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Full Terms & Conditions of access and use can be found at Human and Ecological Risk Assessment: An International Journal ISSN: 1080-7039 (Print) 1549-7860 (Online) Journal homepage: Mercury health risk assessment among petrochemical workers in Rayong Province, Thailand Wantanee Phanprasit, Maytiya Muadchim, Jeongim Park, Mark Gregory Robson, Dusit Sujirarat, Suphaphat Kwonpongsagoon & Sara Arphorn To cite this article: Wantanee Phanprasit, Maytiya Muadchim, Jeongim Park, Mark Gregory Robson, Dusit Sujirarat, Suphaphat Kwonpongsagoon & Sara Arphorn (2018): Mercury health risk assessment among petrochemical workers in Rayong Province, Thailand, Human and Ecological Risk Assessment: An International Journal, DOI: 10.1080/10807039.2018.1465812 To link to this article: Published online: 09 May 2018. Submit your article to this journal Article views: 54 View Crossmark data

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Page 1: Mercury health risk assessment among petrochemical workers ... · day; turnaround; petrochemical; health risk assessment Introduction Mercury is a naturally occurring heavy metal

Full Terms & Conditions of access and use can be found at

Human and Ecological Risk Assessment: An InternationalJournal

ISSN: 1080-7039 (Print) 1549-7860 (Online) Journal homepage:

Mercury health risk assessment amongpetrochemical workers in Rayong Province,Thailand

Wantanee Phanprasit, Maytiya Muadchim, Jeongim Park, Mark GregoryRobson, Dusit Sujirarat, Suphaphat Kwonpongsagoon & Sara Arphorn

To cite this article: Wantanee Phanprasit, Maytiya Muadchim, Jeongim Park, Mark GregoryRobson, Dusit Sujirarat, Suphaphat Kwonpongsagoon & Sara Arphorn (2018): Mercury health riskassessment among petrochemical workers in Rayong Province, Thailand, Human and EcologicalRisk Assessment: An International Journal, DOI: 10.1080/10807039.2018.1465812

To link to this article:

Published online: 09 May 2018.

Submit your article to this journal

Article views: 54

View Crossmark data

Page 2: Mercury health risk assessment among petrochemical workers ... · day; turnaround; petrochemical; health risk assessment Introduction Mercury is a naturally occurring heavy metal

Mercury health risk assessment among petrochemicalworkers in Rayong Province, Thailand

Wantanee Phanprasita, Maytiya Muadchim a, Jeongim Parkb, Mark Gregory Robson c,Dusit Sujiraratd, Suphaphat Kwonpongsagoone, and Sara Arphorna

aDepartment of Occupational Health and Safety, Faculty of Public Health, Mahidol University, Bangkok, Thailand;bDepartment of Environmental Health Sciences, Soon Chun Hyang University, Asan, South Korea; cRutgersSchool of Environmental and Biological Sciences, New Brunswick, New Jersey, USA; dDepartment of Biostatistics,Faculty of Public Health, Mahidol University, Bangkok, Thailand; eDepartment of Sanitary Engineering, Faculty ofPublic Health, Mahidol University, Bangkok, Thailand

ARTICLE HISTORYReceived 15 February 2018Revised manuscriptaccepted 13 April 2018

ABSTRACTBackground: Mercury occurs naturally in environment; thus, retentionof fossil fuels used as feedstock in petrochemical plants is commonlyfound. The purpose of this study was to assess mercury health risksamong petrochemical workers.Methods: In all, 188 operators and 30 office workers were recruitedfrom 3 petrochemical plants. A total of 83 and 56 air samples werecollected during normal working days and turnaround (TA) periods,respectively. Three main meals over 5 consecutive days, drinking waterand spot urine samples were collected. Demographics and lifestyledata were collected using questionnaires. USEPA guidelines formercury health risks were applied.Results: The inhalation exposure during normal working days of thetwo groups was lower than 5% of the Threshold Limit Value (TLV), butduring TA some operators’ exposure exceeded the TLV. The averageurinary mercury concentrations of the two groups did not significantlydiffer. The mercury concentration in the water samples wasundetected and did not differ in the food samples of the two groups.Sixty-six operators presented a hazard quotient, HQinh greater than 0.2,but none of office staff, and 98 of 218 participants had hazard index, HI>1.Conclusion: Unacceptable mercury health risk among the petrochemicalworkermostly cause bymercury in cooked food.

