Environmental implications of the snow chemistry from Mt. Yulong, southeastern Tibetan Plateau

Quaternary International 313-314 (2013) 168e178

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Environmental implications of the snow chemistry from Mt. Yulong, southeastern Tibetan Plateau Hewen Niu a, b, *, Yuanqing He a, b, Guofeng Zhu c, Huijuan Xin b, Jiankuo Du b, Tao Pu a, b, Xixi Lu d, Guoyong Zhao a a

Key Laboratory of Western China’s Environmental Systems, Ministry of Education, Research School of Arid Environment and Climate Change, Lanzhou University, Lanzhou 730000, China State Key Laboratory of Cryospheric Science, Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China c College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, China d Department of Geography, National University of Singapore, Kent Ridge 6516, Singapore b

a r t i c l e i n f o

a b s t r a c t

Article history: Available online 26 November 2012

Snow chemical records were recovered from fresh and surface snow samples in the Mt. Yulong region. Striking seasonal differences were evident among the major ions. The non-monsoon snow samples show higher ionic concentrations than those of the monsoon season. The observations can be categorized into three groups based on their seasonal behavior and characteristic relationships that were explored using correlation and factor analyses. Calculations of backward trajectory modes suggest that the coarse mode ions (e.g. Ca2þ, Mg2þ) were mainly transported from Central Asia, through the south limb of the westerlies, in non-monsoon seasons. The Indian monsoon and southeast monsoon are the prevailing air masses in the Yulong region during the monsoon season, and can account for the extensive precipitation and lower snow ion concentrations in this season. Ion balance calculations indicate that there is an excess of cations in snow chemistry due to higher concentrations of Ca2þ. In addition, the low snow Naþ/Cl ratio shows an obvious excess of Cl concentrations possibly due to the precipitation scavenging of gas-phase HCl in the air and/or different sources between Naþ and Cl. The snow chemical data presented here indicate that Mt. Yulong provides a probably unique record of atmospheric and environmental conditions in southwestern China. Ó 2012 Elsevier Ltd and INQUA. All rights reserved.

1. Introduction Proxy records developed through physical and chemical analyses of snow/ice provide high-resolution and direct views of atmospheric circulation and environment conditions. Since 1996, Mt. Yulong has been established as a famous glacier park in China, open to tourists. It provides excellent conditions for glaciological investigations (He et al., 2002a) and also significantly promotes the local economy development through tourism. High elevated cold glaciers situated in mid-latitude regions are well suited for reconstructing atmospheric concentrations of trace species and documenting the impact of humans on the environment (Olivier et al., 2003). Increases in agricultural activity and biomass burning produced elevated concentrations of ammonium during this time period (e.g. Döscher et al., 1996; Kreutz, 2001; Hou et al., 2003). * Corresponding author. Key Laboratory of Western China’s Environmental Systems, Ministry of Education, Research School of Arid Environment and Climate Change, Room 405, Yifu Science Building, Lanzhou University, 222 Tianshui Nanlu, Lanzhou, Gansu 730000, China. E-mail address: [email protected] (H. Niu). 1040-6182/$ e see front matter Ó 2012 Elsevier Ltd and INQUA. All rights reserved. http://dx.doi.org/10.1016/j.quaint.2012.11.019

Short-term fresh snow and aerosol chemistry sampling during monsoon and non-monsoon seasons has shown low pollutant concentrations in the Himalayan atmosphere, suggesting these sites are representative of the remote troposphere (Wake et al., 1994a, 1994b; Shrestha et al., 1997; Marinoni et al., 2001; Kang et al., 2002, 2004). Comparison of fresh snow chemistry from central Himalayas and investigation of sources of major ions indicate that variations of snow chemistry are strongly influenced by the seasonality more than geographical location (Marinoni et al., 2001; Balerna et al., 2003). Studies of glaciochemistry carried out in Himalayan snow and ice suggest that, over the Tibetan Plateau, snow and ice chemistry is dominated by desert dust coming from the wide arid regions of central Asia (Mayewski et al., 1986; Wake et al., 1990; Williams et al., 1992). This paper systematically presents the fresh and surface snow chemistry research collected from the Mt. Yulong region. This area is located 25 km north of Lijiang city, where anthropogenic activities and traffic emissions somewhat contribute to the atmospheric pollution. In addition, the Yulong region is interesting for climate research, as it has both marine and continental characteristics with

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pronounced seasonality. Much attention has been devoted to glacier ablation and environment evolution-related issues of this region (e.g. He et al., 2001, 2002a, 2002b; Pang et al., 2007; Li et al., 2009a, 2009b, 2010; Zhang et al., 2010, 2012a, 2012b; Zhu et al., 2012). However, little literature has comprehensively focused on the topics relevant to snow chemistry (including dust particles, Ca2þ, Mg2þ) and atmospheric circulation at Mt. Yulong, although the aerosol particles deposited in snow/ice have been well recognized as an important medium and can provide valuable information on environmental changes (Pereira et al., 2004; Cong et al., 2009). In this study, factor and correlation analyses are employed to examine snow chemical composition and the seasonal variation of major ions in the study area. Routine comparison with the existing results of other sites is also conducted in the analysis to expand current knowledge of the spatial and temporal characteristics of snow chemistry. Moreover, the HYSPLIT_4 transport mode is applied to identify the possible new and potential source regions for major ions in snow of Mt. Yulong, and the influence of transport on the chemical signal. In particular, a focus is the differences between snow chemistry from monsoon and non-monsoon seasons, verifying the dominant circulations on snow chemical fluctuation and spatial variations. The study further investigates the climatic and environmental implications of snow chemistry recorded in the Mt. Yulong region. 2. Experimental methods 2.1. Snow sampling Mt. Yulong is situated at the southeastern of the Qinghai-Tibet Plateau, and the southeast margin of the Hengduan Mountains (Fig. 1). This region is characterized by high precipitation (2300e 3000 mm) in the glacier-covered area, a low snow line (4200e 5200 m, which is w800e1200 m lower than that of the polar glaciers in the western Plateau of Tibet), and relatively high temperatures (equilibrium line mean annual value 6  C, summer value 1e5  C) (Shi et al., 1988; Li and Su, 1996; He et al., 2002a,

