Insight into occurrence, profile and spatial distribution of organochlorine pesticides in soils of solid waste dumping sites of Pakistan: Influence of soil properties and implications for environmental fate

Ecotoxicology and Environmental Safety 170 (2019) 195–204

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Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv

Insight into occurrence, profile and spatial distribution of organochlorine pesticides in soils of solid waste dumping sites of Pakistan: Influence of soil properties and implications for environmental fate

T

Marriya Sultana, Sidra Waheeda, Usman Alia, Andrew James Sweetmanb, Kevin C. Jonesb, ⁎ Riffat Naseem Malika, a b

Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan Centre for Chemicals Management, Lancaster Environment Centre, Lancaster University, 12 Bailrigg, Lancaster LA1 4YQ, UK

ARTICLE INFO

ABSTRACT

Keywords: Waste dumping POPs OCPs Black carbon Total organic carbon δ13C stable isotope

Waste dumping sites are considered as significant disposal pathway for waste contaminants including pesticides. In the present study OCPs were analyzed in soils of waste dumping sites of Pakistan. The mean concentrations of OCPs were in the order: ∑DDTs > ∑HCHs > ∑Endosulfan > ∑HCB > Heptachlor. Order of overall ∑OCPs contamination with respect to location was Lahore > Sukkur > Karachi > Kamoki > Faisalabad > Hyderabad > Losar > Gujrat > Peshawar. Distribution of OCPs in solid waste dumping site was mainly influenced by textural classes, input history and pollution source. Soil texture was the dominant factor for retention of OCPs, whereas TOC and black carbon has not significantly impacted the concentrations of OCPs. Diagnostic ratios indicated the historical input, anaerobic degradation pathway and use of technical mixtures of DDTs in majority of waste dumping sites whereas for HCHs recent as well as past usage of technical mixture was prevalent in most of the areas. Regression analysis revealed a weak positive correlation of OCPs with socioeconomic indices (HDI, Population, waste generation) which is linked with history of use of these contaminants in the respective areas. Forecasted waste generation quantity for the year 2026 showed that waste generation amount will get doubled by the year 2026 suggesting the need properly designed waste management system.

1. Introduction

soil, vegetation and ultimately human health. The main sources of pesticides in dumping sites are packing material, house, garden and agriculture waste contaminated with pesticides during spray for pesticide or vector control drives and insecticides usage at dumping sites for public health and hygienic purpose (Minh et al., 2006). In Pakistan the general practice of disposing off empty containers or packaging of pesticide chemical is by either placing in municipality garbage bins, burying in soil or burning them on site (Khooharo et al., 2008). Pesticides waste enters the solid waste streams from industries, commercial areas, agriculture and household waste which contain OCPs. Although the use of OCPs including DDT, HCHs, Endosulfan, Heptachlor etc. has been banned but owing to their illegitimate use in agriculture, industry, vector control and unauthorized disposal their increased contamination in dumping sites is likely. There is no manufacturing unit of OCPs in Pakistan, besides 19 companies involved in production of formulations that are based mainly on imported active ingredients from countries like India, taking advantage of laxity allowed in pesticide import during 1991 (Beg, 2005).

Solid waste is one of the most visible problems of today in many developing countries. It is an interdisciplinary problem influenced sturdily by legal, socio-cultural, economic, environmental factors, existing resources, engineering, architectural and planning functions (Hafeez, 2013; Khajuria et al., 2010). About 54,850 t of waste is generated daily in Pakistan with less than 60% of generated waste being collected (Ejaz et al., 2010). Overall waste generation is about 0.283–0.612 kg/capital/day whereas waste generation growth rate is 2.4% per year (Khan et al., 2012). In large cities owing to increasing urbanization, commercialization and industrialization trend, municipal dumps receives diverse nature of waste from different resources. The historic dumping of organic chemicals along with their tendency to migrate from unsuitably located dumps and landfill sites has resulted in widespread contamination of soils which is main recipient of solid waste dumps where heavy metals, organic pollutants including (POPs) and other toxic elements get accumulated, causing damaging effects on

⁎

Corresponding author. E-mail address: [email protected] (R.N. Malik).

https://doi.org/10.1016/j.ecoenv.2018.11.020 Received 18 March 2018; Received in revised form 7 October 2018; Accepted 6 November 2018 0147-6513/ © 2018 Published by Elsevier Inc.

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Physicochemical properties of soil like pH, soil texture, organic matter, climatic or meteorological factors (temperature and rainfall), agricultural practices and usage or application history of chemical are important for regulating environmental fate and behavior of OCPs (Alamdar et al., 2014). OCPs can be absorbed and degraded in the environment up to a certain degree but due to their low vapor pressure and resistance to oxidation most of them remain in the media (Fang et al., 2017). Inorganic soil constituents strongly influence the sorption of many pesticides in subsoil, where organic matter contents are often low. Soil texture controls distribution of pore size in soils and therefore influences their water associations and aeration characteristics due to which degradation rates of pesticides can be affected (Rodríguez-Cruz et al., 2006). Black carbon (BC), fraction of TOC plays a fundamental role in distribution and fate of persistent organic pollutants and its contribution for soil and sediment is reported as 4% and 9% respectively (Koelmans et al., 2006). Globally limited studies are available on fate of OCPs in solid waste dumping sites. Previously no such studies have been conducted specifically on OCPs from waste dumping sites except few studies on obsolete pesticide dumping sites by (Ahad et al., 2010; Syed et al., 2014). Therefore this study aims to assess the (i) occurrence, source apportionment and magnitude of Organochlorine pesticides contamination in soils of waste dumping sites (ii) Influence of soil properties, soil components and socioeconomic factors on OCPs distribution in soils and (iii) Relationship between TOC and δ13C stable isotope composition in soils of waste dumping sites (iv) Non-carcinogenic Human Risk of OCPs via ingestion (v) Future waste generation projections for year 2026.

Fig. 1. Study Area Map showing locations of sampling sites.

2. Material and methods

analysis.

2.1. Study area

2.3. Physicochemical properties of soils

Study area comprised of nine solid waste dumping sites of populated and Industrial cities of Pakistan including Hazar khawani dump site Peshawar from KPK, From Punjab Losar dump site Rawalpindi, Sheikh Sukkah dump site Gujrat, Chian wali dump site on GT road Kamoki, Chak Muhammad Wala on Jaranwala road Faisalabad and Mahmood booti dumping site Lahore. From Sindh, waste dump site on Rohri highway Sukkur, Autobahn road dump site in Hyderabad and Jam chakro dump site, Karachi was selected for the present study. Locations are shown in Fig. 1. All the selected dumping sites falls under the competences of municipal corporations under local government or designated waste management companies except one located in Hyderabad. Majority disposal sites designated for current study are located in environmentally sensitive, low-lying areas such as wetlands forest edges and adjacent to bodies of water. Besides this they lie in proximity of industrial and agricultural areas where the use of organochlorine pesticide is probable. Detailed description of study area is presented in Supplementary information Table.

