Anshu Sharma, U.C. Kulshrestha This email address is being protected from spambots. You need JavaScript enabled to view it. School of Environmental Sciences, Jawaharlal Nehru University, New Delhi 110067, India
Received:
June 23, 2019
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Revised:
March 4, 2020
Accepted:
March 6, 2020
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||https://doi.org/10.4209/aaqr.2019.06.0279
Sharma, A. and Kulshrestha, U. (2020). Wet Deposition and Long-range Transport of Major Ions Related to Snow at Northwestern Himalayas (India). Aerosol Air Qual. Res. 20: 1249–1265. https://doi.org/10.4209/aaqr.2019.06.0279
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The present study was carried out to understand the snow chemistry with special emphasis on the estimation of wet deposition fluxes and transportation of ionic species to the Himalayan regions from December 2015 to March 2017. All the snow samples were collected from three different sites of two locations, Jammu & Kashmir and Himachal Pradesh. In Jammu and Kashmir we have selected two sites, (an urban area Leh and other one was semi-urban area Beerwah). In Himachal Pradesh, we selected a site at Nirmand village which was a rural area. At Leh and Nirmand village, samples were showing higher alkalinity than at Beerwah site. The pH values of snow at Leh and Nirmand were recorded above 5.6 except one sample of both the sites. However, at Beerwah site almost 60% of the samples were found acidic (below 5.6) in nature. All these three sites showed three different means of neutralization and pH control. The study revealed that the high pH value of snowfall at Leh site could be due to the presence very high value of Ca2+ whereas the moderate pH at Nirmand village may be due to moderate concentration of Ca2+ and high NH4+. In contrast at Beerwah site, low pH is probably due to very low concentrations of all the major cations. This study also suggested that non-sea salt sources contributed a significant fraction of SO42–, K+, Ca2+, and Mg2+. However, on average, a significant amount of HCO3– was measured at all the three sites, indicating a substantial role of crustal sources in the study sites. Results of this study showed that these ionic species are contributed by local as well as long-distance sources in the region. Backward airmass trajectory analysis revealed that the ionic species were contributed by the airmasses coming from North Atlantic Ocean, Africa, Europe, Middle East, and Mediterranean region to all these sites through long-range transport (LRT).HIGHLIGHTS
ABSTRACT
Keywords:
Snow; pH; Ionic chemistry; Wet deposition flux; Back trajectory analysis.
INTRODUCTION Increasing emissions of atmospheric aerosols significantly affect air quality (Allen et al., 2016). The IPCC (2014) report warns of severe consequences on global and regional atmospheric processes due to increasing aerosol particles. Deposition of anthropogenic constituents via wet and dry removal processes from the atmosphere has adverse impacts on terrestrial and aquatic ecosystems (Seinfeld and Pandis, 2006). Snowfall is considered as one of the most active wet removal processes for air pollutants at high altitude sites. It deposits significant amounts of bio geochemically important trace chemical species on various surfaces on Earth. Water-soluble ionic species present in the Himalayan snow is substantially affected by air pollutants from long-range transport of various anthropogenic sources (Kulshrestha and Kumar, 2014). Previous studies on snow chemistry reveals that the combustion of fossil fuel and biomass burning were dominantly responsible for air pollution (Zhang et al., 2013; Kumar et al., 2015, 2016). In general, snow composition shows spatial variation which largely depends upon the sources, characteristics of sampling site, elevation from the sea level, atmospheric conditions, sampling procedure and the transport of air pollutants, etc., (Marinoni et al., 2001). Airmass trajectories combined with snow chemistry data provide valuable information about the origin of air pollutants (Fleming et al., 2012; Kulshrestha and Kumar, 2014) and their impact on various ecosystems through deposition processes. Therefore, extensive study has been undertaken on snow composition in the western countries (Reynolds, 1983; Jenkins et al., 1987; Gunz and Hoffman, 1990; Marinoni et al., 2001; Toom-Sauntry and Barrie, 2002; Rohrbough et al., 2003; Walker et al., 2003; Niu et al., 2013; Xu et al., 2013; Zhang et al., 2013). The Himalayas are remotely located from industrialized urban centers; and they provide ideal locations not only to study the evolution of atmospheric constituents but also in monitoring the tropospheric chemistry (Cunningham and Zoller, 1981). The Himalayas are considered as the most sensitive ecosystem as far as the atmospheric deposition is concerned (Kuylenstierna et al., 2001; Zhang et al., 2012; Tiwari et al., 2012; Liu et al., 2013; Balestrini et al., 2014; Bisht et al., 2017). It is adversely affected by local and long-range transport of pollutants (Tiwari et al., 2012; Kulshrestha and Kumar, 2014; Roy et al., 2016; Bisht et al., 2017). Tourist activities, transportation, and other human activities are some of the local factors that significantly affect snow chemistry and adversely impact the aquatic and