Wednesday, 25 January 2017

4E (Washington State Convention Center )

ABS Consulting has for the last 40 years collected meteorological data at nuclear power plants and used that data to calculate dispersion parameters for use in licensing, routine annual reporting, and accident calculations. In the early days of this data collection there was considerable variation in the quality of the data that could lead to wide swings in the dispersion factors calculated. But now the quality of data is much better. This leads to several questions concerning how much data is enough to use in making these calculations and the differences between using hourly data and annual average dispersion factors in calculating individual and population doses. It is sometimes assumed that a single year of meteorological data is sufficient to characterize a site, and that data reduced to average X/Q data can be substituted for hourly data without materially changing the results. In this study, the authors used data collected for periods of 10 years or more at six sites to statistically assess the following cases:

1. The differences between annual datasets when examining the dose at given locations in the population grid using joint frequency tables of meteorological data.

2. The differences between annual datasets when examining the dose at given locations in the population grid using hourly meteorological data.

3. The differences between doses using joint frequency tables and hourly meteorological data at the same locations in the population grid for the same years.

4. The differences between annual datasets when examining total population dose using joint frequency tables of meteorological data.

5. The differences between annual datasets when examining total population dose using hourly meteorological data.

6. The differences between total population doses using joint frequency tables versus hourly meteorological data for the same years.

7. The effects of using actual population data rather than an average population density on the variations of total population dose.

Results will show whether there are systematic differences between using joint frequency tables and hourly meteorological data, the extent and significance of such differences, and the degree of variation to be expected between years. We will make recommendations concerning the use of hourly meteorological data versus annual average dispersion factors and the number of years of data to use in order to reduce the variation in dispersion factors.

1. The differences between annual datasets when examining the dose at given locations in the population grid using joint frequency tables of meteorological data.

2. The differences between annual datasets when examining the dose at given locations in the population grid using hourly meteorological data.

3. The differences between doses using joint frequency tables and hourly meteorological data at the same locations in the population grid for the same years.

4. The differences between annual datasets when examining total population dose using joint frequency tables of meteorological data.

5. The differences between annual datasets when examining total population dose using hourly meteorological data.

6. The differences between total population doses using joint frequency tables versus hourly meteorological data for the same years.

7. The effects of using actual population data rather than an average population density on the variations of total population dose.

Results will show whether there are systematic differences between using joint frequency tables and hourly meteorological data, the extent and significance of such differences, and the degree of variation to be expected between years. We will make recommendations concerning the use of hourly meteorological data versus annual average dispersion factors and the number of years of data to use in order to reduce the variation in dispersion factors.

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