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Frontiers of Environmental Science & Engineering

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Front.Environ.Sci.Eng.    2014, Vol. 8 Issue (3) : 441-450    https://doi.org/10.1007/s11783-013-0572-6
RESEARCH ARTICLE
Application of probabilistic risk assessment at a coking plant site contaminated by Polycyclic Aromatic Hydrocarbons
XIA Tianxiang1,2,(),JIANG Lin1,2,JIA Xiaoyang1,2,ZHONG Maosheng1,2,LIANG Jing1,2
Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China
Beijing Key Laboratory for Risk Modeling and Remediation of Contaminated Sites, Beijing 100037, China
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Abstract

Application of Probabilistic Risk Assessment (PRA) and Deterministic Risk Assessment (DRA) at a coking plant site was compared. By DRA, Hazard Quotient (HQ) following exposure to Naphthalene (Nap) and Incremental Life Cancer Risk (ILCR) following exposure to Benzo(a)pyrene (Bap) were 1.87 and 2.12 × 10-4. PRA revealed valuable information regarding the possible distribution of risk, and risk estimates of DRA located at the 99.59th and 99.76th percentiles in the risk outputs of PRA, which indicated that DRA overestimated the risk. Cleanup levels corresponding acceptable HQ level of 1 and ILCR level of 10-6 were also calculated for both DRA and PRA. Nap and Bap cleanup levels were 192.85 and 0.14 mg·kg-1 by DRA, which would result in only 0.25% and 0.06% of the exposed population to have a risk higher than the acceptable risk, according to the outputs of PRA. The application of PRA on cleanup levels derivation would lift the cleanup levels 1.9 times for Nap and 2.4 times for Bap than which derived by DRA. For this coking plant site, the remediation scale and cost will be reduced in a large portion once the method of PRA is used. Sensitivity analysis was done by calculating the contribution to variance for each exposure parameter and it was found that contaminant concentration in the soil (Cs), exposure duration (ED), total hours spent outdoor per day (ETout), soil ingestion rate (IRs), the air breathing rate (IRa) and bodyweight (BW) were the most important parameters for risk and cleanup levels calculations.
Keywords Probabilistic Risk Assessment (PRA)      a coking plant      risk      cleanup level      sensitivity analysis      polycyclic aromatic hydrocarbons (PAHs)     
Corresponding Author(s): XIA Tianxiang   
Issue Date: 19 May 2014
 Cite this article:   
XIA Tianxiang,JIANG Lin,JIA Xiaoyang, et al. Application of probabilistic risk assessment at a coking plant site contaminated by Polycyclic Aromatic Hydrocarbons[J]. Front.Environ.Sci.Eng., 2014, 8(3): 441-450.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-013-0572-6
https://academic.hep.com.cn/fese/EN/Y2014/V8/I3/441
input variableunitdistributionparameterspoint estimate
ATcaalognormalμ = 71.3, σ = 3.18 [19]70 [14]
EDalognormalμ = 11.7, σ = 7, min= 1.91, max= 52.78 [20]30 [14]
EFd·a-1uniformmin= 350, max= 365 [17]350 [14]
ETouth·d-1Triangularmin= 1, mode= 2, max= 4 [17]4 [17]
BWkglognormalμ = 57.9, σ = 5.45 [19]60 [14]
IRsmg·d-1lognormallog μ = 4, log σ = 0.31, min= 0, max= 480 [17]100 [14]
IRam3·d-1uniformmin= 11.8, max= 16.7 [19]15 [14]
SAcm2lognormalμ = 4112, σ = 797 [13]4350 [14]
AFmg·cm-2lognormallog μ = 0.04, log σ = 0.047, min= 0.01, max= 0.07 [21]0.07 [22]
ABS%Triangularmin= 0.01, mode= 0.03, max= 0.13 [23]0.13 [23]
Tab.1  
Fig.1  PAHs species concentrations in the soils
chemicalunitpoint estimatedistribution type and distribution parameters
Napmg·kg-1359.9gamma(scale= 620.1, shape= 0.1, 95% = 359.9)
Bapmg·kg-130.2gamma(scale= 52.07, shape= 0.1, 95% = 30.2)
Tab.2  
Fig.2  HQ and ILCR calculated by PRA and DRA approach: (a) Nap-based oral intake HQ; (b) Nap-based dermal contact HQ; (c) Nap-based oral inhalation HQ; (d) Nap-based total HQ; (e) Bap-based oral intake ILCR; (f) Bap-based dermal contact ILCR; (g) Bap-based inhalation ILCR; (h) Bap-based total ILCR
distribution conditionSitenumber of variablesoutputcontaminantsresults
both exposure parameters and soil concentrationscoking plant(this paper)11riskNapDRA/ PRA(95%) = 5.24
BapDRA/ PRA(95%) = 5.61
waste incinerator [28]15riskTCDDDRA/ PRA(95%) = 8.72
PCBsDRA/ PRA(95%) = 2.07
metallurgical plants [29]>8daily intakeAsDRA/ PRA(95%) = 1.76a); 2.19b)
CdDRA/ PRA(95%) = 0.03a); 1.58b)
CrDRA/ PRA(95%) = 2.90a); 0.76b)
CuDRA/ PRA(95%) = 2.31a); 0.83b)
PbDRA/ PRA(95%) = 6.00a); 1.69b)
ZnDRA/ PRA(95%) = 2.64a); 1.57b)
BapDRA/ PRA(95%) = 0.67a); 1.49b)
exposure parameters onlyPCB-containingbuilding [30]8riskPCBDRA/ PRA(90%) = 0.92c)
DRA/ PRA(90%) = 0.82d)
petroleum refining activities [31]12riskPAHsDRA/PRA(95%) = 1.06a);1.89b)(site A)DRA/PRA(95%) = 0.64a);0.30b)(site B)
PBDE products manufacturing [32]80daily intakeOBDEDRA/ PRA(95%) = 0.36
DBDEDRA/ PRA(95%) = 0.55
PeBDEDRA/ PRA(95%) = 0.31
Tab.3  
estimateDRA and PRA cleanup levelsNapBap
deterministicpoint estimate/(mg·kg-1)192.850.14
percentile/%0.250.06
5th percentile/(mg·kg-1)371.540.33
probabilisticmedian1034.680.92
min117.870.12
max9362.818.57
SD848.540.77
CV0.680.68
Tab.4  
Fig.3  Probability distribution of log(RCRs) for Nap and Bap at each exposure pathway: (a) at oral intake pathway; (b) at dermal contact pathway; (c) at inhalation pathway; (d) at all exposure pathways
parametershazard quotient for Napcancer risk for Bapcleanup level for Napcleanup level for Bap
ωiPiωiPiωiPiωiPi
Cs0.96296.19%0.92491.33%////
ATca-0.0140.02%-0.0340.12%0.0610.38%0.0660.45%
ED0.1652.82%0.2486.56%-0.86775.98%-0.86777.73%
EF0.0040.00%0.0020.00%-0.0090.01%-0.0220.05%
ETout0.0750.58%0.0240.06%-0.43719.28%-0.0100.01%
BW-0.0320.10%-0.0300.09%0.1482.21%0.1361.91%
IRs0.0130.02%0.1231.61%-0.0150.02%-0.42018.28%
IRa0.0480.24%0.0050.00%-0.1442.10%-0.0060.00%
SA0.0080.01%0.0170.03%-0.0030.00%-0.0320.11%
AF0.0080.01%0.0260.07%-0.0040.00%-0.0880.81%
ABS0.0100.01%0.0330.11%-0.0020.00%-0.0780.63%
Tab.5  
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