KEYWORDSmercury; normal workingday; turnaround;petrochemical; health riskassessment


Mercury is a naturally occurring heavy metal found in rock and many undergroundresources of the earth’s crust. All fossil fuels such as natural gas, gas condensates, crudeoil, and coal are likely to contain mercury. The use of these fossil fuels as energy sour-ces or feedstock in industry could discharge mercury to environment. Related mercury

CONTACT Wantanee Phanprasit [email protected] Department of Occupational Health and Safety,Faculty of Public Health, Mahidol University, Bangkok 10400, Thailand.© 2018 Taylor & Francis Group, LLC


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studies conducted in Map Ta Phut Industrial Estate in Rayong Province, Thailand, thelargest petrochemical complex in Southeast Asia, showed that mercury concentrationsin ambient air were about 0.72–9.26 ng/m3 (Pollution Control Department 2017); inmarine and sediment about 0.01 mg/L and 2.8 mg/kg dry weight (Pollution ControlDepartment 2013), respectively, and ranged between 0.004 and 0.224 mg/kg in seafood(Thongra-ar et al. 2014).

The metabolic pathway and toxicity of mercury vary depending on its forms and routesof entry. Elemental mercury presents in workplace air as vapor and inhaled mercury israpidly absorbed in the blood and distributed throughout the body in an unchanged form.The main sites of deposition are the kidneys and brain, and the excretion via feces, urine,expired air, sweat, saliva, and breast milk (Pamphlett and Waley 1996, IPCS 1991,Clarkson and Magos 2006). Approximately 1% is excreted in urine over the first threedays and about 8–40% of the dose is excreted in 30 days. The half-life of urinary mercuryvaries from 12.8–98.9 days with a median of 63.2 days. Chronic exposure to mercury byinhalation can produce harmful effects on the lungs, kidneys, digestive system, immunesystem, and nervous system, and symptoms include hand tremors, increased memory dis-turbances, and slight subjective and objective autonomic dysfunction (USEPA 1995).Regarding chronic exposure by ingestion, the majority involves the methylmercury(MeHg) form. MeHg exposure is usually associated with seafood consumption and iseasily absorbed through the digestive tract and can enter the central nervous system(CNS) after passing the blood brain barrier. The result is permanent injury to the CNSparticularly in a developing fetus (WHO 1990, Kim and Zoh 2012).

Health risk assessment is a tool for occupational health personnel to set up a manage-ment plan for workers’ health protection, in which normally only occupational exposurehas been considered. However, a holistic approach to worker well-being has been recog-nized to advance worker well-being, non-occupational risk factors should be consideredwhen they are related to work that contributes to health problems. Workers in petrochem-ical plants, where crude oil, condensate, and natural gas are used as feedstock, may beexposed to mercury in both routine and nonroutine operations, for example, emergencyresponse and maintenance, leaks, spills, and fugitive sources (Garcia and Radford 2012).Although no mercury illness cases have been reported in Rayong, according to factoryhealth surveillance reports (unpublished), urinary mercury exceeding the BEI has beendetected periodically. This study was conducted to assess mercury health risk of the work-ers, operators, and office staff, in petrochemical plants in Rayong Province, Thailandconsidering both non-occupational and occupational exposure during normal workingdays and turnaround periods.

Methods and materials

Studied sites

The studied plants consisted of one refinery and two aromatics plants. All were inRayong Province, Thailand. The office buildings of each plant, where the office staffworked, were close to the main gates and far from the operation buildings and storageareas were enclosed within the same fence. The refinery plant had crude oil and con-densate residue from aromatics plants as feedstock to produce liquid petroleum gas


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(LPG), fuel gas, light and heavy reformate, kerosene, gas and fuel oil, gasohol, etc.While the aromatics plants used condensate, reformate, and pyrolysis gasoline as majorraw material to manufacture benzene, xylenes and hexane with byproducts such asnaphtha, condensate residue heavy aromatics and LPG.


Although production technology and products of the refinery differ from the aromaticsplants, the workers may have similar exposure to mercury from products and raw materialsas their works and activities are similar. Office workers are employed 8 hours daily, 5 daysweekly. However, most operators work 12 hours daily for three days and are off for twodays, as normal working days, and work 12 hours daily, six days weekly throughout the turn-around (TA) period, which normally takes 45–60 days. To better assess inhalation exposure,they were classified in two similar exposure groups (SEG), that is, operators and office staff.The operators were employees working inside the production area comprising field opera-tors, maintenance workers, process engineers, and laboratory technicians. Office workerswere those working in offices, and not involved in production areas consisting of humanresource officers, administrative officers, accountants and nurses.

Inclusion criteria were set to recruit men or women aged from 20 to 55 years who hadworked at least six months in the studied plants before the date of data collection, lived inRayong Province, and only volunteers were recruited to the study. Two hundred and eigh-teen participants were recruited from a total of 1,035 workers in the three studied plants,that is, 188 operators (total number of operators in 3 plants, N D 813) and 30 office workers(N D 222). All participants were asked to sign informed consent forms before enrolling inthe study according to the study protocols, reviewed and approved by the Ethics Committeeon Human Rights Related to Human Experimentation of Mahidol University, Bangkokunder MUPH 2016–029.

