Aerosol Science and Engineering

, Volume 1, Issue 4, pp 160–168 | Cite as

Seasonal Transport and Dry Deposition of Black Carbon Aerosol in the Southeastern Tibetan Plateau

  • Qiyuan Wang
  • Zhuzi Zhao
  • Jie Tian
  • Chongshu Zhu
  • Haiyan Ni
  • Yonggang Zhang
  • Ningning Zhang
  • Zhenxing Shen
  • Yongming Han
  • Junji Cao
Original Paper
  • 212 Downloads

Abstract

To investigate the regional transport and dry deposition of black carbon (BC) aerosol in the southeastern Tibetan Plateau, continuous equivalent BC (eBC) mass concentrations were measured at a high-altitude remote site of Lulang from July 2008 to July 2009. The bivariate polar plots for eBC mass concentrations showed that large eBC values were often associated with low winds (< 2 m s−1) during the pre-monsoon, post-monsoon, and winter seasons. Moreover, strong winds (> 4 m s−1) from southeast or northeast also contribute to the large eBC loadings during the pre-monsoon, monsoon, and post-monsoon seasons. The concentration-weighted trajectory analysis showed that emissions from the eastern Kingdom of Bhutan, Assam of India, and southern Shannan Prefecture of Tibet had the most important contributions to the eBC pollution at Lulang during the pre-monsoon and monsoon seasons. In contrast, the eBC potential source region shifted to the east and southeast of Lulang during the post-monsoon and to the north India and northwest Nepal during the winter. The estimated eBC deposition rate was the highest for the pre-monsoon (6.3–62.6 μg eBC m−2 day−1), followed by the post-monsoon (4.6–45.9 μg eBC m−2 day−1), winter (4.3–43.1 μg eBC m−2 day−1), and monsoon (2.4–24.5 μg eBC m−2 day−1). Further calculations of eBC concentrations in the snow surface were 33.3–333.2, 61.5–614.7, 27.0–269.9, and 58.8–587.6 μg kg−1 during the pre-monsoon, monsoon, post-monsoon, and winter seasons, respectively, which resulted in the snow albedos being reduced by 2.6–25.3, 4.7–46.6, 2.1–20.5, and 4.5–44.5% accordingly.

Keywords

Black carbon Regional transport Dry deposition Tibetan Plateau 

1 Introduction

Black carbon (BC) aerosol is a major particulate light-absorbing substance in the atmosphere (Bond et al. 2013). It is a by-product produced during incomplete combustion processes, including natural and anthropogenic sources (e.g., biomass burning and fossil fuel combustion) (Petzold et al. 2013). BC has substantial effect on the global climate due to its strong absorption of solar radiation, and it has been considered as the second strongest warming forcing agent after carbon dioxide (CO2) (Jacobson 2001; Ramanathan and Carmichael 2008; Bond et al. 2013). BC can further act as cloud condensation nuclei or enhance the evaporation rates in cloud layers, indirectly causing changes in climate (Nenes et al. 2002; Wang 2004). In addition, BC greatly damages air quality (Cao et al. 2012; Wang et al. 2013; Ding et al. 2016), and poses threat to human health (Jansen et al. 2005; Grahame et al. 2014). Since BC has a shorter lifetime compared to other greenhouse gases (e.g., CO2), its reduction can potentially provide a fast solution to mitigate near-term global warming, as well as to improve air pollution, and be beneficial to human health and food security simultaneously (Quinn et al. 2008; Grieshop et al. 2009; Jacobson 2010; Shindell et al. 2012; Bond et al. 2013).

