the National Weather Service's National Centers for Environmental Prediction (NCEP) for the coordinates of 5 39 • N and 69 • E (GDAS modeling resolution of 1 • ) (GDAS, 2019). The temperature and pressure profiles are required in the lidar data analysis for the correction of air backscatter and extinction effects and also, e.g., in the computation of relative humidity from the water-vapor mixing ratio profile (Dai et al., 2018).
Furthermore, the HYSPLIT model (Hybrid Single Particle Lagrangian Integrated Trajectory Model) (HYSPLIT, 2019;Stein et al., 2015;Rolph, 2016) based on 1 • GDAS reanalysis data was used to calculate backward trajectories. From March 2015 to 10 August 2016 daily 120 h backward trajectories were calculated for Dushanbe arrival heights of 1. 5, 2.5, 4.5 and 7.5 km (above ground level, a.g.l.). To describe the general air mass origin and the long-range transport features over Dushanbe, a seasonally resolved HYSLPIT cluster analysis was performed based on the backward trajectories from 2009-2018. The main results are shown in the next section.

Aerosol layering and main aerosol transport features
Based on the 328 aerosol profiles, we analyzed the annual cycle of aerosol layering in the lower, middle, and upper troposphere over Dushanbe. By visual inspection, we found two main regimes: (a) the main aerosol layer that typically extends from the surface to about 3-6 km height and contributes to 500 nm AOT by usually more than 90%, and (b) frequently occurring thin dust layers between 5 and 10 km height that mainly contained aerosol from remote source regions such as the Arabian deserts 20 and Saharan desert. We call the top height of the highest layer containing dust the uppermost aerosol layer top in the following discussion. A measurement example of this layering is shown in Fig. 2.
Besides the visual inspection of the lidar backscatter profiles, we tested several automated top-height detection methods. The most useful approaches (three in total) are considered in Fig. 2b and c. The first technique searches for the height (of the main layer) at which the backscatter coefficient (bsc) at 1064 nm wavelength drops below a threshold value of 2.5e-5 m −1 sr −1 (in 25 Fig. 2b) for the first time above a starting height of, e.g., 500 m above the lidar. The second approach analyses the 1064 nm backscatter ratio (ratio of total-to-Rayleigh backscatter) profile and uses a threshold value (bsc ratio) of 1.8 (in Fig. 2c). The agreement between the different results is good.
In Fig. 2b, the blue dashed horizontal line shows the height level at which the integrated backscatter coefficient (IB, column backscatter) from the surface up to this specific height reaches 90% of the total column backscatter value IB (third method).

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The 90%IB height level of about 4 km means that most of the aerosol is in the main aerosol layer reaching to about 5 km on this day. The depolarization ratios for 355 and 532 nm in Fig. 2c, are far below the depolarization ratios for pure dust of 0.25 (355 nm) and 0.30 (532 nm) and thus indicate a mixture of mineral dust and air pollution. The top heights of the detected uppermost dust layer also vary strongly and indicate the frequent occurrence of dust traces up to the upper troposphere from late winter (February) to autumn (October). Such lofted layers are seldom during November to January. Although optically thin, dust layers in the middle and upper troposphere may have a sensitive impact on ice formation in mixed phase and ice clouds (Ansmann et al., 2019a). Figure 4 provides a statistical overview of the top heights of the main 10 and uppermost layer for the entire 18-month measurement period. Table 3 summarizes the seasonal mean top heights of the main aerosol layer and the detected highest layer in the troposphere.
The results obtained by case-by-case visual inspection and by applying the automated retrievals for the main layer depth are in good agreement (mostly within a range of 10% deviation). The seasonal means for the 90%IB level height indicate that most of the time the aerosol within the main layer ( Fig. 2b) contributes 90% or even more to the overall IB or AOT (as will be shown 15 later). As a consequence, we may conclude from the height-resolved observations that many snow-covered (glaciated) regions of Central Asia (Pamir mountains, Tien Shan) located at heights below 5 km (Treichler et al., 2018) are continuously exposed to dust and aerosol pollution during the summer half year. During the summer season, again regional air mass transport prevails (Fig. 5b,clusters 2,3,and 4,80%) in the main aerosol layer. Source regions are Uzbekistan, western Tajikistan, Aralkum Desert, and southern Kazakhstan. Regarding the upper tropospheric air mass transport Fig. 5c shows that the aerosol originates mainly (62%) from Middle East deserts (cluster 5) and 25 North Africa (clusters 2 and 4), but also from polluted Mediterranean (cluster 1) and eastern European regions (cluster 3).
The cluster analysis suggests that the air masses are transported further to the east, crossing eastern Asia, continuously diluting, but mixing with new dust and pollution over China, and traveling across the Pacific. The upper tropospheric dust and aerosol pollution mixtures as observed over the lidar station at Dushanbe will become part of the northern hemispheric upper tropospheric aerosol background reservoir that influences cirrus formation and precipitation processes on continental to 30 hemispheric scales.

