An Analysis of Elemental and PAH Concentrations in Soils Due to Vehicular Traffic Along the Manali-Leh Highway, Northwestern

An analysis of elemental and PAH concentrations in soils due to vehicular traffic along the Manali-Leh Highway, northwestern

Himalaya, India

A thesis submitted to the Graduate School

The University of Cincinnati

in partial fulfilment of the requirements of the degree of

Master of Science

Department of Geology

McMicken College of Arts and Sciences

Rajarshi Dasgupta

B.Sc. Honours (Geography), University of Calcutta, Kolkata, India, 2005

M.A. (Geography), Jawaharlal Nehru University, New Delhi, India, 2008

March 2014

Advisory Committee:

Dr. Brooke E. Crowley (Chair)

Dr. J. Barry Maynard (Member)

Dr. Aaron F. Diefendorf (Member)

Dr. Lewis A. Owen (Member) ABSTRACT

Vehicles constitute one of the most important sources of environmental pollution. Most studies on roadside soil pollution have been carried out in urban areas, where the main fuel used is petrol. These studies indicate that the concentrations of heavy metals associated with vehicular movement decrease with increasing distance from the highway and with depth in the soil profile. In contrast, most of the vehicles that travel

along the Manali-Leh Highway in northwestern Himalaya, India are fueled by diesel. The present study

assessed the concentrations of the heavy metals (Al, Fe, Cr, Cu, Pb, Ni, Co, Zn, V and Ba), total organic

carbon (TOC), total sulphur and polycyclic aromatic hydrocarbons (PAHs) concentrations along this

highway. Soil samples were collected from four sites at incremental distances from the highway (0m, 2m,

5m, 10m, 20m and 150m) and from three depths in the soil profile (3cm, 9cm and 15cm). The concentrations

of the various elements were measured using X-ray Fluorescence Spectrometry and an Elemental Analyzer,

while those of the PAHs using Gas Chromatography-Mass Spectrometry. Results suggest that heavy metal

concentrations are generally very low compared to those in other published studies. There is no clear

relationship between concentrations of heavy metals and either distance from the highway or depth within

the soil profile. However, elevated concentrations of sulphur are found in the soils. Cluster analysis was

applied to determine the association of various elements in the soil. There are six main clusters, which are

interpreted to be the organic, clay, carbonate, iron oxides, sand and silt and windblown deposited fractions

of the soil. This indicates that most of the metals are associated with the natural fractions of the soils.

Sulphur is found to be clustered with the organic fraction of the soils. PAHs are also found, albeit in very

low concentrations compared to other published studies on highways. The main conclusion of this study is

that at present, the amount of heavy metals in the soils along the Manali-Leh Highway is very low, but there

are elevated sulphur concentrations. High sulphur concentrations can increase soil acidity, which can have

important edaphic implications. The strong association of sulphur with TOC, Pb and Zn, as well as a strong

correlation between sulphur and PAHs suggests that the regular use of the road by an increasing number of

vehicles can contaminate the soil further with metals and PAHs, which may then move up the food chain

i and directly affect human health. The results of this study imply that monitoring of heavy metals alone suggests that there is no contamination of the soils, but by measuring sulphur, it has been shown that that there is, in fact, considerable human impacts along the highway. Therefore, both inorganic and organic pollutants should be regularly monitored in the soils along this highway.

iii

ACKNOWLEDGEMENTS

I would like to mention about a few individuals without whose continuous and endearing support, this thesis would not have seen the light of the day. First and foremost is my advisor, Dr. Brooke Crowley, who decided to take me under her tutelage, and supervised a thesis on a topic that was totally new to me. She has spent countless hours discussing my (often crazy!) research ideas, refining funding applications and reading many drafts of the thesis. Thank you very much Dr. Crowley. It was a pleasure to work with and learn from you. I particularly enjoyed learning the nuances of doing and communicating science. In the same vein, I wish to extend my sincere appreciation to the other members of my advisory committee, namely Dr. Barry Maynard, Dr. Aaron Diefendorf and Dr. Lewis Owen. In particular, Dr. Maynard was like a second advisor to me and provided many crucial inputs and suggestions at various stages of this project; Dr. Diefendorf taught organic and isotopic geochemistry to a complete newbie in the field, while

Dr. Owen chipped in with his expertise on the physical environment of the study area. Thank you gentlemen- I gratefully acknowledge your support.

Thanks are also due to the other faculty and staff members of the Department of Geology, University of

Cincinnati (UC), especially to Dr. Tom Algeo for allowing me to work in the Fisk Laboratory, Drs. Warren

Huff and Yurena Yanes for always maintaining an interest in my research, Drs. Aaron Diefendorf and Andy

Czaja for organizing the weekly colloquiums on Fridays, which helped me (and I am sure, all of us) to unwind a bit at the end of the week, and Mrs. Krista Smilek for taking care of the administrative nitty-gritty of pursuing graduate studies at UC.

I was fortunate to be part of a very vibrant and extremely diverse research group, and my lab mates were a source of joy and support. So thumbs up to you Jani Sparks, Stella Mosher, Eric Baumann, Matt Vrazo and

Bevin Kenney. I acknowledge also the camaraderie of other graduate students in the department, especially

Gary Motz, Julia Wise, Kelsey Feser and Chris Aucoin. Gary and Jules, I can never forget or thank you both enough for all that you have done for me ever since I arrived in Cincinnati; Kels, I really appreciate your general support and especially your words of wisdom on all things statistical when I was stuck and

iv did not know what to do; Chris, I know I spent very little time as your ‘office’ mate, but I really enjoyed our conversations whenever I was in the office and will miss them.

The University of Cincinnati provided me with not only the resources to carry out my research, but also financial support to sustain myself, in terms of a graduate assistantship. Funding for this project was obtained through a UC Research Council faculty research grant to my advisor and a Sigma Xi grant-in-aid of research (No. G20131015322038) to myself.

No words are ever enough to thank my parents for being the biggest source of inspiration and support in my life. I know it would sound cliché, but Mum and Bapi, believe me- you two are THE BEST!! I also want to thank my best friends, Sumanta Chakraborti and Dipanjan Mukherjee, for showing me the signs of positivity even when things were a bit down.

Finally to the Almighty for keeping me in good health and providing me with this opportunity to study in the United States.

CONTENTS

ABSTRACT ...... i

ACKNOWLEDGEMENTS ...... iv

LIST OF FIGURES ...... viii

LIST OF TABLES ...... x

1. INTRODUCTION: ...... 1

1.1. Heavy metals in roadside soils: ...... 1

1.2. Elemental characteristics of petrol (gasoline) and diesel exhaust: ...... 3

1.3. Sulphur in roadside soils: ...... 4

1.4. Polycyclic aromatic hydrocarbons in roadside soils: ...... 6

1.5. Study aim and objectives: ...... 7

2. MATERIALS & METHODS: ...... 8

2.1. Study area: ...... 8

2.2. Sample collection and preparation: ...... 9

2.3. Analytical methods: ...... 10

2.3.1. X-Ray Fluorescence: ...... 10

2.3.2. Carbon-Sulphur Analysis: ...... 10

2.3.3. PAH Analysis: ...... 11

2.4. Data processing and analyses: ...... 11

3. RESULTS AND DISCUSSION: ...... 14

3.1. Concentrations of heavy metals: ...... 14

3.2. Relationship between heavy metals and TOC: ...... 16

3.3. Concentration of total sulphur: ...... 17

3.4. Relationship between TOC and TS: ...... 18

3.5. Association of various elements: ...... 19

3.6. PAH concentrations: ...... 20

3.7. Significance of the study: ...... 22

4. CONCLUSIONS: ...... 24

REFERENCES: ...... 25

vii

LIST OF FIGURES

Fig. 1 Map showing (A) location of the study area within India, and (B) the Manali-Leh Highway. The sampling sites, towns on either end of the highway, mountain passes and major mountain ranges are labeled.

...... 39

Fig. 2 Photographs of the study sites: Kothi, Jispa, Killingsarai and Rumtse. All photographs except the one

at Jispa taken standing on the Manali-Leh Highway. The photograph at Jispa was taken from the agricultural

field across which the transect lay...... 40

Fig. 3 A schematic diagram of sampling protocol for each transect along the Manali-Leh Highway.

Distances and depths are not to scale...... 41

Fig. 4 Bivariate scatter plots of heavy metal concentrations at varying distances from the highway. Only

metals that have a significant relationship with distance are plotted. The error bars represent ± 1 standard

deviation...... 42

Fig. 5 Bivariate scatterplots and power regressions for total sulphur concentrations at varying distances

from the highway for each site. The points represent mean values of each distance and the error bars

represent ± 1 standard deviation. The roadside sample at Rumtse (0m) was excluded from regression

analysis...... 43

Fig. 6 Dendrogram showing cluster analysis of 10 heavy metals, total organic carbon (TOC) and total

sulphur (TS) in soils along the Manali-Leh Highway. The text on the left mentions the most likely soil

fraction with which the various clusters are associated...... 44

viii

Fig. 7 Percentage composition of different ringed PAHs at each site...... 45

LIST OF TABLES

Table 1 Description of the sampling sites...... 46

Table 2 Descriptive statistics of heavy metal concentrations (n=15 samples from 0, 2, 5, 10, and 20 m at each site). The local baseline values were calculated using samples collected at 150 m distance from the highway (based on Dudka, 1993). All values are reported in parts per million (ppm) except Al and Fe, which are reported in percentage (%)...... 47

Table 3 Results for linear regression and Pearson correlation between heavy metal concentrations and distance from highway. Asterisks (*) denote significant relationships at α = 0.05...... 48

Table 4 Comparison of average metal concentrations in soils along the Manali-Leh Highway with other localities discussed in the text...... 49

Table 5 Results for Pearson correlation between total organic carbon and distance from the highway.