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2003). There are 15 modern glaciers distributed on Mt. Yulong, with a total area of 7.65 km2; the largest is Baishui Glacier No. 1, with length 2.26 km and area 1.32 km2. Climate in this region is marked by monsoon and non-monsoon seasons, with maximum precipitation (about 80e90% of annual precipitation amount (He et al., 2004)) in summer (June to September). The moisture is transported northward from the southwestern circulation over the Indian Ocean during the monsoon season, and in the eastern part of the region, the southeastern monsoon from the Pacific Ocean. In the non-monsoon season, the south limbs of the westerly system are the prevailing atmospheric cycle/circulation over the region, with nearly no rainfall or little rainfall in this season. Pollution from human activities has affected most of the atmospheric environment. Fresh and surface snow samples were collected from Yulong Mt. (26 590 e27170 N, 100 040 e100150 E) on the southeastern Tibetan Plateau. The sample site is located on the accumulation area of Baishui glacier No. 1 with the altitude ranges between 4506 and 4810 m a.s.l. Extreme care and stringent sampling protocols were taken at all times during sample collection and handling to assure samples were not contaminated at the meq/L level. A pre-cleaned stainless-steel sampling tool was used to pack samples directly into pre-cleaned 200 ml polypropylene containers, and nonparticulating suits, polyethylene gloves and masks were worn at all times during the sampling campaign. All sampling equipment and sample containers were precleaned with distilled water. A total of 130 surface and fresh snow samples were collected for major ion analyses. The cations 2   2þ 2þ  (Naþ, Kþ, NHþ 4 , Ca , Mg ) and anions (SO4 , Cl , NO3 , NO2 ) were analyzed on a Dionex 300 and a Dionex 600 ion chromatograph, respectively. Results were averaged for individual samples, yielding an estimated error of 10% or less on ion concentrations. Analyses of duplicate samples as well as transport and laboratory blanks demonstrate that sample contamination during sample transfer, transport, and subsequent analytical procedures are negligible (Kang et al., 2004). Snow samples were packed into insulated and cleaned polyethylene bottles and transported frozen into a cold room at 20 C of the laboratory at Lanzhou until

Fig. 1. Location of Mt. Yulong, and the atmospheric circulation affecting the region.

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measurements were performed in a class 100 clean room. All of these sampling techniques have been demonstrated to minimize or eliminate contamination (Mayewski et al., 1984; Wake et al., 1994a; Kang et al., 2000, 2004; Qin et al., 2002). 2.2. Meteorological data For the duration of the sampling campaign, an automatic weather station (AWS, Campbell Company) was installed on Baishui glacier No. 1, nearby the snow sampling site. Its power system of solar cells guaranteed 24-h collection. Local wind speed, temperature, precipitation, and relative humidity were recorded at daily resolution. 3. Results and discussion 3.1. Chemical composition of fresh and surface snow samples Concentration of major ions of snow samples coupling with the local precipitation and temperature are given in Table 1. Table 2 also presents detailed chemical concentrations of snow collected from Mt. Yulong in May 2012. Based on the sampling scenario that the surface and fresh snow samples had been taken from October 30th, 2008 to November 10th, 2009 (Zhu et al., 2012), the sampling period spanned an entire calendar year. According to the seasonal and climatic features of Yulong region, the sampling period was divided into two stages, i.e., monsoon season (Jun., Jul., Aug., Sep.), and non-monsoon season (other months). Furthermore, the study divided the non-monsoon season into pre-monsoon (Mar., Apr., May) and post-monsoon (Oct., Nov., Dec., Jan., Feb.) seasons. Correspondingly, concentrations of major ions for each season are calculated and presented in Table 1.

To provide a general indication of the chemical characteristic of the snow samples, the ion balance DC (sum of cation ion concentration minus sum of anion ion concentration) was calculated for each season sample data. Calculation results indicate that the cations dominate the snow chemical composition (or ion balance) during the post-monsoon and monsoon seasons of the sampling campaign, while the anions dominate in the pre-monsoon season. The ion imbalance and the shift from the cations to the anions indicate that they originated from different sources (i.e., marine ions and crustal ions) and that the cations account for the primary proportion of major ions during the sampling period, comparable to the ion balance scenario of snow and ice on the northern slope of Mt. Qomolangma (Everest) (Ming et al., 2007). The large excess of cations in fresh and surface snow is due to high Ca2þ concentration (Tables 1 and 2), which is related to the limestone around Mt. Yulong. When relatively humidity is low, more dust can be brought to the air by the prevailing winds, thus enhancing the concentration of Ca2þ (Zhang et al., 2010). The anion excess in the postmonsoon season is presumably balanced by the hydrogen ions, and the cation excess is probably balanced by carbonate ions, in the case of samples with high dust concentrations, and/or acids such as methanosulfonate, formate, or acetate (Yalcin et al., 2006b). In addition, imbalance of ions could be ascribed to the influence of  2  CO2 3 and HCO3 in snow. The DC can reflect the CO3/HCO3 ratio (Wake et al., 1992; Li et al., 2006), which is thought to be important in periods with high input of crustally-derived alkaline impurities (i.e., CaCO3 and MgCO3) (Hansson, 1994). The excess amounts of cations assumedly originate from the surrounding dust, as well as 2þ the exchange between CO2 and CO2 is the dominant ion, and 3 . Ca the deficiency of anions is probably attributable to a carbonate concentration which has not been quantified. Among the eight ions, Ca2þ is the most loaded species in the surface snow, and the mean concentration accounts for 49% of the

