Efficient and exact quantum compression

Accepted Manuscript Assessing the level and sources of Polycyclic Aromatic Hydrocarbons (PAHs) in soil and sediments along Jhelum riverine system of lesser Himalayan region of Pakistan Rahat Riaz, Usman Ali, Jun Li, Gan Zhang, Khan Alam, Andrew James Sweetman, Kevin C. Jones, Riffat Naseem Malik PII:

S0045-6535(18)32000-9

DOI:

https://doi.org/10.1016/j.chemosphere.2018.10.139

Reference:

CHEM 22401

To appear in:

ECSN

Received Date: 26 March 2018 Revised Date:

4 September 2018

Accepted Date: 19 October 2018

Please cite this article as: Riaz, R., Ali, U., Li, J., Zhang, G., Alam, K., Sweetman, A.J., Jones, K.C., Malik, R.N., Assessing the level and sources of Polycyclic Aromatic Hydrocarbons (PAHs) in soil and sediments along Jhelum riverine system of lesser Himalayan region of Pakistan, Chemosphere (2018), doi: https://doi.org/10.1016/j.chemosphere.2018.10.139. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Manuscript Number: CHEM52952

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Title: Assessing the level and sources of Polycyclic Aromatic Hydrocarbons (PAHs) in soil and sediments along Jhelum Riverine system of Lesser Himalayan Region of Pakistan Article Type: Research paper

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Section/Category: Environmental Chemistry (including Persistent Organic Pollutants and Dioxins)

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Keywords: PAHs; soil/sediments; PMF; biomass combustion; vehicular emissions; atmospheric transportation Corresponding Author: Miss rahat riaz, Corresponding Author's Institution:

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First Author: rahat riaz Order of Authors: rahat riaz; Usman Ali; Jun Li; Gan Zhang; Khan Alam; Andrew J Sweetman; Kevin C Jones; Riffat N Malik Abstract: Lesser Himalayan region (LHR) is an important mountain ecosystem which supports a wide range of biodiversity of native flora and fauna. Human population in this region is largely dependent upon local sources for their livelihood. Surface soil (n=32) and sediment (n=32) were collected from four different altitudinal ranges of LHR and analyzed for priority Polycyclic Aromatic Hydrocarbons (PAHs) recommended by USEPA. Level, sources and distribution pattern of PAHs were assessed in collected soil and sediments samples. Total PAHs concentration level of PAHs in soil and sediments ranged from 62.79-1080 ng g-1 and 14.54437.43 ng g-1, respectively. Compositional profile of PAHs in both soil and sediment were dominated by low and medium molecular weight PAHs, ranged from 18.02– 402.18 ng g-1 in soil and 0.32-96.34 ng g-1 in sediments. In the context of spatial distribution trend, highest mean concentration of PAHs in soil were recorded in zone D (sites from the rural region) and for sediments the highest concentrations were detected at zone A, which includes dam sites. In all four zones, no altitudinal trend of PAHs in soil and sediments was observed. Source apportionment through receptor modelling by positive matrix factorization (PMF) revealed that local sources such as biomass combustion and vehicular emissions are important sources of PAHs in this region. The prevalence of monsoon atmospheric circulation system in LHR implicated that this region is also influenced by medium and long range atmospheric transportation of PAHs from neighboring countries where potential sources and high level of PAHs have been reported.

ACCEPTED MANUSCRIPT Suggested Reviewers: Alessandra Cincinelli Chemistry, University of Florence [email protected] POPs expert

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Azeem Khalid Environmental Sciences, PMAS Arid Agriculture University, Rawalpindi [email protected] Expert in reviewing wide range of environmental topics

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Athanasios Katsoyiannis Joint Research Centre (JRC), European Commission, Joint Research Centre [email protected] POPs expert

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Luqman Riaz Environmental Sciences, PMAS Arid Agriculture University, Rawalpindi [email protected] Monitoring and LRAT expert Laura Sánchez-García Institute of Environmental Sciences (IUCA), Zaragoza University (Spain) [email protected] Expert in black carbon-POPs relationship

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Zafeer Saqib Environmental Sciences, International Islamic University, Islamabad [email protected] Expert in reviewing environmental studies

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Cover Letter

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March, 2018

Dear Editor,

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Please find attached the manuscript entitled “Assessing the level and sources of Polycyclic Aromatic Hydrocarbons (PAHs) in soil and sediments along Jhelum Riverine system of Lesser Himalayan Region of Pakistan” by Rahat Riaz et al., for submission to Chemosphere. We confirm that the material is original and has not been submitted elsewhere.

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In this study, Lesser Himalayan region (LHR) is an important mountain ecosystem which supports a wide range of biodiversity of native flora and fauna. Human population in this region is largely dependent upon local sources for their livelihood. Surface soil (n=32) and sediment (n=32) were collected from four different altitudinal ranges of LHR and analyzed for priority Polycyclic Aromatic Hydrocarbons (PAHs) recommended by USEPA. Level, sources and distribution pattern of PAHs were assessed in collected soil and sediments samples. Total PAHs concentration level of PAHs in soil and sediments ranged from 62.79-1080 ng g-1 and 14.54-437.43 ng g-1, respectively. Compositional profile of PAHs in both soil and sediment were dominated by low and medium molecular weight PAHs, ranged from 18.02– 402.18 ng g-1 in soil and 0.32-96.34 ng g-1 in sediments. In the context of spatial distribution trend, highest mean concentration of PAHs in soil were recorded in zone D (sites from the rural region) and for sediments the highest concentrations were detected at zone A, which includes dam sites. In all four zones, no altitudinal trend of PAHs in soil and sediments was observed. Source apportionment through receptor modelling by positive matrix factorization (PMF) revealed that local sources such as biomass combustion and vehicular emissions are important sources of PAHs in this region. The prevalence of monsoon atmospheric circulation system in LHR implicated that this region is also influenced by medium and long range atmospheric transportation of PAHs from neighboring countries where potential sources and high level of PAHs have been reported.

Sincerely yours, Rahat Riaz Email: [email protected] Tel. & Fax: +925190643017

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*Highlights (3 to 5 bullet points (maximum 85 characters including spaces per bullet point)

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Polycyclic Aromatic Hydrocarbons (PAHs) were assessed in soil and sediments of the Lesser Himalayan Region (LHR). High concentration of PAHs were observed in urban and sub-urban regions. Biomass combustion and vehicular emissions are important sources of PAHs in LHR.

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Highlights

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Graphical Abstract

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Graphical Abstract

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*Title Page

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Assessing the level and sources of Polycyclic Aromatic Hydrocarbons (PAHs) in soil and sediments along Jhelum Riverine system of Lesser Himalayan Region of Pakistan

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Rahat Riaza, Usman Alia, Jun Lib, Gan Zhangb, Khan Alamc, Andrew James Sweetmand, Kevin C. Jonesd, Riffat Naseem Malika

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*Corresponding Author: Rahat Riaz

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*Address: Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-iAzam University, Islamabad, PO 45320, Pakistan

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Telephone: 00925190643017

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Email: [email protected]

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State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China

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Department of Physics, University of Peshawar, Pakistan

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Centre for Chemicals Management, Lancaster Environment Centre, Lancaster University, 11 Bailrigg, Lancaster LA1 4YQ, UK

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Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-i-Azam 6 University, Islamabad 45320, Pakistan

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*Manuscript (double-spaced and continuously LINE and PAGE numbered) Click here to view linked References

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Abstract

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Lesser Himalayan Region (LHR) is an important mountain ecosystem which supports a

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wide range of biodiversity for native flora and fauna. Human population in this region is largely

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dependent upon local sources for their livelihood. Surface soil (n=32) and sediment (n=32) were

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collected from four different altitudinal ranges of LHR and analyzed for priority Polycyclic

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Aromatic Hydrocarbons (PAHs) recommended by USEPA. Level, sources and distribution

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pattern of PAHs were assessed in soil and sediments samples collected from four altitudinal

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zones in LHR. Total PAHs concentration level of PAHs in soil and sediments ranged from

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62.79-1080 ng g-1 and 14.54-437.43 ng g-1, respectively. Compositional profile of PAHs in both

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soil and sediment were dominated by low and medium molecular weight PAHs, ranged from

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18.02-402.18 ng g-1in soil and 0.32-96.34 ng g-1in sediments. In the context of spatial

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distribution trend, highest mean concentrations of PAHs in soil were recorded in zone D (sites

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from the rural region) and for sediments highest concentrations were detected at zone A, which

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includes dam sites. In all four zones, no altitudinal trend of PAHs in soil and sediments was

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observed. Source apportionment through receptor modelling by positive matrix factorization

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(PMF) revealed that local sources such as biomass combustion and vehicular emissions are

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important sources of PAHs in this region. The prevalence of monsoon atmospheric circulation

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system in LHR implicated that this region is also influenced by medium and long range

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atmospheric transportation of PAHs from neighboring countries where potential sources and

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high level of PAHs has been reported.

