Abstract

The Houjing River has long been an environmental victim of economic development. Industries that have settled along the bank of this river may have largely contributed to severe organic wastes pollution. This study collected water and sediment samples at various points along the river and measured concentrations of 61 volatile organic compounds (VOCs) and 128 semi-volatile organic compounds (SVOCs) for a period of 16 months (Feb 2014–June 2015). Our analyses show that elevated levels of VOCs were observed near two industrial areas, Dashe and Renwu industrial parks. High SVOC concentrations were found in the vicinities of the Nanzih Export Processing Zone (NEPZ) and CingPu station, possibly due to considerable effluent discharges of adjacent industrial and residential areas. Comparing this study's findings with the standard values of different governmental agencies and studies similar to this one, the ecosystem of the Houjing River was seriously contaminated. This study could be used by the government as a basis for future and urgent pollution prevention actions aimed at protecting this ecosystem and reducing the negative impacts of these contaminants on the health and well-being of the local residents and the environment.

INTRODUCTION

Rivers are highly dynamic systems that change as a function of their catchments and water flows. These ecosystems are strongly influenced by the inflow of their effluents and climate change. River-basin monitoring programs require a continuous tracking of several environmental parameters in order to evaluate the state of the local environment. Organic contamination in densely populated areas is often investigated, as this has been proven to be highly dangerous to human health (Lee et al. 2002; Ost et al. 2003; de Gennaro et al. 2013; Senthil Kumar et al. 2017; Chen et al. 2016; Kristin et al. 2016). Therefore, any effort to assess and manage organic contaminant emissions, especially in populated industrial areas, should be extolled.

Anthropogenic activities that commonly take place near or along water bodies around the world have contributed to the rapid degradation of these natural resources (Lekkas et al. 2004; Moliner-Martinez et al. 2013; Hassanzadeh et al. 2014; Liu et al. 2016). River basins have been exposed to diffuse pollution when persistent, toxic and deleterious compounds are released by urban, industrial and agricultural activities (Huang et al. 2014; Villanueva & Ibarra 2016). The use of chlorinated consumer products has been reported as a potential source of organic contamination (Odabasi et al. 2014). Water, soil and sediments have often been used to measure organic contaminants and analyze water body quality (Moliner-Martinez et al. 2013; Hassanzadeh et al. 2014) and to assess contamination in areas' aquatic systems (Moliner-Martinez et al. 2013; Hassanzadeh et al. 2014; Liu et al. 2015).

Taiwan has made remarkable social and political gains since the 1950s due to its huge economic and material progress. The country has gone through a long period of industrial development and is now recognized as home to a world-class semiconductor industry (Lin et al. 2009). The perils of such enormous growth, however, have consequently contributed to the severe degradation of its environment (Williams & Chang 2008), especially its scarce water resources (Hung et al. 2007). Water bodies around Taiwan have been used as waste dumps, and thus are heavily contaminated with organic compounds (Hung et al. 2007; Wang et al. 2015b).

Before the industrialization, the Houjing River was formerly a reliable source of clean water for human use and agricultural activities such as fish and crop farming (Sun & Tsai 2009). The establishment of petrochemical, plastic, and semiconductor industries has contributed to the region's rapid economic expansion (Sun & Tsai 2009; Patterson 2014). Currently, water from the river is unsuitable for household, recreational or agricultural use. Local residents are now exerting strong pressure on the city government in order to restore the ecosystem's water quality.

Organic contamination of the ecosystem may be attributed to the establishment of numerous manufacturing plants in four industrial areas along the river: Dashe and Renwu industrial parks, the Kaohsiung Oil Refinery, and Nanzih export processing zone (NEPZ). Industries located in the two parks and the oil refinery specialize in petrochemical productions. These factories were suspected of flushing high concentrations of toxic compounds such as benzene, toluene, ethylbenzene, and xylene (or BTEX) into the river (Hsieh et al. 2006). Runoff from the Formosa Plastics Corporation, located at the Renwu industrial park, could be responsible for the formation of chlorinated toxic by-product compounds such as vinyl chloride, methylene chloride, 1,1-dichloroethane, chloroform, 1,2-dichloroethane, etc. (Huang et al. 2014). Metal processing, chemical manufacture, and plastics resin production industries are common in the NEPZ, Dashe and Renwu industrial parks. These industrial effluents, coupled with commercial and domestic wastes in the Nanzih District, could be the source of phthalate esters (PAEs) pollution (Staples et al. 1997).