Table 1 Major ion concentrations in snow samples and some items of interest in monsoon and non-monsoon seasons at Yulong snow mountain (unit: meq/L). Seasons Post-monsoon

Mean P

Monsoon

Mean P

Pre-monsoon

Mean P

a b c

Cl

NO3

SO42

Naþ

NH4þ

Kþ

Mg2þ

Ca2þ

DCa

Preb

Temc

Naþ/Cl

1.32 6.61 0.43 1.30 2.32 9.21

11.22 56.1 4.0 12.0 13.6 54.3

33.58 167.9 17.33 52.0 81.95 327.8

0.44 2.20 0.03 0.11 0.93 3.70

0.34 1.70 0.23 0.71 2.17 8.72

0.72 3.60 0.32 1.01 1.63 6.51

8.98 44.9 2.07 6.21 2.25 9.02

471 2355 33.1 99.4 79.77 319.1

435 2177 13.9 42.1 11.1 44.3

35.3 176 340 1019 148 595

4.5 22.5 4.3 12.9 0.63 2.5

0.33 0.33 0.08 0.08 0.41 0.41

2þ 2þ þ þ   2 DC ¼ ([NHþ 4 ] þ [Mg ] þ [Ca ] þ [Na ] þ [K ])  ([Cl ] þ [NO3 ] þ [SO4 ]).

Predprecipitation (unit in mm). Temdtemperature (unit in  C).

Table 2 Mean chemical composition of fresh and surface snow from Mt. Yulong with altitude range from 4506 to 4810 m a.s.l. (unit: meq/L). Date May May May May May May May May May May May May May May May a

3 4 5 9 10 11 12 14 15 16 18 20 24 26 27

Altitude

Cl

NO 2

NO 3

SO2 4

Naþ

NHþ 4

Kþ

Mg2þ

Ca2þ

DCa

Naþ/Cl

4507 4511 4560 4533 4680 4741 4572 4695 4784 4653 4810 4769 4528 4536 4662

2.09 12 5.85 11.4 152 22 5.44 3.07 1.99 25.5 4.66 8.19 13.1 2.53 8.11

0.08 0.06 0.05 0.02 0.04 e 0.04 e 0.05 e 0.04 e e 0.04 0.03

8.85 7.96 4.86 3.41 2.25 1.71 2.53 1.15 3.11 1.62 2.56 5.42 1.68 1.62 0.67

27.1 18.5 10.5 1.62 5.02 1.7 0.94 2.88 1.54 1.98 4.46 7.02 6.64 6.54 2.98

0.54 16.8 7.37 16.3 215 27.9 7.28 2.72 1.48 30.9 6.85 11.6 17.7 3.17 12.2

26.1 25.3 18.5 12.6 64 8.92 9.33 8.63 7.66 10.4 10.4 14 7.91 6.24 6.65

3.31 8.83 4.4 5.89 68.9 11.2 3.41 1.76 1.19 11.8 2.65 4.38 6.54 1.91 4.36

2.5 1.7 0.9 4.4 9.7 12 1.1 4.6 4.8 19 7.1 6.8 8.9 13 15

40 32 17 30 69 104 8.1 203 17.0 67 336 221 50 59 51

34.41 46.15 26.96 52.76 267.3 138.6 20.11 231.3 25.49 50.0 351.2 236.4 69.58 72.27 77.45

0.26 1.41 1.26 1.43 1.41 1.27 1.33 0.88 0.74 1.21 1.47 1.41 1.35 1.25 1.50

2þ 2þ þ þ    2 DC ¼ ([NHþ 4 ] þ [Mg ] þ [Ca ] þ [Na ] þ [K ])  ([Cl ] þ [NO3 ] þ [NO2 ] þ [SO4 ]).