The Tibetan Plateau (TP), covering an area of ~ 2,500,000 km2, is known as the “Third Pole” of the Earth. It holds the largest volume of ice at the low and middle altitudes (Qiu 2008). Serving as the “Water Tower of Asia”, the TP provides critical freshwater source for several major rivers including the Indus, Ganges, Brahmaputra, Yangtze, and Yellow River. These rivers are the lifelines to billions of people living in the downstream (Immerzeel et al. 2010). However, observations and modeling studies show that snowpack and glaciers in the TP have been undergoing rapid melting and shrinking (William et al. 2010; Lee et al. 2013; Loibl et al. 2014; Jacobi et al. 2015; Li et al. 2016; Xu et al. 2016; Ke et al. 2017). Re-analysis of the TP Landsat images and satellite altimetry data show that the glacier area in this region experienced notable shrinkage at a rate of − 0.31 ± 0.04 km2 year−1 during 1976–2013 (Ke et al. 2017). Li et al. (2016) employed multiple remote sensing data to investigate the changes of glaciers in the Dupuchangdake region of northwestern Tibet, and found that the glacier area in this region decreased from 409 to 393 km2 from 1991 to 2013.

BC is an important contributor to the observed rapid glacier retreat (Xu et al. 2009a). Once deposited on snow and ice in the TP, BC can significantly decrease the surface albedo, causing an aggravated surface melting (Ming et al. 2009, 2013; Xu et al. 2009b; Nair et al. 2013; Ménégoz et al. 2014; Qu et al. 2014). Ming et al. (2013) calculated that BC in the winter snowpack reduced the albedo by 11% in the Nam Co region in central Tibet. Qu et al. (2014) reported that the albedo of the Zhadang glacier decreased at a rate of − 0.003 a−1 from 2001 to 2012, and the contribution of BC to albedo reduction was 36% when the glacier was covered by aged snow.

Although anthropogenic activities in the TP are sparse, this region is surrounded by a number of strong BC source areas, including India and China (Wang et al. 2014). Simulated by GEOS-Chem, Kopacz et al. (2011) found that emissions from north India and central China contributed most of BC to the Himalayas, while the TP received a large number of BC from the western and central China, as well as from India, Nepal, the Middle East, and Pakistan. Lu et al. (2012) developed a novel back-trajectory approach to study the origin of BC reaching the Himalayas and the TP, and found that BC received by the Himalayas and the TP increased by 41% from 1996 to 2010. On an annual basis, South Asia was the largest contributor to the Himalayas and TP, accounting for 67%, followed by East Asia (17%), the former USSR region (~ 8%), Middle East (~ 4%), Europe (~ 2%), and Northern Africa (~ 1%). Although the high altitude of Himalayas can act as a “physical wall” that prevents transport of pollutants from South Asia to the TP (Zhao et al. 2017), the valley of Yarlung Tsangpo River created a “leaking wall”, where BC aerosol can be transported up onto the glaciers (Cao et al. 2010). This trans-Himalayas transport of BC is mostly controlled by the meteorological conditions over the Indo-Gangetic Plain. For example, convergent airflows produce a strong northeastward wind from the Bay of Bengal to the Himalayas, resulting in high BC concentrations in the southeastern TP (Zhao et al. 2017).

Currently, studies about BC sources and its impact on snow albedo in the TP based on the seasonal perspective are very limited. In this study, we discussed the impact of regional transport on BC aerosol in the southeastern TP using bivariate polar plot graphical technique (Sect. 3.1) and the concentration-weighted trajectory (CWT) analysis (Sect. 3.2). The BC concentration in the snow surface was calculated based on the assumption of minimal deposition velocity of BC (Sect. 3.3), and its effect on the snow albedo reduction is also assessed in Sect. 3.3.

