Study: Modeling Fukushima NPP Radioactive Contamination Dispersion Utilizing Chino M., et al., source terms

Our goal involved developing contamination dispersion plots of the radionuclides emitted from the Fukushima Daichii Nuclear Power Plant; after which, we compare the simulation results to physical measurements taken at CTBTO monitoring stations located worldwide. Finally, we publish all data to the partMOM application for public analysis.

Click to view the entire array of output images

Method

We took Initial I-131 source term estimations from Chino M., et al. [7]. We developed Cs-137 release rates from the I131/Cs137 ratios published by Chino[7]. All datetimes in the Chino publication were converted to UTC for comparison to other data sets within the partMOM application. After April 5, 2011, a release rate of 1 billion bq/hr (for both I131 and Cs137) was used for the remainder of the simulation. We derived this release rate from the I131/Cs137 ratios for the beginning of April (Chino[7]) and the published release rates of Cs137 through June (TEPCO [11]).

We utilized the open source software FLEXPART for all dispersion models. We used standard FLEXPART configuration. Our transport bounding box extended from pole to pole essentially including the entire Northern and Southern hemisphere. Simulations utilized 0.5 deg GFS weather data and a total particle population of 5 million.  Convection was not accounted for (lconv=0). FLEXPART accounts for I-131 half life in its species definition file. Similarly, standard FLEXPART installations omit the half life of Cs-137 – a reasonable assumption considering the half life of 30+ years.  Accordingly, We did not activate the agespectra feature.

For details about the parameters supplied to the model please see the following files:

Link to Release File

Link to Command File

Link to Outgrid File

Results

In order to determine projected radionuclide concentrations,within the FLEXPART model, we defined >400 receptor points worldwide.  Our defined FLEXPART receptors correlate with locations for which we maintain physical, dose-rate or concentration, measurements. This allows a comprehensive analysis and validation of the FLEXPART model output.

Additionally, The ~8000 pFLEXPART plot maps establish an extensive visual diagram of the radioactive contamination dispersion.

In contrast to most original scientific studies, the aim of this project does not focus on publishing the consensus of a handful of scientists.  Rather, We aim to present the technical data, to a worldwide community, for the purpose of encouraging open commentary.

Please have a look at the published data and plot maps:

partMOM Application: FLEXPART model Utilizing Chino (20111) source terms.

We maintain a separate partMOM application into which we supply an ongoing analysis of this study. We encourage you to open a new partMOM application and begin an open analysis of your own.

Here are a few of the initial findings:

Initial review of the FLEXPART model output included comparison to published CTBTO concentration measurements.  FLEXPART output, in most cases, showed lower concentration levels than those published by the CTBTO.

Here in Takasaki, JP the levels of Cs137 and I131 were smaller,  by one order of magnitude, than CTBTO measured concentrations.

CTBTO publishes concentration measurements for Takasaki, JP when no concentrations are projected by the FLEXPART model output.

March 18, 2011 Sacramento, CA. FLEXPART output indicates concentrations of I131 (2) orders of magnitude lower than those published by the CTBTO while FLEXPART Cs137 level are consistent with those published by the CTBTO.

Upper altitudes (altitudes >32 meters above ground level) showed radionuclide concentrations several orders of magnitude higher than near surface concentrations.  This indicates physical measurements, taken at monitoring stations near ground level, may represent only a fraction of the total concentration of radionuclides dispersed over a location.  A more accurate assessment of radionuclide dispersion requires measurements at several different altitude levels.  Specifically, disclosure of helicopter or deploy-able monitor measurements would provide a much more detailed account of the contamination dispersion.

Sources of Error

Model Input Parameters. Small changes to input parameters can profoundly effect the FLEXPART model output.  For example,  increasing the lsync value by 6 times corresponds to an increase in concentration readings (at long range receptor locations) more than 4 times.  We used standard FLEXPART parameters (see COMMAND file above) but the importance of input parameters should not be overlooked.

Model errors.  FLEXPART uses probabilistic algorithms to predict particle transport.  It is possible the FLEXPART model contains some inaccuracies which would, in turn, produce errant concentration approximations.