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total species concentration. SO2 4 is the second loaded species in þ 2þ  þ þ snow samples, followed by NO 3 , Mg , Cl , NH4 and K . Na is the least loaded species among the major ions in this region. With respect to the standard sea-salt ratio (0.86), the ratios of Naþ/Cl from the Yulong fresh snow in 2008e2009 are very low, with mean values of 0.33, 0.41 and 0.08 for pre-monsoon, postmonsoon and monsoon, respectively, indicating there is a large excess of Cl. This is consistent with the results from fresh snow over the Cho Oyu range (Balerna et al., 2003) and the vicinity of Mt. Everest (Kang et al., 2004), and Mt. Logan Massif (Yalcin et al., 2006b), but in disagreement with the results from the southern slope of the Nepal Himalayas (Valsecchi et al., 1999; Marinoni et al., 2001), in which the Naþ/Cl ratios during the monsoon period are very similar to the classical sea-salt ratio, showing the strong marine contribution related to the monsoon circulation (Kang et al., 2004). The excess Cl can be explained assuming an enrichment of Cl in the snow due to the precipitation scavenging of gas-phase HCl (produced by acidification of sea-salt particles) in the atmosphere (Legrand and Delmas, 1988; Toom-Sauntry and Barrie, 2002). This is supported by comparison between ion concentrations in snow and aerosols over the Hidden Valley (Shrestha et al., 1997, 2002) and Mt. Qomolangma (Everest) (Ming et al., 2007). Differing from the snow samples collected in 2008e 2009, the Naþ/Cl ratios of snow collected in 2012 display relatively larger values compared to the standard sea-salt value (0.86), as nearly all Naþ/Cl ratios exceed 0.86 (Table 2), indicating a substantial excess of Naþ concentration. This indicates the great contributions of Naþ-contained rock dust, related to the slight monsoon circulations over the sampling region in May 2012. 3.2. Seasonality and temporal variations of the major ions Glaciochemical studies of the snow and ice in the Himalayas range have revealed that the concentrations of major ions (e.g. Ca2þ and Mg2þ) in the monsoon season are generally lower than those in the non-monsoon season, presenting striking seasonal variations (Shrestha et al., 2000; Kang et al., 2004; Liu et al., 2010). Fig. 2 displays the variations of major ionic concentrations with the sampling time extension. In general, major ions of fresh and surface snow show high concentrations during non-monsoon seasons. To take account of major ions and climate features, the sampling period was divided into different seasons, marked by dashed vertical lines in Fig. 2. Concentrations of major ions during the premonsoon are higher than that during the post-monsoon, and significantly higher than that of monsoon season. Extensive precipitation and relatively higher humidity/moisture in monsoon season greatly contributed to its lower ionic concentration. In addition, the depressions bring rainfalls during June, July, and August, and thus dust emission decreased simultaneously. Aerosols in atmosphere were scavenged by the frequent precipitation events, and then deposited in the deep ice layers or washed away by meltwater during this season. In addition, the low ion concentrations of monsoon snow may reflect both decreased dust deposition (Wake et al., 1994a; Shrestha et al., 1997; Kang et al., 2002; Liu et al., 2010) and increased scavenging efficiency (Kang et al., 2002, 2004). The concentrations of major ions show high values during the pre-monsoon season, corresponding to the increased spring storm events and dust deposition. Most ions display higher concentration in pre-monsoon than in the post-monsoon and monsoon, although Ca2þ and Mg2þ show higher concentrations in the post-monsoon than in monsoon and pre-monsoon. The variation of two ions is  þ or out of phase with that of Cl, Kþ, Naþ, SO2 4 , NO3 , and NH4 (Fig. 2). The phenomenon clearly indicates the continental source

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for Ca2þ and Mg2þ in the snow of Mt. Yulong. The high concentrations of major ions pertinent to dust (e.g. Ca2þ and Mg2þ) during the winter and spring seasons may be associated with the southern limb of the westerlies (see Section 3.5) and the higher wind speed (Fig. 3), dust particles transported southward from northwest China in the post-monsoon season. Furthermore, the high ion concentrations in pre-monsoon snow may result from dust deposition during the peak in dust-storm activity mainly in April and May over Asia (Parrington et al., 1983; Gao et al., 1992; Qian et al., 1997; Kang et al., 2004) and strongly coincide with the period of greatest wind intensity. Higher wind speed occurred in November and April during the entire sampling campaign, and some occasional high values also occurred in March and May. Higher wind speed significantly promoted the local-to-regional dust and atmospheric aerosol transport and deposition on Yulong, and thus made great contributions to the higher dust particle and aerosol (snow chemical) concentrations in the non-monsoon season, especially in the pre-monsoon season. Changes in local wind speed might have had an influence on dust uplift, with lower wind speeds leading to less dust and lower ionic concentrations. The stronger the wind, the more water vapor is transported, resulting in lower values of relative humidity, and thus the relatively dry atmospheric conditions lead to more transport of dust particles. The Asian dust flux to the open ocean is influenced not only by conditions in or near the source regions but also by large-scale atmospheric circulation patterns (Gao et al., 1992) and less washout by precipitation during transport. The change of concentration between the seasons is more strongly linked to changes of atmospheric parameters than to changes of the source regions. The scenario at Mt. Yulong is consistent with the previous conclusions that dust in the snow and ice on the Tibetan Plateau and Himalayas comes primarily from the arid and semi-arid regions of central Asia (Mayewski et al., 1986; Wake et al., 1990; Williams et al., 1992), and agrees well with the report that the winter dry season (with high aerosol concentrations) and the summer wet season (with low aerosol concentrations) dominate atmospheric and aerosol behavior over the Tibetan Plateau (Wake et al., 1994a; Kang et al., 2000; Shrestha et al., 2000). Moreover, episodic biomass-burning events can overwhelm the seasonal NHþ 4 cycle and produce concentration maxima any time between spring and winter. Kþ concentration peaks coincide with NHþ 4 peaks, suggesting a source from crustal dust or emissions of biomass combustion (Mayewski et al., 1983; Shrestha et al., 1997; Yalcin et al., 2006a). In addition, the temporal variations of major ions in snow collected in May 2012 from Mt. Yulong show distinct trends (Fig. 4). The cations oscillated more than the anion concentrations, with a two-peak pattern during the entire sampling campaign in May 2012, May 10 and around May 20, respectively. Meanwhile, Cl concentration also had a peak on May 10. The single or bimodal pattern of snow chemistry in May can be attributed to the simultaneous occurrence of anthropogenic activities and occasional dust events (during pre-monsoon season), as well as some sea-salt mineral particles, which made significant contribution to the higher ions concentrations under the local and large scale atmospheric circulation patterns. However, both the anions and cations concentrations had gradually decreased at the end of May, and this is consistent with the trend of snow chemistry in 2009 (Fig. 2), corresponding to the shift of large scale atmospheric circulation from the south limb of the westerlies to slight monsoon circulation. Thus, the differences of meteorological characteristics resulted in the variance of snow chemistry distribution in this region.

