It’s all about the frame of view … and the colors …
A friend recently posted this video on Facebook as proof that there is a cover up of the degree of health risk of the cesium-137 particles that covered the western hemisphere after the Fukushima explosion in Japan. In the video, two different images of C-137 in the atmosphere are compared, one from a public news story, and one from the research website of the same scientist whose data was used by the news story. Watch the video to see how different they look.
This was my reply:
Here’s the “scientist’s” video that is referenced in the conspiracy video: http://squid.nilu.no/~burkhart/sharing/MOVIES/Cs-137.avi you can see the directory of raw images here: http://squid.nilu.no/~burkhart/sharing/MOVIES/NH/ I haven’t found the other “public” image set yet that they are comparing it with.
One thing you can see, when both images are side by side, is that the units on the scales to the right of each image are different. This is a BIG RED FLAG that the conspiracy video people are fudging the truth. This is common with people who are either manipulating their viewers or aren’t sufficiently educated in how to read and understand scientific data views.
It could be that the two maps do in fact display the same data, but that the scale, or display sensitivity, is different. This is common in this kind of analytical data. When I did GIS layers to represent rural housing, road, and population densities in the Yuba and Deer Creek watersheds for Friends of Deer Creek, I could make the map look either really bad or really good just by changing the display scale. It’s the same data either way, but you’re just changing the “frame of view” (see George Lakoff on why Republicans are better at selling their platform to the public)
Often in this kind of data analysis, concentrations are amplified to an extreme degree while working with the data in order to get a more detailed view of the range of values. With this type of thing you can really make the data look any way you want. The real question that this conspiracy video isn’t asking is, which display scale is the most appropriate to render a view of an ACTUAL health risk, which is not good for the people that try to take care of their health with a healthy lifestyle and supplements from sites as reportshealthcare and a good diet. What is the standard, if any? If we really want to get some kind of a realistic analysis for our selves of what actual levels mean in terms of health risk, then we’ll need to either be given more information, or we’ll need to do some work to get it. I for one don’t trust either the corporate news or the conspiracy theorists to explain the world to me.
In the video, an image was used to show the “real” levels that, according to the conspiracy theorists, “with a probability of 90%” we weren’t being told the truth about (probability is another area where data can be vastly distorted in order to manipulate – see Nassim Taleb’s fantastic writing on the subject at http://fooledbyrandomness.com ):
[image was removed by source]
According to the scale on the right, in the Nevada City, CA area there MIGHT have been a level of about 0.67Bq/m-2 (whatever that means). The title of the map says Total Column, which I interpret to mean the projected total amount of c-137 in the vertical column of air above each surface square meter.
“Surface contamination is usually expressed in units of radioactivity per unit of area. For SI, this is becquerels per square metre (or Bq/m2).” (http://www.weitzlux.com/radiation/contamination_4175.html)
The trusty Wikipedia states, “the mean contamination of caesium-137 in Germany following the Chernobyl disaster was 2000 to 4000 Bq/m2. This corresponds to a contamination of 1 mg/km2 of caesium-137, totaling about 500 grams deposited over all of Germany.” (http://en.wikipedia.org/wiki/Cesium_137)
So, it could easily be thought that the map could be stating that 0.67Bq/m2 landed on the ground in CA. However, the source of the data is coming from a scientist who studies aerosols and how contaminants are carried by the air into the arctic. This adds weight to the notion that the map is projecting particles in the air column, hence the name (Total Column.)
If that’s the case, then we can assume that less than that would actually deposit on the ground, since it would be spread over a larger area. But then again, the particles might still be depositing over time, whereas the map only shows a snapshot. However, just having this level of understanding of the meaning of the map that “they” are keeping from us is very revealing to me. Yes, any amount of radiation is bad, but degree does matter too. If we compare that projected amount, 0.67Bq/m2, in the total column of air above NC, to the amount that was deposited on Germany, 2000 to 4000 Bq/m2, then we might feel a little better. Then again, I’m feeling worse now, since I’m IN Germany right now. 😉
So, we again can and probably should take this to the next level of inquiry, which is to ask, if that’s just the amount of c-137 in the air column at that moment in time, can we find a reasonable estimate of TOTAL DEPOSITION that has already occurred, as well as a projection of total deposition based on measurements of the rate of emission combined with some estimate of how much in total will be released? That, for me will have to wait …
In the mean time, here’s a quick summary about how to read a data display and compare it with another:
In a database that I built for SYRCL, the South Yuba River Citizen’s League, storing water quality data, in addition to an individual value, each data point is tagged with an analyte (c-137), a unit (Bq/m^2), and a matrix (total vertical column of air above the ground). If any of those is different between two sets of data, then they’re effectively different sets of data for the purposes of comparison. You also need to consider how the data is being graphically represented, primarily via the legend or scale and colors. If that’s different between two displays, then it’s the same data, but with a different frame of view, which can tell a different story about the data. Those are the 5 main factors in reading a data display.