The Linear No Threshold model (Howard Hayden) USofA

The Energy Advocate August 2016 (Vol. 21, No. 1)

A monthly newsletter promoting energy and technology P.O. Box 7609, Pueblo West, CO 81007 Copyright © The Energy Advocate

The LNT The Linear-No-Threshold (LNT) model is commonly used by the Nuclear Regulatory Commission (NRC) to predict possible outcomes of radiation exposures.

Specifically, it says that the likelihood of a cancer resulting from exposure is directly proportional to the amount of exposure (the dose).

To be specific, the model says that the straight line in the graph extends all the way down to the 0 zero-dose, zero-response point 0 (0,0).

The contentious part of the LNT is about the response at very low doses: are very low doses actually hazardous? It is often easy to infer doses accurately, so the position on the horizontal axis can be accurately determined. Only for very strong doses can you determine the hazard, and even that is not so easy. For example, in the bombings of Hiroshima and Nagasaki, there were something like 100,000 survivors who received near-fatal doses, yet it took sophisticated statistical techniques to find that a few hundred cancers resulted from the radiation, against a background of about 20,000 cancers that would have happened anyway.

We will show below that the measure of radiation dose is not an additive quantity. It follows that the response (such as cancer) is not necessarily proportional to dose.

That much said, what is the importance of the possible offset from the (0,0) point? It is simply this: the population of the US is about 300 million, and of the world is about 7 billion.

If you assume that some minuscule radiation exposure to the population will cause a cancer in one person in 1,000,000 people, then there will be 300 cancers in the US and 7,000 cancers in the world. Never mind that there are already over 590,000 annual deaths due to cancer in the US. The 300 presumed deaths add to it, and our regulators get upset about that, and impose stringent, expensive rules on the nuclear industry (and the health industry as well) to be careful.

If the dose-response curve shows a threshold—that is, a dose below which there is no harmful response—then the

Radiation Exposure When we talk about radiation, we are usually talking about three kinds, dubbed alpha (), beta () and gamma (), by early scientists who did not know at the time exactly what the radiation was all about. It was soon learned that -particles are the nuclei of helium atoms, ejected from some nuclei such as radium and uranium. (They were identified as such by deflection in magnetic fields, and proved as such by the presence of helium atoms above a mercury column in which radium had been introduced.)

stringent rules become unnecessary. Nuclear power becomes, perforce, cheaper.

Another dose-response curve is the hormesis model, in which the response on the graph is LT Model negative.

That is, a small dose is beneficial instead of harmful. In this case the stringent rules are not only expensive, but actually harmful. For example, in Fukushima, there were over 1,000 evacuation-related deaths to escape radiation doses that were far below levels naturally occurring elsewhere. Japan decided to shut off all nuclear reactors and get the electricity from more-polluting, imported high-cost fuels. And what if a small dose of radiation actually reduces cancer incidence instead of causing more cancer? Another consideration is whether the high costs imposed by overregulation cause some early deaths, say, by poverty.

A recent letter to Physics Today [1] made a case for the threshold model: Muller’s and Stern’s approaches survive in the LNT model of today, which says that low-dose radiation increases cancer risk.

However, while linearity—the “L” in LNT—was demonstrated only at high doses, the absence of a threshold has never been demonstrated. The only scientific conclusion from the data from 1949 through today is that the linear threshold (LT) model, not the LNT, is correct, and it has a lowdose threshold below which radiation is harmless. Even data from atomic-bomb survivors, the gold standard of doseresponse data, do not support the LNT model; adaptive protections mitigate radiation-induced damage at low doses and low dose rates. No epidemiological studies have ever demonstrated a causal relationship between low-dose radiation exposure and carcinogenesis.

Some letters in the subsequent edition [2] of Physics Today insisted that the LNT is correct, and others insisted that it is not correct.