Sampling strategy and data collection

This study was conducted between March 2016 and July 2017. Air sampling was conductedto estimate inhalation exposure to mercury in the workplace and occupational exposure ofthe participants between May and July 2016 during normal work days for all three plants.Cooked food and drinking water, non-occupational sources of exposure, and urine sampleswere collected during the same period. However, each plant scheduled the TA in differentperiods, normally once every three years. Therefore, air samples in the refinery plant werecollected in May 2016 and those in the aromatics plant #2 in June 2017.

For normal operation days, both area and personal air sampling were conducted to estimatethe operators’mercury exposure depending on their mobility. For maintenance workers, pro-cess engineers and laboratory technicians working in certain areas, static sampling wasapplied. Personal air sampling was employed for the field operators whose work involved theproduction control process in the central control room (CCR) and patrols in production areas.Office staff spent most of the working time in their offices; thus, static air sampling was con-ducted in the offices to estimate their mercury exposure. Active sampling using Hydrar packedsorbent tubes (Carulite, Lot 10187 Cat.NO. 226-17-1A) following the NIOSH method #6009


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was used for both personal and area air sampling. Twenty-seven personal and 56 area sampleswere collected in three studied plants over twelve working days.

During the TA period, passive samplers (SKC Inc., model # 520-02A) were employed fol-lowing the Occupational Safety and Health Administration (OSHA) ID 140 (OSHA 1991)for personal sampling among the field operators. The static sampling in the TA areas usedHydrar packed sorbent tubes following the NIOSH method #6009. Seventeen and fourteenarea and personal air samples, respectively, were collected in the refinery over 8 days, and 25personal air samples were taken in the aromatics plant #2 over 7 days. However, air sampleswere not collected in offices during the TA period.

For active sampling, pre- and post-calibration of the personal pump with the absor-bent tube in line was always conducted to achieve the flow rate in between 0.15 and0.25 L/min. The average of the pre- and post-flow rates was used to calculate mercuryconcentration. The sampler was attached at the coverall collar near the breathing zoneof workers for personal sampling. The sampler was attached to the tripod at a heightapproximately 1.2 m above the ground and set in or nearby working areas, for staticsampling.

For passive sampling, after preparing the sampler according to the operating instructions,the sampler was attached at the coverall collar near the breathing zone of workers. All airsampling was run throughout the work hours, that is, approximately 8 and 12 hours foroffice staff and operators, respectively.

Packs for sample collection comprised 15 zip lock plastic bags for food and 2 polyethylenebottles for drinking water and urine samples were handed to the participants including thesample collection guidelines and self-administrative questionnaire, concerning behaviorsand lifestyles related to mercury exposure, before sample collection started. The participantsput a portion of each main meal consumed in a plastic bag and provided dietary informationover five consecutive days. The samples were preserved at –20�C until analyzed. All foodsamples of each participant were mixed and blended as one sample. Twenty-seven drinkingwater samples, 1.0 liter each, were collected from the drinking water dispensers of the plantsand from a number of voluntary participants’ homes in polyethylene bottles and 1.5 ml ofconcentrated nitric acid (HNO3) was added to preserve. Samples were stored at 4�C untilanalyzed within a few weeks.

Spot urine samples were collected from participants on the last day of food collection. Theparticipants placed their samples in provided ice boxes in front of the toilets, which werecollected every three hours and store at –20�C until analyzed. On the last day of samplecollection, the questionnaire was also collected. In-depth interviews were conducted amongthe participants who had urinary mercury concentrations exceeding the standard of 20 mg/gcreatinine.


All air samples and field blanks, both absorbent tube and passive badge, were preparedaccording to NIOSH 6009 (NIOSH 1994) and OSHA ID 140 (OSHA 1991) methods, respec-tively, and modified to fit analysis using inductively Coupled Plasma Mass Spectrometry(ICP-MS) (Agilent 7500 series, JP82802997) with the injection volume of 1 ml. The standardcurve was acquired from mercury standard solutions of 1, 2.5, 5, 10, 15, 20, and 25 ppb with


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coefficient of determination, r2 D 1. The limit of detection (LOD) was 0.0003 ng/ml, and thedesorption efficiency ranged from 92% to 109%.

Cooked food and drinking water samples were prepared to analyze for total mercuryaccording to the Association of Official Analytical Chemists (AOAC) (AOAC SMPR2012.007 2013) and the American Water Works Association (AWWA) methods (AWWA2012), respectively, and analyzed using ICP-MS with an injection volume of 1 ml. The LODwas 0.001 mg/ml for food samples and 0.001 mg/ml for water samples. The recovery coeffi-cient of standard reference material of ERM-BB422 sample no. 0259 for fish muscle was98–103%.