2 Experimental Methods

2.1 Research Site

The sampling site was located in a remote area at Lulang (Fig. 1), which is situated on the west bank of the Yarlung Tsangpo River in Linzhi Prefecture, China. Continuous sampling was conducted from July 2008 to July 2009 at the Integrated Observation and Research Station for Alpine Environment in South-East Tibet, Chinese Academy of Sciences (94.44°E, 29.46°N, ~ 3300 m above sea level). The region is affected by the Indian monsoon, via the valley of Yarlung Tsangpo River (Yang et al. 2015). Lulang is located in this channel, where major anthropogenic sources nearby are absent, making the sampling site an ideal location for investigating the transport of pollutants from South Asia. Based on the seasonality of atmospheric circulation and meteorological conditions, we defined four seasons as follows: pre-monsoon (18 February 2009–27 April 2009), monsoon (16 July 2008–3 October 2008; 28 April 2009–26 July 2009), post-monsoon (4 October 2008–9 November 2008), and winter (10 November 2008–17 February 2009). More detailed description on the sampling site could be found in Zhao et al. (2013).
Fig. 1

Location of the sampling site. The map was downloaded from http://www.worldmapfinder.com/BingMaps/Cn.html

2.2 Equivalent BC (eBC) Measurement

Five-minute averaged eBC mass concentrations were measured continuously with an aethalometer (Model AE-16, Magee Scientific Company, Berkeley, CA, USA). The term of eBC is specific to aethalometer measurement (Petzold et al. 2013). The detailed principle of aethalometer has been described previously (Hansen et al. 1984; Virkkula et al. 2007). Briefly, the instrument is based on the optical transmittance at a single wavelength of λ = 880 nm, and it measures the light attenuation (ATN) transmitted through a quartz-fiber filter. Sample air was drawn into the aethalometer at a flow rate of 4 L min−1 using a ~ 2 m length of conductive silicone tubing with a total suspended particle inlet. Before the atmospheric particles entered the instrument, they were dried with a silica gel dyer to avoid any effects of water condensation in the sampling line.

Based on the manufacturer’s default specific-attenuation cross section of 16.6 m2 g−1, the aethalometer converts the ATN to eBC concentration. However, a potential limitation of this instrument is that the decreasing transmission will lead to increasing attenuation with time; therefore, the relationship between ATN and eBC concentration will be non-linear (Weingartner et al. 2003). To compensate for the artifacts from the multiple scattering and shadowing effects, two empirical factors, that is, C and R(ATN), were used for correcting the absorption coefficient (b abs) (Weingartner et al. 2003):
$$b_{\text{abs}} = \frac{\text{ATN}}{{C \times R({\text{ATN}})}},$$
(1)
$$R({\text{ATN}}) = \left( {\frac{1}{f} - 1} \right) \times \frac{{\ln \left( {\text{ATN}} \right) - { \ln }(10\% )}}{{\ln \left( {50{\text{\% }}} \right) - { \ln }(10\% )}} + 1,$$
(2)
where C is 2.14 (Weingartner et al. 2003); f is 1.103 for wintertime and 1.114 for the rest of the seasons (Ram and Sarin 2009). The eBC concentrations were adjusted to the standard temperature (273.15 K) and pressure (1013.25 hPa).

3 Results and Discussion

3.1 Transport Direction

Fig. S1 shows a clear seasonal pattern of eBC concentrations, with the highest values in the pre-monsoon (0.98 µg m−3), followed by the post-monsoon (0.60 µg m−3), winter (0.57 µg m−3), and monsoon (0.32 µg m−3). Wind speed and wind direction are important for the dilution and diffusion of pollutants (Fast et al. 2007). Figure 2 presents the box plot of eBC mass concentrations as a function of wind speed increment during the four seasons. A slightly higher wind speed was found during the pre-monsoon (2.4 m s−1) rather than that during the other seasons, which showed similar average wind speed of 2.1 m s−1. As shown in Fig. 2, considerable difference in the mean and median eBC concentrations suggests that the eBC values varied largely at a given range of wind speed. Even so, the mean and median values still exhibited similar patterns for each season. During the post-monsoon, eBC concentrations showed an evident wind speed gradient with high eBC values related to the low wind speed. This can be explained by the strong wind being favorable to local horizontal diffusion, while the weak wind leads to accumulation of eBC aerosol. In contrast, eBC concentrations were relatively stable regardless of the wind speed during the pre-monsoon and monsoon. Although strong winds enhance the horizontal diffusion, it can also carry pollutants from upwind areas resulting in high eBC loadings (Gupta et al. 2017). For wintertime, eBC concentrations decreased with the increased wind speed at < 5 m s−1. However, the eBC concentrations increased with the enhanced wind speed at > 5 m s−1, indicating that regional transport may play an important role in accelerating eBC pollution.
Fig. 2