In order to investigate the spatial variability of OCPs in soil, physiochemical parameters pH, electrical conductivity, soil texture and moisture content of soil TOC and black carbon was analyzed. For pH determination Crison pH meter was used which was calibrated with buffer solution of pH 4, 7 and 9. For analysis a slurry of soil and deionized in a ratio 5:1 (2 gm soil and 10 ml water) was prepared and allow to stand for 30 min prior to measurements. For Electrical conductivity (EC) PCS Testr 35 (multiparameter) EC meter was used. For analysis slurry of 5:1 was prepared by dissolving 2 gm of soil sample in 10 ml of water. For moisture content determination, soil samples were first weighed and then were dried in oven set at 105 °C to remove the moisture content and then re-weighed. Soil texture of samples was determined by dry sieve method. For particle size distribution, sieves of different mesh sizes for sand, silt and clay were used based on USDA particle size distribution and soil texture triangle.

2.2. Soil sampling strategy

2.4. Extraction and instrumental analysis of OCPs

Soil samples were collected from nine dumping sites of Pakistan viz: Peshawar (KPK), From Punjab Losar, Gujrat, Kamoki, Faisalabad, Sukkur, Hyderabad and Karachi from Sindh. Three sampling points within 200–500 m distance were selected from waste dumping sites of Gujrat, Kamoki, Hyderabad and Peshawar, having small area of waste dumping sites. Whereas from large dumping sites of Losar, Faisalabad, Lahore, Sukkur and Karachi soil samples were collected within the distance of 1–2 km. To improve the representativeness of the soil samples, three subsamples were collected and evenly mixed by using the diagonal dividing method for further laboratory analysis. Collected soil samples (n = 27) were preserved in polyethylene zippers and brought to the Environmental Health Laboratory in Quaid-I-Azam University Islamabad, Pakistan. Samples were prepared by drying and sieving through a 2 mm mesh and refrigerated at −4 °C prior to

2.4.1. Extraction and cleanup Prior to OCPs quantification, cleanup and extraction of samples were performed. Soil samples were first thawed and freeze-dried for 24 h, pulverized and sieved through 1 mm stainless steel mesh. Selected OCPs, viz. HCHs (α-HCH, β-HCH, γ-HCH, δ-HCH), DDTs (o,p′, p,p′-DDE, o,p′, p,p′-DDD and o,p′, p,p′-DDT), Endosulfan (α-Endosulfan, βEndosulfan, Endosulfan Sulfate), HCB, Heptachlor and Heptachlor epoxide were Soxhlet-extracted from soil samples (20 g used for 1 sample) by Dichloromethane (obtained from Merck and Co., Inc.) for 18 h. Homogeneous solution comprising of duplicate standards of 2,4,5,6tetrachloro-m-xylene (TCmX) and decachlorobiphenyl (PCB-209). Each sample was spiked with this mixture before extraction. In order to eliminate elemental sulfur, pellets of activated copper were added to the collection vessel. The extract was concentrated by using rotary 196

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evaporator and solvent-exchanged to hexane and purified on an 8 mm alumina/silica column packed with 3 cm neutral alumina and 3% deactivated water, 3 cm neutral silica gel and 3% deactivated water, 50% H2SO4, SiO2 (3 cm), and anhydrous Na2SO4 (1 cm). To obtain OCPs fractions, column was eluted with 50 ml of DCM: Hexane (1:1). Neutral alumina, neutral silica gel, and anhydrous sodium sulfate were Soxhletextracted for 48 h with DCM, and baked for 12 h in 180 °C, 250 °C and 450 °C, respectively before using. 25 μl of dodecane was added to concentrate volume of batch samples upto 0.2 ml via high purity nitrogen gas flow.

ampoule was labelled and removed from the line for isotope ratio measurements onto the Isotope Ratio Mass spectrometer (IRMS). Detailed methodology is presented in Supplementary information. 2.8. Statistical analysis Basic descriptive statistics including minimum, maximum, mean values and standard deviation, Analysis of Variance to determine the significant differences between the means of sampling sites and organochlorine pesticides and Two –tailed Pearson correlation was performed using Statistical Package for the Social Sciences 20 for windows (SPSS). Linear regression plots for evaluating impact of socioeconomic indices on levels of organochlorine pesticides and Scatter plots depicting diagnostic ratios for source identification of organochlorine pesticides were constructed via Microsoft excel 2007. Principal Component Analysis was employed using Multivariate statistical Packages 3.1. It was applied on standardized data set (24 variables and 81 cases) with tolerance of Eigen analysis set at 1E-007 and vector scaling of 1.06 to assess the classification and spatial distribution of Organochlorine pesticides.

2.4.2. Chromatographic analysis of organochlorine pesticides A known quantity of pentachloronitrobenzene (PCNB) was added as an internal standard before GC-MS analysis. Analysis was carried out on Finnigan TRACE Gas Chromatography- Mass Spectrometer (GC–MS) with 50 m capillary column (Varian, CP-Sil 8 CB, 50 m, 0.25 mm, 0.25 µm). Helium was used as the carrier gas at 1.2 ml/min under constant-flow mode was filtered with moisture, hydrocarbon, and oxygen filters before entering the GC system. Initially the temperature of oven was set to 60 °C for 1 min, than increased to 295 °C at the rate of 4 °C/min. The temperature of injector was kept at 250 °C. Split less/split injection of a 1 ml sample was finished with delay time of five minutes and inlet degradation of DDT was checked daily and controlled within 15%.

2.9. Non-carcinogenic human risk assessment Non carcinogenic risk was calculated for Organochlorine pesticides in this study as per the US EPA Exposure Factors Handbook - 1997 (EPA, 1997). The hazard quotient (HQ) was used for estimation of noncarcinogenic risks of OCPs in soils from exposure through soil ingestion. The detailed equations and calculations of health risk assessment are presented in Supporting information.

2.5. Quality control and quality assurance Quality assurance and control was prioritized during the whole analytical procedure. Blanks comprising of a solvent blank, procedural blank and duplicate sample were examined. Solvent blank and procedural blanks were evaluated after every 10 soil samples to authenticate lack of interference by impurities and quality of analysis. Mean recoveries for PCB-209 and TCmX were 89.876% and 50.876%, respectively. Instrumental detection limits (IDLs) and method detection limits (MDLs) were estimated by standard procedures. In case of IDLs, the lowest standards were amplified to the equivalent quantity of analyte that would produce a signal to noise ratio of 3:1. MDLs were expected as three times of standard deviation of blanks. Instruments used in analysis were calibrated daily using calibration standards and glassware were thoroughly cleansed with distilled water and baked at 450 °C for about 6 h.