Asterisks (*) denote significant relationships at α = 0.05...... 49

Table 6 Results for Pearson correlation between of 4 heavy metals (Chromium, Lead, Zinc and Barium)

concentrations and total organic carbon. Asterisks (*) denote significant relationships at α = 0.05. Double

asterisks (**) denote significant relationship at α =0.01...... 50

Table 7 Comparison of traffic volume along the Manali-Leh Highway with other localities discussed in the

text...... 50

Table 8 Descriptive statistics of total sulphur concentrations (n = 15 samples from 0, 2, 5, 10, and 20m at each site). The local baseline values were calculated using samples collected at 150 m distance from the highway (based on Dudka, 1993). All values are reported in parts per million (ppm)...... 51

Table 9 Concentrations of 16 EPA-prioritized polycyclic aromatic hydrocarbons and soil toxicity in each sample. PAH analysis was carried out on a composite sample at a distance of 2m from the highway at each site. ND denotes concentration not detected by GC-MS. All values are reported in micrograms per kilogram

(µg/kg)...... 52

Table 10 Correlation matrix showing the relationship between total organic carbon and the 16 EPA- prioritized polycyclic aromatic hydrocarbons. Asterisks (*) denote significant relationships at α = 0.05.

Double asterisks (**) denote significant relationship at α = 0.01...... 53

1. INTRODUCTION:

Contamination of the physical environment is one of the most common side effects of economic development. In urban or rapidly urbanizing areas, this contamination takes many forms, including atmospheric, terrestrial, aquatic and marine pollution. Within terrestrial settings, soil contamination by various organic and inorganic pollutants has become a major issue for environmental sustainability. These pollutants, including heavy metals and polycyclic aromatic hydrocarbons (PAHs), have multiple sources, namely vehicular emission, industrial discharge and domestic waste (Christoforidis and Stamatis, 2009).

Eventually these pollutants are accumulated in surface soils through long and short distance transport of aerosols, which settle down due to gravity and by means of precipitation (Martin, 2003). Some pollutants may also accumulate in soils via surface and groundwater transport.

Roads are the arteries of modern societies. They are used for travelling as well as transport of goods from one place to another. Apart from their socio-economic uses, roads and the traffic travelling on them have important influences on abiotic components of ecosystems including hydrology, sediment transport and water and air chemistry (Forman and Alexander, 1998; Coffin, 2007). These effects are felt during the construction of a road as well as during its lifetime of use (Spellerberg, 1998).

1.1. Heavy metals in roadside soils:

Roadside environments are frequently adversely affected by vehicular traffic (e.g. Vandenabeele and

Wood, 1972; Hewitt and Candy, 1990; Turer et al., 2001; Chen et al., 2010). Vehicles that travel on roads produce exhaust that contains significant amounts of lead (e.g. Turer and Maynard, 2003; Christoforidis and Stamatis, 2009; Walraven et al., 2014). Additionally, car bodies, brake linings, paint, tyres and asphalt can all release significant amounts of metals, including zinc, copper, chromium, nickel and cadmium

(Lagerwerff and Specht, 1970; Horner, 1996; Hjortenkrans et al., 2006; Harrison et al., 2012). Some of these metals, specifically Cu, Cd, Cr, Pb and Ni, are either carcinogenic or neurotoxic (Hayes, 1997; Järup,

2003).

Over time, metals released from vehicles accumulate in surface soils along roads (Lagerwerff and

Specht, 1970; Turer et al., 2001). The rate of their accumulation is dependent on factors such as traffic volume, distance from the road, depth of the soil profile, age of the road, and vehicle speed (reviewed in

Falahi-Ardakani, 1984). Factors like type of paving material (dirt or asphalt), prevailing wind direction, amount of runoff, local terrain, snow cover, and amount of organic matter in the soil are also important determinants of the degree to which these metals accumulate in soils. Metal contaminants are typically concentrated within 15-20 m from roads (Vandenabeele and Wood, 1972; Ward et al., 1975; Hewitt and

Candy, 1990; Munch, 1993; Turer et al., 2001; Chen et al., 2010), and within the top 10-20 cm of the soil profile (Chow, 1970; Milberge et al., 1980; Wilcke et al., 1998; Imperato et al., 2003; Wei and Yang, 2010).

Previous research has indicated that there is usually an inverse relationship between metal concentrations and distance from the road and depth. (Ward et al., 1975; Hewitt and Candy, 1990; Turer et al., 2001). However, studies conducted in snow-covered or mountainous areas indicate that declining metal concentrations with depth and distance may not be universal. For example, a number of studies conducted in areas receiving seasonal snow cover have found that deicing salts used to keep roads clear in winter have an important influence on the way metals behave in the soil (e.g. Norrström and Jacks, 1998; Amrhein,

1992; Howard and Sova, 1993). In such areas, the Na2+ and Cl - ions produced from deicing salts may cause metals to percolate downwards and also increase in concentration away from the highway. Local topography also has an effect on how metals accumulate in roadside soils. Panek and Zawodny (1993) made an assessment of heavy metal concentration along a roadside in the mountainous terrain of the Sierra

Nevada, Spain. They found that while Pb and Zn declined with distance from the highway, Fe, Mn, Cu, Ni and Cr did not. They also found that on rising slopes, the concentrations of these metals showed a clear decrease but on descending slopes, the concentrations either remained the same or increased with distance from the highway. More recently, Zhang et al. (2012) conducted a study examining the concentrations of heavy metals in agricultural soils along a highway in the vicinity of Kathmandu, Nepal. They found that

2 the concentrations of metals did not decrease consistently with distance away from the highway and attributed this to farming activities, crop growth and the complex terrain of the area.

1.2. Elemental characteristics of petrol (gasoline) and diesel exhaust:

All of the abovementioned studies were carried out in areas where vehicles generally use spark-ignition engines that rely on petrol as fuel. Petrol contains a number of toxic metals, but lead (Pb) is the most intensively studied. Until recently, tetraethyl lead was added to petrol as an anti-knock additive to increase the octane number (i.e. fuel efficiency). An increase in octane number causes better combustion by decreasing detonation or knocking of the engine (Scherzer, 1990). Following fuel combustion, the lead is released into the atmosphere as soluble halides, less soluble oxides, and insoluble sulphates and carbonates

(Olson and Skogerboe, 1975), and eventually settles into roadside surface soil. Once accumulated, lead can persist in soils for more than 100 years (Erel, 1998). Therefore, although the use of leaded petrol has been phased out around the world since the 1970s, petrol-derived lead may still constitute a measurable health threat in many locations (Tong et al., 2000; Nevin, 2007). Consequently, lead is the most intensely studied heavy metal in urban and urbanizing areas.

In some countries, including India, most vehicles have compression-ignition engines that use diesel.

Roughly 70% of the automobiles running on Indian roads use diesel (Murugesan et al., 2009). In diesel engines, dimethyl ether is added as an anti-knock additive. Consequently, the lead content of exhaust from diesel engines is low compared to petrol engines (Parekh et al., 2002). However, diesel engines emit as much as 50-200 times more particulate matter than petrol engines (McClellan, 1986). These particles range from 50-1000 nm in size and they contain high amounts of solid carbonaceous materials, volatile organic compounds like PAHs, ash from heavy metals, and sulphur compounds (Kittelson, 1998). Very little research has been conducted on the elemental concentration of diesel exhaust. Available data indicate that in general, metal concentrations are low in diesel. However, the concentrations of metals that are naturally abundant in the Earth’s crust (i.e. Al, Ca, Fe, Mg and Si) are higher than concentrations of metals that are mostly produced by anthropogenic sources (i.e. Pb, Cu, Cr, Ni, Co and V; Wang et al., 2003; Sharma et al.,

2005). Indian diesel contains very little metals but is 1-2% sulphur by weight, which is amongst the highest

in the world (Reddy and Venkataraman, 2002).

1.3. Sulphur in roadside soils:

Sulphur (S) is an important component of soil organic matter and is necessary for growth and metabolism in plants and animals (Freney et al., 1962; Jamal et al., 2010). The total S content of unpolluted soils varies 0.002% to 10%; the highest levels are present in saline and organic soils (Germida et al., 1992).

Sulphur occurs in both organic and inorganic forms in soils and is cycled between these two forms by mobilization, mineralization, immobilization, oxidation and reduction (Krouse et al., 1996; Scherer, 2009).