terrestrial ecosystems. In spite of its sensitivity, annual and seasonal depositions of various chemical species are poorly understood. There are very few studies reported on aerosols, rainwater and snow geochemistry in the Himalayan region (Ahmad and Hasnain et al., 2001; Gajananda et al., 2005; Tiwari et al., 2012; Kuniyal et al., 2013; Roy et al., 2016; Bisht et al., 2017). Similarly, in the western Himalayan region of India very few studies were done on fresh snowfall chemistry (Kapoor and Paul, 1980; Naik et al., 1995; Lone and Khan, 2007; Kulshrestha and Kumar, 2014; Kumar et al., 2015, 2016). Comparatively low concentration of air pollutants have been reported in the Himalayas on fresh snow chemistry (Marinoni et al., 2001; Shrestha et al., 2002; Kang et al., 2004; Lone and Khan, 2007; Huang et al., 2012; Kumar et al., 2015, 2016; Bisht et al., 2017). Thus, it represents the remotest part of India and could be considered as a reference for further studies. Hence, the main objective of this study was to investigate fresh snow chemistry in the Himalayas, ascertaining the local and long-range sources using NOAA HYSPLIT trajectories. The secondary objective was to investigate the marine and non-marine contributions in snow and discuss their environmental implications. Three sites from the Western part of the Himalayan region, which are having different land use land cover pattern (http://bhuvan.nrsc.gov.in) (Fig. 1), sources and population densities were selected for the study. Among which two sites were Leh and Beerwah located in the state of Jammu and Kashmir while the third one was Nirmand village in Himachal Pradesh, India. The location of all sites has been shown in Fig. 1. Jammu & Kashmir state is divided into three regions- Ladakh, the Jammu division and the Kashmir Valley division. Each site has been separately described in subsequent sections. Leh is one of the districts of the Ladakh division which represents India’s northern boundary adjacent with Pakistan and China, covers approximately 52.6% area of Jammu & Kashmir. The geographical coordinates of Leh are 34.15°N and 77.57°E and 2.3 km to 5 km above mean sea level (amsl). The Topography of Leh is quite uneven and covered mostly with mountains. Ladakh, Karakoram, and Zanskar are three parallel ranges of the Himalayas. Ladakh lies in the rain shadow region of the Himalayas. The artic type of climate prevails in the Ladakh region. Thus, Ladakh is considered as ‘cold desert’ which is located on the western end of the Himalayas with sparse vegetation. At Leh, the recorded minimum temperature in winters is –28°C whereas maximum temperature in summers is 35°C. Average annual rainfall in Leh is about 115 mm. The adverse climatic conditions and inaccessibility of the region are reflected in the limited population of around 150000 in Leh district. The Ladakh region is mainly comprised of Palaeozoic to Cretaceous sediments, meta-sediments, granitic intrusions and the Ladakh batholith. The latter is an intermediate rock which is located to the north of the Indus River (Dortch et al., 2008). Beerwah is a sub-district of Central Kashmir which is a part of the Budgam district of Jammu & Kashmir. The Beerwah lies between 74.59°E and 34.01°N at an elevation of 1.7 km amsl. Karewas, plateau-like terraces kind of agricultural landscape are predominantly present there. Agriculture is the main occupation of the people in this area. It is located about 30 km from Srinagar city in South-West direction. The main sources of pollution are automobiles and brick kilns, which are situated about 3–4 km from the main town. Panjal traps forming hilly and mountainous terrain of the district with hard formations of igneous and metamorphic rocks. The Karewa formation and alluvium of Quaternary and Tertiary age (Plio-Pleistocene) underlie the valley area and consists of alternate bands of sand, silt, gravel & clay, interspersed at two to three levels locally by glacial boulder beds. This formation of Plio-Pleistocene age lies dis-conformably over the older rocks ranging in age from Cambrian to Triassic. Kullu is a broad open valley which is sandwiched between the Lower Himalayan, Pir Panjal and Great Himalayan Ranges. Nirmand village (the study area) is located in Kullu district of Himachal Pradesh, India (31.43°N and 77.65°E). Nirmand village is situated on the border of Kullu and Shimla district, and is often called as Kashi of the Himalayas. It is situated nearly 87 km away in South from the Kullu District headquarters and about 150 km north from Shimla. Their climate is characterized by the cold and dry condition which over the year consists of three seasons. The summer season in Kullu which is from March to June has maximum temperature reaching 30°C during the day with nights retaining a bit of chill. Winters are characterized by snowfall and heavy frosts from December to January with the possibility of early snowfalls occurring in November also. The geological structure of this region is mainly formed by granites (unclassified) formations and it has Udalfs (20) type of soil cover which is high base status of humid regions. The region is without vegetation cover. Fresh snow samples were collected using the snow collector at three sites in Western Himalayan region of India: (1) Leh (the main city of Ladakh): represents urban site having lots of