[1]

Jeffry A. Siegel, Charles W. Pennington, and Bill Sacks, “Lowdose radiation exposure should not be feared,” Physics Today 69(1), 12 (2016); online at http://dx.doi.org/10.1063/PT.3.3037

[2]

J. S. Levinger, “The linear no-threshold theory: Readers weigh in,” Physics Today 69(7), 10 (2016); online at http://dx.doi.org/10.1063/PT.3.3037

Beta () particles are nothing but ordinary electrons that are ejected by some nuclei when one of the neutrons breaks apart into a proton (which remains in the nucleus) and the escaping electron.

Gammas () are electromagnetic radiation—like ordinary light—but of much higher energy, emitted along with  and  emissions. X-rays, also electromagnetic radiation, are created by colliding high-energy electrons with metals (often tungsten).

Cosmic rays in space are mostly high-energy protons, but they result in high-energy x-rays caused by collisions with atmospheric gases.

1 pCi = picocurie. 1 Ci = 3.7 * 1010 disintegrations per second, the approximate activity of a gram of radium; 4pCi = .148 disintegrations per second per liter of air.

probabilities are additive.

Well, in statistics, some probabilities are additive and some are not.

It is perfectly possible for a straight line derived from data at high doses to seem to extrapolate right down to (0,0).

Absent proper accounting of propagation of error—how uncertainties in the data affect both the slope of the line and its intercept—the extrapolation to DOSE the (0,0) point is a matter of opinion, not of fact. Direct measurement near the (0,0) point is necessary.

At a meeting of the Doctors for Disaster Preparedness in Omaha (www.ddponline.org), Dr. Mohan Doss of the Fox Chace Cancer Center gave an excellent presentation of the failures of the LNT, from which much of the following discussion is derived. He presented evidence to show that the incidence of cancer decreases with dose, up to a limit of about 10 mGy/year (1000 mradyear), whereas the government recommends radon remediation when the indoor level is 4 pCi/liter1. Lung cancers decrease with increasing radon concentration up to well beyond 4 pCi/liter.

Doss corrected the atomic bomb survivor data (subtracting observed cancer rate from background cancer rate, as should have been done decades ago), and showed a decided hormesis effect, the J-shaped curve to the right.

He also presented similar data for many other known dose-response cases, for example bone sarcomas in radium-dial painters.

Cancer is, alas, largely a failure of the immune system.

Cells of the body are continuously being damaged and repaired, but suppressing the immune system increases the likelihood of cancer. Low doses of radiation evidently stimulate the immune system, with the result that there is a real hormesis effect. Any dose below about 100 mGy (10,000 mrads) can be considered safe.

RESPONSE

All of this radiation is ionizing. That is, the energies are high enough to knock electrons off of atoms and molecules— abundantly—resulting in ionized particles left behind.

To give some idea of scale, we will revert to the electron-volt (eV), which is the kinetic energy of an electron accelerated by one volt. Photons of visible light have energies in the range of 2-4 eV. Alphas typically have about 4 million eV of energy.

Beta energies are typically in the 100,000 eV range. Gammas vary from about 100,000 eV to a million eV. Cosmic rays have energies that go up to an extremely rare 10 20 eV, more or less equal to the kinetic energy of a major league fastball.

Radiation exposure (dose) is expressed in two ways, neither of which is actually a direct measurement. The first way is the absorbed energy per unit mass (inferred from measurements of the radiation itself, not by measuring the actual energy absorbed by the body). In modern units, it is expressed in joules of energy per kilogram (of exposed body mass), known as grays (abbreviated Gy.) In older units, it was expressed in ergs per gram, known as rads (1 Gy = 100 rads).

The other way of expressing exposure takes into account the fact that some kinds of radiation are more dangerous than others. For example, for a given dose (energy per unit mass), alpha particles are about 10 times as hazardous as x-rays.

When adjustment is made for the type of radiation, the equivalent dose is given in Sieverts (abbr. Sv) or the older rems.

