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Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities

Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities Environ Sci Pollut Res (2016) 23:9549–9558 DOI 10.1007/s11356-016-6182-7 RESEARCH ARTICLE Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities 1,2 2 2 2 3 Jing Ming & Cunde Xiao & Feiteng Wang & Zhongqin Li & Yamin Li Received: 31 August 2015 /Accepted: 26 January 2016 /Published online: 3 February 2016 The Author(s) 2016. This article is published with open access at Springerlink.com . . . . Abstract The Tienshan Urumqi Glacier No.1 (TUG1) usually Keywords Black carbon (BC) Dust Albedo Glacier shows Bgrey^ surfaces in summers. Besides known regional Tienshan warming, what should be responsible for largely reducing its surface albedo and making it look Bgrey^? A field campaign was conducted on the TUG1 on a selected cloud-free day of Introduction 2013 after a snow fall at night. Fresh and aged snow samples were collected in the field, and snow densities, grain sizes, and Mountain glaciers, different from the Arctic and Antarctic ice spectral reflectances were measured. Light-absorbing impurities sheets, are geographically much closer to human settlements, (LAIs) including black carbon (BC) and dust, and number con- such as the mid-latitude glaciers in the Alps, Caucasus, High- centrations and sizes of the insoluble particles (IPs) in the sam- mountain Asia, and Southern Andes (Ming et al. 2015; Gardner ples were measured in the laboratory. High temperatures in sum- et al. 2013;Zengetal. 1984). They store water resources as mer probably enhanced the snow ageing. During the snow age- snow and ice in cold seasons and release them in warm seasons, −3 ingprocess,the snow densityvariedfrom243to458kgm , which directly adjust fresh water supplies to the lives of the associated with the snow grain size varying from 290 to surrounding people, especially to those who are living in arid 2500 μm. The concentrations of LAIs in aged snow were sig- regions. From this angle of view, mountain glaciers are the most nificantly higher than those in fresh snow. Dust and BC varied important water resource in the wide arid and semi-arid regions from 16 ppm and 25 ppb in fresh snow to 1507 ppm and like Central Asia. 1738 ppb in aged snow, respectively. Large albedo difference Tien Shan Mountains, one of few areas holding most con- between the fresh and aged snow suggests a consequent forcing centrated glaciers in the mid-latitudes of the northern −2 of 180 W m . Simulations under scenarios show that snow Hemisphere, is home of nearly 16,000 glaciers (Aizen et al. ageing, BC, and dust were responsible for 44, 25, and 7 % of 2007). More than 100 million people live on the water sourced the albedo reduction in the accumulation zone, respectively. from these glaciers, which are also called the BWater Tower of Central Asia^. The Tienshan glaciers have been shrinking since the end of Little Ice Age in the mid-nineteenth century Responsible editor: Gerhard Lammel (Sorg et al. 2012) and the shrinkage has been accelerated since the 1970s (Bolch and Marchenko 2006). A satellite gravimet- * Jing Ming ric measurement revealed that the mass loss rate in the petermingjing@hotmail.com −1 −1 Tienshan glaciers was −5±6 Gt a (−0.32 ± 0.39 m w.e. a ) for year2003to2010(Jacobetal. 2012). The mass loss of Tienshan glaciers was primarily attributed National Climate Centre, China Meteorological Administration, Beijing 100081, China to the rapid regional warming at a decadal rate of +0.1 to +0.2 °C since the 1970s recorded by the meteorological stations, State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese associated with fewer precipitations contributing to drier sum- Academy of Sciences, Lanzhou 730000, China mers (Sorg et al. 2012). However, sparse studies investigated Peking University Hospital, Beijing 100871, China other factors like the depositions of light-absorbing impurities 9550 Environ Sci Pollut Res (2016) 23:9549–9558 (a) (LAIs) (e.g. aerosol black carbon (BC), dust, etc.) would also 75˚ 80˚ 85˚ 90˚ 95˚ induce a strong surface melting of the glaciers. This issue has 45˚ 45˚ been addressed by the studies regarding snow and ice of Tibet Urumqi Glacier No.1 Urumqi Glacier No.1 and Himalaya, northern China, and Greenland (Dumont et al. 2014;Ginotet al. 2014; Huang et al. 2011; Kaspari et al. 2014; Ming et al. 2012, 2013a, b;Qianetal. 2014;Quetal. 2014; 40˚ 40˚ Wang et al. 2015;Xuet al. 2009;Zhang etal. 2015). The Urumqi Glacier No.1 (TUG1) is one of the few Tienshan glaciers with long-term regular monitor, from which 35˚ 35˚ the results are annually released by the World Glacier Monitoring Service (WGMS 2012). This glacier has been experiencing a dramatic retreat since the 1980s and was sep- 30˚ 30˚ arated into two branches in 1993 (Li et al. 2003, 2007). The average annual mass balance of the glacier was −286 mm w.e. over the period 1959 to 2010 (Zhang et al. 2014). The main 75˚ 80˚ 85˚ 90˚ 95˚ factor inducing the shrinkage was attributed to temperature rising since the mid-1980s, simultaneously suggesting that (b) increased precipitation was not sufficient to compromise the impact of temperature rising (Li et al. 2007). AWS Takeuchi and Li (2008) first suggested that dust deposited S1 in the surface of the TUG1 substantially accounted for the shrinkage of the glacier. Xu et al. (2012) measured BC in a S2 snow pit throughout a 2-year field observation, suggesting S3 large variability of BC from 11 to 3000 ppb. Ming et al. West Branch (2013b) estimated that BC deposited in the glacial surface of S4 the TUG1 could cause an annually radiative forcing of −2 11 W m . None of the earlier studies combined BC and dust 4000 together to investigate the comprehensive effects of the LAIs S5 S6 on the reduction of albedo, especially in summers, when the glacier surface experiences strong melting. East Branch According to the observation records, the TUG1 usually displays Bgrey^ surfaces (very low albedo) in summers, when the albedo could reach as low as 0.1 to 0.3 (Kang and Ohmura Fig. 1 a Geographic map of the Urumqi Glacier No.1 (TUG1), and b study map of the Urumqi Glacier No.1, where sampling sites, elevation 1994). A darkened glacial surface induces strong melting con- contours, and AWS are shown, and the dashed is the traditional ELA line sequently. Besides relatively higher temperature in summers, who could be responsible for the darkening, BC or dust? In this work, we conducted a campaign on the traverse route of recorded by an automatic weather station (AWS) situated near the TUG1 during the summer of 2013 trying to interpret this the terminal of the TUG1 (Fig. 1b). issue partly. Snow sampling, and the measurements of snow density and grain size Study site and experimental methods Snow samples were collected at six sites (S1 to S6) from the The Tienshan Urumqi Glacier No.1 (43.10°N, 86.82°E), in the terminal to the accumulation zone (Fig. 1b). The surface fresh eastern Tienshan mountain (Fig. 1), is the best-monitored gla- snow was about 5–10 cm in depth; the depth of the aged snow cier in China (WGMS 2012). On 10 August 2013, a fine day beneath surface was not directly measured here and was re- with little cloud amount (Table 1)after asnow fall at night, we ported to be usually over 1 m by a multi-year snow-pit inves- conducted a field snow sampling and observations in the tra- tigation (Xu et al. 2012). The distance between two closest verse route of the eastern branch of the TUG1. Figure 2 de- sites was from 100 to 400 m. Aged snow completely covered scribes the usual and