Abstract
Monte Carlo simulation techniques can be used to calculate the return period of a one hour concentration estimate.1 Similar techniques can be used to synthesize dosage probability density functions (PDF) relating dosage level to frequency for a specified exposure interval under a defined set of conditions. Monte Carlo techniques also provide a means to estimate a probability of impact (some specified level of damage or injury) through the convolution of the dosage PDF and a dose-response PDF for the receptor (s) of interest. The technique begins with some months or years of representative hourly meteorologic data for the site in question. If only limited periods are of interest, e.g. daylight hours of the growing season, or episodes of high relative humidity, meteorologic data for only these periods are required. Given appropriate meteorologic data, emission rates, and background concentrations, a long series of concentration estimates (e.g. hour by hour values) are generated for the receptor site(s) of interest, and dosage levels for specified intervals (e.g. 1 hr, 4 hr, 8 hr, etc.) can be tabulated on a running average basis to yield a PDF relating dosage level to frequency for the time interval(s) and conditions of interest. Having derived this synthetic dosage PDF tailored to the conditions of interest, an estimate of the probability that these dosage levels will impact the receptor(s) can be arrived at through convolution of the dosage PDF, with a PDF describing the probability of the specified impact as function of dosage for the receptor(s) of interest under the conditions specified. Simply stated, the Monte Carlo convolution technique works by repeatedly selecting one dosage value from each PDF as a function of its relative probability, comparing the two values (impact or no impact) and recording the result. Done thousands of times, this technique yields an estimate of impact probability for the conditions specified. To examine conditions for dosage intervals or conditions other than those specified, portions of the methodology are repeated to generate the required PDF and the convolution exercise is repeated. Of course this method is no more accurate than the available data. However even with rather crude dosage and dose-response PDF, the method can be used to determine the relative probability of damage associated with different receptor sites over different time intervals. The method can also be used backwards to determine which of a variety of sources might be most responsible for a known impact. Sensitivity analyses performed on the model can also provide a convenient means to study relationships between various system components and the factors which limit model precision. This methodology is general in that it will work for any receptor type (plant, person, or material) under any set of circumstances for which a dose-response PDF can be specified, at any site for which a corresponding dosage PDF can be developed. McVoy2 describes in some detail how this technique can be used to predict the impact of a major air pollutant source upon local flora. Acknowledgment
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