The goal of this study was to measure the contamination levels of volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) in water and sediment samples collected from various sites in the Houjing River to evaluate current ecosystem quality and suggest potential sources of pollution or toxic hotspots. Results of this study could be used to locate ecosystem pollution hotspots necessary to help mitigate the severe negative impact of river contamination on human health and provide the basis for local government to implement more stringent regulations for wastewater and sludge treatment, disposal and recycling.

MATERIALS AND METHODS

Study site

The Houjing River is located in north-west Kaohsiung City, an industrial harbor city in southwestern Taiwan (22°69′ – 22°73′, 120°25′ – 120°33′). The river stems from two streams that flow from Dashe from the northeast (Ciaotou District) and Renwu (Renwu District) from the southeast (Figure 1). These river branches meet at Si-Chingpu Landfill. Except for a few branches fluxing around the area of Nanzih District, the river flows directly toward the Taiwan Strait. It has a length of about 21 km. The climate in the basin is characterized by long summers and winters, while springs and autumns are relatively short. The river used to be a major water source for irrigation and fish farming. However, the progressive installation and expansion of industrial areas along the river, coupled with lenient legislations against illegal wastewater and sludge discharges, have contributed to serious contamination of this ecosystem (Lin et al. 2010). Recent studies showed that the system toxicity has been contaminating biological resources directly consumed by humans (Sun & Tsai 2009; Patterson 2014).

Figure 1

Location and map of the Houjing River in Taiwan showing the nine stations considered in this study.

Figure 1

Location and map of the Houjing River in Taiwan showing the nine stations considered in this study.

Sampling

In order to cover all possible contamination point sources of the river, nine specific sampling sites were chosen: Sannaitan, Jingjian, Bakong, Renwu, Hueifeng, Deming, CingPu, Dehuei and Youchangda. The stations considered were located in four potential contamination source zones. Sannaitan and Jingjian stations were chosen to investigate the potential impact of effluents from the Dashe industrial park. The Bakong, Renwu and Hueifeng stations were considered to examine potential contamination of industries at the Renwu industrial park and the Kaohsiung Oil Refinery. Similarly, Deming, CingPu, Dehuei and Youchangda stations were considered to examine potential contamination of industrial activities at NEPZ. Water and sediment samples were collected based on the United States Environmental Protection Agency (USEPA) methods (Lin et al. 2007; Lin et al. 2009; USEPA 2013, 2014). Water samples were used for VOC analyses. Surface water was collected using a bucket in the middle of the river (about 5 m from the river banks) and kept in 40 mL amber screw VOC vials, which were cleaned with deionized water before the sample collection. Sediment samples were collected for SVOC analyses. Surface sediments (about 10–15 cm from the surface) were collected using an Ekman dredge and stored in pre-cleaned 500 mL amber screw bottles. At each site, two water and sediment replicates were collected. All samples were kept in an ice cooler box during transport. At the laboratory, they were stored and maintained for 3 days at −4 °C until the analysis. Sixty-one VOCs and 128 SVOCs were measured and analyzed for a period of 16 months (Feb 2014 – June 2015). Sample collections were usually attempted to be carried out during sunny days to avoid the potential dilution effect caused by rainfall, runoff and rapid water currents. However, climate instabilities might have affected samples and introduced some biases in our analyses.

Instrumental analysis

Volatile organic compounds

The USEPA Method 8260B was used in this study to quantify VOCs that have boiling points below 200 °C. The most common sample-preparation technique for 8260B is provided by USEPA 5030, which recommends a Purge-and-Trap technique. Both the OI Analytical model 4552 autosampler and the Eclipse 4660 Purge-and-Trap sample concentrator were employed to preprocess samples for analysis by gas chromatography/mass spectrometry (GC/MS). An HP 6890 GC coupled with the 5973N MS system was used for VOC analysis. A total of 61 compounds was analyzed, including BTEX and chlorinated VOCs. Before beginning the 8260B analysis, the GC/MS system should be conditioned and prepared for use. The Purge-and-Trap optimization conditions employed were a 5 mL purge vessel (VOCARB 4560 Trap), with a 40 mL·min−1 helium purge flow at purge-ready temperature of 20 °C for 13 minutes. The purged samples were desorbed at 180 °C for four minutes then baked for 15 minutes at 200 °C. For the GC/MS system, a capillary separation column (HP-624, 60 m × 0.25 mm × 1.5 μm film thickness) was installed. The oven was pre-heated at 40 °C for one minute before increasing the temperature to 180 °C at a rate of 8 °C·min−1 and finally to 220 °C at a rate of 10 °C·min−1 for 10 minutes.

