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Sunday 22 June 2014

Plotting Real Fukushima Data Because I Can

Gunning Fog Index = 12.49

More nerdly fun with data from the EPA radiation monitoring database. It took me a while to make this plot but I find it fascinating.


Not only can you see a Be-7 spike in the month after the Fukushima disaster, you can also see the effect of EPA budget cuts starting in federal fiscal year 2010. We lack what would have been truly significant data because of the budget wars - data that has implications for the health and safety of all citizens. It's not that I'm saying all budget cuts are bad but I do opine that indiscriminate budget cuts or cuts aimed at an agency disliked by powerful special interests can hurt us. Not all regulation is bad and not all businesses act in the public interest, as that great Republican Teddy Roosevelt would have said if he were still alive today. Well, that's my opinion, for what it's worth.

Why am I playing with Fukushima data? Partly because I'm sick and tired of looking at faked Fukushima data on the internet that's designed to scare and panic people. I know where to find real data and I'm not afraid to use it.

As a scientist, what I find really sad about this data is that clump of intense sampling for the month and a half just after Fukushima with no monthly sampling before or after. For a radioisotope like Be-7 which has well-known seasonal and solar-cycle variation cycles, the lack of before and after data makes that clump of post-Fukushima data almost useless because the signal of the Be-7 variation cycles now can not be accurately removed to show the magnitude of the Fukushima pulse.

Thursday 7 November 2013

The Great Obama Healthcare Cover-Up!

Today's subject is an article by Ann Coulter. Looking at the lead article on her website, Health Care for the Pushy, (, accessed 07 Nov 2013), I could not fail to notice several misstatements.

The premise of Coulter's article is that Obama lied about people being able to keep health insurance they like. Regardless if one agrees or disagrees with Coulter's opinion on Obamacare, she doesn't seem to have a good handle on her facts. For instance, she says:

Eighty-five percent of Americans were happy with their health care before Obamacare, according to the American Customer Satisfaction Index -- higher than almost any other product or service polled.

Well, if you go and look at the American Customer Satisfaction Index (, accessed 07 Nov 2013), 72% of people with health insurance in 2012 were satisfied with what they had. If we consider that approximately 85% of Americans had some kind of health insurance in 2012 (ref:, accessed 07 Nov 2013), this means that approximately 61% of Americans had health insurance that they were happy with. I have no idea where Coulter got her numbers - certainly not from the American Customer Satisfaction Index.

In the first 100 words of Coulter's article she cites sources for two statements. The first is simply "Obama lied." Her citation link takes you to the page for her new book, Never Trust a Liberal Over 3, Especially a Republican. That crackling noise you hear is the sound of my mind boggling. I don't think can we hold up Ann Coulter as someone to emulate for her citation style though her marketing style has much to admire.

Coulter's second citation is attached to this statement:

Even without the 2010 Health and Human Services (HHS) report admitting that 93 million Americans would lose their health insurance, anyone with half a brain (which is a pre-existing condition) knew that millions of Americans would be thrown off their insurance plans under Obamacare.

That's quite a statement, and since Coulter was so obliged to provide a link as citation, of course I had to check it out. It turns out that Coulter's citation-by-link takes you not to a government report but to an October 31 article on the Forbes magazine website. The article is Obama Officials In 2010: 93 Million Americans Will Be Unable To Keep Their Health Plans Under Obamacare, in a regular column called The Apothecary by Avik Roy (, accessed 07 Nov 2013).

In the Forbes article, the author cites "an obscure" 2010 study in the Federal Register as support for his contention that:

Obama administration knew that Obamacare would disrupt private plans. If you read the Affordable Care Act when it was passed, you knew that it was dishonest for President Obama to claim that “if you like your plan, you can keep your plan,” as he did—and continues to do—on countless occasions. And we now know that the administration knew this all along. It turns out that in an obscure report buried in a June 2010 edition of the Federal Register, administration officials predicted massive disruption of the private insurance market.

The Forbes article bravely gives the reader a workable link to the study in the Federal Register and even goes so far as to quote and cite the study's contents by page:

The Departments’ mid-range estimate is that 66 percent of small employer plans and 45 percent of large employer plans will relinquish their grandfather status by the end of 2013,” wrote the administration on page 34,552 of the Register.