More than 95% of soil sulphur is in organic form and is concentrated in the upper (O and A) horizons

(Eriksen et al., 1998). Inorganic sulphur is more mobile than organically-bound sulphur and is found at

lower depths. Sulphides, elemental sulphur and sulphates are the main forms of inorganic sulphur; sulphates

being the most important form for plant growth (Germida et al, 1992; Scherer, 2009).

Although sulphur is a naturally occurring and important element for biological processes, excess sulphur in soils can have negative consequences. For example, excess sulphur decreases soil pH, particularly during oxidation, thereby mobilizing toxic metals, and making them more available to plants (Knabe, 1976; Helyar and Porter, 1989; Bolan and Hedley, 2003). Mobilized metals can also percolate downwards to contaminate groundwater. Sulphur-induced soil acidification is also known to reduce activities of microbes and macroinvertebrates in the soil (e.g. Cárcamo et al., 1998), which further affects the soil chemistry. Plants and animals may be exposed to excess sulphur from geological sources like volcanism and sea spray, though in contemporary times, such sources account for only a small portion of the total sulphur in the biosphere

(Rennenberg, 1984). Today the majority of sulphur found in the environment comes from anthropogenic sources, such as sulphur dioxide emissions from combustion of fossil fuels and metallurgical processes like smelting. Sulphur released by these processes is deposited on leaves, and accumulates in surface soils by dry deposition or precipitation (Moss, 1978).

While a relatively large volume of literature exists on the sulphur content of agricultural and forest soils

(e.g. Nyborg et al., 1977; Stanko and Fitzgerald, 1990; Eriksen, 1997a, 1997b, 2009; Prietzel et al., 2004;

Rodríguez-Lado and Macías, 2006; Koptsik and Alewell, 2007; Larssen et al., 2011), only four studies so far have investigated the total sulphur content (sum of both organic and inorganic components) of roadside soils. Iqbal (1988) measured concentrations of total sulphur in plants and soils at four sites in downtown

Karachi, Pakistan, an area where the consumption of diesel had increased since the early 1970s (Ahmed et al., 2001). He found that the sulphur content of soils near roads was 3-6 times higher than that in the control site, which was situated away from the downtown area. Iqbal and Mahmood (1992) also measured total sulphur in plants and soils at incremental distances from a highway on the outskirts of Karachi. The concentration of sulphur (36-77 ppm) in this study was much less than that in downtown Karachi (91-565 ppm; Iqbal, 1988) due to the low volume of traffic on this highway. Nevertheless, the concentration of sulphur in soils declined with distance from the highway, thereby implicating vehicles as the source of sulphur. In the USA, where petrol has historically been the most popular automobile fuel, the impact of vehicles on sulphur concentrations in roadside soils is less clear. Turer et al. (2001) measured total sulphur concentrations in roadside soils of Cincinnati, Ohio. These authors did not examine the relationship between sulphur concentrations and distance from road. However, they did show that the concentrations declined with depth. On average, sulphur in surface soils along the road was 1000 ppm and the concentration declined by a factor of two to three with depth in the soil profile, from 0 cm to 30 cm. Turer and Maynard

(2003) measured total sulphur in roadside soils at two sites in Corpus Christi, Texas and found that average concentration was 1200 ppm at both sites. However, they found that at one site, sulphur concentration declined with distance from the road while at the other, the concentration increased with distance. Depth- wise, the concentrations declined by two to four times in one site and there was a haphazard relationship in the other. This was likely because the second site had a considerable number of oil refineries and diesel- operated trucks that affected the distribution of various elements, including sulphur, in the soil. Although these studies are not unanimous in the patterns that they report, they indicate that like metals, sulphur

content typically declines with distance from the road and depth in the soil profile, particularly in areas that

rely on diesel fuel.

1.4. Polycyclic aromatic hydrocarbons in roadside soils:

Polycyclic aromatic hydrocarbons (PAHs) are a group of compounds that contain two or more fused

benzene rings. They are extremely toxic compounds that are known to be carcinogenic and mutagenic

(Edwards, 1983). Because of their strong carcinogenic and mutagenic properties, the United States

Environmental Protection Agency (USEPA) has classified sixteen of them as priority pollutants (Keith and

Telliard, 1979).

PAHs are produced through incomplete combustion of biomass or fossil fuels. Although vegetation

burning and volcanic eruptions can produce PAHs, these sources are negligible compared to anthropogenic

sources like burning of wood as a cooking fuel and vehicular and industrial emissions (Baek et al., 1991;

Mastral and Callén, 2000; Srogi, 2007). Once released, PAHs travel through the atmosphere and eventually settle on soils through aerosol deposition (Wilcke, 2000).

Since they were first reported by Blumer (1961), PAHs in soils have been routinely investigated.

Establishing the degree to which PAHs accumulate in soils is crucial because human exposure to PAHs is more from soil than from air or water (Menzie et al. 1992). The mean concentration of soil PAHs in parts of the world that are not affected by anthropogenic activities is 328 µg/kg (Nam et al., 2009). PAH concentrations are substantially elevated in urban areas (as much as five to seven times). Consequently most studies have focused on quantifying PAHs in urban soils (e.g. Wilcke et al., 2005; Aichner et al.,

2007; Jiang et al., 2009; Cachada et al., 2012) and in roadside soils (e.g. Yang et al., 1991; Benfenati et al.,

1992; Amagai et al., 1999; Chu et al., 2003; Agarwal, 2009; Essumang et al., 2011). As expected, most of these studies have found that concentrations of PAHs in soils decline with distance from the source. Such studies are important not only because vehicular emission is a significant source of PAHs, but also because

PAHs emitted from fuels tend to accumulate in soils easily (Tolosa et al., 2004).

As mountains represent stark altitudinal and environmental gradients, studying how different organic contaminants like PAHs are distributed in mountainous terrains is especially important as the processes that occur in the mountains may be indicative of the mechanisms that operate in other regions (Daly and Wania,

2005). Studies conducted in the Holy Cross mountains of Poland found that concentrations of several organic contaminants in soils, including PAHs, increased with altitude (Migaszewski, 1999; Migaszewski et al., 2002). Although most human exposure to PAHs is via soil, contamination of drinking water is also of real concern in montane ecosystems because mountains provide drinking water, and these persistent organic pollutants are deposited on glaciers. Monitoring PAH accumulation in the Himalaya is of vital importance because the Himalayan glaciers provide freshwater supplies to more than two billion of the world’s population (Rangwala and Miller, 2012). However, monitoring efforts are rare and the matter needs immediate attention.

1.5. Study aim and objectives:

Major gaps remain in our understanding of elemental and PAH concentrations of soils along roads, particularly where diesel is the main fuel. For example, diesel engines emit twice as many PAHs as petrol engines (Lima et al., 2005). However, only one study has focused on PAH measurement of roadside soils in areas dominated by diesel-fueled vehicles (Agarwal, 2009). Furthermore, very few studies have examined contamination of roadside soils in montane ecosystems (Reiners et al., 1975; Panek and

Zawodny, 1993; Zhang et al., 2012). The Indian Himalaya present an ideal natural laboratory for studying the effects of vehicular pollution. Until relatively recently, communities within these mountains were isolated from the rest of the world. However, since the late 1970s, the Manali-Leh Highway in northwestern

India (Fig. 1) has opened up approximately 480 km of high altitude terrain to vehicular traffic (Owen,

1996). This highway connects Manali, a town in the Kullu valley of Himachal Pradesh to Leh, the capital of the Ladakh district of Jammu and Kashmir (Fig. 1). Although the highway has been in operation for more than 40 years, it first came into prominence during the year 1999, when India and Pakistan were engaged in a fierce battle at Kargil. At that time, the other road to Leh (via Kargil) was under siege.

Therefore, the Manali-Leh Highway was used to provide supplies to the Indian Army. Today this highway accommodates about 50,000 vehicles annually. The majority of this traffic carries fuel and supplies for army outposts along the highway, but an increasing percentage transports tourists. Due to heavy snowfall

(e.g. on some passes), the highway is only open to tourists for four months (mid-June to late-September).

However, army vehicles travel along parts of the road throughout the year. In the present study, the concentrations of 10 heavy metals, total sulphur, total organic carbon and polycyclic aromatic hydrocarbons

(the 16 EPA prioritized ones) have been measured in roadside soils along the Manali-Leh Highway. Three specific hypotheses are tested:

(i) Heavy metal concentrations along the highway are elevated due to vehicular traffic.

(ii) Sulphur from diesel exhaust has accumulated in roadside soils.

(iii) The PAH content in soils close to the highway is high.

