- Email: [email protected]
The emission characteristics and the related malodor intensities of gaseous reduced sulfur compounds (RSC) in a large industrial complex
ARTICLE IN PRESS
Atmospheric Environment 40 (2006) 4478–4490 www.elsevier.com/locate/atmosenv
The emission characteristics and the related malodor intensities of gaseous reduced sulfur compounds (RSC) in a large industrial complex Ki-Hyun Kima,, Eui-Chan Jeona, Ye-Jin Choia, Youn-Seo Koob a
Department of Earth and Environmental Sciences, Sejong University, 98 Goon Ja Dong, Seoul, South Korea b Department of Environmental Engineering, Anyang University, Anyang, South Korea Received 13 December 2005; accepted 9 April 2006
Abstract In this study, the concentrations of major reduced sulfur compounds (RSC: H2S, CH3SH, DMS, CS2 and DMDS) were determined from various emission sources located within the Ban-Wall (BW)/ Si-Hwa (SH) industrial complex in Ansan city, Korea. The measurement data were obtained from a total of 202 individual points at 77 individual companies during 2004–2005. The highest RSC concentration levels came most dominantly from H2S (300 (mean) and 0.86 ppb (median)) followed by CS2, while the results of CH3, DMS, and DMDS are notably lower at the mean concentration levels of a few ppb. These data were evaluated further after being grouped into two different classification schemes: 9 industry sectors and 9 processing unit types. The strongest emissions of RSC, when evaluated among different industry sectors, are generally found from such industry types as leather, food, paper/pulp, as well as waste/sewage related ones. In contrast, when these RSC data are compared across different processing units, the highest values were seen most frequently from such units as junction boxes, aeration tanks, and settling tanks. The assessment of data in terms of relative contribution to malodor intensity showed that H2S and CH3SH are more important than others. The overall results of the present study suggest that information combining RSC speciation and types of anthropogenic activities may be used to distinguish the patterns of odorous pollution in areas affected by strong source processes. r 2006 Elsevier Ltd. All rights reserved. Keywords: Reduced sulfur compounds (RSC); H2S; Malodor; Industrial complex; Korea
1. Introduction It is commonly observed that malodor issues have become one of the hot socio-environmental subjects (Davoli et al., 2003; Emerson and Rajagopal, 2004). Malodor is defined as the single or composite of Corresponding author. Tel.: +82 19 595 3408; fax: +82 2 499 2354. E-mail address: [email protected] (K.-H. Kim).
1352-2310/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2006.04.026
chemical compounds which causes ill feelings by smelling through the sensory organ. Hence, it is often classified as sensory pollution that can damage more mentally or psychologically than physically. The sources of malodor are found to include a variety of man-made activities such as chemical plants, oil refineries, sewage treatments, landfills, livestock facilities, etc. (Al-Shammiri, 2004; Kim et al., 2005a, b; Willig et al., 2004). Evaluation of its impact can be subjective and intuitive, with the
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
complicated nature of odorant chemicals. It is thus considered to be a difficult task to provide a reliable tool to control the release of odorant pollutants from its sources (e.g., Costi et al., 2004). As a consequence, one cannot easily offer a practical
4479
strategy that can help relieve the effects of malodor pollution. Ban -Wall (BW)/Si -Hwa (SH) industrial complex (IC) is generally recognized to be the core production base to produce a variety of goods and
Fig. 1. The geographical location of the study site in Ansan city, Korea.
ARTICLE IN PRESS 4480
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
merchandises near the capital city of Seoul, Korea (refer to Fig. 1). Although BW/SH IC plays a major role in the Korean manufacturing industry, it has been blamed for malodor sources as many complaints have come from the residents residing in the surrounding areas. The occurrence of malodor complaints has increased drastically over the past several years. In light of its potent impact, stringent rules and regulations have been considered and were established to resolve the current situation of malodor pollution in the area. As part of project to characterize the emission patterns of malodor components and to build a malodor control policy, our study group has been involved in an intensive field study to measure the emission concentrations for a list of odorous pollutants released from various industrial activities (Kim et al., 2005b). In light of the fact that RSC belongs to a group of chemicals with strong odor potential, there has been a great demand to describe their emission characteristics in relation with various anthropogenic-source processes. To comply with such social and environmental demand, the measurements of RSC emission concentration have been taken from BW/SH IC from June 2004 to October 2005. In the present study, we attempted to evaluate the emission characteristics of odorous sulfur compounds from various industrial sectors operating in the large BW/SH industrial complex. 2. Materials and methods 2.1. Site characteristics The measurements of odorous compounds have been taken from the BW/SH IC in the city of An San (Gyung Gi province), Korea (Fig. 1). The industrial complex had been established since 1975 on the western side of the city that directly faces the western coastline of Korea. Afterwards, a large residential area consisting of high-altitude apartment buildings was built in the eastern side of the city in the 1990s. Because of the combined effects of geographical and meteorological conditions (e.g., prevalence of westerlies and oceanic winds), the residential area is generally designated as a downwind position to receive odors emitted from the nearby big sources. Aiming to develop plans to relieve malodor problems in Ansan city, we have been involved in a project to investigate sources of odorous emissions in the BW/SH industrial complex. As part of this
project, the concentrations of important odorous compounds have been measured from individual sources representative of various manufacturing units in 77 individual companies during June 2004 to October 2005. The target compounds of interests include the sum of 12 odorous compounds regulated by the Korean Ministry of Environment (KMOE) plus several aromatic VOC (refer to Table 1 for the list of pollutants). The designated 12 odorous pollutants consist of four different types of chemicals: (1) four reduced sulfur compounds (RSC: H2S, CH3SH, DMS, and DMDS), (2) five aldehydes including acetaldehyde, (3) N-compounds (trimethyl amine, and ammonia), and (4) styrene. In this study, we intended to focus solely on the RSC measurement data to provide the fundamental characteristics of the odorous emissions from industrial-source processes. The results of the other odorous pollutants will be dealt in our future publications. 2.2. Sample collection and analysis In this study, RSC samples from various emission sources were collected using the Tedlar bag sampling method (SKC corp., USA). For this purpose, all Tedlar bags (10 L capacity) were placed inside a lung-type gas-sampling system, built as a vacuumgeneration container. By controlling the vacuum pump and a 2-way rotary valve, samples were forced to be drawn directly into the Tedlar bags by the vacuum created inside the container. These samples were then brought to the lab as quickly as possible (e.g., within 24 h) to minimize the possibility of RSC loss due to the storage. To allow RSC measurements of varying sample types (in terms of concentration range), the gas chromatography (GC: Model DS 6200, Donam Instruments, Korea) equipped with a pulsed flame photometric detector (PFPD: Model 5380, O.I. Co.) was interfaced either with a loop injection system (high mode) or with an air server (AS)/thermal desorption (TD) unit (low mode). This dual analytical system has been built to switch between low (e.g., at or below 10 ppbv) and high-concentration ranges (e.g., at or above 10 ppbv). The details of the analytical performance of both analytical modes have been described in a series of articles made from our laboratory (Kim, 2005a, b). For the efficient collection of samples with sufficiently low RSC content, a multi-functioned TD system equipped with an AS unit (UNITY model, Markes International Ltd., UK) was operated to selectively
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4481
Table 1 A full list of odorous pollutants investigated in this study Odor Type
Regulation criteria typea Analytical methodb
Pollutatnts Full name
Short name Structural formula
Formaldehyde Acetaldehyde Acrolein Acetone Propionaldehyde crotonaldehyde Butyraldehyde Benzaldehyde Isovalerldehyde Valealdehyde o-Tolualdehyde m-Tolualdehyde p-Tolualdehyde
Form-A Acet-A Acrolein Acetone Propion-A Croton-A Butyr-A Benz-A Isovaler-A Valer-A o-Tolu-A m-Tolu-A p-Tolu-A
HCHO CH3CHO CH3–CHCHO CH3COCH3 CH3CH2CHO CH3CHQCHCHO CH3CH2CH2CHO C6H5CHO (CH3)2CHCH2CHO CH3(CH2)3CHO CH3C6H4CHO CH3C6H4CHO CH3C6H4CHO
Hydrogen sulfide Methyl mercaptan Dimethyl sulfide Carbon disulfide Dimethyl disulfide
H2S CH3SH DMS CS2 DMDS
H2S CH3SH (CH3)2S CS2 (CH3)2S2
C. Total and individual VOC Total VOC Benzene Toluene Ethylbenzene m,p-Xylene Styrene o-Xylene Bromobenzene 1,3,5-Trimethylbenzene 1,2,4-Trimethylbenzene p-Isopropyltoluene n-Bultylbenzene
TVOC B T E MPX STY OX BB 1,3,5-TMB 1,2,4-TMB p-IPT n-BB
C6H6 C6H5CH3 C6H5C2H5 (CH3)2C6H4 C6H5CHQCH2 (CH3)2C6H4 C6H5Br (CH3)3C6H6 (CH3)3C6H7 C10H14 C10H14
D. Ammonia E. Amine
NH3 TMA
NH3 (CH3)3N
A. Carbonyl compounds
B. Reduced S compounds
Ammonia Trimethyl amine
I
II II
DNPH+HPLC
II II
I I I
TB+GC/PFPD
I
I
TB+GC/FID
I I
IM+UVS TB+GC/FID
a
Pollutant type: Chemicals of type I and II were designated as criteria odorous pollutants before and after the new regulations started in February 2005 by the Korean Ministry of Environment (KMOE), respectively. b Sampling and analytical method: DNPH—sampling by a DNPH-cartridge, TB—sampling by Tedlar bag, IM—impinger, HPLC— analysis by HPLC method, GC—gas chromatography, PFPD—pulsed-flame photometric detector, FID—flame ionization detector, and UVS—UV spectrometer.