2.10. Waste generation projection for year 2026 Solid waste generation projections for the year 2026 were calculated by factoring expected population growth and estimated waste generation per capita. Population was estimated according to data based 1998 census, in line with the report of National bureau of statistics. Growth rate was also projected for year 2016 and 2026 based on waste generation of 1998 census. For waste generation estimation growth rate were projected based on growth rate of waste generation as 2.4% per year (Khan et al., 2012). Future waste generation projection was estimated according to (Weber). The population is calculated by

2.6. Black carbon (CTO-375) and total organic carbon (TOC) analysis

(1)

P1 + r T

where P = initial population people, r = percent growth rate/100 and T = years. Solid waste generation per capita was calculated according to

Around 3 g of dried and homogenized soil samples were acidified with HCL (1 N) and oxidized in a muffle furnace at 375 °C for 17–18 h under constricted air flux. For TOC analysis, soil samples were subjected to digestion by 10% HCl to remove inorganic carbon. Later TOC samples were rinsed and properly washed with deionized water thrice and dried in microwave assisted oven at 60 °C for a day. Finally both organic carbon fractions were quantified by TOC analyzer (Multi N/C 3100 Analytik Jena) (Ali et al., 2016).

P × WGR ×

2.7. Stable carbon isotopic analysis

3. Results and discussions

The analysis of stable Carbon isotopes was performed using modified Varian Mat GD- 150 Mass Spectrometer. Stable isotope data is reported as for δ13C analysis of Total Dissolve Inorganic Carbon. Soil samples were first converted into gas phase. Extraction of CO2 was carried out according to details given in the Supplementary information. The moisture produced during the reaction was removed by cryogenic trap of – 800 C and CO2 gas was passed through vacuum line and purified by freezing in Ultra dipped in liquid nitrogen flask. Other gases were pumped out from line. The liquid N2 flask from CO2 trap was removed to expand CO2 in vacuum line which was finally collected in an ampoule dipped in liquid nitrogen flask at the other end of line. The

3.1. Occurrence and levels of organochlorine pesticides

No. days ÷ kgTons y

1

(2)

where P = population, WGR= waste generation rate, No. d/y = number of day per year

Descriptive statistics of ∑OCPs in soils from solid waste dumping sites of Pakistan is presented in Table. The overall concentration of OCPs in surface soil of waste dumping sites of Pakistan ranged between 4.2 and 30.44 ng/g with mean concentration of 13.79 ± 6.34 ng/g. All the detected OCPs in different waste dumping sites had p-value < 0.05 indicating significant variation. Order of overall OCPs concentration in different sites was Lahore > Sukkur > Karachi > Kamoki > Faisalabad > Hyderabad > Losar > Gujrat > Peshawar whereas the mean concentrations of OCPs were in following order: 197

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∑DDTs > ∑HCHs > ∑Endosulfan > ∑HCB > Heptachlor. The average concentrations of DDTs, HCHs, Endosulfan, HCB and Heptachlor were 6.49 ng/g, 3.5 ng/g, 2.65 ng/g, 1.12 ng/g and 0.93 ng/g respectively. Comparison of current study with global studies is presented in Supplementary information. The possible sources of higher degree of contamination in soils from Lahore is Chemical Industries and presence of number of MNC's involved in manufacturing pesticide formulations from imported active ingredient. Beside this probable source could be the old stocks of HCHs and DDTs available from stock houses for control of insects (Khwaja et al., 2013).

It was detected in concentration range of 0.01–2.25 ng/g with highest detected levels from waste dumping site of Hyderabad (2.25 ng/g) as it was one of high selling pesticide in Sindh during 2003. In rest of dumping sites concentration of α-Endosulfan was < 02 ng/g. 3.1.4. Heptachlor The overall concentration range for Heptachlor was 0.11–3.69 ng/g with very low mean concentration of 0.94 ng/g as compared to concentrations from landfill of Jordan (46.8 ng/g) (Jiries et al., 2002), soils of different land uses in China (6.85 ng/g) (Min et al., 2015) and waste dumping sites of Agra, India (290 ng/g) (Gupta et al., 2015). Order of level in different sites was Losar > Faisalabad > Karachi > Kamoki > Sukkur > Hyderabad > Gujrat > Peshawar > Lahore and detection frequency was 28.3%. Highest concentration of Heptachlor in Losar reflects its usage in wood products, as pest repelling agents and for hygiene control (Syed et al., 2013). It was deregistered in Pakistan in 1997 so its detection in soil samples might be due to its scanty ongoing usage as termicide, for home lawns or in gardens or applications of Trans Chlordane used in agricultural areas previously (Nasir et al., 2014).

3.1.1. DDTs Overall concentration for DDT and its metabolites was in range between 0.16 and 25.66 ng/g with average concentration of 6.46 ± 1.31 ng/g which were less than average concentration of DDTs from waste dumping sites of Vietnam (19 ng/g), India (26 ng/g) and Greece (21.3 ng/g) (Chrysikou et al., 2008; Minh et al., 2006) and higher than average concentrations in agricultural soils of India (1.61 ± 0.33 ng/g) (Kumar et al., 2011) Order of occurrence in different sites was Lahore > Sukkur > Hyderabad > Faisalabad > Kamoki > Karachi > Peshawar > Losar > Gujrat. Whereas occurrence of different DDT metabolites were in order: p, p΄–DDD > o, p΄–DDT > p, p΄–DDT > o, p΄–DDD & p, p΄– DDE > o, p΄–DDE. In majority of sites, p,p΄–DDD was detected in high concentration with overall mean value of 18.8 ng/g. Higher concentration of DDT metabolites in soils were due to subtropical climate in Pakistan that raised the rate of parent DDT transformation into its metabolites (Syed et al., 2013). Detection frequency of all DDT isomers was 100% except p, p′-DDE having detection frequency of 35.8%.

3.1.5. HCB Hexachlorobenzene was detected in the range between 0.01 and 5.87 ng/g with the mean value of 1.12 ng/g in waste dumping sites of Pakistan which were higher the mean values of HCBs in waste dumping sites of Cambodia (0.51 ng/g) and Vietnam (0.19 ng/g) (Minh et al., 2006), comparable to the levels from Beijing, China (1.13 ng/g) (Sun et al., 2009) and very low than the levels detected in India from waste dumping sites of Agra (163 ng/g) (Gupta et al., 2015). Highest concentrations were detected in Karachi with range between 2.58 and 5.87 ng/g followed by Lahore where the concentration range was between 0.33 and 5.21 ng/g and Gujrat 0.14–2.36 ng/g. In rest of dumping sites the concentrations were less than 01 ng/g. Formation of HCB as a by-product during manufacturing process is due to its use as an impurity in various chlorinated pesticides, including lindane mainly (Škrbić and urišić-Mladenović, 2007). Detection of HCB in these areas might be linked with burning of e-waste in waste dumping sites and secondary organochlorines products (Chakraborty et al., 2010).