Five milliliters of urine sample were used to determine creatinine levels using the COBASanalyzer. Only urine samples with creatinine concentration ranging from 0.3–3 g/l were fur-ther analyzed for urinary mercury, which totaled 97 samples. A hundred microliters of urinewas pipetted in 900 ml of 2% nitric solution, mixed in a vortex mixer and analyzed usingICP-MS modified by Goulle (Goulle et al. 2005). The LOD was 0.001 mg/ml. The certifiedreference material (ClinChek� -Control, Urine Control, lyophil for trace elements level Iand II) was analyzed in parallel with the samples.

Data management

Regarding statistical analysis, for samples with mercury quantity less than the LODs, one-half LOD value was assigned (Glass and Gray 2001). Statistical analyses were conductedusing IBM SPSS, Version 18. Descriptive statistics, correlation, and tests to determine differ-ences were performed. Significance level was at p � 0.05.

Health risk assessment of mercury was conducted as stated in the USEPA’s guide-lines for noncancer (USEPA 2009). Although there are some studies on the ratio ofMeHg to total Hg in fish (May et al. 1986.), rice (Rothenberg et al. 2014) and seafood(Sevillano-Morales et al. 2015) but not mixed food. Furthermore, mixed food sampleswere analyzed as stated in, “Sampling strategy and data collection,” so mercury concen-tration tended to be diluted. Thus, to have the most sensitive result of risk assessment,the worst-case scenario was assumed, that is, total mercury analyzed in the food sam-ples was MeHg. The average daily dose (ADD) was estimated based on the data frominhalation and ingestion during normal operations and the TA period. The referenceconcentration, RfCinh, of 0.3 mg/m3 (USEPA 1995), and the reference dose, RfDing, of0.1 mg/kg-day (Methyl mercury) (USEPA 1987) were used to calculate the hazard quo-tient (HQ). The hazard index (HI) was acquired from the sum of HQs for inhalationand ingestion exposure. When HQ was greater than 0.2, or the HI was greater than 1,risk management would be suggested. Parameters and values for mercury health riskassessment are shown in Table 1.


The demographics of the participants, operators, and office staff, are presented in Table 2.Statistical analyses were conducted to determine any differences in the two groups, and theresults showed that only work period in the organization and education level significantlydiffered. Most participants were male and lived farther than 5 km from the plants in thehousing estate zone.


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Data concerning all samples, air, water, urine, and cooked food, were tested fordistribution using the Kolmogorov–Smirnov test revealing that all were log-normally dis-tributed. Therefore, the Mann–Whitney U test was used to test differences in the mediansof the two groups.

Exposure assessment

Air sampleThe results of the mercury concentrations analyses obtained from area and personal air sam-ples during normal operations and TA period in the studied plants are presented in Table 3.

During normal operation days, the average 8-hour TWA concentration of the fieldoperators obtained from personal sampling was significantly higher than that from the area

Table 1. Parameters and values for mercury health risk assessment calculation.

Parameter Sign & Value

Body weight (BW) Individual’s value from questionnaireInhalation rate (IRair) 0.89 m3/hr (USEPA 2011)Food ingestion rate (IRfood) Food consumed per meal (0.407 kg) (Prime Minister’s Office 2001)

£ Meals per day (kg/day)Drinking water intake rate (IRwater) D 2 L/day (USEPA 2004)Exposure duration (ET) 12 hr/day for operators

8 hr/day for office workersExposure frequency (EF), Normal work days 180 days/year (for operators)

240 days/year (for office workers)During TA RefineryD 17 days/year (TA operation was 52 days/ 3 years)

Aromatics 1 and 2 D 15 days/year (TA operation 45 day/3 years)

Table 2. Demographics of the participants.

Demographics Operators (n D 188) Office workers (n D 30) p-value

Age, mean (SD) 39.91 (8.72) 37.30 (8.52) 0.1371

Body weight, mean (SD) 70.35 (10.77) 68.97 (12.96) 0.2741

Work period, mean (SD) 14.58 (7.67) 10.99 (7.40) 0.0201

Sex, n (%) 0.2632

Male 175 (93.09) 26 (86.67)Female 13 (6.91) 4 (13.33)

Education, n (%) <0.0013

Lower than Bachelor’s 71(37.77) 0 (0.0)Bachelor’s 73 (38.83) 17 (56.67)Higher than Bachelor’s 18 (9.57) 8 (26.67)No data 26 (13.83) 5 (16.66)

Residence distance from work, n (%) 0.3682

<5 km 11 (5.85) 0 (0.0)�5 km 177 (94.15) 30 (100.00)

Residence areas, n (%) 0.6352

Rural 42 (22.34) 5 (16.67)Urban 146 (77.66) 25 (83.33)

House location, n (%) 0.2003

Near agriculture area 29 (15.42) 4 (13.33)Near business and trade area 69 (36.70) 17 (56.67)Near industrial area 15 (7.98) 1 (3.33)Housing Estate 75 (39.90) 8 (26.67)

Remark: p-value< 0.05 was considered significant.1Tested by Mann–Whitney test.2Tested by Fisher’s Exact test.3Tested by Pearson’s Chi-square.