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Keywords: Positive matrix factorization; biomass combustion; vehicular emissions;

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monsoon; atmospheric transportation

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1.

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Introduction Polycyclic Aromatic Hydrocarbons (PAHs) are groups of the ubiquitous organic pollutant

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that are semi-volatile, lipophilic, photosensitive and have low water solubility. Naturally,

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hundreds of PAHs are present in the environment, but only sixteen congeners have been

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categorized as Priority Pollutants by United States of Environmental Protection Agency

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(USEPA). This list is based upon their historic significance and presence at high concentrations

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in many environmental matrices. Fate and transport PAHs congeners is dependent upon their

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molecular weight, number of rings and phases. Based on these criterions, congeners of PAHs are

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categorized as low (2-3 rings), medium (4-rings) and high molecular weight (5-6 rings)

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(Tobiszewski and Namieśnik, 2012). Low and medium molecular weight PAHs exist in the

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vapor phase and subjected to atmospheric transportation, while high molecular weight congeners

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are present in both particulate and gaseous phases and subjected to local deposition.

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Furthermore, eight congeners of PAHs are identified as carcinogens and have the tendency to

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bio-accumulate in human body(UNEP, 2003) Owing to their persistence, pervasive presence,

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potential for long range transport and proven carcinogenicity, toxic effects of PAHs on both

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human and ecosystem are well established (Keyte et al., 2013).

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PAHs are produced by both natural (forest fire, volcanic eruption and sedimentary rocks)

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and anthropogenic sources (biomass and fossil fuel combustion). However, the contribution from

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natural sources is negligible as compared to anthropogenic sources. Sources of PAHs are

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categorized as petrogenic and pyrogenic sources (Srogi, 2007). Due to combustion of petrogenic

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or pyrogenic sources, PAHs emit directly into the atmosphere in both gaseous and particulate 5

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phases. By the process of atmospheric precipitation (both wet and dry) these recalcitrant

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compounds deposit in soil (Demircioglu et al., 2011; Westgate and Wania, 2013) which act as a

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primary reservoir for PAHs. Sequestration of hydrophobic chemicals in soil is due to preferential

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sorption of these contaminants in amorphous organic compounds as well as carbonaceous

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geosorbent (commonly known as organic carbon and black carbon). Soil plays a decisive role in

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fate and distribution of organic pollutants by absorption in organic matter and adsorption to black

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carbon. In soil, deposited PAHs will experience multiple soil-air exchange processes depending

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upon environmental conditions and their physicochemical characteristics. As gaseous phase will

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PAHs will be subject to re-volatilization from soil during summer and re-deposit during winter

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season (Wang et al., 2014). While sediments permanently entrapped these chemicals owing to

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lack of soil- air exchange processes and act as an ultimate sink for organic pollutants (Bozlaker et

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al., 2008). In the context of deposition and accumulation of organic pollutants, remote regions

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are areas of particular concern. In remote mountain regions, sources of organic pollutants are

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virtually absent but transportation and enrichment of volatile pollutants such as PAHs are

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facilitated by atmospheric transportation and high organic content in soil and sediments.

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Enrichment of PAHs in these remote regions is also attributed to lipophilic and hydrophobic

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characteristics, due to which PAHs entered into the food chain (Fernández et al., 2005). Remote

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mountain ecosystem covers 27% of the land surface and has 22% of the total world’s population.

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Although these regions are scarcely populated and traditionally considered as pristine regions,

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but geography and certain local scale activities in these regions make them potential sink for

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pollutants (Beniston, 2006). Such as in remote Himalayan mountain ranges, local scale biomass

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burning activities and Indian monsoon circulation system facilitate enrichment of semi-volatile

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PAHs. The Himalayan ranges that stretch along Tibetan Plateau and Indian sub-continent have

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been identified as an important sink for locally produced and atmospherically transported organic

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pollutants (Loewen et al., 2005; Yang et al., 2016). Himalayan rages are one of the important

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mountain ecosystems of the world. Cryospheric regions of Himalaya are buffer zones of

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hydrological seasonality in the Indian subcontinent and glaciated ranges of this region are

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considered as water tower of South Asia, which ensures food and water security of more than

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800 million population (Immerzeel et al., 2010). Enrichment and accumulation of carcinogenic

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pollutants in this region is contact source of threat for the population through bio-accumulation

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(Wang et al., 2012).

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The part of the Himalayan range that span along the northern region of Pakistan and

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stretches along Islamabad, Mansehra, Batagram and Pakistan Administered Azad Kashmir (AJK)

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is known as Lesser Himalayan Range (LHR). LHR is influenced by the Indian monsoon system

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and may receive trans-boundary pollutant load from neighboring regions such as Pakistan, India

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and Bangladesh. Moreover, LHR is also influenced by tourism related activities and extensive

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and intensive biomass burning activities which may act as a potential source of PAHs in this

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region. Pakistan is ranked as the seventh major emitter of PAHs (Zhang and Tao, 2009) and in

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urban regions, vehicular and industrial emissions are identified as important source of PAHs

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(Kamal et al., 2015) while in rural areas (70% of total population) 94% of primary energy needs

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are full filled by biofuel (Colbeck et al., 2011). Similarly, a major part of the population from

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LHR is also dependent upon biomass burning to acquire their energy demands. Dependence on

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biomass burning, local scale activities and favorability of region for trans-boundary atmospheric

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transportation led this region potential hub for PAHs. Although recent studies have been carried

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out to assess the level of POPs (OCPs, PCBs) in LHR. No studies have focused and reported the

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level of PAHs in this region. This study aimed to assess the (i) level and sources of PAHs in soil

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and sediment from LHR and (ii) relationship of PAHs level with altitudinal gradient,

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meteorological factors and carbon content (TOC, BC) from LHR.

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2.

Materials and methods 2.1.