Deionized (DI) water was used for the preparation of standards and test samples. All samples and calibration standards were then spiked with an internal standard/surrogates mixture. The mixture used is composed of non-deuterated fluorobenzene as the internal standard and non-deuterated 4-bromofluorobenzene with deuterated 1,2-dichlorobenzene as surrogates. Non-deuterated fluorobenzene gave the closest retention time to the target analyte, and was used in the response factor (RF) calculation for each compound. As a minimum, the 8260B method requires a five-point calibration curve. In this study, calibration levels at 2, 5, 20, 40 and 100 μg·mL−1 were considered. The correlation coefficients (r-value) of curves estimated were >0.995. Water blanks from laboratory and field samples were analyzed to establish a baseline. Seven samples with the same concentration were prepared to estimate the method detection limits (MDLs). Each individual analyte's MDL was obtained by multiplying three times the standard deviation (SD) by the appropriate one-sided 99% t-statistic. The MDL values for VOCs ranged from 0.3 to 0.9 μg·L−1. Water, laboratory and field samples showed non-detected (ND) values. For every batch of 10 samples, standard mid-point and spiked-sample checks were performed. Standard mid-point and spiked sample percent recoveries were from 90 to 110% and from 75 to 94%, respectively. Accuracies of the measures were 100 ± 10%.

Semi-volatile organic compounds

A low concentration method was performed by mixing a 10-gram dried sediment sample with 20 g anhydrous sodium sulfate to form a free-flowing powder. USEPA Method 3550C was the ultrasonic process used to extract nonvolatile and SVOCs with solvent three times at three minute intervals. A 10-μL surrogate standard solution was added before performing the dichloromethane (DCM) ultrasonic extraction. The DCM extract was collected and concentrated by a Turbo Vap II concentrator prior to injection into the GC/MS system for analysis. The Method 8270D was the GC/MS used to determine SVOC concentrations. A total of 120 compounds were analyzed. Sediment sample preparation and analysis employed were based on Lin et al. 2009.

Standard SVOC mixtures and deuterated internal standards (1,4-dichlorobenzene, naphthalene, acenaphthene, phenanthrene, chrysene, perylene) were purchased from SUPELCO (Bellefonte, Pennsylvania, USA). Six calibration levels (1.25, 5, 10, 20, 40 and 100 μg·mL−1) were considered for the Method 3550C. Relative RFs of all compounds were above 0.05, while the percentage of deviation of each compound was <20%. In order to ensure good data quality, a decafluorotriphenylphosphine (DFTPP) standard check was performed to calibrate the mass selective detector (MSD) before analysis. A system proficiency calibration check (SPCC) was also performed once every 12 hours of analysis. Blank and spike recovery tests were carried out afterwards. Similar to VOC measurements, MDLs were estimated from blanks and seven samples of the same concentration. Again, an individual MDL analyte was calculated from the product of the SD by the appropriate one-sided 99% t-statistic. The MDL values for SVOCs ranged from 0.1 to 0.5 mg·kg−1 dry weight. The blanks showed ND values. Standard mid-point and spiked-sample checks were performed per 10-sample batch. Standard mid-point and spiked-sample recoveries were from 90 to 108% and from 79 to 85%, respectively. Accuracies of the measures were 100 ± 10%.

All the chemicals were of reagent grade and all standards were NIST traceable quality. DI water was used in all analyses.

RESULTS AND DISCUSSION

Spatial distribution and potential sources of VOC contamination

Figure 2 shows the spatial distribution of the total VOC concentrations in different sampling sites of the Houjing River. VOCs were detected in all stations except Bakong and Sannaitan. High SDs around mean values could be due to variation in findings over time. Total VOC concentrations in samples collected at Jingjian and Renwu stations were unusually high (102.7 ± 184.5 and 131.2 ± 105.1 μg·L−1, respectively). Observed concentrations at CingPu and Hueifeng stations (16.3 ± 18.3 and 42.4 ± 27.9 μg·L−1, respectively) were considerably lower. VOC concentrations continued to decline at the Dehuei (17.9 ± 15.2 μg·L−1) and Youchangda (9.8 ± 7.3 μg·L−1) stations. These two latter stations were located near the river mouth, where freshwater was constantly mixed with seawater. Based on these results, the potential main sources that contributed to severe total VOC contamination of the ecosystem were most likely located around the vicinity of Jingjian and Renwu stations. These two stations were located near the Dashe and Renwu industrial parks, which included numerous petrochemical and plastic manufacturers. Total VOCs decreased progressively towards the downstream areas of the river, possibly due to the natural dilution effect caused by seawater. Special attention was given to BTEX, a well-known carcinogen, and chlorinated VOC pollutants, which are harmful to both human and environmental health, and results are further discussed below.

