Random Monte Carlo simulation analysis and risk assessment for ammonia concentrations in wastewater effluent disposal

High concentrations of ammonia in a river can cause fish kills and harms to other aquatic organisms. A simple water quality model is needed to predict the probability of ammonia concentration violations as compared to the US Environmental Protection Agency’s ammonia criteria. A spreadsheet with Random Monte Carlo (RMC) simulations to model ammonia concentrations at the mixing point (between a river and the effluent of a wastewater treatment plant) was developed with the use of Microsoft Excel and Crystal Ball add-in software. The model uses effluent and river ammonia, alkalinity, and total carbonate data to determine the probability density functions (PDFs) for the Monte Carlo simulations. Normal, lognormal, exponential and uniform probability distributions were tested using the Chi-square method and p-value associated with it to choose the best fit to the random data selected from the East Burlington wastewater treatment plant in North Carolina and the Clinch River in Tennessee. It is suggested that different options be tested with a minimum of three classes and a maximum of n/5 classes (n = number of data points) and the highest probability (p-value) for the PDF being tested be chosen. The results indicted that six violations to the EPA criterion for maximum concentration (CMC) were predicted when using 2000 RMC simulations and PDFs fitted to the available data, which violate the current criterion of no more than one violation over 3 years. All violations occur when the pH of the blend ranges from 8.0 to 9.0. No violations were found to the criteria of chronic concentration (CCC) using RMC.