Source Terms. The exact emissions from FNPP are not known.  Chino(2011) uses deductive algorithms to evaluate source terms – but the fact remains that no direct measurements, of the emissions at the FNPP reactors, were taken (or if they were they have not been publicly released). Any statistical or algorithmic errors in the evaluation could lead to errant source terms.  Furthermore, Chino(2011) does not consider the possibility of emissions from the spent fuel pools at reactors 2,3,and 4 – this possibility remains widely debated.  It should be pointed out that a “core melt on fresh air”, at spent fuel pool 4, has been specifically mentioned in an Areva report to the Japanese government.

Measurement Inaccuracies. It is possible the the physical measurements taken at monitoring stations contain some errors or that actual valid measurements have been withheld.

Weather Data.  We utilize GFS data at .5 degree resolution.  This resolution is sufficient for long range and meso scale dispersion forecasts; however, local weather data is preferable for short range transport and deposition modeling.

Conclusion

FLEXPART output consistently showed concentrations 1-2 orders of magnitude lower than those published by the CTBTO.  We cannot explain the conflict, between modeled and measured data, using model error solely.  We consider errors in the source term evaluation as one possible source of these conflicts. Our ongoing research includes utilizing source terms 2-3x greater than those published by Chino(2011).

Particle dispersion and deposition models, such as FLEXPART, currently do not exactly reproduce physical events.  That is to say, the model provides a statistical estimation of the movements of a particle in time and space which may differ from the actual physical movements of the particle.  If we maintained exact physical measurements of these particles, throughout their lifetime and travels, we would not need a dispersion model.

Models, utilizing statistical algorithms to approximate the properties of a population, present the potential for errors. It’s important to note, statistical models accurately reflect reality only if both the underlying algorithms and the parameters supplied to the model are correct.

The FLEXPART model (and others like it) provides a framework upon which we can both  develop ideas about both the travel and dispersion of radionuclides and forecast populations and locations with a potential for exposure to high levels of contamination. As we observed with the model of the Namie evacuation, FLEXPART revealed locations, along the existing evacuation route, subjected to high levels of contamination – this leads to very helpful inferences such as: “Evacuating [Namie town] to a location 15km Northwest may not be such a great idea – a better idea may be to visit your aunt, in Niigata prefecture, on the west side of the island”.

We contend that particle dispersion models, such as FLEXPART, should play an important role in both forecasting the dispersion of contamination and identifying “hot spot” locations exposed to high levels of contamination.

Study: Modeling Fukushima NPP Pu-239 and Np-239 Atmospheric Dispersion

A recently disclosed Tepco documentation indicates total emissions estimates of both plutonium 239 and neptunium 239 for the first 100 hours of the catastrophe.  This leaked Tepco document [19] suggests a release of 1.2 trillion bq of pu-238,pu-239,p-240 and pu-241 collectively and 76 trillion bq of Np-239 within the first 100 hours of the catastrophe. Our goal with this study included developing atmospheric dispersion plots of these emissions and modeling radionuclide concentrations at receptors worldwide.  We then publish these results to the partMOM application for public analysis.

pFLEXPART output of P239 and NP239 atmospheric dispersion.

Click here for the full array of plot maps.

Method

In order to develop a time frame of the emissions we utilized the temporal framework established by Chino M., et al. [7]. Specifically we assumed the first 100 hours of the catastrophe to include March 12, 2011 01:00 – March 16, 2011 05:00, adjusted to UTC time.

Similarly, we implemented release ratios identical to those of I-131, as established by Chino(2011).  That is to say, for the period 3/12 01:00 – 3/14 14:00 (61 hours total) we assumed a release of 2% of the total emissions of both pu-239 and np-239. The following table outlines the release ratios for the duration of the 100 hour emission interval:

After the initial 100 hours we assumed emissions of pu-239 and np-239 did not continue.  We acknowledge this may not represent an accurate emissions profile for the isotopes as it’s likely the isotopes were continuously emitted even after the initial 100 hour emission interval.

We utilized the open source software FLEXPART for all dispersion models. We used standard FLEXPART configuration. Our transport bounding box extended from pole to pole essentially including the entire Northern and Southern hemisphere. Simulations utilized 0.5 deg GFS weather data and a total particle population of 5 million.  Convection was not accounted for (lconv=0).

We added a species definition to FLEXPART for both pu-239 and np-239. We assumed both isotopes were completely volatilized and had properties similar to volatilized Cs-137. A link to both species definitions follows:

Pu-239 Species File

Np-239 Species File

Neptunium 239 quickly (2.3 days) decays into Plutonium 239.  FLEXPART does not account for beta decay and it does not suffice to simply drop the Neptunium isotopes from the model after 2.3 days (via a half-life parameter or agespectra definition) because the result of the decay (Pu-239) is of great interest. Instead we omit the half-life of Np-239 from the species definition and use the resulting concentrations of Np-239 to proceed with decay chain calculations.

