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Identifying iron foundries as a new source of unintentional polychlorinated naphthalenes and characterizing their emission profiles Guorui Liu, Pu LV, Xiaoxu Jiang, Zhiqiang Nie, and Minghui Zheng Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es503161v • Publication Date (Web): 14 Oct 2014 Downloaded from http://pubs.acs.org on October 17, 2014

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Environmental Science & Technology

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Identifying iron foundries as a new source of unintentional

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polychlorinated naphthalenes and characterizing their emission

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profiles

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Guorui Liu1, Pu Lv1,2, Xiaoxu Jiang1, Zhiqiang Nie1, Minghui Zheng1,∗

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1

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Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871,

7

Beijing 100085, China

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2

9

China

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research

Beijing China Sciences General Energy & Environment Co, Ltd. Beijing 100036,

10 11 12



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E-mail address: [email protected] (M. Zheng).

Corresponding author. Tel.: +86 10 6284 9172; fax: +86 10 6292 3563.

14 15

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ABSTRACT

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Iron foundries have been identified as dioxin sources in previous field

18

investigations. Similar formation mechanisms between dioxins and unintentional

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polychlorinated naphthalenes (PCNs) have led us to speculate that iron foundries are

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also potential PCN sources. In this study, PCNs in stack gas and fly ash samples

21

representing atmospheric and residue emissions from 13 typical iron foundry plants

22

were analyzed. The average emission factor of ∑2-8PCNs to residue was calculated to

23

be 61 µg t−1, with a range of 10–107 µg t−1. The emission factors of ∑2-8PCNs to air in

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two case plants were 267 and 1472 µg t−1. The derived emission factors might be

25

useful for estimating annual emissions and understanding the contribution of PCNs

26

from iron foundries. The possible formation mechanisms of PCNs, based on the PCN

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profiles, are discussed. Successive reductions in the abundance of homologs were

28

observed to occur with the increase in chlorine substituted numbers. Abundances of

29

congeners containing more β-position chlorines in the naphthalene skeleton were

30

much higher than those of congeners containing more α-position chlorines for penta-,

31

hexa- and hepta- homologs, which suggests that the β-positions are favored for

32

chlorination. Potential chlorination pathways from tetra- to octa- homologs are

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proposed.

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INTRODUCTION

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Polychlorinated naphthalenes (PCNs), which have a similar structure (Figure 1)

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and toxicity to polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated

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dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyl (dl-PCBs), are

41

ubiquitous persistent organic pollutants (POPs).1-3 Studies associated with the

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comparison of PCNs, PCDDs, PCDFs, and dl-PCBs in environmental matrices, biota,

43

and human samples from some areas have suggested that PCNs might have

44

comparable or even higher toxic equivalents (TEQs) than PCDDs, PCDFs, and

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dl-PCBs.4-6 Moreover, the POP review committee (POPRC) has reviewed PCNs

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according to the screening criteria in Annex D covered under the Stockholm

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Convention on POPs. The POPRC concluded that di- to octa-chlorinated homologs of

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PCNs meet the screening criteria of POPs, and has therefore listed PCNs as candidate

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POPs for eliminating their unintentional emissions and banning their manufacture and

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use in technical formulations.

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The manufacture and use of technical PCN formulations has almost ceased

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globally, while industrial activities, including waste incineration and metal smelting,

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are widely considered to be the current important sources of unintentional PCNs into

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air.7,8 Metal smelting industries are considered to be much more important sources of

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unintentional POPs than before, and their relative importance is considered to be

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higher than that of waste incineration.9,10 Some widely recognized smelting sources of

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unintentional POPs, including iron ore sintering, electric arc furnace for steel making, 3

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and secondary nonferrous smelting processes, have been investigated for PCN

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emissions.11-14 However, for some important industries with intensive activities in

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developing countries, there are still no available data or knowledge about emission

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levels and profiles of PCNs. Identifying potential sources of unintentional PCNs is the

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essential primary step for evaluating source priority and implementing emission

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controls. Thus, it is important to identify potential industrial sources, particularly from

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industries with intensive activities in developing countries, and to estimate and

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characterize their PCN emissions.

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Iron foundry is an important industry in China. There are several thousand iron

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foundries of different scales, employing different techniques in China. The annual

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production of cast iron from these plants accounted for about 30% of world

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production.15 Thus, the investigation of PCN emissions from Chinese iron foundries

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will likely be important for the preliminary estimation of total global PCN emissions.

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In our previous study, an intensive investigation of 14 plants of different scales and

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employing different techniques was carried out to estimate and characterize the

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emission levels and profiles of PCDD/Fs and dl-PCBs from Chinese iron foundries.

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Co-occurrence and similar formation mechanism between PCNs and PCDD/Fs have

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been reported.16-18 Thus, we speculate that iron foundries might also be important

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potential sources of PCNs. However, there are still no available data or knowledge

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about PCN levels, profiles, and emission factors from iron foundries to date.

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In this study, stack gas and fly ash samples representing atmospheric and residue 4

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emissions collected from the 13 plants used in our previous study15 were analyzed for

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PCNs by isotopic dilution high-resolution gas chromatography combined with a

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high-resolution mass spectrometer (HRGC/HRMS) technique. To our knowledge, this

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is the first intensive investigation of PCN emission concentrations, profiles, and

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emission factors from the iron foundry industry, which is potentially important for

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recognizing this new source of PCNs, for estimating and characterizing emission

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levels and profiles, and for the development of an emission inventory of unintentional

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PCNs from industrial thermal sources.

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EXPERIMENTAL SECTION

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Information on the investigated iron foundry plants

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Iron foundries normally adopt cupola furnaces for metal smelting and refining in

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China. By this method, metals or alloys are melted and prepared in a furnace, and

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molten metal is poured into the assembled mold, either via a ladle or directly from the

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furnace. When the metal has cooled, the mold and core material are removed and the

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casting is cleaned and dressed. A cupola furnace is a tall, vertical furnace, open at the

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top with hinged doors at the bottom. It is charged from the top with alternate layers of

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coke, limestone, and metal; the molten metal is removed from the bottom. Air is

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blown through the charge from openings at the bottom and the combustion of coke

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heats, melts, and purifies the iron.