after-snowfall looks of the TUG1 in the the surface of the glacier on the 9th (Fig. 2a). Five fresh snow summer. The snow depth on the land surface was 5 to 10 cm samples were collected from the same surface layer at each due to the snowfall checked on the 10th morning, and the site, and then the upper fresh snow was scraped off using a precipitation amount on the 9th to 10th was 35 mm w.e. stainless scoop and left a fresh-snow-free area of around 1 m . Environ Sci Pollut Res (2016) 23:9549–9558 9551 Table 1 The sampling sites, field measurements, and the BC and dust and insoluble particles in snow samples Site Long Lati Alti Cloud amount Sample Density Sample Snow grain Sample BC Dust BC Dust Particle Mean particle −3 5 −1 code (°E) (°N) (m) (10 = 100 %) type (kg m ) code median size (mm) volume (ml) (μg) (mg) (ppb) (ppm) (×10 ml ) size (μm) S1 86.8119 43.1164 3845 2 Fresh snow 239 1-1 0.2 39.0 2.45 1.51 63 39 n/a n/a 171 1-2 28.0 1.74 1.07 62 38 0.72 1.35 191 1-3 26.0 0.85 0.53 33 20 1.41 1.41 1-4 31.5 1.54 1.59 49 50 1.88 1.52 1-5 39.0 1.14 1.40 29 36 1.04 1.27 S2 86.8111 43.1142 3881 1 Fresh snow 188 2-1 0.35 38.0 0.96 0.61 25 16 1.36 1.48 135 2-2 35.5 1.63 1.62 46 46 1.73 1.30 180 2-3 45.5 1.34 0.56 30 12 2.87 1.21 2-4 45.0 0.75 0.54 17 12 1.37 1.58 2-5 50.0 0.97 0.46 19 9 1.05 1.31 S3 86.8106 43.1131 3893 3 Fresh snow 192 3-1 0.275 52.5 1.58 0.60 30 12 1.00 1.33 213 3-2 54.0 0.88 0.59 16 11 0.94 1.81 216.5 3-3 51.5 1.22 0.58 24 11 0.74 2.20 3-4 53.0 0.82 1.16 16 22 1.08 1.66 3-5 58.0 1.79 0.88 31 15 0.92 1.58 Aged snow n/a n/a n/a n/a n/a n/a n/a S4 86.8089 43.1106 3934 3 Fresh snow 228.5 4-1 0.35 58.0 1.34 1.43 23 25 1.75 1.29 215.5 4-2 52.0 1.54 0.60 30 12 1.62 1.42 203 4-3 47.0 0.90 1.48 19 31 1.13 1.38 4-4 64.0 1.80 0.53 28 8 1.71 1.43 4-5 57.0 0.88 0.32 15 6 1.53 1.40 Aged snow n/a 4-1* n/a 40.0 n/a 206.83 n/a 5171 2.88 3.81 n/a 4-2* 41.0 n/a 59.48 n/a 1451 98.59 1.80 n/a 4-3* 31.5 n/a 71.71 n/a 2277 65.12 1.93 4-4* 34.0 n/a 206.16 n/a 6063 259.40 1.92 4-5* 45.5 n/a 226.04 n/a 4968 45.21 1.59 S5 86.8078 43.1058 4040 1 Fresh snow 260 5-1 0.2 41.5 1.18 0.31 28 8 2.86 1.36 301.5 5-2 65.0 1.84 1.10 28 17 2.71 1.23 261.5 5-3 51.5 1.76 0.79 34 15 1.78 1.43 5-4 66.5 1.45 0.71 22 11 2.22 1.38 5-5 54.0 1.15 0.69 21 13 1.16 1.67 Aged snow 427.5 5-1* 3 61.0 41.69 2.39 683 39 8.20 1.79 455.5 5-2* 69.5 26.39 1.95 380 28 4.50 1.68 492 5-3* 55.0 71.12 4.27 1293 78 3.98 1.99 9552 Environ Sci Pollut Res (2016) 23:9549–9558 The distinct colours and hardness feeling of aged and fresh snow may guarantee the complete removal of the fresh snow away from the top of aged snow. The aged snow was exposed and five samples were collected at each site from S4 to S6 (Table 1). All the samples were stored in pre-cleaned HDPE bottles and kept frozen until submitting to instrument for anal- ysis. Snow densities were measured for both fresh and aged snow using an electrical scale (±1 g) and a 200-ml steel-wedge container. Snow grain sizes were measured using a ×25 lens with the precision of 0.02 mm. The measurement of snow surface reflectance and calculation of broadband albedo At each site, snow surface spectral reflectance from visible to near-infrared (350–1050 nm) wavelengths was measured using a portable spectroradiometer (MS-720, Eiko Seiki, Japan). The optical measurements followed the method used by Takeuchi and Li (2008). The optical sensor of MS-720 was held and fixed at a height of 20 cm above the snow surface in the nadir-viewing position, allowing a measuring spot of 8.9 cm in diameter on snow. The optical measurement at each site was conducted ran- domly three times both for fresh and aged snow surfaces. Before Fig. 2 Pictures of the TUG1 taken on a 9th and b 10th August of 2013 Table 1 (continued) Site Long Lati Alti Cloud amount Sample Density Sample Snow grain Sample BC Dust BC Dust Particle Mean particle −3 5 −1 code (°E) (°N) (m) (10 = 100 %) type (kg m ) code median size (mm) volume (ml) (μg) (mg) (ppb) (ppm) (×10 ml ) size (μm) 5-4* 43.5 178.07 7.68 4093 177 5.93 2.24 5-5* 59.0 132.10 7.03 2239 119 5.55 2.31 S6 86.8064 43.1053 4050 0 Fresh snow 378.5 6-1 0.275 51.5 1.16 0.66 23 13 1.65 1.34 344.5 6-2 61.0 1.60 0.91 26 15 1.92 1.27 319.5 6-3 61.7 1.82 1.06 29 17 1.35 1.33 6-4 56.7 1.53 1.00 27 18 1.98 1.34 6-5 53.5 1.50 1.12 28 21 1.48 1.39 Aged snow 446 6-1* 2 90.5 n/a 40.76 n/a 450 2.86 2.69 440.5 6-2* 85.5 n/a 21.83 n/a 255 4.69 2.68 495 6-3* 84.0 n/a 16.68 n/a 199 2.85 2.95 6-4* 90.0 n/a 42.71 n/a 475 4.06 2.73 6-5* 90.0 n/a 76.41 n/a 849 2.48 3.72 Environ Sci Pollut Res (2016) 23:9549–9558 9553 and after the measurement at a specific site, the surface of a Hydrochloric acid (2–4 %) was added into the filters to re- white reference panel that is nearly 100 % reflective and diffuse move possible carbonates for the latter BC analysis and let dry. wasmeasuredbyMS-720to get theincomingirradiance. The More detailed description of the pretreatment of the snow sam- spectral reflectance of the sites was obtained by dividing snow ples before BC analysis can be referred to the earlier studies surface irradiance by the irradiance acquired from the reference (Ming et al. 2009, 2013a). A DRI-2001® model carbon analyser panel. The mean of the three surface measurements at a given (USA) was used to measure BC content in the sample filters. site is the average reflectance at that site. And the broadband This instrument is built on thermal/optical reflectance (TOR) albedo of a specific surface was calculated as the sum of the method and following the Interagency Monitoring of Protected reflective irradiance at all spectral wavelengths divided by the Visual Environments (IMPROVE) protocol (Chow et al. 2004). sum of the incoming irradiance. The sample filter is heated stepwise at 120, 250, 450, and 550 °C The uncertainty of measuring the albedos of fresh and aged for organic carbon (OC) in a non-oxidizing (He) atmosphere, snow remains here. For optically thin snow, the albedo of snow- and at 550, 700, and 800 °C for total BC in an oxidizing atmo- pack will be influenced by the albedo of underlying ground. In sphere of 2 % oxygen and 98 % He. Evolved carbon is oxidized our work, aged snow is beneath surface fresh snow, and beneath to CO , and then reduced to CH detected by a flame ionization 2 4 aged snow is the glacier ice. This has been taken into account detector. The portion of BC detected at 550 °C until the laser when simulating the albedos of different snow types. signal returns to its initial value is assigned to pyrolyzed organic carbon (OP). BC is calculated as the residue amount by The measurements of insoluble particle numbers and sizes subtracting the OP from total BC. in snow samples More detailed description of the working principle of DRI- 2001 can be referred to by DRI (2005). The mean BC-mass −2 In the laboratory, snow samples were put in room temperature density of the five blanks is 0.41 ± 0.29 μgcm . BC loadings and allowed to melt into liquid within 2 h. Ultrasonic bath was on the sample filters were the BC masses measured by DRI applied for the sample bottles for 15 min to remove insoluble subtracting the mean mass of the blank filters. Only BC is particles (IPs) in samples possibly attached to the walls of the adopted for this study, and OC is not considered here bottle (Ming et al. 2008). Then 1-ml aliquot of the liquid (Table 1). Unfortunately, the instrument could not measure sample was transferred by a pipette and submitted to the BC in the aged snow samples collected at S4, and S6, proba- Single Particle Optical Sensing system (Accusizer 780A, bly due to high dust loads in the filters. Only samples from the PPS, USA). This instrument allows a single particle in the size site S5 were successfully measured for BC. range of 0.5 to 400 μm to pass the laser (630 μm) to measure the sizes and numbers of the IPs in the sample (Table 1). The other liquid portions of the snow sample would be applied for Results and discussion the measurement of LAIs. Fresh and aged snow surfaces of the UR1 The measurements of the LAIs in the snow samples The UR1 experiences strong melting in summers, when The volumes of the snow samples were measured with a grad- 80 % surface usually looks Bgrey^ (Fig. 2a). However, uated cylinder (±1 ml) (Table 1) and then filtered through when snow falls occasionally, it will whiten the surface, quartz-fibre filters (25 mm). These filters were preheated for and the Bwhite^ surface usually lasts a few days (Fig. 2b). 