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  寒旱区科学  2018, Vol. 10 Issue (3): 207-218  DOI: 10.3724/SP.J.1226.2018.00207


Niu HW, Shi XF, Li G, et al. 2018. Characteristics of total suspended particulates in the atmosphere of Yulong Snow Mountain, southwestern China. Sciences in Cold and Arid Regions, 10(3): 207-218. DOI: 10.3724/SP.J.1226.2018.00207.

Correspondence to

HeWen Niu, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. No. 320, West Donggang Road, Chengguan District, Lanzhou, Gansu 730000, China. Tel: +86-15009461932; E-mail: niuhw@lzb.ac.cn

Article History

Received: December 25, 2017
Accepted: January 27, 2018
Characteristics of total suspended particulates in the atmosphere of Yulong Snow Mountain, southwestern China
HeWen Niu 1, XiaoFei Shi 1,3, Gang Li 2, JunHua Yang 1, ShiJin Wang 1    
1. Yulong Snow Mountain Glacier and Environmental Observation Research Station, State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;
2. Key Open Laboratory of Arid Climatic Change and Disaster Reduction of China, Lanzhou, Gansu 730020, China;
3. College of Earth Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China
Abstract: The measurement of black carbon (BC) and organic carbon (OC), dust in total suspended particulates (TSP) was carried out at Yulong Snow Mountain (Mt. Yulong) and Ganhaizi Basin, in the Mt. Yulong region, southwestern China. TSP samples were analyzed using a thermal/optical reflectance carbon analyzer. Results show that average BC and OC concentrations in TSP in the Mt. Yulong region were 1.61±1.15 μg/m3 and 2.96±1.59 μg/m3, respectively. Statistical results demonstrated that there were significant differences in mean BC and OC contents between Ganhaizi Basin and Mt. Yulong at the 0.05 level. Strong correlations between BC and OC indicate their common dominant emission sources and transport processes. Temporal variations of BC, OC, and optical attenuation (ATN) values were consistent with each other in carbonaceous aerosols. The ratios of OC/BC in monsoon season were significantly higher than in non-monsoon in aerosols from Ganhaizi, which is closely related to the formation of secondary organic carbon (SOC) and extensive motor vehicle emissions from tourism activities. The temporal variations of BC, OC and ATN in carbonaceous aerosols in Ganhaizi and Mt. Yulong were totally different, probably due to elevation difference and diverse tourism activity intensity between the two sites. Time-averaged aerosol optical depth (AOD) at the wavelength of 550 nm in Mt. Yulong was higher than that of the inland of the Tibetan Plateau (TP). Source apportionment indicated that intensive exhaust emissions from tourism vehicles were the main local sources of atmospheric pollutant in the Mt. Yulong region. Biomass-burning emissions released from South Asia could penetrate into the inland of the TP under the transport of summer monsoon. Further study is needed to assess light absorption and radiative forcing of carbonaceous aerosols, and modeling research in combination with long-term in-situ observations of light-absorbing particulates (LAPs) in the TP is also urgently needed in future work.
Key words: black carbon    total suspended particulates    LAPs    Tibetan Plateau    

1 Introduction

It has been found that warming of the climate system is unequivocal, particularly since the 1950s, and many of the observed changes are unprecedented over decades to millennia. The atmosphere has warmed and the amounts of snow and ice have diminished significantly (IPCC, 2013). The Tibetan Plateau (TP) is the home of major glaciers and water resources in High Asia, which are very sensitive to climate change and fluctuate with climatic cooling and warming (Qian et al., 2015 ). Concentrations of atmospheric light-absorbing particulates (LAPs) over the TP are highly dependent on elevation and distance to emission sources (Cao et al., 2010 ). This dependency also influences the deposition of LAPs on snow/glacier and induces snow darkening and glacial melt effect. LAPs consist of aerosols including black carbon (BC) and mineral dust, cryoconite, and biogenic micro-organisms. Generally, dust makes up the majority of impurities on glaciers (Bøggild et al., 2010 ; Takeuchi et al., 2014 ; Goelles et al., 2015 ), but BC has a great effect on surface snow/ice albedo (Warren and Wiscombe, 1980), and could cause 2%–10% snow albedo reduction (Niu et al., 2017a ).

