At Bad Astronomy, Phil Plait says President Obama’s proposed new plan for slowing down atmospheric carbon dioxide by reducing coal use for generating electricity is huge.
But is it huge? As a mind set, a psychological Rubicon, an opening wedge for more government action on greenhouse gases and climate change, maybe. But in terms of practical impact on greenhouse gases, not so much. Here’s why.
The aim is to cut carbon-dioxide emissions from the nation’s power plants as much as 30 percent below 2005 levels by 2030. Brad Plumer summarizes and explains the proposals at Vox–and he points out that the goal is not really as ambitious as you might think.
That’s because natural gas has gotten so cheap, and the Great Recession has reduced power use so much, that power-plant emissions plunged by 15 percent between 2005 and 2013. So they are already halfway to the 2030 goal. They achieved the first half of emissions reduction in well under ten years, and now they have more than 15 years to get the rest of the way. Dot Earth’s Andrew Revkin parsed the proposed rules and assembled several comments on why they aren’t enough.
Plumer followed up his first Vox post with a summary of how the EPA’s new rules would work. A central feature is that there are different emissions goals for each of the 49 states that have coal-fired power plants. That’s going to be fun.
At Watts Up With That, Anthony Watts has turned his skeptical platform over to Patrick Michaels, the high-profile climatologist/climate-change skeptic. Michaels points out, correctly, that there is no chance this new policy will have any detectable effect on global temperature. Thus he agrees with climate-change activists that the policy does not go nearly far enough. He also says the only way the 30 percent reduction can be achieved is by “upgrading almost all combustion units, and the ultimate cost of the upgrades will make coal noncompetitive with much-less-expensive natural gas–fired facilities.”
Um, I think that’s the whole point.
The death of Big Coal is greatly exaggerated
In his two-part roundup of media coverage of the announcement, Knight Science Journalism Tracker Charlie Petit forecasts that “Big Coal in the US may be looking death in the face. It is unleashing its armies.” In a second post, Petit praises Paul Barrett’s BloombergBusinessweek analysis of what Barrett calls the phony war on the Obama plan and also partly takes back his forecast of Big Coal’s demise. Turns out that when we reach that coal reduction apotheosis in 2030, coal will still be generating 30% of US electricity. Last year it was 39%.
David Wogan, in a post last fall at SciAm’s Plugged In, argued that EPA rules are not really a War on Coal. Structural and market forces have been attacking coal’s position for some time, so it’s likely that coal will bite the dust eventually anyway, even if the process takes several decades. Natural gas is beating it to death, and nearly all coal-fired power plants are elderly and near-moribund anyway.
Follow the money
Chris Mooney explains at Grist why Republican claims that the new climate rules will wreck the economy are wrong. The US Chamber of Commerce has also issued a report inveighing against what it claims are the enormous costs of the new EPA coal regulations.
But at his blog Conscience of a Liberal, economist Paul Krugman took a look at their data and found–somewhat to his own surprise, it sounds like–that even the Chamber’s own estimate of $50 billion would amount to only 0.2 percent of GDP. The Nobel Prize-winning economist’s academic technical analysis:”That’s cheap!”
If there is a War on Coal, Jonathan Weisman says at the New York Times, it’s going to be like the War on Tobacco in the 1990s. It will feature buyouts and compensation for the most-affected states. But Weisman quotes Republican economist Doug Holtz-Eakin arguing that the analogy is less than perfect. “In the end, smoking became unacceptable. That was not a legal statement. It was a social statement, and consensus was broad and has held for a long time,” Mr. Holtz-Eakin said. “Maybe you get there on carbon emissions, but right now, this is an issue for the elites.”
Those compensation programs can be extraordinarily effective. I was living in southern Maryland, at that point a tobacco-growing region, when in the 1990s Maryland launched a program to compensate farmers into giving up tobacco and moving to other crops. The huge leafy plants disappeared from my neighbors’ fields almost overnight, and the ubiquitous tobacco barns fell into picturesque decay with startling suddenness.
Where the campaign to reduce coal is analogous to the tobacco buyout is that, like tobacco, coal has serious health effects. And EPA is exploiting that fact in arguing for its program. In his post, Revkin pointed out that the EPA’s new rhetorical approach–talking about carbon pollution rather than carbon dioxide or greenhouse gas emissions–signals that the agency plans to emphasize the immediate health benefits of using less coal.