2. MATERIALS & METHODS:

2.1. Study area:

The Manali-Leh Highway (Fig. 1) is situated at an average elevation of 4000 m above sea level. It traverses the Pir Panjal range in the Middle Himalaya and the Zanskar Range in the Trans-Himalaya. The geomorphology and glacial history of this region have been documented in detail by Owen et al. (1995,

1997, 2001); Taylor and Mitchell (2000); Owen (2010, 2011); Dortch et al. (2011); Hedrick et al. (2011) and Owen and Dortch (2014). In general, the route traverses a rugged landscape comprised of U-shaped valleys, mountainous peaks, slopes developed on massively jointed granites and meta-sedimentary debris deposits of Palaeozoic and Cretaceous eras, and small fluvial and glacial landforms (Steck, 2003; Adams et al., 2009). Despite the varied geology, the soils along the Manali-Leh Highway can all be classified as sandy loams. The sand content in this region varies from 20-68% (Sagwal, 1991) and the pH is neutral to alkaline (Katoch et al., 2012). Four major mountain passes (called ‘La’ in Tibetan language) lie along this route: Rohtang La (3978 m), Baralacha La (4890 m), Lachulung La (5059 m) and Taglang La (5328 m)

(see Fig. 1). Landslides are a recurrent phenomenon (Weidinger et al., 2002; Dortch et al., 2009) and cause frequent traffic congestions.

Due to the presence of numerous peaks that are higher than 4500 m in the Greater Himalayan ranges, most of the precipitation from the Indian summer monsoon does not reach the study area (Bookhagen et al.,

2005). However, the monsoon still dominates regional moisture transport and precipitation (Mayewski et al., 1984; Benn and Owen, 1998). There is a steep moisture gradient (1000-200 mm/year) from south to north along the highway (Hedrick et al., 2011). In response to this moisture gradient, the lush forested slopes of the Pir Panjal in the south give way to sparse grasses and small shrubs to high altitude desert as one moves northwards from Manali to Leh (Bhattacharya, 1989).

2.2. Sample collection and preparation:

Soil samples were collected from four sites along the Manali-Leh Highway (Figs. 1 and 2). These sites were selected because they occupy relatively flat terrain and have been affected to varying degrees by humans. A description of each collection site is provided in Table 1. At each site, samples were collected from a transect perpendicular to the highway. Soil pits were dug at distances of 0m (roadside), 2m, 5m,

10m, 20m and 150m from the road, and within each pit, soil samples were collected from three depths-

3cm, 9cm and 15cm using a stainless steel hand trowel (Fig. 3). To avoid cross-contamination, the trowel was cleaned with alcohol wipes before and after collecting each sample. The samples were collected in

15ml polypropylene centrifuge tubes, which were pre-washed with 5% HNO 3 and distilled deionized water.

Tube caps were sealed with parafilm tape and kept in a cool, dark place until they were shipped to the

United States. The samples were imported under USDA permit No. P330-13-00060 (to B.E. Crowley).

Upon arrival in the US, the samples were lyophilized to remove moisture. They were then ground to a fine powder using an agate mortar and pestle. Next the samples were passed through a US size 40 (0.400mm) nylon mesh to achieve consistency of particle size. After filtering, samples were stored in ashed glass vials in a cool, dark place.

2.3. Analytical methods:

To analyze the concentrations of metals, total organic carbon (TOC), total sulphur (TS) and PAHs, soil samples were subjected to a number of analytical methods. Metal concentrations were quantified using X-

Ray Fluorescence spectrometry, TOC and TS were determined using an Elemental Analyzer and PAHs were quantified by Gas Chromatography-Mass Spectrometry. Each step is briefly described below:

2.3.1. X-Ray Fluorescence:

Three to four g of soil were pressed into pellets under a pressure of 20 tonnes for 3-4 minutes. The pellets were then run on a Rigaku 3070 spectrometer against a US Geological Survey rock standard, the

Ohio Black Shale (SDO-1) to achieve quality control. Concentrations of a suite of elements are normally provided by the spectrometer. The ones that have been considered in this study are Aluminum (Al), Iron

(Fe), Chromium (Cr), Copper (Cu), Lead (Pb), Nickel (Ni), Cobalt (Co), Zinc (Zn), Vanadium (V) and

Barium (Ba) because they are commonly reported in vehicle-related pollution studies (Lagerwerff and

Specht, 1970; Hewitt and Candy, 1990; Turer et al., 2001). The concentrations are reported in percentages for major elements (Al and Fe) and in ppm for trace elements (Cr, Cu, Pb, Ni, Co, Zn, V and Ba).

2.3.2. Carbon-Sulphur Analysis:

Total Sulphur (TS) and Total Organic Carbon (TOC) in the samples were measured using an ELTRA C-S

2000 C/S analyzer. TS was run using 0.1g of dried, untreated samples. For TOC, 0.1g of the samples were acidified with 20mL of 7% HCl. The acidified samples were placed on a hot plate at 60 °C for 7 hours. The solution was then filtered through 47mm glass fibre filters and the residue was rinsed with distilled water to remove all remaining acid. Samples were then dried overnight at 50 °C. Results were calibrated using US

Geological Survey standard Ohio Black Shale [SDO-1] (C = 9.68%, S = 5.35%), internal laboratory standard Devonian Black Shale [DBS-1] (C = 3.5%, S = 1.97%), and the Alpha Resources soil standard (C

= 0.10%, S = 0.11%).

2.3.3. PAH Analysis:

PAH concentrations were measured in soils collected at 2m from the highway using a composite sample of all three depths for each transect to identify the sixteen priority compounds identified by the USEPA (Table

8). Samples were analyzed by ALS Environmental Inc. in Kelso, WA. About 20g of soil were mixed with surrogate compounds (PAH standards). These standards are similar in structure to the analyzed compounds.

The mixture was extracted using Dichloromethane (DCM) in an automated Soxhlet (USEPA method 3541).

All solvents used were of reagent grade or higher quality. The extracted samples were then concentrated to

5mL using a fine stream of nitrogen gas. Following concentration, the extracts were cleaned using silica

gel column chromatography (USEPA method 3630). Before use, the silica gel was activated by heating to

150 °C for 16 hours. A 1mL aliquot was put into the columns and was eluted four times with 10 mL of 1:1

DCM:n-hexane. The four solvent fractions were combined and concentrated to 1mL under a gentle stream

of nitrogen gas. The samples were then analyzed using Gas Chromatography-Mass Spectrometry (USEPA

method 8270D). Briefly, the extract was introduced to the Gas Chromatograph (GC). The GC separated the

analytes, which were then detected by a Mass Spectrometer (MS) attached to the GC. The compounds were

identified by comparing the peaks of the samples to the peaks of the standards and quantified by comparing the peaks of various compounds in the sample to the same peaks in the standards using a five-point calibration curve. To ensure quality control, all the methods were checked for accuracy and precision.

Procedural blanks were run periodically to check for contamination, and recovery efficiency was checked by spiking the samples (Matrix Spike-MS) with a known amount of PAH standard. Recoveries ranged from

60-83%.

2.4. Data processing and analyses:

The X-ray fluorescence spectrometer produces ‘raw’ results in the form of counts per second, which

are in proportion to the concentration of particular elements in the sample. Post analysis, these counts were

converted to concentrations using regression. For trace elements, power regressions were used. The

concentrations of the major elements were determined by multiple regressions.

All statistical analyses were carried out using SPSS 22.0. Significance was set at α = 0.05 for all tests. The data were checked for normality of distribution and homogeneity of variances. Most of the elements were found to be positively skewed. Log 10 transformation did not considerably improve the

distribution. Therefore, analyses were carried out on the untransformed data. The homogeneity of variance

was checked using Levene’s tests as well as non-parametric Levene’s tests. In both cases, the variances

were found to be significantly different ( p < 0.05) for most elements. Therefore, it was decided that parametric tests cannot be used with this dataset. Instead, the non-parametric Kruskal-Wallis tests (hereafter referred to as K-W tests) were used. Significant differences were found in the median concentrations of

various elements among transects. Consequently, each transect was treated as a separate entity in all

subsequent analyses.

To determine if there were differences in elemental concentrations among various depths in the soil

profile, K-W tests were used. In cases where the relationship was significant, pairwise posthoc tests were

carried out to find out which depths differed.

To determine the relationship between metal concentrations in soils and increasing distance from

the highway, scatter plots were created and Pearson correlation coefficients (r), coefficients of

determination (R 2), and their associated p values were calculated. For sulphur, power regression was used

to determine the relationship between distance from highway and the concentration of sulphur. The non-

parametric Mann-Whitney U tests were also used to compare concentrations near the highway (i.e. < 5m)

and distant from the highway (i.e. > 5m). Because no geochemical baseline data exists for soils in India,

the local baseline concentration of each metal in each transect was estimated by calculating the geometric

mean of samples from the three depths at a distance of 150 m from the highway (following Dudka, 1993).

Cluster analysis (CA) was applied to determine the association of the various heavy metals, TS and

TOC in the soil. CA is essentially a visual representation of a correlation matrix. It has been used extensively

in previous studies that measured heavy metal concentrations in soils (e.g. Turer et al., 2001; Abollino et

al., 2002; Micó et al., 2006; Christoforidis and Stamatis, 2009). There are two types of cluster analyses-

12 hierarchical and non-hierarchical. In hierarchical CA, each observation is initially placed in its own cluster, but subsequently the clusters are merged until n-1 clusters remain such that finally all n observations are contained in one cluster (n is the number of observations i.e. the various elements in this study). The process is considered to be hierarchical because once two clusters are merged, they cannot be separated at a later stage (Rogerson, 2001). Hierarchical cluster analysis was used in this study. Because the units of the data were not the same and the data were not normally distributed, for the purpose of CA, the data was transformed following Schuenmeyer and Drew (2011):

− × (1)

where x is the concentration of a particular element, is the mean of all concentrations of that element and

is the standard deviation of that particular element. Ward’s method was chosen as the clustering technique and the resultant clusters are shown in a dendrogram.