tourist activities (2) Beerwah: this is semi-urban site (3) Nirmand: this site in the Kullu valley represent rural site away from the urban site Shimla, considered as a green belt area due to less or no tourist activity. Total 40 snow samples were collected during the sampling period-13 from Leh, 11 from Beerwah and 16 from Nirmand. Sample collector (a plastic tray having ~30cm diameter) was placed about ~2 m above the ground level usually on rooftops or at elevated places. Samples were collected on an event by-event basis from December 2015 to January 2017. Sampling was done according to the methodology adopted by Kumar et al. (2015). The collector was thoroughly washed with Milli-Q and air dried before, and after each time the sample was collected. The collector was kept on the rooftop during the snowfall event and removed immediately after the collection. Fresh snowfall samples deposited on the collector was immediately transferred into pre-cleaned polypropylene bottles. Biological degradation of the samples was avoided by adding Thymol (< 5 mg) to each batch. Ambient conditions of the samples were preserved by storing them in a refrigerator. Samples were brought in the laboratory within 15 days from their collection and preserved for further analysis. Measurements of pH and EC of snow samples were done immediately so that the samples could be processed further for major cations and anions. Field blanks were also collected and analyzed using procedures similar to the snow sample. The major water-soluble ionic species such as cations (Na+, K+, NH4+, Ca2+, Mg2+) and anions (Cl–, F–, SO42–, NO3–, HCO3–) were quantitatively determined by Ion Chromatograph (Metrohm 883Basic IC Plus). Metrosep C4-100/4.0 column and an eluent of 1.7 mmol L–1 nitric acid and 0.7 mmol L–1 Dipicolinic acid at a flow rate of 0.9 without suppressor was used for determination of cations. While Metrosep A SUPP 4, 250/4.0 column and an eluent of 1.8 mmol L–1 Na2CO3 and 1.7 mmol L–1 NaHCO3 at a flow rate of 1.0 with Metrohm suppressor technique were used for determination of anions. HCO3– was determined by using 0.0025 NH2SO4. The details of the chemical analysis procedure are discussed elsewhere (Singh et al., 2014). Ion balance technique was used to check the quality of analytical data of water-soluble ionic species for all sites (WMO, 1994). The mean ionic ratio helps us to know the reliability of the analytical results. If all the major anions and cations are analyzed, the ratio is expected to the present study, the ratio was found to be 1.08 ± 0.16, 1.4 ± 0.13 and 1.04 ± 0.14 for Leh, Beerwah, and Nirmand, respectively. The higher significant correlation coefficients between ∑– and ∑+ were observed over all the sites. The ratio was found to be close to unity over Leh and Niramnd site suggesting the completeness and correctness of the analytical measurements. However, the ratio over Beerwah shows significant deviation from unity, suggesting the acidic nature of snow where acidic component is not completely neutralized by basic cation. Wet deposition flux (F) of all ionic species was calculated during the winter season of 2015–2017 by using the formula here: F = Deposition Flux in meq m–2 C = Average concentration of Ionic components in µeq L–1 V = Volume of snow (36.98 L for Beerwah and Nirmand site, and 16.86L for Leh), A = Area of the tray (314 cm2). We have used the following methodology to identify the source of contributed ionic species: Equivalent ratio and enrichment factor (EF) of measured ions viz. Cl–, SO42–, Mg2+, K+, Ca2+ were calculated in order to determine the marine and non-marine contributions in snow. Sodium was taken as the reference element in above calculations assuming all sodium coming from marine sources (Keene et al., 1986). The sea salt fraction (ssf) and non-sea salt fraction (nssf) were assessed by using the formula given below (Kumar et al., 2015). where [X] is the concentration of desired ionic species (µeq L–1). The EF > 1, suggested significant influences of other sources instead of marine sources. Norman et al. (2001) reported non- marine fraction by the entrainment of atmospheric particulate matters in precipitation occurring along the air mass trajectories. Non- marine sources can be categorized into two major categories i.e., crustal and anthropogenic sources. Out of these two, anthropogenic sources mostly enhance the acidity of precipitation while crustal sources decrease the acidity by buffering of the acidifying species (Rodhe et al., 2002; Kulshrestha, 2013). Due to opposite characteristics in controlling acidity of precipitation, it is essential to quantify separately the non-marine fraction into crustal associated fractions and anthropogenic fractions. We have termed crustal associated fractions which has fractions of acidic components (SO42–, NO3–) present as salt of calcium i.e., CaSO4 or Ca (NO3)2. We have followed the approach of Kulshrestha et al. (1997) and Jain et al. (2000) to calculate the contribution of crustal associated fraction and anthropogenic fraction of ionic species. For the calculation of the crustal associated fraction (CF) of major ionic components, nssCa2+ was considered as reference element in snowfall samples (Kulshrestha et al., 2003). The presence of crustal components in the form of nssCa2+ has been reported in precipitation globally (Rahn, 1976; Rodhe et al., 2002; Kulshrestha et al., 2003; Budhavant et al., 2014). Percent crustal fraction (CF) was calculated as follows here: y = nss concentration of ionic species (nssSO42–, nssCa2+, nssK+, nssMg2+, NO3–, NH4+ and F–) in µeq L–1; (y/nssCa2+) Soil is taken as standard ratio of local soils. Then, the percent Anthropogenic (Anthro) fractions of each component were calculated as follows Average contribution of different sources: The average contribution of different sources viz. marine, crustal and anthropogenic was calculated by the following formula: here ∑Xssf = Sum of concentration of all ssf values in each air mass cluster in µeq L–1. ∑XTotal = Sum of concentration of all components in each air mass cluster in µeq L–1. here ∑XCF = Sum of concentration of all Crustal Fraction values in each air mass cluster in µeq L–1. Three-days back trajectory analysis was also performed (Figs. 6(a)–6(c)) for the confirmation of the possible sources of pollutants over the Himalayan region. Backward airmass trajectories for 72 h of 2000 m above ground level were calculated using the geographic information system (GIS) based software, TrajStat for all snowfall samples (Wang et al., 2009). Kaya and Tuncel (1997) reported that the acidification potential of wet precipitation is mainly determined by the presence of HNO3, H2SO4, and organic acids, whereas alkaline (basic) substances such as NH3, MgCO3 and CaCO3 are primarily responsible for their neutralization. Hence, the relative abundance of these acidic and alkaline species greatly determines the pH of precipitation. Cations such as (Ca2+, Mg2+, and NH4+) react with acids (H2SO4 and HNO3) to form NO3– and SO42– salts in the atmosphere. The neutralization factor of these species were calculated by the following formula where [Xi] = The concentration of desired ionic species i.e., nss Ca2+, nss Mg2+ and NH4+ in µeq L L–1. The pH of snow samples at Leh site ranged from 7.02 to 8.11 with an average of 7.48 ± 0.38, at Nirmand site varies from 5.30 to 7.09 with an average 6.39 ± 0.48 (Fig. 2), a similar range of pH at Mukteshwar site, Nainital and Kullu, in the north western Himalayan region have been reported by Tiwari et al. (2012), Kumar et al. (2015) and Bisht et al. (2017), respectively. As alkaline precipitation is considered to be a typical feature of the Indian region, the snow samples were observed with > 5.6 pH due to its enrichment of suspended atmospheric dust with calcium carbonates (Kulshrestha et al., 2003). Influence of natural dust particles in the rainwater chemistry has been reported over India (Delhi) by Kulshrestha et al. (1996, 2003); Jain et al. (2000). The pH of precipitation is usually measured at 5.6 in a clean atmosphere owing to the equilibration with atmospheric CO2 (Charlson and Rodhe, 1982). The enrichment of natural particles with carbonate and bicarbonates of calcium that eventually neutralize the resulting acidity. At Beerwah site, the pH was found to be slightly acidic and vary from 5.18 to 6.47 with the mean 5.77 ± 0.37. Kumar et al. (2016) have also reported an almost similar range of pH at Gulmarg site. Of this, about 45% of total snow samples were found to be acidic (below 5.6) at this site. Many co-workers have been also found the similar range of pH in precipitation at different sites of Himalayan region (Valsecchi et al., 1999; Liu et al., 2013; Kulshrestha and Kumar, 2014; Roy et al., 2016). The average concentration of ionic species at three sites (Leh, Beerwah, and Nirmand) over Western Himalayan regions of India along with the minimum and maximum concentrations in snow collected during the winter season of 2015–2016 and 2016–2017 is presented in Table 1. The pH and conductivity of snow samples have also been shown in Table 1. At Leh site the mean concentration (µeq L–1) of cations in snow samples were found in the following order Ca2+ > Mg2+ > NH4+ > Na+ > K+ whereas the abundance of anions were as follow HCO3– > Cl– > SO42– > NO3– > F-. At Beerwah site the mean concentration (µeq L–1) of cations were found in the following order Ca2+ > NH4+ > Mg2+ > Na+ > K+ whereas the anions were found as follow HCO3– > Cl– > SO42– > NO3– > F–. At Nirmand site the mean concentration of were like NH4+ > Ca2+ > Na+ > K+ > Mg2+ for cations and HCO3– > Cl– > SO42– > NO3– > F– for the anions. Their percentage contribution in the snow samples has been calculated and depicted in Fig. 3 for all the sites. At the Leh and Beerwah site, the Ca2+ ions were the most dominant whereas at Nirmand site it was much lower. At Leh site, the average concentration of Ca2+ accounts for approximately 18% of all ions and 42% among all cations, whereas at Beerwah site it accounts approximately 12% of all ions and 33% among all cations. It was observed that the average concentration of Ca2+ at Beerwah site was lower than Gulmarg (Kumar et al., 2016) (Fig. 4). The highest concentration of Ca2+ in precipitation mainly contributed by local and transported dust (Satyanarayana et al., 2010; Budhavan et al., 2011; Balestrini et al., 2014; Bisht et al., 2017; Khan et al., 2018), from the suspended soil (Rahn et al., 1976; Kulshrestha and Kumar et al., 2014) and from vehicular emission, cement factory etc. (Sanusi et al., 1996). In the present study, we observed high concentration of both Ca2+ and HCO3– at Leh and Beerwah site. It was