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Fig. 2. Major ionic concentrations variation of fresh and surface snow collected from Mt. Yulong. Vertical dashed lines represent the seasonal boundaries.

3.3. Seasonality of number abundances for major ions The numerical abundance of the different chemical ions in snow is displayed in Fig. 5 for non-monsoon and monsoon samples. Clearly, both monsoon and non-monsoon seasons are dominated by calcium ions. Higher crustal particle (dust) loading occurs in non-monsoon periods (Kang et al., 2004, 2007; Cong et al., 2009). However, the relative abundance of sulfuric (30%) and nitrate (7%) ions in the monsoon period are much higher than in the non-monsoon season (15%, 4%), indicating that the Mt. Yulong region received more anthropogenic influence in the monsoon than the non-monsoon season. This differs from the results detected in Mt. Qomolangma region (Cong et al., 2009). This assumption is further reinforced by the presence of potassium ions in monsoon samples (1%), while no potassium was observed in non-monsoon samples. 3.4. Factor and correlation analyses for snow chemical composition Linear regression of species measured in snow samples (Table 3) showed that strong correlations exist among different major ions. Precipitation and temperature are highly correlated (r ¼ 0.88), but not correlated with other chemical components, with the exception of slight negative relations among the precipitation and other major ions.

Table 3 Correlation coefficients between soluble species in fresh and surface snow collected at Mt. Yulong. Species

Cl

NO 3

SO2 4

Naþ

NHþ 4

Kþ

Mg2þ

Ca2þ

Pre

NO 3 SO2 4 þ Na NHþ 4 Kþ Mg2þ Ca2þ Pre Tem

0.79 0.79 0.89 0.81 0.94 0.11 0.16 0.46 0.25

0.94 0.46 0.86 0.88 0.45 0.32 0.36 0.17

0.51 0.98 0.94 0.16 0.00 0.25 0.04

0.59 0.76 0.16 0.06 0.45 0.24

0.96 0.03 0.12 0.24 0.03

0.05 0.00 0.35 0.11

0.80 0.35 0.29

0.48 0.59

0.88

In order to identify the main sources of major ionic components, principal component analysis (PCA) was applied to chemical data.  2 þ 2þ The PCA involved eight initial variables (NHþ 4 , K , NO3 , SO4 , Ca , Mg2þ, Cl, Naþ). Three factors, which explained 97% of the total variance (F3 only accounting for 9% of the total variance), are pre2 þ sented in Table 4. The first factor (F1) loaded with NO 3 , SO4 , NH4 , and Kþ (Fig. 6), can be attributed to local transport and background contribution, and it controls the acidity of fresh snow. NHþ 4 and SO2 4 are highly correlated (r ¼ 0.98), suggesting an anthropogenic source of short-range transport from Lijing city, and presumably present primarily in the accumulation mode as NH4HSO4$aerosol

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Fig. 3. Wind speeds (m/s) variation over the entire sampling event/duration at nearby Mt. Yulong.

(Seinfeld and Pandis, 1998). In addition, high correlations exist   þ between SO2 4 and NO3 (r ¼ 0.94), NO3 and NH4 (r ¼ 0.86) as well þ 2  þ as K and NH4 , SO4 , NO3 , with correlation coefficients are 0.96, 0.94, 0.88, respectively. This further confirms the anthropogenic contribution. Table 4 Results of PCA carried out on all data: factor loading, eigenvalues and percentual explained variance.

Fig. 4. Temporal variations of major ions (in mg/L) in surface and fresh snow collected from Mt. Yulong in May 2012.

Species

F1

F2

F3

Cl NO 3 SO2 4 Naþ NHþ 4 Kþ Mg2þ Ca2þ Eigenvalue % variance

0.63 0.89 0.97 0.31 0.94 0.85 0.17 0.06 5.09 63.57

0.13 0.36 0.04 0.11 0.12 0.01 0.93 0.96 1.97 24.63

0.76 0.23 0.22 0.94 0.31 0.53 0.15 0.09 0.75 9.41

The high correlation between Ca2þ and Mg2þ (r ¼ 0.80) relates the second factor (F2) to a strong continental contribution due to the south limb of the westerlies and circulation activities. The attribution of the principal component to this source can be confirmed by observing the factor loading plot (Fig. 6), which shows the solely loading of Mg2þ and Ca2þ on the positive side of F2-axis, near the zero of the F1-axis. They are representative of a non-monsoon period dominated by local

Fig. 5. Average abundances of major ions for non-monsoon and monsoon snow samples.

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Fig. 6. Results of PCA carried out on all data: Factor loading plot.

circulation with some inclusion of north-westerly geotropic winds driving cold and dry continental air. The major synoptic pattern is the winter position of the Central Asian High, which progress rapidly from the west to the east of Mongolia, creating stronger winds and intense dust storms (from arid and semiarid regions of central Asia and even northern Africa (Liu et al., 1981; Parrington et al., 1983; Gao et al., 1992)). The maximum activity (April and May) occurs in the southern Gobi region (Kang et al., 2004). In addition, the third factor was loading with Cl and Naþ, and the high correlation between Cl and Naþ (r ¼ 0.89), indicating a strong marine contribution due to the monsoon circulation. Water vapor originates from the Arabian Sea/Bay of Bengal, and arrives at Mt. Yulong in a few days (Section 3.6). In sum, PCA confirms that observations can be statistically categorized into three classes corresponding to the different sampling periods. The correlation analysis implies relations exist among the ions that have the same sources, and no relations can be detected among ions with different sources. 3.4.1. Monsoon data PCA analysis was carried out on monsoon chemical data. Table 5 shows the first 3 factors accounting for 99% of total variance. F1 loaded with most ions, other than Naþ, indicating a comprehensive atmospheric circulation and anthropogenic contribution to the ionic deposition. The second factor, loaded with the sea-salt species Naþ related to monsoon, is on the negative side of the F2-axis, and near the zero point of the F1axis (Fig. 7). F3 indicates the anthropogenic species with relatively high concentrations of NHþ 4 . Sun et al. (1998) provided evidence that ammonium concentration in snow is controlled by