For example, a 1-milligray (mGy) dose of alpha particles results in an equivalent dose of 10 mSv. Again, the two units differ by a factor of 100: 1 Sv = 100 rems; 1 mSv = 100 mrem, etc.

All of this is standard introductory fare for people who will be involved in radiation exposure: x-ray technicians, nuclear plant operators and technicians, radiation therapists, dentists, and radiologists. The implication of the assumed LNT model is that doses are an additive quantity. That is, if a person receives 3 mSv of environmental radiation every year for 20 years, and 10 mSv (some from the environment, some from xrays) for 2 years, the total exposure is 80 mSv. The LNT model further implies that the exposures of many people add up to a “population exposure.” If, say, all 100,000 people in a certain city receive 3 mSv per year for 50 years, the population exposure is 100,000 people multiplied by 150 mSv, or 15,000,000 mSv, or 15,000 Sv. Then, assuming that 50 Sv (this estimate changes a bit over time) is enough to cause a cancer, some 300 cancer cases will ensue.

Missing from the standard fare is the fact that exposure is not inherently additive.

Exposure, in the lingo of thermodynamics, is an intensive variable, like temperature or pressure, that does not increase as the quantity of matter increases. Examples of extensive variables are the internal energy, entropy, volume, and the number of molecules, all of which increase as the quantity of matter increases.

Imagine a one-kilogram mass of leg muscle exposed to one mJ of x-radiation. The dose of exposure is 1 mGy, and the equivalent dose is 1 mSv. Now, mentally separate the one-kg mass into two half-kg masses, each receiving 1 mGy (½ mJ divided by ½ kg). You can’t add the 1-Gy exposures to get 2 Gy. The absorbed energy is additive, but the dose is not.

Notwithstanding that radiation dose is an intensive variable that is not inherently additive, the people involved in radiation safety still add doses to get cumulative doses for individuals and population doses for large groups of people.

These statistical sums are basically proxies for probabilities that cancers will result. The underlying assumption is that the

Thirty-One? Not Quite!

Ari Halperin, a biologist specializing in coral reefs, has delved into the climate-change “consensus letter” promoted by the American Association for the Advancement of Science (AAAS).

Allegedly, 31 scientific societies signed the letter.

First, let it be known that the 31 societies did not poll their memberships.

The letter (available at http://www.eurekalert.org/images/2016climateletter6-2816.pdf) begins, “We, as leaders of major scientific organizations, write to remind you…”

Observations throughout the world make it clear that climate change is occurring, and rigorous scientific research concludes that the greenhouse gases emitted by human activities are the primary driver.

On July 6th Halperin “sent fact-checking emails to the CEO of the AAAS and to the top officials and/or media contacts of the 30 other organizations… The emails asked only about signing the letter, not about its content” [3]. He further asked to see the signatures of those who signed. The AAAS replied with a letter reminiscent of somebody shaking a feather pillow in your face [3]: In its reply, AAAS changed the published allegation that the letter was signed to “reflect the participation of leaders of each of the 31 named scientific societies” (Fact #1). My follow up letter, asking AAAS to confirm that the letter was actually signed, went unanswered.

That bit of evasion said a lot. Halperin writes Only two out of 11 societies that were classified as Tier 1 – the American Meteorological Society and the Geological Society of America – plainly confirmed that they signed the letter. Remarkably, the Geological Society disavowed the content of the letter simultaneously with its publication, right in the press release:

Geological studies have demonstrated that climate has changed repeatedly in the past and that future climate change is inevitable. Understanding the complex processes involved in climate change is necessary for adaptation and mitigation.

— Jonathan G. Price, Ph.D., CPG, President, Geological Society of America … The American Physical Society has explicitly rejected the discussed letter: “The American Physical Society did not

sign the letter because it was presented as a fait accompli, and there are significant differences between the letter and the APS Statement on Earth’s Changing Climate.” This fact alone refutes the letter’s claim to represent “consensus scientific view.”