Study Area and Sampling Strategy

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LHR is present in the northern region of Pakistan in the latitude of 33o – 36o ʹN and

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longitude of 73o – 75oʹE. This region spans over an area of 2.3 million ha with a total population

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of four million. The riverine system in LHR is of particular importance as it acts as the catchment

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basin for the Indus waters system. Water system comprised of three major rivers, several

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perennial water tributaries and one water reservoir. Major rivers included Neelum, Jhelum and

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Poonch River and Mangla Dam is only multipurpose water reservoir of this region. The riverine

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system of this region is collectively known as Jhelum River System. This riverine system has

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tremendous topographic variation owing to its altitudinal aspects, with approximate elevation

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ranges between 300-3000 meters. Neelum and Jhelum Rivers enters into the Himalayan from

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India range at Taobat and Chakothi, respectively. Flowing along LHR, both these rivers finally

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drained into water reservoir ‘Mangla Dam’ (Akram et al., 2011; Mughal et al., 2016) This

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reservoir expanding over an area of about 265 km2 with the storage capacity of about5.86-

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7.25km3 (Saleem et al., 2013). By conserving the massive amount of surplus water especially

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during the monsoon period, Mangla Dam fortifying irrigation system of the country as part of

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Indus Basin Project under Indus Waters Treaty 1960. Besides supporting to irrigation system,

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Dam has hydropower generation capacity of about 1000 MW, thus further strengthening the

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economy of the country. . LHR was selected to conduct a study for assessment of the potential

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enrichment of PAHs in soil and sediments. For this purpose, the sampling strategy was designed

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along LHR, and sampling campaign was conducted during the post-monsoon period (Nov-Dec

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2016). Depending upon different land use or extent of anthropogenic influence, four zones were

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selected at different altitudinal ranges along the Neelum-Jhelum river system of LHR. Zone A

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(357-383 masl) is categorized as dam area, zone B as sub-urban (397-733 masl), zone C is

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classified as urban (737-975) and zone D (1351-2324 masl) as a rural region. In total thirty-two

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sites, with eight sites in each zone were selected for detailed soil and sediment sampling. Details

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are given in SI Figure 1 and SI Table 1. At each sampling point, soil (n=32) and sediment

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(n=32) samples were collected at depth of 0-10cm in four composites. Samples were collected by

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using hand trowel, kept in polyethylene bags and transported to Environmental Biology and

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Ecotoxicology Laboratory, Quaid-i-Azam University, Islamabad, Pakistan. After preliminary

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treatment i-e., drying, mixing and sieving, collected samples were stored at -4 ⁰C for further

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analysis.

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2.2.

Sample Extraction and Analysis

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All soil and sediment samples (20g of each sample) were spiked with deuterated PAHs as

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recovery/surrogate standards (acenapthene-D10, phenanthrene-D10, chrysene-D12 and perylene-

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D12) before soxhlet-extraction for 48h with dichloromethane (DCM). The extract was

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concentrated and solvent-exchanged to hexane and purified on 8 mm i.e. alumina/silica column

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packed, from top to bottom, with neutral alumina (3cm, 3% deactivated), silica (3 cm), and

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anhydrous sodium sulfate (1 cm). The column was eluted with 50 ml of DCM/hexane (1:1). The

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extract from the followed cleanup procedure was concentrated to 20-25 µL under a gentle high

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purity nitrogen stream. 10µL of hexamethylbenzene was added as an internal standard in the

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final extract before chromatographic analysis. Sixteen EPA PAHs (∑PAHs16) were analyzed in

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soil and sediment samples in this study. Target analytes included Naphthalene (Naph),

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Acenapthene (Ace), Acenapthylene (Acey), Fluorene (Flu), Phenanthrene (Phe), anthracene

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(Anth), Fluoranthene (Flua), Pyrene (Pyr), Benzo[a]anthracene (BaA), Chrysene (Chr),

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Benzo[b]fluoranthene

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Dibenzo[a,h]anthracene (DahA), Indeno[1,2,3-c,d]pyrene (IcdP) and Benzo[g,h,i]perylene

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(BghiP). All target compounds were analyzed by Agilent gas chromatograph (Agilent GC-7890)

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(BbF),

Benzo[k]fluoranthene

(BkF),

Benzo[a]pyrene

(BaP),

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having a capillary column (DB-5MS, 30 m, 0.25 mm, 0.25 µm) and mass spectrometric detector

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(MSD -Agilent 5975). Extract of the sample (0.5-1 µL) was injected, by using helium as a carrier

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gas, with a temperature of transfer line and the injector was 300°C and 290°C respectively.

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2.3.

Quality Control/Quality Assurance (QA/QC)

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Quality control and quality assurance procedures were strictly followed during the

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sampling process and the analytical procedure. Four filed blank, four transportation blank and

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one procedural blank with every batch of eight samples were analyzed. The insignificant

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difference was observed between analyte concentrations in field, transportation and laboratory

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blanks which depict negligible contamination during sampling, transportation and analysis.

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Average recoveries for deuterated PAHs were 70% ± 11% for soil (72% ± 12 acenapthene-D10,

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70% ± 12 phenanthrene-D10, 70% ± 11 chrysene-D12, 71% ± 10 perylene-D12) and 74 % ±

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12% for sediments (70% ± 11 % acenapthene-D10, 73% ± 13% phenanthrene-D10, 84% ± 10%

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chrysene-D12, 72% ± 14% perylene-D12). The average recoveries hexamethylbenzene were

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80% ± 11% for soil and 83% ± 12% for sediments respectively. The Instrumental Detection

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Limit (IDL) values were calculated by extrapolating the lowest standards and corresponding

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analytes concentration that produce a signal-to-noise ratio (S/N ratio) of 3:1. All target analytes

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in samples and procedural blanks were under IDL. Limit of Quantifications (LOQs) of PAHs in

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soil and sediments were 0.1 ng g-1 0.05 ng g-1 respectively. The Method Detection Limit (MDLs)

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values were the average values and ±3 times the standard deviations of the analytical blanks.

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Reported values were blank corrected. Details are given in supporting information (SI Table 7).

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2.4.

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Source Apportionment of PAHs by PMF

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Positive matrix factorization (PMF) is a source-receptor model that gives a quantitative

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solution for source distribution equations through dimension reduction. In comparison to PCA, 10

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PMF treats the receptor modelling equation as a least squares problem and does not employ

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Eigen-based analyses and provide non-negative constraints solutions (Sofowote et al., 2015). The

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detail descriptions of EPA PMF v5.0 are described in the user guide (Norris et al., 2014). This

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model is based on the following equation:

Equation 1

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Xij is the concentration of jth congeners in an ith sample and Gik is the contribution of a kth

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factor to ith sample, Fkj is a fraction of kth factor from j congener and E is residual between

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measured and modelled Xij by using p principal component. It gives the solution for

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concentration matrix of specie (X) at receptor sites as a product of two matrices, factor

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contribution (G) and factor profile (F) with residual matrix (E). As its name indicates both G and

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F are non-negative or positive matrixes. Moreover, this model gives weightage to an individual

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data point in the matrix and provides an opportunity to define the impact of each data point

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depending upon confidence in the measurement. Such as a data point below the method detection

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limit (MDL) used in the model after adjusting their uncertainty, so that have a low impact over

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entire data set (i.e. data above MDL). The basic purpose of PMF is dimension reduction by

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determining an appropriate number of factors. Q value (Q true and Q robust) is important to

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extract an appropriate number of factor. Q value is the sum of squares of difference original data

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set and modelled values by PMF (Polissar et al., 2001; Bzdusek and Christensen, 2006). For this

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study, total PAHs PMF results were bootstrapped by using 100 runs and default values (R2=0.6

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and seed=random). The optimum number of factors were determined by using Q values (Qrobust

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and Qtheoretical). Three-factor solution, which produced the most stable results and was adopted for

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both sediment and soil data sets.

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3.

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Results and Discussion 11

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3.1.

Level and Spatial Distribution of PAHs

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Total sixteen target PAHs compounds were analyzed, however, Naphthalene (Naph) did

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not satisfy the QA/QC criteria given in this study for both soil and sediment samples. As the

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blank values for Naph were four times higher than the method detection limit, therefore, Naph

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omitted from the further discussion. ∑PAHs15 concentration in surface soil and sediments were

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further discussed in this study.

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3.1.1. Level and Spatial Distribution of PAHs in Sediment

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Descriptive statistics of detected ∑PAHs15 in the sediment of LHR, Pakistan are provided in

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Table 1. Overall in Lesser Himalayan Region (LHR), the concentration of ∑PAHs15 in surface

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sediments ranged from 14.54-437.43 ng g-1 (with mean 492 ng g-1). PAHs concentrations

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detected in LHR from this study were comparable to previously reported concentrations from

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mountain lakes in Europe (Fernandez et al., 1999; Muri et al., 2003; Jiao et al., 2009), Tibetan

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Plateau (Yang et al., 2016), and one to two orders of magnitude lower than sediment

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concentrations reported from lakes in High Tatras (van Drooge et al., 2011) and Himalayan

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region (Choudhary and Routh, 2010), but concentration level measured in this study was higher

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than reported from southern Himalayan lakes (Guzzella et al., 2011)and Arctic region (Klánová

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et al., 2008; Jiao et al., 2009). In LHR, ∑PAHs15 exhibits different spatial distribution pattern in

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all four zones as shown in Figure 1. Highest means concentration was observed at zone C (174.