At the Washington Post‘s new To Your Health blog, Lenny Bernstein describes some of these benefits. The American Lung Association says the plan would ”prevent up to 4,000 premature deaths and 100,000 asthma attacks” just in its first year. This because power plant emissions contain sulfur dioxide, nitrogen oxide and mercury. All contribute to lung disease, heart attacks and asthma. There will also be lung benefits from a reduction in tiny particles of soot, which clog lungs.
Hericanes and Himicanes
Kind of fascinating, how much statistician ire has been provoked by that PNAS paper claiming that female-named hurricanes have killed more people than male-named ones. The supposed reason being that people in their paths have taken male hurricanes more seriously and gotten out of the way
The statisticians are not objecting to the premise that people respond unconsciously to the relative power implied by male and female names. That seems to strike most of the bloggers as not implausible. But the data and the methodology have statistics-minded commentators jumping up and down with rage. I haven’t seen a single defense, so I conclude that the paper is at best problematic.
For example, the researchers studied hurricane aftermaths from 1950 on, despite the fact that hurricanes all had female names until 1979. You don’t have to be a statistician to find that . . . odd. At The Monkey Cage, statistician Andrew Gelman agrees that including pre-1979 data makes no sense.
The hypothesis might be true, he says, but he doesn’t think the male/female thing is the most important feature of hurricane names. He wonders if it would be more sensible to compare the power implied by some names over others, Omar vs. Irving, for instance. Or whether it’s a good idea to name hurricanes at all, since perhaps names make them seem more cuddly.
A post at the Guardian by evolutionary biologist Grrlscientist and biostatistician Bob O’Hara concludes, “When we compare the data to the model itself, the ‘femininity effect’ of hurricane names completely disappears.” (This post raised a side question for me. Sandy, the megastorm of recent memory that was officially a hurricane for only a part of the time it spent slapping New York and New Jersey around, is classified as female. But Sandy is also a man’s name. Surely the single-sex classification can’t be kosher?)
Gelman refers us to an analysis by the mathematically minded sociologist Jeremy Freese at Scatterplot. Freese has problems with the model too, calling the effect sizes it implies “astonishing.” The paper’s own example claims “that if a hurricane named Eloise killed 42 people, the same hurricane named Charley would be predicted to only kill 15.” In other words, most of the deaths could be prevented if only the hurricane had a masculine name.
Freese considers the actual hurricane Andrew, which was severe in terms of damage but killed only 62 people. The paper’s model fits Andrew well, predicting 59 deaths. But, says Freese, “if the hurricane had been named Diana instead, the model predicts over 25,000 people would have died.” This implies “that tens of thousands of Floridians owe their lives to the fact that Andrew was not preceded by another storm that season, because then what we know as Hurricane Andrew would have been called Hurricane Bonnie.” The dramatically different fatality estimate for Diana (or Bonnie) doesn’t seem likely, does it?
What we have here is another failure of science communication
Freese is also trenchant on the topic of how scientific studies are relayed to the public. I will quote him at length because he is identifying an increasing problem: hype for a piece of research where the hype emanates not originally from journalists (although they are usually blamed for it), but from the authors of a paper and their research institutions.
Just last week I described such a case here, involving a paper on the microbial inhabitants of the human placenta. The first author gave interviews in which she implied that the paper showed a connection between gum disease and unhealthy pregnancy, especially premature delivery. The paper did not show that, but top-flight science journalists nonetheless relayed her declarations. I discussed this paper and the media clamor surrounding it in a column last week at the Genetic Literacy Project.
In the case of the gendered hurricane naming, Freese points out (and the emphases are his): “The authors’ university issued a press release with a dramatic presentation of results. The release includes quotes from authors and a photo, as well as a quote from a prominent social psychologist calling the study ‘proof positive.’ So this isn’t something that the media just stumbled across and made viral.”
Freese goes on: “I have become especially impatient by the two-step in which a breathless set of claims about findings is provided in a press release, but then the authors backtrack when talking to other scientists about how of course this is just one study and of course more work needs to be done. In particular, I have lost patience with the idea the media are to blame for extreme presentations of scientists’ work, when extreme presentations of the scientists’ work are distributed to the media by the scientists’ employers.”
I rest my case.
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