BC is a component in carbonaceous particulates which strongly absorbs visible sun-light, is formed primarily in flames (Bond et al., 2013 ) and is emitted to the atmosphere through incomplete combustion of fossil fuel and biomass fuel. In recent years, rising concentrations of carbonaceous aerosols is an important anthropogenic driving force of the observed changes in the high elevations (>5,000 m a.s.l.) and remote regions (such as the TP and Himalayas region) (Ramanathan and Carmichael, 2008; Lau et al., 2010 ). Particularly, extensive emissions and long-range transportation of carbonaceous particulates from South Asia are the main origins of BC in the atmosphere and deposited on the glaciers of the TP. It is reported that carbonaceous aerosols in atmospheric brown clouds widely diffused in South-Asia can reach southeastern TP by crossing the Himalayas (Lüthi et al., 2014 ; Cong et al., 2015a ; Wang et al., 2015 ; Li et al., 2016a ,b) and deposited on glaciers of the Mt. Yulong region (Niu et al., 2017a ,b, 2018). Absorbing aerosols heat the air and alter regional atmospheric stability, and affect the large-scale circulation and hydrologic cycle with significant regional climate effects (Menon et al., 2002 ; Li et al., 2016d ).

Radiative forcing (RF) by anthropogenic aerosols is recognized as an important contributor to climate change (IPCC, 2013). BC has a unique and important role in Earth's climate system and energy budget (Von Schuckmann et al., 2016 ). Carbonaceous aerosols can directly warm/heat the atmosphere in the Indian-monsoon region (Penner et al., 1998 ; Yasunari et al., 2010 ; Li et al., 2015a ,b; Raju et al., 2016 ) and also southwest monsoon region of China by absorbing solar radiation. Specific absorption co-efficient of BC is estimated in the range of 7–12 m2/g at 0.55 μm of wavelength (Adams et al., 1989 ; Horvath, 1993). Many modeling studies of BC RF have been conducted in the TP and surrounding areas, suggesting that BC is the second most vital factor in causing the fast melting of the Himalayas and TP glaciers (Ramanathan and Carmichael, 2008; Menon et al., 2010 ; Wang et al., 2014a ; Qian et al., 2015 ). A previous study estimated that BC RF of 20 W/m2 was found over the TP in the spring (Qian et al., 2011 ).

Recent carbonaceous aerosol sampling and climate effect studies have improved our ability to understand the characteristics of BC concentrations (Wu et al., 2009 ; Cong et al., 2015a ,b; Begam et al., 2016 ; Li et al., 2016b ). Goelles et al. (2015) found that carbonaceous aerosols have an effect on glacier volume, dust and BC accumulation causing ice sheet mass loss. Wet and dry depositions are the main two forms of BC aerosol deposition. It was reported that atmospheric lifetime of BC aerosols ranges from days to weeks depending on regional meteorological conditions. Thus, medium- and long-range transports are important in the spatial distribution of BC aerosols (Begam et al., 2016 ). One such example is BC observations in the Arctic regions which was attributed to long-range transport (Yang et al., 1996 ; Schneidemesser et al., 2009 ; Safai et al., 2013 ). BC concentrations were high in some parts of Africa and Asia due to emissions from coal combustion and biomass burning (Ramanathan and Carmichael, 2008; Cao et al., 2010 ; Chen and Bond, 2010; Begam et al., 2016 ). In Europe, North and South America, over half of the BC emissions result from fossil fuel combustion, particularly from vehicle engines (Bond et al., 2004 , 2013).

Data set in the wide TP is currently inadequate to fully assess the characteristics of carbonaceous aerosols in the high atmosphere, effects on glacial melting and RF after their deposition. The main purposes of the present work are (1) to characterize BC concentrations in total suspended particulates (TSP) over Mt. Yulong, in southeastern TP; (2) to investigate relations between BC and carbon-containing parameters in aerosols; (3) to improve our understanding of seasonal variations of BC and OC in TSP in Mt. Yulong; finally, (4) calculate aerosol optical depth (AOD) and sources of aerosols in the study area.