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sampling, (p-value < 0.001). Therefore, the average concentration obtained from the per-sonal air samples was used for the field operators who were not selected for air sampling.Whereas, other operators’ TWA concentrations were calculated from the concentrationsobtained from area air samples taken in their workplace and time they spent in such areas.The mean TWA mercury concentration among all operators in the three plants was0.43 £ 10¡3 § 0.15 £ 10¡3 mg/m3, and for the office workers was 0.15 £ 10¡3 § 0.04 £10¡3 mg/m3. The median TWAs of the two groups during normal working days significantlydiffered (p-value < 0.001); however, all participants’ exposure was very low, that is, less than5% of the American Conference of Governmental Industrial Hygienist (ACGIH) recom-mended standard, TLV, 0.025 mg/m3. TWA concentrations of the participants are presentedin Table 4.

Table 3. Average mercury concentration in workplace air.

Mercury concentration (mg/m3)

Samples A/P No. of sample Median Mean § SD Min–Max

RefineryTA period (Shut down)- Field operators P 14 0.70 £ 10¡2 2.56 £ 10¡2 § 3.24 £ 10¡2 ND–10.37 £ 10¡2

- Decontamination areas A 17 0.01 £ 10¡2 0.02 £ 10¡2 § 0.04 £ 10¡2 ND–0.16£ 10¡2

Normal working days- Field operators P 7 0.50 £ 10¡3 0.48 £ 10¡3 § 0.34 £ 10¡3 ND–0.63£ 10¡3

- Production area A 4 0.15 £ 10¡3 0.20 £ 10¡3 § 0.07 £ 10¡3 ND–8.01£ 10¡3

- Laboratory A 3 0.20£ 10¡3 1.40£ 10¡3 § 2.08 £ 10¡3 ND–3.79£ 10¡3

- Workshop A 8 0.15£ 10¡3 0.41£ 10¡3 § 0.54 £ 10¡3 ND–1.67£ 10¡3

- Office areas A 6 0.15£ 10¡3 0.13 £ 10¡3 § 0.03 £ 10¡3 ND–0.30£ 10¡3

Aromatics plant #1Normal working days- Field operators P 10 0.15 £ 10¡3 0.24 £ 10¡3 § 0.17 £ 10¡3 ND–0.58£ 10¡3

- Production area A 3 0.15 £ 10¡3 0.63 £ 10¡3 § 0.84 £ 10¡3 ND–1.46£ 10¡3

- Workshop A 7 0.15£ 10¡3 0.44£ 10¡3 § 0.72 £ 10¡3 ND–9.51£ 10¡5

- Office areas A 8 0.15£ 10¡3 0.23 £ 10¡3 § 0.12 £ 10¡3 ND–0.40£ 10¡3

Aromatics plant #2TA period- Field operators (Shut down) P 16 0.39 £ 10¡2 1.20 £ 10¡2 § 1.89 £ 10¡2 ND–5.83£ 10¡2

- Field operators (Maintenance) P 9 0.15 £ 10¡2 0.67 £ 10¡2 § 0.90 £ 10¡2 ND–0.03Normal working days- Field operators P 10 0.15 £ 10¡3 0.47 £ 10¡3 § 0.66 £ 10¡3 ND–2.08£ 10¡3

- Production area A 3 0.20 £ 10¡3 0.30£ 10¡3 § 0.26 £ 10¡3 ND–5.65£ 10¡4

- Laboratory A 1 – ND –- Workshop A 9 0.40£ 10¡3 0.52£ 10¡3 § 0.37 £ 10¡3 ND–1.13£ 10¡3

- Office areas A 4 0.15£ 10¡3 0.22 £ 10¡3 § 0.09 £ 10¡3 ND–0.34£ 10¡3

Remark: ND, not detected, LOD D 0.03 mg/sample.Workplace air standard, elemental and inorganic form (TLV-TWA) D 0.025 mg/m3 (ACGIH 2017).A D Area samples; P D Personal samples.

Table 4. TWA concentrations of mercury during normal working days.

