Dispersion of Short- and Medium-Chain Chlorinated Paraffins (CPs

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Dispersion of short- and medium-chain chlorinated paraffins (CPs) from a CP production plant to the surrounding surface soils and coniferous leaves Jiazhi Xu, Yuan Gao, Haijun Zhang, Faqiang Zhan, and Jiping Chen Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03595 • Publication Date (Web): 02 Nov 2016 Downloaded from http://pubs.acs.org on November 2, 2016

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Environmental Science & Technology

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Dispersion of short- and medium-chain chlorinated

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paraffins (CPs) from a CP production plant to the

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surrounding surface soils and coniferous leaves

4

Jiazhi Xu,

5 6 7 8

†,‡

†

†,*

Yuan Gao, Haijun Zhang,

Faqiang Zhan,

†,‡

Jiping Chen†

,*

†

Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China ‡

University of Chinese Academy of Sciences, Beijing 100049, China

TOC/Abstract Art Atmospereic dispersion

CP production

SCCPs CP storage

MCCPs

deposition

9 10 11 12 13 14 15

*Corresponding Authors

16

Phone: +86-411-8437-9972, fax: +86-411-8437-9562; e-mail: [email protected].

17

Phone/fax: +86-411-8437-9562; e-mail: [email protected].

ACS Paragon Plus Environment


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ABSTRACT

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Chlorinated paraffin (CP) production is one important emission source for short- and

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medium-chain CPs (SCCPs and MCCPs) in the environment. In this study, 48 CP congener

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groups were measured in the surface soils and coniferous leaves collected from the inner

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and surrounding environment of a CP production plant that run has been operation for more

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than 30 years to investigate the dispersion and deposition behavior of SCCPs and MCCPs.

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The average concentrations of the sum of SCCPs and MCCPs in the in-plant coniferous

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leaves and surface soils were 4548.7 ng g–1 dry weight (dw) and 3481.8 ng g–1 dw, which

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were 2-fold and10-fold higher than those in the surrounding environment, respectively. The

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Gaussian air pollution model explained the spatial distribution of CPs in the coniferous

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leaves, whereas the dispersion of CPs to the surrounding surface soils fit the Boltzmann

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equation well. Significant fractionation effect was observed for the atmospheric dispersion

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of CPs from the production plant. CP congener groups with higher octanol-air partitioning

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coefficients (KOA) were more predominant in the in-plant environment, whereas ones with

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lower KOA values had the elevated proportion in the surrounding environment. A radius of

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approximately 4-km from the CP production plant was influenced by the atmospheric

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dispersion and deposition of CPs.

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INTRODUCTION

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Chlorinated paraffins (CPs) are complex mixtures of polychlorinated n-alkanes with

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chain lengths between 10 and 30 carbon atoms, containing thousands of congeners, isomers,

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enantiomers and diastereomers.1,2 They are widely used as flame retardants and plasticizers

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in plastics and sealants and as additives in metal-working fluids, lubricants, paints and

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coatings.3 The commercial CP formulations are sub-divided according to their carbon chain

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length into three categories: short-chain CPs (SCCPs, C10–13), medium-chain CPs (MCCPs,

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C14–17) and long-chain CPs (LCCPs, C>17). Among them, SCCPs have been listed as a group

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of candidate persistent organic pollutants (POPs) because of their environmental ACS Paragon Plus Environment

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persistence, long-range transport potential, tendency to bioaccumulate, and high toxicity to

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aquatic organisms.4–7 MCCPs should also be of concern because of their similarities to

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SCCPs with respect to chemical and physical properties.8, 9

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In the last decade, SCCPs and MCCPs have been ubiquitously found in natural

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environmental compartments such as air, water, soil and sediment.10–12 However, the

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understanding of how CPs are released into the environment is still limited. CPs cannot be

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formed naturally, and thus, almost all SCCPs and MCCPs in the environmental matrix are

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emitted from the CP product life cycle, including the production, storage, transport and

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industrial use of CPs, as well as the routine use and waste-disposal of products containing

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CPs.13,14 An emission inventory prediction indicated that the total emission of SCCPs into

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the environment in China was as high as 1789 tons in 2011.15 Therefore, it is urgent to

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investigate the pollution levels of SCCPs and MCCPs in the environments surrounding

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important sources, along with their potential ecological risks.