Figure 2

Total VOC (μg·L−1) and SVOC (mg·kg−1 dry weight) concentrations in water and sediment samples collected from the Houjing River, respectively. NEPZ: Nanzih Export Processing Zone; KOR: Kaoshing Oil Refinery; RIP: Renwu industrial park; DIP: Dashe industrial park.

Figure 2

Total VOC (μg·L−1) and SVOC (mg·kg−1 dry weight) concentrations in water and sediment samples collected from the Houjing River, respectively. NEPZ: Nanzih Export Processing Zone; KOR: Kaoshing Oil Refinery; RIP: Renwu industrial park; DIP: Dashe industrial park.

BTEX contamination

Samples collected from the Jingjian station showed the highest BTEX value of 102.7 ± 184.5 μg·L−1, which may be due to petrochemical industry effluents in the Dashe industrial park. A comparison with established standards by the USEPA (USEPA 2015) and Japan's Ministry of Environment (JMOE) (MOE 1993) was provided for a more comprehensive view of the current BTEX river contamination (Table 1). Benzene, toluene and ethylbenzene were detected in water samples from the five BTEX compounds analyzed. The ethylbenzene maximum value was estimated at 270.6 μg·L−1, which is four times higher than the accepted USEPA limit (68 μg·L−1). In this study, the more stringent value of USEPA for toluene (57 μg·L−1) was selected for the comparison. Highest toluene concentration at the Jingjian station (17.0 μg·L−1) estimated was found to be within the acceptable USEPA limit. The mean concentration of benzene (44.5 μg·L−1) exceeded the Japan MOE's limit (10 μg·L−1) and was more than twentyfold higher than the upper limit set by USEPA's range (0.58–2.1 μg·L−1). Ethylbenzene concentrations ranged from 0 to 270.6 μg·L−1, with some far above the USEPA limit (68 μg·L−1) while others were lower (mean value 54.5 μg·L−1). Meanwhile, no xylene compounds were observed.

Table 1

Min-max BTEX concentrations (μg·L−1) in water samples at the Jingjian station (n = 8)

Compound name MDLs Min Max Mean USEPA JMOE 
Benzene 0.4 0.9 158.0 44.5 0.58–2.1 10 
Toluene 0.3 17.0 3.7 57 600 
Ethylbenzene 0.6 270.6 54.5 68 NA 
p,m-Xylene 0.5 ND ND ND NA 400 
o-Xylene 0.6 ND ND ND NA 400 
Compound name MDLs Min Max Mean USEPA JMOE 
Benzene 0.4 0.9 158.0 44.5 0.58–2.1 10 
Toluene 0.3 17.0 3.7 57 600 
Ethylbenzene 0.6 270.6 54.5 68 NA 
p,m-Xylene 0.5 ND ND ND NA 400 
o-Xylene 0.6 ND ND ND NA 400 

USEPA (United States Environmental Protection Agency): National Recommended Water Quality Criteria – Human Health Criteria Table.

JMOE (Japan's Ministry of Environment): Environmental Quality Standards for Water Pollution.

MDLs: method detection limits; NA: not available; ND: not detected.

A highly elevated benzene concentration (158.0 μg·L−1) at Jingjian station was observed from this study. Similar to ethylbenzene at the same station, this exceeded the standard limits established by both USEPA (2.1 μg·L−1) and JMOE (10 μg·L−1). This is also one of the worst and highly extensive hazardous types of air pollution, especially in Taipei (Williams & Chang 2008). Benzene is considered a very good solvent and has been used widely in the petrochemical industry since the early 1990s (Chung et al. 2010; Uragami et al. 2016). This industry is recognized as an important source of emissions of chemical substances with adverse health results to the residents (Chen et al. 2016). Many studies proved benzene to be highly poisonous (Casale et al. 2016; Hosseinzadeh & Moosavi-Movahedi 2016) and carcinogenic (Maltoni et al. 1983; McMichael 1988; Smith et al. 1989; Golding & Watson 1999). Despite the evidence of its toxicity to human and environmental health (Weaver et al. 1983; Lee et al. 2007; Chung et al. 2010), this industrial chemical still has been utilized extremely by petrochemical plants in many countries (Yin et al. 1987; Liu et al. 2009; Chung et al. 2010).

Chlorinated-VOC contamination

The Renwu station (131.2 ± 105.1 μg·L−1) was possibly the main source of chlorinated-VOC contamination due to a lower observed estimation in Hueifeng (42.4 ± 27.9 μg·L−1) and the absence of background contamination at Bakong (Table 2). Concentration estimated at the Deming (42.3 ± 25.2 μg·L−1) station was slightly lower than the value obtained in Huiefeng. A progressive decline in concentrations were noted at the Dehuei (17.9 ± 15.2 μg·L−1), CingPu (16.3 ± 18.3 μg·L−1) and Youchangda (9.8 ± 7.3 μg·L−1) stations, which might be due to the freshwater dilution effect. No chlorinated-VOCs were found in water samples from Bakong, Sannaitan and Jingjian stations.

