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Environmental Risk Assessment of Emerging Contaminants Using Degradation Data

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Abstract

The degradation behavior of an emerging contaminant is a key factor in its environmental risk assessment. Existing risk assessment methods based on EC degradation data commonly neglect the time-varying volatility of the degradation, the possible correlations in degradation between different ECs, and the estimation errors. To fill the gaps, this paper proposes an EC risk assessment framework based on the Wiener process. We first focus on degradation data from competitive experiments, which are adopted to evaluate a useful risk indicator, i.e., the bimolecular rate constant of a degradation reaction. A two-dimensional Wiener process model is developed to capture the degradation behaviors of the target EC and a reference contaminant in the experiment. Point and interval estimations of desired quantities, including the rate constant and the degradation half-life, are developed. We further extend the model to the multivariate case, which is applicable to waste water treatment where multiple ECs degrade in a mixed solution. A risk indicator for the mixed solution is proposed, based on which a minimal treatment time can be determined. Both point and interval estimation procedures of the risk indicator and the minimal treatment time are proposed. Two EC degradation datasets are used to demonstrate the proposed methodologies.   Supplementary materials accompanying this paper appear on-line.

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References

  • Arnold, W. A. and Roberts, A. L. (2000), “Pathways and kinetics of chlorinated ethylene and chlorinated acetylene reaction with Fe (0) particles,” Environmental Science & Technology, 34(9), 1794–1805.

    Article  Google Scholar 

  • Benitez, F. J., Acero, J. L., Real, F. J., Roldan, G., and Rodriguez, E. (2013), “Photolysis of model emerging contaminants in ultra-pure water: kinetics, by-products formation and degradation pathways,” Water Research, 47(2), 870–880.

    Article  Google Scholar 

  • Buxton, G. V., Greenstock, C. L., Helman, W. P., and Ross, A. B. (1988), “Critical review of rate constants for reactions of hydrated electrons, hydrogen atoms and hydroxyl radicals (\(\cdot \text{ OH }/\cdot \!\! \text{ O }^-\)) in aqueous solution,” Journal of Physical and Chemical Reference Data, 17(2), 513–886.

    Article  Google Scholar 

  • Carrico, C., Gennings, C., Wheeler, D. C., and Factor-Litvak, P. (2015), “Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting,” Journal of Agricultural, Biological, and Environmental Statistics, 20(1), 100–120.

    Article  MathSciNet  MATH  Google Scholar 

  • Casella, G. and Berger, R. L. (2002), Statistical Inference, Duxbury Pacific Grove, CA.

    MATH  Google Scholar 

  • Chen, P. and Ye, Z.-S. (2018), “Uncertainty quantification for monotone stochastic degradation models,” Journal of Quality Technology, 50(2), 207–219.

    Article  Google Scholar 

  • Gmurek, M., Rossi, A. F., Martins, R. C., Quinta-Ferreira, R. M., and Ledakowicz, S. (2015), “Photodegradation of single and mixture of parabens–kinetic, by-products identification and cost-efficiency analysis,” Chemical Engineering Journal, 276, 303–314.

    Article  Google Scholar 

  • Gupta, A. K. and Nagar, D. K. (1999), Matrix Variate Distributions, CRC Press.

  • Hannig, J., Iyer, H., and Patterson, P. (2006), “Fiducial generalized confidence intervals,” Journal of the American Statistical Association, 101(473), 254–269.

    Article  MathSciNet  MATH  Google Scholar 

  • Hong, L. and Ye, Z.-S. (2017), “When is acceleration unnecessary in a degradation test?” Statistica Sinica, 27, 1461–1483.

    MathSciNet  MATH  Google Scholar 

  • Hong, L., Ye, Z.-S., and Josephine, K. S. (2018), “Interval estimation for Wiener processes based on accelerated degradation test data,” IISE Transactions, (to appear).

  • Iyengar, S. (1985), “Hitting lines with two-dimensional Brownian motion,” SIAM Journal on Applied Mathematics, 45(6), 983–989.

    Article  MathSciNet  MATH  Google Scholar 

  • Lin, A. Y.-C., Yu, T.-H., and Lin, C.-F. (2008), “Pharmaceutical contamination in residential, industrial, and agricultural waste streams: risk to aqueous environments in Taiwan,” Chemosphere, 74(1), 131–141.