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CP production is regarded as one important source of SCCPs in the environment. 15, 16 In

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China, a larger quantity of commercial CP mixtures were produced without been classified

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by the carbon chain length. However, the survey data on the emission levels of SCCPs and

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MCCPs from the CP production plant and their levels in the surrounding environment are

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still scarce. CPs are produced by the direct free radical reaction of chlorine with selected

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n-alkanes from petroleum distillation, in which almost no wastewater is discharged and

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only a small volume of waste gas is emitted after a cleaning treatment. Therefore, the

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emission of SCCPs and MCCPs from a CP production plant should mainly occur through

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volatilization and dust drift. The volatilized CPs can partition between the gaseous and

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particulate phases in the atmosphere, which is an important process that affects the

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deposition, degradation and long-range transportation. The wind-blowing dust and larger

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particles bound with CPs tend to be deposited in the ambient environment, which would

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result in the higher pollution levels of SCCPs and MCCPs in the soils surrounding the CP ACS Paragon Plus Environment


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production plant according to Level III fugacity modeling.17 Coniferous leaves, with

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lipid-rich cuticle and stomata structures on its surfaces, are found to have a higher ability to

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trap and accumulate CPs,18–20 and therefore they can be employed as good indicators of

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pollution dispersion of SCCPs and MCCPs from the CPs production plant.

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Although the atmospheric occurrence and deposition of semi-volatile hydrophobic

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organic pollutants (HOCs) in the industrial, urban and suburban sites have been extensively

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investigated, only a few studies modeled the atmospheric dispersion of semi-volatile HOCs

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from the point sources and metropolitan areas.21–23 It was found that the one-dimensional

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Gaussion diffusion model could explain the long-range atmospheric transport of

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semi-volatile HOCs from urban area to the surrounding environment, which was mainly

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driven by wind.21,

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dispersion and the rapid deposition of particle-associated chemical pollutants might be not

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negligible. To our knowledge, the dispersion behavior of semi-volatile HOCs from a single

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non-combustion point source in small scale has been never specifically characterized under

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well-controlled environmental conditions.

22

However, in the small area near the pollution source, the lateral

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In the present study, surface soil and coniferous leaf samples were collected from the

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inner and surrounding environment of a CP production plant in China with a history of CP

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production that exceeded 30 years. The test CP production plant is far away from urban

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areas and other factories. The objectives of this study were to characterize the

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environmental pollution caused by the production of CPs, and to explore the dispersion and

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deposition mechanism of CPs from the CP production plant to the surrounding environment.

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The obtained results will also help understand the short-range dispersion behavior of other

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semi-volatile HOCs from a point source mainly via atmospheric transport.

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EXPERIMENTAL SECTION

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Chemicals and Materials. The standard stock solutions of the SCCPs and MCCPs with

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different chlorine contents were obtained from Dr. Ehrenstorfer GmbH (Augsburg, ACS Paragon Plus Environment

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Germany). An internal standard solution of 13C6-δ-hexachlorocyclohexane (13C6-δ-HCH) in

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n-nonane (100 µg/L) and an recovery standard solution of

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(13C10-trans-CD) in n-nonane (100 µg/L) were both provided by Cambridge Isotope

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Laboratories (Andover, MA, USA). Silica gel (63–100 µm) and basic alumina (Activity

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Super I, 63–200 µm, pH 10) were purchased from Sunchrom (Friedrichshafen, Germany)

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and MP Biomedicals (Eschwege, Germany), respectively. All of the solvents, including

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n-hexane, dichloromethane and n-nonane, were of pesticide residue grade and were

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obtained from J. T. Baker (Phillipsburg, USA).

