A Statistical Method of Detecting Bioremediation

De-Chang Chen ； Michael Fries ； John M. Lyon

《Journal of Data Science》 1卷1期 (2003/01) Pp. 27-41

https://doi.org/10.6339/JDS.2003.01(1).109

並列摘要

Hydrocarbon contaminated soils result from pipeline ruptures, petroleum manufacture spills, as well as storage and transportation accidents (Bossert and Bartha (1984)). The cost of removal of the contaminated solids followed by incineration or by disposal in a landfill is prohibitive. Bioremediation-the use of microorganism populations to eliminate hydrocarbon contaminations from the environment-is the most acceptable technology for hydrocarbon cleanup (Bossert and Bartha (1984)). It can be argued that a decrease of the oil concentration in soil is not due to biodegradation but due to sorption. If this were the case, since mass transfer of sorption is a gradual process, a slow decrease in the oil recovery rate may be observed after a spill. However, a rapid or sudden decrease in the oil concentration during the incubation should exclude sorption as the primary mechanism contributing to the observed hydrocarbon loss. A Bayesian procedure is given to detect a change of the linear relationship between the oil concentration (the dependent variable) and the time in days since the addition of the oil (the independent variable). The advantage of this procedure is that it does not need to assume that the variance of the error before the change is equal to that after the change. The implementation of this procedure is straightforward.

並列關鍵字

Bioremediation ； change point ； linear model ； posterior distribution