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51±133.28 ng g-1) followed by zone A (169.12±123.37 ng g-1), zone B (156.14±127.48 ng g-1)

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and zone D (99.37±44.72 ng g-1). Zone C, includes sites along an upper part of Jhelum River and

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categorized as an urban region. This zone includes a capital city (Muzaffarabad; JU3) and its

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peripheries. High concentration of sediment PAHs was observed for site JU3 (357 ng g-1) and

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JU4 (306 ng g-1). Zone A includes all sites in the dam region. Extensive anthropogenic and

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industrial activities around dam region and high sedimentation rate within dam (Saleem et al.,

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2013) may be important factors for environmental contamination in this region. In zone A, high

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sediment PAHs concentration is observed at site D4 (344 ng g-1) and D7 (370 ng g-1) and both

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these sites are discharging points of Jhelum River into Mangla dam. Zone B was categorized as a

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sub-urban region and includes sites along the lower part of the Jhelum River. This zone is

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wedged between the dam area (zone A) and urban region (zone C). Most of the sites in this zone

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are present around junctions of the road network of different cities in LHR and has experienced

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high traffic density (Ali et al., 2018c). The highest concentrations of sediment PAHs were

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observed in zone C at Kohala (JR8; 433 ng g-1), which is the main entrance point in LHR. Zone

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D (altitudinal range of 1351-2324 masl) in LHR differs from other zones in altitudinal,

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topological and demographical aspects and includes sites in Neelum River along the international

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boundary between Pakistan and India. For this study, the lowest concentration of sediment PAHs

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was observed in zone D.

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3.1.2. Level and Spatial Distribution of PAHs in Soil

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In soil, total PAHs15 concentration of 32 sampling sites in four zones range from 62.79 ng

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g-1 with an average concentration of 433 ng g-1 as presented in Table 2. The concentration of

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PAHs in the present study is higher than concentrations reported from mountain soils of the

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Tibetan Plateau (Tao et al., 2011; Wang et al., 2014; He et al., 2015), background soils from

230

Himalaya (Guzzella et al., 2016), Canadian mountains (Choi et al., 2009) and Norway (Nam et

231

al., 2008). Meanwhile, concentration range of PAHs measured from this study is comparable to

232

mean values of mountain soils from Alps, Tatras, Montensy, Pyrenees (Quiroz et al., 2011) UK

233

(Nam et al., 2008), southeast part of Tibetan Plateau (Wang et al., 2009; Yang et al., 2013)

234

southern slope of Changbai Mountain in Northeast China (Zhao et al., 2015), Eastern Europe

235

(Maliszewska-Kordybach et al., 2009) and Chez republic (Holoubek et al., 2009). Spatial

236

distribution of soil PAHs in the study area is shown in Figure 2. Highest mean concentration of

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soil PAHs was observed in zone C (527.88 ± 211.66 ng g-1) followed by zone D (437.09 ±

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300.93 ng g-1), zone B (343.86 ± 379.21 ng g-1) and zone A (428.50 ± 252.90 ng g-1.. In the urban

239

region (zone C) high soil PAHs concentration was observed around the capital and its vicinity

240

i.e. JU2 (799 ng g-1 ) and JU3 (761 ng g-1). For this study, the highest concentration of soil PAHs

241

was observed in N1, N3 & N6 in zone D. In zone B, Kohala site (JR8) has experienced high

242

PAHs concentration (832 ng g-1) and zone A follows a similar pattern as in the case of sediment

243

i.e. high concentration of soil PAHs measured around D7 (10 ng g-1) and D8 (640.25 ng g-1).

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3.2.

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In this study, concentration and level of soil PAHs are higher than sedimentary PAHs

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(Figure 3). The difference in soil and sediment PAHs level is attributed certain factors. Firstly,

247

LHR region is influenced by long and medium range atmospheric transportation of pollutants

248

and high precipitation rate (1592 mm/year). In LHR, high TOC content of soil (6.8-41.3 mg g-1)

249

and high biomass combustion activities due to low temperature (average -2oC) (Ali et al., 2018a)

250

are the important descriptor for high soil PAHs level. Soil acts as an initial recipient of PAHs

251

from sources as well as through wet and dry atmospheric depositions whereas enrichment of

252

pollutants in sediments is facilitated by surface-run off and ‘secondary deposition’ through water

253

(Zhang et al., 2012). The findings from this study are in conformance with recently published

254

data from LHR, where a high concentration of OCPs and PCBs were reported in the soil as

255

compared to sediments (Ali et al., 2018; a,b). Secondly, the difference in soil and sediment PAHs

256

level might be due to the difference of spatial distribution among sampling sites. Such as in zone

257

D, the lowest level of PAHs in sediment (N1, N2, N3, N6) and highest level of PAHs in soil (N1,

258

N3, N6) were observed. In this zone, soil samples from forest region and sediment samples along

259

the Neelum River were collected. The high organic content of forest soil results into high PHAs

260

at these sites due to preferential absorption of PAHs in organic matter (Semple et al., 2013).

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While, a high altitudinal range of zone D (1351-2324 masl) and steep slope of the Neelum River

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results into low sedimentation and low level of contaminants enrichment,

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Anambra River, Nigeria (Obiakor et al., 2014)and Cao-E River, China (Chen and Lu, 2014).

264

Contrary, zone A and C are highly influenced by anthropogenic activities and relatively high

265

level of soil and sediment PAHs was observed as compared to zone B.

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as observed in

In LHR, as discussed in previous sections (3.1.1 and 3.1.2) level and concentration of

267

PAHs in both soil and sediment were in comparable ranges with previously reported studies.

268

However, such comparison is complicated due to a different analytical method used and number

269

of PAHs congeners analyzed (Jiao et al., 2009). It is suggested that comparison should be made

270

among studies in which similar compounds were analyzed and that have comparable

271

environmental conditions. Nevertheless, even such type of comparisons is ambiguous and does

272

not give a true contamination picture. For example, if PAHs level (soil/ sediment) only from

273

remote regions were considered, a general conclusion cannot be drawn on concentration level.

274

Such as in Tenerife Island (Ribes et al., 2003) only three PAHs congeners (Phe, Flua and Pyr)

275

were analyzed in soil and reported concentration was comparable to other studies conducted in

276

remote regions in which sixteen or more than sixteen congeners were analyzed (SI Table 2). A

277

similar situation was observed in sediments PAHs from Himalayan region (SI Table 3). As

278

PAHs level in sediments from Lake Bhimtal (PAHs5 compounds were analyzed) and Naintal

279

(PAHs8 compounds were analyzed) were significantly higher than concentrations reported in

280

sediments from similar Himalayan range (fifteen-sixteen congeners were analyzed). Similarly,

281

PAHs 15 were analyzed in sediments in High Tatras and the level is five to six order of magnitude

282

more than values reported from remote regions in which a similar number of compounds were

283

analyzed (SI Table 3). Generally, it is recommended to consider geographical aspects and extent

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of anthropogenic influence when such comparisons are made as both these factors are unique in

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every study area.

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3.3.