Results

In order to determine projected radionuclide concentrations,within the FLEXPART model, we defined >500 receptor points worldwide.  No model validation has taken place due to the absence of any, as far as we know, publicly disclosed Plutonium or Neptunium measurements.

Additionally, The ~2000 pFLEXPART plot maps establish an extensive visual diagram of the radioactive contamination dispersion.

In contrast to most original scientific studies, the aim of this project does not focus on publishing the consensus of a handful of scientists.  Rather, We aim to present the technical data, to a worldwide community, for the purpose of encouraging open commentary.

Please have a look at the published data and plot maps:

partMOM Application: Modeling Pu-239 dispersion with FLEXPART

Sources Of Error

Translation. We depended entirely on outside sources for translation of the leaked Tepco documentation.  There remains some possibility that the document has been interpreted incorrectly.

Release Rates. We made several assumptions as to the release rate of both isotopes.  The release rates represent our best educated guess at actual release rates.  As no physically measured release rates currently exist, our release estimates may contain errors.

Physical Measurements. No validation of FLEXPART dispersion maps took place due to the absence of any published physical measurements of the isotopes modeled.

Conclusion

It remains difficult to determine the prevalence (or lack thereof) of Pu-239 or Np-239 as Japanese and American officials have disclosed few if any measurements of the isotopes.

Spec: DATAPOKE Model Data – Chino(2011)[7]

When we run a dispersion model, we set up >500 receptor points (mostly populated cities across the globe) to measure simulated radionuclide concentration at specific time intervals.  This datafile contains the results of I131 and Cs137 measurements, at three hour intervals, at these receptor points.  Please see our study for more information on this dispersion simulation.

partMOMDataPoke Models and Data – Chino(2011)

Source: Datapoke atmospheric dispersion simulation.

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: dp_chino

Commentary:  Check out the study of this data set!

Spec: California Air Quality Datafile

Air Quality Data (AQ) collected by the California Air Resources Board (ARB). The ARB measures Air Pollutants at >180 locations across California.

partMOM: California AQ App

Source: California Environmental Protection Agency

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: california_air_quality

Commentary:  Notable air pollutants measure by the ARB include:

Black Carbon, Carbon Dioxide, Carbon Monoxide, COH, Hydrogen Sulfide, Light Scattering, Methane, Nitrogen Dioxide, Nitric Oxide, NOx, NOy, Non Methane Hydrocarbons, Ozone, Total Hydrocarbons.

Of particular interest:

ARB also measures Particulate matter with aerodynamic diameters less than or equal to 10 microns and 2.5 microns, PM10 and PM2.5 respectively. Off the top of my head, I don’t recall the diameters of the particulate emanating from FNPP – but this is something to look into.

Sulfur Dioxide and PM10 – sulfate is also measured.  According to the paper by  Priyadarshi A., et al. [13] both of these compounds provide evidence of neutron leakage from FNPP. I haven’t scoured the data but its there for anyone who’s interested.

We are looking for more Air Quality Measures from around the country! (and the world for that part).

Spec: CTBTO Air Sampling

As part of the Comprehensive Nuclear-Test-Ban Treaty, an International Monitoring Network was set up to measure radionuclide concentrations in the atmosphere.  The data is aggregated by the CTBT Preparatory Commission and disseminated to the participating countries.  The CTBTO will not publish the data – only the participating country can choose to publish the measurements. Currently very few countries have the guts to publish this data – Germany is the source of this material.

partMOM: CTBTO app

Source: The Federal Office for Radiation Protection in Germany (BFS)

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: ctbto_air_sampling

Commentary:  A useful set of data that contains I131 and Cs137 readings from ~15 locations worldwide. I usually use this data set as a preliminary validation of any dispersion plots.  The fact that the data did not have to be disclosed, but was released by choice, leads me to believe that it may be one of the more transparent data sets currently available.

Spec: EPA Laboratory Monitoring

The US Environmental protection agency produces (from what I gather) 2 types of data sources.  One comes from their persistent RADNET monitoring network and the other from laboratory analysis on a per need basis.