To make a long story short, the AAAS lied.

[3]

Ari Halperin, “Ooops! Not all 31 scientific societies actually signed the AAAS ‘consensus’ letter: Recursive Lies and “Scientific Consensus” Letters,” 7/21/16, https://wattsupwiththat.com/2016/07/21/ooops-not-al-31scientific-societies-actually-signed-the-aaas-consensus-letter/

At night, Juan Piñeda López hears the hum of a wind turbine that churns 300 yards away from his adobe house.

Sometimes he catches the stench of lubricant that spews down the turbine’s mast.

Basically, all benefit in Mexico went to wind developers and to temporary workers who put up the wind turbines, but not to anybody else. Oh, and prices for electricity rose.

[4]

[5]

Coral Davenport, “As Wind Power Lifts Wyoming’s Fortunes, Coal Miners Are Left in the Dust,” New York Times,, June 19, 2016 Victoria Burnett, “Mexico’s Wind Farms Brought Prosperity, but Not for Everyone, New York Times, July 26, 2016

Old News There is one aspect in which gasoline engines differ greatly from electric motors. In a gasoline engine, the power is proportional to the amount of air sucked into the intake manifold (hence to the amount of fuel supplied to burn in that air). The faster the engine turns, the greater the power, up to a point where the opening and closing of valves becomes a problem.

The power produced by an electric motor is the product of the voltage (the energy per unit charge) and the current (the number of charges per second going through the motor). That seems simple enough, but things are not as simple as they seem. A spinning motor is also a generator. That is, a current-carrying coil that rotates in a field always generates a voltage in the coils. Figure 1 shows a rotor and stator of the electric motor from a dieselelectric locomotive. There are actually many different coils in the rotor (each somewhat as shown with a rudimentary one-loop coil) in the inset), that are fed current through the copper commutator bars on the right. (The gear on the left turns a ring gear on one wheel of the locomotive.)

Wind Fraud Exported The coal mining business is sorely beset by President Obama’s war on coal (based on the belief that CO2 is turning the earth into a hothouse), competition from natural gas which has been made cheap through hydraulic fracturing (“fracking”), and artificially low prices of wind and solar. In particular, coal mining in Gillette, Wyoming is on the wane, leaving coal miners without an income [4]. Fear not, because wind developers are receiving lavish subsidies elsewhere in Wyoming, namely in Carbon County. Carol Davenport writes [4] Today, about 66 percent of the electricity in the United States is produced by coal and natural gas, and just 7 percent is produced by renewable sources such as wind and solar. But market forces and government regulations are rapidly changing that picture.

Actually, market forces would shun expensive, unreliable, undispatchable electricity from wind and solar. If the picture is changing, it is entirely due to meddlesome politicians and bureaucrats manipulating prices to make wind and solar look economical.

Victoria Burnett begins a New York Times article [5] about wind power in Mexico: 2 Initially, the term emf was shorthand for electromagnetic force, which is not actually a force. (It is generated energy per unit charge, aka, voltage.)

Figure 1: The rotating coil (left) and the stator coils (right) produce a four-pole magnetic field (N-S-N-S around the edge) from a locomotive. Magnified image is of commutator bars that are connected to the electricity source via brushes

The current in the coil of resistance R causes the force that causes the coil to rotate. But the rotation itself causes a voltage in the very same coil—the faster the rotation, the larger the voltage. That voltage, called the back emf,2 actually subtracts from the applied voltage yielding V net  V appl  back emf , thereby reducing the current in the coil. As you would suspect, the back emf is zero when the motor is not rotating, and

maximum when the motor is at full RPM. For this reason, motors draw maximum power from their voltage source when the motor is not turning (or turning slowly). The power is

P  V net I  V net

2 V net V net  R R

We see that the input power is reduced because of the reduced voltage, and also because of the reduced current.