For PAHs, the mean of each of the compounds were calculated and correlation analyses were carried out to find the relationship of the total PAH content of the soil at each site with its TS and TOC values.

Soil toxicity was assessed in terms of Benzo(a)pyrene-equivalent concentration (BaPEq) because BaP is known to be the most carcinogenic PAH. The Toxic Equivalency Factors (TEFs) proposed by Nisbet and

LaGoy (1992) were used to compare the carcinogenic potential of each of the compounds relative to BaP.

The total BaPEq was calculated as:

Total BaPEq = Σ(C i × TEF i) (2)

where C i is the concentration of an individual PAH compound and TEF i is its corresponding toxic

equivalency factor.

3. RESULTS AND DISCUSSION:

3.1. Concentrations of heavy metals:

In this section, the hypothesis that the concentrations of heavy metals along the Manali-Leh

Highway are elevated due to vehicular traffic is tested by checking whether the concentrations of metals

change with increasing distance from the highway and increasing depth in the soil profile.

Summary statistics for each metal are presented in Table 2. These are based on distances up to 20m

from the highway. Local baseline values (estimated for samples collected at 150m from the highway) are

also included in this table. Table 3 provides the details for the correlations (r and associated p values) and

linear regressions (R 2 and associated p values) between distance and metal concentrations.

As can be seen in Table 2, all metals are well within the local baseline values at Kothi and Killingsarai. In

Jispa, all metals are above the local baseline values, while in Rumtse, only Fe, Cr, Ni, Co, V and Ba are

above the baseline. There is no significant relationship between metal concentration and depth within the

soil profile for any of the metals in any transect (K-W p > 0.05). In terms of distance, however, some trends

are observed, which are described below:

Kothi (Transect 1):

There is an apparent but insignificant ( p > 0.05) increase in concentration with distance from the highway

for most metals. This pattern is significant and strongly positive for two of the ten metals: Al and Cu (Fig.

4; Table 3).

Jispa (Transect 2):

There is an apparent but insignificant ( p > 0.05) decrease in concentration with distance from the highway

for most metals. This relationship is significant and strongly negative for three metals: Fe, Cu and Ni (Fig.

4; Table 3).

Killingsarai (Transect 3):

There is an apparent but insignificant ( p > 0.05) increase in concentration with distance from the highway for most metals. This relationship is significant and strongly positive for Al, Fe, Pb, Ni, V and Ba (Fig. 4;

Table 3).

Rumtse (Transect 4):

The concentrations of most metals are relatively constant with increasing distance from the highway. The exceptions are Cr and Co, which record an apparent decline in concentrations with distance from the highway. However, none of the metals shows any significant (linear regression p > 0.05) relationship (Table 3). It is also noteworthy that the concentrations of Cr and Ni in the roadside (0m) sample is much higher than the mean concentrations of these two metals in this site. This particular sample also has high Mg and low Si concentrations, thereby suggesting that this sample is likely derived from ultramafic rocks sourced from a different region. Furthermore, as the roadside samples are essentially paving materials, it is possible that the material that was sampled at Rumtse was laid down recently, and has not been exposed to vehicular traffic for long.

The published literature on roadside soil pollution suggests that concentrations of various heavy metals decline with distance from road and with depth in the soil profile (e.g. Wilcke et al., 1998; Turer et al., 2001). In all those cases, the metal concentrations were much higher than their respective local background levels. Overall, the results from this study suggest that the concentrations of heavy metals in soils along the Manali-Leh Highway are not elevated compared to either local baseline values or results of other studies on roadside soil pollution (Table 4). It is also apparent from above that with the exception of

Jispa (Transect 2), there is no consistent pattern of decline of metal concentration with distance from the highway. There are also no differences in metal concentrations among soil depths.

3.2. Relationship between heavy metals and TOC:

The TOC content of the measured samples varies from 0.13 to 11.81% with a mean value of 1.53%.

There is great spatial variability of TOC content as one moves from Manali to Leh along the highway. In general, there is a fairly strong and significantly negative correlation between elevation and TOC content

(r = -0.65, p < 0.05). In terms of distance, the amount of TOC increases significantly with distance from

the highway at Kothi, but at all other sites, the concentration, in general, is very low (Table 5).

In their study of roadside soil contamination in Texas, Turer and Maynard (2003) found that organic matter had an important role in determining the concentrations of heavy metals in soils. They found that as the amount of organic carbon in the soil increased, the concentrations of Cr, Ba, Pb and Zn also increased.

In the present study, there is not a significant relationship between Cr and TOC at any of the localities

(Table 6). Ba displays a positive and highly significant relationship ( p < 0.01) at Rumtse only. For Pb there is a positive and highly significant relationship with TOC at Jispa and Rumtse ( p < 0.01), a negative and

insignificant relationship with TOC at Killingsarai ( p > 0.05) and a positive but insignificant relationship at Kothi ( p > 0.05). Zinc shows a positive and highly significant relationship with TOC at Jispa and Rumtse

(p < 0.01), a moderately positive but significant relationship at Kothi ( p < 0.01) and an extremely weak and

insignificant relationship at Killingsarai ( p > 0.05). This suggests that along the highway, Pb and Zn are

likely associated to a refractory form of organic matter that is derived from anthropogenic sources (Turer

and Maynard, 2003).

Although the highway is closed to tourists for eight months of the year, army vehicles are presumed to

travel much of its length during the winter. During the cold period, deicing salt is used to keep the road

clear. As discussed in the introduction, previous studies in snow-covered areas have indicated that use of

decicing salt might result in dispersal of heavy metals both away from the road as well downward in the

soil profile. In the present study, it is seen that there is an apparent increase in metal concentrations with

distance from the highway at Kothi and Killingsarai, almost no change in concentrations at Rumtse and an

apparent decrease in concentrations at Jispa. Although at Jispa, the concentrations of metals decrease with

16 distance from the highway, overall it may be said that the effect of deicing salts is seen in this study also.

However to confirm this, a detailed study on soil chemistry of samples collected during early June (when the snow has just melted) and in late September (i.e. after the first snowfall).

Summarily, it is seen from the above discussion that the concentrations of heavy metals along the

Manali-Leh highway are very low. Concentrations close to the highway are similar to the local baselines

(Table 2) and lower than the results of previously published studies (Table 4). Therefore, it is found that the hypothesis regarding elevated concentrations of heavy metals due to use of vehicles is not valid. This finding may be attributed to the fact that the total vehicular load on this highway is very low compared to some other studies (Table 7). It may also reflect the low metal content of diesel fuel in India, unlike its sulphur content, which is considerably high.

3.3. Concentration of total sulphur:

As mentioned in the introduction, very few studies have investigated the concentration of sulphur in

roadside soils. However, it is crucial to assess the concentrations of sulphur in roadside soils, especially in areas where diesel-fueled vehicles dominate. In this section the hypothesis that the concentration of sulphur in soils along the Manali-Leh Highway is elevated due to diesel exhaust is tested by investigating whether sulphur concentrations decrease with increasing distance from the road and with increasing depth within the soil profile.

Table 8 shows the descriptive statistics of sulphur concentration in the four sites along the Manali-Leh highway. It is seen from the table that the concentration of sulphur at Jispa is much higher than that at the other three sites. This is true for all distances. It is possible that the soil at Jispa receives additional sulphur input from the use of manure like cow dung (Place et al., 2007), as the transect here lay across an agricultural field adjacent to the highway. The roadside sample (0m) at Rumtse has substantially less sulphur than the corresponding samples in the other three sites. As mentioned earlier, this sample might be recently laid down paving materials and might not been exposed to vehicular traffic for long.

K-W tests reveal that there is no significant difference in the concentration of sulphur with depth within the soil profile at any of the sites. Power regressions were used to determine the relationship between sulphur concentration and distance from the highway. As mentioned earlier, the roadside (0m) sample at Rumtse was not produced in situ. Therefore, this sample was not considered in the power regression for Rumtse.

Results suggest that at all four sites, the concentration of sulphur declines with increasing distance from the highway (Fig. 5), but the regressions are significant only at Kothi and Killingsarai. Mann-Whitney U tests were conducted and it was found that there is a marginally significant difference in concentrations of sulphur near and away from the road only at Kothi and Jispa (p = 0.057 in both sites), but not at the other two locations.

3.4. Relationship between TOC and TS:

Previous studies (e.g. Eriksen et al., 1998) have found that most of the sulphur in soils is concentrated

in the upper horizons, particularly the organic horizon, thereby suggesting that there is a strong relationship

between TOC and TS. At Kothi, there is a negative but significant relationship between TS and TOC (r = -

0.60, p = 0.018). On the other hand, at Jispa, Killingsarai and Rumtse, there is a positive relationship

between these two variables (r = 0.54 p = 0.039; r = 0.18 p = 0.521, and r = 0.22 p = 0.423 respectively).