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Basic Information on the CP Production Plant. The investigated CP production

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plant is located in Dalian city, northeast China. It has a history of CP production that

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exceeds 30 years, and the annual CP production is approximately 50,000 tons. CP mixtures

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are produced from C9–28-n-alkanes using the method of photochemical-thermal chlorination,

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in which no wastewater or solid waste is emitted. The hydrogen chloride produced from

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chlorination together with the unreacted chlorine gas is recovered by a two-stage falling

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film absorber combined with an alkali absorption tower, and then the tail gas is emitted to

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the atmosphere. Commercial CP mixtures, CP-42 (CPs with a chlorine content of 42%),

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CP-52 and CP-70, are mainly produced. SCCPs in these industrial CP mixtures, sampled

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from the plant in 2014, were analyzed using carbon skeleton gas chromatography method

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described by Koh et al.

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1.3 mg/g, 114.0 mg/g and 200.5 mg/g in CP-42, CP-52 and CP-70, respectively.

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Sample Collection. A total of 50 environmental samples, including 25 surface soil

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samples, 16 pine (Pinus thunbergii) needle samples, 7 cypress (Sabina chinensis) leaf

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samples and 2 spruce (Picea koraiensis) needle samples, were collected from the inner and

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surrounding environment of the investigated CP production plant from October 2013 to

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April 2014. The spatial distribution of the sampling sites is shown in Figure 1. The soil

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samples were collected from uncultivated land. Five separate soil subsamples at a depth of

24

13

C10-trans-chlordane

The total SCCP (ΣSCCPs) concentrations were determined to be



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0–5 cm were taken using a stainless steel scoop and were then mixed together to form a

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composite sample. Pine and spruce needles as well as cypress leaves were collected at the

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heights of 2–4 m and 0.7–1.2 m above the ground level, respectively. Several small

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branches were cut off of a tree using steel scissors, and all of the coniferous leaves on the

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branches were collected without distinguishing ages. The coniferous leaves were sampled

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from 4–6 trees and then mixed to form a composite sample. The collected samples were

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packed in pre-cleaned self-sealing polyethylene bags with zippers, and transported to the

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laboratory. Surface soil samples were freeze-dried, ground and homogenized by passing a

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stainless steel 60-mesh sieve. Leaf samples were freeze-dried and ground under a liquid

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nitrogen atmosphere. The lyophilized samples of the surface soils and tree leaves were

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stored in pre-cleaned brown glass bottles at –20 °C until analysis.

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Sample Extraction and Cleanup. After spiking with an aliquot of the

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internal standard, the surface soil and tree leaf samples were Soxhlet extracted with 250 mL

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of hexane/dichloromethane (1:1, v/v) for 20 h. The lipids in the leaf extracts and the

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sulfur-containing compounds in the soil extracts were removed using a concentrated

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sulfuric acid treatment and activated copper powder treatment, respectively. The

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concentrated extracts were subjected to a successive cleanup procedure, multi-layer silica

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gel column and subsequent basic alumina column. The clean extract was gradually

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transferred to a micro-vial, evaporated to near dryness with a nitrogen stream, and then

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re-dissolved in 40 µL of the recovery standard solution for instrumental analysis. The

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detailed information on the sample extraction and cleanup can be seen in the Supporting

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Information (SI).

144


13

C6-δ-HCH

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N

24 26

21

22 W

E

16

S

15 14 12 13

7 9

17

10

8 5

1 3

2

19 4

6

11

Surface Soil Coniferous leaves

18 23

20 25

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Figure 1. Map of the study areas and sampling sites. ☆ represents the location of the CP production

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plant.

148 149

Instrumental Analysis and Quantification. Measurements of the SCCPs and MCCPs

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were carried out on a Shimadzu GCMS-QP2010 plus system operating in ECNI mode with

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a splitless injection. The GC was equipped with a DB-5 capillary column (15 m × 0.25 mm

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i.d. × 0.25 µm film thickness, J&W Scientific, U.S.). The temperature program was set as

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follows: initially 100 °C for 2 min, ramped to 260 °C at 20 °C/min and held for 2 min, and

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then ramped to 310 °C at 30 °C/min and held for 12 min. Helium and methane (99.995%

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purity) were used as the carrier gas and reagent gas, respectively. The ion source, transfer

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line and injector temperatures were kept at 200 °C, 280 °C and 280 °C, respectively.