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It is widely recognized that the scale, raw materials, process technique, and air 5

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pollution control system (APCS) are important factors influencing the formation and

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emission of unintentional POPs during industrial thermal processes.19-21 Stack gas and

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fly ash samples normally represent the atmospheric and residue emissions of

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unintentional POPs from industrial thermal sources.13,22 Thus, 14 typical iron

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foundries were chosen for our previous study; plants were selected based on their

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scale, raw materials used, technique, and APCS, and stack gas and fly ash samples

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were analyzed to estimate and characterize the levels and profiles of PCDD/Fs and

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dl-PCBs in our previous study.15 At present, routine monitoring of PCNs, PCDD/Fs,

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and dl-PCBs is normally not required for iron foundries because no regulations on

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these compounds exist. Thus, the sampling point set in most of the iron foundry plants

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in China for monitoring common pollutants such as nitrogen and sulfur oxides is not

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suitable for field sampling of stack gas using automatic isokinetic sampling

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equipment for monitoring dioxins and dioxin-like compounds. Finally, two iron

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foundry plants equipped with sampling points suitable for automatic isokinetic

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sampling by a TCR system (TECORA, Italy) were investigated for preliminarily

115

evaluating stack gas emissions of unintentional POPs. Solid residue is evaluated as an

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important medium for POP emissions. Moreover, solid residue, especially for fly ash,

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has been widely recognized as an important matrix for promoting formation of

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unintentional POPs during industrial thermal processes.23,24 Thus, solid residue

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samples were collected for the evaluation of POP contamination from those iron

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foundries. 6

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The annual capacity of the iron foundry plants investigated in our previous study

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ranged from 1 to 200 thousand tons.15 The normally adopted furnaces in China

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comprising hot air cupola and cold air cupola were involved in those investigated

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plants. The raw materials used in the investigated plants were iron ore lump, sinter, or

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scrap. The adopted APCS in the investigated plants were fabric filter, cyclone, or wet

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scrubber systems. A large amount of air was introduced into the APCS to cool the flue

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gas. The output volume of stack gases ranged from about 14000–36500 m3 t−1 for the

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EF and LF case plants. One plant that is not equipped with any APCS was also

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included in the study. Basic information on the iron foundries was reported in our

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previous publication15 and is provided in Table 1. In this study, the stack gas and fly

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ash samples from those plants were analyzed by isotopic dilution HRGC/HRMS for

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the purpose of obtaining the emission concentrations, profiles, and emission factors of

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PCNs from iron foundries.

134 135

Sample collection, preparation, and chemical analysis of PCNs

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An automatic isokinetic sampling system (TECORA) was used for the collection

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of stack gas samples in our previous studies.13,15,25 The sampling train was mainly

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composed of a heated probe, a filter box equipped with a quartz fiber filter and a

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water-cooled XAD-2 adsorbent trap. The glass fiber filter was used to collect

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particle-bound pollutants, and XAD-2 adsorbent resin was used for trapping the

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vapor-phase contaminants. A detailed description of the collection of stack gas 7

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samples has been provided in previous publications.13,15,25 The fly ash samples were

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collected from fabric filter or cyclone filters, and filter cakes were collected from wet

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scrubbers. For the plant that has a cupola furnace not equipped with any APCS, the

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fugitive ash samples were collected from around the ground surface.15

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PCNs were analyzed by isotope dilution HRGC/HRMS, which has been

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described previously.13,26 Briefly, the samples were spiked with known amounts of

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13

149

13

150

13

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fly ash samples, samples were digested with 1 mol L−1 hydrochloric acid, rinsed with

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deionized water, and dried completely before Soxhlet extraction. Those samples were

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then Soxhlet extracted for approximately 24 h. The extracts were concentrated, then

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subjected to column cleanups, including silica gel treated with 44% (by weight)

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sulfuric acid, multilayer silica gel columns, and basic alumina columns. The final

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extracts were reduced to about 20 µL and a 13C10-123457-hexaCN injection standard

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(catalog no. ECN-5260; Cambridge Isotope Laboratories, Cambridge, MA, USA) was

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added prior to instrumental analysis. Peaks of congeners were identified based on

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retention time compared with available individual standards and ion ratios, and

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considering the elution order on the DB-5 column. Peaks were quantified if

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target/qualifier ion ratios were within 15% of theoretical values. The recoveries of

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13

C10-labeled

PCN

internal

13

C10-1234-tetraCN, C10-123567-hexaCN,

standards

13

(catalog

no.

containing

13

C10-1357-tetraCN,

C10-1234567-heptaCN, and

ECN-5102,

C10-12357-pentaCN,

13

C10-12345678-octaCN). For

C10-PCN internal standards relative to labeled injection standards in the samples 8

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were evaluated in this study. The recoveries of internal standards were 56−108% for

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13

165

13

166

13

C10-1234-tetraCN, C10-12357-pentaCN,

51−112% 69−121%

13

for

C10-1357-tetraCN,

13

for

C10-123567-hexaCN,

49−85% 52−88%

for for

C10-1234567-heptaCN, and 35−62% for 13C10-12345678-octaCN.

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RESULTS AND DISCUSSION

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Concentrations and TEQs of PCNs in fly ash and stack gas samples

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PCNs have been proposed to be included in the list of POPs covered under the

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Stockholm Convention. The POP review committee evaluated the properties of PCNs

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and concluded that the homologs from di- to octa-chlorinated naphthalenes meet the

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four main characteristics of POPs. Thus, the total PCNs (∑2-8PCNs) were termed the

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sum of di- to octa-homologs in this study. As shown in Table 1, the concentration of

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∑2-8PCNs in fly ash samples ranged from 665–7664 pg g−1, with an average value (±

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standard deviation) of 2497 ± 2297 pg g−1. The median and geomean values of

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∑2-8PCNs in fly ash samples were 1649 and 1896 pg g−1, respectively. The

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concentrations of ∑2-8PCNs in the stack gas samples were converted to dry standard

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conditions (273 K and 101.3 kPa). The average concentrations of ∑2-8PCNs in stack

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gas samples were 7339 pg m−3 for the EF plant and 104445 pg m−3 for the LF plant.