Have you ever spent time trying to read statutes and regulations issued by the federal government? My sympathy to those, like me, who have had to do so in pursuit of employment. (Frankly, if I never have to see another EPA rule on drinking water standards, I will die a happy camper.) It is well known that federal regulations have off-label uses for curing insomnia and driving mothers-in-law into long-term care in a sanatarium. The Federal Register document cited here is no exception.

If you visit page 34,552 of the 2010 Federal Register, what you will find is a page that's in the middle of an analysis to estimate how many grandfathered employer-provided health insurance plans would be retained or relinquished for new plans as a function of different market conditions. It looked at existing patterns of insurance plan turn-over, the availability of plans with more competitive pricing, annual increases in insurance costs and factors that might lead a small business to drop employee health insurance altogether, to name some of the variables examined.

It's worth looking at this section of the Federal Register document a little closer. Here's the section and sub-section titles:

Estimates of Number of Plans and Employees Affected
  1. . Methodology for Analyzing Plan Changes Over Time in the Group Market
  2. . Impacts on the Group Market Resulting From Changes From 2008 to 2009
  3. . Sensitivity Analysis: Assuming That Employers Will Be Willing To Absorb a Premium Increase in Order To Remain Grandfathered
  4. . Sensitivity Analysis: Incomplete Flexibility To Substitute One Cost-Sharing Mechanism for Another
  5. . Estimates for 2011–2013

In a nutshell, this analysis began by explaining how the estimates would be derived, looked at data from 2008 and 2009 as an aid in making estimates, pushed the data through two different scenarios to test how different market conditions would impact the numbers calculated, and then made estimates based on all of that. Forbes neglected to say anything about the character of this speculative analysis, and in fact, Forbes managed to leave off the first clause of the sentence it quoted directly. Here's the whole statement, including what Forbes left out:

Under this assumption, the Departments’ mid-range estimate is that 66 percent of small employer plans and 45 percent of large employer plans will relinquish their grandfather status by the end of 2013.

Did you catch that? "Under this assumption..." This statement is conditional on an assumption. What assumption is that? Let's the Federal Register speak for itself:

Estimates are provided above for the percentage of employers that will retain grandfather status in 2011. These estimates are extended through 2013 by assuming that the identical percentage of plan sponsors will relinquish grandfathering in each year. Again, to the extent that the 2008–2009 data reflect plans that are more likely to make frequent changes in cost sharing, this assumption will overestimate the number of plans relinquishing grandfather status in 2012 and 2013.

Basically, this document looked at employer-provided insurance plan turnover data from previous years and then used it to extrapolate those rates for 2012/13.

This is a far cry from saying that Obama knew that 93 million people would have their insurance cancelled on them.

Here's the kicker, at least for me - the title of this Federal Register document is:

Interim Final Rules for Group Health Plans and Health Insurance Coverage Relating to Status as a Grandfathered Health Plan Under the Patient Protection and Affordable Care Act

Right below this title you will find:

ACTION: Interim final rules with request for comments.

This analysis included in this Federal Register document isn't a "2010 Health and Human Services (HHS) report" as Coulter described it, nor an "obscure report buried in a June 2010 edition of the Federal Register" as it was described in Forbes. This analysis was the internal commentary of the proposed final form of the regulations governing grandfathered health insurance under the Affordable Care Act, complete with a call for commentary to be considered prior to the issuance of the final regulations.

Were there any statements in these Interim Final Rules on grandfathered health plans that the Obama administration knew 93 million Americans would have their insurance cancelled on them in 2013? I think there are two ways to answer that. The first is easy: no, there is no such statement in this Federal Register document. The second is similar: an estimate that approximately half of all employer-provided health plans will relinquish grandfathered status due to market conditions is not the same things as saying 93 million people will have their health insurance cancelled on them. Those statements may look the similar but they are not the same. A citron is not an orange despite the fact that they are both round juicy citrus fruits. And I don't buy the sudden discovery by pundits that the current administration knew the sky would fall back in 2010 and knowingly kept it from everyone. Publication of proposed regulations with requests for commentary in the Federal Register is not at all obscure. In addition, are conservative pundits really so dense that they missed calling Obama out on the keep-your-health-plan comment when folks like took him to task in 2009 for it? Say it ain't so!

The real issue at hand is not the misquoting the Federal Register. The real issue is that President Obama said that people would be able to keep the health insurance plans they liked. The patent absurdity of that statement was blown out of the water in the same year that Obama uttered it, by no less than that great non-partisan debunker of political hyperboles, (see, accessed 07 Nov 2013).