Electric cars, perforce, are very good at getting up to speed after a stop. They have maximum power when they are barely moving. People who take a Tesla for a test drive will be favorably impressed. Accelerating from 60 mph (100 kpm) to 70 mph (113 kpm) is another matter.

The problem with electric cars remains what it has been for well over a century: the batteries. The 1905 photograph to the right shows a car being recharged.

We have discussed batteries in some detail (see, for example, TEA, March 2015.) A possibility that looks more promising (on the surface at least) would be to use a fuel cell instead of a battery.

When a fuel is burned in air, the oxygen in the air is called an oxidizer and the fuel is called a reducer. One disadvantage of batteries for transportation is that the battery must carry the weight of both an oxidizer and a reducer. A fuel cell uses atmospheric oxygen for its oxidizer, and there does not require its weight to be carried.

None of this is news. Both electric motors and fuel cells were invented well over a century ago. The science is well understood. Nevertheless, the New York Times regards the technology as new [6].

Despite the litany of advantages of electric cars and fuel cells, there remains one rather nasty limitation. Fuel cells use a fuel for which there is no natural source: hydrogen.

Hydrogen sold and used commercially is derived from natural gas, primarily methane (CH4). It is more efficient overall to use the natural gas directly than to extract its hydrogen (making a gas that is harder to transport) for use in fuel cells.

As every student who has taken a class in chemistry knows, hydrogen can also be extracted from water via a process called hydrolysis. There is a cost, however. You put in more energy into hydrolysis than you get back from the hydrogen.

[6]

Neal E. Boudette, “Water Out of the Tailpipe: A New Class of Electric Car Gains Traction,” New York Times 7/21/16

STEM Notes The Tacoma Narrows Bridge collapsed spectacularly on November 7, 1940, even though it was only a few months old. (Use your browser to look up some videos of the event.) It twisted back and forth around its centerline, driven by a steady wind of about 35 mph (56 kph).

To all appearances, the torsional oscillation looked like a resonance phenomenon. A resonance occurs when (A) there is something that vibrates, (B) there is a periodic driver of some sort causing the vibrations, and the frequency of the driver equals the natural frequency of the vibrator. Under these

conditions, no matter what direction the mass of the vibrator is going, it is being pushed in that direction, always increasing its speed. The bridge clearly had two conditions, a natural frequency (almost everything does) and a driving force (the wind).

But, how could a steady wind cause that behavior?

Imagine that the bridge is slightly tilted, and that there is a steady wind at right angles to the bridge.

The tilt guarantees a larger force on the stretched cable than on the other one, hence a tendency to rotate toward the no-tilt orientation, and to overshoot. Meanwhile, the forces from the wind give a force perpendicular to the bridge, which is alternately downward and upward as the bridge tilts the way shown and then in the opposite orientation. That small up-and-down force (the highly exaggerated green arrow) became large enough to overcome the damping forces so that the oscillations could be maintained and even grow with time.

Micromanagement Humans have made wine for countless centuries.

Traditionally, wine was brewed and kept in cellars, where the temperature is relatively constant.

In modern times, red wines are served at cellar temperature, and white wines served cold.

Accordingly, manufacturers have sold commercial refrigerators specifically designed to hold wine bottles. Fortunately, as reported by the Media Research Center [7] the world has been saved from such independent behavior by new regulations from the Department of Energy [8]. Fortunately, there are only 161 pages to read about how to test such refrigerators.

Word has it that the DOE will be soon writing “Test Procedures for Cellars in a Warming Earth.” Stay tuned.

[7]

[8]

Alissa Lopez, DOE: New Regulations For Wine Refrigerators,” Media Research http://www.mrctv.org/blog/doe-new-regulationswine-refrigerators Energy Conservation Program: Final Coverage Determination; Test Procedures for Miscellaneous Refrigeration Products,” http://energy.gov/sites/prod/files/2016/06/f32/MREF%20TP%20F inal%20Rule_0.pdf.

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