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Selected ion monitoring (SIM) mode was applied for the detection of the most abundant

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signal within the isotope clusters of the [M−Cl]− fragment ion for each CP congener group.

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A total of 48 CP congener groups with carbon chain lengths of 10−17 and chlorine atom

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numbers of 5−10 were monitored. Comparisons of the retention time, signal profile, and

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corrected isotope ratio between the samples and standards were conducted for the

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identification of possible interferences from the CPs themselves and other interfering



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compounds. For each sample, two individual injections were executed for the detection of

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the SCCPs and MCCPs, respectively.

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The signal response interferences between the SCCP and MCCP congener groups were

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deducted using the calculation methods described by Zeng et al.,25 with minor modification.

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The corrected chromatographic peak areas of the SCCP and MCCP congener groups were

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used for the quantifications according to the procedure described by Reth et al..26 A linear

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correlation was obtained between the total response factors of reference CP mixture

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standards and their calculated chlorine contents, which was allowed to compensate the

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effect of the chlorine content differences on the total response factors between the CPs in

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the environmental samples and the reference CP mixture standards. The detailed

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instrumental analytical method and quantification are shown in the SI.

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The total organic carbon (TOC) content in the surface soils was analyzed using the

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high-temperature combustion method with a total organic carbon analyzer (Vario TOC

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cube, Elementar, Germany). Each sample was pretreated with 1 mol/L HCl to remove the

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carbonate residues for the TOC measurements. The lipid content in the leaf samples was

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determined by a gravimetric method (extraction with petroleum ether).

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Quality Assurance and Quality Control. All of the glassware was rinsed in triplicate

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with n-hexane before use. The procedural and solvent blanks were included in each batch of

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5 samples. No CPs was detected in the procedural and solvent blanks. The procedural

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blanks spiked with a small quantity of SCCP and MCCP mixture standards were used to

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determine the method detection limits (MDL), which was calculated as three times the

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standard deviation at 6 time measurements. The MDL values for the total SCCPs (ΣSCCPs)

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were estimated to be 1.62 ng g–1 dry weight (dw) for surface soils and 8.09 ng g–1 dw for

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leaf samples; and the corresponding values for the total MCCPs (ΣMCCPs) were estimated

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to be 2.34 ng g–1 dw for surface soils and 11.70 ng g–1 dw for leaf samples. The recoveries

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of the internal standard

13

C6-δ-HCH in all of the samples were in the range of


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65.7%–118.6%. The reported data in this study were not blank and surrogate recovery

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corrected. As for the samples in triplicate, the relative standard deviations for the

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quantification of the total SCCPs and total MCCPs were both < 18%.

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Data Processing. Partial least squares discriminant analysis (PLS-DA) was applied with

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unit variance (UV) scaling to characterize the congener group distribution of the SCCPs

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and MCCPs. Concentrations that were below the MDL values were assigned a value of

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zero before conducting PLS-DA. All statistics and drawings were conducted using the

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following software: ArcGIS 10.3 (Esri Inc., USA), Origin 8.5 (OriginLab Inc., USA),

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SigmaPlot 12.0 (SigmaPlot Software Inc.), SIMCA-P11.5 (Umetrics, Sweden), Surfer 11

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(Golden Software Inc.) and SPSS PASW (SPSS Inc., Chicago, IL).

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RESULTS AND DISCUSSION

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Concentrations and Spatial Distribution of the SCCPs and MCCPs in

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Coniferous Leaves. Coniferous leaves can serve as a passive air sampler that integrates

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the gas and particulate phase associated pollutants over the years and provides averaged

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information about the contamination level.27 In this study, SCCPs and MCCPs were found

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at quantifiable concentrations in all of the coniferous leaf samples. The concentrations were

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in the ranges of 218.7–2196.6 ng g–1 dw for the ΣSCCPs, 337.8–4388.4 ng g–1 dw for the

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ΣMCCPs, and 745.8–6585.0 ng g–1 dw for the sum of the SCCPs and MCCPs (Table 1 and

