An integrated GIS-based approach in assessing carcinogenic risks via food-chain exposure in arsenic-affected groundwater areas.
This study presented an integrated GIS-based approach for assessing potential carcinogenic risks via food-chain exposure of ingesting inorganic arsenic (As) in aquacultural tilapia, milkfish, mullet, and clam in the As-affected groundwater areas. To integrate spatial information, geographic information system (GIS) was adopted to combine polygon-shaped features of aquacultural species with cell-shaped features of As contamination in groundwater. Owing to sparse measured data, Monte Carlo simulation and sequential indicator simulation were used to characterize the uncertainty of assessed parameters. Target cancer risks (TRs) of ingesting As contents at fish ponds were spatially mapped to assess potential risks to human health. The analyzed results reveal that clam farmed at the western coastal ponds and milkfish farmed at the southwestern coastal ponds have high risks to human health, whereas tilapia cultivated mainly at the inland ponds only has high risks at the 95th percentile of TR. Mullet in general has low risks to human health. Moreover, to decrease risks, this study suggests reducing the use of As-affected groundwater at clam and milkfish ponds due to high bioconcentration factor (BCF) of clam and inorganic As accumulation ratio of milkfish. The integrated GIS-based approach can provide fishery administrators with an effective management strategy at specific fish ponds with high risks to human health.
Liang
Ching-Ping
CP
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan, 106, Republic of China.
Jang
Cheng-Shin
CS
Liu
Chen-Wuing
CW
Lin
Kao-Hung
KH
Lin
Ming-Chao
MC
D000818:Animals; D017756:Aquaculture; D001151:Arsenic / Q000032:analysis* / Q000378:metabolism; D049872:Bivalvia / Q000378:metabolism; D002274:Carcinogens, Environmental / Q000032:analysis* / Q000378:metabolism; D004781:Environmental Exposure / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods; D005399:Fishes / Q000378:metabolism; D020387:Food Chain; D040362:Geographic Information Systems; D006801:Humans; D008962:Models, Theoretical; D018570:Risk Assessment; D012307:Risk Factors; D014874:Water Pollutants, Chemical / Q000032:analysis* / Q000378:metabolism
D002274:Carcinogens, Environmental; D014874:Water Pollutants, Chemical; D001151:Arsenic