mainly due to the influence of natural dust particles enriched with carbonate and bicarbonates of calcium (Kulshrestha et al., 1996; Cong et al., 2007; Li et al., 2007). Similar results were also reported in various studies in the Himalayan region (Huang et al., 2012; Zhang et al., 2012; Balestrini et al., 2014; Kumar et al., 2015). After Ca2+ and Mg2+, NH4+ ion has been the most abundant at Leh and Beerwah site, whereas at Nirmand site the average concentration of NH4+ was highest among all the cations (Fig. 4). A high concentration of NH4+ amongst major cations at Nirmand site suggested a significant influence of anthropogenic sources such as livestock, agricultural activities, human and animal excreta, (Galloway, 1995; Singh and Kulshrestha, 2012; Khan et al., 2018). Khan et al. (2018) suggested the nearby vegetation and agriculture farming may contribute to the raised concentration of biogenic NH4+. Other sources such as increased tourist activities could also be considered as a significant source for NH4+ in this region nowadays. Among all the anions, HCO3– and Cl– was highest at all three sites. Similar results were observed at high altitude Himalayan stations (Kumar et al., 2015; Roy et al., 2016; Bisth et al., 2017). We have found the average SO42– concentration was higher than the NO3– concentration at all the three sites (Fig. 4). Similar results were reported by (Zhang et al., 2012; Tiwari et al., 2012; Liu et al., 2013; Balestrini et al., 2014; Roy et al., 2016; Bisht et al., 2017) over Himalayan region. The high concentration of SO42– could be attributed to the anthropogenic sources which emit SO2. Since industrial activities were found to be lacking at all these sites, the maximum contribution to SO42– from the LRT and trans-boundary transport of other regions as well as the local influence of diesel driven vehicular emissions cannot be ruled out. NO3– concentrations were very low at all the three sites. In snow samples, high concentrations of NO3– could be attributed to their primary emissions as NOx from the increased vehicular activities that are eventually transformed to water-soluble NO3– species in the atmosphere (Finlayson-Pitts and Pitts, 1986). Other than vehicular emissions, biomass burning by locals to produce heat during winters could be another regional factor (Singh et al., 2014). Apart from regional emissions, long-range transport of NOx/NO3– by various air masses approaching the sampling sites could be attributed to a high concentration of NO3–. At all the three sites concentration of carbonate was found to be very high in snow samples due to the contribution of soil dust comprising high fractions of CaCO3, MgCO3, and MgSO4. Table 2 represents the average wet deposition fluxes for all the samples collected during the winter and spring seasons. From the table, it is very clear that the average wet deposition fluxes at Leh was in the order like- HCO3–> Ca2+ > Mg2+ > NH4+ > Na+ = Cl– > SO42– > K+ > NO3– > F– and at Beerwah followed the order- HCO3– > Ca2+ > NH4+ > Mg2+ > Cl– > Na+ > K+ > SO42– > NO3– >F– while at Nirmand site it is like HCO3– > NH4+ > Cl– > Ca2+ > Na+ > K+ > S O42– > Mg2+ > F– > NO3–. At Leh and Beerwah, the highest value of wet deposition fluxes was recorded for HCO3– and Ca2+ which may be due to crustal influence (Jain et al., 2000; Kulshrestha et al., 2003). Whereas at Nirmand site maximum wet deposition fluxes were recorded for HCO3– and for NH4+ suggested anthropogenic activity in this region. Elevated deposition fluxes for Na+ and Cl– might be due to marine aerosols deposited at all sites. Acidic species like SO42– and NO3– are lesser in comparison to Ca2+ suggesting alkaline nature of precipitation, which is very common in the Indian region. For assessing the role of source categories and their percentage contribution, the results were further evaluated with marine and non-marine fractions. Non marine fractions were estimated for their crustal and anthropogenic fractions using the approach reported by Kulshrestha et al. (1997). The sea salt fraction(ssf) and non-sea salt fractions (nssf) of viz. Cl–, SO42–, K+, Mg2+, and Ca2+ were calculated and presented in Table 3. At Leh and Beerwah sites, the ratios of SO42–, K+, Ca2+, Mg2+ were found to be higher than that of seawater. Similar results were also found by Kumar and co-workers (2015) at Mukhteshwar site of Kullu Distrct. However, at Nirmand site, the ratios of Cl–, SO42–, K+, and Ca2+ were found to be more than that of seawater, which indicates that crustal (soil dust) and anthropogenic influence of these ions are in the snow over the western Himalayas in India. At all the sites, the results showed that Cl–/Na+ ratio was very close to seawater ratios representing its major contribution from marine sources. In Indian region, higher ratios of SO42–/Na+, K+/Na+, and Ca2+/Na+ in precipitation have been reported at various sites (Kulshrestha et al., 2003; Safai et al., 2004; Tiwari et al., 2007; Bisht et al., 2015). Ali et al. (2004) revealed that the compounds containing Ca2+, Mg2+, and K+ are incorporated into the atmosphere by the erosion of soil in the form of their carbonate salts. The nssf of SO42–, K+, Mg2+, and Ca2+ confirms the dominance of crustal and anthropogenic sources of Ca2+, K+, Mg2+, and SO42–. The similar results have also been reported by various studies on the