Box plot of eBC mass concentrations as a function of wind speed increment during the a pre-monsoon, b monsoon, c post-monsoon, and d winter. In each panel, the lower and upper edges of the boxes denote the 25 and 75% percentiles, respectively. The black line and red markers indicate the median and mean values, with vertical bars showing the 10th and 90th percentiles

Bivariate polar plot graphical technique was used to further investigate the relationship between eBC concentration and wind field, and to identify the transport directions of eBC aerosol. Figure 3 shows the bivariate polar plots for eBC mass concentrations at Lulang during the four seasons. For the pre- and post-monsoon, the prevailing wind directions were both northeasterly and southeasterly. For the monsoon season, the distribution of the wind direction was rather dispersed. During winter, the prevailing wind direction was northeasterly. The different patterns of the bivariate polar plots may reflect diverse directions of transport for eBC aerosol, which may be due to the varied seasonal eBC emissions and meteorological conditions. During the pre-monsoon, the average mass concentration of eBC was 0.72 µg m−3, and the large eBC values (> 0.65 µg m−3) were mainly associated with the low wind speed (< 2 m s−1) or with the high wind speed (> 4 m s−1) from the southeast. This indicates that both local and regional transport had important contributions to the eBC pollution occurring at Lulang. During the monsoon season, the average mass concentration of eBC was low with a value of 0.34 µg m−3. Occasionally, high eBC values (> 0.4 µg m−3) were observed at wind speed > 4 m s−1 from the southeast. During the post-monsoon, the average concentration of eBC was 0.53 µg m−3, with large eBC loadings (> 0.6 µg m−3) measured at low wind speed < 2 m s−1 or high wind speed > 6 m s−1 from the northeast and southeast. During winter, the average concentration of eBC was 0.51 µg m−3. The high eBC values (> 0.6 µg m−3) were concentrated at wind speed < 2 m s−1, indicating that eBC pollution may be mainly contributed by local emissions.
Fig. 3

Bivariate polar plots for the eBC mass concentrations based on the hourly data during the a pre-monsoon, b monsoon, c post-monsoon, and d winter

