But how much radiation was really released? There are several ways to measure radiation, but what we’re usually concerned with is the dose received — that is, how much radiation has hit the body of someone who gets exposed. It can be thought of like sunburn — if you’re out in strong sunlight for fifteen minutes, you are getting a “small dose” of sun; four hours, and you get a “big dose” and may get a sunburn.
In the U.S., this is usually measured as Roentgen, named for the discoverer of X-rays. (Strictly, it’s measured as “Roentgen absorbed dose” or rad, and the dose in humans is “Roentgen equivalent in man” or rem, but for our purposes it’s close enough to say 1 Roentgen = 1 rad, = 1 rem.) In the rest of the world, dose is measured in Sievert, with 100 Roentgen to 1 Sievert. A whole-body dose of 6 Sievert or 600 Roentgen is called the “LD 50/30 dose,” meaning that 50 percent of the people who get that dose will die within 30 days.
The highest dose rate — that is, the dose received in a period of time — that was observed around the Fukushima reactors was about 1015 microSeiverts per hour, but rapidly dropped to about 70 microSeiverts per hour. In other words, 0.001015 Sieverts per hour, or about 0.1 Roentgen per hour. The highest total body dose reported so far has been 106 milliSieverts, 0.106 Sieverts, or about 10 Roentgen.
What does this mean? Well, in the U.S., the average background radiation is around 7 milliSieverts (700 milli-Roentgen) a year; we here in Colorado nearly double that (more in some places, like Leadville) and some places have a background radiation of 50 times that or more.
So 1015 microSieverts is pretty significantly above normal background radiation, but that’s not the whole story either. By comparison, a CT scan exposes you to about 5 milliSieverts, 0.5 Roentgen; the total dose of the highest exposure reported has been about 20 CT scans. High altitude commercial flights have more radiation than normal background; 10 Roentgen is about twice what a intercontinental flight attendant gets in a year.
Effects of radiation
There’s no question that the effects of big doses of radiation are pretty awful; various systems break down, you can’t absorb food — in fact, vomiting and diarrhea are some of the first symptoms, along with hair loss — and eventually, your immune system fails and you die as a result of massive infections, or hemorrhaging, or dehydration. These effects are known as acute radiation syndrome, ARS.
Low levels of radiation are another thing. Obviously, we all are exposed to some radiation because of the normal background. The usual model, based on the people affected in Hiroshima and Nagasaki, and later Chernobyl, is called a “linear dose response model,” and assumes that if a dose of 100 rem causes there to be 10 percent more deaths in a population, then a dose of 10 rem will mean 1 percent more, 1 rem about 1/10th of one percent more, and so on.
This is a conservative model, but it has a problem — it predicts that places with high background radiation, like Colorado, will have higher cancer rates than places with low background radiation.
What really happens is exactly the opposite — we in Colorado have a lower cancer rate than people at sea level.
Why this would happen is currently unknown, and in any case the rates of cancer are small enough it’s hard to be sure how much of it is due to normal radiation exposure anyway, but there’s certainly some reason to think that the linear dose-response model is too conservative, that some amount of radiation has no particular harmful effect.
What happens, though, is that the model affects how we think about radiation. Very small amounts of radiation are detectable — it’s literally “shining a light” at us, begging to be detected. Following the linear dose response model, there are assumed to be health effects of very small radiation exposures, and that means the regulations require even very very small releases to be reported.
Unfortunately, they tend to be reported as “a very small release of RADIATION.”
Still, what some people are saying is this is “another Chernobyl.” So let’s talk about Chernobyl for a minute. The accident at Chernobyl was the biggest reactor accident that’s well-known, although probably not the worst reactor accident of any kind. In the Chernobyl accident, a reactor of a radically different design, with a containment building but no containment vessel, overheated and exploded; most sources say the graphite that made up the bulk of the reactor core caught fire, although some sources say the graphite didn’t actually catch fire, combust, it just was very hot. According to the UN report, about 50 people died as a result of the accident, some of them dying from acute radiation syndrome. The highest exposure reported was about 16 Gray — which is another damn unit. There are more physicists than there are things to measure, I guess they have to pack them in somehow. But a Gray is a Sievert, approximately.
That 16 Gray dose is about 1600 Roentgen, 1600-1700 rem, or nearly three times the “lethal” dose. That’s 160 times as great as the worst dose reported from Fukushima.
What’s more, the Chernobyl fire distributed large amounts of radioactive material around — including about 10 tons of the actual reactor core. Unlike the Fukushima reactors, Chernobyl had no containment vessel, so once it was burning it was open to the outside, and diffused easily through the atmosphere, eventually spreading across much of northern Europe and a good bit of western Asia.
At the time of the accident, there were many terrifying predictions of the long-term health effects of the radiation.
The UN investigated these effects, and reported on them, in 2005, 2008, and 2011. The report concludes that there may be as many as 4000 additional deaths total that can be attributed to the effects of Chernobyl, but that’s among all the deaths in one of the most densely populated parts of the world. In other words, the linear dose-response model predicts that perhaps one person in a million might die somewhat earlier than they would have otherwise. Statistically. But we can never know if the prediction is correct.