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PCNs could induce aryl hydrocarbon receptor-mediated responses and thus

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display similar toxic mechanisms to dioxins.27,28 Toxic equivalent factors (TEFs) of

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several PCN congeners relative to 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) 9

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have been studied.27-31 Noma et al. summarized the TEF of PCN congeners in 2004,32

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and Falandysz et al. (2013) recently evaluated and updated the relative potency

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factors of PCN congeners relative to 2,3,7,8-TCDD.33 In this study, the TEFs of

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several PCN congeners summarized by Noma et al.32 were used for the calculation of

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∑2-8PCN TEQs for facilitating the comparison with other industrial sources reported

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in previous publications.11-13,25,34 The ∑2-8PCN TEQs in fly ash samples ranged from

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0.01–1.04 pg TEQ g−1, with an average value (± standard deviation) of 0.19 ± 0.34 pg

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TEQ g−1. The median and geomean values of ∑2-8PCN TEQs in fly ash samples were

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0.05 and 0.07 pg TEQ g−1, respectively. The average TEQs of ∑2-8PCNs in stack gas

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samples were 0.49 pg TEQ m−3 for the EF plant and 1.90 pg TEQ m−3 for the LF

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plant.

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To our knowledge, this study is the first intensive investigation of the

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concentrations of PCNs in fly ash and stack gas samples from iron foundries, and no

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other published data on PCN levels from iron foundries are available for comparison.

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In our previous studies, we have investigated and reported PCN levels from metal

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smelting processes, including primary copper (5.8–253 ng m−3 in stack gas, 18.4–164

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ng g−1 in fly ash) and magnesium (2.5–93.4 ng m−3 in stack gas, 0.18–0.49 ng g−1 in

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fly ash) smelting, secondary copper (41.3–1107 ng m−3 in stack gas, 9.5–20840 ng g−1

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in fly ash), aluminum (98.9–2245 ng m−3 in stack gas, 6.9–6000 ng g−1 in fly ash),

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zinc (8021 ng m−3 in stack gas, 2670 ng g−1 in fly ash), and lead (887 ng m−3 in stack

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gas, 2.3 ng g−1 in fly ash) smelting, iron ore sintering (3–983 ng m−3 in stack gas), and 10

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electric arc furnace for steel-making processes (458–1099 ng m−3 in stack gas).11-14,35

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The levels of PCNs in fly ash samples from iron foundries were far lower than those

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of secondary copper, aluminum, and zinc smelting processes, and were higher than

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those of primary magnesium smelting processes. In our previous investigation, we

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analyzed PCDD/Fs in those samples.15 Although the mass concentrations of PCNs

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(7339–104445 pg m−3 in stack gas, 665–7664 pg g−1 in fly ash) were higher than those

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of PCDD/Fs (712–2619 pg m−3 in stack gas, 8.13–983 pg g−1 in fly ash), the PCN

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TEQs (0.49–1.90 pg TEQ m−3 in stack gas, 0.01–1.04 pg TEQ g−1 in fly ash) were far

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lower than those of PCDD/Fs (56.5–232 pg TEQ m−3 in stack gas, 1.83–57.6 pg TEQ

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g−1 in fly ash) as a result of the much lower TEF of PCN congeners compared with

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those of PCDD/F congeners. The correlations between PCNs and PCDD/Fs produced

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from iron foundry processes were examined in this study (Figure S1, Supporting

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Information). There were no significant correlations between PCNs and PCDDs

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observed for iron foundry processes. The correlation coefficients (R) between PCNs

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and PCDFs were about 0.7. The much closer correlation observed between PCNs and

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PCDFs than that observed between PCNs and PCDDs for iron foundry processes is in

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agreement with correlations reported for waste incineration processes.17

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Raw materials, scale, and technique employed might be important factors

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influencing emissions of unintentional POPs during industrial thermal processes. The

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possible influences of raw materials, furnace types, and plant scales on PCN

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concentrations in fly ash samples were preliminarily discussed in this study. There 11

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were no significant correlations observed between plant scale and emission

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concentrations in fly ash samples for iron foundries in this study. The emission

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concentrations of PCNs were evaluated according to the classification of the furnace

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types and raw materials. The average concentration of PCNs in fly ash was 5080 pg

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g−1 (geomean value: 3278 pg g−1; median: 6910 pg g−1; range: 665–7664 pg g−1) for

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plants using cold air cupola furnaces with scrap as raw materials; this was higher than

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the average concentration of plants using hot air cupola furnaces with scrap as raw

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materials, which had an average value of 1827 pg g−1 (geomean value: 1805 pg g−1;

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median: 1649 pg g−1; range: 1501–2205 pg g−1). For plants with iron ore lump as raw

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materials using hot air cupola furnaces, the average concentration of PCNs in fly ash

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was 1489 pg g−1 (geomean value: 1418 pg g−1; median: 1379 pg g−1; range: 980–2108

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pg g−1). Thus, the preliminary comparison results show that the PCN concentrations in

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fly ash samples from iron foundries using scrap as raw materials were slightly higher

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than those of iron foundries using iron ore lump as raw materials when both types of

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plants used hot air cupola furnaces. The concentrations of PCNs in fly ash samples

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from the plants using sinter as raw materials were lower than the average values in fly

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ash samples of plants using scrap or iron ore lump as raw materials when all plants

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used hot air cupola furnaces. The possible occurrence of organic impurities in scrap

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might be an important factor contributing to the higher concentrations of PCNs in fly

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ash from plants using scrap as raw materials. However, further simulation studies are

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needed to clarify the underlying factors influencing PCN emission levels. 12

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Homolog distribution and congener profiles of PCNs in stack gas and fly ash

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samples

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Homolog distribution and congener profiles of PCNs might provide useful

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information for understanding the formation mechanism of PCNs. In this study, the

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homolog concentrations were normalized to the ∑2-8PCN, and the PCN homolog

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distributions in the fly ash and stack gas samples from iron foundries are shown in

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Figure 2. As seen in Figure 2, the homolog patterns were dominated by the

254

tri-chlorinated homologs, followed by the di- and tetra-chlorinated homologs.