2 h in an oven at 800 °C to eliminate any carbon contents. A The meteorological data recorded by the AWS show that hand vacuum pump was used to accelerate filtering. After the mean temperature at the terminal of the TUG1 in the filtering of each sample, the containers and filtration unit were daytime of 10th August was 8 °C. High air temperatures rinsed four times with ultra-pure water to make sure transfer- in the summer time enhance surface snow ageing and ring the carbonaceous particles to the filter. The capture of BC melting. Snow density and snow grain size are very dif- particles was believed to be better than 97 % (Cachier and ferent for fresh and aged snow. The mean snow density of −3 Pertuisot 1994). freshsnowfrom S1to S6 is 243 kg m ,while that of −3 The filters would be moved into the petri-slides and set in aged snow from S5 to S6 is 460 kg m (Table 1). The the laminar flow cabinet to let dry. The rinsing solution after mean snow grain size of fresh snow is 0.29 mm, while washing the blank bottles with ultrapure water would pass that of aged snow (2.5 mm) is much larger. The monitor- through clean filters for making five blank filters. Before ing record of the TUG1 shows that the equilibrium line and after filtering, the mass of the filter was measured three altitude (ELA) of the UR1 was 4267 m in 2013, which is times with a microbalance (±1 μg), respectively. The dust approximately 200 m higher than the mean of 1959–2010 loading on the sample filter was determined as the weight of (Zhang et al. 2014) and indicating that extremely strong the filter after filtering subtracting that before filtering. surface melting occurs. The elevations of all sampling 9554 Environ Sci Pollut Res (2016) 23:9549–9558 Fig. 3 The mean concentrations (a) (b) Site Code Site Code of a BC and b dust in fresh (blue S4* S5* S6* S4* S5* S6* line and dots) and aged (red line 70 4000 50 10000 and dots) snow at the sampling sites. Error bars were calculated as the standard deviations of five samples at each site 50 1000 40 2000 30 100 10 0 0 10 S1 S2 S3 S4 S5 S6 S1 S2 S3 S4 S5 S6 Site Code Site Code sites are far below the ELA of 2013. These sites are all typical glaciers in Tibet (Ming et al. 2013b). The spatial dis- located in strong ablation zone and fresh snow can change tributions of the LAIs in the aged-snow sites could not be to aged snow easily, which would make the TUG1 look discussed here in detail due to very limited data. One possi- not Bwhite^ any more in a short time (Fig. 2). bility is that the BC concentrations in the aged snow at the sites S4 and S6 should be much higher than at S5, if a similar The LAIs and the IPs in fresh and aged snow correlation between dust and BC like in the fresh snow applies to the aged snow. The LAIs in aged snow are generally 1 to 2 The spatial distributions of BC and dust in the sites (S1 to S6) orders of magnitude higher than those in fresh snow. The BC of aged snow at S5 is as high as 1738 ppb with large uncer- collecting fresh snow are closely related, although their mean concentrations show large uncertainties at each site (Fig. 3). tainty (Fig. 3a), and the dust of aged snow varies from 88 ppm at S5 to nearly 4000 ppm at S4 (Fig. 3b). Variability of BC The co-variation of BC and dust in fresh snow suggests they could be well mixed after post-deposition process (Xu et al. from fresh to aged snow here is similar to that measured by Xu et al. (2012). The mean of the IP numbers in fresh snow is 2012). The largest mean BC (47 ppb) in fresh snow is found at 5 −1 S1, in consistent with dust, of which the largest mean is (1.54 ± 0.41) × 10 ml , showing smaller variation than that 5 −1 37 ppm at S1, and at the sites of S2 to S6, the concentrations in aged snow. The IP number can reach 99 × 10 ml in aged snow at S4 (Fig. 4a). The mean IP size in fresh snow is of the LAIs do not show large variations, but more stable (25 ± 2 ppb for BC and 16± 2 ppm for dust). BC in fresh snow of 1.4 μm, while that in aged snow is 1-μm larger (Fig. 4b). The number-and-size variations of IP associated with BC TUG1 has no large difference with that measured in other Fig. 4 The a concentrations and (a) (b) Site Code Site Code b sizes of the insoluble particles in S4* S5* S6* S4* S5* S6* fresh (blue line and dots)and 10 10 3.5 3.5 aged (redlineand dots) snow at the sampling sites. Error bars 8 8 3 3 were calculated as the standard deviations of five samples at each site 5.6 6 6 2.5 2.5 4 4 2 2 3.4 2 2 1.5 1.5 0 0 1 1 S1 S2 S3 S4 S5 S6 S1 S2 S3 S4 S5 S6 Site Code Site Code -1 Insoluble Particle (×10 ml ) BC (ppb) 5 -1 Insoluble Particle ( ×10 ml ) BC (ppb) Dust (ppm) Dust (ppm) Environ Sci Pollut Res (2016) 23:9549–9558 9555 Fig. 5 a The mean spectral (a) (b) Site Code reflectances of the fresh (blue) S3* S4* S5* S6* 1 1 and aged (red) snow surfaces with one ± σ,and b the broadband albedos of the fresh (blue)and 0.8 0.8 0.8 aged (red) snow surfaces 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0 0 0 350 450 550 650 750 850 950 1050 S1 S2 S3 S4 S5 S6 Wavelength (nm) Site Code and dust in fresh and aged snow imply IPs including BC and Simulating the impacts of BC and dust on the snow albedo dust could be aggregated during the post-depositional process and darken the surface of the UR1. The process of a Bwhite^ glacier turning into Bgrey^ glacier is associated with the evolution of fresh snow to aged snow and the aggregations of the IPs including dust and BC. The online Surface reflectances and broadband albedos of fresh SNICAR model was developed by Flanner et al. (2007)and and aged snow and estimated forcing commonly used in simulating the impacts of LAIs on snow- and-ice albedos (Hadley and Kirchstetter 2012; McConnell The mean spectral surface reflectances of fresh and aged et al. 2007;Qu et al. 2014). Basically, the model utilizes a snow are presented in Fig. 5a. For the fresh snow, most two-stream radiative transfer method (Toon et al. 1989), assem- spectral reflectances in the wavelength range of 350– bles input parameters (e.g. radiation condition, surface spectral 1050 nm are higher than 0.8, with no significant differ- distribution, snow grain effective radius, black carbon and dust, ences from that measured for the newly fallen snow pack etc.) in an online platform (http://snow.engin.umich.edu/), and at Tibet (Ming et al. 2013a), while the reflectances of the can be easily operated. More details can be referred to from aged snow drop dramatically and vary around 0.4 at the Flanner et al. (2007). Snow ageing (snow density increases visible and infrared wavelengths. The mean broadband albedos of the fresh and aged snow are 0.85 and 0.43, respectively, showing large differences (Fig. 5b). Roughly, higher sites have larger albedos (Fig. 5b). For fresh snow, the mean broadband albedos show smaller variability (Fig. 5a). Downward shortwave radiation data recorded by the AWS at the terminal of the TUG1 (Fig. 1b)can be used to calculate the surface budget of solar radiation. For the enhanced directly reflecting and diffusing effect in a val- -2 427 W m ley glacier, true downward solar radiation may be even stronger. On 10th August, the downward solar radiation varied between a few watts per square metre early in the −2 morning and late in the night and nearly 1000 W m peakingatnoon(Fig. 6). In the surface of fresh snow, −2 the net flux of solar radiation was 64 W m ,taking −2 427 W m as the mean incoming radiation. However, −2 for aged snow, the net flux is as high as 243 W m . 