cryofocus samples with low S contents. The details of the AS/TD settings have been explained previously in our recent publications (Kim, 2005a). In contrast, to analyze RSC samples collected from strong-source areas, the loop injection system was employed directly by following the procedures introduced in our recent study (Kim, 2005b). The reduced S compounds delivered from either the AS/TD or loop system were then analyzed by a GC equipped with a pulsed flame photometric detector (PFPD: O.I. Co., Model 5380). Chromatographic separation of different RSC was done via BP-1
column (60 m 0.32 mm, 5.0 mm, SGE) for 20 min cycles. Other conditions for the GC analysis can be summarized as follows: Detector temp. of PFPD: 220 1C Flow rate (mL min1): Air(1) ¼ 10, Air(2) ¼ 10, H2 ¼ 11.5 Carrier gas : N2, 1.2 mL min1 (20 psi) Cold trap : low ¼ 15 1C, high ¼ 220 1C, hold time ¼ 5.0 min Outlet split : 5.0 mL min1 (5:1 split ratio) Flow path temp.: 80 1C
ARTICLE IN PRESS 4482
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
3. Results and discussion
criteria were used to initially divide all the individual companies to eight industrial sectors (Fig. 2) such as: (1) compound and chemical product (acronym, C), (2) food and beverage (F), (3) leather, bag, and shoes production (L), (4) metal assembly and production (M), (5) pulp and paper (P), (6) steel production (S), (7) textile production (T), and (8) waste treatment, sewage, and cleaning (W). Although 66 out of the total 77 companies were put together into those eight individual classes, all the remaining 11 companies defying such classification were grouped together as the ninth sector: (9) the miscellaneous or extra class (X). According to this grouping scheme, as plotted in Fig 2, all those 11 companies belonging to the class X are seen to consist of such industrial types as automobiles and trailers to wood and its products. Our field measurements were conducted to cover 2 to 4 measurement points for each individual company; each point was hence selected to represent the most important emission source processes (or units) in the given facility. During the entire study period, a total of 202 measurement points were selected and investigated from all 77 companies investigated. As shown in Table 2, many different types of source processes including diverse indoor spots were also investigated to evaluate the effects of different source process units. To simplify the classification of all those processes, all measurement points were classified into 9 different source categories. According to this classification criterion introduced in Table 2, scrubber rearside (SR) is found to be investigated most intensively (N ¼ 81) followed by manufacturing process (MP: N ¼ 45), aeration tank (AT: N ¼ 24), and so on.
3.1. Basic classification criteria for the industrial sectors and source process types
3.2. Emission concentrations of RSCs among industrial sectors and source process types
In Table 2, all RSC measurement data collected during the entire study period are pooled together and classified into two different classification schemes: (1) across different industrial sectors and (2) across different source process types. To simplify the comparison of emission patterns across different sectors and source types, two different types of acronyms were assigned to facilitate the classification as shown in Table 2; single-letter acronyms were used to distinguish a total of 9 industrial sectors, while two-letter ones were assigned for 9 operation (or treatment) process types. In the case of the former, the Korean standard classification
To assess the general characteristics of odorous RSC emissions in the study area, the emission concentration data were investigated by the two classification schemes introduced above. Hence in Table 3, a statistical summary of the entire measurement data is given in terms of both industry type and source process type. As compared by the overall mean concentration values of different RSCs of Table 3 (A), the mean concentration of H2S is found to record the highest of all compounds at 300 ppb. The mean concentration values of the other RSCs are found to be significantly reduced with their magnitude varying in the order CS2
In order to allow a simple comparison of the PFPD’s responses between different S compounds, integration of their peak areas was made in the linear mode with the square root (SR) function on. As the use of the SR function efficiently masks the squared response of the detector (i.e., due to the conversion of S atoms to an S2 complex), the whole calibration procedure can be facilitated by handling a simple first-order equation. Because the noise level of the blank was sufficiently low, calibration curves obtained from three (or four) points calibration typically showed an excellent linearity; correlation coefficients above 0.99 were commonly achieved, even at the offset mode, which forced the curve to pass through zero on both the x and y axes (Kim, 2005a). The analytical performance of the GC/PFPD setting between the loop injection and the PC/TD system was slightly different in terms of sensitivity. If the absolute DL values of RSC are compared between the two systems, the high-mode system generally exhibited the DL values of as little as a few pg (CH3SH, DMS, and DMDS) to 30 pg (H2S). It was however found that the DL values expressed in terms of absolute mass quantity were generally larger for the low-mode system than for the highmode system by a few times. In addition, if the precision is evaluated in terms of the relative standard error (RSE) of the triplicate analyses, it was found that the RSE values of both systems tend to fall in the range of 1–5%. The reproducibility of S gas detection was however rather variable with respect to the time and type of the RSC.
Symbol C F L M P S T W X 2 4 1 24
2
AT 5 4 6
Aeration Tank
2 5
1 2
JB
Junction Box
2 3 12 8 3 45
MP 5 8 4
Manufacturing Process
5 6 2 2 2 3 3 23
SF
Scrubber Front
1 4
1
1
SK 1
Stack
2 1 12
1
SP 3 1 4
Storing Place
13 81
SR 16 11 8 5 6 7 15
Scrubber Rear
6
2
1
1 2
ST
Settling Tank
2
XP 2
Miscellaneous Process
32 26 31 11 14 13 32 19 24 202
Sum
Two types of symbols are introduced here; single letter acronyms of C through X are given for the classification of each industrial type, while 2-letter ones for each source process type. a The ninth class of X named as miscellaneous ones include the following industrial sectors: (1) automobile and trailer, (2) electronic machine and converter, (3) electronics, gas and vapor, (4) furniture, (5) miscellaneous machine and instrument, (6) printing and publishing, (7) sewing and fur product, and (8) wood and its product.
Compound and chemical product Food and beverage Leather, bag, and shoes production Metal assembly and production Pulp, paper, etc. Steel production Textile Waste treatment, sewage and cleaning Miscellaneous onesa Sum
Type of industry (single letter) vs. Source process type (double letter Acronyms)
Table 2 Compilation of odorous emission sources for both industrial (N ¼ 9) and source process types (N ¼ 9) in this study with the definition of their acronyms using single and double letters, respectively
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
ARTICLE IN PRESS 4483
ARTICLE IN PRESS
Type of industry (Major code)
4484
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
Compound and chemical product (C) Food and beverage (F) Leather, bag, and shoes production (L) Metal assembly and production (M) Pulp, paper, etc. (P) Steel product (S) Textile (T) Waste treatment, Sewage and cleaning (W) Automobile and trailer (X1) Electronic machine and convertor (X2) Electronics, gas, and vapor (X3) Furniture (X4) Miscellaneous machine and instrument (X5) Printing and publishing (X6) Sewing, fur product (X7) Wood and its product (X8) 0
5
10
15
20
Number of companies Fig. 2. A list of industry types and grouping results of 77 companies investigated for the characterization of odor emission patterns. Classification is made based on a standard industrial classification code of Korea. First, a sum of 66 companies are classified into the 8 individual industrial groups with the symbols of C (Compound and chemical product) through W (Waste treatment, sewage, and cleaning). Then, the sum of remaining 11 companies (with their symbols of X1 (Automobile and trailer) through X8 (Wood and its product)) is combined together as the last 9th class (using symbol X) for statistical treatment.