snow chemistry (Keene et al., 1986; Naik et al., 1995; Zhu et al., 2012; Niu et al., 2013; Kumar et al., 2015). Table 4 shows the percent contribution of crustal fractions (CF) and anthropogenic fractions (Anthro) of each ionic species of snowfall species. As shown in Table 4, all the three sites have maximum Ca2+ contribution, which is associated with the crustal fraction. A similar result was found at a different site of the Himalayan region by Kumar et al. (2015, 2016). Some researchers have suggested that nssCa2+ in snow samples is due to transported dust at Himalaya and Tibetan Plateau (Mayewski et al., 1983; Kumar et al., 2015, 2016). The percent contribution of NO3– and NH4+ were found to be higher in anthropogenic in comparison to crustal fraction. At all the three sites, very high fraction of anthropogenic NO3– was observed. Previous studies also reported NO3– is mostly of anthropogenic in nature (Das et al., 2005; Singh et al., 2007; Budhavant et al., 2009; Tiwari et al., 2012; Bisht et al., 2015; Roy et al., 2016; Bisht et al., 2017). In global precipitation, NO3– has also been reported in airmass trajectories due to long-range transport (Avila and Alacron, 1999; Satyanarayana et al., 2010). The nssSO42–, at Beerwah and Leh site showed the higher percentage contribution of Anthropogenic SO42. This might be due to fossil fuel combustion at the origin of airmasses as well as during the transport of airmasses before reaching the site. Apart from LTR, the contribution from local sources such as the use of generators which are mostly operated on diesel cannot be ruled out. The presence of anthropogenic SO42– in the form of (NH4)2SO4 and NH4HSO4 has been reported in precipitation worldwide (Finlayson-Pitts and Pitts, 1986; Kulshrestha et al., 2003). At Leh and Nirmand site the crustal fraction of SO42– was very high than that of anthropogenic form. This high crustal SO42– at both the sites may be due to SO2 adsorption onto Ca2+ rich dust particles as it scavenges acidic precursor (Kulshrestha et al., 2003b; Kulshrestha, 2013), which is very common in India. The maximum percentage fraction of nssK+ is contributed by crustal sources at Leh and Beerwah sites. Sometimes local soils contain a very high level of potassium (Jain et al., 2000). But at Nirmand site nssK+ mainly contributed by anthropogenic sources. At this rural site biomass burning is the main reason for high nssK+ by anthropogenic sources. Apart from biomass burning, nssK+ due to crustal sources have been reported in precipitation (Zhang et al., 2007). Besides marine origin, Mg2+ is also contributed by crustal sources at all three sites. Mg2+ has been reported in snow samples due to a significant contribution from crustal sources (Kang et al., 2004). The average percent contribution of marine, crustal, and anthropogenic sources was calculated and showed in Fig. 5. The order of dominance followed the sequence- at Leh: Crustal (56%) > Marine (24%) > Anthropogenic (20%), at Beerwah: Crustal (46%) >Marine (27%) = Anthropogenic (27%). The dominant contribution of crustal fraction in snow samples due to local as well as long range transport has been suggested by Shrestha et al. (2002) and Zhang et al. (2013). After crustal, the contribution of the marine fraction is dominated over anthropogenic. A similar result was observed by Kumar and co-workers in snow at different sites of Himalayas (Kumar et al., 2015, 2016). The pH of snow samples at both sites also suggested a significant contribution of crustal components, i.e., alkaline species over anthropogenic components, i.e., acidic species whereas seasalt fraction does not play an important role in controlling the pH of precipitation samples. At the Nirmand site the contribution from sources followed the sequence- Anthropogenic (40%) > Crustal (33%) > Marine (27%). At this mainly activities are biomass burning, agriculture, suggested pollution coming from this contribute to anthropogenic sources. The pH of this site and the results of ions suggested complete neutralization of (SO42–) by NH4+ to form (NH4)2SO4 & NH4HSO4 and CaCO3 rich dust particles forming calcium sulphate. Three-days back trajectory analysis was also performed (Figs. 6(a)–6(c)) for the confirmation of the possible sources of pollutants over the Himalayan region. Backward airmass trajectories for 72 h of 2000 m above ground level were calculated using the geographic information system (GIS) based software, TrajStatfor all snowfall samples (Wang et al., 2009). Mostly westerly air masses prevailed during the study. The air mass trajectories at Leh site show that the North Atlantic Ocean, Africa, Europe, Middle East, China, and Mediterranean region are the sources which contribute through the long-range transport of pollutants (Fig. 6(a)). At Beerwah site, the airmasses arrived from Africa, Europe, Pakistan, Kazakhstan, Afganistan and Middle-East along with Punjab, Haryana, Delhi, Uttar Pradesh (Fig. 6(b)). Both the LRT and the local sources are responsible for deposition of pollutants in snow at this site. At the Nirmand site, the airmasses mainly approached from Africa, China, Pakistan, Uzbekistan, Tazakistan along with Punjab, Haryana, Delhi, Uttar Pradesh, Madhya- Pradesh, Maharastra (Fig. 6(c)). Statistical analysis is also used to identify the relationship between major ions in snow samples and their