At Kothi, vegetation cover increases as one moves away from the roadside. Therefore, absorption of sulphur

by plants increases with distance away from the road. This results in decrease of sulphur concentration with

distance from the road. As far as TOC is concerned, the soil here receives some of it from vehicles, and at

a same time, there is a contribution of TOC from decomposition of plant litter. The latter component of the

TOC increases with distance from the road. So an inverse relationship between TOC and TS is observed at

this site. On the other hand, in the remaining three sites, there is practically no vegetation cover, except to

some extent at Jispa. Moreover, vegetation cover in these sites do not increase with distance from the

highway. Therefore, the consumption of sulphur from soil is low and practically, does not vary with distance

from the road. At the same time, there is very little contribution of TOC from decomposition of plant litter.

For this reason, both TS and TOC originate from vehicles, resulting in a positive relationship between these

two variables.

In summary, from the above discussion it is seen that total sulphur concentrations in the soils along

the Manali-Leh Highway are substantially elevated when compared to local baseline values. The

concentration of total sulphur declines with increasing distance from the highway at all four sites. There is

no variation of concentration of total sulphur with depth in the soil profile. On the basis of these results, it

is likely the exhaust of diesel run vehicles is the source of TOC and TS in roadside soils, particularly in

Jispa, Killingsarai and Rumtse. This is of concern because excess levels of sulphur in soils can lower soil

pH, resulting in acidification that can render already small amounts of arable lands in the area unproductive.

Furthermore, intake of excessive sulphur, either as sulphate or as elemental sulphur, can cause a number of

toxic effects in animals and human beings (e.g. Kandylis, 1984).

3.5. Association of various elements:

Cluster analysis was applied to find associations among the ten heavy metals, TOC and TS. The results

of the cluster analysis are shown in the dendrogram in Fig. 6. The horizontal axis on the dendrogram

represents the correlation between the different variables: lower values mean stronger correlations

(Facchinelli et al., 2001). In the cluster analysis, a few additional elements (Si, Y, Th, Nb, Mo, Ti, Mn, Mg,

Ca and K) have been included to determine how the metals considered in this study remain associated with

additional elements after entering the soil.

Zinc forms a cluster with TOC very early and immediately forms another cluster with Pb and TS. This strongly suggests that these four elements are organically bound. As mentioned in section 4.1, it is possible that Pb, Zn and TS in the study area are associated with an insoluble form of organic matter, which itself is derived from anthropogenic sources like hydrocarbons in vehicular exhaust (Turer and Maynard, 2003). Al and V form a cluster with K, which probably occur in the soil as part of clay minerals. The main clay minerals like kaolinite, illite and smectite all contain these three elements (Velde and Meunier, 2008).

Although clay content is anticipated to be low in the soils of the Manali-Leh Highway, some clay is present.

Ca and Mg form a cluster and represent the carbonate minerals in the soil. Cr and Ni form a cluster with Si

and are associated with local or windblown silt and sand. The metals Y, Th, Nb and Mo are also likely

derived from windblown deposits. Finally, Fe and Co are strongly associated with each other and form a

cluster with Cu, Ti, Ba and Mn, which suggests that these metals are bound to iron oxides in the soil.

Overall, the results of the cluster analysis indicate how the pollutants are associated with other elements in

the soil. This determines their mobility within the soil. For example, as mentioned earlier, excess sulphur can reduce soil pH, which in turn can mobilize toxic metals, in this case potentially Zn and Pb, and make them more available in surface soils (Bolan and Hedley, 2003). These excess metals are readily absorbed by plant roots and transported to leaves, which in turn are eaten by animals. This results in passive transfer of these pollutants through the food chain (Kloke et al., 1984). These metals can also leach downwards and pollute groundwater.

3.6. PAH concentrations:

The term ΣPAHs refers to the sum of the sixteen USEPA-listed priority pollutants that are analyzed in this study. This analysis was carried out on a composite of the samples of the three depths collected at 2m distance from the highway in each site. The ΣPAHs concentrations are 108.26 µg/kg at Kothi, 293.27 µg/kg at Jispa, and 74.65 µg/kg at Killingsarai (Table 9). At Rumtse, the concentrations of most of the compounds are under detection limit, making it impossible to calculate ΣPAH for this site. As this sample was derived from materials sourced from another region (see section 3.1), it is likely that it has lower PAH contents than soils produced in situ. These results are much lower than the PAH content of roadside soils in Brisbane,

Beijing or Delhi (Yang et al., 1991; Chu et al., 2003; Agarwal, 2009), but comparable to the soil PAH content of the Tibetan Plateau (59.9 µg/kg; Wang et al., 2014) and the mountains of western Canada (203-

789 µg/kg; Choi et al., 2009). The molecular compositions of the PAHs at various sites are shown in Fig.

7. Three of the four sites (Kothi, Killingsarai and Rumtse) are dominated by low molecular weight PAHs

(2-3 rings), which suggest that these are ‘multi-hop’ compounds that were transported over long distances

away from their source areas. On the other hand, Jispa is dominated by high molecular weight PAHs (4-6

rings), thereby implying that these are ‘single-hop’ compounds that were deposited close to the source

areas. The ratio of low molecular weight PAHs to high molecular weight PAHs has often been used to trace

the origin of these pollutants. The lower the ratio, the more is the contribution of pyrolitic factors (e.g. fossil fuel combustion) rather than petrogenetic factors, like volcanic eruptions (Neff, 1979). This ratio was computed for each site except Rumtse (Table 9) and was found to be lowest at Jispa (0.20), thereby confirming that the PAHs in the soil there have indeed been derived from local sources, potentially combustion of automobile fuels. Research in Australia has shown that close to a road, particles deposit rapidly due to sedimentation, turbulent diffusion and impact of inertia (Yang et al., 1991). So it is possible

that that the high molecular weight PAHs for the soil sample from Jispa might have been deposited

immediately after being emitted by vehicles, resulting in higher concentration there. Although the soil

sample from Kothi has a higher percentage of low molecular weight PAHs, it also has a substantial amount

of high molecular weight PAHs (20%). Therefore it may be said that PAHs in the soil at Kothi were derived

from both local and non-local sources. Although Kothi, Killingsarai and Rumtse are dominated by low

molecular weight PAHs, based on the abovementioned ratio, it is possible that these compounds, which

have been transported over long distances and then deposited in these three places, may have originated

from vehicular exhaust in their source areas.

Soils that have higher TOC content typically also have higher ΣPAHs (Wilcke and Amelung, 2000).

Along the Manali-Leh Highway, a significant relationship between TOC and ΣPAH was found (r = 0.98, p

= 0.018). This strong relationship may be explained by the quick adsorption of PAHs to the anthropogenic

component of soil organic matter (e.g., black carbon) rather than natural components like humus or leaf

litter (He et al., 2009). The correlation matrix further confirms this strong relationship (Table 10), where it

is seen that TOC is more significantly correlated to the high molecular weight PAHs, which are themselves

emitted by anthropogenic sources.

Although many studies have examined the PAH content of diesel fuel, none have examined the correlation between sulphur and PAH content. In soils along the Manali-Leh Highway, there is a strong positive correlation between TS and ΣPAHs, but it is insignificant (r = 0.90, p > 0.05). This lends credibility to the hypothesis that the sulphur is generated by diesel vehicles.

The rate of wet deposition of PAHs is more than that by dry deposition (Wania and Westgate, 2008).

Assuming the same quantity of available PAHs in air, the deposition will be higher in areas of higher precipitation and vice versa. In the present study area, precipitation is inversely related to altitude. The four site can be arranged in order of decreasing precipitation as Kothi>Jispa>Rumtse>Killingsarai. So it is expected that in terms of ΣPAHs, the sites would also be arranged as Kothi>Jispa>Rumtse>Killingsarai.

However, results show that Jispa has the highest ΣPAHs value, followed by Kothi and Killingsarai. As mentioned earlier, the ΣPAHs value could not be computed for Rumtse. The high value of ΣPAHs at Jispa may be explained by the presence of a source of PAHs other than vehicles. Jispa is, in fact, more populated than both Kothi and Killingsarai and is occupied throughout the year. Consequently, people burn wood for cooking and heating purposes. Such burning emits considerable quantities of PAHs, resulting in higher

ΣPAHs values in Jispa.

Soil toxicity (measured in terms of BaPEq) has been found to be minimum in Killingsarai (5.34

µgBapEq/kg) and maximum in Jispa (52.25 µgBapEq/kg), with a mean value of 21.36 µgBapEq/kg (Table

9). These toxicity values are negligible compared to some more urbanized sites like Shanghai and Delhi

(Agarwal, 2009; Jiang et al., 2009). So at present, soil toxicity is not a threat here.