Table 2

Chlorinated-VOC concentrations (μg·L−1) in water samples (n = 8 per station) collected from the Houjing River

  Dashe branch
 
Renwu branch
 
To the ocean
 
Sampling location Sannaitan Jingjian CingPu Bakong Renwu Hueifeng Deming Dehuei Youchangda 
Range ND ND 0–44.6 ND 1.2–331.6 1.3–76.7 5.8–69.4 0–39.2 0.7–21.0 
Mean ± S.D ND ND 16.3 ± 18.3 ND 131.2 ± 105.1 42.4 ± 27.9 42.3 ± 25.2 17.9 ± 15.2 9.8 ± 7.3 
Median ND ND 8.0 ND 100.7 39.5 45.3 14.7 10.2 
  Dashe branch
 
Renwu branch
 
To the ocean
 
Sampling location Sannaitan Jingjian CingPu Bakong Renwu Hueifeng Deming Dehuei Youchangda 
Range ND ND 0–44.6 ND 1.2–331.6 1.3–76.7 5.8–69.4 0–39.2 0.7–21.0 
Mean ± S.D ND ND 16.3 ± 18.3 ND 131.2 ± 105.1 42.4 ± 27.9 42.3 ± 25.2 17.9 ± 15.2 9.8 ± 7.3 
Median ND ND 8.0 ND 100.7 39.5 45.3 14.7 10.2 

ND: not detected.

Chlorinated-VOCs were examined only in five stations located in the Renwu branch and the river mouth (Table 3). Our results showed that unusually high contamination levels were only observed in one or two of these stations. Among the stations considered, Renwu had the highest concentrations of three of the five chlorinated-VOCs examined. These were vinyl chloride (29.0 ± 26.6 μg·L−1), chloroform (108.3 ± 102.2 μg·L−1) and 1,1-dichloroethane (6.2 ± 5.2 μg·L−1). The pollution rate decreased for stations located near the mouth of the river. Again, may be due to the fresh-saltwater mixing effect. For the 1,1-dichloroethane, this contaminant was only observed in the Renwu station and was not detected in the other sites. Methylene chloride (14.0 ± 8.4 μg·L−1) and 1,2-dichloroethane (15.7 ± 10.0 μg·L−1) were highest at the Deming station located near NEPZ, and this might be caused by the computer chip packaging plants prevalent in this zone. On the other hand, 1,2-dichloroethane was absent at the Dehuei and Youchangda stations.

Table 3

Mean concentrations (μg·L−1) of chlorinated-VOCs observed at some stations of the Houjing River

    Renwu branch
 
Near the ocean
 
Compound name MDLs Renwu Hueifeng Deming Dehuei Youchangda 
Vinyl chloride 0.3 29.0 ± 26.6 9.7 ± 3.9 5.5 ± 3.2 2.2 ± 1.0 1.7 ± 0.9 
Chloroform 0.4 108.3 ± 102.2 34.0 ± 10.2 33.5 ± 12.2 20.2 ± 15.8 8.6 ± 6.2 
1,1-Dichloroethane 0.4 6.2 ± 5.2 ND ND ND ND 
Methylene chloride 0.3 12.4 ± 7.1 4.5 ± 4.4 14 ± 8.4 3.0 ± 2.1 2.1 ± 1.9 
1,2-Dichloroethane 0.5 11.8 ± 9.8 6.3 ± 1.9 15.7 ± 10.0 ND ND 
    Renwu branch
 
Near the ocean
 
Compound name MDLs Renwu Hueifeng Deming Dehuei Youchangda 
Vinyl chloride 0.3 29.0 ± 26.6 9.7 ± 3.9 5.5 ± 3.2 2.2 ± 1.0 1.7 ± 0.9 
Chloroform 0.4 108.3 ± 102.2 34.0 ± 10.2 33.5 ± 12.2 20.2 ± 15.8 8.6 ± 6.2 
1,1-Dichloroethane 0.4 6.2 ± 5.2 ND ND ND ND 
Methylene chloride 0.3 12.4 ± 7.1 4.5 ± 4.4 14 ± 8.4 3.0 ± 2.1 2.1 ± 1.9 
1,2-Dichloroethane 0.5 11.8 ± 9.8 6.3 ± 1.9 15.7 ± 10.0 ND ND 

MDLs: method detection limits.