3.1.2. HCHs The mean concentration of HCHs (sum of isomers α–HCH + β–HCH + γ–HCH + δ -HCH) ranged from 0.81 to 14.94 ng/g with average concentration of 3.50 ± 0.74 ng/g which were higher than HCHs in landfill from Slovak republic (12 ng/g) (Veningerová et al., 1997) Greece (9.63 ng/g) (Chrysikou et al., 2008) and lower than concentrations from waste dumping sites of Cambodia (1.7 ng/g) and Vietnam (0.83 ng/g) (Minh et al., 2006). Overall order of HCHs mean concentrations in sampling areas was Lahore > Kamoki > Karachi > Sukkur > Losar > Gujrat > Hyderabad > Peshawar > Faisalabad. The order of HCHs isomers was α–HCH > β–HCH > γ–HCH > δ-HCH. Highest concentration of α –HCH (10.72 ± 2.2 ng/g) was detected in waste dumping site of Lahore which could be explained by the use of technical mixture of HCHs, containing high percentage of α–HCH in the composition. Being more volatile than other isomers of HCH, α-HCH could be received by soils via atmospheric transport from areas where it is being recently used (Hou et al., 2013; Hou et al., 2013). The detection frequency of all isomers of HCH was 100% except δ –HCH having detection frequency of 62% therefore its contribution to the overall HCH contamination is low.

3.2. Potential source apportionment of organochlorine pesticides Isomeric and parent substance/metabolite ratios have been used commonly to detect past and recent sources of pollutants in soils (Zhao et al., 2017). Cross plots for diagnostic ratio of OCPs are presented in Supplementary information. In order to discriminate the contribution of dicofol from technical DDT, indicative ratios of o, p′-DDT/ p, p′-DDT were utilized. A ratio of > 1 indicates use of dicofol whereas a ratio of < 1 infers to the use of technical mixture (Min et al., 2015). In present study o, p′-DDT/p, p′-DDT ratios were > 1 in all sampling sites from Lahore (10.55–19.46 ng/g) indicating the use of dicofol, whereas Losar (0.11–8.0) Hyderabad (0.95–2.18) Sukkur (0.76–2.33) and Karachi (0.17–1.74) had ratios both < 1 and > 1 in few of sampling sites, indicating use of both dicofol and technical mixture of DDT in these areas. Dicofol being cheaper and containing 3–7% DDTs was used widely after the ban of technical DDT in Pakistan (Eqani et al., 2011; Mahmood et al., 2014). In Peshawar, Gujrat Kamoki and Faisalabad ratio was < 1 in majority of sampling sites showing usage of technical mixture of DDT. The ratio of p, p´-DDT/(p, p´-DDE + p, p′-DDD) was used to specify historic inputs p, p′- DDT in soils or current use. Ratios > 1 suggest the presence of new DDT sources (Fang et al., 2017). Ratio of p, p´-DDT/( p,p´-DDE + p,p′-DDD) in current study was > 1 in all sampling sites from Gujrat, inferring the recent use of DDT whereas in Kamoki, Faisalabad, Sukkur and Karachi diagnostic ratios indicated both historical and recent use of DDTs in these areas. For Peshawar, Losar, Lahore and Hyderabad the ratio was < 1 in all sampling sites, indicating the

3.1.3. Endosulfan The overall concentration of Endosulfan ranges between 0.10 and 9.62 ng/g with mean concentration of 2.65 ng/g which was below than mean concentration detected in waste dumping site of Jordan (6.4 ng/ g) and from soils of different land use from Urqumi, China (17.12) (Jiries et al., 2002; Min et al., 2015) Results were comparable to the concentrations from soils of Nepal (2.0 ng/g) (Wong et al., 2010). Occurrence was in order: Endosulfan Sulfate > α-Endosulfan > β-Endosulfan. β-Endosulfan has 100% detection frequency whereas Endosulfan sulfate has lowest detection frequency of 30.8% among Endosulfan isomers. Order of levels in various site was Sukkur > Faisalabad > Karachi > Kamoki > Hyderabad > Gujrat > Losar > Lahore > Peshawar. Endosulfan sulfate was detected in highest concentration upto 4.11 ng/g whereas α- Endosulfan has lowest mean concentration (2.25 ng/g) as compared to other isomers of endosulfan. 198

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accordance with results of (Gao et al., 2013; Min et al., 2015; Parween et al., 2014), whereas it has negative significant correlations for δ-HCH and Heptachlor epoxide. For other HCHs reason might be low levels or varying TOC content in soil (Gao et al., 2013). No significant correlation was found for rest of OCPs and TOC, so high concentrations of these OCPs were result of input history. Low BC content was quantified in the present study with BC % ranged between 0.03 and 0.8 showing positive correlation for only p, p′-DDT however it correlated negatively for most of the OCPs suggesting that OCPs adsorption onto BC is not an important mechanism in their distribution due to short residence time of BC in soils, similar results were reported in study by (Tan et al., 2009; Yadav et al., 2016). TOC and BC appeared to be correlated in the present study. Related studies have been stated by (Nam et al., 2008; Parween et al., 2014). Soil textural classes also had significant influence over the distribution of OCPs. Soils from all of the sites were classified as silty-loamy except from Kamoki which was classified as loamy. Sand % has positive correlations with majority of OCPs (β-HCH, δ-HCH, o, p′DDE, p, p′-DDE, p, p′-DDT, Heptachlor, and β-endosulfan) although sand donot facilitates the sorption of organic compounds because of having less surface area. Silt showed positive correlations for α-HCH, γHCH, δ-HCH and o, p′-DDT. Clay minerals has positive correlations with o, p′- DDD, p, p′-DDD, o, p′-DDT, α-HCH and heptachlor epoxide. Soil moisture demonstrated positive correlations for γ-HCH and heptachlor. EC has range of 0.10–3.57 ms−1 and exhibited positive correlations for α-HCH, γ-HCH, o, p′-DDD, p, p′-DDE and heptachlor. High EC regulates the OCPs level and promotes the degradation of OCPs (Parween et al., 2014). pH has range of 7.3–9.3 and showed positive correlations for p, p′-DDD, p, p′-DDT, α-endosulfan and endosulfan sulfate and negative correlations for γ-HCH, Heptachlor and o, p′-DDD however for pH most of studies have reported insignificant or negative correlations of OCPs with pH (Gao et al., 2008, 2013; Min et al., 2015; Qu et al., 2016; Zhang et al., 2006).

Fig. 2. Association between δ13C isotopic finger prints and Total organic Carbon in soils of waste dumping sites.