(14.9), DMS (7.66), CH3SH (3.17), and DMDS (0.71 ppb). The observed RSC concentration levels in this study, when compared against those reported for other strong-source types, are comparable to the ones reported for ventilated landfill gas (LFG) samples in inactive landfill sites (Kim et al., 2005a). In our previous study of landfill composition, we found that the LFG concentration of H2S from inactive landfill was found as little as 336 ppb, while it goes up to a few thousand ppm in active LFG samples. The presence of such strong emissions for some RSCs (such as H2S and DMS) was also recognized from other urban-source processes (Muezzinoglu, 2003); this author found that H2S concentrations vary from as little as below 1 ppm and up to about 1000 ppm from creek water polluted by industrial wastes in Turkey. It is interesting to note that the distributions of most RSCs investigated in this study are extremely variable with their SD values typically exceeding the mean values by several times. Because of such variability, these RSC data have also been compared and evaluated by the median values along with the mean concentration values. It indicates that the magnitude of median values is reduced substantially from that of the mean values without exception. In fact, the H2S data seem to experience the most significant reduction such as from 300 (mean) to 0.86 ppb (median). However, the distribution patterns, when evaluated simply in terms of
median values only, seem to change in a rather narrow and constant range; their median values are in general smaller by one to two orders of magnitude than the mean values with the descending order of CS2 (1.39), H2S (0.86), DMS (0.13), CH3SH (0.09), and DMDS (0.05 ppb). In order to examine the occurrence patterns of RSC emissions more meaningfully, a comparison of these measurement data has been made after grouping them either into different industry types or into process types in Table 3B and C respectively. Their occurrence patterns are also plotted by each of the two classification criteria in Figs. 3 and 4, respectively. The results of this comparison suggest that most of RSC emissions may proceed in a low ppb concentration range, while their mean values are also affected persistently by the existence of exceptionally high values, especially in the case of H2S and CS2. Because of these unusually wide concentration ranges for most RSCs, comparison of the data measured in this study may be more meaningful with the aid of median values, if possible. For the purpose of comparison, their mean values shown in Table 3B and C were evaluated initially by their magnitude with the arbitrary two-stage criteria of 10 (first) and 1 ppb (second criterion). According to this approach, only 4 cases out of 45 individual cells (5 compounds 9 different sectors) exceeded the initial criterion of 10 ppb. The presence of those high mean
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4485
Table 3 A statistical summary of the emission concentrations of reduced S compounds (RSC) measured in this study Class
H2S
A. Summary on the entire data set All 30071911 (0.86)a 0.01–23311 (202)b B. Classification by industrial typec C 6.15717.9 (0.91) 0.04–97.4 (32) F 4.39715.9 (0.28) 0.01–78.6 (24) L 190074617 (134) 0.01–23310 (31) M 1.8873.61 (0.46) 0.02–12.3 (11) P 21.1751.1 (1.36) 0.07–174 (14) S 0.8871.92 (0.18) 0.01–7.12 (13) T 1.6176.52 (0.19) 0.01–37.6 (33) W 28.07102 (0.98) 0.03–448 (19) X 4.39715.9 (0.28) 0.01–78.6 (24) C. Classification by source process typed AT 113974735 (5.52)a 0.05–23311 (24)b JB 326974759 (6.75) 0.81–10468 (5) MP 8.63726.8 (0.42) 0.01–134 (42) SF 24.0787.4 (0.38) 0.01–328 (14) SK 0.9771.20 (0.55) 0.26–3.34 (6) SP 56571536 (1.54) 0.01–5691 (18) SR 36.37255 (0.58) 0.01–2360 (86) ST 73271419 (20.1) 0.82–3256 (5) XP 0.1670.14 (0.16) 0.06–0.26 (2)
CH3SH
DMS
CS2
DMDS
3.17710.7 (0.09) 0.004–91.3 (202)
7.66769.0 (0.13) 0.003–952 (202)
14.97105 (1.39) 0.03–1277 (202)
0.7172.84 (0.05) 0.001–28.1 (202)
2.0077.47 (0.07) 0.01–40.39 (32) 0.1870.24 (0.05) 0.01–0.78 (24) 7.31712.4 (2.11) 0.01–53.7 (31) 0.0670.08 (0.04) 0.01–0.30 (11) 0.9471.47 (0.05) 0.02–4.28 (14) 0.3971.22 (0.06) 0.01–4.44 (13) 0.0870.11 (0.03) 0.004–0.47 (33) 6.85716.5 (0.19) 0.02–59.4 (19) 0.1870.24 (0.05) 0.01–0.78 (24)
1.8874.82 (0.26) 0.004–26.2 (32) 0.6671.80 (0.08) 0.01–8.73 (24) 0.5071.10 (0.18) 0.004–5.98 (31) 0.3170.48 (0.10) 0.01–1.61 (11) 0.2570.50 (0.04) 0.003–1.68 (14) 0.1770.23 (0.04) 0.01–0.66 (13) 0.0970.10 (0.05) 0.003–0.45 (33) 3.4876.63 (0.45) 0.02–27.9 (19) 0.6671.80 (0.08) 0.01–8.73 (24)
1.2970.93 (0.90) 0.34–3.57 (32) 4.0775.66 (2.39) 0.13–20.6 (24) 87.07259 (2.72) 0.17–1277 (31) 1.2671.57 (0.71) 0.03–5.10 (11) 1.4571.79 (0.52) 0.04–6.39 (14) 1.2670.88 (0.68) 0.29–3.10 (13) 1.4171.19 (1.17) 0.05–4.95 (33) 1.9871.65 (1.94) 0.03–6.60 (19) 4.0775.66 (2.39) 0.13–20.6 (24)
0.6971.44 (0.06) 0.01–5.41 (32) 1.3173.04 (0.06) 0.002–14.2 (24) 0.2170.49 (0.06) 0.002–2.44 (31) 0.2470.61 (0.05) 0.005–2.07 (11) 0.0770.08 (0.05) 0.005–0.35 (14) 0.1170.16 (0.06) 0.01–0.48 (13) 0.1270.44 (0.01) 0.001–2.25 (33) 0.3970.51 (0.20) 0.001–1.68 (19) 1.3173.04 (0.06) 0.002–14.18 (24)
6.30713.7 (0.62) 0.004–53.7 (24) 6.4478.70 (0.17) 0.01–16.7 (5) 0.4971.35 (0.10) 0.004–8.21 (42) 0.6672.36 (0.04) 0.01–8.84 (14) 0.4370.73 (0.13) 0.04–1.90 (6) 5.47710.6 (1.70) 0.02–38.3 (18) 3.13712.2 (0.05) 0.004–91.3 (86) 4.1075.93 (2.90) 0.06–14.4 (5) 0.0470.04 (0.04) 0.01–0.07 (2)
7.12722.9 (0.77) 0.004–112 (24) 0.7970.86 (0.56) 0.10–2.24 (5) 24.97147 (0.06) 0.003–952 (42) 0.0970.11 (0.03) 0.01–0.37 (14) 0.0770.09 (0.03) 0.003–0.24 (6) 0.7971.51 (0.27) 0.004–6.52 (18) 4.51724.6 (0.10) 0.003–166 (86) 5.79712.3 (0.34) 0.02–27.9 (5) 0.1770.05 (0.17) 0.13–0.20 (2)
15.1756.0 (1.65) 0.08–275 (24) 2577570 (2.80) 0.46–1276 (5) 1.8173.24 (1.15) 0.02–20.6 (42) 1.3971.34 (0.71) 0.31–4.95 (14) 3.8475.89 (1.67) 0.55–15.8 (6) 34.77131 (1.80) 0.03–559 (18) 1.9372.22 (1.45) 0.04–16.2 (86) 99.047217 (2.18) 0.64–488 (5) 0.4070.09 (0.40) 0.34–0.46 (2)
1.4875.32 (0.06) 0.002–25.9 (24) 1.3371.52 (0.53) 0.001–3.44 (5) 0.6272.21 (0.05) 0.001–14.2 (42) 0.0470.08 (0.02) 0.004–0.31 (14) 1.1271.82 (0.32) 0.02–4.71 (6) 0.7171.32 (0.24) 0.02–5.41 (18) 0.9373.93 (0.04) 0.001–28.1 (86) 0.2570.36 (0.10) 0.03–0.90 (5) 0.0370.04 (0.03) 0.01–0.06 (2)
In superscript a, three different numbers denote mean, 1SD, and median. In superscript b, three different numbers denote minimum, maximum, and the total number of measurements. c Refer to Table 2 for the original information of all single letter acronyms C through X. d Refer to Table 2 for the original information of all double letter acronyms of AT through XP.
(or median) values, when compared by such a dominant compound as H2S of Table 3(B) is found most abundantly in the following industrial sectors: L (leather: 1900 (mean) and 134 ppb (median)), P (paper and pulp: 21.1 and 1.36 ppb), and W sector (waste and sewage: 28.0 and 0.98 ppb). In the case of CS2, only the L sector seems to exceed the first criterion (87.0 and 2.72 ppb). If this
comparison is extended further by the second criterion of 1 ppb, the sum of additional 20 cases is found to meet that criterion. However, unlike the results of those two dominant compounds, other RSCs are generally found at significantly reduced values. The findings of the maximum mean value of CH3SH at the L sector suggest that its occurrence may be affected by the processes similar to that of
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490 20
C L P T
H2S
10
25 20
5
15 10
C L P T
DMS
15
F M S W
10
10 10 0 10 00 10 00 <
9
15
F M S W
10
< 00
10
0
00 10
10
10
9
7
5
3 1
0.
01
10 0 10 00 10 00 <
9
10
7
5
3
1
1 0.
1
0
0 01
C L P T
CS2
5
5
0.
20
0.
Frequency
20
7
Concentration (ppb)
Frequency
25
5
3
1
0. 01
< 00
10
0
00
10
10
9
10
7
5
3
1
1 0.
01
1
0
Concentration (ppb)
Concentration (ppb)
Concentration (ppb) 25
C L P T
DMDS 20
Frequency
F M S W
5
0 0.
C L P T
CH3SH
0.
Frequency
15
F M S W
Frequency
4486
15
F M S W
10 5
10 0 10 00 10 00 <
9
10
7
5
3
1
0. 1
0.
01
0
Concentration (ppb)
Fig. 3. A plot of frequency distribution pattern of RSC data for the comparison across the main 8 industrial sectors using their acronyms of C through W. Refer to Table 2 (or Fig 2) for the full information of those acronyms.
H2S. However, the results of DMS and DMDS are much different from those patterns with their maximum mean values occurring at the W and the F sectors, respectively. As shown in Table 3C, the RSC data measured from this study can also be compared among different source process types. Then, the occurrences of high mean values (e.g., above 10 ppb) are found more abundantly in H2S and CS2 than those evaluated on the basis of industrial sector. In the
case of H2S, the mean values exceeding the first criterion of 10 ppb are found from 6 out of 9 process types, including aeration tank (AT: 1139 (mean) and 5.52 ppb (median)), junction box (JB: 3,269 and 6.75 ppb), storing place (SP: 565 and 1.54 ppb), and so on. The occurrence of such large mean values are also found in CS2 at such units as JB (257 and 2.80 ppb), SP (34.7 and 1.80 ppb), and ST (99.0 and 2.18 ppb). However, the patterns for the other RSCs including CH3SH, DMS, and DMDS are seen
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
AT
JB
MP
SF
25
SK
SP
20
SR
ST
H2S
Frequency
30
15
50
CH3SH 40
Frequency
35
4487
30
AT
JB
MP
SF
SK
SP
SR
ST
20
10 10
5
JB
30
MP
SF
25
SK
SP
SR
ST
20 15 10
10
10 0 10 00 10 00 <
9
40
CS2 30
Frequency
Frequency
AT
DMS
7
Concentration (ppb)
Concentration (ppb) 35
5
3
1
0. 01
10 10 0 10 00 10 00 <
9
7
5
3
1
0. 1
0. 01
0. 1
0
0
AT
JB
MP
SF
SK
SP
SR
ST
20
10
5
DMDS
Frequency
40 30
10
10 0 10 00 10 00 <
9
7
5
3
1
0. 1
9
10
7
5
3
1
0. 1
0. 01
10 0 10 00 10 00 <
Concentration (ppb)
Concentration (ppb) 50
0. 01
0
0
AT
JB
MP
SF
SK
SP
SR
ST
20 10
10 0 10 00 10 00 <
9
10
7
5
3
1
0. 1
0.