2 Study area

The study area is Yulong Snow Mountain (abbreviated Mt. Yulong). Mt. Yulong (26°59′N–27°17′N, 100°04′E–100°15′E) is located in southeastern TP and is the southernmost glaciated mountain in China (Figure 1). Mt. Yulong is exposed to Indian emissions in South Asia and more tend to be impacted by BC and brown carbon (BrC) aerosols than other regions in the TP. Baishui Glacier No. 1 (27°06′16″N, 100°11′44″E) is a temperate glacier in the TP that has large energy fluxes, particularly at lower snow-covered elevations. The climate of Mt. Yulong is typically affected by southwest and southeast monsoons during the rainfall or monsoon season (June–September), while in the winter the climate is mainly affected by the southern branches of the westerly jet, with minimal rainfall.

Figure 1 Sampling sites and the location of Mt. Yulong

Total suspend particulate (TSP) samples were simultaneously collected at two sampling sites in the Mt. Yulong region. One sampling site was on Mt. Yulong at an elevation of 4,510 m a.s.l., which is near the upper cableway station (27°06′16.953″N, 100°11′59.297″E) for tourism on Mt. Yulong. The second sampling site (27°06′08.285″N, 100°15′25.418″E) is in the Ganhaizi Basin, located on the eastern side and at the foot of Mt. Yulong, with an elevation of 3,054 m a.s.l.. It is separated from an urban area, but is an increasingly popular tourist destination, with a golf course and geological museum. There is little pollution except for exhaust emissions from local tourism vehicles. These two sampling sites are located in southeastern TP, far from urban cities and are considered typical remote areas of the Northern Hemisphere (Li et al., 2016b ) and ideal observation areas for atmospheric environment in a glacial region. Elevation difference is approximately 1,500 m between the two sampling sites.

3 Materials and methods 3.1 TSP sampling

TSP samples were continuously collected at Mt. Yulong and Ganhaizi, using a particulate sampling apparatus or TSP cyclones (TH150-A, Wuhan Tianhong INST Group). The sampling apparatuses were 15 m above the ground, away from surface dust and any specific pollutant sources. Atmospheric air (coupling with suspended particulates) was sampled at a flow rate of 100 L/min and each sample was collected for 24 h using a stable vacuum pump, and the sampling interval for each TSP sample was 6 days. The collected TSPs were loaded on 90 mm (in diameter) pre-combusted (heating at 550 °C for 6 h in an oven) quartz fiber filters (Whatman Corp).

After sampling, the filters were wrapped with aluminum foil and kept in a refrigerator at 4 °C in the Yulong Glacial Station in Lijiang City, and then were transported to the State Key Laboratory of Cryospheric Sciences in Lanzhou City for chemical analysis. In addition, precautions were taken in both collection and analysis processes to avoid possible contamination of TSP samples.

3.2 Sample analysis

OC and BC on the filters were analyzed using a Desert Research Institute (DRI) Model 2001 thermal/optical reflectance carbon analyzer (Atmoslytic Inc., Calabasas, California) (Chow et al., 2001 ; Li et al., 2016b ; Niu et al., 2017b ). Every filter was analyzed for a portion of carbon in a 0.296 cm2 punch. A temperature peak (550 °C) was designed to decrease measuring time. The applied working conditions permitted the separation of BC portions in a 2% O2/98% helium (He) atmosphere and OC portions in a He atmosphere (Wang et al., 2015 ; Niu et al., 2017a ). The dust content in the TSP samples was detected by drying the quartz fiber filters (at 550 °C for 6 hours) and weighing the mass by a high precision scale before and after sampling and combustion.

3.3 Statistical analysis

We used the analysis of variance (ANOVA) method to statistically analyze BC, OC, and other measured data in this work. ANOVA is a collection of statistical models utilized to analyze the distinctions among groups' means and their associated procedures, providing a statistical test of whether the means of several groups are equal or not, and generalizes the t-test to more than two groups (Niu et al., 2017b ).

All statistical analysis was performed employing software SPSS 17.0. Pearson correlation analysis for BC and other species was performed in this study. The statistical tests for differences and correlations were significant at p <0.05 level.