Position group n Median Mean§SD Min–Max

Operators 188 0.50 £ 10¡3 0.43 £ 10¡3§0.15£ 10¡3 0.12 £ 10¡3–1.10 £ 10¡3

-Field operator 124 0.50 £ 10¡3 0.42 £ 10¡3§0.16£ 10¡3 0.12 £ 10¡3–1.10 £ 10¡3

-laboratory technician 18 0.50 £ 10¡3 0.45 £ 10¡3§0.18£ 10¡3 0.15 £ 10¡3–0.97 £ 10¡3

-Maintenance worker 11 0.48 £ 10¡3 0.43 £ 10¡3§0.11£ 10¡3 0.20 £ 10¡3–0.50 £ 10¡3

- Process engineer 35 0.48 £ 10¡3 0.44 £ 10¡3§0.10£ 10¡3 0.20 £ 10¡3–0.5 £ 10¡3

Office worker 30 0.15 £ 10¡3 0.15 £ 10¡3§0.04£ 10¡3 0.11 £ 10¡3–0.40 £ 10¡3


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During the TA period, the operators’ tasks involved steam decontamination, hydro-carbon draining, and measuring toxic chemical concentrations at a manhole usingdirect reading instruments at the end of each decontamination cycle. Nine of 39 airsamples taken from the field operators exceeded the TLV. The highest exposure amongthe operators was 0.10 mg/m3 found in the refinery plant. The mercury exposureamong the field operators in the aromatics plant #2 and in the refinery plant, duringthe TA period, did not significantly differ. However, the exposure of the field operatorsduring the TA period was significantly higher (p-value < 0.001), than that during thenormal working days.

Cooked foodAll 218 cooked food samples were analyzed, and the results showed that 44 samples con-tained mercury exceeding the standard of 0.50 mg/kg (Table 5). The cooked food of theoperators in the refinery plant had the highest mean and median of the mercury concentra-tions. However, mercury concentration in cooked food samples of the two groups, operatorsand office workers, showed no significant difference (p-value D 0.12).

Drinking waterThe mercury concentrations in all samples were lower than the LOD; thus, they were lowerthan the standard of 0.001 mg/L. Table 5 shows the results regarding mercury exposure byingestion of cooked food and drinking water of the participants.

UrineThe concentration of creatinine in 97 of 218 participants’ urine samples were in theoptimum range. Eighty of 84 operators’ and 11 of 13 office workers’ urinary mercuryconcentrations were less than 50% of the ACGIH Biological Exposure Index, BEI (20mg/g creatinine) (ACGIH 2017). However, the median difference of urinary mercurywas analyzed, and no significant difference was found between operators’ and officeworkers’ (p-value D 0.874) (Table 6). Two operators had urinary mercury exceedingthe BEI; thus, in-depth interviews were conducted. The most related event could havebeen their work during one small shutdown in the last one to two months before the

Table 5. Mercury concentrations in cooked food samples.

Operators Office workers

Samples n Median Mean § SD (Min–Max) n Median Mean § SD (Min–Max) p-value

Cooked food (mg/kg) 0.120Refinery 122 0.28 0.38 §0.45 (ND–1.97) 26 ND 0.19 §0.32 (ND–1.17)Aromatics plant #1 29 ND 0.10 § 0.28 (ND–1.33) 3 ND NDAromatics plant #2 37 ND 0.09 §0.20 (ND–0.65) 1 ND NDDrinking water (mg/L)Refinery 14 ND ND 2 ND ND —Aromatics plant #1 2 ND ND 3 ND NDAromatics plant #2 6 ND ND 2 ND ND

Remark: ND, undetected; LOD cooked food D 0.001 mg/ml; LOD drinking water D 0.001 mg/ml.Standard for mercury in food < 0.50 mg/kg (Ministry of Public Health, Thailand 1987) and in drinking water < 0.001 mg/l(WHO 2011).

The mean difference test using Mann–Whitney U Test and p-value<0.05.


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urine collection of this study. Their duty involved steam decontamination. However, airsamples were not taken at that time.

Lifestyle and behaviors which may have affected the urinary mercury concentrations suchas using facial whitening cream (Wuttiadirek and Pumket 2016, Boonprachom et al. 2013)and dental amalgam (Akerstrom et al. 2017), consuming herbal products (Caldasa andMachadob 2004), tap water (Health Canada 2009), and exposure to pesticides, herbicidesand fungi control chemicals on plant seed (Almeida et al. 1976; Gilkeson 1996). Dataregarding these factors were collected by questionnaire and the results are shown in Table 7.The correlation test was also applied revealing that all the variables did not significantlycorrelate with urinary mercury.

Table 6. Urinary mercury concentrations of the participants.

Operators Office workersmg/g creatinine mg/g creatinine

Plant N Median Mean § SD (Min–Max) n Median Mean § SD (Min–Max) p-value*

Refinery 56 2.76 4.34 § 4.78 (0.20–29.41) 11 2.41 3.66 § 3.71 (0.01–13.21) 0.874Aromatics 1 16 1.78 3.64 § 5.67 (0.47–23.75) 2 6.25 6.25 § 8.40 (0.31–12.19)Aromatics 2 12 2.93 2.71 § 1.93 (0.40–6.08) 0 — —

Remark: LOD D 0.30 ng/ml, standard for total mercury in urine D 20 mg/g creatinine (ACGIH 2017).�The statistical significance test for mean difference was the Mann–Whitney U Test; statistically significant at p-value< 0.05.