01
0
Concentration (ppb)
Fig. 4. A plot of frequency distribution pattern of RSC data for comparison of the 8 main source process types. Refer to Table 2 for the double letter acronyms designated for source process types.
to be substantially lower than most process units. In compliance with general expectations, stack emissions of RSC are unlikely to be significant under the conditions favorable for their removal or destruction due to oxidization. The results of our comparative analysis on RSC emission patterns thus indicate that the RSC emissions can be distinguished to a certain degree by the combined criteria of both industry and process types.
As described above, a direct evaluation of concentration values among different RSCs has been meaningful to understand the fundamental aspects of RSC emissions from strong-source environments. However, if one considers that different chemicals possess different potentials as odors (e.g., Hurst et al., 2005), comparison of the measurement data in relation with malodor strength is useful to account for the relative importance of
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4488
Table 4 The relationship between relative malodor intensity and the matching RSC concentrationsa (A) A 1st-order function for the derivation of the malodor intensityb,c Pollutants
H2S
CH3SH
DMS
DMDS
Y ¼ 2.850 log X+4.14
Y ¼ 3.750 log X+5.99
Y ¼ 2.352 log X+4.06
Y ¼ 2.955 log X+4.51
(B) Comparison of malodor intensity (or degree of malodor) and the corresponding RSC concentration (in ppb unit) Degree of malodor
1 2 2.5 3 3.5 4 5
Corresponding RSC concentration in ppb H2S
CH3SH
DMS
DMDS
0.50 5.60 19.0 63.0 210 710 8000
0.12 0.65 1.60 4.10 10.0 26.0 160
0.12 2.30 10.0 44.5 190 840 1600
0.28 2.90 9.20 30.0 94.0 300 3100
a
All numerical functions for the derivation of malodor intensity have been introduced by Nagata (2003) and references therein. No equation is available for the compound CS2. c To begin with, RSC concentration in ppm scale is inserted into the formula as X; the resulting value of Y is yielded to express malodor intensity (or degree of malodor). b
different RSCs as odor components. For this purpose, we have adopted a series of numerical formulae introduced by Nagata and his colleagues (e.g., Nagata and Takeuchi, 1980; Nagata, 2003). Application of these formula can allow the conversion of the concentration values into the malodor intensity with index numbers of 1 through 5. As shown in Table 4A, the equations are built so that the converted intensity values are in some sense compatible with those of the sensory method (Hellman and Small, 1974; Leonardos et al., 1969; van Harreveld et al., 1999). A sample of computed data matching the malodor intensity and computed concentration values is also provided in Table 4B. This modified approach is thus applied to derive malodor intensity based on the mean concentration values of each RSC assorted in terms of the two classification criteria, industry type and process unit (Fig. 5). In the course of this conversion, the data sets for CS2 were not used, as it does not have comparable equations for such an application. However, if one considers that the odor threshold of CS2 is remarkably higher than other RSCs (e.g., 210 ppb of CS2 vs. 0.4 ppb of H2S (Nagata and Takeuchi, 1990)), its contribution is unlikely to be of significance relative to the other RSCs. According to this comparative approach, the importance of RSC emission sources is distinguished from each other in a simplistic manner. The significance of the
leather production industry (in terms of industry type) or aeration tank, settling tank, and junction box (in terms of process unit) is clearly distinguished from others with strong malodor intensity values. However, the patterns for these malodor intensity values differ slightly from those of the absolute values. For instance, although the relative importance of H2S is found to be most dominant on the basis of both criteria, that of CH3SH is also highly noticeable in terms of malodor intensity, mainly due to its strong threshold values (e.g., 0.1 ppb). 4. Conclusions In order to investigate the odor emission patterns from a large industrial area, the emission concentrations of RSCs were measured from 202 measurement points in a total of 77 companies at Ban Wall/Si Hwa industrial complex, Ansan city, Korea. The results of the analysis indicated that there are large differences in their concentration levels, while H2S generally tends to record the highest values of all RSCs. However, as seen by the comparison of statistical parameters, the distribution patterns of each compound vary remarkably. The mean concentration values are found to exceed the corresponding median values by one to two orders of magnitude. Such large variability can be explained by the effect of some exceptionally strong emissions
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4489
5
H2S CH3SH 4
DMS
Degree of malodor
DMDS 3
2
1
0
C
F
L
M P S Representative industrial sectors
T
W
X
5
H2S CH3SH
Degree of malodor
4
DMS DMDS
3
2
1
0
AT
JB
MP
SF SK SP Process classification
SR
ST
XP
Fig. 5. Relative contribution of each RSC to malodor intensity is compared for both (A) each individual industrial sector and (B) each source process type. Refer to Table 2 for the full information of both single- and double-letter acronyms (on the x-axis) selected to represent each sector or type. (Note that relative contribution of CS2 is not considered due to the unavailability of its conversion formula.) (A) Comparison of malodor intensity among each industrial sector (B) Comparison of malodor intensity among each source process type.
from certain source processes and/or certain industry types. As such, all of RSC emission data have been classified and compared in terms of two criteria: (1) industry type and (2) process (or treatment) type. When the RSC data are compared by the former criterion, the patterns showed some similarities in that strong emissions generally stem from a few industrial sectors such as the leather, sewage, paper and pulp, and food sectors. Similar to the H2S patterns, the strongest emissions of CH3SH were found from the leather and food industry sectors. When all data are compared in terms of process type within a given facility, there were more
clear distinctions in their distribution patterns. In the case of H2S, its emissions were found to be significant from almost all units, including aeration tank, junction box, and so on. Only exceptions to such trend were seen from stack and some miscellaneous ones. Other than H2S data, CS2 results showed strong emissions from four different units. However, when the results were evaluated in terms of their contribution to the formation of malodor by means of malodor intensity formula, the patterns were modified to a degree in that the patterns are dominated by H2S and CH3SH. In the present study, we intended to evaluate the
ARTICLE IN PRESS 4490
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
speciation and quantification of RSC emission concentration levels in a relatively broad range of industrial sectors. To acquire more quantitative information about the absolute contribution of RSC to odorous pollution in the study area, we are currently attempting to establish methods to obtain their emission fluxes under field-study conditions. Acknowledgements This study was supported by a grant offered by Ansan city through the management of Ansan Environmental Technology Development Center (AETDC). Part of this study was also aided by a Korea Research Foundation grant (KRF2005-201C00045). References Al-Shammiri, M., 2004. Hydrogen sulfide emission from the Ardiyah sewage treatment plant in Kuwait. Desalination 170, 1–13. Costi, P., Minciardi, R., Robba, M., Rovatti, M., Scile, R., 2004. An environmentally sustainable decision model for urban solid waste management. Waste Management 24, 277–295. Davoli, E., Gangai, M.L., Morselli, L., Tonelli, D., 2003. Characterization of odorants emissions from landfills by SPME and GC/MS. Chemosphere 51, 357–368. Emerson, C.W., Rajagopal, R., 2004. Measuring toxic emissions from landfills using sequential screening. Computers, Environment and Urban Systems 28, 265–284. Hellman, T.M., Small, F.H., 1974. Characterization of the odor properties of 101 petrochemicals using sensory method. Journal of Air Pollution Control Association 24 (10), 979–982.
Hurst, C., Longhurst, P., Pollard, S., Smith, R., Jefferson, B., Gronow, J., 2005. Assessment of municipal waste compost as a daily cover material for odour control at landfill sites. Environmental Pollution 135, 171–177. Kim, K.-H., 2005a. Some insights into the gas chromatographic determination of reduced sulfur compunds (RSC) in air. Environmental Science and Technology 39 (17), 6765–6769. Kim, K.-H., 2005b. Performance characterization of the GC/PFPD for H2S, CH3SH, DMS, and DMDS in air. Atmospheric Environment 39 (12), 2235–2242. Kim, K.-H., Choi, Y.-J., Jeon, E.-C., Sunwoo, Y., 2005a. Characterization of malodorous sulfur compounds in landfill gas. Atmospheric Environment 39 (6), 1103–1112. Kim, K.-H., Choi, Y.-J., Hong, Y.J., Sa, J.H., Park, J.H., Jeon, E.-C., Choi, C.R., Koo, Y.S., 2005b. Source characteristics of odorous compounds in the Ban Wal industrial complex and a preliminary study of industry-specific odor indices. Journal of Korean Atmospheric Environment 21 (2), 215–226. Leonardos, G., Kendall, D., Barnard, N., 1969. Odor threshold determination of 53 odorant chemicals. Journal of Air Pollution Control Association 19 (2), 91–95. Muezzinoglu, A., 2003. A study of volatile organic sulfur emissions causing urban odors. Chemosphere 51, 245–252. Nagata, Y., 2003. Odor intensity and odor threshold value. Journal of Japan Air Cleaning Association 41 (2), 17–25. Nagata, Y., Takeuchi, N., 1980. Relationship between concentration of odorants and odor intensity. Bulletin of Japan Environmental Sanitation Center 7, 75–86. Nagata, Y., Takeuchi, N., 1990. Measurement of odor threshold by triangle odor bag method. Bulletin of Japan Environmental Sanitation Center 17, 77–89. van Harreveld, A.P., Heeres, P., Harssema, H., 1999. A review of 20 years of standardization of odor concentration measurement by dynamic olfactometry in Europe. Journal of the Air and Waste Management Association 49, 705–715. Willig, S., Lacorn, M., Claus, R., 2004. Development of a rapid and accurate method for the determination of key compounds of pig odor. Journal of Chromatography 1038, 11–18.