4 Results 4.1 Concentration levels of BC and OC in the samples

Carbonaceous aerosol samples were collected from Mt. Yulong and Ganhaizi Basin, and the measured BC, OC, dust contents, and OC/BC ratio are presented in Table 1. Statistical tests were carried out to observe if the differences of BC and OC concentrations in aerosols were statistically significant in Mt. Yulong and Ganhaizi. Statistical test results indicate that there were significant differences in mean BC and OC concentrations between Ganhaizi and Mt. Yulong (Table 2). These results demonstrated that aerosols from Mt. Yulong had slightly higher mean BC content of 1.68 μg/m3, ranging from 0.02 to 6.83 μg/m3. But for OC concentrations, compared with the value found in Ganhaizi, Mt. Yulong had lower mean value of 1.85 μg/m3, ranging from 0.07 to 5.97 μg/m3. Similarly, SOC concentrations and OC/BC ratio in atmospheric aerosols from Ganhaizi were higher than from Mt. Yulong, probably due to higher OC content in the atmosphere in Ganhaizi Basin. Dust contents in TSP samples from Ganhaizi Basin were substantially higher than that from Mt. Yulong.

Table 1 Characteristics of the concentrations of carbonaceous matter in TSP in the Mt. Yulong region

Table 2 Statistical analysis for BC and OC concentrations in TSP samples from Mt. Yulong and Ganhaizi Basin
4.2 Correlations among BC and other carbon-containing variables

In the study area, a strong correlation was observed between BC and OC concentrations (OC = 1.25BC+1.26, R2=0.66) in carbonaceous aerosols (Figure 2), indicating their common dominant emission sources and transport processes. In addition to BC and OC relations, we examined correlations among BC, SOC, and OC/BC. Results demonstrated that strong relations exist between BC and OC (correlation coefficient r = 0.59, p <0.01), OC and SOC ( r = 0.88, p <0.01), and there was strong negative relation between BC and OC/BC ratio ( r = −0.42, p <0.01) in aerosols from Mt. Yulong ( Table 3). For aerosols from the Ganhaizi Basin, similar degree correlations were also found among these variables. Therefore, apart from their common origins (e.g., biomass burning and fossil fuel combustion), dust deposition and the formation of secondary OC were the main origins of OC. Moreover, OC could be generated by biogenic sources (Cong et al., 2015a ).

Figure 2 Correlations between BC and OC concentrations in TSP samples from Mt. Yulong

We further evaluated relations among BC, OC, and SOC in TSP. Results demonstrated that there are substantial differences in the correlations of SOC and OC and BC between Ganhaizi and Mt. Yulong (Figure 3). Analysis of triplet relations demonstrated that OC and SOC played more important roles among three variables in carbonaceous aerosols in Mt. Yulong than in Ganhaizi.

Table 3 Correlation coefficients among BC, OC, SOC, and OC/BC

Figure 3 Triplet plot among BC, OC, and SOC concentrations in TSP from (a) Ganhaizi and (b) Mt. Yulong
4.3 Temporal variations of BC and OC in TSP

The temporal variations of BC, OC and ATN values, and the OC/BC ratios in TSP samples collected from Ganhaizi and Mt. Yulong were determined. For TSP samples in Ganhaizi, the measured results indicated that these four parameters have distinct seasonal trends from December, 2014 to December, 2015 (Figure 4). The trends of BC, OC and ATN were consistent with each other during the whole sampling year, whereas the trend of OC/BC ratio was opposite to those of the other three parameters. Particularly, during the monsoon season the adverse trends were more distinct. The entire monsoon season had the lowest BC, OC concentrations, and ATN values in TSP samples from Ganhaizi. Lower concentrations in monsoon season were primarily due to frequently rainfall events which washed the aerosols from the atmosphere.

Figure 4 Temporal variations of BC, OC concentrations and the OC/BC ratios in TSP samples from Ganhaizi Basin. Shadowing part indicates the monsoon period

Different from the trend found in Ganhaizi aerosols, BC, OC, and ATN in aerosols were almost significantly increased during the entire period of June 1 to December 1, 2015 at Mt. Yulong (Figure 5). Moreover, it has a large fluctuation within the overall rising trend. However, for OC/BC ratio, the trend was reverse with the trend of BC, OC and ATN, it only has two peaks of values (i.e., during the period of December, 2014 to February, 2015, and from May to July, 2015) in the whole year.

