Skip to main content
SpringerLink
Log in

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

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

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 (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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Azevedo LGT, Gates TK, Fontane DG, Labadie JW, Porto RL (2000) Integration of water quantity and quality in strategic river basin planning. J Water Resour Plann Manag 126(2):85–97

    Article  Google Scholar 

  • Bowie GL, Mills WB, Porcella DB, Campbell CL, Pagenkopf JR, Rupp GL, Johnson KM, Chan PWH, Gherini SA (1985) Rates, constants, and kinetic formulation in surface water quality modeling. Rep. EPA/600/3-85/040, U.S. Environmental Protection Agency, Athens, GA

  • Brown LC, Barnwell TO Jr (1987) The enhanced stream water quality models QUAL2E and QUAL2E-UNCAS: documentation and user manual. EPA-600/3-87/007. U.S. Environmental Protection Agency, Athens, GA

  • Burgues SJ, Lettenmaier DP (1975) Probabilistic methods in stream quality management. Water Resour Bull 11(1):115–130

    Google Scholar 

  • Chapra SC (1997) Surface water quality modeling. WCB/McGraw-Hill, USA

    Google Scholar 

  • Decisioneering, Inc. (2001) Crystal Ball ® 2000.2 user manual. Denver, Colorado

  • E.P.A. (1980) Technical guidance manual for performing waste load allocations. Simplified analytical method for determining NPDES effluent limitations for POTWs discharging into low-flow streams. Office of Water Regulations and Standards, Washington, DC

  • E.P.A. (1984) Ambient water quality criteria for ammonia—1984. EPA 440/5-85-001 January 1985. Office of Water Regulations and Standards Division, Washington, DC

  • E.P.A. (1999) 1999 Update of ambient water quality criteria for ammonia. EPA-822-R-99-014 December 1999. Office of Water. Office of Science and Technology. Washington, DC

  • Haan CT (1977) Statistical methods in hydrology. The Iowa State University Press, Ames, Iowa

    Google Scholar 

  • House LB, Skavroneck S (1981) Comparison of the propane-area tracer method and predictive equations for determination of stream reaeration coefficients on two small streams in wisconsin. U.S. Geological Survey Water-Resources Investigations Rep. 80–105, U.S. Geological Survey, Madison, WI, USA

  • Kiely G (1997) Environmental engineering. McGraw-Hill, Berkshire, England

    Google Scholar 

  • Kottegoda NT, Rosso R (1997) Statistics, probability, and reliability for civil and environmental engineers. McGraw-Hill, Berkshire, England

    Google Scholar 

  • Marr JK, Canale RP (1988) Load allocation for toxics using Monte Carlo techniques. J Water Pollut Control Federation 60:659–666

    Google Scholar 

  • McIntyre NR, Wagener T, Wheater HS, Chapra SC (2003) Risk-based modeling of surface water quality: a case study of the Charles River, Massachusetts. J Hydrol 274:225–247

    Article  Google Scholar 

  • McIntyre NR, Wagener T, Wheater HS (2004) A tool for risk-based management of surface water quality. Environmental Modeling and Software (in press, available online at http://www.sciencedirect.com)

  • Melching CS, Yoon CG (1996) Key sources of uncertainty in Qual2e Model of Passaic River. J Water Resour Plann Manag 122(2):105–113

    Article  Google Scholar 

  • Mihelsic JR (1999) Fundamentals of environmental engineering. Wiley, New York, NY

    Google Scholar 

  • Mooney CZ (1997) Monte Carlo simulation—quantitative applications in the social sciences. SAGE University Paper No. 116

  • Rossman LA (1989) Wastewater treatment and receiving water body interactions. Dynamic modeling and expert systems in wastewater engineering. Lewis Publishers, Inc., Chelsea, MI, USA

    Google Scholar 

  • Sawyer CN, McCarty PL (1967) Chemistry for sanitary engineers. McGraw-Hill series in sanitary science and water resources engineering, New York, US

    Google Scholar 

  • Scavia D, Powers WF, Canale RP, Moody JL (1981) Comparison of FOEA and MCS in time dependent lake eutrophication models. Water Resour Res 17:1051–1059

    Google Scholar 

  • Schnoor JL (1996) Environmental modeling: fate and transport of pollutants in water, air, and soil. Wiley, New York, NY

    Google Scholar 

  • Sincock AM, Wheater HS, Whitehead PG (2003) Calibration and sensitivity analysis of a river water quality model under unsteady flow conditions. J Hydrol 277:214–229

    Article  Google Scholar 

  • Song Q, Brown LC (1990) DO model uncertainty with correlated inputs. J Environ Eng 116(6):1164–1180

    Google Scholar 

  • Streeter HW, Phelps EB (1925) A study of the pollution and natural purification of the Ohio River, III. Factors concerning the phenomena of oxidation and reaeration. U.S. Public Health Service, Pub. Health Bulletin No.146, February, 1925. Reprinted by U.S., DHEW, PHA, 1958

  • Sturges HA (1926) The choice of a class interval. J Am Stat Assoc 21:65–66

    Google Scholar 

  • Tung YK, Hathhorn WE (1988) Assessment of probability distribution of dissolved oxygen deficit. J Environ Eng ASCE 114(6):1421–1435

    Google Scholar 

  • Warwick JJ, Cale WG (1986) Effects of parameter uncertainty in stream modeling. J Environ Eng 112(3):479–489

    Google Scholar 

  • Wotton CL, Lence BJ (1995) Water quality management of ammonia under uncertainty. Integrated water resources planning for the 21st century. In: Proceedings of the 22nd annual conference, Cambridge, MA, 7–11 May

Download references

Acknowledgements

The Department of Energy Samuel Massie Chair of Excellence Program under Grant Number DE-FG01-94EW11425 sponsored this work. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the funding agency.

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, North Carolina A&T State University, Greensboro, NC, 27411, USA

    Ivan Jose Carrasco & Shoou-Yuh Chang

Authors
  1. Ivan Jose Carrasco
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shoou-Yuh Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shoou-Yuh Chang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Carrasco, I.J., Chang, SY. Random Monte Carlo simulation analysis and risk assessment for ammonia concentrations in wastewater effluent disposal. Stoch Environ Res Ris Assess 19, 134–145 (2005). https://doi.org/10.1007/s00477-004-0221-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-004-0221-5

Keywords

Search

Navigation