EPA step up their lab monitoring of precipitation, drinking water, and milk during the first few months after the FNPP Catastrophe. Here is the data.

partMOM: EPA Lab app

Source: EPA Radiation Monitoring

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: epa_air_filter

datafile: epa_drinking_water

datafile: epa_milk

datafile: epa_percipitation

Commentary:  Overall a pretty meager set of data containing ~50 sites nation wide. Most sites might have two or three recorded measurements dates. This is one of the smallest data sets we’ve come across. In my opinion there is more data that has not been disclosed.

Spec: EPA RADNET Monitors

This data comes from the EPA’s persistent RADNET monitoring network.

partMOM: RADNET App

Source: EPA RADNET

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: epa_radnet

Commentary:  A fairly robust data set containing measurements from ~50 sites nation wide. Measurements are taken at hourly intervals.  The data is published real-time so one would assume a fairly high degree of transparency.  The data also happens to be cryptic as the EPA labels their gamma spectrum not by energy range but by some other esoteric method. After some research I’ve managed to find the corresponding gamma energy ranges:

Energy Ranges Energy Range Number Gamma Energies (keV)
1 Reserved by software for instrument stabilization
2 100-200
3 200-400
4 400-600
5 600-800
6 800-1000
7 1000-1400
8 1400-1800
9 1800-2200
10 2200-2800

The ranges allow for some ambiguity, which may be a protective measure – the EPA can say something like “That spike in range 3 was not due to Iodine-131 it was due to naturally occurring Lead-214″. Which we could not dispute because we do not know the specific energy levels at which gamma counts took place. It would be very helpful if the EPA would disclose gamma counts at specific energy levels. For example how many gamma counts at 364Kev (this would be a strong indication of I131 presence). Do they have this data? If they did would it ever be disclosed publicly?

Spec: Speedi Data

From Sendung.de:

People around the world are concerned about the level of radiation in Japan due to major damages on the Fukushima Daiishi nuclear power plant. The Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan publishes real time radiation measurement data acquired by the “System for Prediction of Environment Emergency Dose Information” (SPEEDI).

However, these measurements published by the japanese administration are not very accessible to the public. Raw data cannot be accessed. And historic values are only available as graphical representations.

The next step then was to harvest the published data programmatically. Measurements are now crawled automatically and extracted from the HTML pages. The extracted data is provide in the CSV file available above.

partMOM: Speedi App

Source: Japan Radiation Open Data

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: speedi_data

Commentary:  An Incredibly rich source of data.  This set includes radiation dose measurements from over 200 locations across Japan.  The measurements are taken every 10 minutes – thats alot of data.  My next step involves converting these dose rates to concentrations for comparison to dispersion simulations. Want to help?

Spec: CDC Morbidity and Mortality Datafile

The US Centers for Disease Control publishes weekly summaries of mortality and morbidity figures for ~120 major cities across the country.

partMOM: CDC Mortality App

Source: Morbidity and Mortality Weekly Report (MMWR)

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: datafile: cdc_deaths

Commentary:  Inspired by the hot debate, surrounding Dr. Janette Sherman’s blog post, I decided to compile over 1 year of morbidity data from the CDC and run some statistics algorithms on the set.  My algorithms and methods may contain some errors so please contact us with any errors. The data includes weekly fatality numbers for 5 separate age groups.  Also included in the datafile is fatalities attributed to pneumonia and influenza.  Any other diseases I should be on the look out for? let me know.

Spec: NILU Flexpart products for Fukushima

Once upon a time, The Norwegian Institute for Air Research published radionuclide dispersion plots of the FNPP contamination.  We picked these up before the images went terminal.

partMOM: C137 Dispersion Plots

Xe133 Dispersion Plots

I131 Dispersion Plots

Source: FLEXPART products for Fukushima

Download: We’re working to integrate our datasets into Google Fusion Tables and/or Pachube.  If you’d like to help please contact us.

Wiki: mapfile: NILU Cesium Northern Hemisphere Total

mapfile: NILU Cesium Pacific Ocean surface

mapfile: NILU Iodine Northern Hemisphere Total

mapfile: NILU Cesium Pacific Total

mapfile: NILU Iodine North America Total

mapfile: NILU Xenon Pacific

mapfile: NILU Xenon Northern Hemisphere

Commentary:  “We have discontinued our Flexpart forecast of the atmospheric dispersal of radionuclides from Fukushima. This due to the fact that we do not have access to reliable release rates reflecting the current situation at the plant to be used as input to our simulations”. NILU (2011)