Table 7. Correlation of the urinary mercury concentrations and lifestyle and behavior.

Urinary mercury (mg/L)

Lifestyle factors n Median p-value

Dental amalgamYes 77 2.47 0.459No 20 2.18

Alcohol consumptionYes 36 1.88 0.085No 61 3.05

SmokingYes 8 2.72 0.115No 89 2.41

Seafood consumption 0.331Yes 78 2.33No 19 3.14

Herbal extract consumption 0.935Yes 5 3.95No 92 2.37

Tap water consumption 0.444Yes 9 1.49No 88 2.43

Gardening 0.275Yes 12 1.89No 84 2.46

Pesticides or herbicides used 0.154Yes 5 1.48No 92 2.43

Face whitening and cosmetic used 0.672Yes 41 2.33No 56 2.67

Remark: Statistical test by Mann–Whitney U test, statistically significant at p-value<0.05.


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Health risk assessment

The results of health risk assessment are summarized and presented in Table 8. When thestatistical test for differences of ADDinh between the office staff and the operators wasapplied, the result significantly differed, but not that of the ADDing. This implied that theinhalation exposure to mercury of the office staff and operators differed as expected. How-ever, the exposure by ingestion was similar, and could be due to all participants living in thesame area and eating foods from the same sources. HQ50 for the inhalation and ingestionexposure of both office staff and operators was less than 0.2, an acceptable level, (HealthCanada 2004) while the maximum HQinh of only the office staff was less than 0.2. Sixty-sixoperators presented a HQinh greater than 0.2, 56 (84.84%) field operators, 7 (10.61%) labtechnicians, and 3 (4.54%) process engineers.

Although only 44 of 218 cooked food samples contained mercury exceeding the standard,95 participants presented an HQing > 1 because ADDing considers the quantity of food thatthe participants ate for each meal. The HQinh and HQing, HI was calculated revealing 90operators and 8 office workers had HI > 1, and the major source of mercury exposure ofnearly all cases of HI > 1 was cooked food.

Discussion and conclusion

This study aimed at assessing health risks for petrochemical workers. Both operators andoffice workers were recruited in the study, and HQ for inhalation and ingestion were usedto calculate HI. The occupational exposure to mercury vapor caused 66 operators’ HQinh topresent a greater than acceptable level of 0.2 (Heath Canada 2004), but none of the officestaff did. The exposure to mercury vapor among the field operators during the TA periodwas significantly higher than that during the normal work days causing the HQinh of twooperators to exceed 1. The area air samples taken in the TA areas were well below the TLV,that is, the highest was 0.0016 mg/m3. Therefore, the findings supported the notion that theoffice staff would not have significantly increased mercury exposure during such period.

During normal working days, the operators’ exposure was higher than that of the officeworkers, but all were still lower than 5% of the TLV. In this study, during March 2016 andJuly 2017, average occupational exposure to mercury vapor of the operators and the office

Table 8. ADD, HQ, and HI by group of participants and route of exposure.

ADD (mg/kg-day)HQ HI

Mean § SD (min–max) HQ50 HQ95 HQmin–HQmax HQ >1, n (%) HI 50 HI95 HI > 1, n (%)

InhalationOperators 0.10 § 0.10

(0.78 £ 10¡2–0.77)0.16 0.84 0.03–2.57 2 (1.06) Operators:

0.86 10.02 90(47.87)

Office workers 0.01 § 2.65£ 10¡3

(0.70 £ 10¡2–1.84 £ 10¡2)0.04 0.05 0.02–0.06 0 Office staff:

0.05 8.76 8(26.67)

IngestionOperators 0.23 § 0.35 (0.01 £ 10¡2–1.95) 0.01 9.68 0.01–19.46 87 (46.28)Office workers 0.16 § 0.29 (0.01 £ 10¡2–1.09) 0.01 8.72 0.01–10.93 8 (26.67)


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workers was 1.89 mg/m3 and 0.15 mg/m3, respectively, higher than the annual mean concen-tration of mercury in Rayong Province during 2014 and 2017 ranging from 0.00153–0.00308 mg/m3 (Pollution Control Department 2017). Though the data were from differentperiods of time, since 2009 the ambient pollutant concentrations including mercury havebeen reduced and varied in a narrow range, when all areas near and in Map Ta PhutMunicipality in Rayong Province were announced to constitute the “Pollution Control Zone”(Pattaya Daily News 2009). Furthermore, the urinary mercury concentrations, used to assesschronic exposure to elemental mercury of the two groups, did not differ significantly, reflect-ing low inhalation exposure of the participants as mentioned above. The average urinarymercury levels of the participants reflected exposure during the normal work days (3.97 mg/g creatinine for operators and 4.05 mg/g creatinine for office workers). These levels wereclose to those of the general population living in Rayong Province (4.22 mg/g creatinine)(Siphuang 2010).