The OC and BC concentrations, along with ATN values show no obvious variations before May 15, 2015 (Figure 5). This is due to frequent snowfall events at Mt. Yulong during December 1, 2014 to May 10, 2015, and was fully covered by snowpack (nearly 4 m in depth) at elevations above 4,300 m, which is significantly different from the scenario found at Ganhaizi Basin.

Therefore, the temporal variations of BC, OC and ATN in aerosols in Ganhaizi and Mt. Yulong were totally different, probably due to elevation differences and local climate conditions; in addition, different intensities of tourism activity between the lower Ganhaizi Basin and higher Mt. Yulong were also the main driving forces of the divergence in temporal variations.

Figure 5 Temporal variations of BC, OC concentrations and the OC/BC ratios in TSP samples from Mt. Yulong at an elevation of 4,510 m a.s.l.

In addition to the study of temporal variations, we investigated the seasonal variations of OC, BC, and the OC/BC ratio, according to the sampling protocol. Seasonal differences in BC, OC, and even OC/BC ratios in aerosols both from Mt. Yulong and Ganhaizi Basin are presented in Figure 6. Results show that there exist distinct seasonal differences in BC, OC, and OC/BC, particularly for aerosols in Ganhaizi Basin. There was no obvious seasonal variations for BC and OC concentrations in the atmosphere in Mt. Yulong, probably due to the counteract effect of snowfall (versus dust events) during the non-monsoon season. It is notable that the OC/BC ratio in monsoon season was higher than in non-monsoon season in carbonaceous aerosols from Ganhaizi. Thus, the large amount of motor vehicle emissions from extensive tourism activity in the Ganhaizi Basin is one of the main factors contributing to this phenomenon. Moreover, average BC, OC concentrations and OC/BC ratios in aerosols from Ganhaizi were obviously higher than from Mt. Yulong (Figures 6a, 6b) either in monsoon season or in non-monsoon season.

Figure 6 Seasonal differences in BC, OC, dust concentrations and the OC/BC ratio in aerosols from Mt. Yulong
5 Discussions 5.1 Comparison of BC in Mt. Yulong with other sites

In addition to determining BC and OC concentrations in aerosols from Ganhaizi and Mt. Yulong, we summarized measurements of BC in aerosols from all relevant studies known to the authors of this study. We reported means of all published measurements from each location. Analysis methods varied among referenced literature and were considered the varying extents in each reference. Among all of the compared locations, Agra, Indian had the highest BC concentrations in aerosols (Pachauri et al., 2013 ), followed by Lhasa City (Zhang et al., 2008 ). Whereas Nam Co in China and Pyramid in Nepal (Ming et al., 2010 ) had the lowest BC concentrations in aerosols (Table 4). However, BC concentrations in Ganhaizi and Mt. Yulong aerosols have nearly comparable values with the results found in Manora Peak in the Himalayas (Ram et al., 2010 ). Moreover, we carried out statistical tests to observe if the BC concentrations in aerosols in Mt. Yulong and other interesting sites were significant. We divided the study areas listed in Table 4 into four groups according to their geographical locations and general BC concentration levels, and then employed the ANOVA method to analyze the significance. Statistical results indicate that there were significant differences in BC concentrations between four groups at the 0.05 level (Table 5). Thus, there indeed exist spatial differences of BC concentrations in aerosols from various locations, though the characteristic of spatial distribution of BC contents in aerosols was not the study focus of this work. Raju et al. (2016) found that three times more BC occur at urban sites than at rural sites in western India. Numerous potential factors could substantially induce the spatial differences of BC contents, such as location elevation, sources of carbonaceous aerosols, emission intensity, distances from the source regions, and wind direction and velocity.

Biomass burning and fossil fuel combustion are the main sources of BC in carbonaceous aerosols. Compared with other regions in the TP, Mt. Yulong region was more easily affected by anthropogenic (or vehicle) emissions derived from Lijiang City and surrounding areas. Intensive exhaust emissions from tourism vehicles were the main local sources of atmospheric pollutants in the Ganhaizi Basin. In addition, it has been reported that extensive biomass-burning emissions released from South Asia can penetrate into the inland of the TP (Lüthi et al., 2014 ; Chen et al., 2015 ; Cong et al., 2015a ,b; Li et al., 2016a ,b,c).