3.7. Significance of the study:

Because the Indian Himalaya represent a unique terrain that has a fragile environment and is increasingly impacted by humans, assessing pollution there is essential. The results of this study indicate that heavy metals in soils along the Manali-Leh Highway are quite low and in most cases, well below the local background levels. So at first glance, it appears that vehicular pollution is not an issue here. However,

22 elevated sulphur levels in the soils suggest that exhaust from vehicles does, indeed, have an impact on roadside environments. Diesel is the most widely used automobile fuel in India and Indian diesel has high sulphur concentrations in it (Reddy and Venkataraman, 2002). Apart from sulphur, diesel exhaust also emits other toxic compounds like PAHs. The concentrations of PAHs in the soils along the highway are low at present. However, as PAHs are not decomposed easily and have long residence times in soils (Albers,

2003), accumulation may be a concern. PAHs in soils may travel up the food chain. Domesticated animals eat plants growing in roadside soils, and their milk and meat is consumed by humans. Some PAHs, especially those with less than five rings, can be transferred to animal products like milk (Bulder et al.,

2006). In addition, PAHs react with other atmospheric pollutants, such as ozone, nitrogen dioxide and sulphur dioxide, forming compounds like oxy-PAHs, nitro-PAHs and hydroxyl-PAHs (Rajput and Lakhani,

2010). Some of these compounds (e.g. nitro-PAHs) are mutagenic (Edwards, 1983).

Apart from releasing PAHs that can cause cancer and DNA alteration, exhaust fumes from diesel engines are also known to cause other ailments like asthma, headaches, allergies, eyes and nose problems (Sydbom et al., 2001). In addition to potential health risks, emission from diesel automobiles can have serious environmental implications. Diesel exhaust contains a large amount of solid carbonaceous materials, which occur mostly as black carbon (BC). Ramanathan and Carmichael (2008) provided evidence that BC particles can travel long distances, and mixing with other aerosols, can form atmospheric brown clouds that extend 3-5 km above the earth surface. These brown clouds interfere with the surface radiation from the earth at night, enhancing the greenhouse effect. In the Himalaya, climate modeling suggests that advection of warm air heated by BC from south Asia results in a mean annual warming of about 0.6 °C (Ramanathan et al., 2007). Such prolonged heating will not only cause melting of the Himalayan glaciers, but may also induce greater incidences of drought, and irregularities in the Indian monsoon (Menon et al., 2002; Meehl et al., 2008).

4. CONCLUSIONS:

This study has investigated the heavy metal, TOC, TS and PAH contents of soils along the Manali-Leh

Highway in the northwestern Himalaya. This is an area that is unique not only because of its inclement terrain and climate, but also because most of the vehicles that travel the highway are diesel-run. Compared to the large literature on the impact of petrol driven vehicles on the elemental concentrations of roadside soils, there have been very few studies on the accumulation of pollutants emitted by diesel exhaust. To the best of the author’s knowledge, this is the first study to have documented the accumulation of pollutants in roadside soils released from diesel vehicles in the Himalayan region. The results of this study indicate that at present, the level of heavy metal contamination of soil due to vehicles is low. On the other hand, elevated levels of sulphur are found in roadside soils at all four sites, which is of concern from both health and ecological points of view. PAHs derived from diesel exhaust are also present in the soil, although in relatively low quantities. The traffic volume along the Manali-Leh Highway has been rising drastically, with a reported increase of 35% between 2010 and 2011 (Times of India, 2011). With an enormous increase of vehicles running along this highway, it is quite likely that the concentrations of all pollutants derived from diesel-run vehicles will increase rapidly. The rise in the number of vehicles calls for periodic assessments of elemental and PAH concentrations of soils along the highway. It will also be critical to establish the degree to which these pollutants are transferred to the animals and people that live along the

Manali-Leh Highway.

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Fig. 1 Map showing (A) location of the study area within India, and (B) the Manali-Leh Highway.

The sampling sites, towns on either end of the highway, mountain passes and major mountain ranges are labeled.

Fig. 2 Photographs of the study sites: Kothi, Jispa, Killingsarai and Rumtse. All photographs except the one at Jispa taken standing on the Manali-Leh Highway. The photograph at Jispa was taken from the agricultural field across which the transect lay.

Fig. 3 A schematic diagram of sampling protocol for each transect along the Manali-Leh Highway.

Distances and depths are not to scale.

Fig. 4 Bivariate scatter plots of heavy metal concentrations at varying distances from the highway. Only metals that have a significant relationship with distance are plotted. The error bars represent ± 1 standard deviation.

Fig. 5 Bivariate scatterplots and power regressions for total sulphur concentrations at varying distances from the highway for each site. The points represent mean values of each distance and the error bars represent ± 1 standard deviation. The roadside sample at Rumtse (0m) was excluded from regression analysis.

Fig. 6 Dendrogram showing cluster analysis of 10 heavy metals, total organic carbon (TOC) and total sulphur (TS) in soils along the Manali-Leh Highway. The text on the left mentions the most likely soil fraction with which the various clusters are associated.

Fig. 7 Percentage composition of different ringed PAHs at each site.

100%

90%

80%

70%

60%

50% 6 rings 5 rings 40% 4 rings 30% 3 rings

20% 2 rings

Composition of differentringed PAHs (%) 10%

0% Kothi Jispa Killingsarai Rumtse Sites

Table 1 Description of the sampling sites.

Site Latitude Longitude Elevation Remarks

Situated about 30 km north of Manali; located on a gentle Kothi 32 °19’28” N 77 °11’36” E 2579 m slope towards the road; paved road with moderate traffic; dense vegetation cover; evidence of recent rain Situated about 150 km north of Manali; located on a terrace of the River Bhaga; Jispa 32 °38’15.5” N 77 °10’53.9” E 3275 m paved road with moderate traffic; moderately dense vegetation cover with animal dung found in places; no evidence of recent rain Situated about 215 km north of Manali; located on a terrace Killingsarai 32 °49’28.8” N 77 °26’59.2” E 4562 m of the River Tsarap Chu; unpaved road with low traffic; vegetation cover consists only of grasses; no evidence of recent rain Situated about 80 km south of Leh; located on a gentle slope away from the road; paved road Rumtse 33 °37’27” N 77 °45’55.9” E 4259 m with low traffic; vegetation consists of small plants, concentrated along the 10m and 20m marks; no evidence of recent rain; a rivulet passes by the site

Site Elements Maximum Minimum Mean SD Local baseline Al 13.26 6.45 9.85 1.37 11.20 Fe 7.96 3.13 5.67 1.38 7.84 Cr 171 84 142 26 151 Cu 55 26 38 4 50 Pb 29 20 24 3 26 Kothi Ni 105 45 68 14 80 Co 28 12 20 4 21 Zn 125 52 102 23 111 V 38 15 28 7 35 Ba 675 356 498 89 657 Al 16.78 14.26 15.71 1.04 12.34 Fe 5.95 3.52 5.22 0.68 2.60 Cr 109 51 88 17 61 Cu 48 29 42 5 21 Pb 50 21 27 8 24 Jispa Ni 59 44 55 4 37 Co 26 12 19 4 9 Zn 267 58 129 67 38 V 87 38 66 16 25 Ba 843 459 605 129 393 Al 15.17 10.99 12.88 1.08 15.23 Fe 4.76 3.23 3.97 0.51 5.18 Cr 83 39 55 11 69 Cu 51 27 33 6 40 Pb 17 8 11 2 19 Killingsarai Ni 48 40 44 2 51 Co 16 7 12 2 16 Zn 69 29 39 10 42 V 59 21 34 13 52 Ba 695 448 515 60 647 Al 19.11 12.31 15.68 2.44 16.85 Fe 8.16 4.49 5.94 1.47 5.77 Cr 254 51 126 63 91 Cu 45 32 37 4 37 Pb 34 16 21 6 25 Rumtse Ni 137 49 73 33 57 Co 23 10 17 4 16 Zn 112 51 73 20 75 V 102 41 72 20 71 Ba 618 363 476 88 475

Table 3 Results for linear regression and Pearson correlation between heavy metal concentrations and distance from highway. Asterisks (*) denote significant relationships at α = 0.05. Site Elements Correlation Regression r p R2 p Slope Al 0.84 0.039* 0.70 0.039* 0.009 Fe 0.39 0.444 0.15 0.444 0.014 Cr 0.28 0.594 0.08 0.594 0.100 Cu 0.91 0.012* 0.83 0.012* 0.090 Pb 0.27 0.607 0.07 0.607 0.011

Ni 0.50 0.315 0.25 0.315 0.119 Kothi Co 0.22 0.675 0.05 0.675 0.014 Zn 0.26 0.614 0.07 0.614 0.090 V 0.60 0.204 0.37 0.204 0.055 Ba 0.74 0.093 0.55 0.093 1.207 Al -0.14 0.795 0.02 0.795 -0.009 Fe -0.94 0.005* 0.89 0.005* -0.018 Cr -0.64 0.168 0.41 0.168 -0.192 Cu -0.92 0.010* 0.84 0.010* -0.154 Pb -0.24 0.649 0.06 0.649 -0.027 Jispa Ni -0.94 0.005* 0.88 0.005* -0.123 Co -0.79 0.060 0.63 0.060 -0.072 Zn -0.57 0.241 0.32 0.241 -0.719 V -0.80 0.057 0.64 0.057 -0.286 Ba -0.56 0.245 0.32 0.245 -1.401 Al 0.84 0.038* 0.70 0.038* 0.018 Fe 0.87 0.024* 0.76 0.024* 0.009 Cr 0.71 0.111 0.51 0.111 0.112 Cu 0.68 0.139 0.50 0.139 0.049 Pb 0.90 0.015* 0.81 0.015* 0.051 Killingsarai Ni 0.97 0.002* 0.94 0.002* 0.053 Co 0.81 0.051 0.66 0.051 0.033 Zn 0.20 0.709 0.04 0.709 0.018 V 0.83 0.041* 0.69 0.041* 0.133 Ba 0.89 0.019* 0.78 0.019* 0.914 Al 0.30 0.570 0.09 0.570 0.012 Fe 0.06 0.914 0.003 0.914 0.001 Cr -0.26 0.623 0.07 0.623 -0.272 Cu 0.03 0.954 0.001 0.954 0.002 Pb 0.40 0.436 0.16 0.436 0.037 Rumtse Ni -0.25 0.632 0.06 0.632 -0.139 Co -0.05 0.926 0.002 0.926 -0.003 Zn 0.14 0.786 0.02 0.786 0.044 V 0.08 0.887 0.006 0.887 0.025 Ba 0.10 0.849 0.01 0.849 0.140

Table 4 Comparison of average metal concentrations in soils along the Manali-Leh Highway with other localities discussed in the text.