Atmospheric Environment 40 (2006) 4478–4490 www.elsevier.com/locate/atmosenv
The emission characteristics and the related malodor intensities of gaseous reduced sulfur compounds (RSC) in a large industrial complex Ki-Hyun Kima,, Eui-Chan Jeona, Ye-Jin Choia, Youn-Seo Koob a
Department of Earth and Environmental Sciences, Sejong University, 98 Goon Ja Dong, Seoul, South Korea b Department of Environmental Engineering, Anyang University, Anyang, South Korea Received 13 December 2005; accepted 9 April 2006
Abstract In this study, the concentrations of major reduced sulfur compounds (RSC: H2S, CH3SH, DMS, CS2 and DMDS) were determined from various emission sources located within the Ban-Wall (BW)/ Si-Hwa (SH) industrial complex in Ansan city, Korea. The measurement data were obtained from a total of 202 individual points at 77 individual companies during 2004–2005. The highest RSC concentration levels came most dominantly from H2S (300 (mean) and 0.86 ppb (median)) followed by CS2, while the results of CH3, DMS, and DMDS are notably lower at the mean concentration levels of a few ppb. These data were evaluated further after being grouped into two different classification schemes: 9 industry sectors and 9 processing unit types. The strongest emissions of RSC, when evaluated among different industry sectors, are generally found from such industry types as leather, food, paper/pulp, as well as waste/sewage related ones. In contrast, when these RSC data are compared across different processing units, the highest values were seen most frequently from such units as junction boxes, aeration tanks, and settling tanks. The assessment of data in terms of relative contribution to malodor intensity showed that H2S and CH3SH are more important than others. The overall results of the present study suggest that information combining RSC speciation and types of anthropogenic activities may be used to distinguish the patterns of odorous pollution in areas affected by strong source processes. r 2006 Elsevier Ltd. All rights reserved. Keywords: Reduced sulfur compounds (RSC); H2S; Malodor; Industrial complex; Korea
1. Introduction It is commonly observed that malodor issues have become one of the hot socio-environmental subjects (Davoli et al., 2003; Emerson and Rajagopal, 2004). Malodor is defined as the single or composite of Corresponding author. Tel.: +82 19 595 3408; fax: +82 2 499 2354. E-mail address: [email protected] (K.-H. Kim).
1352-2310/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2006.04.026
chemical compounds which causes ill feelings by smelling through the sensory organ. Hence, it is often classified as sensory pollution that can damage more mentally or psychologically than physically. The sources of malodor are found to include a variety of man-made activities such as chemical plants, oil refineries, sewage treatments, landfills, livestock facilities, etc. (Al-Shammiri, 2004; Kim et al., 2005a, b; Willig et al., 2004). Evaluation of its impact can be subjective and intuitive, with the
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
complicated nature of odorant chemicals. It is thus considered to be a difficult task to provide a reliable tool to control the release of odorant pollutants from its sources (e.g., Costi et al., 2004). As a consequence, one cannot easily offer a practical
4479
strategy that can help relieve the effects of malodor pollution. Ban -Wall (BW)/Si -Hwa (SH) industrial complex (IC) is generally recognized to be the core production base to produce a variety of goods and
Fig. 1. The geographical location of the study site in Ansan city, Korea.
ARTICLE IN PRESS 4480
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
merchandises near the capital city of Seoul, Korea (refer to Fig. 1). Although BW/SH IC plays a major role in the Korean manufacturing industry, it has been blamed for malodor sources as many complaints have come from the residents residing in the surrounding areas. The occurrence of malodor complaints has increased drastically over the past several years. In light of its potent impact, stringent rules and regulations have been considered and were established to resolve the current situation of malodor pollution in the area. As part of project to characterize the emission patterns of malodor components and to build a malodor control policy, our study group has been involved in an intensive field study to measure the emission concentrations for a list of odorous pollutants released from various industrial activities (Kim et al., 2005b). In light of the fact that RSC belongs to a group of chemicals with strong odor potential, there has been a great demand to describe their emission characteristics in relation with various anthropogenic-source processes. To comply with such social and environmental demand, the measurements of RSC emission concentration have been taken from BW/SH IC from June 2004 to October 2005. In the present study, we attempted to evaluate the emission characteristics of odorous sulfur compounds from various industrial sectors operating in the large BW/SH industrial complex. 2. Materials and methods 2.1. Site characteristics The measurements of odorous compounds have been taken from the BW/SH IC in the city of An San (Gyung Gi province), Korea (Fig. 1). The industrial complex had been established since 1975 on the western side of the city that directly faces the western coastline of Korea. Afterwards, a large residential area consisting of high-altitude apartment buildings was built in the eastern side of the city in the 1990s. Because of the combined effects of geographical and meteorological conditions (e.g., prevalence of westerlies and oceanic winds), the residential area is generally designated as a downwind position to receive odors emitted from the nearby big sources. Aiming to develop plans to relieve malodor problems in Ansan city, we have been involved in a project to investigate sources of odorous emissions in the BW/SH industrial complex. As part of this
project, the concentrations of important odorous compounds have been measured from individual sources representative of various manufacturing units in 77 individual companies during June 2004 to October 2005. The target compounds of interests include the sum of 12 odorous compounds regulated by the Korean Ministry of Environment (KMOE) plus several aromatic VOC (refer to Table 1 for the list of pollutants). The designated 12 odorous pollutants consist of four different types of chemicals: (1) four reduced sulfur compounds (RSC: H2S, CH3SH, DMS, and DMDS), (2) five aldehydes including acetaldehyde, (3) N-compounds (trimethyl amine, and ammonia), and (4) styrene. In this study, we intended to focus solely on the RSC measurement data to provide the fundamental characteristics of the odorous emissions from industrial-source processes. The results of the other odorous pollutants will be dealt in our future publications. 2.2. Sample collection and analysis In this study, RSC samples from various emission sources were collected using the Tedlar bag sampling method (SKC corp., USA). For this purpose, all Tedlar bags (10 L capacity) were placed inside a lung-type gas-sampling system, built as a vacuumgeneration container. By controlling the vacuum pump and a 2-way rotary valve, samples were forced to be drawn directly into the Tedlar bags by the vacuum created inside the container. These samples were then brought to the lab as quickly as possible (e.g., within 24 h) to minimize the possibility of RSC loss due to the storage. To allow RSC measurements of varying sample types (in terms of concentration range), the gas chromatography (GC: Model DS 6200, Donam Instruments, Korea) equipped with a pulsed flame photometric detector (PFPD: Model 5380, O.I. Co.) was interfaced either with a loop injection system (high mode) or with an air server (AS)/thermal desorption (TD) unit (low mode). This dual analytical system has been built to switch between low (e.g., at or below 10 ppbv) and high-concentration ranges (e.g., at or above 10 ppbv). The details of the analytical performance of both analytical modes have been described in a series of articles made from our laboratory (Kim, 2005a, b). For the efficient collection of samples with sufficiently low RSC content, a multi-functioned TD system equipped with an AS unit (UNITY model, Markes International Ltd., UK) was operated to selectively
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4481
Table 1 A full list of odorous pollutants investigated in this study Odor Type
Regulation criteria typea Analytical methodb
Pollutatnts Full name
Short name Structural formula
Formaldehyde Acetaldehyde Acrolein Acetone Propionaldehyde crotonaldehyde Butyraldehyde Benzaldehyde Isovalerldehyde Valealdehyde o-Tolualdehyde m-Tolualdehyde p-Tolualdehyde
Form-A Acet-A Acrolein Acetone Propion-A Croton-A Butyr-A Benz-A Isovaler-A Valer-A o-Tolu-A m-Tolu-A p-Tolu-A
HCHO CH3CHO CH3–CHCHO CH3COCH3 CH3CH2CHO CH3CHQCHCHO CH3CH2CH2CHO C6H5CHO (CH3)2CHCH2CHO CH3(CH2)3CHO CH3C6H4CHO CH3C6H4CHO CH3C6H4CHO
Hydrogen sulfide Methyl mercaptan Dimethyl sulfide Carbon disulfide Dimethyl disulfide
H2S CH3SH DMS CS2 DMDS
H2S CH3SH (CH3)2S CS2 (CH3)2S2
C. Total and individual VOC Total VOC Benzene Toluene Ethylbenzene m,p-Xylene Styrene o-Xylene Bromobenzene 1,3,5-Trimethylbenzene 1,2,4-Trimethylbenzene p-Isopropyltoluene n-Bultylbenzene
TVOC B T E MPX STY OX BB 1,3,5-TMB 1,2,4-TMB p-IPT n-BB
C6H6 C6H5CH3 C6H5C2H5 (CH3)2C6H4 C6H5CHQCH2 (CH3)2C6H4 C6H5Br (CH3)3C6H6 (CH3)3C6H7 C10H14 C10H14
D. Ammonia E. Amine
NH3 TMA
NH3 (CH3)3N
A. Carbonyl compounds
B. Reduced S compounds
Ammonia Trimethyl amine
I
II II
DNPH+HPLC
II II
I I I
TB+GC/PFPD
I
I
TB+GC/FID
I I
IM+UVS TB+GC/FID
a
Pollutant type: Chemicals of type I and II were designated as criteria odorous pollutants before and after the new regulations started in February 2005 by the Korean Ministry of Environment (KMOE), respectively. b Sampling and analytical method: DNPH—sampling by a DNPH-cartridge, TB—sampling by Tedlar bag, IM—impinger, HPLC— analysis by HPLC method, GC—gas chromatography, PFPD—pulsed-flame photometric detector, FID—flame ionization detector, and UVS—UV spectrometer.