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Generally, successive reductions of homologs (through tri- to octa-homologs) were

256

observed to occur with the increase in chlorine substituted numbers, which indicates

257

that chlorination might be an important pathway for PCN formation. The homolog

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distributions of PCNs between fly ash and stack gas emissions were very similar,

259

indicating possible similar formation mechanisms of PCNs in both fly ash and stack

260

gas phases.

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The concentrations of PCN congeners were expressed as the fractions of their

262

corresponding homolog concentrations to obtain a clear comparison of congener

263

abundances in respective homologs. The PCN patterns in stack gas from EF and LF

264

foundry plants are compared in Figure S2 (Supporting Information). Although the

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difference in concentrations between EF and LF plants was large, the PCN patterns in

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stack gas from the two plants were generally similar (Figure S2). Hierarchical cluster

267

analysis (HCA) has been widely used to compare congener patterns between dioxins 13

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and dioxin-like compounds.11,17 In this study, HCA was adopted to cluster the fly ash

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samples based on the PCN congener profiles. Three clusters of fly ash samples were

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obtained (Figure S3). The average PCN profiles of each cluster are presented in

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Figure S4. The fractions of 14/16-DiCN and 145-TiCN in cluster 1 were higher than

272

that in cluster 2 and 3. For the tetra-homolog, the fractions of 1368/1256-, 1234-, and

273

1267-TeCN in cluster 3 were higher than those in clusters 1 and 2, while the fractions

274

of 2367/1248-, 1258/1268-, and 1458-TeCN, in cluster 3 were lower than in clusters 1

275

and 2. The congener fractions of 12356- and 12367-PeCN in cluster 3 were higher

276

than in clusters 1 and 2. The fractions of 12358/12368- and 12345-PeCN in cluster 3

277

were lower than those in clusters 1 and 2, while for hexa- and hepta-homologs, the

278

congener profiles were similar between the three clusters.

279

The average congener profiles are shown in Figure 3. As seen in the figure, the

280

lower chlorinated homologs displayed relatively even isomer distribution patterns.

281

The formation of several 18- and 128-congeners indicate that the chlorination of

282

α-positions of the naphthalene ring were thermodynamically unfavorable;36 these

283

congeners were also found in very low abundances in samples from waste

284

incineration under normal combustion conditions.37 In this study, the abundances of

285

18- and 128-congeners in iron foundry processes were very low. For the tetraCN

286

homolog, congeners comprising 1257/1246/1247-, 1467-, 1368/1256-, 1234-, and

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1267-chlorinated congeners were dominant over other congeners in both fly ash and

288

stack gas emissions. Those congeners are substituted by two β- and two α-position 14

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chlorines with the exception of the 1267-congener with three β- and one α-position

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chlorines. With the successive chlorination of PCNs, the abundances of congeners

291

with more β-position chlorines were much higher than those of congeners with more

292

α-position chlorines, suggesting that β-positions are more favored for chlorination

293

than α-positions in PCN formation during iron-casting processes. For example,

294

abundances of congeners composed of 12357/12467-, 12346-, 12356-, and 12367-

295

(with three β-position chlorines) were much higher than abundances of congeners

296

composed of 12457-, 12468-, 12456-, 12478-, and 12458- (with three α-position

297

chlorines). Similar trends in congener abundance have also been observed for hexa-

298

and hepta-homologs. Congeners of 123467/123567- with up to four β-position

299

substituted chlorines were the most dominant in hexaCN. The abundance of congener

300

1234567- with four β-position chlorines was also much higher than the

301

1234568-congener with four α-position chlorines. The relative abundances of the

302

congeners in penta-, hexa-, and hepta-homologs unintentionally produced during

303

iron-casting processes were also in good agreement with the stability estimate

304

obtained by density functional theory.36

305

Generally, the successive reductions in homolog fractions that occur with the

306

increase in chlorine numbers were observed to begin from tri-chlorinated homologs

307

and continue through octa-chlorinated homologs. Obviously favored chlorination at

308

the β-position was observed to begin from tetra-chlorinated homologs. Based on the

309

homolog distributions and congener profiles in stack gas and fly ash phases, we 15

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speculate that successive chlorination might be a dominant formation pathway of

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higher chlorinated homologs (from penta- to octa-homologs) during iron foundry

312

processes. The possible chlorination pathways we propose for major congeners from

313

tetra- to octa-homologs during iron foundry processes are shown in Figure 4. The

314

congener profiles of PCNs between fly ash and stack gas emissions were generally

315

similar for most congeners in tetra- to hepta-homologs, as seen in Figure 3. This

316

phenomenon indicates that similar formation mechanisms might occur for higher

317

chlorinated homologs in both fly ash and stack gas phases. The formation pathways of

318

lower chlorinated homologs (from di- to tetra-) might be much more complex. Several

319

studies by Kim et al. have indicated that mono- and di-chlorophenols were important

320

precursors for the formation of di-, tri-, and tetra-chlorinated naphthalenes.38-40

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Formation of PCNs through specific polycyclic aromatic hydrocarbons (PAHs)

322

isomers have also been confirmed by Weber et al.16 and Iino et al.41 Results of these

323

studies indicate that, in addition to chlorination pathways, the formation of di- to

324

tetra-homologs from some precursors, such as chlorophenols or specific PAHs, might