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Compositional Profile of PAHs in Soil and Sediment As mentioned earlier, depending upon the number of benzene rings, PAHs congeners are

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classified as low (2-3rings), medium (4-rings) and high (5-6 rings) molecular weight PAHs

289

(Keyte et al., 2013). In LHR, for both soil and sediment, an overall ∑PAHs15 profile was

290

dominated by low and medium molecular weight PAHs. In sediment samples, 69% of the

291

compositional profile was contributed by three-four rings PAHs and only 30% by five-six rings

292

PAHs (Figure 4a). Similarly, for soil samples, low and medium congeners collectively

293

contribute 66% of PAHs profile and 34% contribution by high molecular weight PAHs.

294

Observed trend of PAHs compositional profile in sediment samples for zone A and D was 3-

295

ring>4-ring>5-ring >6-ring, while zone B and D have a similar compositional profile; 4-ring>3-

296

ring>5-ring>6-ring. Same as in the case of sediments, three-four rings dominate in all four zones

297

and exhibits similar profile trend, i.e. 4-ring>3-ring>5ring>6-ring (Figure 4b). In both soil and

298

sediments, all individual sites follow the same composition profile trend as observed in their

299

respective zones (SI Figure 2). The dominance of compositional profile by low and medium

300

molecular weight PAHs from this study is in accordance with the profile is observed in remote

301

regions. Such as PAHs profile previously observed in sediment and soil from remote Himalayan

302

lakes (Guzzella et al., 2011), ice samples in central Himalayas (ping Wang et al., 2008), water

303

and benthic macro-invertebrates in alpine stream of New Zealand (Shahpoury et al., 2014) Alps,

304

Pyrenees (Vilanova et al., 2001) and Changbai Mountain’s surface soil (Zhao et al., 2015).

305

Prevalence of three-four rings PAHs in environmental matrices of the remote region may be

306

attributed to the presence of local pyrogenic sources (low-temperature combustion) such as

307

biomass and kerosene combustion (Tobiszewski and Namieśnik, 2012). It may also reflect the

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condensation of atmospherically transported PAHs as owing to volatility low and medium

309

molecular weight PAHs easily transported and condensed in remote regions such as in Tibetan

310

(Yang et al., 2013a; 2016).

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3.4.

Source resolution of PAHs by PMF

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For qualitative analysis of source apportionment of PAHs in soil and sediment samples

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from LHR, PMF analyses were conducted. This model was applied by using 15 PAHs from 32

314

sites for both soils (15×32) and sediments (15×32). For understanding the variability of data sets

315

(soil and sediments), the model was run for 20 times for each data set; by starting from different

316

initial seed number (1-20) and each time number of factors varied. The Qrobust value (soil; 280 &

317

sediment; 257) was closest to Qtheoretical value (339 for soil and sediment) for three factors; the

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eighth run for soil and fourteenth run for sediment was chosen for having lowest Qtrue value (soil;

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255 & sediment; 235). Three factors solution provided a good fit for both sediment (e.g., R2

320

ranged from 0.79 (Flu) to 0.95 (IcdP)) and soil (R2 0.83 (Ace)-0.96 (BaA)) and were adopted for

321

this study. These factors were explained by the percentages of fifteen congeners based on PMF.

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3.4.1. Sources in Sediment

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Factor profile and contribution of measured fifteen congeners of PAHs in sediments are

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shown in Figure 5 (a,b,c). Factor 1 explains 29.42% of the total factors contribution and this

325

factor was characterized by both low (3-rings) and high molecular weight PAHs (5-6 rings).

326

According to percentage variation, factor 1 accounted for more than 70% of these compounds

327

(Figure 5d). Acey, Ace and Anth are signatures of biomass combustion (Parker et al., 2012) and

328

Chr, BkF, IcdP, BghiP are related to diesel and gasoline-related vehicular emissions of PAHs

329

(Luo et al., 2008; Nguyen et al., 2014). According to literature, factor 1 might represent

330

miscellaneous sources of PAHs including biomass combustion and vehicular emissions (diesel+

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gasoline). Factor 2 is dominated majorly by five-six rings such as BbF, BkF, BaP, DahA. This

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factor explains 75% contribution of BbF and more than 40 % contribution by BkF, BaP and IcdP

333

as shown in Figure 5 (d). These congeners are indicator of gasoline emissions (Wang et al.,

334

2009). Thus, factor 2 with 38.27% of total contribution might represent gasoline emissions as a

335

major source of PAHs. Factor 3 is predominated by three-four rings PAHs and explains 32.30%

336

of total variability. This factor dominated by Flu, Flua, Pyr, BaA and Chr. This factor is the main

337

contributor of Chr (85%) followed by Flua, Pyr and BaA with approximately 60% contribution

338

explained by each congener. These congeners are correlated with coal burning and biomass

339

combustion (Guzzella et al., 2016). Thus factor represents biomass combustion as a source of

340

PAHs.

341

3.4.2. Sources in Soil

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Three factors resolved by PMF for soil samples are shown in Figure 6 (a,b,c). Factor 1

343

explains 24.54% of total PAHs contribution. This factor explained more than 80% contribution

344

from IcdP, about 70% from Phe and more than 60% contribution from BkF and BaP (Figure 6

345

d). According to literature, these compounds are the indicator of coal burning (Phe) and gasoline-

346

related vehicular emissions (BkF, BaP, IcdP) (Cao et al., 2011; Yang et al., 2013). Factor 1 was

347

identified as source profile of PAHs from coke and gasoline emissions. Factor 2 explained

348

21.79% of variability and was dominated by Pyr, BaA, Chr, BbF, BkF and DiB. According to

349

percentage variation, factor 2 explained more than 50% variability for Pyr, BaA, BbF and DiB.

350

BaA, Chr and BbF are indicators of coal emissions while Pyr, DiB, BkF and BbF signified

351

gasoline engine emissions as a major source of PAHs (Mu et al., 2013; Yuan et al., 2015; Yang

352

et al., 2016). Factor 3 shows a mixed profile, co-dominated by both three and four rings PAHs.

353

This factor explained 53.72% of total PAHs and explained more than 50% total variability of

354

Flu, Flua, BghiP and Ace. These low to medium molecular weight PAHs are correlated with low

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temperature pyrolysis such as coal and biomass (wood and grass) combustion (Quiroz et al.,

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2010; He et al., 2015). BghiP is only high molecular weight PAHs in this factor and this

357

congener indicate vehicular emissions for PAHs profile. Similar PAHs congener profile and

358

contribution was observed in selected zones of the study area in sediments (SI Figure 3) and soil

359

(SI Figure 4).

360

3.5.

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Implications for Source

To summarize the result from PMF, it is concluded that in sediments and soils of LHR,

362

biomass combustion (wood, grass and coal) and vehicular emissions were major sources of

363

PAHs. Biomass combustion contributing 56.7% of global PAHs production, and Pakistan is a

364

seventh major emitter of PAHs (Zhang and Tao, 2009). Biomass burning, generally in the whole

365

country and particularly in the rural and mountainous region is a major activity that is practiced

366

to meet energy demands (Butt et al., 2013). In the Lesser Himalayan region, wood and coal

367

burning is a major activity to meet energy demands, not only for cooking but also for space

368

heating, as average temperature of this region is below freezing point in the winter season (mean

369

temperature, 2oC in winter season) (Ahmad et al., 2012). LHR is characterized as a scarcely

370

populated mountainous region with temperate forest ecosystem. Similar to other developing

371

regions, biomass burning is the primary activity in practice to meet energy demands of 88% of

372

the total population in this region (PND-AJK, 2014). Total dependence of major part of the

373

population of this region is on biomass burning which not only results into massive deforestation

374

(16% of forest cover as compared 47% in the 1950s) (Mir, 2014) but also acts as local source of

375

pollution in this pristine and remote region. Vehicular emissions are also important sources of

376

PAHs in this whole region. Similar to other altitudinal mountainous ranges such as Alps (Bogdal

377

et al., 2011), Himalaya (Guzzella et al., 2016) and Tibet Plateau (Zhao et al., 2015) this region is

378

also experiencing the dramatic increase in tourism-related developmental activities. The major

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focus is progressive tourism facilities including roads, transportation and accommodations under