Aerosol optical properties: AOT, DOT, and particle extinction profile
The characterization of the aerosol optical properties is based on the lidar and AERONET sun photometer observations. Figure 6 provides an overview of the basic optical properties obtained from the lidar measurements. For the comparison with AERONET products (column-integrated values), the lidar-derived 532 nm AOT was determined from the particle extinction profile in Fig. 6b. By means of the Raman lidar method (Ansmann et al., 1992;Baars et al., 2012) the 355 and 532 nm particle extinction coefficients are directly computed from the respective 387 and 607 nm nitrogen Raman signal profiles for heights >1 km above the lidar. The large uncertainty in the correction of the incomplete laser-beam receiver field-of-view overlap prohibits a trustworthy extinction coefficient retrieval from the nitrogen Raman signal profiles in the near range, i.e., for the lowest 5 1000 m above the lidar. To extend the particle extinction profiles towards the ground, we use the 532 nm particle backscatter coefficient in Fig. 6a. This quantity is obtained from ratio of the elastic backscatter signal to the respective nitrogen Raman backscatter signal (Ansmann et al., 1992;Baars et al., 2012) so that overlap effects widely cancel out. The 532 nm particle backscatter coefficients are trustworthy down to about 100 m above the lidar. We estimate the respective particle extinction coefficient for heights below 1-1.5 km by multiplying the backscatter coefficient with the lidar ratio of the actual measurement, in 10 the present case measured at about 1.4 km height as shown in Fig. 6c and indicated by a dashed magenta line. The 532 nm AOT is finally obtained by the integration of the entire extinction profile up to 6 km height. In this way, we obtained 276 nighttime extinction profiles. Residual AOT contributions from heights above 6 km were usually <0.02.
To check the accuracy of lidar-derived AOT values we compared the lidar-derived AOTs with respective AERONET 500 nm AOTs measured with the sun photometer in the afternoon, preferably close to sunset. For this purpose, 192 lidar extinction 15 profiles were computed. The averaging time ranged from 15 min to 1 h 40 min with an average of about one hour. The temporal distance to the last AERONET measurement ranged from 2 hours to about 5 hours. Figure 7 shows the comparison. The agreement is acceptable. A small bias is observed and most probably related to the fact that the AERONET observations are is the potential to separate the dust from non-dust backscattering and thus to obtain an accurate estimate of the dust optical thickness (DOT). The distribution of DOT is given in Fig. 8c. Most DOT values are ≤0.2. This is in agreement with findings of Li and Sokolik (2018). These authors concluded from in-depth analysis of long-term spaceborne passive remote sensing over Central Asia that most DOTs are below 0.2 at 550 nm. Higher AOTs over western than over eastern Tajikistan were observed and as a general finding, more dust was observed in the western parts of Central Asia (closer to the Caspian Sea) than in the eastern parts. The dust and non-dust aerosol fractions of the total aerosol burden is further discussed in the next sections. and contributes by about 50% to AOT in spring and summer and to 80% during the winter months. The remaining part of the main aerosol layer (from about 1.5 to 4.5 km height) causes almost the entire residual AOT contribution. Only 10% of the AOT is caused by particles in the middle and upper troposphere during spring. 20 The 18-month climatology for the 532 nm extinction coefficient is shown in Fig. 10. The figure is based on the 276 height profiles discussed above. Typical particle extinction values are 25-50 Mm −1 in spring and autumn, 50-100 Mm −1 in summer, and 50-150 Mm −1 during the winter season. According to the shown seasonal mean extinction profiles, the main aerosol layer reaches up to 5-5.5 km in spring, summer autumn and to about 2 km in winter. A moderate atmospheric variability in terms of particle extinction is observed in spring, autumn and winter, but a strong variability is found during the summer season.

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This is the result of partly major dust storms with extreme particle extinction values of the order of 1500 Mm −1 and related horizontal visibilities of 2 km and less. Near-surface extinction values are highest in winter during the domestic heating period.
The pollution is then trapped in the shallow aerosol layer with depth of 2 km only.