325

also be important pathways during iron foundry processes.16,38-40 Although the PCN

326

profiles were similar for most congeners between stack gas and fly ash samples, there

327

were substantial differences observed between several congeners, especially for lower

328

chlorinated congeners, including 145-, 124/146-, 127-triCN, and others. This might

329

also indicate the occurrence of other formation pathways of PCNs besides

330

chlorination during iron foundry processes. 16

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331 332

Emission factors and preliminary estimations of PCNs from iron foundries

333

The emission factor of contaminants is typically used for estimating total annual

334

emissions and for establishing inventory based on limited data.25,26,42 The emission

335

factor can be considered the emission rate of PCNs relative to the intensity of iron

336

foundry activities. The emission factor of PCNs in residue and stack gas for the

337

investigated iron foundries was derived using the following equations: 25,26,42 Emission factor by fly ash = concentration × amount of fly ash per ton of products . (1) Emission factor by stack gas = (concentration × flow rate of stack gas) ÷ output rate . (2)

338

The mass emission factors of ∑2-8PCNs in fly ash from the investigated iron

339

foundry plants ranged from 10–107 µg t−1, with an average value (± standard

340

deviation) of 61 ± 30 µg t−1. The median and geomean values of emission factors of

341

∑2-8PCNs in fly ash samples were 59 and 51 µg t−1, respectively. The average

342

emission factors of ∑2-8PCNs in stack gas samples were 267 µg t−1 for the EF plant

343

and 1472 µg t−1 for the LF plant. The TEQ emission factors of PCNs in fly ash from

344

the investigated iron foundry plants were also derived and the values ranged from

345

0.81–12.6 ng TEQ t−1 with an average value (± standard deviation) of 2.91 ± 3.75 ng

346

TEQ t−1. The median and geomean values of emission factors of ∑2-8PCN TEQs in fly

347

ash samples were 1.54 and 1.79 ng TEQ t−1, respectively. The average TEQ emission 17

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348

factors of ∑2-8PCNs in stack gas samples were 17.8 ng TEQ t−1 for the EF plant and

349

26.8 ng TEQ t−1 for the LF plant. The PCN emission factor from stack gas was higher

350

than that from fly ash for the EF plant, while for PCDD/Fs, in some industrial thermal

351

plants equipped with advanced APCS, the emission factors in stack gas were lower

352

than those in fly ash. We speculate that the following factors may contribute to the

353

converse trends observed between PCNs and PCDD/Fs. First, the different

354

physicochemical properties of PCNs and PCDD/Fs, such as higher vapor pressure of

355

PCNs than PCDD/Fs might lead to a greater distribution of PCNs in the gas phase

356

compared with PCDD/Fs. For example, the fraction of PCNs occurring in the gas

357

phase of air samples was higher than that of PCNs in the particle phase,43,44 while for

358

PCDD/Fs, most were distributed in the particle phase.45 Second, the absorption and

359

removal efficiency of PCNs only through bag filters is potentially low; this

360

observation has been made in waste incinerators.46 It has also been observed that the

361

absorption of activated carbon could decrease PCN emissions from waste

362

incinerations.46 For the EF iron foundry plant, no absorbent was used to control

363

atmospheric emissions in this study, and the low absorbent and removal ability of only

364

bag filters might lead to higher PCN emissions in stack gas than in fly ash.

365

The annual production from iron foundry plants with cupola furnaces in China

366

was about 44.6 million tons in 2008.15 Average emission factors of PCNs by fly ash

367

and stack gas emissions were adopted for preliminarily estimating the annual

368

emissions of PCNs from iron foundry industries in this study. The annual total 18

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369

emissions of ∑2-8PCNs from Chinese iron foundry plants with cupola furnaces were

370

preliminarily estimated to be about 2.7 kg (0.13 g in TEQ) by fly ash and 39 kg (1 g

371

in TEQ) by stack gas, which were far lower than the estimated annual emissions of

372

PCDD/Fs from Chinese iron foundry plants with cupola furnaces (16.3 g TEQ by

373

residue and 121 g TEQ by stack gas).15 The preliminary estimation indicated that

374

PCN atmospheric emissions from iron foundries (995 mg TEQ) were lower than those

375

of iron ore sintering industries (1390 mg TEQ), but higher than those of secondary

376

nonferrous smelting industries (860, 390, 10, and 9 mg TEQ for secondary copper,

377

aluminum, zinc, and lead smelting, respectively), primary magnesium smelting

378

industries (16 mg TEQ), and coking industries (430–692 mg TEQ),7 indicating that

379

emissions from iron foundries in China are relatively high. These derived emission

380

factors and preliminary estimates of annual emissions of PCNs might be useful for

381

understanding the contribution of iron foundries to PCN contamination. However,

382

there might be uncertainties in estimating the emission factors and annual emissions

383

of PCNs because of relatively small sample numbers, especially for stack gas

384

emissions. Much more intensive investigations are needed to establish a

385

comprehensive PCN emission inventory.

386

Emission factors of PCNs were also evaluated according to the furnace types and

387

raw materials used. The average mass emission factors of PCNs were 44 µg t−1

388

(geomean value: 41 µg t−1; median: 54 µg t−1; range: 25–61µg t−1) for hot air cupola

389

furnaces with scrap as raw materials, and 61 µg t−1 (geomean value: 42 µg t−1; median: 19

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390

80 µg t−1; range: 10–93 µg t−1) for cold air cupola furnaces with scrap as raw

391

materials. This indicates that mass emission factors of PCNs in fly ash samples from

392

cold air cupola furnaces were higher than those from hot air cupola furnaces; this

393

finding is in agreement with the observed PCN concentrations in fly ash samples. The

394

average mass emission factors of PCNs in fly ash were 91 µg t−1 (geomean value: 90

395

µg t−1; median: 93 µg t−1; range: 74–107 µg t−1) for plants with iron ore lump as raw

396

material using hot air cupola furnaces. The mass emission factors of PCNs in fly ash

397

samples from iron foundries using iron ore lump as raw materials were higher than

398

those of foundries using scrap as raw materials, which was in opposition to the

399

findings on the influence of raw materials on PCN concentrations in fly ash samples.