I think Obama is going to regret what he said about people keeping their health care plans. I think it's going to be the greatest foot-in-mouth moment of the Obama presidency, one just as reknowned as "Read my lips - no more taxes" and "I'm not a crook!"

As far as legacy quotes are concerned, it's nowhere as good as "I did not have sexual relations with that woman!"

Wednesday 18 September 2013

Miscaptioning Atrazine

What a difference a few words makes. Today's offering is a figure caption from Wikipedia. Maybe it's unfair to pick on Wikipedia - but since it has become the launching point for many an inquiry, I don't think they should be exempted from scrutiny. All things considered, I think Wikipedia is a good thing. I'm a big fan of not having barriers to knowledge for people outside of academe. Given the open and egalitarian nature of Wikipedia, there's far more that's right with it than wrong. The downside of Wikipedia is that it takes time to craft quality articles from a neutral perspective when anyone at all can contribute to writing and editing. It will never be the Encyclopedia Britannica but it has become a great place to start a research project on the net.

I debated whether to even bother with a post about one small figure caption on Wikipedia. Then I realized that if the same figure caption had shown up in a scientific article that I had been asked to peer review for a journal, I would have no mercy on the article authors. Why? Because figure captions matter. A lot of science professionals read articles outside their discipline by skimming in the following manner: first one reads the abstract followed by the figures and figure captions. Depending on the ego and nastiness of any given scientist, some would include a third step which would be to check the references to see if one had been cited. After all, it really is a publish and perish world out there and citations matter.

Basically, figure captions matter. When you consider that journalists and bloggers often lift figures out of journal articles and reprint them in internet or newspaper content, then figure captions matter a whole lot more than one would think. So in this context, I decided that, yes, I would indeed pick on just one short figure caption in Wikipedia.

Earlier today, I was reading a string of comments on Facebook about a murderer and his victims. Someone made a comment speculating that the murderer could have poisoned one of his victims with atrazine. This immediately hit my HUH? filter big time and left me wondering how much atrazine comprised a lethal dose for an adult human.

These days, I tend to look at Wikipedia first for regulatory, physical chemistry and toxicology information since many chemical pages on Wikipedia often include that info. If the Wikipedia page is any good, there will be a link back to a public health, industrial hygene, health physics or envirnomental science authority or journal where cited numbers can be verified. For the record, unless I already know a number off the top of my head (for example, I know most of the EPA MCLs for heavy metals by heart), I almost always verify numbers, especially if I'm going to be commenting or blogging about it later. Just as a quick FYI, the CDC is even better than the EPA if you want to look up understandable environmental and toxicological info about pollutants.

Getting back to our main topic here, which is a figure caption on the English-language Wikipedia site for atrazine, I found the comment from Facebook rather odd since herbicides are not popular or widely used poisons for homicides. As I suspected after looking at the toxicology numbers for atrazine, the amount needed to poison someone would be several tablespoons. Nope, atrazine would make a lousy homicide poison on the basis of quantity required. I suspect it would also taste bad too. Arsenic and strychnine are in no danger of being displaced as effective human poisons by atrazine. I'm sure that's a great relief to know! You can sleep better tonight knowing that evil atrazine from the blue earth corn fields of Minnesota will not waylay you and bring you to death's door before you wake.

Of course, atrazine has its own little anti-fan club because of its use in American farming, for cereal crops and especially maize, the iconic crop of the Midwest. Like all other things that farmers put on their crops in liquid form, atrazine has infiltrated into drinking water aquifers wherever farming is big. If you believe that atrazine is a danger to public health or the environment, then this is a matter of concern.

Regardless of the real or imagined danger posed by atrazine, having good facts at hand on its spread, prevalence and impact is necessary for meaningful debate. For the people out there who go to Wikipedia - and no farther - for their information, getting the facts right on the page for Atrazine strikes me as highly desirable. Now there are a few things that could use some fixing on this wiki page, but the one and only figure caught my eye immediately. Here's what it looks like, straight off my monitor screen: atrazine2.png

Did you spot the caption below the figure? "Atrazine use in pounds per square mile by county."

I made the mistake of really getting eye tracks all over this figure BEFORE blowing it up for finer inspection. Right off the bat, I thought all that green-level use of atrazine in New England was off-base. Seriously, New England - the home of rocky ground and non-existent top soil - was using that much atrazine? You don't use atrazine if you're farming apples, potatoes, maple syrup, trees or cows - which are all the main aggie products in the New England states. Now look at California and southern Idaho - especially southern Idaho where one of the biggest crops is barley. I would have thought the atrazine use in these area would be much higher than on the figure.