possible sources. For, the estimates of correlation coefficients, the graph were plotted between the water-soluble ions in snow samples in Figs. 7(a)–7(c) for the respective sites. A good correlation between SO42– and NO3– in snow samples at all the site suggesting the origin of these ions from the similar sources such as combustion of fossil fuel in which SO2 and NOx are emitted that eventually get oxidised into SO42– and NO3– (Kulshrestha et al., 2005; Kumar et al., 2016). A strong correlation between major sea salt components such as Na+ and Cl– at all the sites indicative of their origin from marine source. Similarly, a good correlation is observed between ions such as Ca2+ and SO42– at all sites, Ca2+ and Mg2+ at Beerwah and Nirmand site, Mg2+ and SO42– at Beerwah site. It might be due to the chemical interactions between crustal components rich in Ca2+ and Mg2+ with the acids such as H2SO4 and HNO3 in precipitation. These reactions enhance the alkalinity of precipitation and decrease the acidity of snow samples interestingly SO42– and NO3– showed good correlation with NH4+ derived from anthropogenic activities as well as with crustal components such as Ca2+ and Mg2+. The strong correlation suggested the chemical reaction between these ion said in the stoichiometric neutralization of the acidic moieties present in the snow melt. The formation of NH4, SO4, (NH4)2SO4 and NH4NO3 in precipitation samples have been reported due to reaction of ammonia in the atmosphere with H2SO4 and HNO3 (Kulshrestha et al., 2005; Seinfield and Pandis, 2006). The principal component analysis (PCA) was attempted using snow chemistry data to identify the processes and emission sources of water-soluble ions in snow. Table 5 presents PCA results with varimax rotation. At Leh site, PC the total variance and showed high loading for F–, Na+, Ca2+ and Mg2+ clearly reflecting their origin from crustal sources. PC2 explains 22.38% of variance had a high loading of Na+ and NH4+. Na+ mainly comes from sea salt and also derived from soil, whereas NH4+, indicating its unique anthropogenic source from volatilization of animal manure, human excreta and agricultural activities. The PC3 contained K+ with 15.32% of the total variance, may be linked with biomass burning. PC4 explains11.76% of the total variance and due to high loading of NO3–, could be vehicular emissions. At Beerwah site, three components that were extracted may be attributed to three different sources. PC1 explained the 40.33% of the total variance and was found to be loaded with NH4+, Na+, K+, Cl–, NO3– and SO42– indicating the influence of secondary inorganic aerosol from the anthropogenic sources. This factor can be attributed to regional pollution arising from coal-burning activities (Na+, K+, Cl–, SO42–) and agricultural practices (NH4+). PC2 was loaded with Ca2+ and Mg2+ and explained the 18.38% of the total variance. Loading of these variables in second factor suggests the influence of crustal and windblown soil dust. PC3 explained 14.02% of the variance and found to be loaded with K+ and F–. Presence of K+, and F– variables indicate the influence of biomass burning sources over the studied area. At Nirmand site, PC 1 showed high loading of NH4+, K+, Na+ and Cl– with total variance of 34.91%. Na+ and Cl– suggested the contribution from salty soil profile in the region and longrange transport of sea winds. K+ and NH4+ are tracer of biomass burning which includes domestic burning of firewood and agricultural residues. This PC represents a combination of coal and biomass burning. PC2 showed high loading of NH4+, NO3–, and SO42– with a total variance of 26.14%. These ions are secondary in origin and formed by chemical reactions in the atmosphere of ammonium sulfate and ammonium nitrate. PC3 showed high loading of Mg2+ and Ca2+ with a total variance of 17.48%. Theses ions are typically associated with crustal materials in windblown dust, resuspended dust, and dust from paved and unpaved roads. Therefore, the overall conclusion could be inferred from both the statistical approach viz. correlation matrix and PCA that at Leh site Ca2+ and Mg2+ have strong correlation and PCA suggested they have common sources mainly coming from crustal sources. At Beerwah Na+, K+, Cl–, SO42– and NH4+ are major source of pollution suggested local burning, agriculture activities are dominant in this region. At Nirmad site correlation table shows NH4+, K+, NO3–, SO42– have good correlation and PCA suggested they all are coming from anthropogenic sources. At Leh, the neutralization factor (NF) values of Ca2+, NH4+, and Mg2+ were estimated and found to be 2.34, 0.92, and 0.90, respectively (Fig. 8). Beerwah site also showed a pattern of NF where the NF value of Ca2+, NH4+, and Mg2+ was estimated and found to be 1.62, 1.07, and 0.70, respectively. These results suggested that at both sites, maximum neutralization occurred by Ca2+ and NH4+ in snow. Similar results were also observed by Kumar and co-workers in the snow at other sites of India, showing maximum neutralizing capacity for Ca2+ is about 1.65 at Mukhteshwar (Kumar et al., 2015) and 1.17 at Gulmarg (Kumar et al., 2016). The maximum neutralization by Ca2+ and NH4+ in precipitation has been reported by other workers worldwide (Kulshrestha et al., 2003; Zhang et al., 2007; Satyanarayana et al., 2010; Roy et al., 