Food consumption accounted for the majority of the mercury exposure. Mercuryconcentration in food samples from the operators and office workers did not differ sig-nificantly. Similarly, participants exposed to mercury by food consumption could havebeen because most of the food came from the same sources. For other ingestion expo-sures, only samples of drinking water were collected; thus, this method might haveunderestimated this route of exposure. In one related study, dried tea, soft drinks, andcorn syrup contained detectable levels of mercury and the highest concentrations were0.023 mg/kg, 0.011 ppm, and 0.0002 ppm, respectively (Canadian Food InspectionAgency 2014).

Other possible environmental exposure sources of mercury such as dental amalgamand facial whitening cream, for which approximately 79% and 42% of the participantshad used, did not correlate with the participants’ urinary mercury concentrations.Regarding dental amalgam, old dental fillings might release mercury but at very lowlevels (Akerstrom et al. 2017). Although the age of the participants’ amalgam was notincluded in the questionnaire, normally the median age for amalgam fillings is 6 to15 years. (Antony et al. 2008) Thus, quite possibly the amalgam of a number of partici-pants was old and could be the reason for not correlating between the two factors. Forthe use of facial cream, because of the participants’ quite high level of education, theywere unlikely to use facial cream without Food and Drug Administration certification.Thus, no correlation was found regarding the urinary mercury concentration.

Based on the result of this study, adverse chronic health effects, that is, impairment of thecentral and peripheral nervous systems, could be expected among the operators. Further-more, when environmental exposure by food consumption was taken into account, the num-ber of the participants whose HI > 1 increased from 2 to 98. Thus, unacceptable risk to CNScould have occurred in both groups of participants, and environmental exposure by foodconsumption probably was the major source of mercury exposure among them. Therefore,to control health risk of mercury among the petrochemical industry workers in RayongProvince the personnel should know and understand the sources of mercury exposureincluding how to reduce or eliminate them. For example, they should be trained to followthe safety operating procedures (SOP) issued by the factories at all work times and for alltypes of works and to avoid eating fish and seafood especially those that may be contami-nated with chemicals. Regarding the suggestions above, two responsible individuals would


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be the factory managers and local government officials. The factory management shouldprovide the facilities and devices in accordance with the SOP. In addition, the local govern-ment should take role in food inspection and provide information by posting in areas wheremost or all can access.


This study was designed to account for most known and controllable sources of varia-tion. However, some uncontrollable or unavoidable factors, such as wind direction, var-iation in sampling and analyzing equipment/instrument, the use of reference doses andconcentrations, may have caused uncertain results. Furthermore, food and drinkingwater samples were provided on the voluntary basis; thus, this may have caused uncer-tain results as well. Those uncertainties which may have affected the results of thestudy are listed below.

Inhalation exposure: First, two different sampling devices were used, that is, personalpassive sampling was used to estimate the field operators’ exposure while area activesampling was used for the others. Though both were accepted by OSHA, some varia-tion was observed, that is, the coefficient of variation of the passive sampler wasapproximately 10% compared with the NIOSH method #6009 (OSHA 1989). Second,exposure was estimated from static samples; the exposure to mercury obtained fromthe static or area air samples may not truly represent the exposure of all workers insuch area. Moreover, the time spent in each area was an approximated value given bythe participants. Third, exposure was estimated from personal air samples; the fieldoperators were randomly selected assuming that they were SEG and the average mer-cury concentration of all samples was used for those who were not selected. Thesewere designed to suit the work conditions and costs but could have resulted for uncer-tainty regarding mercury exposure.

Ingestion exposure: Concerning cooked food samples; participants might not haveprovided every kind of food they ate at every meal and the quantity of each food given as thesample may not have been in the same proportions for all kinds. Additionally, the food sam-ples were mixed before being analyzed; thus, mercury concentration in the sample could eas-ily have been diluted. Furthermore, if the participants ate the same kinds of food every day, itwould add uncertainty to the risk assessment as well.


This work was supported by the Strategic Scholarships Fellowships Frontier Research NetworkSpecific for the Southern Region, The Office of the Higher Education Commission, Thailand includinga grant from a petrochemical company. The authors wish to thank all petrochemical staff and contrac-tors and laboratory staff from the Bureau of Occupational and Environmental Disease, ReferenceLaboratory and Toxicology Center, Thailand including support from NIEHS P30 Center GrantES005022 and the New Jersey Agricultural Experiment Station.


This work was supported by a grant from PTT Global Chemical Public Company Limited (PTTGC).


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Conflict of interest

The authors declare they have no conflicts of interest.


Maytiya Muadchim Gregory Robson


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