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

Abstract

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 (pvalue) 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.

Screening level ecological risk assessment for synthetic musks in surface water of Lake Taihu, China

“…eutrophication, declines in aquatic species, and extensive list of exotic species) in aquatic ecosystem (Wu et al 2001;Wang et al 2008;Qin et al 2011;Luo and Opaluch 2011). These changes have been linked to conventional pollutants, such as heavy metals (Schuler et al 2008), ammonia (Carrasco and Chang 2005), salinity (Muschal 2006), chlorinated ethenes (Benekos et al 2007), PAHs (Guo et al 2012a), and OCPs (Guo et al 2012b) in the aquatic ecosystem. However, some emerging persistent organic pollutants increasingly occurred in the environmental compartments and their ecological risks to aquatic organisms deserved most concern.…”

A Spreadsheet-Based Site Specific Risk Assessment Tool for Land-Applied Biosolids

“…There are a number of applications of spreadsheets in microbial risk assessment, most of which are in the area of food safety [22][23][24]. Several studies use spreadsheets to develop individual parts of the quantitative microbial risk assessment, such as modeling initial concentrations [25], dose-response relationships [26], pathogen transmission dynamics [27], and risk ranking [28]. While there are several well-developed spreadsheet-based environmental fate and transport models [16,[29][30][31], to date, there are no available comprehensive spreadsheet models that link quantitative microbial risk assessment with microbial fate and transport modeling.…”

Active Sampling Device for Determining Pollutants in Surface and Pore Water – the In Situ Sampler for Biphasic Water Monitoring

“…Accurate and efficient environmental sampling is therefore integral for the evaluation of inherent risks associated with environmental contamination. Measured concentrations of environmental contaminants are used in compliance reporting, modeling, and risk assessment for biota and humans 3 4 . Some contaminants, such as persistent organic pollutants, pose a long-term threat to ecosystems because they can remain in the environment for decades 5 .…”

“…Some contaminants, such as persistent organic pollutants, pose a long-term threat to ecosystems because they can remain in the environment for decades 5 . This issue is complicated by the fact that many persistent pollutants are hydrophobic, with n- octanol-water partitioning coefficient (K OW ) values on the order of 10 4 or greater. These hydrophobic organic contaminants (HOCs) are mostly sequestered by organic carbon (OC) in sediments, often irreversibly 6 7 .…”