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Table S3), respectively. The highest concentrations of the ΣSCCPs (2196.6 ng g–1 dw) and

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ΣMCCPs (4388.4 ng g–1 dw) were both detected in the cypress leaves sampled at site 2

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inner the CP production plant (Figure 1 and Table S3). Spruce needles from sampling site 3,

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located approximately 500 m away from the CP plant, also showed higher concentrations of

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ΣSCCPs (1742.2 ng g–1) and ΣMCCPs (3711.1 ng g–1). The ΣSCCP and ΣMCCP

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concentrations in the other coniferous leaf samples from the CP production plant

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surroundings were in the ranges of 218.7–1441.2 ng g–1 dw (average: 653.7 ng g–1 dw) and

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337.8–3586.5 ng g–1 dw (average: 1585.2 ng g–1 dw), respectively. The pollution levels ACS Paragon Plus Environment


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were much higher than those in spruce needles in the European Alps (total CPs level:

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26–450 ng g–1 dw)18 and those in most Masson pine needle samples from Shanghai

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(geometric means: 63.7 ng g–1 dw for ΣSCCPs, 677 ng g–1 dw for ΣMCCPs),20 while they

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are comparable to those in pine needles from Beijing (ΣSCCPs: 400–4010 ng g–1 dw).19

219 220

Table 1. The ΣSCCP and ΣMCCP concentrations (range and mean in parenthesis) in the

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collected surface soils and coniferous leaves

Samples

In-plant coniferous leaves

Ambient coniferous leaves

In-plant surface soils

Ambient surface soils

No

Total SCCPs

Total MCCPs

SCCPs + MCCPs

.

(ng/g dw)

(ng/g dw)

(ng/g dw)

1280.9–2196.6

1231.5-4388.4

2512.4–6585.0

(1738.7)

(2809.9)

(4548.7)

218.7–1742.2 (701.0)

337.8–3711.1 (1677.7)

745.8–5453.3 (2378.7)

1018.4–1824.4

2028.0–2074.8

3093.2–3870.4

(1421.4)

(2051.4)

(3481.8)

24.8–481.6 (141.9)

19.3–1460.6 (199.4)

63.8–1884.4 (341.4)

2

23

2

23

222 223

The extractable lipid contents in the collected coniferous leaves ranged from 4.1% to

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9.8% with an average of 7.4%. The lipid contents in the cypress leaves (average: 8.2%)

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were found to be significantly higher than those in pine needles (average: 7.0%).

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Nevertheless, there was no significant difference between the CP concentrations in these

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two types of leaves sampled from adjacent sites. This suggested that the accumulation

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levels of the CPs in the coniferous leaves from the environment surrounding the CP

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production plant should mainly depend on the pollution diffusion gradient and rely less on

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the lipid content in the coniferous leaves.

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The spatial distributions of the SCCPs and MCCPs in the coniferous leaves were also

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presented in Figure 2. Within a 1.5-km radius of the production plant, the concentrations of

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ΣSCCPs and ΣMCCPs in the coniferous leaves both showed a rapidly decreasing tendency

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from the center of the CP production plant to the surrounding environment. The pine


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needles sampled from sites 7 and 22, located near the small residential areas, showed an

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abruptly elevated concentration of ΣMCCPs (Figure 1 and Table S3), and thus, resulted in

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two unexpected pollution dispersion sources in the iso-concentration map (Figure 2b). One

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was located approximately 1.6 km northwest of the CP production plant and another was

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located approximately 5.4 km north of the CP production plant. The pollution dispersion

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from the CP production plant could not provide an adequate explanation for the abruptly

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elevated concentrations, and therefore, the most probable cause was the incidental pollution

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as a result of residential activity.

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244 245

Figure 2. Iso-concentration maps of CPs in the inner and surrounding environment of the

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tested CP production plant. a: ΣSCCPs in coniferous leaves, b: ΣMCCPs in coniferous leaves, c:

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the sum of SCCPs and MCCPs in coniferous leaves, d: ΣSCCPs in surface soils, e: ΣMCCPs in

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surface soils, and f: the sum of SCCPs and MCCPs in surface soils.



