Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed
被引:12
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作者:
Liao, Hehuan
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机构:
Virginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USAVirginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
Liao, Hehuan
[1
]
Krometis, Leigh-Anne H.
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Virginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USAVirginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
Krometis, Leigh-Anne H.
[1
]
Kline, Karen
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机构:
Virginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
Virginia Tech, Ctr Watershed Studies, 155 Ag Quad Lane, Blacksburg, VA 24061 USAVirginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
Kline, Karen
[1
,2
]
机构:
[1] Virginia Tech, Dept Biol Syst Engn, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
[2] Virginia Tech, Ctr Watershed Studies, 155 Ag Quad Lane, Blacksburg, VA 24061 USA
Fecal indicator bacteria;
Human illness risks;
Quantitative microbial risk assessment;
Total maximum daily load;
Waterborne diseases;
FECAL INDICATOR BACTERIA;
ESCHERICHIA-COLI;
RECREATIONAL WATERS;
DIE-OFF;
PATHOGENS;
FECES;
STORMWATER;
QUALITY;
QUANTIFICATION;
ENTEROCOCCI;
D O I:
10.1016/j.scitotenv.2016.02.044
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Within the United States, elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments requiring formal remediation plans under the federal Clean Water Act's Total Maximum Daily Load (TMDL) program. The sufficiency of compliance with numerical FIB criteria as the targeted endpoint of TMDL remediation plans may be questionable given poor correlations between FIB and pathogenic microorganisms and varying degrees of risk associated with exposure to different fecal pollution sources (e.g. human vs animal). The present study linked a watershed-scale FIB fate and transport model with a dose-response model to continuously predict human health risks via quantitative microbial risk assessment (QMRA), for comparison to regulatory benchmarks. This process permitted comparison of risks associated with different fecal pollution sources in an impaired urban watershed in order to identify remediation priorities. Results indicate that total human illness risks were consistently higher than the regulatory benchmark of 36 illnesses/1000 people for the study watershed, even when the predicted FIB levels were in compliance with the Escherichia coli geometric mean standard of 126 CFU/100 mL. Sanitary sewer overflows were associated with the greatest risk of illness. This is of particular concern, given increasing indications that sewer leakage is ubiquitous in urban areas, yet not typically fully accounted for during TMDL development. Uncertainty analysis suggested the accuracy of risk estimates would be improved by more detailed knowledge of site-specific pathogen presence and densities. While previous applications of the QMRA process to impaired waterways have mostly focused on single storm events or hypothetical situations, the continuous modeling framework presented in this study could be integrated into long-term water quality management planning, especially the United States' TMDL program, providing greater clarity to watershed stakeholders and decision-makers. (C) 2016 Elsevier B.V. All rights reserved.
机构:
Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Pacific Northwest Natl Lab, Atmospher Sci & Global Change Div, Richland, WA USAMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Qiu, Han
Niu, Jie
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机构:
Guizhou Univ, Coll Resources & Environm Engn, Guiyang 550025, Peoples R ChinaMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Niu, Jie
Baas, Dean G.
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机构:
Michigan State Univ, Agr & Agribusiness Inst, MSU Extens, E Lansing, MI 48824 USAMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Baas, Dean G.
Phanikumar, Mantha S.
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机构:
Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
MSU AgBioRes, E Lansing, MI 48824 USAMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
机构:
Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Div Earth Sci, Berkeley, CA 94720 USAMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
Niu, Jie
Phanikumar, Mantha S.
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机构:
Michigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USAMichigan State Univ, Dept Civil & Environm Engn, E Lansing, MI 48824 USA
机构:
USDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
Ascough, J. C., II
David, O.
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机构:
Colorado State Univ, Dept Civil & Environm Engn, Ft Collins, CO 80523 USA
Colorado State Univ, Dept Comp Sci, Ft Collins, CO 80523 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
David, O.
Krause, P.
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机构:
Thuringian State Inst Environm & Geol, Jena, GermanyUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
Krause, P.
Heathman, G. C.
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机构:
Purdue Univ, USDA ARS, Natl Soil Eros Res Lab, W Lafayette, IN 47907 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
Heathman, G. C.
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机构:
Kralisch, S.
Larose, M.
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机构:
Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
Larose, M.
Ahuja, L. R.
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机构:
USDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA
Ahuja, L. R.
Kipka, H.
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机构:
Colorado State Univ, Dept Civil & Environm Engn, Ft Collins, CO 80523 USAUSDA ARS, Agr Syst Res Unit, Ft Collins, CO 80526 USA