cryofocus samples with low S contents. The details of the AS/TD settings have been explained previously in our recent publications (Kim, 2005a). In contrast, to analyze RSC samples collected from strong-source areas, the loop injection system was employed directly by following the procedures introduced in our recent study (Kim, 2005b). The reduced S compounds delivered from either the AS/TD or loop system were then analyzed by a GC equipped with a pulsed flame photometric detector (PFPD: O.I. Co., Model 5380). Chromatographic separation of different RSC was done via BP-1
column (60 m 0.32 mm, 5.0 mm, SGE) for 20 min cycles. Other conditions for the GC analysis can be summarized as follows: Detector temp. of PFPD: 220 1C Flow rate (mL min1): Air(1) ¼ 10, Air(2) ¼ 10, H2 ¼ 11.5 Carrier gas : N2, 1.2 mL min1 (20 psi) Cold trap : low ¼ 15 1C, high ¼ 220 1C, hold time ¼ 5.0 min Outlet split : 5.0 mL min1 (5:1 split ratio) Flow path temp.: 80 1C
ARTICLE IN PRESS 4482
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
3. Results and discussion
criteria were used to initially divide all the individual companies to eight industrial sectors (Fig. 2) such as: (1) compound and chemical product (acronym, C), (2) food and beverage (F), (3) leather, bag, and shoes production (L), (4) metal assembly and production (M), (5) pulp and paper (P), (6) steel production (S), (7) textile production (T), and (8) waste treatment, sewage, and cleaning (W). Although 66 out of the total 77 companies were put together into those eight individual classes, all the remaining 11 companies defying such classification were grouped together as the ninth sector: (9) the miscellaneous or extra class (X). According to this grouping scheme, as plotted in Fig 2, all those 11 companies belonging to the class X are seen to consist of such industrial types as automobiles and trailers to wood and its products. Our field measurements were conducted to cover 2 to 4 measurement points for each individual company; each point was hence selected to represent the most important emission source processes (or units) in the given facility. During the entire study period, a total of 202 measurement points were selected and investigated from all 77 companies investigated. As shown in Table 2, many different types of source processes including diverse indoor spots were also investigated to evaluate the effects of different source process units. To simplify the classification of all those processes, all measurement points were classified into 9 different source categories. According to this classification criterion introduced in Table 2, scrubber rearside (SR) is found to be investigated most intensively (N ¼ 81) followed by manufacturing process (MP: N ¼ 45), aeration tank (AT: N ¼ 24), and so on.
3.1. Basic classification criteria for the industrial sectors and source process types
3.2. Emission concentrations of RSCs among industrial sectors and source process types
In Table 2, all RSC measurement data collected during the entire study period are pooled together and classified into two different classification schemes: (1) across different industrial sectors and (2) across different source process types. To simplify the comparison of emission patterns across different sectors and source types, two different types of acronyms were assigned to facilitate the classification as shown in Table 2; single-letter acronyms were used to distinguish a total of 9 industrial sectors, while two-letter ones were assigned for 9 operation (or treatment) process types. In the case of the former, the Korean standard classification
To assess the general characteristics of odorous RSC emissions in the study area, the emission concentration data were investigated by the two classification schemes introduced above. Hence in Table 3, a statistical summary of the entire measurement data is given in terms of both industry type and source process type. As compared by the overall mean concentration values of different RSCs of Table 3 (A), the mean concentration of H2S is found to record the highest of all compounds at 300 ppb. The mean concentration values of the other RSCs are found to be significantly reduced with their magnitude varying in the order CS2
In order to allow a simple comparison of the PFPD’s responses between different S compounds, integration of their peak areas was made in the linear mode with the square root (SR) function on. As the use of the SR function efficiently masks the squared response of the detector (i.e., due to the conversion of S atoms to an S2 complex), the whole calibration procedure can be facilitated by handling a simple first-order equation. Because the noise level of the blank was sufficiently low, calibration curves obtained from three (or four) points calibration typically showed an excellent linearity; correlation coefficients above 0.99 were commonly achieved, even at the offset mode, which forced the curve to pass through zero on both the x and y axes (Kim, 2005a). The analytical performance of the GC/PFPD setting between the loop injection and the PC/TD system was slightly different in terms of sensitivity. If the absolute DL values of RSC are compared between the two systems, the high-mode system generally exhibited the DL values of as little as a few pg (CH3SH, DMS, and DMDS) to 30 pg (H2S). It was however found that the DL values expressed in terms of absolute mass quantity were generally larger for the low-mode system than for the highmode system by a few times. In addition, if the precision is evaluated in terms of the relative standard error (RSE) of the triplicate analyses, it was found that the RSE values of both systems tend to fall in the range of 1–5%. The reproducibility of S gas detection was however rather variable with respect to the time and type of the RSC.
Symbol C F L M P S T W X 2 4 1 24
2
AT 5 4 6
Aeration Tank
2 5
1 2
JB
Junction Box
2 3 12 8 3 45
MP 5 8 4
Manufacturing Process
5 6 2 2 2 3 3 23
SF
Scrubber Front
1 4
1
1
SK 1
Stack
2 1 12
1
SP 3 1 4
Storing Place
13 81
SR 16 11 8 5 6 7 15
Scrubber Rear
6
2
1
1 2
ST
Settling Tank
2
XP 2
Miscellaneous Process
32 26 31 11 14 13 32 19 24 202
Sum
Two types of symbols are introduced here; single letter acronyms of C through X are given for the classification of each industrial type, while 2-letter ones for each source process type. a The ninth class of X named as miscellaneous ones include the following industrial sectors: (1) automobile and trailer, (2) electronic machine and converter, (3) electronics, gas and vapor, (4) furniture, (5) miscellaneous machine and instrument, (6) printing and publishing, (7) sewing and fur product, and (8) wood and its product.
Compound and chemical product Food and beverage Leather, bag, and shoes production Metal assembly and production Pulp, paper, etc. Steel production Textile Waste treatment, sewage and cleaning Miscellaneous onesa Sum
Type of industry (single letter) vs. Source process type (double letter Acronyms)
Table 2 Compilation of odorous emission sources for both industrial (N ¼ 9) and source process types (N ¼ 9) in this study with the definition of their acronyms using single and double letters, respectively
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
ARTICLE IN PRESS 4483
ARTICLE IN PRESS
Type of industry (Major code)
4484
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
Compound and chemical product (C) Food and beverage (F) Leather, bag, and shoes production (L) Metal assembly and production (M) Pulp, paper, etc. (P) Steel product (S) Textile (T) Waste treatment, Sewage and cleaning (W) Automobile and trailer (X1) Electronic machine and convertor (X2) Electronics, gas, and vapor (X3) Furniture (X4) Miscellaneous machine and instrument (X5) Printing and publishing (X6) Sewing, fur product (X7) Wood and its product (X8) 0
5
10
15
20
Number of companies Fig. 2. A list of industry types and grouping results of 77 companies investigated for the characterization of odor emission patterns. Classification is made based on a standard industrial classification code of Korea. First, a sum of 66 companies are classified into the 8 individual industrial groups with the symbols of C (Compound and chemical product) through W (Waste treatment, sewage, and cleaning). Then, the sum of remaining 11 companies (with their symbols of X1 (Automobile and trailer) through X8 (Wood and its product)) is combined together as the last 9th class (using symbol X) for statistical treatment.