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In environmental science, Gaussian air pollution models are successfully employed to

251

predict the short-range dispersion of both gaseous pollutants and particles from a point

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source with simplifying assumptions that landscape is approximately flat and unobstructed,

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and only dry deposition occurs.28–31 In this study, there were 3 low hills in the sampling

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area. Nevertheless, the altitude differences for all of the sampling sites were less than 20 m.

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Therefore, the dispersion process of the CPs from the production plant to the surrounding

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coniferous leaves should essentially agree with the simplifying assumptions of Gaussian air

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pollution models.

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The coniferous leaves generally accumulated CPs from the atmosphere for 0.5–3 years.

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During this period, the atmospheric stability and downwind speed often varies according to

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the weather. In sampling area, the static wind weather (wind speed < 0.5 m/s) accounts for

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about 140–180 days per year. The average wind speed is about 3.3 m/s, and the wind

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directions occurred at almost all the orientations (Figure S1). Therefore, the lateral diffusion

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and the wind speed can both exert the significant influence on the atmospheric dispersion of

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CPs from the CPs production plant in small scale. In addition, the emission rate of CPs

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(mainly via volatilization) also largely changed with the production activity intensity and

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weather temperature. When considering that the accumulation of CPs in coniferous leaves

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results from the long-term atmospheric deposition, the parameters reflecting dispersion,

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wind speed and emission rate can be assumed to constants. Therefore, the Gaussian air

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pollution model can be simplified to

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 1 y Ci = C 0 + A × exp  −   2  σ y 

   

2

   

(4)

271

where Ci and Co are the actual and background concentrations of CPs in coniferous leaves,

272

respectively; y is the lateral distance from the source, and σy is a lateral dispersion

273

coefficient; A is a constant, reflecting the overall average results of vertical dispersion,


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lateral dispersion, wind speed and emission rate. The detailed derivation of eq. 1 is shown

275

in Supporting Information.

276

The derived Gaussian air pollution model (eq. 1) well fit the relationship between CP

277

concentrations in the coniferous leaf samples and the distances of the sampling sites from

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the center of the production plant (Figure 3a, Table S5). The fitted data were all

279

significantly (P < 0.01) correlated to the determined data for the ΣSCCPs (r = 0.709),

280

ΣMCCPs (r = 0.595) and their sum (r = 0.681). These results indicate that the Gaussian air

281

pollution model can predict the dispersion process of the CPs from the production plant to

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the surrounding coniferous leaves.

283 284

Figure 3. Concentrations of the CPs in coniferous leaves and surface soils as a function of the

285

distances from the center of the tested CP production plant, together with the fitting curves of

286

Gaussian (a) and Boltzmann (b), respectively.

287 288

Concentrations and Spatial Distribution of the SCCPs and MCCPs in the

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Surface Soils. SCCPs and MCCPs were also detected out in all of the surface soil

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samples. The ΣSCCP and ΣMCCP concentrations were in the ranges of 24.8–1842.4 ng g–1

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dw and 19.3–2074.8 ng g–1 dw, respectively (Table 1). The highest ΣSCCP (1842.4 ng g–1)

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and ΣMCCP (2074.8 ng g–1) concentrations in soils were found at site 1 and site 2 inner the

293

CP production plant, respectively (Figure 1 and Table S4). Surface soil from sampling site 3,



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located approximately 500 m away from the CP plant, also showed significantly high

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ΣSCCP (423.9 ng g–1) and ΣMCCP (1460.6 ng g–1) concentrations. The ΣSCCP and

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ΣMCCP concentrations in the other ambient surface soils ranged from 24.8 ng g–1 dw to

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481.6 ng g–1 dw with an average of 141.9 ng g–1 dw and from 19.3 ng g–1 dw to 1460.6 ng

298

g–1 dw with an average of 199.4 ng g–1 dw, respectively. The pollution levels were much

299

higher than those in background soils from Western Europe (ΣSCCPs:

Dispersion of Short- and Medium-Chain Chlorinated Paraffins (CPs

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