Fig. 7. Results of PCA carried out on monsoon data: Factor loading plot in rotated space.

post-depositional processes. Recent studies (e.g., Shrestha et al., 2000; Kang et al., 2002) suggest that SO2 4 has various sources (anthropogenic or crustal) in atmosphere or glaciochemical records near Mt. Qomolangma. Generally, the accumulation  2 mode ions (i.e. NHþ 4 , NO3 , SO4 ) have complex sources. From the earlier analyses, the nitrate sources could include continental, atmospheric and stratospheric contributions, anthropogenic activity effects, consisting of biomass burning soils and dust, oxidation of NH3, photochemical processes, and lightning, and several effects of cosmic-related factors (Legrand and Kirchner, 1990; Shrestha et al., 1997; Hou et al., 2003; Yalcin et al., 2006a). Ammonium in the Himalayan snow and ice is closely related with monsoon air masses rich in NH3 that originated from biogenic activities (Mayewski et al., 1983). SO2 has 4 anthropogenic and crustal sources in general, but at most times the anthropogenic contribution dominates. Generally, the value 2þ of SO2 is calculated to separate the anthropogenic 4 /Ca contribution from the dust source of the concentration peak of SO2 4 .

Table 5 Results of PCA carried out on monsoon data: factor loading, eigenvalues and percentual explained variance. Species

F1

F2

F3

Cl NO 3 SO2 4 þ Na NHþ 4 Kþ Mg2þ Ca2þ Eigenvalue % variance

0.99 0.97 0.99 0.49 0.88 0.97 0.98 0.97 6.77 84.67

0.12 0.02 0.08 0.85 0.32 0.07 0.2 0.23 0.95 11.85

0.04 0.23 0.02 0.17 0.35 0.24 0.07 0.10 0.28 3.47

3.4.2. Non-monsoon data The non-monsoon data (including snow chemical data of May 2012) have been subjected to a further PCA analysis in order to have a more detailed view of the different sources and air mass types involved in fresh-snow deposition. PCA analysis was carried out by using a varimax raw rotation to facilitate graphical interpretation, and rotation converged in 4 iterations. Table 6 shows the first three factors accounting for 98% of total variance. F1 loaded with accumulation mode ions and Kþ. The nitrate enrichment is likely due to the growth of traffic and the associated rise of the emission of precursor gases NOx. The ammonium signal recorded in the Mt. Yulong snow is primarily attributed to biogenic emissions, biomass burning and anthropogenic emissions related to nitrogen-contained energy combustions and agricultural activities (e.g. livestock and the use of nitrogen-rich fertilizer). Kþ loading with NHþ 4 , suggests a biomass-burning source related largely from agricultural activity (Mayewski et al., 1983; Davidson et al., 1986; Wake et al., 1994a; Shrestha et al., 1997; Kang et al., 2002). F2, loaded with Ca2þ and Mg2þ, is easily associated to a crustal source and dust input transported by the southern limb of the westerlies, as displayed in the factor loading plot (Fig. 8). The third factor, loaded with Naþ and Cl, partly originated from the marine source. The sodium and chloride signals in the northeastern and southeastern regions of the Tibetan Plateau could be related to monsoon precipitation but are effectively masked by sodium and chloride derived from the arid and semi-arid regions in China (Wake et al., 1993; Olivier et al., 2003).

H. Niu et al. / Quaternary International 313-314 (2013) 168e178 Table 6 Results of PCA carried out on non-monsoon data: factor loading, eigenvalues and percentual explained variance.

Cl NO 3 SO2 4 Naþ NHþ 4 Kþ Mg2þ Ca2þ Eigenvalue % variance

F1

F2

F3

0.72 0.93 0.98 0.37 0.96 0.88 0.05 0.05 5.22 65.29

0.11 0.24 0.06 0.14 0.15 0.05 0.99 0.99 2.07 25.97

0.68 0.26 0.21 0.92 0.24 0.47 0.01 0.07 0.63 7.93

3.5. Spatial variation of major ions in snow/ice Snow or ice chemistry data varied greatly in different regions. þ 2þ  The ions (Naþ, NHþ 4 , K , Mg , Cl ) of snow in Mt. Yulong show the highest concentrations among the existing snow chemistry reported in the literature. There excess cations in snow of Mt. Yulong, similar to the Tien Shan, Xixabangma, Dasuopu and Altai, due to high coarse species (Ca2þ and Mg2þ) concentrations resulting from the frequent Asian dust events in the non-monsoon season. In contrast, the chemical ions are close to balanced in Mt. Everest, Khumbu-Himal, and the Mt. Logan Massif. There exists a distinct spatial difference of Naþ/Cl ratio, as in Mt. Yulong region. Most sites have excess sea-salt species Cl, except in Tien Shan and Altai. The strong storm events and semi-arid landform conditions (containing sea-salt mineral particles) significantly contributed to the continental source ions (include Naþ). The difference of the Naþ/Cl ratios and the concentrations of Cl and Naþ in snow and ice between the southern (e.g. Mt. Yulong, southern Mt. Everest) and northern (e.g. Tien Shan, Altai, Xixabangma) slopes of the Himalayas may indicate that the crest of the Himalayas acts as an effective barrier to the spatial distribution of Naþ and Cl (Liu et al., 2010) and also indicates their different origins. In addition, the Naþ/ Cl ratios have great temporal variation, which can be confirmed by the differences between 2008 and 2012. The higher concentrations þ 2 of NO 3 , NH4 and SO4 in the Yulong region indicate substantial anthropogenic activities and traffic emissions as the predominate sources for these ions in the Mt. Yulong area. Areas away from cities or human disturbances show lower accumulation mode ionic concentrations in snow or ice, such as Mt. Everest and Yukon Territory. It is suggested that anthropogenic sulfate was observed in snow from northwest China (Wake et al., 1992) and transported