400

This phenomenon might be attributed to the larger amount of fly ash produced from

401

plants using iron ore lump as raw materials than those that use scrap as raw materials.

402 403

Acknowledgments

404

We gratefully acknowledge support from the National Natural Science Foundation of

405

China (No. 21037003), Strategic Priority Research Program of the Chinese Academy

406

of Sciences (No. XDB14020102), and SKLECE (KF2013-11).

407 408

Supporting Information Available

409

Table S1 and Figure S1-S4. This information is available free of charge via the

410

Internet at http://pubs.acs.org/. 20

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411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452

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PCDD/Fs and dioxin-like PCBs from Chinese iron foundries. Chemosphere 2011, 82, 759-763. (16) Weber, R.; Iino, F.; Imagawa, T.; Takeuchi, M.; Sakurai, T.; Sadakata, M. Formation of PCDF, PCDD, PCB, and PCN in de novo synthesis from PAH: Mechanistic aspects and correlation to fluidized bed incinerators. Chemosphere 2001, 44, 1429-1438. (17) Oh, J. E.; Gullett, B.; Ryan, S.; Touati, A. Mechanistic relationships among PCDDs/Fs, PCNs, PAHs, CIPhs, and CIBzs in municipal waste incineration. Environ. Sci. Technol. 2007, 41, 4705-4710. (18) Imagawa, T.; Lee, C. W. Correlation of polychlorinated naphthalenes with polychlorinated dibenzofurans formed from waste incineration. Chemosphere 2001, 44, 1511-1520. (19) Tuppurainen, K.; Asikainen, A.; Ruokojarvi, P.; Ruuskanen, J. Perspectives on the formation of polychlorinated dibenzo-p-dioxins and dibenzofurans during municipal solid waste (MSW) incineration and other combustion processes. Acc. Chem. Res. 2003, 36, 652-658. (20) Gullett, B.; Grandesso, E.; Touati, A.; Tabor, D. Effect of Moisture, Charge Size, and Chlorine Concentration on PCDD/F Emissions from Simulated Open Burning of Forest Biomass. Environ. Sci. Technol. 2011, 45, 3887-3894. (21) Chi, K. H.; Chang, S. H.; Chang, M. B. Reduction of dioxin-like compound emissions from a Waelz plant with adsorbent injection and a dual baghouse filter system. Environ. Sci. Technol. 2008, 42, 2111-2117. (22) Fiedler, H. National PCDD/PCDF release inventories under the Stockholm convention on persistent organic pollutants. Chemosphere 2007, 67, S96-S108. (23) Cieplik, M. K.; De Jong, V.; Bozovic, J.; Liljelind, P.; Marklund, S.; Louw, R. Formation of dioxins from combustion micropollutants over MSWI fly ash. Environ. Sci. Technol. 2006, 40, 1263-1269. (24) Cains, P. W.; McCausland, L. J.; Fernandes, A. R.; Dyke, P. Polychlorinated dibenzo-p-dioxins and dibenzofurans formation in incineration: Effects of fly ash and carbon source. Environ. Sci. Technol. 1997, 31, 776-785. (25) Liu, G. R.; Zheng, M. H.; Lv, P.; Liu, W. B.; Wang, C. Z.; Zhang, B.; Xiao, K. Estimation and characterization of polychlorinated naphthalene emission from coking industries. Environ. Sci. Technol. 2010, 44, 8156-8161. (26) Liu, G. R.; Liu, W. B.; Cai, Z. W.; Zheng, M. H. Concentrations, profiles, and emission factors of unintentionally produced persistent organic pollutants in fly ash from coking processes. J. Hazard. Mater. 2013, 261, 421-426. (27) Blankenship, A. L.; Kannan, K.; Villalobos, S. A.; Villeneuve, D. L.; Falandysz, J.; Imagawa, T.; Jakobsson, E.; Giesy, J. P. Relative potencies of individual polychlorinated naphthalenes and halowax mixtures to induce Ah receptor-mediated responses. Environ. Sci. Technol. 2000, 34, 3153-3158. (28) Villeneuve, D. L.; Kannan, K.; Khim, J. S.; Falandysz, J.; Nikiforov, V. A.; Blankenship, A. L.; Giesy, J. P. Relative potencies of individual polychlorinated naphthalenes to induce dioxin-like responses in fish and mammalian in vitro bioassays. Arch Environ Con Tox 2000, 39, 273-281. (29) Hanberg, A.; Waern, F.; Asplund, L.; Haglund, E.; Safe, S. Swedish Dioxin Survey 22

