Journal
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
Volume 23, Issue 3, Pages 390-409Publisher
SPRINGER
DOI: 10.1007/s13253-018-0326-9
Keywords
Interval estimation; Multi-dimensional degradation model; Risk indicator; Stochastic process
Funding
- Natural Science Foundation of China [71601138]
- Singapore AcRF [R-266-000-113-114]
- National Research Foundation Singapore under Campus for Research Excellence and Technological Enterprise (CREATE)
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available