historical use of DDTs. The ratios of DDE/DDD are effective markers for estimating degradation status (pathway) of DDT. Ratio > 1 indicates the anaerobic degradation of DDT into DDD, whereas ratio < 1 reflects transformation of DDT into DDE via aerobic degradation (Ali et al., 2016). Ratios were < 1 only for Peshawar indicating dominance of DDE conversion from DDT via aerobic pathway. Ratios from Gujrat (0.85–11.6) and Kamoki (0.73–7.54), shows both aerobic and anaerobic degradation pathways in these areas Whereas rest of the areas showed higher ratios ranging from 2.61 to 133.96 with highest ratio being observed in Lahore denoting anaerobic pathway of DDT degradation into DDD. Ratios of α/γ- HCH and β/ α + γ-HCH were used to identify the pollution source and input history as presented in Fig. 3.5. Ratios of α/ γ-HCH were < 3 for Peshawar losar and Gujrat indicating the use of Lindane in these sites whereas in rest of sites the ratios were > 3 indicating use of technical HCH. Input history was assessed using ratios of β/ α + γ-HCH that were < 3 for only Peshawar indicating historical use while rest of sites has ratios > 3 indicating recent input of HCHs in these sites. Soil samples from Lahore had very high ratios of α/γ-HCH that could be related to old inputs of technical usage of HCHs. Diagnostic ratios for potential source apportionment of Endosulfan are presented in Fig. The ratio of α-/β-endosulfan > 2.3 is indicative of historical use of endosulfan whereas ratio < 2.3 indicates fresh application of endosulfan (Yadav et al., 2016). In this study, Kamoki (0.03–3.26) and Hyderabad (0.2–1.19) has ratios both < 2.3 and > 2.3 in some of the sampling sites suggesting historical as well as and recent use of endosulfan in the area whereas in all other areas ratios were < 2.3 indicating fresh use of endosulfan in these areas. Heptachlor epoxide / Heptachlor ratio has been used to predict the age of heptachlor. Fig shows the diagnostic ratios of Heptachlor for source apportionment. Ratio < 1 indicates recent use of heptachlor while that > 1 reflects either, conversion into epoxide by biotic or abiotic pathways or volatilization which causes loss of heptachlor (Gonzalez et al., 2005) Ratio was < 1 for all sites (Losar 0.61–0.80, Gujrat 0.5, Kamoki 0.7, Faisalabad 0.58–0.96, Sukkur 0.8, Hyderabad 0.04 and Karachi 0.65–0.70) indicating recent use of Heptachlor. Heptachlor Epoxide was not detected in any of sample from Peshawar and Lahore.

3.4. Variation in TOC content of soils in waste dumping sites: Evidence from δ13C isotopic finger prints In the present study carbon isotopic fingerprints (the variations of the C13/C12) in inorganic carbon fraction of organic matter were utilized to trace the source of carbon in soil. As organic matter decomposition occurs, total organic carbon content decreases, results in fractionation resulting in enrichment of molecules with heavy isotopes (Golchin et al., 1994). It is hypothesized that depletion of δ 13C value indicates organic source of Carbon for OCPs retention in soil whereas high δ13C values indicates inorganic source of carbon. Inorganic fractions have δ 13C values near zero per mil (-0.02 to −4.4%) (Rask and Schoenau, 1993). However values of δ 13C in present study ranges from −5.61 to −0.29% with highest values being detected in Karachi. The range of δ 13C in soils from waste dumping sites of Karachi, Kamoki, Faisalabad, Gujrat, Losar and Sukkur indicated the presence of inorganic source carbon whereas values of δ 13C in soils of Lahore and Hyderabad showed the contribution of organic carbon source in overall pool of soil carbon. In waste dumping sites of Hyderabad high quantity of TOC was present which could be due the presence organic sources of carbon like vegetation and high fraction of organic waste in solid waste dumping sites of Hyderabad. High δ 13C values in soils from waste dumping sites of Karachi could be explained by fraction of fine material containing carbonate introduced by metal slag from metallurgical activities, industrial waste or construction material in waste dumping sites (Boeckx et al., 2006). The regression analysis as shown in Fig has also indicated negative correlation between TOC and δ 13C (R2 = 0.35) which shows an agreement with the hypothesis formulated with the help literature studies. The correlation is although weak which could be explained by variation in precipitation and texture of an area (Fig. 2)

3.3. Influence of soil properties and soil components on organochlorine pesticide levels Influence of soil properties (pH, EC, Soil moisture, Soil Texture) and soil components (TOC, black carbon) and the concentrations of HCHs and DDTs was evaluated using correlation analysis as shown in Table. In the present study TOC % ranged from 0.19 to 1.9 and has significant positive correlations for only endosulfan sulfate and β-HCH which is in 199

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Fig. 3. (a) Principal Component Analysis showing classification and distribution of ∑OCPs; (b) Principal Component Analysis showing Classification and distribution of OCPs metabolites.

3.5. OCPs distribution and classification using principal component analysis (PCA)

group with clay. A distinct group of ∑Heptachlor with EC could be observed in Losar. Sand and soil moisture are showing positive correlations in Kamoki and Peshawar whereas BC and TOC with ∑Endosulfan in Karachi, Hyderabad and Gujrat. PCA for individual OCP metabolite reveals detailed information on grouping and correlations. PCA biplot Fig. 3.9 (b) shows a distinct grouping of α -HCH and DDT metabolites ie o, p′ -DDD, p, p´-DDD, o, p´-DDT in Lahore, explained by similarities in relation to their high concentration. The high concentrations of α -HCH and these DDT metabolites are explained by their adsorption onto finer fraction of silt and clay due to their large surface area (Gómez et al., 2011). Significant positive correlations of α –HCH, p, p´-DDD and o, p´DDT with silt and clay also been explained by Pearson correlation analysis. Very high ratios of α-HCH/γ-HCH related to old inputs and transformation of γ -HCH into α -HCH as well as recent use of technical HCH may also be the probable source of high α –HCH levels in the waste dumping site of Lahore. o, p′-DDE, p, p′-DDT, β -HCH, α-Endosulfan, β-endosulfan and Endosulfan sulfate showed strong positive correlations with TOC in Karachi and Hyderabad. Correlation analysis has showed only strong positive correlations of Endosulfan sulfate and β –HCH with TOC. As they have high values Koc and Kow therefore they have tendency of

In current study it was applied on ∑OCPs as well as individual OCP metabolites to assess the spatial distribution of targeted OCPs, their sources and relation to soil properties and soil components as presented in Fig. 3(a) and (b). PCA implied on individual OCP metabolites, extracted 4 component axis (PCs) for 16 OCPs, explaining 62.2% of the total variance. Eigenvalues > 1 and scores > 0.3 were considered significant. PC-1 explained 21% of the total variance with significant positive loadings (> 0.1) of δ-HCH, o,p´-DDE, p,p′-DDE, p,p′-DDT, αEndosulfan, β-endosulfan, endosulfan sulfate and sand and negative loadings of α-HCH, γ -HCH, o,p′-DDD, p,p´-DDD, o,p´-DDT, EC, silt and clay. PC-2 accounts for positive loadings of, soil moisture, EC, γ -HCH, o,p′-DDD, p,p′-DDE, δ -HCH, Heptachlor and sand and negative loadings for o,p′ -DDT, p,p′- DDT, α -Endosulfan, pH, α -HCH, β -HCH, HCB, silt and TOC explaining 18% of the overall variance. In this Euclidean biplot, sites were indicated as dependent variable whereas arrows depict the independent variables. Fig. 3(a) shows PCA biplot for ∑OCPs, explaining grouping of ∑HCH and ∑DDT in Lahore and Faisalabad showing with positive correlation with silt. Faisalabad is forming a 200

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Fig. 4. Impact of Socioeconomic Indices on levels of Organochlorine Pesticides.