0 8:00 10:00 12:00 14:00 16:00 18:00 20:00 The total forcing caused by the transformation from the 10 Aug, 2013 −2 fresh snow to the aged could be 180 W m ,presuming Fig. 6 The downward solar irradiance measured by the AWS, where the that the TUG1 on 10th would be evolved to the grey black dots are the half-hour measurements, the blue line is the running average, and the red dashed is the mean surface on 9th in a few days. Reflectance -2 Incoming shortwave irradiance recorded by AWS (W m ) Albedo Albedo 9556 Environ Sci Pollut Res (2016) 23:9549–9558 Table 2 The parameters used in the albedo simulation for fresh and aged snow and other designed scenarios at site 5 Snow types and scenarios Surface fresh Beneath aged Snow ageing Fresh Fresh Snow Snow Remark snow at S5 snow at S5* excluding BC snow + dust snow + BC ageing + dust ageing + BC and dust aggregation aggregation aggregation aggregation aggregation excluding snow excluding snow excluding BC excluding dust ageing and BC ageing and dust aggregation aggregation aggregation aggregation Solar zenith angle (°) 37 37 37 37 37 37 37 Snowpack depth (m) 0.1 1 1 0.1 0.1 1 1 −3 Snow density (kg m ) 274 458 458 274 274 458 458 Cloud amount 111 1111Clear-skyfor (10 = 100 %) modelling Snow grain radius (μm) 100 1500 1500 100 100 1500 1500 Albedo of underlying 0.62 0.2 0.2 0.62 0.62 0.2 0.2 ground (0.3–0.7 μm) Albedo of underlying 0.53 0.1 0.1 0.53 0.53 0.1 0.1 ground (0.7–5.0 μm) Sulfate-coated BC (ppb) 27 1738 27 27 1738 27 1738 Dust(ppm) 138813 88138813 Mean particle size (μm) 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 Mean sizes are 1.41 and 2.00 μmfor fresh and aged snow, respectively MAC scaling factor 11.3 11.3 11.3 11.3 11.3 11.3 11.3 Hydrophilic BC (experimental) Simulated albedo 0.782 0.325 0.580 0.752 0.667 0.511 0.316 Measured albedo 0.771 0.587 Albedo reduction 0.457 0.202 0.030 0.115 0.271 0.466 Attributable proportion 44 7 25 59 (%) Environ Sci Pollut Res (2016) 23:9549–9558 9557 and grain size grows) due to warming, and BC and dust aggre- For being lack of more comprehensive observation data, a gations were considered to be three main factors impacting sur- complete conclusion of the impacts of LAIs on the surface face albedo. Here, the model is applied to calculate the albedo of albedo of TUG1 glacier cannot be drawn here. the fresh snow, aged snow, and other three presumed surface conditions of the TUG1. We only made a case study specific for site S5, due to the incompleteness of the dataset obtained at other Conclusions sites needed for simulating the albedo reduction caused by LIAs. The snow-pack depth was set to be 1 m, according to an earlier Fresh and aged snow samples were collected on the east study (Xu et al. 2012). Other different parameters needed for the branch of the TUG1 on 10 August 2013 after a snowfall at fresh and aged snow were listed in Table 2. night. Measurements including snow densities and grain sizes Here are some descriptions how to choose the parameters and spectral reflectances were made in the transect route from to simulate the albedo of different snow using online SNICAR the terminal to the accumulation zone. High temperatures in model. Solar zenith angle was calculated according to the the summer probably enhanced the surface snow ageing and local sampling time and geographic locations. Snowpack melting. The snow density and grain size increased from 243 −3 depth was considered as 0.1 m for fresh snow and 1 m for to 458 kg m and from 290 to 2500 μm during the ageing aged snow. Snow densities were taken as measured. Clear sky process, along with the number and size of the IPs increase. and direct radiation were chosen for the very low cloud Concentrations of dust and BC in fresh snow are 16 ppm and amount (∼1). We consider aged snow and glacier ice are the 25 ppb, respectively. While in aged snow beneath the fresh, underlying grounds for fresh snow and aged snow. Thus, the their concentrations can be as high as 1507 ppm and underlying albedos of fresh and aged snow was set as 0.62 1738 ppb. The albedo discrepancy of fresh and aged snow (0.3–0.7 μm) and 0.53 (0.7–5.0 μm) as measured, and 0.2 can be as large as 0.40, indicating a consequent forcing of −2 (0.3–0.7 μm) and 0.1 (0.7–5.0 μm) by Zeng et al. (1984), 180 W m during the post-deposition process. At the accu- respectively. BC was thought to be sulfate-coated after long- mulative zone, snow ageing (44 %) is the most significant distance transport (Ming et al. 2009) and to be hydrophilic factor decreasing the albedo, BC (25 %) is the next, and then with the median mass absorption cross section (MAC) of dust (7 %). For the lack of dataset, the complete conclusion of 2 −1 11.3 m g (Flanner et al. 2007). Mean particle size was set impacting factors decreasing the surface albedo of TUG1 can- according to the measured mean size. not be drawn at present. Simulated albedo of the fresh snow at S5 was 0.77, close to the measured value (0.78). The model did not simulate the expected albedo of aged snow at S5. The simulated albedo Acknowledgments We would like to thank Chunhai Xu and Wuhua Chen for helping with the field work, and Yuman Zhu and Yun Yang for of the beneath aged snow was 0.33, remarkably lower than the helping analyse the samples. This work is supported by the Chinese measured (Table 2). The simulated albedo was close to that of Academy of Sciences (KJZD-EW-G03-03), Visiting Scholarship the aged snow only considering snow ageing, possibly indi- Program of the China Scholarship Council (2014), China Special Fund cating snow ageing due to warming was the predominant to for Meteorological Research in the Public Interest (GYHY201406016), and the Special Fund on Climate Change of China Meteorological reduce the snow albedo, concealing the impacts of other LAIs Administration (2013–2014). during the post-deposition processes. We presumed another two independent scenarios; only dust and only BC with mea- Open Access This article is distributed under the terms of the sured concentrations were applied to fresh snow, separately. In Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted the condition fresh snow only with dust aggregation was con- use, distribution, and reproduction in any medium, provided you give sidered, the albedo decreased from 0.78 to 0.75. If fresh snow appropriate credit to the original author(s) and the source, provide a link only with BC aggregation was considered, the albedo de- to the Creative Commons license, and indicate if changes were made. creased from 0.78 to 0.67. The effect of BC on albedo reduc- tion exceeded that of dust. However, the reality was the mea- sured albedo of aged snow is not the expected simulated val- References ue, but far higher than that. 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Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities

Environmental Science and Pollution Research International , Volume 23 – Feb 3, 2016