3.2 Identification of eBC Source Regions

The CWT analysis was performed for each season to investigate the spatial distribution of eBC potential source areas. It was based on the 5-day backward trajectories, and each trajectory was calculated when arriving at 500 m above ground level using the hybrid single-particle lagrangian integrated trajectory (HYSPLIT) model (Draxler and Rolph 2003). To calculate the CWT values, the entire geographic region covered by the trajectories is divided into an array of grid cells (defined by the cell indices i and j). In this study, ~ 12,616, ~ 17,052, ~ 19,200, and ~ 30,240 grid cells of 0.5° latitude × 0.5° longitude were retrieved for the pre-monsoon, monsoon, post-monsoon, and winter, respectively. Each grid cell is given a residence time-weighted concentration obtained by hourly averaged eBC concentration associated with the trajectories crossing that grid cell (Hsu et al. 2003):
$$C_{ij} = \frac{{\mathop \sum \nolimits_{l = 1}^{M} C_{l} \tau_{ijl} W_{i,j} }}{{\mathop \sum \nolimits_{l = 1}^{M} \tau_{ijl} W_{i,j} }},$$
(3)
where C ij is the average-weighted concentration in the ijth grid cell, C l the measured concentration of eBC on the arrival of trajectory l, τ ijl the number of trajectory end points in the ijth grid cell by trajectory l, and M the total number of trajectories. A high C ij value denotes that air parcels traveling over the ijth grid cell would contribute to eBC pollution. To reduce the effect of small values of τ ijl , the CWT values were multiplied by an arbitrary weight function W ij . The weighting function reduced the CWT values when the total number of end points per a particular cell was less than about three times the average values of the end points per cell (Wang et al. 2006).
$$W_{ij} = \left\{ \begin{aligned} 1.00\quad 120 < n_{ij} \hfill \\ 0.70\quad 40 < n_{ij} \le 120 \hfill \\ 0.42\quad 20 < n_{ij} \le 40 \hfill \\ 0.17\quad n_{ij} \le 20 \hfill \\ \end{aligned} \right..$$
(4)
The seasonal maps of CWT results are shown in Fig. 4a–d. For discussion purposes, we defined “eBC pollution” as the eBC concentration larger than the 75th percentile of all the data in each corresponding season. The 75th percentile values were 0.65, 0.35, 0.63, and 0.55 µg m−3 for the pre-monsoon, monsoon, post-monsoon, and winter, respectively. The CWT concentration gradients showed a similar source region for eBC pollution at Lulang during the pre-monsoon and monsoon. The source region was located to the southwest of Lulang (Region I), which includes the eastern Kingdom of Bhutan, Assam of India, and southern Shannan Prefecture of Tibet. However, the most important potential source region for the eBC pollution during the post-monsoon shifted to the east and southeast of Lulang (Region II), including Mêdog County of Tibet and northeast of Assam. The sources from Mêdog County indicated the pollution from the interior of the TP. Although the population is sparse in the TP, biofuels (e.g., yak dung and wood) are the main household energy for local residents (Ping et al. 2011), which produce noticeable amount of eBC aerosol, and hence in turn affects the atmosphere of the TP. It should be noted that sources from the northern part of Bangladesh (Region III) may also contribute to the high eBC loadings at Lulang. During the winter season, the largest possible source region for eBC pollution was located in north India and northwest Nepal (Regional IV). Moreover, high CWT values were occasionally found in central Tibet (Regional V), indicating sources from the interior of the TP. Further, time-averaged maps of BC column mass density, retrieved from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), were employed to describe the mean atmospheric eBC loadings around the TP (Fig. 5). As shown in Fig. 5, in general there were moderate or strong emissions observed in Region I, Region III and Region IV (see makers in Fig. 4), which are consistent with the distribution of large CWT values. This further supports that eBC pollution at Lulang was influenced by these regions.
Fig. 4

The maps of the concentration-weighted trajectory (µg m−3) for eBC concentrations during the a pre-monsoon, b monsoon, c post-monsoon, and d winter

Fig. 5

The maps of BC column mass density (kg m−2) around the Tibetan Plateau for the a pre-monsoon, b monsoon, c post-monsoon, and d winter. The green circles represent the sampling site

3.3 Estimated Impact of eBC Deposition

The total eBC mass dry deposition flux per 1 h was estimated through Eq. (5) (Santos et al. 2014):
$$F = C_{\text{eBC}} \times V_{\text{d}} \times 3600,$$
(5)
where F is the dry deposition flux (µg m−2), C eBC represents eBC concentration (µg m−3), and V d denotes the dry deposition velocity (m s−1). V d is a complex parameter related to the terminal velocity by gravitational settling and the resistances of atmospheric aerodynamic, quasi-laminar layer, and surface or canopy resistances. In this study, a constant minimal V d range of 1.0 × 10−4–1.0 × 10−3 m s−1 was used (Pryor et al. 2008). The total mass of eBC deposited on the surface was calculated as the sum of the eBC deposition integrated with all available data during the entire campaign. The estimated total eBC deposition amount was 1083.2–10,832.1 μg eBC m−2 during the whole sampling period, which corresponds to 3.6–36.1 μg eBC m−2 day−1. The eBC deposition rate showed clear seasonal patterns, with a maximum of 6.3–62.6 μg eBC m−2 day−1 for the pre-monsoon, followed by the post-monsoon (4.6–45.9 μg eBC m−2 day−1), winter (4.3–43.1 μg eBC m−2 day−1), and a minimum during the monsoon (2.4–24.5 μg eBC m−2 day−1). It should be noted that these values are representative of the lowest line of the actual eBC deposition due to our assumption of minimal range of deposition velocity.