sorption and forming complexes with organic carbon constituents (Leadprathom et al., 2009) so their high concentrations were result of TOC retention in these sites. Gujrat showed weak positive correlation of p, p′-DDT and β -HCH with TOC and BC. Weak correlation of these OCPs with TOC or BC could be related to more recent contamination of these OCPs. In Gujrat the high concentrations of p, p′-DDT and β-HCH were reflection of recent application of technical mixtures. For high β-HCH levels, other reasons could be low vapor pressure, low water solubility and high partition coefficients than other isomers of HCH which makes it stable for microbial degradation and persistent (Yuan et al., 2017). δ -HCH, p, p′-DDE and Heptachlor displayed positive correlations with sand in Kamoki. Sand is generally assumed to limit the adsorption and persistence of pollutants in the soil (Do Nascimento et al., 2004). Therefore the high concentrations in Kamoki were the result of present use of these contaminants in the area. γ -HCH, o, p′-DDD, EC and soil moisture forms a group together in Losar and Peshawar. High concentration of γ -HCH could be explained by use of fresh application of lindane in these areas whereas past application of DDT and its conversion into DDD via anaerobic pathway could be the reason of high concentration of o, p -DDD in Peshawar.

Fig. 5. Forecasted waste generation for the year 2026.

4.93 × 109. For HCHs range of values were between 7.34 × 1010 and 5.71 × 109, for Endosulfan 0–7.6 × 109, Heptachlor, between 1.51 × 1010 and 9.33 × 1010 and HCB had values between 1.19 × 1010 and 6.2 × 1010. HQ of OCPs (γ –HCH, p, p′-DDT, Heptachlor, αEndosulfan and HCB) with available RFD values was calculated. The estimated HQ values of these OCPs were much lower than tolerable safe level of risk (HQ ≤1), indicating negligible risk to the residents living in the proximity of dumping sites. However synergistic effects of these pesticides couldn’t be neglected which could possibly cause drastic effects on human health.

3.6. Potential non-carcinogenic human risk from solid waste dumping sites OCPs uptake through ingestion of soil may exert detrimental effects on humans. Non cancer human health risk was evaluated by exposure of OCPs via ingestion of soil particles targeting the residents living in the proximity of waste dumping site. Values of Average daily dose (ADD) and Hazard quotient (HQ) was used for evaluation of potential human health risks from OCPs in soils. Results are summarized in Table. ADD values of all targeted OCPs from waste dumping sites where below than the values of reference dose of the compounds. For DDTs range of ADD values was from 1.71 × 109 - 1.26 × 108 with mean value of

3.7. Influence of socioeconomic indices on OCPs levels Socioeconomic conditions and seems to be the important factors in determining the distribution of contaminants as they are associated 201

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Table 1 Basic descriptive statistics ∑OCPs in soil (ng/g). Site % DF PES LOS GUJ KAM FAI LAH SUK HYD KAR All p-Value

Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean ± S.D Median Min-Max Mean Median

∑DDTs 96.08

∑HCHs 100

∑Endosulfan 72.3

∑Heptachlor 65.4

HCB 100

∑OCPs 86.756

1.71–3.61 2.63 ± 0.67 2.62 3.63–7.19 5.37 ± 1.24 5.26 2.16–3.42 2.77 ± 0.50 2.67 4.47–7.74 5.94 ± 1.25 5.94 5.28–6.77 6.17 ± 0.52 6.2 9.02–16.5 13.7 ± 2.72 14.2 4.99–9.07 6.76 ± 1.31 6.56 6.98–10.53 9.19 ± 1.20 9.1 3.48–8.44 5.58 ± 1.87 5.28 1.7–16.57 6.46 ± 1.31 5.99 0.002

1.33–1.67 1.54 ± 0.18 1.57 1.58–2.40 2.02 ± 0.28 2.03 1.63–2.90 1.95 ± 0.39 1.79 3.28–4.78 3.91 ± 0.47 3.83 0.93–2.34 1.55 ± 0.50 1.42 9.25–14.94 12.17 ± 1.94 11.98 0.81–2.31 1.62 ± 0.47 1.62 1.57–4.4 3.18 ± 0.94 3.28 1.48–5.82 3.58 ± 1.51 3.48 0.81–14.94 3.50 ± 0.74 0.36 0.001

0.12–0.16 0.14 ± 0.01 0.14 1.41–1.81 1.58 ± 0.14 1.57 1.16–3.62 2.08 ± 1.05 1.51 1.88–4.77 2.97 ± 1.08 2.86 2.67–7.19 4.34 ± 1.38 4.3 0.72–2.16 1.00 ± 0.44 0.9 1.5–4.25 2.48 ± 0.78 2.24 4.26–7.55 5.55 ± 1.19 5.05 2.61–4.90 3.67 ± 0.83 3.6 0.0–2.251 2.65 ± 0.77 2.24 0.002

0.21–0.41 0.32 ± 0.07 0.33 2.36–3.08 2.74 ± 0.25 2.74 0.28–0.54 0.43 ± 0.10 0.44 0.38–1.61 0.66 ± 0.38 0.56 0.62–3.84 2.17 ± 1.12 1.99 0.11–0.36 0.21 ± 0.09 0.18 0.25–2.1 0.47 ± 0.21 0.26 0.47–0.72 0.55 ± 0.08 0.5 0.36–1.71 0.82 ± 0.62 0.46 0.12–7.55 1.12 ± 0.47 0.48 0.004

0.11–0.36 0.24 ± 0.09 0.24 0.01–0.15 0.09 ± 0.05 0.09 0.14–2.36 1.11 ± 0.81 1.05 0.39–0.59 0.5 ± 0.08 0.47 0.36–0.69 0.51 ± 0.11 0.54 0.33–5.21 2.72 ± 1.67 2.8 0.11–0.26 0.18 ± 0.05 0.18 0.14–0.69 0.35 ± 0.19 0.34 2.58–5.87 4.42 ± 1.16 4.76 0.01–5.87 0.93 ± 0.32 0.4 0.001

4.22–5.7 4.89 ± 0.57 4.69 10.2–13.9 11.8 ± 1.26 11.9 5.78–8.61 7.1 ± 0.87 7.12 11.7–15.9 13.5 ± 1.38 13.4 12.6–16.03 14.4 ± 1.20 14.54 24.2–30.44 27.5 ± 1.73 27.2 9.3–14.4 11.52 ± 1.68 11 16.6–21.03 18.63 ± 1.61 9.8–17.2 13.46 ± 2.35 13.2 4.2–30.44 13.79 ± 6.34 12.9 0.005

will get doubled by the year 2026. Waste generation forecasts signify the need of larger land areas for waste disposal in future and also the need of proper waste management (Figs. 4 and 5).

with usage history and loads (Calamari et al., 1995). Regression analysis applied between socio-economic indices including quantifiable variables like gross population, human development index and quantity of waste generation with OCP concentration (as shown in Fig) reveals gross population to be the influencing factor among others affecting the OCP concentrations with standardized regression coefficient of 0.27 and weak positive correlation. HDI and Waste generation quantity has regression coefficient value of 0.237 and 0.227 respectively. The weak correlation of OCPs concentration with socio-economic indices is linked with the history of use of these contaminants in the respective areas. The diagnostic ratios also indicated the past usage of organochlorine pesticides in most of the areas of current study. As Pesticide ordinance 1971 and 1973 has banned their usage and production in the country so their presence in environmental matrices indicates illegal use of these OCPs. Cities with less population and HDI like Kamoki and Gujrat have high concentrations of OCPs because of their probable high usage in these areas as compared to others the due to inadequate control on access to the banned pesticides.

