Spatial dynamic assessment of health risks for urban river cruises
- 92 Downloads
River cruising ships move along river courses, and thus health risks to passengers may vary spatially due to the accidental exposure of river fecal pollution. This study performed a spatial dynamic assessment of health risks for river cruises in the highly urbanized Tamsui River Basin. First, the spatial distributions of river Escherichia coli (E. coli) were probabilistically characterized using indicator kriging (IK). Moreover, the current river cruise information was surveyed to obtain cruise routes and transit times. Then, to explore the parametric uncertainty of quantitative microbial risk assessment (QMRA), the ingestion rate (IR) for boating was determined using Monte Carlo simulation (MCS). Moreover, river E. coli distributions were estimated using nonparametric MCS according to multi-threshold IK estimates. Eventually, after combining the distribution of the joint probability of the IR and E. coli in QMRA, the β-Poisson dose–response function was adopted to analyze risks to river cruise passengers at discretized segments of cruise routes. Health risks to river cruise passengers were integrated at the discretized segments to explore suitable recreational strategies for river cruises. The research results indicate that all health risks do not exceed a daily target level of 8 illnesses per 1000 exposures for single-trip cruise routes. However, health risks to passengers can exceed this level for round-trip cruise routes along highly polluted urban river courses.
KeywordsRiver cruise Indicator kriging Monte Carlo simulation Escherichia coli Quantitative microbial risk assessment Uncertainty
The authors would like to thank the Taiwan Environmental Protection Administration for generously supporting the data on E. coli in the Tamsui River Basin, and the Taiwan Ministry of Science and Technology for financially supporting this research under Contract No. MOST 106-2410-H-424-020.
This study received financial support from Taiwan Ministry of Science and Technology under Contract No. MOST 106-2410-H-424-020.
- Chica-Olmo, M., Luque-Espinar, J. A., Rodriguez-Galiano, V., Pardo-Igúzquiza, E., & Chica-Rivas, L. (2014). Categorical indicator kriging for assessing the risk of groundwater nitrate pollution: the case of Vega de Granada aquifer (SE Spain). Science of the Total Environment, 470–471, 229–239.CrossRefGoogle Scholar
- Department of Transportation, Taipei City Government (DOT-TCG) (2017). River cruise. Department of Transportation, Taipei City Government. http://english.dot.gov.taipei/lp.asp?ctNode=65642&CtUnit=35701&BaseDSD=7&mp=117002. Accessed 25 Oct 2017.
- Deutsch, C. V., & Journel, A. G. (1998). GSLIB: geostatistical software library and user’s guide (2nd ed.). New York: Oxford University Press.Google Scholar
- Geosyntec. (2008). Dry and wet weather risk assessment of human health impacts of disinfection vs. no disinfection of the Chicago area waterways system (CWS) (pp. 99–110). Chicago: Metropolitan Water Reclamation District of Greater Chicago.Google Scholar
- Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation (pp. 259–368). New York: Oxford University Press.Google Scholar
- Goovaerts, P., AvRuskin, G., Meliker, J., Slotnick, M., Jacquez, G., & Nriagu, J. (2005). Geostatistical modeling of the spatial variability of arsenic in groundwater of southeast Michigan. Water Resources Research, 41. https://doi.org/10.1029/2004WR003705.
- Haas, C. N., Rose, J. B., & Gerba, C. P. (2014). Quantitative Microbial Risk Assessment (2nd ed.) (pp.72–73 and pp.267–321)). New York: Wiley.Google Scholar
- Health Canada. (2012). Guidelines for Canadian Recreational Water Quality (3rd ed.p. 26). Ottawa: Water, Air and Climate Change Bureau, Healthy Environments and Consumer Safety Branch, Health Canada.Google Scholar
- Jang, C. S. (2016). Using probability-based spatial estimation of the river pollution index to assess urban water recreational quality in the Tamsui River watershed. Environmental Monitoring and Assessment, 188(36), 1–17.Google Scholar
- Jang, C. S., Liu, C. W., Lin, K. H., Huang, F. M., & Wang, S. W. (2006). Spatial analysis of potential carcinogenic risks associated with ingesting arsenic in aquacultural tilapia (Oreochromis mossambicus) in blackfoot disease hyperendemic areas. Environmental Science & Technology, 40, 1707–1713.CrossRefGoogle Scholar
- Money, E. S., Carter, G. P., & Serre, M. L. (2008). Improving the assessment of E. coli exposure levels along un-monitored stream reaches. Epidemiology, 19(6), S162–S163.Google Scholar
- Money, E. S., Carter, G. P., & Serre, M. L. (2009). Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey. Environmental Science & Technology, 43, 3736–3742.CrossRefGoogle Scholar
- Taiwan Environmental Protection Administration (Taiwan EPA) (2017). Environmental water quality information. Environmental Protection Administration, Executive Yuan, Taiwan. http://wq.epa.gov.tw/WQEPA/Code/?Languages=en. Accessed 1 Aug 2017.
- Tseng, L. Y., & Jiang, S. C. (2012). Comparison of recreational health risks associated with surfing and swimming in dry weather and post-storm conditions at Southern California beaches using quantitative microbial risk assessment (QMRA). Marine Pollution Bulletin, 64(5), 912–918.CrossRefGoogle Scholar
- U.S. Environmental Protection Agency (U.S. EPA). (1986). Ambient Water Quality Criteria for Bacteria - 1986 (p. 15) (EPA 440-5-84-002)). Washington, DC: U.S. Environmental Protection Agency.Google Scholar
- U.S. Environmental Protection Agency (U.S. EPA). (2001). Risk Assessment Guidance for Superfund (RAGS) Volume III - Part A: Process for Conducting Probabilistic Risk Assessment (pp.3–1~3–27). Washington, DC: Office of Emergency and Remedial Response, U.S. Environmental Protection Agency.Google Scholar
- U.S. Environmental Protection Agency (U.S. EPA). (2012). Recreational Water Quality Criteria (p. 14) (EPA-820-F-12-058)). Washington, DC: Office of Water, United States Environmental Protection Agency.Google Scholar
- U.S. Environmental Protection Agency (U.S. EPA). (2014). Microbiological Risk Assessment (MRA) Tools, Methods, and Approaches for Water Media (pp.90–94 and pp.104–110) (EPA-820-R-14-009). Washington, DC: Office of Science and Technology Office of Water, U.S. Environmental Protection Agency.Google Scholar
- World Health Organization (WHO). (2003). Guidelines for safe recreational water environments. Vol. 1. Coastal and fresh waters (pp. 82–87). Geneva: World Health Organization.Google Scholar
- World Health Organization (WHO). (2016). Quantitative microbial risk assessment: application for water safety management (pp. 171–179). Geneva: World Health Organization.Google Scholar
- Yu, W. H., Harvey, C. M., & Harvey, C. F. (2003). Arsenic in groundwater in Bangladesh: A geostatistical and epidemiological framework for evaluating health effects and potential remedies. Water Resources Research, 39(6). https://doi.org/10.1029/2002WR001327.