Fig. 8. Results of PCA carried out on non-monsoon data: Factor loading plot in rotated space.

175

southward under the south limb of the westerlies. An enhanced MongHi strengthens the transport of dust aerosols southward, from arid regions over central Asia, to Everest, during the winter season (Kang et al., 2002). However, part of the sulfate and nitrate at Yulong originates from SO2 and NOx emissions because of increasing vehicle traffic during recent years. From the spatial differences, concentrations of major ion in snow and ice core varied significantly, over central Mt. Everest to the southern slope of Himalayas, and over the central Tien Shan to the southeastern Tibet Plateau, as well as the Siberian Altai and the polar region of Canada. The geographical features over the short distance from Lijiang city to Mt. Yulong resulted in absolutely higher ionic concentrations in snow at Mt. Yulong compared with other study regions. In addition, the Tien Shan surrounded by vast Asia desert has comparable ion concentrations with Mt. Yulong, significantly affected by local/regional anthropogenic emissions and continental dust. Comparison results further confirm the previous suggestion that the crest of the Himalayas is not a completely effective barrier to the spatial distribution of fresh snow chemistry during either nonmonsoon or monsoon seasons, at least in the high mountain regions in the vicinity of Mt. Everest (Kang et al., 2004). In addition, as the mean concentrations of Ca2þ and Mg2þ of the Yulong region firn core are much higher than that of all the other snow ice cores, indicating that most of the impurities in the Mt. Yulong snow or ice come from a continental source rather than a marine one (He et al., 2002a). Furthermore, differences in geography features, such as altitude and topography, may also play an important role in the spatial distribution of snow chemistry between the western and eastern Himalayas (Liu et al., 2010). 3.6. Source analysis for the prevailing air masses The seasonal difference of chemical components of the Mt. Yulong can be explained mainly by the different atmospheric circulation patterns in different seasons. Atmospheric backward trajectories for some typical months (among Nov. 2008 to Dec. 2009 and May 2012) were calculated with the HYSPLT_4 transport model (Fig. 9; Draxler and Rolph, 2012; Rolph, 2012), and the 400 hPa atmospheric transmission paths during winter, spring, summer and autumn for the sampling sites were simulated. Backward trajectories can indicate source regions and large scale circulation patterns affecting the region during the sampling campaign (e.g., Carrico et al., 2003; Yalcin et al., 2006b) It is apparent that the 400 hPa aerosphere over Mt. Yulong is controlled by the southern limb of the westerlies during the winter and spring seasons (Fig. 9aec, i), indicating the source regions of Central/West Asia such as the Taklamakan desert, Qaidam basin and Junggar Basin, as well as the Thar desert in south Asia. This suggestion is complementary to previous conclusions that dust in snow and ice on the Tibetan Plateau and Himalayas comes primarily from the arid and semi-arid regions of central Asia (Luo and Yanai, 1983; Mayewski et al., 1986; Murakami, 1987; Wake et al., 1990; Williams et al., 1992). The long-range southward transport of dust substantially promoted the higher concentration of aerosols in nonmonsoon seasons. Dust can be entrained into the atmosphere and stay aloft for long distances, especially fine dust, prior to being scavenged by precipitation events in the Yulong region. In addition, several river valleys on the southeastern plateau, which channel moisture from the Bay of Bengal towards the north, provide the routes by which particles are transported into the interior of the plateau (Xiao et al., 2002). During the summer (monsoon) season, the southwest (Indian monsoon) and southeast air masses (monsoons) controlling the atmosphere in the Yulong region (Fig. 9deg). The Indian monsoon strengthens bringing more monsoon precipitation over the southern Tibetan Plateau and the

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H. Niu et al. / Quaternary International 313-314 (2013) 168e178

Fig. 9. Air mass backward trajectories generated using NOAA HYSPLIT_4 model for prevailing air masses in Mt. Yulong regions (Source + at 27.06 N, 100.11 E).