Table 4 Comparison of atmospheric BC contents in Mt. Yulong and various interesting sites

Table 5 Statistical analysis for BC concentrations in six groups of aerosols from Mt. Yulongand other interesting sites
5.2 OC/BC ratio and its implications

Determining the correlation between BC and OC in TSP can provide meaningful insights into the sources and possible physio-chemical reaction processes (Turpin and Huntzicker, 1995; Cong et al., 2015a ). The OC/BC ratio can be used to explain the emission and transformation characteristics of carbonaceous aerosols (Pachauri et al., 2013 ), and is usually employed to evaluate the combustion fuel sources, although there might be uncertainties when using this parameter. Previous studies reported that the global mean of OC/BC by biomass burning was higher than fossil fuel burning (Liousse et al., 1996 ; Bond et al., 2004 ; Ming et al., 2010 ). Cao et al. (2010) found that mean OC/BC ratios measured from plumes of residential biomass-burning and coal combustion are considerably higher than from vehicle exhaust. Generally, various emission sources mainly include biomass burning (OC/BC ratio: 6.6), vehicle exhaust (OC/BC ratio: 1.1) and long-rang transport (OC/BC ratio: 12.0) (Sandradewi et al., 2008 ; Sudheer and Sarin, 2008; Ram et al., 2010 ). Mt. Yulong in southeastern TP, where our samples were collected, has no industry and is a famous tourist attraction. Vehicle emissions from large quantities of tour buses were one of the main sources of atmospheric BC and OC in Mt. Yulong. An emission inventory released in 2000 revealed that mean OC/BC ratios by biomass and fossil fuel burning were approximately 6.9 and 2.7 in TP, respectively (Streets et al., 2003 ; Ming et al., 2010 ). Thus, the average OC/BC ratio (3.03±0.39) in atmospheric aerosols found in this study might indicate more contribution from fossil fuel combustion than biomass or coal burning. OC/BC ratios in carbonaceous aerosols in the monsoon season are significantly higher than in non-monsoon in Ganhaizi, which is closely related to the formation of large amount of SOC (2.39±0.16 μg/m3) in the monsoon season when extensive photochemical processes occur (Grannas et al., 2004 ; Schneidemesser et al., 2009 ; Antony et al., 2011 ; Cong et al., 2015a ). Also, SOC accounts for 82% of OC contents in the monsoon seasons in the Ganhaizi Basin. Similarly, local scale SOC accounted for a great contribution to OC content in atmospheric aerosols over the Nam Co region (Ming et al., 2010 ). It was found that secondary organic aerosol is a large source of organic carbon due to active photochemistry (at Summit) (Schneidemesser et al., 2009 ). Moreover, higher humidity (90%) and temperature (5.08 °C) in rainy or monsoon seasons in the Mt. Yulong region are favorable to form SOC. Thereby the role of SOC cannot be neglected in the assessment of climate effects of carbonaceous aerosols.

Seasonal differences of BC, OC concentrations in carbonaceous aerosols found in this work were consistent with our previous studies on snow chemistry (Niu et al., 2014 , 2016, 2017b). The lower concentration of OC and BC during monsoon season in Ganhaizi was due to wash-out effect of large amount of rainfall, as a significant fraction of OC is water-soluble so it was scavenged during rainfall events. Increased emissions from household heating (coal combustion) and motor vehicles and unfavorable atmospheric dispersion (e.g., low mixing-layer height) lead to higher BC and OC concentration during non-monsoon (winter) season (Pachauri et al., 2013 ).

5.3 Estimation of AOD and transport mechanism of TSP

In order to investigate the optical characteristic and climate effect of aerosols, we employed the parameter AOD to evaluate the light attenuation role. The expanded meteorological model WRF-Chem (version 3.5.1) from mid-scale Weather Research and Forecasting (WRF) model (Skamarock et al., 2005 ), can well simulate gas-phase chemical and aerosol microphysical processes with various meteorological fields (Wang et al., 2014b ; Gao et al., 2015 ; Yang et al., 2016 ). Our simulated results indicate that in the south and southeast fringe (Mt. Yulong) of the TP, the AOD value was notably higher than the value in inland of the TP (Figure 7). This can indirectly reflect air quality and pollution conditions of the atmosphere in the TP and the surrounding areas, and simultaneously verified that carbonaceous aerosols (including BrC) were substantially transported from South Asia. In Mt. Yulong, AOD value at the wavelength of 550 nm was about 0.06, lower than the value (0.12±0.06) found in Nam Co atmosphere (Yang et al., 2016 ) of a heavy pollution event, though it was slightly higher than that of the inland of the TP.