4. Conclusions This study presents the findings of a comprehensive survey of studied solid waste dumping sites of nine cities of Pakistan providing first systematic baseline data of OCPs occurrence, fate and distribution in soils samples. ∑DDTs were comparatively more prevalent in the soils of waste dumping site among which p,p′-DDD was dominant isomer in majority of dumping sites. The distribution of majority of DDT metabolite was explained by textural classes. For HCHs recent use of technical mixtures in majority of the studied sites has influenced their distribution. Order of overall ∑OCPs contamination with respect to location was Lahore > Sukkur > Karachi > Kamoki > Faisalabad > Hyderabad > Losar > Gujrat > Peshawar. Distribution of OCPs in solid waste dumping site was mainly influenced by textural classes, input history and pollution source. TOC and Black carbon has not significantly influenced the concentrations of OCPs. Inverse relation between δ13C and TOC by regression analysis as in agreement with the hypothesis, showed high δ13C values in soils and respective low TOC indicates inorganic source of Carbon with more inorganic waste components in dumping sites. Regression analysis demonstrated weak positive correlation of OCPs with socioeconomic indices (HDI, Population, waste generation) which is linked with history of use of these contaminants in the respective areas. Over all study shows that OCPs distribution in soils of waste dumping sites is a complex process and depends on environmental factors (soil properties and components, metrological conditions), inherent properties of pollutants as well on socio-economic condition of studied areas (Tables 1 and 2).

3.8. Solid waste prediction for the year 2026: Implication for better waste management strategies Heightened urbanization, industrialization and economic progress leading to enhanced population fundamentally generate massive solid waste in developing world. It has been observed that waste generation increases annually in proportion to the increase in population and urbanization. As concentration of contaminants in environmental matrices and risk to environment and humans is impacted by amount of waste generation and amount of waste in dumping sites, moreover waste management and disposal are also designed on the basis of population and waste generation projections so in current study waste generation quantity for the year 2026 was forecasted as presented in Figure. Projected waste generation showed that the solid waste amount 202

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Table 2 Physico-chemical properties of soil. City

Kamoke Lahore Karachi Sukkur Faisalabad Gujrat Losar Peshawar Hyderabad

Code

KAM-DS-S1 KAM-DS-S2 KAM-DS-S3 LAH-DS-S1 LAH-DS-S2 LAH-DS-S3 KAR-DS-S1 KAR-DS-S2 KAR-DS-S3 SUK-DS-S1 SUK-DS-S2 SUK-DS-S3 FAI-DS-S1 FAI-DS-S2 FAI-DS-S3 GUJ-DS-S1 GUJ-DS-S2 GUJ-DS-S3 LOS-DS-S1 LOS-DS-S2 LOS-DS-S3 PES-DS-S1 PES-DS-S2 PES-DS-S3 HYD-DS-S1 HYD-DS-S2 HYD-DS-S3

pH

8.1 8.0 8.0 8.1 7.9 8.4 8.5 8.4 8.2 8.0 8.0 8.3 9.3 8.7 9.0 7.7 7.7 7.7 8.5 8.3 8.4 7.8 7.9 7.9 8.5 8.5 8.5

EC (mS)

Moisture Content %

2.86 1.94 1.92 0.42 4.28 0.38 0.15 0.21 0.31 0.15 0.13 0.11 0.74 0.80 3.57 0.29 0.14 0.14 0.11 0.68 0.10 3.52 2.40 2.36 0.14 0.10 0.17

19 09 11 07 10 05 14 19 16 10 10 09 02 01 03 07 12 08 16 14 14 20 12 22 13 16 13

Appendix A. Supplementary material

Soil Texture % Sand

% Silt

% Clay

52.0 52.0 52.0 5.50 5.50 5.50 38.7 38.7 38.7 19.0 19.0 19.0 17.0 17.0 17.0 24.0 24.0 24.0 21.1 21.1 21.1 27.0 27.0 27.0 41.0 41.0 41.0

37.0 37.0 37.0 74.0 74.0 74.0 54.0 54.0 54.0 71.0 71.0 71.0 65.0 65.0 65.0 65.6 65.6 65.6 59.0 59.0 59.0 68.5 68.5 68.5 56.7 56.7 56.7

11.0 11.0 11.0 19.5 19.5 19.5 8.00 8.00 8.00 10.0 10.0 10.0 18.0 18.0 18.0 10.4 10.4 10.4 20.0 20.0 20.0 4.50 4.50 4.50 2.30 2.30 2.30

Golchin, A., et al., 1994. Soil structure and carbon cycling. Soil Res. 32, 1043–1068. Gómez, S., et al., 2011. Organochlorine pesticide residues in sediments from coastal environment of Cantabria (northern Spain) and evaluation of the Atlantic Ocean. Environ. Monit. Assess. 176, 385–401. Gonzalez, M., et al., 2005. Evaluation of conventionally and organically produced vegetables for high lipophilic organochlorine pesticide (OCP) residues. Food Chem. Toxicol. 43, 261–269. Gupta, N., et al., 2015. Comparison of organochlorine pesticide levels in soil and groundwater of Agra, India. Ind. Pollut. Control. 2013. Hafeez, M.S., 2013. Comparison of Solid Waste Management Between Oslo (Norway) and Lahore (Pakistan) (Vol. Masters). Norwegian University of Life Sciences (UMB), Oslo, Norway, pp. 1–51. Hou, H., et al., 2013. Organochlorine pesticides and polychlorinated biphenyls in soils surrounding the Tanggu Chemical Industrial District of Tianjin, China. Environ. Sci. Pollut. Res. 20, 3366–3380. Jiries, A.G., et al., 2002. Pesticide and heavy metals residue in wastewater, soil and plants in wastewater disposal site near Al-Lajoun Valley, Karak/Jordan. Water Air Soil Pollut. 133, 97–107. Khajuria, A., et al., 2010. Estimation of municipal solid waste generation and landfill area in Asian developing countries. Khan, A.A., et al., 2012. Issues with solid waste management in South Asian countries: a situational analysis of Pakistan. J. Environ. Occup. Sci. 1, 129–131. Khooharo, A., et al., 2008. An assessment of farmers' level of knowledge about proper usage of pesticides in Sindh Province of Pakistan. Sarhad J. Agric. Khwaja, S., et al., 2013. Monitoring of biochemical effects of organochlorine pesticides on human health. Health 2013. Koelmans, A.A., et al., 2006. Black carbon: the reverse of its dark side. Chemosphere 63, 365–377. Kumar, B., et al., 2011. Persistent organochlorine pesticides and polychlorinated biphenyls in intensive agricultural soils from North India. Soil Water Res. 6, 190–197. Leadprathom, N., et al., 2009. Transport and deposition of organochlorine pesticides from farmland to estuary under tropical regime and their potential risk to aquatic biota. J. Environ. Sci. Health Part B 44, 249–261. Mahmood, A., et al., 2014. Levels, distribution pattern and ecological risk assessment of organochlorines pesticides (OCPs) in water and sediments from two tributaries of the Chenab River, Pakistan. Ecotoxicology 23, 1713–1721. Min, C., et al., 2015. Assessment, composition and possible source of organochlorine pesticides in surface soils from Ürümqi, China. Pedosphere 25, 888–900. Minh, N., et al., 2006. Contamination by persistent organic pollutants in dumping sites of Asian developing countries: implication of emerging pollution sources. Arch. Environ. Contam. Toxicol. 50, 474–481. Nam, J.J., et al., 2008. Relationships between organic matter, black carbon and persistent organic pollutants in European background soils: implications for sources and environmental fate. Environ. Pollut. 156, 809–817. Nasir, J., et al., 2014. Selected organochlorine pesticides and polychlorinated biphenyls in urban atmosphere of Pakistan: concentration, spatial variation and sources. Environ. Sci. Technol. 48, 2610–2618.