Location Al Fe Cr Cu Pb Ni Zn Co Ba V Source Auckland, - - 66 57 1650 87 250 - - - Ward et al. (1977) New Zealand Greater - - - - 201 96 217 - - - Yassoglou et al. Athens, (1987) Greece Cincinnati, - - 67 141 405 53 294 - - - Turer et al. (2001) USA Corpus - - 106 56 329 47 183 - 401 - Turer and Maynard Christi, USA (2003) Kathmandu, - - - 20 23 - 76 - - - Zhang et al. (2012) Nepal Kothi, India 9.85 5.67 142 38 24 68 102 20 498 28 This study Jispa, India 15.71 5.22 88 42 27 55 129 19 605 66 This study Killingsarai, 12.88 3.97 55 33 11 44 39 12 515 34 This study India Rumtse, India 15.68 5.94 126 37 21 73 73 17 476 72 This study

Table 5 Results for Pearson correlation between total organic carbon and distance from the highway.

Asterisks (*) denote significant relationships at α = 0.05.

Site r p

Kothi 0.85 0.033

Jispa -0.45 0.374

Killingsarai -0.70 0.122

Rumtse -0.04 0.933

Table 6 Results for Pearson correlation between of 4 heavy metals (Chromium, Lead, Zinc and

Barium) concentrations and total organic carbon. Asterisks (*) denote significant relationships at α

= 0.05. Double asterisks (**) denote significant relationship at α =0.01.

Site Elements r p Cr 0.46 0.055 Pb 0.17 0.501 Kothi Zn 0.59 0.010** Ba 0.57 0.014* Cr 0.09 0.724 Pb 0.83 0.000** Jispa Zn 0.99 0.000** Ba -0.22 0.372 Cr -0.31 0.211

Pb -0.09 0.731 Killingsarai Zn 0.001 0.997 Ba -0.28 0.256 Cr -0.07 0.799

Pb 0.72 0.001** Rumtse Zn 0.77 0.000** Ba 0.75 0.000**

Table 7 Comparison of traffic volume along the Manali-Leh Highway with other localities discussed

in the text.

Location Age of the road in the Average number of Source year of publication vehicles per day (years) Auckland, New Zealand 17 10000 to 50000 Ward et al. (1977)

Greater Athens, Greece Not Available 15000 to 35000 Yassoglou et al. (1987)

Cincinnati, USA 38 156670 Turer et al. (2001)

Corpus Christi, USA 34 45000 to 48000 Turer and Maynard (2003) Trishuli Highway, Nepal 47 1569 Zhang et al. (2012)

Manali-Leh Highway, 35 137 # This study India # Derived from an approximately 50000 vehicles per year

Location Maximum Minimum Mean SD Local baseline

Kothi 2200 206 732 697 311

Jispa 1249 301 835 276 492

Killingsarai 1000 375 551 174 287

Rumtse 2141 218 636 455 277

Table 9 Concentrations of 16 EPA-prioritized polycyclic aromatic hydrocarbons and soil toxicity in

each sample. PAH analysis was carried out on a composite sample at a distance of 2m from the

highway at each site. ND denotes concentration not detected by GC-MS. All values are reported in

micrograms per kilogram ( µµµg/kg).

PAH compound Abbreviation Nos. of rings Kothi Jispa Killingsarai Rumtse Napthalene Naph 2 57 35 35 1.8 Acenapthylene Ace 3 ND 0.97 ND ND Acenapthene Acen 3 5.3 1.3 1.1 2.1 Anthracene Anth 3 0.81 1.7 0.69 ND Phenanthrene Phen 3 4 8.8 3.4 ND Fluorene Flu 3 0.76 1.2 0.66 ND Fluoranthene Flan 4 7.1 16 1.4 ND Benz(a)anthracene BaA 4 3.5 17 1.3 0.75 Chrysene Chry 4 3.3 24 7.6 ND Pyrene Pyr 4 5.8 20 5 ND Benzo(a)pyrene BaP 5 3.8 36 2.4 ND Benzo(b)fluoranthene BbF 5 6.3 48 3.7 ND Benzo(k)fluoranthene BkF 5 1.8 15 ND ND Dibenz(a,h)anthracene DBA 5 0.99 4.3 2 ND Benzo(g,h,i)perylene BgP 6 3.9 31 8.1 ND Indeno(1,2,3-cd)pyrene IP 6 3.9 33 2.3 ND ΣPAHs 108.26 293.27 74.65 - Neff ratio 1.68 0.20 1.21 - BaPEq 6.50 52.25 5.34 -

Table 10 Correlation matrix showing the relationship between total organic carbon and the 16 EPA-prioritized polycyclic aromatic

hydrocarbons. Asterisks (*) denote significant relationships at α = 0.05. Double asterisks (**) denote significant relationship at α = 0.01. TOC Naph Ace Acen Anth Phen Flu Flan BaA Chry Pyr BaP BbF BkF DbA BgP IP

TOC 1 0.25 0.99* -0.30 0.93 0.94 0.83 0.95* 0.99** 0.97* 0.99* 0.98** 0.99* 0.99** 0.93 0.98* 0.99** * Naph 0.25 1 0.08 0.56 0.56 0.54 0.71 0.45 0.22 0.23 0.36 0.17 0.20 0.18 0.34 0.22 0.18 Ace 0.99 0.08 1 -0.39 0.86 0.87 0.73 0.91 0.99** 0.96* 0.96* 0.99** 0.99* 0.99** 0.90 0.97 0.99** * * Acen - 0.56 -0.40 1 -0.14 -0.15 -0.04 -0.001 -0.26 -0.46 -0.26 -0.34 -0.32 -0.29 - -0.44 -0.33 0.30 0.45 Anth 0.93 0.56 0.86 -0.14 1 1** 0.98* 0.94 0.91 0.93 0.97* 0.90 0.91 0.89 0.95 0.93 0.91 Phen 0.94 0.54 0.87 -0.16 1** 1 0.97* 0.95 0.92 0.94 0.98* 0.91 0.92 0.90 0.95 0.94 0.92 * Flu 0.83 0.71 0.73 -0.04 0.98* 0.97* 1 0.87 0.80 0.85 0.90 0.79 0.80 0.78 0.90 0.84 0.80 Flan 0.95 0.45 0.91 -0.001 0.94 0.95 0.88 1 0.96* 0.88 0.96 0.94 0.94 0.95 0.85 0.90 0.94 BaA 0.98 0.22 0.99* -0.26 0.91 0.92 0.80 0.96* 1 0.95 0.98* 1** 1** 1** 0.90 0.97* 0.98** ** Chry 0.97 0.23 0.96* -0.46 0.93 0.94 0.85 0.88 0.95 1 0.98* 0.97* 0.97* 0.95 0.99 1** 0.97* * * Pyr 0.99 0.36 0.95* -0.26 0.97* 0.98* 0.90 0.96* 0.98* 0.98* 1 0.98* 0.98* 0.97* 0.96 0.98* 0.98* * * BaP 1** 0.17 1** -0.34 0.90 0.91 0.79 0.94 1** 0.97 0.97* 1 1** 1** 0.92 0.98* 1** BbF 1** 0.20 0.99* -0.32 0.91 0.92 0.80 0.94 1** 0.97* 0.98 1** 1 1** 0.92 0.98* 1** * BkF 1** 0.18 1** -0.29 0.89 0.90 0.78 0.95 1** 0.95 0.97* 1** 1** 1 0.89 0.96* 1** DbA 0.93 0.34 0.90 -0.45 0.95 0.95* 0.90 0.85 0.90 0.99* 0.96* 0.92 0.92 0.89 1 0.98* 0.92 BgP 0.98 0.22 0.97* -0.44 -0.93 0.94 0.84 0.90 0.97* 1** 0.98* 0.98* 0.98* 0.96* 0.98 1 0.98* * * IP 1** 0.18 1** -0.33 0.91 0.92 0.80 0.94 1** 0.97* 0.98* 1** 1** 1** 0.92 0.98* 1