So I enlarged the figure: atrazine.png

I just love how the highest usage area overlaps the Midwest corn belt. Check out the non-linear scale too. There's all sorts of fun on this figure.

The enlarged figure did two things for me. First, I could actually read the text inside the figure box. I couldn't before because I've reached that point of middle age where I should really be wearing reading glasses and I'm too vain to enlarge the type size like an old person. After enlarging the figure, I could read the rest of the text on the figure and saw that the original caption was "Average annual use of active ingredient (pounds per square mile of agricultural land in county)."

Wow! That's a big difference. Use per square mile of farm land in a county is a lot different than use per mile of all land in a county! This figure would never convey how much bulk atrazine was being spread around on a per area basis. It only tells you how likely it is that farms will use atrazine on a county by county basis, regardless of how much farm land is in any given county.

The bottom line is that the Wikipedia caption that's big enough for an old person like me to read is misleading. As soon as I can figure out how to send in edits to Wikipedia, I'll try to fix this caption.

The second thing that enlarging the figure did for me was confuse me terribly. If the figure is showing me usage BY COUNTY, then I should be able to discern county shapes in the data but I should not be able to pick up details smaller than counties. The problem here is that there are features in the data that are obviously smaller than whole counties.

For starters, you can pick out pieces of interstates, like I-80 west of Chicago and the I-39 corridor in northern Illinois. You can see the Platte River in eastern and central Nebraska. You can see Columbus, Indianapolis, Peoria, and Cleveland but not Toledo or Des Moines. Cities and rivers are at scales finer than counties. A figure that's captioned as presenting data on a "by county" basis is mislabeled if you're seeing details smaller than counties.

The explanation turns out that the figure really isn't on a per county basis in a weird sort of way but you have to go to the source of the data to find that out. The source of the figure turns out to be respectable and reputable. The data and the figure both are from a very recent USGS report on pesticide usage in the USA. The complete citation is: Thelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States, 1992–2009: U.S. Geological Survey Scientific Investigations Report 2013-5009. You can also find it online at (accessed 18 Sept 2013). The authors of this USGS report did something kinda strange with their data and I'm left wondering why they bothered since it strikes me as somewhat counter-intuitive. Here's their explanation from the USGS webpage that explains how they made the pesticide usage maps in their report:

Individual crop types....were reclassified to simply differentiate agricultural land (including pasture and hay) from non-agricultural land....then generalized to one square kilometer cell size and the percentage of agricultural land for each cell was calculated. The proportion of county agricultural land included in each one square kilometer cell was multiplied by the total county use for each pesticide to calculate the proportional amount of use allocated to each cell. To display pesticide use on the annual maps for each compound, all of the cell values nationwide for the entire period were divided into quintiles and a color-coded map was generated for each year; the quintile classes were converted to pounds per square mile.


You follow all of that? They proportioned out the farm land in each county by one kilometer cells, allocated to each cell the amount of pesticide known for the county multiplied by the proportion of farmland in the cell, and then rebinned it all to present it on one national map in units of pounds of pesticide used on a per square mile basis. At the scale of the entire country, this conversion from kilometers to miles is a monstrous amount of work which would not change the level of detail one could see on the maps in their report. For their purpose, the conversion step was essentially superfluous!

One last thing. If you sit down and actually read this USGS report, you'll discover that the usage numbers for almost all the pesticide and herbicide data broken out by county is estimated based on statewide data.

My brain hurts.

Saturday 27 April 2013

ARG! More Keystone Pipeline Misreporting!


Well, the New York Times (NYT) did it again. They have asserted that a source says something it actually did not say when you go and look at the original documents being discussed. Sadly, the uber-topic is the Keystone XL Pipeline...again. I'm beginning to doubt that anyone at the NYT can appoach this subject objectively. The original NYT editorial can be found here:

The editorial is a commentary on the EPA's review of the US State Department Environmental Impact Statement (DSEIS). A copy of the letter can be seen here:

There are multiple distortions and demonstrable misstatements in the editorial about the EPA letter, but for the sake of not excessively beating the dead horse subject of the NYT objections to this pipeline, I will restrict myself to just one of the more blatant examples of spin.