We further estimated the eBC concentration in surface snow. Since the snow impurities are derived from dry deposition of atmospheric aerosols, the top layer of snow surface contains more impurities than the deeper part of the snow layer (Aoki et al. 2000, 2007). In this study, the concentration of eBC in the top layer of snow (e.g., 2-cm thickness) was estimated based on the assumption of uniform distribution for eBC in the top pure snow. Because eBC concentration is associated with snow water content, and snow density data in Lulang area are not available, the average snow density of 300 kg m−3 at the Parlong No. 4 Glacier was used (Yang et al. 2011). The glacier, located in the upper Yarlung Zangbu River Basin of southeast TP, has an area of ~ 11.7 km2 and a length of nearly 8 km. If the total eBC of 1083.2–10,832.1 μg eBC m−2 during the entire campaign was deposited on 2-cm thickness of pure snow, the eBC concentration in the snow surface would be 180.5–1805.4 μg kg−1. The seasonal variations for eBC concentrations in the snow surface showed that the highest value was obtained during the monsoon (61.5–614.7 μg kg−1), followed by the winter (58.8–587.6 μg kg−1) and pre-monsoon (33.3–333.2 μg kg−1), with the minimum value for post-monsoon (27.0–269.9 μg kg−1). Zhang et al. (2017) collected surface snow and snowpit samples from different glaciers in the southeastern TP in June 2015, and found that the eBC concentrations were 97.3, 318, and 125 μg kg−1 in the snow point samples collected from Dongga, Renlongba, and Demula glaciers, respectively. The amounts of eBC in the fresh snow and snowpits were generally lower than those in the aged snow and surface granular ice. Although direct comparison is not suitable for various studies due to their different analytical methodologies, sampling dates, and snow conditions, the high eBC concentrations in the southeastern glaciers indicate that the polluted air masses transported from South Asia may have a significant impact on these glacier melts.

Snow albedo is an important factor influencing glacier surface energy balance (Yang et al. 2011). To further evaluate the potential change in snow albedo caused by the deposited eBC, we used a simple linear regression equation derived from reduced albedo and BC concentration ([BC]) in snow (Ming et al. 2009):
$${\text{Reduced albedo}} = 0.0757 \times \left[ {\text{BC}} \right] + 0.0575,$$
(6)
where the units of reduced albedo and [BC] are % and µg kg−1, respectively. Based on the concentrations of eBC in the top layer of snow during the four seasons, the albedos reduced by 2.6–25.3, 4.7–46.6, 2.1–20.5, and 4.5–44.5% for the pre-monsoon, monsoon, post-monsoon, and winter, respectively. Due to the assumption of minimal range of deposition velocity, our estimation on snow albedo reductions may represent the lower boundary of the real condition. Moreover, the deposition of additional mineral dust onto snow surface also reduces the surface albedo, and thereby increases snow melting. For example, Zhang et al. (2017) used the SNICAR model to simulate the glacier albedo reduction in the southeastern TP and found that the albedo reduction for aged snow/granular ice caused by BC and dust ranged from ~ 10–19 and ~ 6–15%, respectively. Kaspari et al. (2014) indicates that BC concentrations in the winter–spring snow/ice horizons at Mera La (5400 m a.s.l., Nepal) reduced albedo by 6–10%, whereas dust can reduce albedo by 40–42%. Naturally, further field-based measurements combined with model studies for BC and mineral dust deposition onto TP regions and their impacts on snow albedo feedback are in urgent demand.