Aerosol microphysical and cloud-relevant properties: Profiles of mass, CCN and INP concentrations
The POLIPHON method permits the conversion of dust and non-dust extinction coefficients into height profiles of dust and 30 non-dust mass, CCN, and INP concentration. The full retrieval procedure, starting from the basic data sets of 532 nm particle backscatter and linear depolarization ratio profiles is described in Sect. 2 and shown in Fig. 11. Recently, the required conversion parameters factors for mineral dust were updated and include now Central Asian and Middle East dust conditions (Ansmann et al., 2019b). The measured particle depolarization ratio at 532 nm was close to 0.3 at heights above 3 km and indicated the presence of an almost pure dust layer up to 8 km height. Only in the lower part (below 2.5 km height) the depolarization ratio dropped below 0.2 and indicates a mixture of mineral dust, aerosol pollution (urban industrial particles, biomass burning smoke), and continental background aerosol. This case was already discussed by Hofer et al. (2017).
In the shown example, the dust mass concentration was low (<25 µg m −3 ) in the polluted layer and >150 µg m −3 in the center of the lofted dust layer. The mass concentration of continental aerosol pollution was much lower with values <5 µg m −3 5 throughout the troposphere. The estimated profiles for the dust and non-dust CCN concentrations show values of up 300 cm −3 in the center of the lofted dust plume and a total CCN concentration of about 150 cm −3 in the polluted layer below 2 km height (see Fig. 11c). By means of the derived height profiles of dust particle number concentration considering particles with radius >250 nm only and the dust particle surface area concentration in Fig. 11 together with the respective GDAS temperature profile, the profile segments for the INP concentrations are obtained in Fig. 11e. We distinguish profiles relevant for immersion freezing  show dust from the surface up to 10 km height (Fig. 13h). As can be seen, the profile-mean dust mass fraction is in most cases 70-80%. The dust mass fraction typically decreases with height from 90% to about 50% in the uppermost part of the profile.
The other way around, the anthropogenic aerosol mass fraction is always of the order of 20-30% in the main aerosol layer up to 4-5 km height, and also in the lofted dust layers higher up (5-10 km height range). This is in consistency with the DOT and

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AOT mean values and DOT/AOT ratios discussed above. Figure 14 highlights the decreasing number of dust cases (available for dust profile averaging up to a given top height) with increasing height. Figure 14 is similar to Fig. 13, but considers a higher resolution concerning the defined top heights in the averaging procedure. The main result is a very smooth, decreasing curve for the frequency of occurrence of dust layers. In terms of the number of observed dust cases, close to 100% (with 80% mean dust mass fraction) out of all 328 nighttime profiles 35 show dust up to 3 km top height, as already mentioned above, 65% in the case of the 5 km top height (mean dust fraction of 74%), and only a few cases of dust (<10%) when the defined top height is >9 km.  The results for CCN concentrations in Fig. 15 show that dust particles lead to mean dust CCN concentrations of the order of   from 8-10 km height (ice cloud and deposition nucleation regime). In autumn and winter, the seasonal means indicate a rather 25 low potential for heterogeneous ice formation at the given height levels.

Conclusion/Outlook
Deteriorating environmental conditions expressed by melting glaciers, desiccating lakes and strong risks for further severe changes in near future, and on the other hand side the lack of advanced aerosol observations in Central Asia was the motivation for the 18-month CADEX campaign. The main results were presented here. For the first time, vertical profiling of the 30 annual cycle of aerosol conditions over Dushanbe, Tajikistan with a state-of-the-art multiwavelength aerosol lidar was conducted. By applying modern data analysis techniques the mixtures of mineral dust and anthropogenic aerosol pollution were described in terms of DOT, AOT, seasonal mean height profiles of 532 nm particle extinction coefficient, dust and non-dust mass concentration and dust fraction profiles, as well as in terms of cloud-relevant aerosol properties such as large particle number concentration n 250 , particle surface area concentration, CCN and INP concentrations. These latter parameters describe the impact of aerosols on cloud formation processes. The Dushanbe lidar long term study demonstrates the strong potential of modern lidar instruments to contribute to aerosol and aerosol-cloud interaction research, and environmental (air quality) monitoring. 5 The key results can be summarized as follows. The main aerosol layer over Dushanbe (which may be a representative site for Central Asia) reaches typically 4-5 km height in spring to autumn so that most of the local glacier regions are exposed to polluted and dusty air throughout the year, except the winter period. Frequently lofted dust-containing aerosol layers were observed at heights from 5-10 km, indicating a sensitive potential of dust to influence cloud ice formation. Typical dust mass fractions were of the order of 60-80%, i.e., a considerable part of the aerosol is anthropogenic pollution and biomass burning itoring, we also need more ground-based systems in this region of the world for an improved stratospheric aerosol monitoring.
Step Description 1 Retrieval of particle backscatter coefficient and particle linear depolarization ratio profiles at 532 nm wavelength 2 Separation of dust and non-dust backscatter coefficients using thresholds of the particle depolarization ratio for dust and non-dust 3 Conversion to dust and non-dust extinction coefficients from dust and non-dust particle backscatter coefficients using dust and non-dust lidar ratios 4 Conversion to dust and non-dust particle mass, number, and surface area concentrations from dust and non-dust extinction coefficient and temperature (immersion freezing), and using dust surface area concentration and temperature (deposition nucleation) Table 2. Applied values of the conversion parameters required in the POLIPHON retrieval Ansmann, 2016, 2017;Ansmann et al., 2019b). The conversion factors are explained in the text and are needed to convert particle extinction coefficients into particle mass concentrations and cloud-relevant parameters (CCN and INP concentrations      c) MAM 7.5 km a.g.l.   DOT is obtained from the height profile of the dust-related backscatter coefficient multiplied by a typical dust lidar ratio of 35 sr.