Huge amounts of chlorinated-VOC effluents were released by plastic manufacturers, who used this substance as plastic building blocks, as solvents and as scavenging or degreasing agents (Huang et al. 2014). Other manufacturing activities might also produce chlorinated-VOCs in solid and liquid forms (Huang et al. 2014). Based on the results of this study, it might be reasonable to infer that industrial factories at Renwu industrial park and NEPZ might contribute largely to chlorinated-VOC river contamination. Due to their adverse health effects in humans, (Yu & Chou 2000; Nagano et al. 2006; Gwinn et al. 2011), the use of some chlorinated-VOCs has been highly regulated or even banned following the Montreal Protocol because they belong to a list of compounds that highly contribute to ozone layer depletion, global warming and photochemical smog formation (UNEP 1987; Michalik-Zym et al. 2015).

Spatial distribution and potential sources of SVOC contamination

Figure 2 presents the spatial distribution of total SVOCs in the different sampling areas. For this analysis, sediment samples were collected to measure total SVOCs with high SDs around mean values resulting from differences over time. SVOCs were detected in all nine stations considered in the study. Our results showed low levels of SVOCs at the Bakong (1.5 ± 0.4 mg.−1), Renwu (6.5 ± 1.1 mg·kg−1), Hueifeng (2.3 ± 1.0 mg·kg−1) and Youchangda (2.1 ± 0.8 mg·kg−1) stations. These suggested that Renwu industrial park and the Kaohsiung Oil Refinery did not contribute heavily to the total SVOC contamination. Some sites showed elevated SVOC concentrations. This was the case for the two stations at the Dashe river branch: Jingjian (25.6 ± 16.0 mg·kg−1) and Sannaitan (52.5 ± 72.8 mg·kg−1). A considerably high concentration was observed at the Deming (70.0 ± 152.1 mg·kg−1) station along the Renwu river branch, probably due to the occurrence of many semiconductor industries in the area. SVOC occurrence at the Dehuei (40.3 ± 24.3 mg·kg−1) might be due to cumulated impacts of industrial, commercial and residential activities. Among all the stations considered, the CingPu station showed a considerably high SVOC pollution (122.0 ± 176.2 mg·kg−1).

PAEs accounted for more than 90% of the total SVOCs in this study. These synthetic compounds are used as additives to improve production quality of plastics (Van Wezel et al. 2000; Gao et al. 2014), pharmaceutical, detergents, pesticides, toys and cosmetics (Staples et al. 1997). PAEs are carcinogens (Murahashi et al. 2003; Diamanti-Kandarakis et al. 2009) and are suspected to be endocrine disrupters (Van Wezel et al. 2000). The potential carcinogenic and mutagenic effects of PAEs have been well studied (Hauser & Calafat 2005; Meng et al. 2014). PAE exposure could impair human metabolism and reproductive system functioning (Bell 1982; Jurewicz & Hanke 2011) and they have been associated with miscarriages and sterility complications (i.e., ovulation problems, teratogenicity, and low semen quality) (Wang et al. 2015a). Table 4 shows the contamination levels of the 5 PAEs analyzed. Among these, di(2-ethylhexyl)phthalate (DEHP) was present at all sampling sites. It was the principal PAE pollutant, and levels observed overshadowed the other phthalates considered in this study. Used globally as a plasticizer (plastic softener) in many polyvinyl chloride (PVC) products (Hauser et al. 2005; Van Vliet et al. 2011), DEHP does not bind chemically to PVCs and leaches out of the product to which it is added (Van Vliet et al. 2011). The highest mean DEHP concentrations were observed at the CingPu (120.3 mg·kg−1) and Deming (86.3 mg·kg−1) stations. Lower concentrations were observed at Sannaitan (25.3 mg·kg−1), Dehuei (22.1 mg·kg−1) and Jingjian (21.4 mg·kg−1) sites. Food processing and packaging factories near the Deming and Dehuei stations were the most likely culprits in river DEHP pollution.

Table 4

PAE concentrations (mg·kg−1 dry weight) in sediment samples (n = 6 per station) of the Houjing River