380

tourism promotion project that led to an influx of average 400,000 tourists per year (ERRA,

381

2012). Additionally, certain mega ventures such as Neelum-Jehlum hydropower project along

382

zone B, C (Jhelum River) and Zone D (Neelum River) are the important contributing source of

383

high PAHs budget in this region. To summarize the results, biomass combustion and vehicular

384

emissions are very dominant and prominent sources for PAHs in LHR. Due to the prevalence of

385

local sources such as biomass combustion and vehicular emissions, it is observed that level of

386

PAHs (from this study) is hundred times more than level of OCPs and PCBs in parallel

387

conducted studies (Ali et al., 2018; a,b). A similar source of PAHs has been identified through

388

qualitative analysis by diagnostic molecular ratios of Flua/(Flua+Pyr) and IcdP/(IcdP+BghiP) (SI

389

Figure 5). Sources of PAHs in soil and sediments were qualitatively assessed by PCA-MLR

390

(Principal Component Analysis-Multiple liner Regression). PCA-MLR is receptor model widely

391

used for source apportionment. Method is given in SI (text SI1). According to results, for total

392

source contribution in sediments, biomass- coal combustion, gasoline and vehicular emissions

393

contributes 37.28%, 25.4% and 37% respectively (Table SI 5). While in the soil, coke and

394

gasoline are identified as major sources (84% contribution) followed by coal and biomass

395

burning (13.46%) (Table SI 6).

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In addition to tourism, high traffic density and local activities, intra and trans-boundary

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atmospheric transportation are also important sources of semi-volatile PAHs. Air is an important

398

vector for transportation of PAHs to remote areas such as Tibetans Plateau (Meehl et al., 2008;

399

Xu et al., 2009), Himalayan range (Wang et al., 2006; ping Wang et al., 2008) and polar region.

400

Wet and dry precipitation scavenge these compounds from air and enrich into soil and sediments,

401

which are considered as ultimate sinks of environmental contaminants (Jonker and Smedes,

402

2000; Keyte et al., 2013). Owing to unique ecology, meteorology and topography, Himalayan 20

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ranges are subject to the atmospheric transportation of pollutants by Indian monsoon, local and

404

regional wind circulation systems (Loewen et al., 2005; Sheng et al., 2013). LHR is also

405

favorable for trans-boundary as well as atmospheric transportation of PAHs within the country,

406

where potential sources and high concentrations have been reported (Smith et al., 1995; Khan et

407

al., 2008; Colbeck et al., 2011; ud Din et al., 2013; Kamal et al., 2014; Hamid et al., 2018). As

408

mentioned earlier, in LHR PAHs profile was dominated by three and four rings. These are highly

409

volatile congeners and can easily be subjected to atmospheric transportation (Wang et al., 2014;

410

Zhao et al., 2015; Guzzella et al., 2016). It has been already observed that LHR is susceptible for

411

atmospheric transportation of volatile organic pollutants such as OCPs and PCBs (Ali et al.,

412

2018b). Similarly atmospheric transportation might also be a secondary source of dominated

413

lower and medium molecular weight of PAHs in this region. As LHR is under influence of

414

medium and long range atmospheric transportation from neighboring countries (SI Figure 6)

415

such as China and India which are considered as major emitter of PAHs (Zhang and Tao, 2009).

416

3.6.

417

3.6.1. Elevation and Precipitation

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Effect of other factors

Altitudinal aspect is an important factor that influences the distribution of volatile organic

419

pollutants in soil and sediments of remote mountains (Wang et al., 2006; Quiroz et al., 2010).

420

However, in this study, for both soil and sediments statistically non-significant relation was

421

observed between PAHs distribution along the altitudinal gradient (SI Table 4). This deviation

422

from the altitudinal gradient in the study area can be explained by two factors. First, generally, in

423

remote regions, altitudinal enrichment of PAHs is observed when sampling sites are along

424

altitudinal transect (Guzzella et al., 2011; Luo et al., 2016), while multitudinal range of sampling

425

sites in mountain regions also results into deviance from altitudinal trend (Weiss et al., 2000;

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Kallenborn, 2006). Secondly, uneven and widely disperse sources in mountainous regions are

427

also a very important factor for non-conformity of altitudinal enrichment as observed by (Daly

428

and Wania, 2005; Wang et al., 2014). In this study, sampling sites were not arranged along the

429

altitudinal transect and as discussed in the previous section, sources of PAHs were widely

430

scattered in the Lesser Himalayan valley. In this study, a positive correlation was found between

431

PAHs in soil and annual average precipitation (R2= 0.963, P<0.05). The Low temperature of

432

LHR (average= 110C) and average rainfall of 100–130 mm in north and 70-90 mm in the south,

433

coupled with snow results into the entrapment of volatile PAHs into soil compartment. As wet

434

deposition (rain and snow) is defined as an efficient mechanism for scavenging atmospheric

435

PAHs in soil (Demircioglu et al., 2011; Keyte et al., 2013; Westgate and Wania, 2013).

436

3.6.2. Role of TOC and BC

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BC and TOC values for this study were used from a previously published paper of this

438

series (Ali et al., 2018a; Ali et al., 2018c). In sediment, BC and TOC ranged between 0.3-43.5

439

and 1.7-65.4 mg g-1, respectively and according to BC/TC ratio (0.008-2.58), biomass

440

combustion is identified as a major source for BC in sediments. Normalization of PAHs data to

441

BC and TOC exhibits statistically significant correlation for BC (r2=0.82, p=0.05) as compared

442

to TOC (Table 3). Important role of BC for PAHs distribution as compared to TOC is more

443

evident in sub-data set, as strong relation is observed in zone A (r2=0.81, p=0.05), C (r2=0.88,

444

p=0.01) and D (r2=0.48, p=0.01). Preferential sorption of PAHs to BC as compare to TOC could

445

be explained by co-emission of PAHs and BC (Sánchez-García et al., 2010). As it has been

446

confirmed from that biomass combustion is the major source of PAHs (from this study) and BC

447

in LHR. Co-emission of PAHs and BC, hydrophobicity and planarity of PAHs congeners, highly

448

aromatic and nonporous structure (occlusion sites) of BC result into higher sorption and low

449

desorption of PAHs into BC (Jonker and Smedes, 2000; Koelmans et al., 2006). Low

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concentration of TOC (1.7−65.4 mg/g) is an important descriptor for a non-significant relation

451

between TOC and PAHs as was observed in subalpine lakes (Lake Thun, Switzerland) and

452

proglacial lake (Lake Oberaar, Switzerland) (Bogdal et al., 2011). Moreover, vulnerability of

453

TOC for bio-degradation as compared to BC (Semple et al., 2013)slight alkaline nature of

454

sediments (pH=7.7) led to higher sorption of PAHs into BC as compare to TOC as sorption

455

capacity of organic matter decreased with higher pH due to deprotonation (Bucheli et al., 2004).

456

In soil, a slight different behavior of PAHs with BC and TOC was observed (Table 3).

457

Statistically, no correlation was found for five-six rings PAHs, while weak positive correlation

458

was found with three-four rings PAHs for both TOC and BC (Table 3). High molecular weight

459

PAHs (5-6 rings) exist in atmospheric particulate phase, these compounds are influenced by wet

460

deposition and undergoes bio-degradation. Contrary, 3-4 rings are present in the gaseous phase

461

and subjected to multiple air-soil exchange processes. These low-medium molecular weight

462

congeners are volatile and overtime associated in soil with high organic content as compare to

463

high molecular weight compounds (Brändli et al., 2008; Nam et al., 2008). Loss of correlation

464

with 5-6 rings PAHs can also be explained by analytical uncertainties associated with the CTO-

465

375 method, which involves the presence of a considerable fraction of BC which is not resistant

466

to this method i.e., charring effect. BC sorption is an adsorption process while CTO-375 detect

467

BC by mass not by surface area (Shrestha et al., 2010; Bogdal et al., 2011). Low BC/TOC ratio

468

also mask the sorption capacity of BC due to natural attenuation (Agarwal and Bucheli, 2011).