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© The Author(s) 2016
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0944-1344
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10.1007/s11356-016-6182-7
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Abstract

Environ Sci Pollut Res (2016) 23:9549–9558 DOI 10.1007/s11356-016-6182-7 RESEARCH ARTICLE Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities 1,2 2 2 2 3 Jing Ming & Cunde Xiao & Feiteng Wang & Zhongqin Li & Yamin Li Received: 31 August 2015 /Accepted: 26 January 2016 /Published online: 3 February 2016 The Author(s) 2016. This article is published with open access at Springerlink.com . . . . Abstract The Tienshan Urumqi Glacier No.1 (TUG1) usually Keywords Black carbon (BC) Dust Albedo Glacier shows Bgrey^ surfaces in summers. Besides known regional Tienshan warming, what should be responsible for largely reducing its surface albedo and making it look Bgrey^? A field campaign was conducted on the TUG1 on a selected cloud-free day of Introduction 2013 after a snow fall at night. Fresh and aged snow samples were collected in the field, and snow densities, grain sizes, and Mountain glaciers, different from the Arctic and Antarctic ice spectral reflectances were measured. Light-absorbing impurities sheets, are geographically much closer to human settlements, (LAIs) including black carbon (BC) and dust, and number con- such as the mid-latitude glaciers in the Alps, Caucasus, High- centrations and sizes of the insoluble particles (IPs) in the sam- mountain Asia, and Southern Andes (Ming et al. 2015; Gardner ples were measured in the laboratory. High temperatures in sum- et al. 2013;Zengetal. 1984). They store water resources as mer probably enhanced the snow ageing. During the snow age- snow and ice in cold seasons and release them in warm seasons, −3 ingprocess,the snow densityvariedfrom243to458kgm , which directly adjust fresh water supplies to the lives of the associated with the snow grain size varying from 290 to surrounding people, especially to those who are living in arid 2500 μm. The concentrations of LAIs in aged snow were sig- regions. From this angle of view, mountain glaciers are the most nificantly higher than those in fresh snow. Dust and BC varied important water resource in the wide arid and semi-arid regions from 16 ppm and 25 ppb in fresh snow to 1507 ppm and like Central Asia. 1738 ppb in aged snow, respectively. Large albedo difference Tien Shan Mountains, one of few areas holding most con- between the fresh and aged snow suggests a consequent forcing centrated glaciers in the mid-latitudes of the northern −2 of 180 W m . Simulations under scenarios show that snow Hemisphere, is home of nearly 16,000 glaciers (Aizen et al. ageing, BC, and dust were responsible for 44, 25, and 7 % of 2007). More than 100 million people live on the water sourced the albedo reduction in the accumulation zone, respectively. from these glaciers, which are also called the BWater Tower of Central Asia^. The Tienshan glaciers have been shrinking since the end of Little Ice Age in the mid-nineteenth century Responsible editor: Gerhard Lammel (Sorg et al. 2012) and the shrinkage has been accelerated since the 1970s (Bolch and Marchenko 2006). A satellite gravimet- * Jing Ming ric measurement revealed that the mass loss rate in the petermingjing@hotmail.com −1 −1 Tienshan glaciers was −5±6 Gt a (−0.32 ± 0.39 m w.e. a ) for year2003to2010(Jacobetal. 2012). The mass loss of Tienshan glaciers was primarily attributed National Climate Centre, China Meteorological Administration, Beijing 100081, China to the rapid regional warming at a decadal rate of +0.1 to +0.2 °C since the 1970s recorded by the meteorological stations, State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese associated with fewer precipitations contributing to drier sum- Academy of Sciences, Lanzhou 730000, China mers (Sorg et al. 2012). However, sparse studies investigated Peking University Hospital, Beijing 100871, China other factors like the depositions of light-absorbing impurities 9550 Environ Sci Pollut Res (2016) 23:9549–9558 (a) (LAIs) (e.g. aerosol black carbon (BC), dust, etc.) would also 75˚ 80˚ 85˚ 90˚ 95˚ induce a strong surface melting of the glaciers. This issue has 45˚ 45˚ been addressed by the studies regarding snow and ice of Tibet Urumqi Glacier No.1 Urumqi Glacier No.1 and Himalaya, northern China, and Greenland (Dumont et al. 2014;Ginotet al. 2014; Huang et al. 2011; Kaspari et al. 2014; Ming et al. 2012, 2013a, b;Qianetal. 2014;Quetal. 2014; 40˚ 40˚ Wang et al. 2015;Xuet al. 2009;Zhang etal. 2015). The Urumqi Glacier No.1 (TUG1) is one of the few Tienshan glaciers with long-term regular monitor, from which 35˚ 35˚ the results are annually released by the World Glacier Monitoring Service (WGMS 2012). This glacier has been experiencing a dramatic retreat since the 1980s and was sep- 30˚ 30˚ arated into two branches in 1993 (Li et al. 2003, 2007). The average annual mass balance of the glacier was −286 mm w.e. over the period 1959 to 2010 (Zhang et al. 2014). The main 75˚ 80˚ 85˚ 90˚ 95˚ factor inducing the shrinkage was attributed to temperature rising since the mid-1980s, simultaneously suggesting that (b) increased precipitation was not sufficient to compromise the impact of temperature rising (Li et al. 2007). AWS Takeuchi and Li (2008) first suggested that dust deposited S1 in the surface of the TUG1 substantially accounted for the shrinkage of the glacier. Xu et al. (2012) measured BC in a S2 snow pit throughout a 2-year field observation, suggesting S3 large variability of BC from 11 to 3000 ppb. Ming et al. West Branch (2013b) estimated that BC deposited in the glacial surface of S4 the TUG1 could cause an annually radiative forcing of −2 11 W m . None of the earlier studies combined BC and dust 4000 together to investigate the comprehensive effects of the LAIs S5 S6 on the reduction of albedo, especially in summers, when the glacier surface experiences strong melting. East Branch According to the observation records, the TUG1 usually displays Bgrey^ surfaces (very low albedo) in summers, when the albedo could reach as low as 0.1 to 0.3 (Kang and Ohmura Fig. 1 a Geographic map of the Urumqi Glacier No.1 (TUG1), and b study map of the Urumqi Glacier No.1, where sampling sites, elevation 1994). A darkened glacial surface induces strong melting con- contours, and AWS are shown, and the dashed is the traditional ELA line sequently. Besides relatively higher temperature in summers, who could be responsible for the darkening, BC or dust? In this work, we conducted a campaign on the traverse route of recorded by an automatic weather station (AWS) situated near the TUG1 during the summer of 2013 trying to interpret this the terminal of the TUG1 (Fig. 1b). issue partly. Snow sampling, and the measurements of snow density and grain size Study site and experimental methods Snow samples were collected at six sites (S1 to S6) from the The Tienshan Urumqi Glacier No.1 (43.10°N, 86.82°E), in the terminal to the accumulation zone (Fig. 1b). The surface fresh eastern Tienshan mountain (Fig. 1), is the best-monitored gla- snow was about 5–10 cm in depth; the depth of the aged snow cier in China (WGMS 2012). On 10 August 2013, a fine day beneath surface was not directly measured here and was re- with little cloud amount (Table 1)after asnow fall at night, we ported to be usually over 1 m by a multi-year snow-pit inves- conducted a field snow sampling and observations in the tra- tigation (Xu et al. 2012). The distance between two closest verse route of the eastern branch of the TUG1. Figure 2 de- sites