    Dashe branch
 
Renwu branch
 
Near the ocean
 
Compound name MDLs Sannaitan Jingjian CingPu Bakong Renwu Hueifeng Deming Dehuei Youchangda 
Diethyl phthalate (DEP) 0.1 0.1 ± 0.2 0.3 ± 0.2 0.1 ± 0.1 0.2 ± 0.2 ND ND ND 0.4 ± 0.3 0.5 ± 0.5 
Diphenylamine (DPA) 0.1 ND ND ND ND 0.2 ± 0.1 ND 0.1 ± 0.1 ND ND 
Di-n-butyl phthalate (DnBP) 0.1 0.1 ± 0.2 3.6 ± 2.9 1.1 ± 1.0 0.4 ± 0.3 2.4 ± 2.0 1.4 ± 1.1 0.4 ± 0.3 15.5 ± 10.0 1.2 ± 1.2 
Di (2-ethylhexyl) phthalate (DEHP) 0.2 25.3 ± 18.6 21.4 ± 19.7 120.3 ± 85.7 0.7 ± 0.5 3.7 ± 2.9 0.8 ± 0.7 86.3 ± 65.1 22.1 ± 11.8 0.5 ± 0.4 
Di-n-octyl phthalate (DnOP) 0.1 ND 0.2 ± 0.3 0.5 ± 0.4 0.2 ± 0.1 0.2 ± 0.2 0.1 ± 0.1 0.3 ± 0.2 2.2 ± 1.4 ND 
    Dashe branch
 
Renwu branch
 
Near the ocean
 
Compound name MDLs Sannaitan Jingjian CingPu Bakong Renwu Hueifeng Deming Dehuei Youchangda 
Diethyl phthalate (DEP) 0.1 0.1 ± 0.2 0.3 ± 0.2 0.1 ± 0.1 0.2 ± 0.2 ND ND ND 0.4 ± 0.3 0.5 ± 0.5 
Diphenylamine (DPA) 0.1 ND ND ND ND 0.2 ± 0.1 ND 0.1 ± 0.1 ND ND 
Di-n-butyl phthalate (DnBP) 0.1 0.1 ± 0.2 3.6 ± 2.9 1.1 ± 1.0 0.4 ± 0.3 2.4 ± 2.0 1.4 ± 1.1 0.4 ± 0.3 15.5 ± 10.0 1.2 ± 1.2 
Di (2-ethylhexyl) phthalate (DEHP) 0.2 25.3 ± 18.6 21.4 ± 19.7 120.3 ± 85.7 0.7 ± 0.5 3.7 ± 2.9 0.8 ± 0.7 86.3 ± 65.1 22.1 ± 11.8 0.5 ± 0.4 
Di-n-octyl phthalate (DnOP) 0.1 ND 0.2 ± 0.3 0.5 ± 0.4 0.2 ± 0.1 0.2 ± 0.2 0.1 ± 0.1 0.3 ± 0.2 2.2 ± 1.4 ND 

MDLs: method detection limits; ND: not detected.

In 2006, DEHP was listed as an important potentially dangerous chemical recognized as one of the priority existing chemicals to be treated by the National Industrial Chemicals Notifications and Assessment Scheme (NICNAS) under the 1989 Industrial Chemicals Act. Like many other PAE compounds, DEHP was reported to be an endocrine disruptor and is known to cause many human cardiovascular and reproductive complications (Tickner et al. 2001). The USEPA has issued a limit of 6 ppb for DEHP in drinking water (USEPA 2008). The Occupational Safety and Health Administration (OSHA) restricted occupational exposure to DEHP to less than 5 mg·m−3 of air (OSHA 2004). The ‘plasticizer’ DEHP has been banned under European Union (EU) law since 2015 after being listed among the toxic substances in Annex XIV under the EU's REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) regulations (EU 2011). As can be seen in Table 5, DEHP concentrations in the Houjing River were high, but lower that those reported for the Songhua River (China) by Gao et al. (2014) and those reported for the Kaveri River (India) by Selvaraj et al. (2015). However, the concentrations in this study were well above the acceptable environmental risk limit in sediment of 1 mg·kg−1 fresh weight as suggested by Van Wezel et al. (2000). These findings suggested that DEHP contamination was very serious in the Houjing River and should also be monitored regularly and regulated by national authorities.

Table 5

Comparison of estimated BTEX (μg·L−1), chlorinated-VOCs (μg·L−1) and DEHP (mg·kg−1 dry weight) concentrations in the Houjing River with other ecosystems

Geographical areas Types of water bodies BTEX
 
Chlorinated VOCs DEHP Reference 
Benzene Toluene Ethylbenzene m + p – Xylene o – Xylene 
Bangladesh River 0.35–0.38 0.20–0.27 0.12–0.17 0.21–0.14a – – Mottaleb et al. (2003)  
Swiss Lake Lake 0–0.47 0–1.02 0–0.39 0–2.05a – – Schmidt et al. (2004)  
India River 0–1.50 0–0.82 0–0.07 0–0.16 0–0.15   Lokhande et al. (2009)  
Portugal Rivers 0.01–0.70 0.01–4.77 0.09–4.75 0.01–27.61 0.02–2.16 – – Moliner-Martinez et al. (2013)  
Canada River – – – – – 0–30.00 – Kaiser & Comba (1983)  
Greek Rivers – – – – – 0–40.00 – Kostopoulou et al. (2000)  
Japan Rivers – – – – – 0–55.60 – Yamamoto et al. (2001)  
Germany Rivers – – – – – – 0.21–8.44 Fromme et al. (2002)  
The Netherlands Rivers – – – – – – 0–19.26 Peijnenburg & Struijs (2006)  
China River – – – – – – 227.08–566.54 Gao et al. (2014)  
Iran River – – – – – – 2.00–1,438.00 Selvaraj et al. (2015)  
Taiwan River 0.9–158.0 0–17.0 0–270.6 ND ND 0–331.6 0.5–120.3 This study 
Geographical areas Types of water bodies BTEX
 