469

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Conclusions

In this study, level of PAHs was assessed in surface soil and sediments from the lesser

471

Himalayan region of Pakistan. The study reported highest levels of PAHs in urban and sub-urban

472

regions (zone A and C) that are highly influenced by anthropogenic activities. Source

473

apportionment through receptor model revealed that biomass combustion, vehicular emissions 23

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(diesel and gasoline), tourist related activities and local scale developmental projects are

475

important sources of PAHs in this region. The dominance of PAHs profile by low molecular

476

weight congeners suggested that LHR is susceptible for medium and long range atmospheric

477

transportation of PAHs from neighboring regions through the monsoon circulation system. In

478

addition, BC and TOC influence the distribution of PAHs in soil and sediment of this region. It is

479

suggested to investigate the enrichment of PAHs in in the aquatic and terrestrial ecosystem of

480

LHR, which is an important ecosystem to maintain biodiversity.

481

Acknowledgements:

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This research was supported by the Higher Education Commission, Pakistan under National Research Program for Universities (Project # NRPU-4730). References:

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Agarwal, T., Bucheli, T.D., 2011. Is black carbon a better predictor of polycyclic aromatic hydrocarbon distribution in soils than total organic carbon? Environmental pollution 159, 64-70. Ahmad, Z., Hafeez, M., Ahmad, I., 2012. Hydrology of mountainous areas in the upper Indus Basin, Northern Pakistan with the perspective of climate change. Environmental monitoring and assessment 184, 5255-5274. Akram, M., Iqbal, A., Husaini, S., Malik, F., 2011. Determination of boron contents in water samples collected from the Neelum valley, Azad Kashmir, Pakistan. Biological trace element research 139, 287-295. Ali et al., 2018; a,b. Ali, U., Riaz, R., Sweetman, A.J., Jones, K.C., Li, J., Zhang, G., Malik, R.N., 2018a. Role of black carbon in soil distribution of organochlorines in Lesser Himalayan Region of Pakistan. Environmental Pollution 236, 971-982. Ali, U., Sweetman, A.J., Jones, K.C., Malik, R.N., 2018b. Higher atmospheric levels and contribution of black carbon in soil-air partitioning of organochlorines in Lesser Himalaya. Chemosphere 191, 787-798. Ali, U., Sweetman, A.J., Riaz, R., Li, J., Zhang, G., Jones, K.C., Malik, R.N., 2018c. Sedimentary black carbon and organochlorines in Lesser Himalayan Region of Pakistan: Relationship along the altitude. Science of The Total Environment 621, 1568-1580. Beniston, M., 2006. Mountain weather and climate: a general overview and a focus on climatic change in the Alps. Hydrobiologia 562, 3-16. Bogdal, C., Bucheli, T.D., Agarwal, T., Anselmetti, F.S., Blum, F., Hungerbühler, K., Kohler, M., Schmid, P., Scheringer, M., Sobek, A., 2011. Contrasting temporal trends and relationships of total organic carbon, black carbon, and polycyclic aromatic hydrocarbons in rural low-altitude and remote high-altitude lakes. Journal of environmental monitoring 13, 1316-1326.

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Figure 1: Distribution of PAHs congeners in sediment from four different altitudinal zones of LHR

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Figure 2: Distribution of PAHs congeners in soil from four different altitudinal zones of LHR

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Figure 3: Spatial distribution of overall PAHs in the LHR in soil and sediment samples

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Figure 4: Compositional profile of PAHs in sediment (a) and soil (b) in study area (LHR) and sub-groups (zones)

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Figure 5: Estimated source profile for PAHs in sediment through factor analysis by PMF (a,b,c) and source contribution percentages from three PMF estimated factors to the 15 PAHs in LHR (d)

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Figure 6: Estimated source profile for PAHs in soil through factor analysis by PMF (a,b,c) and source contribution percentages from three PMF estimated factors to the 15 PAHs in LHR (d)

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Figure 1: Distribution of PAHs congeners in sediment from four different altitudinal zones of LHR

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Figure 2: Distribution of PAHs congeners in soil from four different altitudinal zones of LHR

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Figure 3: Spatial distribution of overall PAHs in the LHR in soil and sediment samples

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Figure 4: Compositional profile of PAHs in sediment (a) and soil (b) in study area (LHR) and sub-groups (zones)

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Figure 5: Estimated source profile for PAHs in sediment through factor analysis by PMF (a,b,c) and source contribution percentages from three PMF estimated factors to the 15 PAHs in LHR (d)

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Figure 6: Estimated source profile for PAHs in soil through factor analysis by PMF (a,b,c) and source contribution percentages from three PMF estimated factors to the 15 PAHs in LHR (d)

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Table 1: Concentration (ng/g dw) of PAHs in sediment of LHR, Pakistan

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Table 2: Concentration (ng/g dw) of PAHs in soil of LHR, Pakistan

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Table 3: Correlation analysis of TOC, BC and normalized PAHs data

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Zone ZoneAA

Zone ZoneBB

Mean±SD Mean±SD

Range Range

Mean±SD Mean±SD

Range Range

Mean±SD Mean±SD

Acey Acey Ace Ace Flu Flu Phe Phe Anth Anth Flua Flua Pyr Pyr BaA BaA

0.26-23.41 0.02-41.66 0.40-25.72 0.02-35.41 1.17-53.48 0.11-43.18 2.32-218.69 0.49-110.80 0.08-72.13 0.01-25.34 0.34-126.19 0.82-175.35 0.64-125.59 0.31-33.29 2.61-126.62 0.22-36.51

4.68±6.01 5.52±9.28 6.61±6.01 5.22±8.24 21.09±0.01 10.2±9.02 64.62±6.01 23.2±26.98 8.85±8.01 5.52±6.81 49.44±4.01 13.2±10.18 38.98±9.01 13.2±10.10 39.02±0.01 13.2±14.34

0.26-5.69 5.50-20.52 2.91-10.00 4.49-22.42 9.16-24.13 64.61-24.33 2.32-164.48 55.59-48.13 1.49-72.13 61.69-21.85 10.76-76.50 45.41-28.21 0.64-70.77 24.21-25.20 2.84-89.07 32.36-22.11

1.84±1.89 7.73±8.81 5.16±2.48 7.85±8.93 14.09±4.82 11.07±7.54 53.65±56.03 24.43±15.76 12.36±24.33 8.52±8.22 32.76±27.62 16.39±7.65 25.23±28.31 14.49±8.17 23.20±29.98 10.71±7.73

0.67-23.41 .18-41.66 0.40-20.39 .80-35.41 1.17-46.43 3.25-43.18 7.96-172.70 3.24-56.33 0.99-28.41 1.78-25.34 0.34-114.43 .31-29.40 5.84-87.35 .55-28.76 2.61-96.41 3.42-30.51

7.35±9.00 6.40±14.28 8.63±8.44 6.41±11.80 21.31±16.27 12.55±13.44 50.89±53.78 15.89±18.87 10.18±11.07 6.17±7.83 53.14±44.27 13.84±9.96 41.81±29.16 15.41±10.38 39.34±34.33 14.83±7.64

