Modeling Nicotine Induced Chlorine Loss with EPANET-MSX
Citation:
Burkhardt, J., B. Burkhart, AND F. Shang. Modeling Nicotine Induced Chlorine Loss with EPANET-MSX. 2023 World Environmental & Water Resources Congress, Henderson, Nevada, ALAND ISLANDS, May 21 - 24, 2023.
Impact/Purpose:
This presentation/abstract focuses on highlighting the use of EPANET-MSX for modeling a complex multi-species reaction in water distribution systems. With the updates to EPANET-MSX, highlighting changes to the professional community within the Water Distribution Systems Analysis group will ensure up-to-date information is available to these users. The EWRI conference is frequently attended by academic and professionals working on advance water quality modeling techniques that would benefit from this information.
Description:
Many reactions that occur in water distribution systems cannot be completely described by the single species reactions available within EPANET, such as disinfectant byproduct (DBP) formation and associated disinfectant loss. To address this limitation, EPANET-MSX (Multi Species eXtension) was developed and recently updated (v1.0 to v2.0) to function with EPANET 2.2, and to add the capability to model dispersion. Dispersion can be relevant in premise plumbing systems or in dead-end or low-flow portions of a network. To demonstrate the new features, a series of nicotine injections in a laboratory distribution system will be discussed. New Python based EPANET-MSX handling scripts were used to automate the file handling, model execution, and data analysis. Following the events of September 11th, 2001, numerous studies were undertaken to understand the risk of intentional contamination events to distribution systems. One of those studies used nicotine because of its ease of acquisition and potential to deplete chlorine in piped systems. Reaction rate parameters were estimated from laboratory bottle tests and used to model a series of laboratory injection experiments. Adding dispersion to the models improved the accuracy of water quality simulations. Furthermore, the dual nicotine species model provided superior performance compared to the single-species model. These results highlight the value of multi-species modeling and demonstrate the potential for growth in this area.