(14.9), DMS (7.66), CH3SH (3.17), and DMDS (0.71 ppb). The observed RSC concentration levels in this study, when compared against those reported for other strong-source types, are comparable to the ones reported for ventilated landfill gas (LFG) samples in inactive landfill sites (Kim et al., 2005a). In our previous study of landfill composition, we found that the LFG concentration of H2S from inactive landfill was found as little as 336 ppb, while it goes up to a few thousand ppm in active LFG samples. The presence of such strong emissions for some RSCs (such as H2S and DMS) was also recognized from other urban-source processes (Muezzinoglu, 2003); this author found that H2S concentrations vary from as little as below 1 ppm and up to about 1000 ppm from creek water polluted by industrial wastes in Turkey. It is interesting to note that the distributions of most RSCs investigated in this study are extremely variable with their SD values typically exceeding the mean values by several times. Because of such variability, these RSC data have also been compared and evaluated by the median values along with the mean concentration values. It indicates that the magnitude of median values is reduced substantially from that of the mean values without exception. In fact, the H2S data seem to experience the most significant reduction such as from 300 (mean) to 0.86 ppb (median). However, the distribution patterns, when evaluated simply in terms of
median values only, seem to change in a rather narrow and constant range; their median values are in general smaller by one to two orders of magnitude than the mean values with the descending order of CS2 (1.39), H2S (0.86), DMS (0.13), CH3SH (0.09), and DMDS (0.05 ppb). In order to examine the occurrence patterns of RSC emissions more meaningfully, a comparison of these measurement data has been made after grouping them either into different industry types or into process types in Table 3B and C respectively. Their occurrence patterns are also plotted by each of the two classification criteria in Figs. 3 and 4, respectively. The results of this comparison suggest that most of RSC emissions may proceed in a low ppb concentration range, while their mean values are also affected persistently by the existence of exceptionally high values, especially in the case of H2S and CS2. Because of these unusually wide concentration ranges for most RSCs, comparison of the data measured in this study may be more meaningful with the aid of median values, if possible. For the purpose of comparison, their mean values shown in Table 3B and C were evaluated initially by their magnitude with the arbitrary two-stage criteria of 10 (first) and 1 ppb (second criterion). According to this approach, only 4 cases out of 45 individual cells (5 compounds 9 different sectors) exceeded the initial criterion of 10 ppb. The presence of those high mean
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4485
Table 3 A statistical summary of the emission concentrations of reduced S compounds (RSC) measured in this study Class
H2S
A. Summary on the entire data set All 30071911 (0.86)a 0.01–23311 (202)b B. Classification by industrial typec C 6.15717.9 (0.91) 0.04–97.4 (32) F 4.39715.9 (0.28) 0.01–78.6 (24) L 190074617 (134) 0.01–23310 (31) M 1.8873.61 (0.46) 0.02–12.3 (11) P 21.1751.1 (1.36) 0.07–174 (14) S 0.8871.92 (0.18) 0.01–7.12 (13) T 1.6176.52 (0.19) 0.01–37.6 (33) W 28.07102 (0.98) 0.03–448 (19) X 4.39715.9 (0.28) 0.01–78.6 (24) C. Classification by source process typed AT 113974735 (5.52)a 0.05–23311 (24)b JB 326974759 (6.75) 0.81–10468 (5) MP 8.63726.8 (0.42) 0.01–134 (42) SF 24.0787.4 (0.38) 0.01–328 (14) SK 0.9771.20 (0.55) 0.26–3.34 (6) SP 56571536 (1.54) 0.01–5691 (18) SR 36.37255 (0.58) 0.01–2360 (86) ST 73271419 (20.1) 0.82–3256 (5) XP 0.1670.14 (0.16) 0.06–0.26 (2)
CH3SH
DMS
CS2
DMDS
3.17710.7 (0.09) 0.004–91.3 (202)
7.66769.0 (0.13) 0.003–952 (202)
14.97105 (1.39) 0.03–1277 (202)
0.7172.84 (0.05) 0.001–28.1 (202)
2.0077.47 (0.07) 0.01–40.39 (32) 0.1870.24 (0.05) 0.01–0.78 (24) 7.31712.4 (2.11) 0.01–53.7 (31) 0.0670.08 (0.04) 0.01–0.30 (11) 0.9471.47 (0.05) 0.02–4.28 (14) 0.3971.22 (0.06) 0.01–4.44 (13) 0.0870.11 (0.03) 0.004–0.47 (33) 6.85716.5 (0.19) 0.02–59.4 (19) 0.1870.24 (0.05) 0.01–0.78 (24)
1.8874.82 (0.26) 0.004–26.2 (32) 0.6671.80 (0.08) 0.01–8.73 (24) 0.5071.10 (0.18) 0.004–5.98 (31) 0.3170.48 (0.10) 0.01–1.61 (11) 0.2570.50 (0.04) 0.003–1.68 (14) 0.1770.23 (0.04) 0.01–0.66 (13) 0.0970.10 (0.05) 0.003–0.45 (33) 3.4876.63 (0.45) 0.02–27.9 (19) 0.6671.80 (0.08) 0.01–8.73 (24)
1.2970.93 (0.90) 0.34–3.57 (32) 4.0775.66 (2.39) 0.13–20.6 (24) 87.07259 (2.72) 0.17–1277 (31) 1.2671.57 (0.71) 0.03–5.10 (11) 1.4571.79 (0.52) 0.04–6.39 (14) 1.2670.88 (0.68) 0.29–3.10 (13) 1.4171.19 (1.17) 0.05–4.95 (33) 1.9871.65 (1.94) 0.03–6.60 (19) 4.0775.66 (2.39) 0.13–20.6 (24)
0.6971.44 (0.06) 0.01–5.41 (32) 1.3173.04 (0.06) 0.002–14.2 (24) 0.2170.49 (0.06) 0.002–2.44 (31) 0.2470.61 (0.05) 0.005–2.07 (11) 0.0770.08 (0.05) 0.005–0.35 (14) 0.1170.16 (0.06) 0.01–0.48 (13) 0.1270.44 (0.01) 0.001–2.25 (33) 0.3970.51 (0.20) 0.001–1.68 (19) 1.3173.04 (0.06) 0.002–14.18 (24)
6.30713.7 (0.62) 0.004–53.7 (24) 6.4478.70 (0.17) 0.01–16.7 (5) 0.4971.35 (0.10) 0.004–8.21 (42) 0.6672.36 (0.04) 0.01–8.84 (14) 0.4370.73 (0.13) 0.04–1.90 (6) 5.47710.6 (1.70) 0.02–38.3 (18) 3.13712.2 (0.05) 0.004–91.3 (86) 4.1075.93 (2.90) 0.06–14.4 (5) 0.0470.04 (0.04) 0.01–0.07 (2)
7.12722.9 (0.77) 0.004–112 (24) 0.7970.86 (0.56) 0.10–2.24 (5) 24.97147 (0.06) 0.003–952 (42) 0.0970.11 (0.03) 0.01–0.37 (14) 0.0770.09 (0.03) 0.003–0.24 (6) 0.7971.51 (0.27) 0.004–6.52 (18) 4.51724.6 (0.10) 0.003–166 (86) 5.79712.3 (0.34) 0.02–27.9 (5) 0.1770.05 (0.17) 0.13–0.20 (2)
15.1756.0 (1.65) 0.08–275 (24) 2577570 (2.80) 0.46–1276 (5) 1.8173.24 (1.15) 0.02–20.6 (42) 1.3971.34 (0.71) 0.31–4.95 (14) 3.8475.89 (1.67) 0.55–15.8 (6) 34.77131 (1.80) 0.03–559 (18) 1.9372.22 (1.45) 0.04–16.2 (86) 99.047217 (2.18) 0.64–488 (5) 0.4070.09 (0.40) 0.34–0.46 (2)
1.4875.32 (0.06) 0.002–25.9 (24) 1.3371.52 (0.53) 0.001–3.44 (5) 0.6272.21 (0.05) 0.001–14.2 (42) 0.0470.08 (0.02) 0.004–0.31 (14) 1.1271.82 (0.32) 0.02–4.71 (6) 0.7171.32 (0.24) 0.02–5.41 (18) 0.9373.93 (0.04) 0.001–28.1 (86) 0.2570.36 (0.10) 0.03–0.90 (5) 0.0370.04 (0.03) 0.01–0.06 (2)
In superscript a, three different numbers denote mean, 1SD, and median. In superscript b, three different numbers denote minimum, maximum, and the total number of measurements. c Refer to Table 2 for the original information of all single letter acronyms C through X. d Refer to Table 2 for the original information of all double letter acronyms of AT through XP.
(or median) values, when compared by such a dominant compound as H2S of Table 3(B) is found most abundantly in the following industrial sectors: L (leather: 1900 (mean) and 134 ppb (median)), P (paper and pulp: 21.1 and 1.36 ppb), and W sector (waste and sewage: 28.0 and 0.98 ppb). In the case of CS2, only the L sector seems to exceed the first criterion (87.0 and 2.72 ppb). If this
comparison is extended further by the second criterion of 1 ppb, the sum of additional 20 cases is found to meet that criterion. However, unlike the results of those two dominant compounds, other RSCs are generally found at significantly reduced values. The findings of the maximum mean value of CH3SH at the L sector suggest that its occurrence may be affected by the processes similar to that of
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490 20
C L P T
H2S
10
25 20
5
15 10
C L P T
DMS
15
F M S W
10
10 10 0 10 00 10 00 <
9
15
F M S W
10
< 00
10
0
00 10
10
10
9
7
5
3 1
0.
01
10 0 10 00 10 00 <
9
10
7
5
3
1
1 0.
1
0
0 01
C L P T
CS2
5
5
0.
20
0.
Frequency
20
7
Concentration (ppb)
Frequency
25
5
3
1
0. 01
< 00
10
0
00
10
10
9
10
7
5
3
1
1 0.
01
1
0
Concentration (ppb)
Concentration (ppb)
Concentration (ppb) 25
C L P T
DMDS 20
Frequency
F M S W
5
0 0.
C L P T
CH3SH
0.
Frequency
15
F M S W
Frequency
4486
15
F M S W
10 5
10 0 10 00 10 00 <
9
10
7
5
3
1
0. 1
0.
01
0
Concentration (ppb)
Fig. 3. A plot of frequency distribution pattern of RSC data for the comparison across the main 8 industrial sectors using their acronyms of C through W. Refer to Table 2 (or Fig 2) for the full information of those acronyms.
H2S. However, the results of DMS and DMDS are much different from those patterns with their maximum mean values occurring at the W and the F sectors, respectively. As shown in Table 3C, the RSC data measured from this study can also be compared among different source process types. Then, the occurrences of high mean values (e.g., above 10 ppb) are found more abundantly in H2S and CS2 than those evaluated on the basis of industrial sector. In the
case of H2S, the mean values exceeding the first criterion of 10 ppb are found from 6 out of 9 process types, including aeration tank (AT: 1139 (mean) and 5.52 ppb (median)), junction box (JB: 3,269 and 6.75 ppb), storing place (SP: 565 and 1.54 ppb), and so on. The occurrence of such large mean values are also found in CS2 at such units as JB (257 and 2.80 ppb), SP (34.7 and 1.80 ppb), and ST (99.0 and 2.18 ppb). However, the patterns for the other RSCs including CH3SH, DMS, and DMDS are seen
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
AT
JB
MP
SF
25
SK
SP
20
SR
ST
H2S
Frequency
30
15
50
CH3SH 40
Frequency
35
4487
30
AT
JB
MP
SF
SK
SP
SR
ST
20
10 10
5
JB
30
MP
SF
25
SK
SP
SR
ST
20 15 10
10
10 0 10 00 10 00 <
9
40
CS2 30
Frequency
Frequency
AT
DMS
7
Concentration (ppb)
Concentration (ppb) 35
5
3
1
0. 01
10 10 0 10 00 10 00 <
9
7
5
3
1
0. 1
0. 01
0. 1
0
0
AT
JB
MP
SF
SK
SP
SR
ST
20
10
5
DMDS
Frequency
40 30
10
10 0 10 00 10 00 <
9
7
5
3
1
0. 1
9
10
7
5
3
1
0. 1
0. 01
10 0 10 00 10 00 <
Concentration (ppb)
Concentration (ppb) 50
0. 01
0
0
AT
JB
MP
SF
SK
SP
SR
ST
20 10
10 0 10 00 10 00 <
9
10
7
5
3
1
0. 1
0.