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Determination of 2,3,7,8-Tcdd Toxic Equivalent Factors for Some Polychlorinated-Biphenyls and Naphthalenes Using Biological Tests. Chemosphere 1990, 20, 1161-1164. (30) Behnisch, P. A.; Hosoe, K.; Sakai, S. Brominated dioxin-like compounds: in vitro assessment in comparison to classical dioxin-like compounds and other polyaromatic compounds. Environ. Int. 2003, 29, 861-877. (31) Kannan, K.; Yamashita, N.; Imagawa, T.; Decoen, W.; Khim, J. S.; Day, R. M.; Summer, C. L.; Giesy, J. P. Polychlorinated naphthalenes and polychlorinated biphenyls in fishes from Michigan waters including the Great Lakes. Environ. Sci. Technol. 2000, 34, 566-572. (32) Noma, Y.; Yamamoto, T.; Sakai, S. I. Congener-specific composition of polychlorinated naphthalenes, coplanar PCBs, dibenzo-p-dioxins, and dibenzofurans in the halowax series. Environ. Sci. Technol. 2004, 38, 1675-1680. (33) Falandysz J; Fernandes A; Gregoraszczuk E; M, R. Aryl hydrocarbon receptor mediated (dioxin-like) relative potency factors for chlornaphthalenes. Organohalogen Compd. 2013, 75, 336-338. (34) Nie, Z. Q.; Zheng, M. H.; Liu, G. R.; Liu, W. B.; Lv, P.; Zhang, B.; Su, G. J.; Gao, L. R.; Xiao, K. A preliminary investigation of unintentional POP emissions from thermal wire reclamation at industrial scrap metal recycling parks in China. J. Hazard. Mater. 2012, 215, 259-265. (35) Nie, Z. Q.; Zheng, M. H.; Liu, W. B.; Zhang, B.; Liu, G. R.; Su, G. J.; Lv, P.; Xiao, K. Estimation and characterization of PCDD/Fs, dl-PCBs, PCNs, HxCBz and PeCBz emissions from magnesium metallurgy facilities in China. Chemosphere 2011, 85, 1707-1712. (36) Zhai, Z. C.; Wang, Z. Y. Computational study on the relative stability and formation distribution of 76 polychlorinated naphthalene by density functional theory. Journal of Molecular Structure-Theochem 2005, 724, 221-227. (37) Jansson, S.; Fick, J.; Marklund, S. Formation and chlorination of polychlorinated naphthalenes (PCNs) in the post-combustion zone during MSW combustion. Chemosphere 2008, 72, 1138-1144. (38) Kim, D. H.; Mulholland, J. A. Temperature-dependent formation of polychlorinated naphthalenes and dihenzofurans from chlorophenols. Environ. Sci. Technol. 2005, 39, 5831-5836. (39) Kim, D. H.; Mulholland, J. A.; Ryu, J. Y. Formation of polychlorinated naphthalenes from chlorophenols. P Combust Inst 2005, 30, 1245-1253. (40) Kim, D. H.; Mulholland, J. A.; Ryu, J. Y. Chlorinated naphthalene formation from the oxidation of dichlorophenols. Chemosphere 2007, 67, S135-S143. (41) Iino, F.; Imagawa, T.; Takeuchi, M.; Sadakata, M. De novo synthesis mechanism of polychlorinated dibenzofurans from polycyclic aromatic hydrocarbons and the characteristic isomers of polychlorinated naphthalenes. Environ. Sci. Technol. 1999, 33, 1038-1043. (42) Liu, G. R.; Zheng, M. H.; Liu, W. B.; Wang, C. Z.; Zhang, B.; Gao, L. R.; Su, G. J.; Xiao, K.; Lv,

P.

Atmospheric

emission

of

PCDD/Fs,

PCBs,

hexachlorobenzene,

and

pentachlorobenzene from the coking industry. Environ. Sci. Technol. 2009, 43, 9196-9201. (43) Gregoris, E.; Argiriadis, E.; Vecchiato, M.; Zambon, S.; De Pieri, S.; Donateo, A.; Contini, D.; Piazza, R.; Barbante, C.; Gambaro, A. Gas-particle distributions, sources and health 23

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537 538 539 540 541 542 543 544 545 546 547 548 549

effects of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polychlorinated naphthalenes (PCNs) in Venice aerosols. Sci. Total Environ. 2014, 476, 393-405. (44) Odabasi, M.; Bayram, A.; Elbir, T.; Dumanoglu, Y.; Kara, M.; Altiok, H.; Cetin, B. Investigation of seasonal variations and sources of atmospheric polychlorinated naphthalenes (PCNs) in an urban area. Atmos Pollut Res 2012, 3, 477-484. (45) Li, Y. M.; Jiang, G. B.; Wang, Y. W.; Cai, Z. W.; Zhang, Q. H. Concentrations, profiles and gas-particle partitioning of polychlorinated dibenzo-p-dioxins and dibenzofurans in the ambient air of Beijing, China. Atmos. Environ. 2008, 42, 2037-2047. (46) Sakai, S.; Yamamoto, T.; Noma, Y.; Giraud, R. Formation and control of toxic polychlorinated compounds during incineration of wastes containing polychlorinated naphthalenes. Environ. Sci. Technol. 2006, 40, 2247-2253.

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550

Table and Figure Captions

551

Table 1. Basic information on iron foundries,15 and concentrations and emission

552

factors of PCNs in stack gas and fly ash samples

553 554

Figure 1. PCN structure, with the α and β positions and the carbon atom numbers

555

indicated7

556

Figure 2. Homolog profiles of PCNs in stack gas and fly ash samples

557

Figure 3. Profiles of PCN congeners relative to their corresponding homologs

558

Figure 4. The proposed possible chlorination pathways for major congeners of tetra-

559

to octa-homologs during iron foundry processes

560

Note: The data shown in parentheses are the percentages of congeners relative to

561

their respective homologs. The superscripts indicate the unresolved congeners on

562

the DB-5 column and the corresponding data in the parentheses indicate the

563

percentages of the co-eluted congeners

25

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Table 1. Basic information on iron foundries,15 concentrations, and emission factors of PCNs in stack gas and fly ash samples plant denota tion

cupola furnace

raw material

APCS

annual capacity (103 t)

ash output (t year-1)

release route

DJ

hot air cupola

3750

hot air cupola

200

EF

cold air cupola

scrap

fabric filter fabric filter fabric filter

50

DX

iron ore lump sinter

7

ER

hot air cupola

scrap

GF

hot air cupola

JY LF

hot air cupola cold air cupola

iron ore lump scrap scrap

ME

hot air cupola

MY

hot air cupola

iron ore lump scrap

QZ

hot air cupola

scrap

YL

cold air cupola

scrap

YR

hot air cupola

scrap

ZW

cold air cupola

scrap

fabric filter fabric filter cyclone wet scrubber fabric filter wet scrubber no APCS fabric filter fabric filter fabric filter

TEQ concentration (pg TEQ g-1 or pg TEQ m-3) 0.02

mass emission factor (µg t-1)