Chlorinated VOCs DEHP Reference 
Benzene Toluene Ethylbenzene m + p – Xylene o – Xylene 
Bangladesh River 0.35–0.38 0.20–0.27 0.12–0.17 0.21–0.14a – – Mottaleb et al. (2003)  
Swiss Lake Lake 0–0.47 0–1.02 0–0.39 0–2.05a – – Schmidt et al. (2004)  
India River 0–1.50 0–0.82 0–0.07 0–0.16 0–0.15   Lokhande et al. (2009)  
Portugal Rivers 0.01–0.70 0.01–4.77 0.09–4.75 0.01–27.61 0.02–2.16 – – Moliner-Martinez et al. (2013)  
Canada River – – – – – 0–30.00 – Kaiser & Comba (1983)  
Greek Rivers – – – – – 0–40.00 – Kostopoulou et al. (2000)  
Japan Rivers – – – – – 0–55.60 – Yamamoto et al. (2001)  
Germany Rivers – – – – – – 0.21–8.44 Fromme et al. (2002)  
The Netherlands Rivers – – – – – – 0–19.26 Peijnenburg & Struijs (2006)  
China River – – – – – – 227.08–566.54 Gao et al. (2014)  
Iran River – – – – – – 2.00–1,438.00 Selvaraj et al. (2015)  
Taiwan River 0.9–158.0 0–17.0 0–270.6 ND ND 0–331.6 0.5–120.3 This study 

Concentrations are expressed as min–max values. ND: not detected.

aSum for all xylene isomers.

Comparative study of VOCs and SVOCs with other ecosystems

Table 5 shows a summary of primary VOCs and SVOCs observations in different countries. Maximum levels of total VOC pollutants analyzed in this study exceeded tremendously observations made in other freshwater ecosystems. Except for xylene, benzene (158.0 μg·L−1), toluene (17.0 μg·L−1), and ethylbenzene (270.6 μg·L−1) pollutions in the Houjing River were highly elevated compared to other rivers and lakes. The chlorinated-VOC concentrations in the Houjing River were much higher than those reported for the Welland River (Kaiser & Comba 1983), northern rivers and lakes in Greece (Kostopoulou et al. 2000) and Osaka (Yamamoto et al. 2001). In terms of DEHP, the pollution level was higher compared to results observed in several rivers and lakes in Germany (Fromme et al. 2002) and the Netherlands (Peijnenburg & Struijs 2006). This phthalate compound, however, was lower compared to the observations of Gao et al. (2014) and Selvaraj et al. (2015) in China and Iran, respectively.

CONCLUSIONS

This study has provided pertinent data on the levels of both volatile and semi-volatile organic contaminants in the Houjing River. The Renwu station had the highest level of total VOC toxicity, while the highest level of total SVOCs was observed at the CingPu station. Petrochemical industries, particularly, might be involved in VOC contamination in the river, particularly BTEX and chlorinated VOCs. These pollutants were detected in water samples with concentrations considerably elevated compared to other freshwater ecosystems. Stations located near the Dashe and Renwu industrial parks showed the highest VOC pollution, originating from numerous petrochemical and plastics industries. For SVOCs, especially DEHP, the highest contamination levels were observed at the Deming and the Cingpu stations, mainly originating from sewage and industrial wastewater, sewage sludge application, discarded plastic effusion and probably atmospheric deposition. The concentrations of BTEX, chlorinated VOCs and DEHP suggested that the river is a highly contaminated ecosystem in urgent need of environmental management plans and waste discharge regulations at both local and national levels. Local and national authorities should take action to regulate and limit pollution if they want to restore the river's diminished water quality. Regular water, sediment and wastewater monitoring and assessments should be implemented.

ACKNOWLEDGEMENTS

The authors would like to thank the sampling team of National Kaohsiung Marine University for their great help collecting the samples for this study. The authors appreciate the reviewers, whose knowledgeable comments and suggestions have largely contributed to the improvement of the quality of our work.

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