4 Conclusions

Surface eBC concentrations were measured with an aethalometer at Lulang, a high-altitude remote site in the southeastern TP, from July 2008 to July 2009. The bivariate polar plots for eBC mass concentrations showed obviously seasonal patterns. For the pre-monsoon season, the large eBC values (> 0.65 µg m−3) were mainly associated with the low wind speed (< 2 m s−1) or with the high wind speed (> 4 m s−1) from southeast, indicating the effects of local accumulation and regional transport. For the monsoon season, high eBC values (> 0.4 µg m−3) occasionally occurred at wind speed > 4 m s−1 from the southeast. For the post-monsoon season, large eBC loadings (> 0.6 µg m−3) were measured at low wind speed < 2 m s−1 or high wind speed > 6 m s−1 from the northeast or southeast. For the winter season, the high eBC values (> 0.6 µg m−3) were concentrated at wind speed < 2 m s−1, indicating that eBC pollution may be mainly caused by local emissions. The CWT analysis together with the distributions of the BC column mass density showed that sources located to the southwest of Lulang were the most important for eBC pollution during the pre-monsoon and monsoon. However, the possible source region for eBC pollution during the post-monsoon shifted to the east and southeast of Lulang, indicating the importance of biofuel burning emissions from the interior of the TP. During the winter, the largest potential source region for eBC pollution was located in north India and northwest Nepal.

The estimated total eBC deposition amount was 1083.2–10,832.1 μg eBC m−2, which corresponds to 3.6–36.1 μg eBC m−2 day−1. The eBC deposition rate showed clear seasonal variations, with a maximum of 6.3–62.6 μg eBC m−2 day−1 for the pre-monsoon, followed by the post-monsoon (4.6–45.9 μg eBC m−2 day−1) and winter (4.3–43.1 μg eBC m−2 day−1), and a minimum during the monsoon (2.4–24.5 μg eBC m−2 day−1). The average eBC concentration on 2-cm thickness of pure snow was estimated to be highest for the monsoon (61.5–614.7 μg kg−1), followed by the winter (58.8–587.6 μg kg−1) and pre-monsoon (33.3–333.2 μg kg−1), with the minimum value for the post-monsoon (27.0–269.9 μg kg−1). Based on these eBC concentrations in the top layer of snow, the albedos reduced by 2.6–25.3, 4.7–46.6, 2.1–20.5, and 4.5–44.5% for the pre-monsoon, monsoon, post-monsoon, and winter, respectively.

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (41230641, 41503118, and 41661144020). The authors are grateful to the Integrated Observation and Research Station for Alpine Environment in South-East Tibet, Chinese Academy of Sciences, for their assistance with field sampling.

Compliance with Ethical Standards

Conflict of interest

On behalf of all the authors, the corresponding author states that there is no conflict of interest.

Supplementary material

41810_2017_16_MOESM1_ESM.docx (22 kb)
Supplementary material 1 (DOCX 21 kb)

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Copyright information

© Institute of Earth Environment, Chinese Academy Sciences 2017

Authors and Affiliations

  • Qiyuan Wang
    • 1
  • Zhuzi Zhao
    • 1
  • Jie Tian
    • 2
  • Chongshu Zhu
    • 1
  • Haiyan Ni
    • 1
  • Yonggang Zhang
    • 1
  • Ningning Zhang
    • 1
  • Zhenxing Shen
    • 2
  • Yongming Han
    • 1
    • 3
  • Junji Cao
    • 1
    • 4
  1. 1.Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary GeologyInstitute of Earth Environment, Chinese Academy of SciencesXi’anChina
  2. 2.Department of Environmental Sciences and EngineeringXi’an Jiaotong UniversityXi’anChina
  3. 3.School of Human Settlements and Civil EngineeringXi’an Jiaotong UniversityXi’anChina
  4. 4.Institute of Global Environmental Change, Xi’an Jiaotong UniversityXi’anChina

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