Chr

0.15-71.99

12.2±12.79

2.23-24.24

10.96±8.89

.64-65.49

BbF

0.00-65.49

9.32±9.19

02.08-31.09

11.80±12.08

.16-23.41

BkF

0.91-132.51

6.22±7.16

7.73-22.69

8.06±8.80

BaP

0.09-31.09

7.52±8.79

21.21-23.58

9.41±9.22

IcdP

0.03-22.69

4.12±6.18

3.37-18.99

6.87±7.71

DahA

0.20-30.02

7.72±8.57

81.87-26.20

10.33±9.99

Bghip 3-ring

0.12-25.21

10.2±12.12

3.33-20.66

10.47±7.65

0.48-96.34

50.2±45.85

818.83-136.83

59.60±41.93

4-ring

0.32-26.20

53.2±33.41

212.21-98.98

52.56±31.71

5-ring

0.22-45.79

27.2±28.75

47.41-96.34

6-ring

1.52-52.86

18.2±17.44

22.25-46.87

PAHs

14.54-437.43

492±111.76

144.11-370.78

Range Range

0.56-21.52 0.02-0.51 0.63-25.72 0.03-0.05 1.83-32.23 0.11-1.70 10.95-173.77 0.49-4.80 0.08-21.49 0.01-0.65 11.14-95.56 0.31-3.29 1.06-112.93 0.22-2.51 15.74-80.63 0.15-1.04

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Zone CC Zone

Mean±SD Mean±SD

5.44±6.80 3.83±6.81 7.60±8.04 4.47±7.38 19.42±9.46 11.22±8.82 98.73±66.37 40.97±43.87 7.76±6.50 5.25±7.07 54.46±34.05 17.34±12.39 45.45±38.09 19.67±11.52 43.77±25.93 13.63±9.75

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Table 1: Concentration (ng/g dw) of PAHs in sediment of LHR, Pakistan 23 Zone D D Zone Range Range

0.30-11.15 4.11±3.26 0.06-19.03 4.36±6.49 25 0.78-17.62 5.06±6.23 0.02-6.84 2.09±2.39 26 3.74-53.48 29.55±18.53 0.25-16.32 8.01±5.71 3.14-218.69 55.22±71.89 2.04-38.94 12.71±12.06 27 1.48-11.17 5.10±3.81 0.09-6.94 2.40±2.19 28 0.88-126.19 57.39±46.75 29 0.51-28.93 8.05±9.39 2.06-125.59 43.41±38.12 30 0.65-12.28 5.23±4.23 10.83-126.62 49.76±40.73 31 0.35-71.99 15.99±26.06

9.12±8.43

0.00-20.42

9.47±8.31

7.57±7.94

0.09-0.19

10.20±10.74

0.35-17.05

7.94±6.00

.81-22.58

8.11±8.91

0.07-0.65

4.70±6.72

0.03-10.20

4.30±3.15

.48-30.02

8.39±10.23

0.20-2.21

8.62±11.14

0.20-5.87

3.57±1.98

.47-12.72

2.54±4.14

0.12-1.21

5.05±8.47

0.12-5.85

2.06±1.83 36

1.36-25.84

9.46±10.21

0.73-7.26

7.57±8.94

0.32-8.31

3.49±3.09

.22-27.01

9.37±11.13

0.34-3.65

12.86±15.29

0.33-45.79

9.70±15.03

14.53-175.35

47.42±54.43

0.82-8.12

65.75±57.98

2.46-66.46

29.57±18.85

15.44-132.51

63.26±36.40

0.91-9.26

59.76±32.19

02.33-109.09

38.74±34.25

36.15±37.37

2.22-76.72

26.62±28.27

0.48-4.93

28.57±34.28

0.71-33.97

17.88±9.83

20.80±16.59

1.69-52.86

18.84±21.22

1.52-46.65

20.43±19.10

01.67-46.11

13.19±14.62

169.12±123.37

60.32-437.43

156.14±127.48

14.54-357.43

174.51±133.28

047.44-164.73

99.37±44.72

TE D

0.01-0.50

EP

24

Mean±SD Mean±SD

19.18±20.70

AC C

22

32 33 34 35

Table 2: Concentr ation (ng/g dw) of PAHs in soil of LHR, Pakistan

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0.08-113.47

44.26±2.01

0.15-89.58

34.78±42.03

9.51-98.00

42.04±32.32

0.08-113.47

59.01±37.35

17.55-89.46

41.21±25.32 37

BbF

0.75-106.44

37.20±2.01

0.75-106.44

25.68±38.31

4.58-69.04

40.10±24.10

3.72-96.27

40.91±32.42

10.36-95.48

42.12±32.61

BkF

0.10-94.88

17.50±5.01

0.47-57.07

9.31±19.61

0.10-49.73

16.67±16.63

0.81-57.07

17.00±19.73

0.17-94.88

27.03±33.12

BaP

0.04-152.48

36.06±0.01

1.45-116.50

27.44±41.33

0.04-55.32

24.29±24.78

0.63-84.60

32.18±29.50

9.75-152.48

60.34±51.89 39

IcdP

0.54-167.79

35.56±5.01

0.94-167.79

38.32±60.02

0.54-81.19

31.54±32.74

1.49-109.04

39.84±41.34

1.11-156.14

32.55±51.31

DahA

-0.71-56.78

6.97±9.01

-0.71-7.92

3.08±3.10

1.84-56.78

12.59±19.02

1.08-21.32

7.03±6.43

1.39-13.00

Bghip

0.14-176.79

32.23±2.01

0.14-176.79

35.97±66.49

1.20-101.66

28.62±34.00

1.57-129.46

49.29±48.38

1.18-59.88

3-rings

20.01-284.32

105.86±8.01

20.26-211.42

87.09±69.90

20.01-237.45

98.36±68.13

36.43-227.42

138.94±78.06

33.38-284.32

4-rings

18.02-402.18

171.69±6.01

18.02-324.81

115.96±122.47

25.63-396.18

176.33±133.46

5-rings

4.59-454.41

126.33±3.01

4.59-401.65

100.76±149.76

12.52-207.04

112.60±71.32

6-rings

1.59-183.26

39.21±2.01

1.59-183.26

39.05±68.81

4.81-114.37

41.21±43.28

PAHs

62.79-1028.76

443.09±0.01

62.79-1028.76

342.86±379.21

69.82-832.21

49 50 51

SC 54.30-320.72

202.69±98.88

89.55-402.18

30.46-206.14

129.93±73.22

24.90-454.41

6.13-133.29

56.32±48.69

4.00-72.88

156.92-779.84

527.88±211.66

177.80-897.82

M AN U 428.50±252.90

PAHs 0.389 0.594 0.489 0.498 0.305

TE D

EP

Zone A Zone B Zone C Zone D LHR

AC C

Zone A Zone B Zone C Zone D LHR

TOC normalized correlation for sediment 3-ring 4-ring 5-ring 6-ring 0.421 0.416 0.342 0.364 0.598 0.577 0.607 0.594 0.428 0.613 0.280 0.392 0.467 0.481 0.404 0.716* 0.291 0.321 0.257 0.306 BC normalized correlation for sediment 0.757* 0.813* 0.756* 0.828* 0.396 0.110 0.037 0.828* 0.261 0.593 0.111 0.425 0.564 0.885** 0.764* 0.802* 0.399* 0.490** 0.430* 0.420*

RI PT

Chr

0.811* 0.888** 0.628 0.485** 0.821*

38

40 41 15.05±21.18 42 99.03±79.58 43 191.78±121.71 44 162.04±147.87 45 20.24±23.71 46 473.09±300.93 47 48 5.19±4.09

BC normalized correlation for soil 3-ring 4-ring 5-ring 6-ring 0.489 0.424 0.432 0.459 0.042 0.134 0.393 0.782* 0.329 0.598 0.147 0.757* 0.553 0.663 0.397 0.624 0.279 0.296 0.419* 0.374* TOC normalized correlation for soil 0.228 0.496 0.313 0.101 0.417 0.052 0.708* 0.855** 0.574 0.017 0.080 0.776* 0.012 0.052 0.568 0.009 0.223 0.071 0.426* 0.494**

Table 3: Correlati on analysis of TOC, BC and normaliz ed PAHs data

PAHs 0.447 0.511 0.721* 0.628 0.376* 0.382 0.779* 0.617 0.263 0.451**

*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

40

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EP

TE D

M AN U

SC

RI PT

Supplementary Material Click here to download Supplementary Material: Supporting Information.doc

AC C

1 2