Figure 7 Time-averaged AOD map over the TP and Mt. Yulong in the 2015 monsoon season

In addition to estimating AOD in the Mt. Yulong region, we further investigated backward trajectories of the prevailing air masses for two typical months (August and October, 2015) using NOAA HYSPLIT_4 model (Figure 8; Stein et al., 2015 ; Rolph, 2017). Backward trajectories can indicate source regions and large scale circulation patterns affecting the region during the sampling period (Carrico et al., 2003 ; Yalcin et al., 2006 ; Niu et al., 2013 ). It is apparent that the 500 hPa aerosphere over Mt. Yulong is mainly controlled by the southeast and southwest monsoons during a typical monsoon season (Figure 8a), indicating the sources of atmospheric pollutants, i.e., which were predominately transported from South Asia. Moreover, while in the non-monsoon season, air masses over the Mt. Yulong region were primarily affected by the southern branch of the westerlies (Figure 8b). This phenomenon laterally reflects the potential transport mechanisms and sources of suspended particulates in the atmosphere over the southeastern TP during the non-monsoon season.

Figure 8 Seven-day backward trajectories at Mt. Yulong on two sampling days during the study period (Source at 27.06°N, 100.11°E). (a) August 29, 2015; (b) October 29, 2015
6 Conclusion remarks

This study is based on the field sampling and measurement of TSP aerosols in Ganhaizi and Mt. Yulong, in southwestern China. We firstly evaluated general concentration levels of BC and OC in TSP aerosols, where statistical results demonstrated significant differences in mean BC and OC contents between Ganhaizi and Mt. Yulong. Average BC and OC concentrations in TSP samples in the Mt. Yulong region were 1.61±1.15 μg/m3 and 2.96±1.59 μg/m3, respectively.

Correlation analysis between BC and OC denoted that there exists strong relations, i.e., OC = 1.25BC+ 1.26, R2=0.66, indicating their common dominant emission sources and transport processes, moreover, correlations among BC and other carbon-containing variables indirectly reflecting that dust deposition and the formation of SOC were the main origins of OC. Temporal variations of BC, OC, and ATN were consistent with each other in aerosols in Ganhaizi and Mt. Yulong, while for the OC/BC ratio, the trend was reverse with the other three variables.

The temporal variations of BC, OC and ATN in TSP in Ganhaizi and Mt. Yulong were totally different, probably due to elevation difference and local climate conditions. Additionally, different intensities in tourism activity between the lower Ganhaizi Basin and higher Mt. Yulong were also the driving forces of the divergence in temporal variations.

Time-averaged AOD at the wavelength of 550 nm in Mt. Yulong was higher than that of the inland of the TP. Source apportionment indicated that intensive exhaust emissions from tourism vehicles were the main local sources of atmospheric pollutant in the Mt. Yulong region. Biomass-burning emissions released from South Asia could penetrate into the inland of the TP under the transport of summer southwest and southeast monsoons.

Further study is needed to assess light absorption and radiative forcing of carbonaceous aerosols, with special attention paid to the relative proportion of LAPs in the atmosphere in the TP derived from anthropogenic versus natural sources. Moreover, modeling research in combination with long-term in-situ observations of LAPs in the TP is also urgently needed in future studies.


This work was supported by the National Natural Science Foundation of China (41601071, 41721091), the Key Research Program for Frontier Science of Chinese Academy of Sciences (QYZDJ-SSW-DQC039); the independent program of SKLCS (SKLCS-ZZ-2018), the CAS "Light of West China" Program (Y62992) and Postdoctoral Science Foundation (2015M582725, 2016T90963). The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for provision of the HYSPLIT transport and dispersion model and/or READY website (http://www.ready.noaa.gov) used in this publication.

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