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2018.11.020. References Ahad, K., et al., 2010. Monitoring results for organochlorine pesticides in soil and water from selected obsolete pesticide stores in Pakistan. Environ. Monit. Assess. 166, 191–199. Alamdar, A., et al., 2014. Organochlorine pesticides in surface soils from obsolete pesticide dumping ground in Hyderabad City, Pakistan: contamination levels and their potential for air–soil exchange. Sci. Total Environ. 470, 733–741. Ali, U., et al., 2016. Significance of black carbon in the sediment–water partitioning of organochlorine pesticides (OCPs) in the Indus River, Pakistan. Ecotoxicol. Environ. Saf. 126, 177–185. Beg, M.A.A., 2005. Pestic. Toxic., Specif. Polit. 358. Boeckx, P., et al., 2006. Spatial patterns of δ 13 C and δ 15 N in the urban topsoil of Gent, Belgium. Org. Geochem. 37, 1383–1393. Calamari, D., et al., 1995. Relationships between chlorinated hydrocarbons in vegetation and socioeconomic indices on a global scale. Environ. Sci. Technol. 29, 2267–2272. Chakraborty, P., et al., 2010. Selected organochlorine pesticides in the atmosphere of major Indian cities: levels, regional versus local variations, and sources. Environ. Sci. Technol. 44, 8038–8043. Chrysikou, L., et al., 2008. Distribution of persistent organic pollutants, polycyclic aromatic hydrocarbons and trace elements in soil and vegetation following a large scale landfill fire in northern Greece. Environ. Int. 34, 210–225. Do Nascimento, N., et al., 2004. Pollution by hexachlorobenzene and pentachlorophenol in the coastal plain of Sao Paulo state, Brazil. Geoderma 121, 221–232. Ejaz, N., et al., 2010. Environmental impacts of improper solid waste management in developing countries: a case study of Rawalpindi city. Sustain. World 379–388. EPA, U., 1997. Exposure Factor Handbook 1. Exposure Assessment Division Versar Inc. Springfield, VA, pp. 1216. Eqani, S.A.-M.-A.-S., et al., 2011. The level and distribution of selected organochlorine pesticides in sediments from River Chenab, Pakistan. Environ. Geochem. Health 33, 33–47. Fang, Y., et al., 2017. Organochlorine pesticides in soil, air, and vegetation at and around a contaminated site in southwestern China: concentration, transmission, and risk evaluation. Chemosphere 178, 340–349. Gao, F., et al., 2008. Occurrence and ordination of dichlorodiphenyltrichloroethane and hexachlorocyclohexane in agricultural soils from Guangzhou, China. Arch. Environ. Contam. Toxicol. 54, 155–166. Gao, J., et al., 2013. Factors influencing the persistence of organochlorine pesticides in surface soil from the region around the Hongze Lake, China. Sci. Total Environ. 443, 7–13.

203

Ecotoxicology and Environmental Safety 170 (2019) 195–204

M. Sultan et al. Parween, M., et al., 2014. Persistence, variance and toxic levels of organochlorine pesticides in fluvial sediments and the role of black carbon in their retention. Environ. Sci. Pollut. Res. 21, 6525–6546. Qu, C., et al., 2016. The status of organochlorine pesticide contamination in the soils of the Campanian Plain, southern Italy, and correlations with soil properties and cancer risk. Environ. Pollut. 216, 500–511. Rask, H., Schoenau, J., 1993. 13 C natural abundance variations in carbonates and organic carbon from boreal forest wetlands. Biogeochemistry 22, 23–35. Rodríguez-Cruz, M.S., et al., 2006. Field-scale study of the variability in pesticide biodegradation with soil depth and its relationship with soil characteristics. Soil Biol. Biochem. 38, 2910–2918. Škrbić, B., urišić-Mladenović, N., 2007. Principal component analysis for soil contamination with organochlorine compounds. Chemosphere 68, 2144–2152. Sun, K., et al., 2009. Organochlorine pesticides and polybrominated diphenyl ethers in irrigated soils of Beijing, China: levels, inventory and fate. Chemosphere 77, 1199–1205. Syed, J.H., et al., 2013. Organochlorine pesticides in air and soil and estimated air–soil exchange in Punjab, Pakistan. Sci. Total Environ. 444, 491–497. Syed, J.H., et al., 2014. Organochlorine pesticides in surface soils and sediments from obsolete pesticides dumping site near Lahore city, Pakistan: contamination status and

their distribution. Chem. Ecol. 30, 87–96. Tan, L., et al., 2009. Distribution and sources of organochlorine pesticides in water and sediments from Daliao River estuary of Liaodong Bay, Bohai Sea (China). Estuar., Coast. Shelf Sci. 84, 119–127. Veningerová, M., et al., 1997. Analytical methods for the determination of organochlorine compounds: application to environmental samples in the Slovak Republic. J. Chromatogr. A 774, 333–347. Wong, F., et al., 2010. Organochlorine pesticides in soils of Mexico and the potential for soil–air exchange. Environ. Pollut. 158, 749–755. Yadav, I.C., et al., 2016. Occurrence, profile and spatial distribution of organochlorines pesticides in soil of Nepal: implication for source apportionment and health risk assessment. Sci. Total Environ. 573, 1598–1606. Yuan, H., et al., 2017. Historical records and sources of polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in sediment from a representative plateau lake, China. Chemosphere. Zhang, H., et al., 2006. Residues of organochlorine pesticides in Hong Kong soils. Chemosphere 63, 633–641. Zhao, Z., et al., 2017. Spatial correlation analysis of polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in sediments between Taihu Lake and its tributary rivers. Ecotoxicol. Environ. Saf. 142, 117–128.

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