The editorial states:

(The State Department's) biggest problem, the (EPA) agency said, is a flawed assumption that distorts all of its analyses: that “oil sands crude will find a way to market with or without” the Keystone pipeline. This is a kind of magical thinking. If this pipeline won’t do, the State Department argues, other pipelines will be built or rail traffic will be ramped up. One way or another, the department says, oil sands production will go ahead full speed. For a variety of reasons, not least the cost of rail transportation, the E.P.A. has serious doubts.

That's not really what the EPA letter said. The EPA did not say the DSEIS assumption concerning the inevitability of Alberta oil sands development was flawed. Rather, the EPA argued that the DSEIS conclusion was based on incomplete economic modeling and rigor. To wit:

Although the DSEIS describes the GHG (green house gas) intensity of oil sands crude, the DSEIS nevertheless concludes that regardless of whether the Project permit is approved, projected oil sands production will remain substantially unchanged. This conclusion is based on an analysis of crude oil markets and projections of oil sands crude development, including the potential for other means of transport to bring oil sands crude to market.

The EPA went on to say:

Because the market analysis is so central to this key conclusion, we think it is important that it be as complete and accurate as possible. We note that the discussion in the DSEIS regarding energy markets, while informative, is not based on an updated energy-economic modeling effort.

Nowhere did the EPA label the DSEIS conclusion as an "assumption" nor did the EPA ever state that it doubted the State Deparment's argument or call it "flawed." What the EPA did say was that the economic analysis lacked sufficient rigor and details to support the statement the Albertan oil sands would be developed no matter what means of shipment were available.

The EPA uses its own two-part ranking system to evaluate environmental impact statements. The first part deals with its own conclusion about the environmental risks and hazards of a project. The second part deals with the reasoning behind its evaluation. The hazards and risks are rated as "lack of objections", "environmental concerns", "environmental objections", and "environmentally unsatisfactory." The reasoning is described as "adequate", "insufficient information", and "inadequate."

The EPA gave the DSEIS a rating of "Environmental Objections - Insufficient Information." In other words, the EPA has objections to the DSEIS because it did not have enough information in areas of environmental concern. The economic modeling was a chief concern because the State Department's most important arguement for the pipeline was the inevitability of Albertan oil sands development. The EPA objected and aksed for more modeling and market analysis.

Contrary to the NYT, The EPA letter did not say that the State Department:

"gave short shrift to the corrosive effect of the oil and its dangers to the vital aquifer underlying part of the pipeline’s latest route."

I have no idea where the term "corrosive" came from. It's not used at all in the EPA evaluation letter. Granted, the EPA had two other major objections to the DSEIS, both on the grounds of insufficient information on environmental, not economic, concerns. The first deals with the oils sands product that is pumped in a pipeline, called dilbit. Dilbit is a relatively new form of pipeline product and the growing experience around the world with dilbit spills has shown that it is harder to remediate compared to regular crude. Because dilbit spills are more difficult to deal with, especially in surface waters, the EPA wanted to see a spill prevention and remediation plan in or with DSEIS based on the unique characteristics of dilbit. The other objection dealt with the lack of any discussion of possible alternative routes for the pipeline which could potentially minimize the exposure of the North Great Plains aquifers and rivers to potential pipeline spills. Again, as in the case of the economic modeling, the EPA asked that alternative routes be addressed. Nowhere in the letter did the EPA call the DSEIS flawed or faulty or incorrect. The EPA charged that the DSEIS was incomplete and expressed willingness to work with the State Department in filling in the information it wanted to see.

While I understand the reasoning behind the EPA request for rigorous economic modeling of the impact of transportation mode and availability on oil sands development, one could argue alternatively that it's unnecessary and moot. The reason is very simple supply and demand. The population-driven demand for fuels is increasing and the supply of fuels is finite. The supply of cheap fossil fuels is in demonstrable decline which is why we are now seeing the expansion into difficult fuels to extract like shale-based natural gas and oil sands. The pursuit of expensive fuels wouldn't be happening if the cheap fuels weren't already gone. Until and unless cleaner forms of energy become economically viable and/or politically acceptable, fossil fuels like oil sands will be developed. It's a matter of when, not if. So in that respect, the EPA demand for economic modeling is moot, especially in the long term.

There is one other thing that the EPA showed no sensitivity to or awareness of regarding the development of the Alberta oil sands. Those are not our oil sands. They're Canada's oil sands, and it is up to the people, government and businesses in Canada as to whether those oil sands are exploited. If the Canadians decide that the oils sands will be exploited, then they'll be exploited regardless of what the EPA and New York Times think.