    Article  Google Scholar 

  • Ling, R., Chen, J. P., Shao, J., and Reinhard, M. (2018), “Degradation of organic compounds during the corrosion of ZVI by hydrogen peroxide at neutral pH: Kinetics, mechanisms and effect of corrosion promoting and inhibiting ions,” Water Research, 134, 44–53.

    Article  Google Scholar 

  • Liu, X., Al-Khalifa, K. N., Elsayed, E. A., Coit, D. W., and Hamouda, A. S. (2014), “Criticality measures for components with multi-dimensional degradation,” IIE Transactions, 46(10), 987–998.

    Article  Google Scholar 

  • Mazille, F., Schoettl, T., Klamerth, N., Malato, S., and Pulgarin, C. (2010), “Field solar degradation of pesticides and emerging water contaminants mediated by polymer films containing titanium and iron oxide with synergistic heterogeneous photocatalytic activity at neutral pH,” Water Research, 44(10), 3029–3038.

    Article  Google Scholar 

  • Pal, A., Gin, K. Y.-H., Lin, A. Y.-C., and Reinhard, M. (2010), “Impacts of emerging organic contaminants on freshwater resources: review of recent occurrences, sources, fate and effects,” Science of the Total Environment, 408(24), 6062–6069.

    Article  Google Scholar 

  • Petrie, B., Barden, R., and Kasprzyk-Hordern, B. (2015), “A review on emerging contaminants in wastewaters and the environment: current knowledge, understudied areas and recommendations for future monitoring,” Water Research, 72, 3–27.

    Article  Google Scholar 

  • Porat, B. and Friedlander, B. (1986), “Computation of the exact information matrix of Gaussian time series with stationary random components,” IEEE Transactions on Acoustics, Speech, and Signal Processing, 34(1), 118–130.

    Article  MathSciNet  Google Scholar 

  • Steinfeld, J. I., Francisco, J. S., and Hase, W. L. (1989), Chemical Kinetics and Dynamics, Prentice Hall Englewood Cliffs, New Jersey.

    Google Scholar 

  • Stork, L. G., Gennings, C., Carter, W. H., Teuschler, L. K., and Carney, E. W. (2008), “Empirical evaluation of sufficient similarity in dose–response for environmental risk assessment of chemical mixtures,” Journal of Agricultural, Biological, and Environmental Statistics, 13(3), 313–333.

    Article  MathSciNet  MATH  Google Scholar 

  • Weerahandi, S. (1993), “Generalized confidence intervals,” Journal of the American Statistical Association, 88(423), 899–905.

    Article  MathSciNet  MATH  Google Scholar 

  • Whitmore, G., Crowder, M., and Lawless, J. (1998), “Failure inference from a marker process based on a bivariate Wiener model,” Lifetime Data Analysis, 4(3), 229–251.

    Article  MATH  Google Scholar 

  • Xu, Y., Nguyen, T. V., Reinhard, M., and Gin, K. Y.-H. (2011), “Photodegradation kinetics of p-tert-octylphenol, 4-tert-octylphenoxy-acetic acid and ibuprofen under simulated solar conditions in surface water,” Chemosphere, 85(5), 790–796.

    Article  Google Scholar 

  • Ye, Z.-S., Wang, Y., Tsui, K.-L., and Pecht, M. (2013), “Degradation data analysis using Wiener processes with measurement errors,” IEEE Transactions on Reliability, 62(4), 772–780.

    Article  Google Scholar 

  • You, L., Nguyen, V. T., Pal, A., Chen, H., He, Y., Reinhard, M., and Gin, K. Y.-H. (2015), “Investigation of pharmaceuticals, personal care products and endocrine disrupting chemicals in a tropical urban catchment and the influence of environmental factors,” Science of the Total Environment, 536, 955–963.

    Article  Google Scholar 

  • Zhai, Q. and Ye, Z.-S. (2018), “Degradation in common dynamic environments,” Technometrics, (to appear).

Download references

Acknowledgements

We are grateful to the editor, the associate editor, and the referee for their insightful comments that have lead to a substantial improvement of an earlier version of the paper. This work was supported in part by the Natural Science Foundation of China (71601138), Singapore AcRF Tier 1 funding (R-266-000-113-114), and the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE).

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Correspondence to Zhi-Sheng Ye.

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Hong, L., Ye, ZS. & Ling, R. Environmental Risk Assessment of Emerging Contaminants Using Degradation Data. JABES 23, 390–409 (2018). https://doi.org/10.1007/s13253-018-0326-9

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  • DOI: https://doi.org/10.1007/s13253-018-0326-9

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