TEQ emission factor (ng TEQ t-1)

fly ash

mass concentration (pg g-1 or pg m-3) 980

73.5

1.51

10000

fly ash

1122

0.05

56.1

2.34

108

fly ash

665

0.05

10.3

0.84

30

340

stack gas fly ash

7339 2205

0.49 0.07

267 25

17.8 0.81

60

4000

fly ash

1379

0.01

92.7

0.98

27 18

1000 280

fly ash stack gas

1649 104445

0.03 1.90

61.1 1472

0.95 26.8

20

1020

fly ash

2108

0.04

108

1.86

11

360

fly ash

1649

0.03

54

0.84

1

36

fly ash

1501

0.05

54

1.83

30

349

fly ash

6910

0.75

80.4

8.78

62

720

fly ash

2130

0.14

24.7

1.57

12

150

fly ash

7664

1.04

92.7

12.6

26

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β Cln

β

α

α

8

1

5

4 α

7 6 α

2 3

β β

Clm

Figure 1. PCN structure, with the α and β positions and the carbon atom numbers indicated7

27

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Environmental Science & Technology

0.8 fly ash stack gas

0.7 0.6

fraction

0.5 0.4 0.3 0.2 0.1

O ct aC N

H ex aC N H ep ta C N

Te tra C N Pe nt aC N

iC N Tr

D iC

N

0.0

Figure 2. Homolog profiles of PCNs in stack gas and fly ash samples

28

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0.8

Di- and Tri-

0.7

fly ash stack gas

0.6 fraction

0.5 0.4 0.3 0.2 0.1 1 14 3/1 15 6/2 26 7/1 712 23 18 13 613 51 12 37 4/ 14 612 512 616 127 7/ 12 323 613 814 512 8-

0.0

0.32 0.28

Tetra-

fly ash stack gas

fraction

0.24 0.20 0.16 0.12 0.08 0.04 0.00 57 47 67 67 56 58 37 34 67 45 48 68 58 38 78 13 /12 13 14 /12 /13 12 12 12 12 /12 /12 14 12 12 46 68 35 67 58 12 13 12 23 12 7/ 5 12

0.40 0.35

Penta-

fly ash stack gas

fraction

0.30 0.25 0.20 0.15 0.10 0.05 0.00 2 7/1 35 12

86766878587846 245 246 234 235 236 245 247 236 245 234 237 1 1 1 1 1 1 1 1 1 1 /1 8 35 12

1.0

Hexa- and Heptafraction

0.8

fly ash stack gas

0.6 0.4 0.2 0.0

68 67 78 67 68 78 78 56 58 45 45 36 35 35 35 45 34 34 3 3 2 2 2 2 2 2 2 1 1 1 1 /1 /1 /1 12 12 67 57 68 34 34 45 12 12 12

Figure 3. Profiles of PCN congeners relative to their corresponding homologs

29

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Page 30 of 31

Cl α 1

α

Cl

8

β7 β6

5

1257-

α

α

4

Cl

α 1

α 8 5

Cl

α

α

1246-

8

β7 β6

Cl

β7 β6

5

Cl 2 β 3 β

4

α 1

β7 β6

5

4

α

α

1247-

2 β 3 β

5

Cl

α

α

α 1

α β7 β6

5

Cl

α

α

β7 β6

5

α

Cl

α

12346-

4

α 1

α

Cl 2 β 3 β

β7 β6

5

Cl

1256-

α

α

4

2 β 3 β β7 β6

Cl

Cl Cl

(15%)

α 1

α 8 5

α

α

4 Cl

(9%)

Cl 8

α 1

5

4

α β7 β6

Cl

α

5

4

α

α

α

Cl

β7 β6 Cl Cl

8 5

α

8 5

α

α

Cl 2 β 3 β

4

4

Cl

Cl

(85%)

Cl Cl

d

β7 β6

α 1

α

4

2 β 3 β

β7 β6

Cl

Cl

α

α 1

8 5

Cl

β7 β6 Cl Cl

Cl

α

α 1

8 5

α

Cl

2 β 3 β

α

4

Cl

α

α 1

8 5 Cl

Cl

Cl

Cl

Cl

Cl

Cl

α

α

1234567Cl

(59%) d

2 β 3 β

α 1

α

Cl

123567-

Cl

Cl

Cl α

Cl

2 β 3 β

Cl

(15%)

2 β 3 β

α

5

Cl

Cl 2 β 3 β

Cl α

Cl

12356-

Cl

1234-

Cl

8

Cl

4

Cl

α 1

α

5

8

β7 β6

Cl

8

(59%)

Cl

Cl α 1

α

Cl

123467-

β7 β6

Cl

Cl

α 1

Cl

Cl 8

4 Cl

α

Cl

Cl

(12%)

(7%)

β7 β6

4

2 β 3 β

α

(14%) c

β7 β6 α 1

α 8

α

Cl 2 β 3 β

123457-

Cl

Cl

1467-

2 β 3 β

(23%) b

Cl 8

5 Cl

Cl

12467-

Cl

8

Cl

4

α 1

α

Cl α 1

8

β7 β6

Cl

Cl

Cl

β7 β6

α

Cl

(19%) a Cl

4

Cl

(23%) b

Cl α

α

12357-

Cl

8

α

Cl 2 β 3 β

Cl

a

Cl

α 1

α

Cl

Cl

(19%) a

(19%)

Cl 2 β 3 β

α

α

Cl Cl 2 β 3 β

4

α

α

Cl 2 β 3 β

4

Cl Cl

12345678Cl 2 β 3 β

octaCl

Cl

1234568(15%)

Cl

123568-

hepta-

(14%) c Cl

12367-

hexa-

(13%)

penta-

1267(9%)

tetra-

Figure 4. The proposed possible chlorination pathways for major congeners through tetra- to octa-homologs during iron foundry processes Note: The data shown in parentheses are the percentages of congeners relative to their respective homologs. The superscript indicates the unresolved congeners on DB-5 column and the corresponding data in the parentheses indicate the percentages of the co-eluted congeners

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