was from 100 to 400 m. Aged snow completely covered scribes the usual and after-snowfall looks of the TUG1 in the the surface of the glacier on the 9th (Fig. 2a). Five fresh snow summer. The snow depth on the land surface was 5 to 10 cm samples were collected from the same surface layer at each due to the snowfall checked on the 10th morning, and the site, and then the upper fresh snow was scraped off using a precipitation amount on the 9th to 10th was 35 mm w.e. stainless scoop and left a fresh-snow-free area of around 1 m . Environ Sci Pollut Res (2016) 23:9549–9558 9551 Table 1 The sampling sites, field measurements, and the BC and dust and insoluble particles in snow samples Site Long Lati Alti Cloud amount Sample Density Sample Snow grain Sample BC Dust BC Dust Particle Mean particle −3 5 −1 code (°E) (°N) (m) (10 = 100 %) type (kg m ) code median size (mm) volume (ml) (μg) (mg) (ppb) (ppm) (×10 ml ) size (μm) S1 86.8119 43.1164 3845 2 Fresh snow 239 1-1 0.2 39.0 2.45 1.51 63 39 n/a n/a 171 1-2 28.0 1.74 1.07 62 38 0.72 1.35 191 1-3 26.0 0.85 0.53 33 20 1.41 1.41 1-4 31.5 1.54 1.59 49 50 1.88 1.52 1-5 39.0 1.14 1.40 29 36 1.04 1.27 S2 86.8111 43.1142 3881 1 Fresh snow 188 2-1 0.35 38.0 0.96 0.61 25 16 1.36 1.48 135 2-2 35.5 1.63 1.62 46 46 1.73 1.30 180 2-3 45.5 1.34 0.56 30 12 2.87 1.21 2-4 45.0 0.75 0.54 17 12 1.37 1.58 2-5 50.0 0.97 0.46 19 9 1.05 1.31 S3 86.8106 43.1131 3893 3 Fresh snow 192 3-1 0.275 52.5 1.58 0.60 30 12 1.00 1.33 213 3-2 54.0 0.88 0.59 16 11 0.94 1.81 216.5 3-3 51.5 1.22 0.58 24 11 0.74 2.20 3-4 53.0 0.82 1.16 16 22 1.08 1.66 3-5 58.0 1.79 0.88 31 15 0.92 1.58 Aged snow n/a n/a n/a n/a n/a n/a n/a S4 86.8089 43.1106 3934 3 Fresh snow 228.5 4-1 0.35 58.0 1.34 1.43 23 25 1.75 1.29 215.5 4-2 52.0 1.54 0.60 30 12 1.62 1.42 203 4-3 47.0 0.90 1.48 19 31 1.13 1.38 4-4 64.0 1.80 0.53 28 8 1.71 1.43 4-5 57.0 0.88 0.32 15 6 1.53 1.40 Aged snow n/a 4-1* n/a 40.0 n/a 206.83 n/a 5171 2.88 3.81 n/a 4-2* 41.0 n/a 59.48 n/a 1451 98.59 1.80 n/a 4-3* 31.5 n/a 71.71 n/a 2277 65.12 1.93 4-4* 34.0 n/a 206.16 n/a 6063 259.40 1.92 4-5* 45.5 n/a 226.04 n/a 4968 45.21 1.59 S5 86.8078 43.1058 4040 1 Fresh snow 260 5-1 0.2 41.5 1.18 0.31 28 8 2.86 1.36 301.5 5-2 65.0 1.84 1.10 28 17 2.71 1.23 261.5 5-3 51.5 1.76 0.79 34 15 1.78 1.43 5-4 66.5 1.45 0.71 22 11 2.22 1.38 5-5 54.0 1.15 0.69 21 13 1.16 1.67 Aged snow 427.5 5-1* 3 61.0 41.69 2.39 683 39 8.20 1.79 455.5 5-2* 69.5 26.39 1.95 380 28 4.50 1.68 492 5-3* 55.0 71.12 4.27 1293 78 3.98 1.99 9552 Environ Sci Pollut Res (2016) 23:9549–9558 The distinct colours and hardness feeling of aged and fresh snow may guarantee the complete removal of the fresh snow away from the top of aged snow. The aged snow was exposed and five samples were collected at each site from S4 to S6 (Table 1). All the samples were stored in pre-cleaned HDPE bottles and kept frozen until submitting to instrument for anal- ysis. Snow densities were measured for both fresh and aged snow using an electrical scale (±1 g) and a 200-ml steel-wedge container. Snow grain sizes were measured using a ×25 lens with the precision of 0.02 mm. The measurement of snow surface reflectance and calculation of broadband albedo At each site, snow surface spectral reflectance from visible to near-infrared (350–1050 nm) wavelengths was measured using a portable spectroradiometer (MS-720, Eiko Seiki, Japan). The optical measurements followed the method used by Takeuchi and Li (2008). The optical sensor of MS-720 was held and fixed at a height of 20 cm above the snow surface in the nadir-viewing position, allowing a measuring spot of 8.9 cm in diameter on snow. The optical measurement at each site was conducted ran- domly three times both for fresh and aged snow surfaces. Before Fig. 2 Pictures of the TUG1 taken on a 9th and b 10th August of 2013 Table 1 (continued) Site Long Lati Alti Cloud amount Sample Density Sample Snow grain Sample BC Dust BC Dust Particle Mean particle −3 5 −1 code (°E) (°N) (m) (10 = 100 %) type (kg m ) code median size (mm) volume (ml) (μg) (mg) (ppb) (ppm) (×10 ml ) size (μm) 5-4* 43.5 178.07 7.68 4093 177 5.93 2.24 5-5* 59.0 132.10 7.03 2239 119 5.55 2.31 S6 86.8064 43.1053 4050 0 Fresh snow 378.5 6-1 0.275 51.5 1.16 0.66 23 13 1.65 1.34 344.5 6-2 61.0 1.60 0.91 26 15 1.92 1.27 319.5 6-3 61.7 1.82 1.06 29 17 1.35 1.33 6-4 56.7 1.53 1.00 27 18 1.98 1.34 6-5 53.5 1.50 1.12 28 21 1.48 1.39 Aged snow 446 6-1* 2 90.5 n/a 40.76 n/a 450 2.86 2.69 440.5 6-2* 85.5 n/a 21.83 n/a 255 4.69 2.68 495 6-3* 84.0 n/a 16.68 n/a 199 2.85 2.95 6-4* 90.0 n/a 42.71 n/a 475 4.06 2.73 6-5* 90.0 n/a 76.41 n/a 849 2.48 3.72 Environ Sci Pollut Res (2016) 23:9549–9558 9553 and after the measurement at a specific site, the surface of a Hydrochloric acid (2–4 %) was added into the filters to re- white reference panel that is nearly 100 % reflective and diffuse move possible carbonates for the latter BC analysis and let dry. wasmeasuredbyMS-720to get theincomingirradiance. The More detailed description of the pretreatment of the snow sam- spectral reflectance of the sites was obtained by dividing snow ples before BC analysis can be referred to the earlier studies surface irradiance by the irradiance acquired from the reference (Ming et al. 2009, 2013a). A DRI-2001® model carbon analyser panel. The mean of the three surface measurements at a given (USA) was used to measure BC content in the sample filters. site is the average reflectance at that site. And the broadband This instrument is built on thermal/optical reflectance (TOR) albedo of a specific surface was calculated as the sum of the method and following the Interagency Monitoring of Protected reflective irradiance at all spectral wavelengths divided by the Visual Environments (IMPROVE) protocol (Chow et al. 2004). sum of the incoming irradiance. The sample filter is heated stepwise at 120, 250, 450, and 550 °C The uncertainty of measuring the albedos of fresh and aged for organic carbon (OC) in a non-oxidizing (He) atmosphere, snow remains here. For optically thin snow, the albedo of snow- and at 550, 700, and 800 °C for total BC in an oxidizing atmo- pack will be influenced by the albedo of underlying ground. In sphere of 2 % oxygen and 98 % He. Evolved carbon is oxidized our work, aged snow is beneath surface fresh snow, and beneath to CO , and then reduced to CH detected by a flame ionization 2 4 aged snow is the glacier ice. This has been taken into account detector. The portion of BC detected at 550 °C until the laser when simulating the albedos of different snow types. signal returns to its initial value is assigned to pyrolyzed organic carbon (OP). BC is calculated as the residue amount by The measurements of insoluble particle numbers and sizes subtracting the OP from total BC. in snow samples More detailed description of the working principle of DRI- 2001 can be referred to by DRI (2005). The mean BC-mass −2 In the laboratory, snow samples were put in room temperature density of the five blanks is 0.41 ± 0.29 μgcm . BC loadings and allowed to melt into liquid within 2 h. Ultrasonic bath was on the sample filters were the BC masses measured by DRI applied for the sample bottles for 15 min to remove insoluble subtracting the mean mass of the blank filters. Only BC is particles (IPs) in samples possibly attached to the walls of the adopted for this study, and OC is not considered here bottle (Ming et al. 2008). Then 1-ml aliquot of the liquid (Table 1). Unfortunately, the instrument could not measure sample was transferred by a pipette and submitted to the BC in the aged snow samples collected at S4, and S6, proba- Single Particle Optical Sensing system (Accusizer 780A, bly due to high dust loads in the filters. Only samples from the PPS, USA). This instrument allows a single particle in the size site S5 were successfully measured for BC. range of 0.5 to 400 μm to pass the laser (630 μm) to measure the sizes and numbers of the IPs in the sample (Table 1). The other liquid portions of the snow sample would be applied for Results and discussion the measurement of LAIs. Fresh and aged snow surfaces of the UR1 The measurements of the LAIs in the snow samples The UR1 experiences strong melting in summers, when The volumes of the snow samples were measured with a grad- 80 % surface usually looks Bgrey^ (Fig. 2a). However, uated cylinder (±1 ml) (Table 1) and then filtered through when snow falls occasionally, it will whiten the surface, quartz-fibre filters (25 mm). These filters were preheated for and the Bwhite^ surface usually lasts a few days (Fig. 2b). 