01
0
Concentration (ppb)
Fig. 4. A plot of frequency distribution pattern of RSC data for comparison of the 8 main source process types. Refer to Table 2 for the double letter acronyms designated for source process types.
to be substantially lower than most process units. In compliance with general expectations, stack emissions of RSC are unlikely to be significant under the conditions favorable for their removal or destruction due to oxidization. The results of our comparative analysis on RSC emission patterns thus indicate that the RSC emissions can be distinguished to a certain degree by the combined criteria of both industry and process types.
As described above, a direct evaluation of concentration values among different RSCs has been meaningful to understand the fundamental aspects of RSC emissions from strong-source environments. However, if one considers that different chemicals possess different potentials as odors (e.g., Hurst et al., 2005), comparison of the measurement data in relation with malodor strength is useful to account for the relative importance of
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4488
Table 4 The relationship between relative malodor intensity and the matching RSC concentrationsa (A) A 1st-order function for the derivation of the malodor intensityb,c Pollutants
H2S
CH3SH
DMS
DMDS
Y ¼ 2.850 log X+4.14
Y ¼ 3.750 log X+5.99
Y ¼ 2.352 log X+4.06
Y ¼ 2.955 log X+4.51
(B) Comparison of malodor intensity (or degree of malodor) and the corresponding RSC concentration (in ppb unit) Degree of malodor
1 2 2.5 3 3.5 4 5
Corresponding RSC concentration in ppb H2S
CH3SH
DMS
DMDS
0.50 5.60 19.0 63.0 210 710 8000
0.12 0.65 1.60 4.10 10.0 26.0 160
0.12 2.30 10.0 44.5 190 840 1600
0.28 2.90 9.20 30.0 94.0 300 3100
a
All numerical functions for the derivation of malodor intensity have been introduced by Nagata (2003) and references therein. No equation is available for the compound CS2. c To begin with, RSC concentration in ppm scale is inserted into the formula as X; the resulting value of Y is yielded to express malodor intensity (or degree of malodor). b
different RSCs as odor components. For this purpose, we have adopted a series of numerical formulae introduced by Nagata and his colleagues (e.g., Nagata and Takeuchi, 1980; Nagata, 2003). Application of these formula can allow the conversion of the concentration values into the malodor intensity with index numbers of 1 through 5. As shown in Table 4A, the equations are built so that the converted intensity values are in some sense compatible with those of the sensory method (Hellman and Small, 1974; Leonardos et al., 1969; van Harreveld et al., 1999). A sample of computed data matching the malodor intensity and computed concentration values is also provided in Table 4B. This modified approach is thus applied to derive malodor intensity based on the mean concentration values of each RSC assorted in terms of the two classification criteria, industry type and process unit (Fig. 5). In the course of this conversion, the data sets for CS2 were not used, as it does not have comparable equations for such an application. However, if one considers that the odor threshold of CS2 is remarkably higher than other RSCs (e.g., 210 ppb of CS2 vs. 0.4 ppb of H2S (Nagata and Takeuchi, 1990)), its contribution is unlikely to be of significance relative to the other RSCs. According to this comparative approach, the importance of RSC emission sources is distinguished from each other in a simplistic manner. The significance of the
leather production industry (in terms of industry type) or aeration tank, settling tank, and junction box (in terms of process unit) is clearly distinguished from others with strong malodor intensity values. However, the patterns for these malodor intensity values differ slightly from those of the absolute values. For instance, although the relative importance of H2S is found to be most dominant on the basis of both criteria, that of CH3SH is also highly noticeable in terms of malodor intensity, mainly due to its strong threshold values (e.g., 0.1 ppb). 4. Conclusions In order to investigate the odor emission patterns from a large industrial area, the emission concentrations of RSCs were measured from 202 measurement points in a total of 77 companies at Ban Wall/Si Hwa industrial complex, Ansan city, Korea. The results of the analysis indicated that there are large differences in their concentration levels, while H2S generally tends to record the highest values of all RSCs. However, as seen by the comparison of statistical parameters, the distribution patterns of each compound vary remarkably. The mean concentration values are found to exceed the corresponding median values by one to two orders of magnitude. Such large variability can be explained by the effect of some exceptionally strong emissions
ARTICLE IN PRESS K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
4489
5
H2S CH3SH 4
DMS
Degree of malodor
DMDS 3
2
1
0
C
F
L
M P S Representative industrial sectors
T
W
X
5
H2S CH3SH
Degree of malodor
4
DMS DMDS
3
2
1
0
AT
JB
MP
SF SK SP Process classification
SR
ST
XP
Fig. 5. Relative contribution of each RSC to malodor intensity is compared for both (A) each individual industrial sector and (B) each source process type. Refer to Table 2 for the full information of both single- and double-letter acronyms (on the x-axis) selected to represent each sector or type. (Note that relative contribution of CS2 is not considered due to the unavailability of its conversion formula.) (A) Comparison of malodor intensity among each industrial sector (B) Comparison of malodor intensity among each source process type.
from certain source processes and/or certain industry types. As such, all of RSC emission data have been classified and compared in terms of two criteria: (1) industry type and (2) process (or treatment) type. When the RSC data are compared by the former criterion, the patterns showed some similarities in that strong emissions generally stem from a few industrial sectors such as the leather, sewage, paper and pulp, and food sectors. Similar to the H2S patterns, the strongest emissions of CH3SH were found from the leather and food industry sectors. When all data are compared in terms of process type within a given facility, there were more
clear distinctions in their distribution patterns. In the case of H2S, its emissions were found to be significant from almost all units, including aeration tank, junction box, and so on. Only exceptions to such trend were seen from stack and some miscellaneous ones. Other than H2S data, CS2 results showed strong emissions from four different units. However, when the results were evaluated in terms of their contribution to the formation of malodor by means of malodor intensity formula, the patterns were modified to a degree in that the patterns are dominated by H2S and CH3SH. In the present study, we intended to evaluate the
ARTICLE IN PRESS 4490
K.-H. Kim et al. / Atmospheric Environment 40 (2006) 4478–4490
speciation and quantification of RSC emission concentration levels in a relatively broad range of industrial sectors. To acquire more quantitative information about the absolute contribution of RSC to odorous pollution in the study area, we are currently attempting to establish methods to obtain their emission fluxes under field-study conditions. Acknowledgements This study was supported by a grant offered by Ansan city through the management of Ansan Environmental Technology Development Center (AETDC). Part of this study was also aided by a Korea Research Foundation grant (KRF2005-201C00045). References Al-Shammiri, M., 2004. Hydrogen sulfide emission from the Ardiyah sewage treatment plant in Kuwait. Desalination 170, 1–13. Costi, P., Minciardi, R., Robba, M., Rovatti, M., Scile, R., 2004. An environmentally sustainable decision model for urban solid waste management. Waste Management 24, 277–295. Davoli, E., Gangai, M.L., Morselli, L., Tonelli, D., 2003. Characterization of odorants emissions from landfills by SPME and GC/MS. Chemosphere 51, 357–368. Emerson, C.W., Rajagopal, R., 2004. Measuring toxic emissions from landfills using sequential screening. Computers, Environment and Urban Systems 28, 265–284. Hellman, T.M., Small, F.H., 1974. Characterization of the odor properties of 101 petrochemicals using sensory method. Journal of Air Pollution Control Association 24 (10), 979–982.
Hurst, C., Longhurst, P., Pollard, S., Smith, R., Jefferson, B., Gronow, J., 2005. Assessment of municipal waste compost as a daily cover material for odour control at landfill sites. Environmental Pollution 135, 171–177. Kim, K.-H., 2005a. Some insights into the gas chromatographic determination of reduced sulfur compunds (RSC) in air. Environmental Science and Technology 39 (17), 6765–6769. Kim, K.-H., 2005b. Performance characterization of the GC/PFPD for H2S, CH3SH, DMS, and DMDS in air. Atmospheric Environment 39 (12), 2235–2242. Kim, K.-H., Choi, Y.-J., Jeon, E.-C., Sunwoo, Y., 2005a. Characterization of malodorous sulfur compounds in landfill gas. Atmospheric Environment 39 (6), 1103–1112. Kim, K.-H., Choi, Y.-J., Hong, Y.J., Sa, J.H., Park, J.H., Jeon, E.-C., Choi, C.R., Koo, Y.S., 2005b. Source characteristics of odorous compounds in the Ban Wal industrial complex and a preliminary study of industry-specific odor indices. Journal of Korean Atmospheric Environment 21 (2), 215–226. Leonardos, G., Kendall, D., Barnard, N., 1969. Odor threshold determination of 53 odorant chemicals. Journal of Air Pollution Control Association 19 (2), 91–95. Muezzinoglu, A., 2003. A study of volatile organic sulfur emissions causing urban odors. Chemosphere 51, 245–252. Nagata, Y., 2003. Odor intensity and odor threshold value. Journal of Japan Air Cleaning Association 41 (2), 17–25. Nagata, Y., Takeuchi, N., 1980. Relationship between concentration of odorants and odor intensity. Bulletin of Japan Environmental Sanitation Center 7, 75–86. Nagata, Y., Takeuchi, N., 1990. Measurement of odor threshold by triangle odor bag method. Bulletin of Japan Environmental Sanitation Center 17, 77–89. van Harreveld, A.P., Heeres, P., Harssema, H., 1999. A review of 20 years of standardization of odor concentration measurement by dynamic olfactometry in Europe. Journal of the Air and Waste Management Association 49, 705–715. Willig, S., Lacorn, M., Claus, R., 2004. Development of a rapid and accurate method for the determination of key compounds of pig odor. Journal of Chromatography 1038, 11–18.