2017). Kulshrestha et al. (1995) have suggested that neutralization by Ca2+ and Mg2+ done through a below-cloud process, whereas by NH4+ done via an in-cloud process. Further, coarse mode aerosols predominantly contain Ca2+ and Mg2+ ions, and fine mode aerosols contain NH4+ ion. Jain et al. (2000) suggested in, calcite-rich suspended dust neutralizes acidic component present in precipitation in India. At Nirmand site the NF values of NH4+, Ca2+, and Mg2+ were estimated and found to be 5.15, 2.35 and 0.22 respectively, showing that NH4+ neutralization dominant over Ca2+ at this site. The high concentration of NH4+ was consistent with more NH3 sources found at this site, mainly emitted from biomass burning, fertilizer, and animal breeding (Bouwman et al., 1997). The higher NF of NH4+ than Ca2+ was also observed over a rural station near Bhubaneswar on the east coast of Bay of Bengal (Das et al., 2005; Das et al., 2010). Roy et al. (2017) also reported the same results at high altitude Himalayan stations in eastern India. The mean pH of snow at Leh, Beerwah and Nirmand was 74 ± 0.38, 5.77 ± 0.35 and 6.46 ± 0.39 respectively well above 5.60, which is the reference pH of snow and ranged between 5.18 and 8.11. During the study period, almost 60% of snow-water samples were found to be acidic in nature at Beerwah. Maximum pH was observed at Leh site, and the minimum was observed at Beerwah site. The average pH was higher at Leh (urban) and Nirmand (rural) then at Beerwah (semi-urban) due to the dominance of soil-derived particles. Overall the study revealed that basic ions largely control pH and acidity of snow water over the Himalayan region. The acidity in the snow is largely neutralized by Ca2+ at Leh and Beerwah site, whereas at Nirmand site it was neutralized by NH4+. The order of measured major cations Ca2+ > Mg2+ > NH4+ at Leh and Beerwah, but at Nirmand NH4+ > Ca2+ > Na+. The dominant anion was HCO3– at all the sites. The major acidifying ion in snow was sulfate (SO42–), which was influenced by the long-range transport from the North Atlantic Ocean, Africa, Europe, the Middle East, and Mediterranean region. The high concentrations of cations were associated with depressions rich in calcite. Among the cations, Ca2+ makes the highest contribution at Leh and Beerwah sites, indicating the incorporation of soil dust into the snow samples, which reflects a major crustal influence, whereas at Nirmand site NH4+ contribution was highest, due to more agricultural or anthropogenic activity in this region. As the results suggested high concentrations of ions at the Leh site than Beerwah and Nirmand site, their limited deposition pathways at Leh reflected signatures of climate change over the upper Himalayan ranges and lesser transboundary sources during the advections from the west. This study also reveals the LTR of air pollutants being transported more to the lower regions than the upper region. The neutralizing factor analysis highlighting the influence of anthropogenic as well as crustal sources. The results of this study have indicated that soil dust, sea salts, burning of biomass and coal are the major contributor of atmospheric deposition. We sincerely thank the financial support received from DST-PURSE, UGC-UPE and CSIR- UGC to carry out this research work. The present work has been part of DRSNet network of Professor UC Kulshrestha’s group.
METHODOLOGY
Sampling SitesFig. 1. Map showings the sampling sites.
Leh
Beerwah
Nirmand
Chemical Analysis and Quality Control
The Data Quality Control
Wet Deposition fluxes through Snowfall Deposition
The Contribution of Ionic Species Through Different Sources
Marine Contribution
Non-marine Contribution
Back Trajectory Analysis
The Neutralization Factor of the Ionic Species
RESULTS AND DISCUSSION
pH of SnowFig. 2. Monthly average pH variation of snow at different sites of Himalayas. Note Red line indicates the neutral cloud water pH.
Deposition of Major Ions in Snow
Fig. 3. The percentage contribution of individual cations and anions in snow samples at all sites.Fig. 4. Distributions of analyzed water-soluble ionic species at the three sampling sites in Himalayan region. The box plots along with box normal distribution indicate the mean (solid rectangular box within box) and median (solid line within box) distributions and the 90th, 75th, 25th, and 10th percentiles.
Wet Deposition Fluxes Through Snow Fall Deposition
Source Apportionment
Marine Contribution
Non-marine ContributionFig. 5. Marine, crustal and anthropogenic fraction at all sites.
Fig. 6. Airmass back trajectory at Leh, Beerwah and Nirmand respectively.
Statistical Approach for Source IdentificationFig. 7(a). Correlation matrix and frequency distribution graphs of water soluble ions in snowmelt at Leh site.
Fig. 7(b). Correlation matrix and frequency distribution graphs of soluble ions in snow at Beerwah site.
Fig. 7(c). Correlation matrix and frequency distribution graphs of soluble ions in snow at Nirmand site.
Source Identification of Ions Using Principal Component Analysis
Acidification and Neutralization PotentialsFig. 8. Neutralization factor of nssCa2+, nssMg2+, NH4 + at (a) Leh, (b) Beerwah and (c) Nirmand sites (the axis break on Y-axis has given from 0.3 to 1.8).
CONCLUSION
ACKNOWLEDGEMENT
REFERENCES
Aerosol Air Qual. Res. 20 :1249 -1265 . https://doi.org/10.4209/aaqr.2019.06.0279