Himalayas. This reduces the loading of summer atmospheric dust aerosols in the region (Kang et al., 2002). The Indian monsoon weakens gradually in the autumn season, and is replaced subsequently by the westerlies (Fig. 9h). In addition, westerlies were the prevailing air masses in the upper air of Mt. Yulong area in early May 2012 (Fig. 9j), and gradually the monsoon air masses penetrated into this area (Fig. 9k, l). At the end of May, the lower monsoon air masses (include southwest and southeast monsoons) replaced the westerlies (Fig. 9l). More water vapor was transported to this area and thus more precipitation events occurred in the following days due to large scale atmospheric circulation. The southwest monsoon, which is the prevailing airflow in the Mt. Yulong region, can be divided into two branches. The Indian monsoon originates from the Arabian Sea/Indian Ocean, passing across the Indian Peninsula and the Himalayas to the southern Tibetan Plateau. The second southwest monsoon is the Bengal

monsoon, from the Bay of Bengal, moving along the channel of Bengal and Burma to the Hengduan Mountains (Tian et al., 2001; He et al., 2003; Liu et al., 2010). Moreover, the southeast monsoon originates from the North Pacific, crossing over most of southeastern China and conveying large quantities of precipitation to the Hengduan Mountains (He et al., 2003). Thus, the different vapor sources due to atmospheric circulation patterns may contribute to the differences in major ionic concentrations in different seasons and areas with snow and ice. 4. Conclusions Snow chemical composition of fresh and surface snow in Mt. Yulong region on the southeastern Tibetan Plateau expands the database and the current understanding of snow chemistry in remote and high mountain regions. Ion balance calculations

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Appendix A. Supplementary data

indicate that fresh and surface snow samples are imbalanced due to the excess Ca2þ concentrations in non-monsoon seasons. The snow Naþ/Cl ratio shows an obvious temporal variation, probably due to the precipitation scavenging of gas-phase HCl in the atmosphere and/or different sources between Naþ and Cl. Major ion concentrations from fresh and surface snow samples collected in monsoon and non-monsoon seasons display absolutely higher concentrations for non-monsoon than those of the monsoon season. Striking seasonal differences are demonstrated for each major ion. Pre-monsoon SO2 4 is one order of magnitude higher in concentration among the major ions. Post-monsoon Ca2þ and Mg2þ are one order of magnitude higher than the monsoon values.

Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.quaint.2012.11.019. References Balerna, A., Balerna, E., Pecci, M., Polesello, S., Smiraglia, C., Valsecchi, S., 2003. Chemical and radio-chemical composition of fresh snow samples from northern slope of Himalayas (Cho Oyu range, Tibet). Atmospheric Environment 37 (12), 1573e1581. Carrico, C.J., Bergin, M.H., Shrestha, A.B., Dibb, J.E., Gomes, L., Harris, J.M., 2003. The importance of carbon and mineral dust to seasonal aerosol properties in the Nepal Himalaya. Atmospheric Environment 37, 2811e 2824.

Table 7 Major ion concentrations (meq/L) of fresh snow, snow pit and ice core samples from the Yulong snow mountain and other areas of interest. Sampling date

Elevation (m a.s.l.)

Cl

5, 2012

4506e4700

17.81

NO 3 3.39

Naþ

NHþ 4

Kþ

Mg2þ

6.76

24.19

15.92

9.47

7.02

45.64

0.50

0.93

0.90

5.01

SO2 4

Ca2þ

Naþ/Cl

Location

Source

111.2

1.36

Yulong Snow Mt.

Present work

180.7

0.35

Yulong Snow Mt.

Zhu et al., 2012

Mt. Everest Khumbu-Himal, Nepal Yukon Territory Mt. Logan Massif Tien Shan Altai, Belukha Xixabangma Dasuopu Glacier

Kang et al., 2004 Marinoni et al., 2001

Surface/fresh snow Surface/fresh snow Fresh snow Fresh snow

2008e2009

4600e4800

1.43

8e9, 1998 5e10, 1998

5800e6500 5050e6100

1.02 2.26

1.14 1.16

0.72 2.90

0.41 2.09

0.34 2.32

0.15 1.51

0.23 0.55

1.71 3.50

0.03 3.96

0.30 0.92

Snow pit Fresh snow Ice core Ice core Fresh snow Ice core

5e6, 2002 5e6, 2001 1992e1998 1940e2000 8e9, 1997 2006

370e500 4130 5100 4062 5400e7000 7000

0.49 0.45 9.70 0.90 1.59 0.67

0.67 1.07 5.50 4.31 1.53 2.56

0.93 1.18 13.5 11.03 1.03 2.25

0.39 0.29 10.9 1.01 1.35 0.54

0.34 0.79 9.7 11.40 3.02 7.67

0.06 0.08 0.90 0.41 0.40 0.31

0.52 0.21 4.70 1.62 0.33 0.43

1.63 0.97 66.2 9.40 2.60 5.62

0.79 0.36 63.71 7.60 3.55 9.09

0.80 0.64 1.12 1.11 0.85 0.81

10.2

The identification of the main sources of major ionic components by a principal component analysis (PCA) coupling with correlation analysis of chemical data confirm that observations can be statistically categorized into three classes. Central Asia dust events and anthropogenic emissions make substantially contribution to the corresponding ions, such as Ca2þ, SO2 4 , respectively. Comparison of the data with those snow chemical compositions over the extensive spatial regions shows that there is a substantial relation of major ionic distribution in snow at different high-altitude regions. The atmospheric backward trajectories calculated with the HYSPLIT_4 transport model show that the high concentrations of major ions during the nonmonsoon seasons may come from Thar Desert in the south Asia, and the Taklamakan desert, Qaidam basin and Junggar Basin in Central Asia. The difference of vapor sources due to atmospheric circulation patterns (the south limb of westerlies and monsoons) and geographical features may result in the spatial and seasonal distribution of snow chemistry in the Mt. Yulong region. Mt. Yulong provides a probably unique character of atmospheric and environmental conditions in southwestern China, central Asia. Acknowledgements This work was jointly supported by the Foundation from the State Key Laboratory of Cryospheric Sciences, a Project of the National Natural Science Foundation of China (40971019) and a West Light Foundation of China’s Academy of Sciences (O828A11001). The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website (http:// ready.arl.noaa.gov) used in this publication.

82.57

DC

231

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