2 h in an oven at 800 °C to eliminate any carbon contents. A The meteorological data recorded by the AWS show that hand vacuum pump was used to accelerate filtering. After the mean temperature at the terminal of the TUG1 in the filtering of each sample, the containers and filtration unit were daytime of 10th August was 8 °C. High air temperatures rinsed four times with ultra-pure water to make sure transfer- in the summer time enhance surface snow ageing and ring the carbonaceous particles to the filter. The capture of BC melting. Snow density and snow grain size are very dif- particles was believed to be better than 97 % (Cachier and ferent for fresh and aged snow. The mean snow density of −3 Pertuisot 1994). freshsnowfrom S1to S6 is 243 kg m ,while that of −3 The filters would be moved into the petri-slides and set in aged snow from S5 to S6 is 460 kg m (Table 1). The the laminar flow cabinet to let dry. The rinsing solution after mean snow grain size of fresh snow is 0.29 mm, while washing the blank bottles with ultrapure water would pass that of aged snow (2.5 mm) is much larger. The monitor- through clean filters for making five blank filters. Before ing record of the TUG1 shows that the equilibrium line and after filtering, the mass of the filter was measured three altitude (ELA) of the UR1 was 4267 m in 2013, which is times with a microbalance (±1 μg), respectively. The dust approximately 200 m higher than the mean of 1959–2010 loading on the sample filter was determined as the weight of (Zhang et al. 2014) and indicating that extremely strong the filter after filtering subtracting that before filtering. surface melting occurs. The elevations of all sampling 9554 Environ Sci Pollut Res (2016) 23:9549–9558 Fig. 3 The mean concentrations (a) (b) Site Code Site Code of a BC and b dust in fresh (blue S4* S5* S6* S4* S5* S6* line and dots) and aged (red line 70 4000 50 10000 and dots) snow at the sampling sites. Error bars were calculated as the standard deviations of five samples at each site 50 1000 40 2000 30 100 10 0 0 10 S1 S2 S3 S4 S5 S6 S1 S2 S3 S4 S5 S6 Site Code Site Code sites are far below the ELA of 2013. These sites are all typical glaciers in Tibet (Ming et al. 2013b). The spatial dis- located in strong ablation zone and fresh snow can change tributions of the LAIs in the aged-snow sites could not be to aged snow easily, which would make the TUG1 look discussed here in detail due to very limited data. One possi- not Bwhite^ any more in a short time (Fig. 2). bility is that the BC concentrations in the aged snow at the sites S4 and S6 should be much higher than at S5, if a similar The LAIs and the IPs in fresh and aged snow correlation between dust and BC like in the fresh snow applies to the aged snow. The LAIs in aged snow are generally 1 to 2 The spatial distributions of BC and dust in the sites (S1 to S6) orders of magnitude higher than those in fresh snow. The BC of aged snow at S5 is as high as 1738 ppb with large uncer- collecting fresh snow are closely related, although their mean concentrations show large uncertainties at each site (Fig. 3). tainty (Fig. 3a), and the dust of aged snow varies from 88 ppm at S5 to nearly 4000 ppm at S4 (Fig. 3b). Variability of BC The co-variation of BC and dust in fresh snow suggests they could be well mixed after post-deposition process (Xu et al. from fresh to aged snow here is similar to that measured by Xu et al. (2012). The mean of the IP numbers in fresh snow is 2012). The largest mean BC (47 ppb) in fresh snow is found at 5 −1 S1, in consistent with dust, of which the largest mean is (1.54 ± 0.41) × 10 ml , showing smaller variation than that 5 −1 37 ppm at S1, and at the sites of S2 to S6, the concentrations in aged snow. The IP number can reach 99 × 10 ml in aged snow at S4 (Fig. 4a). The mean IP size in fresh snow is of the LAIs do not show large variations, but more stable (25 ± 2 ppb for BC and 16± 2 ppm for dust). BC in fresh snow of 1.4 μm, while that in aged snow is 1-μm larger (Fig. 4b). The number-and-size variations of IP associated with BC TUG1 has no large difference with that measured in other Fig. 4 The a concentrations and (a) (b) Site Code Site Code b sizes of the insoluble particles in S4* S5* S6* S4* S5* S6* fresh (blue line and dots)and 10 10 3.5 3.5 aged (redlineand dots) snow at the sampling sites. Error bars 8 8 3 3 were calculated as the standard deviations of five samples at each site 5.6 6 6 2.5 2.5 4 4 2 2 3.4 2 2 1.5 1.5 0 0 1 1 S1 S2 S3 S4 S5 S6 S1 S2 S3 S4 S5 S6 Site Code Site Code -1 Insoluble Particle (×10 ml ) BC (ppb) 5 -1 Insoluble Particle ( ×10 ml ) BC (ppb) Dust (ppm) Dust (ppm) Environ Sci Pollut Res (2016) 23:9549–9558 9555 Fig. 5 a The mean spectral (a) (b) Site Code reflectances of the fresh (blue) S3* S4* S5* S6* 1 1 and aged (red) snow surfaces with one ± σ,and b the broadband albedos of the fresh (blue)and 0.8 0.8 0.8 aged (red) snow surfaces 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0 0 0 350 450 550 650 750 850 950 1050 S1 S2 S3 S4 S5 S6 Wavelength (nm) Site Code and dust in fresh and aged snow imply IPs including BC and Simulating the impacts of BC and dust on the snow albedo dust could be aggregated during the post-depositional process and darken the surface of the UR1. The process of a Bwhite^ glacier turning into Bgrey^ glacier is associated with the evolution of fresh snow to aged snow and the aggregations of the IPs including dust and BC. The online Surface reflectances and broadband albedos of fresh SNICAR model was developed by Flanner et al. (2007)and and aged snow and estimated forcing commonly used in simulating the impacts of LAIs on snow- and-ice albedos (Hadley and Kirchstetter 2012; McConnell The mean spectral surface reflectances of fresh and aged et al. 2007;Qu et al. 2014). Basically, the model utilizes a snow are presented in Fig. 5a. For the fresh snow, most two-stream radiative transfer method (Toon et al. 1989), assem- spectral reflectances in the wavelength range of 350– bles input parameters (e.g. radiation condition, surface spectral 1050 nm are higher than 0.8, with no significant differ- distribution, snow grain effective radius, black carbon and dust, ences from that measured for the newly fallen snow pack etc.) in an online platform (http://snow.engin.umich.edu/), and at Tibet (Ming et al. 2013a), while the reflectances of the can be easily operated. More details can be referred to from aged snow drop dramatically and vary around 0.4 at the Flanner et al. (2007). Snow ageing (snow density increases visible and infrared wavelengths. The mean broadband albedos of the fresh and aged snow are 0.85 and 0.43, respectively, showing large differences (Fig. 5b). Roughly, higher sites have larger albedos (Fig. 5b). For fresh snow, the mean broadband albedos show smaller variability (Fig. 5a). Downward shortwave radiation data recorded by the AWS at the terminal of the TUG1 (Fig. 1b)can be used to calculate the surface budget of solar radiation. For the enhanced directly reflecting and diffusing effect in a val- -2 427 W m ley glacier, true downward solar radiation may be even stronger. On 10th August, the downward solar radiation varied between a few watts per square metre early in the −2 morning and late in the night and nearly 1000 W m peakingatnoon(Fig. 6). In the surface of fresh snow, −2 the net flux of solar radiation was 64 W m ,taking −2 427 W m as the mean incoming radiation. However, −2 for aged snow, the net flux is as high as 243 W m . 