Modeling the Diffusion of Contaminated Site Remediation Technologies

Hou, Deyi; O’Connor, David; Al-Tabbaa, Abir

Modeling the Diffusion of Contaminated Site Remediation Technologies

2014

Hou, Deyi | O’Connor, David | Al-Tabbaa, Abir

The present study developed epidemic models to predict the diffusion of remediation technology. Hypotheses were derived from the models and then tested using data collected from a questionnaire survey (n = 223) and a qualitative interview (n = 28) mainly conducted in the USA, UK, and China, as well as data from the US Superfund program. Hypothesis testing results indicate that: (1) tacit knowledge in innovative remedial technologies leads to logistic rather than exponential growth in their adoption, and (2) social-economic and regulatory factors affect the adoption of remediation technologies. For specific remedial technologies adopted in the US Superfund program, it was found that in-situ bioremediation (ISB) has a higher maximum adoption rate than in-situ chemical treatment (ISC), likely due to lower cost and higher social acceptance associated with ISB. The diffusion of ISC was found to be more rapid than that of ISB due to a greater degree of tacit knowledge associated with ISB.

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