0 8:00 10:00 12:00 14:00 16:00 18:00 20:00 The total forcing caused by the transformation from the 10 Aug, 2013 −2 fresh snow to the aged could be 180 W m ,presuming Fig. 6 The downward solar irradiance measured by the AWS, where the that the TUG1 on 10th would be evolved to the grey black dots are the half-hour measurements, the blue line is the running average, and the red dashed is the mean surface on 9th in a few days. Reflectance -2 Incoming shortwave irradiance recorded by AWS (W m ) Albedo Albedo 9556 Environ Sci Pollut Res (2016) 23:9549–9558 Table 2 The parameters used in the albedo simulation for fresh and aged snow and other designed scenarios at site 5 Snow types and scenarios Surface fresh Beneath aged Snow ageing Fresh Fresh Snow Snow Remark snow at S5 snow at S5* excluding BC snow + dust snow + BC ageing + dust ageing + BC and dust aggregation aggregation aggregation aggregation aggregation excluding snow excluding snow excluding BC excluding dust ageing and BC ageing and dust aggregation aggregation aggregation aggregation Solar zenith angle (°) 37 37 37 37 37 37 37 Snowpack depth (m) 0.1 1 1 0.1 0.1 1 1 −3 Snow density (kg m ) 274 458 458 274 274 458 458 Cloud amount 111 1111Clear-skyfor (10 = 100 %) modelling Snow grain radius (μm) 100 1500 1500 100 100 1500 1500 Albedo of underlying 0.62 0.2 0.2 0.62 0.62 0.2 0.2 ground (0.3–0.7 μm) Albedo of underlying 0.53 0.1 0.1 0.53 0.53 0.1 0.1 ground (0.7–5.0 μm) Sulfate-coated BC (ppb) 27 1738 27 27 1738 27 1738 Dust(ppm) 138813 88138813 Mean particle size (μm) 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 1.0–2.5 Mean sizes are 1.41 and 2.00 μmfor fresh and aged snow, respectively MAC scaling factor 11.3 11.3 11.3 11.3 11.3 11.3 11.3 Hydrophilic BC (experimental) Simulated albedo 0.782 0.325 0.580 0.752 0.667 0.511 0.316 Measured albedo 0.771 0.587 Albedo reduction 0.457 0.202 0.030 0.115 0.271 0.466 Attributable proportion 44 7 25 59 (%) Environ Sci Pollut Res (2016) 23:9549–9558 9557 and grain size grows) due to warming, and BC and dust aggre- For being lack of more comprehensive observation data, a gations were considered to be three main factors impacting sur- complete conclusion of the impacts of LAIs on the surface face albedo. Here, the model is applied to calculate the albedo of albedo of TUG1 glacier cannot be drawn here. the fresh snow, aged snow, and other three presumed surface conditions of the TUG1. We only made a case study specific for site S5, due to the incompleteness of the dataset obtained at other Conclusions sites needed for simulating the albedo reduction caused by LIAs. The snow-pack depth was set to be 1 m, according to an earlier Fresh and aged snow samples were collected on the east study (Xu et al. 2012). Other different parameters needed for the branch of the TUG1 on 10 August 2013 after a snowfall at fresh and aged snow were listed in Table 2. night. Measurements including snow densities and grain sizes Here are some descriptions how to choose the parameters and spectral reflectances were made in the transect route from to simulate the albedo of different snow using online SNICAR the terminal to the accumulation zone. High temperatures in model. Solar zenith angle was calculated according to the the summer probably enhanced the surface snow ageing and local sampling time and geographic locations. Snowpack melting. The snow density and grain size increased from 243 −3 depth was considered as 0.1 m for fresh snow and 1 m for to 458 kg m and from 290 to 2500 μm during the ageing aged snow. Snow densities were taken as measured. Clear sky process, along with the number and size of the IPs increase. and direct radiation were chosen for the very low cloud Concentrations of dust and BC in fresh snow are 16 ppm and amount (∼1). We consider aged snow and glacier ice are the 25 ppb, respectively. While in aged snow beneath the fresh, underlying grounds for fresh snow and aged snow. Thus, the their concentrations can be as high as 1507 ppm and underlying albedos of fresh and aged snow was set as 0.62 1738 ppb. The albedo discrepancy of fresh and aged snow (0.3–0.7 μm) and 0.53 (0.7–5.0 μm) as measured, and 0.2 can be as large as 0.40, indicating a consequent forcing of −2 (0.3–0.7 μm) and 0.1 (0.7–5.0 μm) by Zeng et al. (1984), 180 W m during the post-deposition process. At the accu- respectively. BC was thought to be sulfate-coated after long- mulative zone, snow ageing (44 %) is the most significant distance transport (Ming et al. 2009) and to be hydrophilic factor decreasing the albedo, BC (25 %) is the next, and then with the median mass absorption cross section (MAC) of dust (7 %). For the lack of dataset, the complete conclusion of 2 −1 11.3 m g (Flanner et al. 2007). Mean particle size was set impacting factors decreasing the surface albedo of TUG1 can- according to the measured mean size. not be drawn at present. Simulated albedo of the fresh snow at S5 was 0.77, close to the measured value (0.78). The model did not simulate the expected albedo of aged snow at S5. The simulated albedo Acknowledgments We would like to thank Chunhai Xu and Wuhua Chen for helping with the field work, and Yuman Zhu and Yun Yang for of the beneath aged snow was 0.33, remarkably lower than the helping analyse the samples. This work is supported by the Chinese measured (Table 2). The simulated albedo was close to that of Academy of Sciences (KJZD-EW-G03-03), Visiting Scholarship the aged snow only considering snow ageing, possibly indi- Program of the China Scholarship Council (2014), China Special Fund cating snow ageing due to warming was the predominant to for Meteorological Research in the Public Interest (GYHY201406016), and the Special Fund on Climate Change of China Meteorological reduce the snow albedo, concealing the impacts of other LAIs Administration (2013–2014). during the post-deposition processes. We presumed another two independent scenarios; only dust and only BC with mea- Open Access This article is distributed under the terms of the sured concentrations were applied to fresh snow, separately. In Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted the condition fresh snow only with dust aggregation was con- use, distribution, and reproduction in any medium, provided you give sidered, the albedo decreased from 0.78 to 0.75. If fresh snow appropriate credit to the original author(s) and the source, provide a link only with BC aggregation was considered, the albedo de- to the Creative Commons license, and indicate if changes were made. creased from 0.78 to 0.67. The effect of BC on albedo reduc- tion exceeded that of dust. However, the reality was the mea- sured albedo of aged snow is not the expected simulated val- References ue, but far higher than that. 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Published: Feb 3, 2016

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