Random Thoughts

Wind penetration in the midwest

 

The scientific consensus on beta blockers for heart failure prior to 1973

This post contains an email exchange I had with a medical scientist, in an attempt to resolve a debate about whether there was a "scientific consensus" prior to 1973 that beta blockers were contraindicated for heart failure. (There most certainly was!)

The medical scientist is Dr. Christian Funck-Brentano, author of Beta-blockade in CHF: from contraindication to indication: I wrote to Dr. Funck-Brentano:

Dear Dr. Funck-Brentano:

Would you say there was a scientific consensus that beta blockers were contraindicated for heart failure prior to 1973? If you think there was a scientific consensus prior to 1973 that beta blockers were contraindicated for heart failure, what was the scientific basis for that consensus?

With many thanks and deepest respect,
Mark Bahner

P.S. Is it all right if I share your reply with some people with whom I'm discussing the matter?

Dr. Funck-Brentano responded:

Dear Sir,

I cannot tell you exactly the date beta-blockers were officially contraindicated in patients with heart failure but, clearly, there was a scientific consensus that this was the case until the CIBIS II and MERIT-HF trials were published in 1999. Beta-blockers are negative inotropes (they decrease myocardial contractility) and their use in heart failure was justified by the deleterious effects of sympathetic activation in patients with heart failure. Only, they need to be slowly up-titrated.

Official indication followed the publications of these two landmark clinical trials, I think in 2000. Before CIBIS II and MERIT-HH were completed, Dr Karl Swedberg had reported individual cases and under-powered studies suggesting the benefit of beta-blockers in heart failure.

I attach an article I published on this history of moving from contraindication to indication. You are welcome to share this article as long as you comply with copyrights issues.

Best regards
Christian Funck-Brentano M.D., Ph.D., FESC
Professor of Medicine and Pharmacology
Sorbonne University - School of Medicine
Department of Pharmacology
Clinical Investigation Center Paris-Est
Hôpitaux Universitaires Pitié-Salpêtrière - Charles-Foix
47-83 Boulevard de l'Hôpital
75013 - Paris
FRANCE

I followed up with:

Dear Dr. Funck-Bretano,

Many thanks for your detailed response. Unfortunately, I have no medical degree or experience in medical research, so I want to make sure I'm not misunderstanding your reply.

I think you are saying that there was a scientific consensus that beta-blockers were contraindicated for heart failure all way up to 1999.

So am I correct in assuming that the scientific consensus would be even stronger--essentially 100 percent--that beta blockers were contraindicated for heart failure prior to 1973?

And the scientific consensus that they were contraindicated for heart failure would be due to their negative inotropic properties (and the adverse results reported in 1966, as described in the Introduction in your paper)?

Thank you so much,
Mark

Dr. Funck-Brentano replied:

Right

Christian Funck-Brentano
(Sent from a Smartphone with highly imperfect spell checking. Excuse my brevity)

        

EIA AEO 2019 projections versus MAB (yours truly)

The Energy Information Administration has a long and sorry history of underestimating the growth of renewable energy in the U.S. I think their AEO (Annual Energy Outlook) in 2019 is no different. On a somewhat-related note, the folks at the Watts Up With That website seem to be hung up on the fantasy that coal-fired electric power will remain at the levels projected by the EIA. They also dream of a nuclear power revival in the U.S...or even that nuclear power won't fade to nearly nothing in the U.S. in the next 3 decades. (Don't get me wrong...I like to dream about liquid fluoride thorium reactors myself...but I know it's a dream at least for the next 2-3 decades.)

Here is a table that contains energy consumption in quads (quadrillion Btu) in the U.S. in 2017, and then projected for 2030, 2040, 2050, and 2070. There are values from the the EIA AEO 2019, and values from me (MAB).

There are many significant differences between the EIA projections and mine. Here's a list, in rough order of importance:

1)  I think the EIA once again blows their "Other Renewable Energy" projections, big-time. They have Other Renewable Energy (i.e. photovoltaics and wind) only increasing from 3 quads to 9 quads from 2017 to 2050. My projection is 3 quads to 42 quads from 2017 to 2050. In particular, I predict an explosion in photovoltaic electricity production. 

2)  The EIA only has coal dropping from 14 quads in 2017 to 11 quads in 2050. I predict coal will be at 2 quads in 2050. I expect more than 90 percent of the utility coal-fired power plants that were operating in 2017 to be closed by 2050.

3)  The EIA has nuclear power only dropping from 8 quads in 2017 to 7 quads in 2050. Presumably they expect virtually all the nuclear plants operating in the U.S. in 2017 to still be operating in 2050. I think that's insane. Many of those plants would be over 70 years old!

4)   The EIA predicts virtually no drop in oil consumption from 2017 to 2050. I predict a drop of 36 percent, as the transportation system becomes electrified (with battery operated cars, buses, and many trucks). 

Who's in "Fantasy Land"?

The "Watts Up With That?" website has a review of the Energy Information Administration's (EIA's) 2018 Annual Energy Outlook (AEO 2018) by David Middleton. Mr. Middleton thinks AEO 2018 "rocks." He very impressed that "Coal Keeps on Chugging Away" (see his graph with that title, below). The EIA AEO 2018 predicts that coal-fired power plant capacity ("summer capacity, per Mr. Middleton) will drop from about 274 in 2015 to about 218 GW in 2026, but then will remain almost perfectly flat until 2050. 

Graph per David Middleton, based on EIA AEO 2018.

Why does the EIA think that coal-fired power plant capacity will hold constant from 2026 to 2050? I'm not sure, because coal-fired power plants aren't getting any younger, and many of them are in serious economic danger even in 2018, which will be a brutal year for coal-fired power plants.

Per Mr. Middleton, the AEO 2018 also has on page 86, that, "The Reference case projects a steady decline in nuclear electric generating capacity—from 99 gigawatts (GW) in 2017 to 79 GW in 2050 (a 20% decline)—with no new plant additions beyond 2020."

According to the EIA in August 2017, there were 99 nuclear reactors in the U.S. So that's 99 reactors, with a capacity of approximately 99 GW, or approximately 1 GW per reactor. It appears that their initial commercial operation dates break down as follows:

Initial Commercial Operation	Number of Plants
1965-1970	5
1971-1975	32
1976-1980	14
1981-1985	20
1986-1990	25
Post 1990	3

From looking at the table, it can be seen that all but 3 reactors will have been in commercial operation for more than 60 years in 2050, if they are still operating in 2050. And a total of 51 of them started commercial operation before 1980, so they will have been in commercial operation for more than 70 years if they're still operating in 2050. What is the probability that 79 GW of the existing fleet of nuclear reactors (i.e. approximately 79 reactors, at 1 GW per reactor) will still be operating in 2050? I say the answer is that the probability is much less than 50 percent.

Finally, David Middleton noted that, "About 45% of the current natural gas capacity consists of peakers, ~202 GW."

He provided an Excel spreadsheet which purportedly had an EIA list of the power plants expected to retire by 2047:  EIA Table 6-6, Released January 24, 2018

I didn't see many natural gas "peaker" plants (either natural gas combustion turbines or natural gas steam turbines) in the list. So I made the following predictions:

1) Many nuclear units are going to retire in the 2026-2047 time frame.

2) Many coal units are going to retire in the 2026-2047 time frame.

3) Many…and possibly *all*–natural gas peaking plants will retire between now and 2047. (Natural gas peaker plants will be replaced by batteries. It’s a question of when, not if.)

David Middleton's response:

"Maybe in Fantasy Land."

So who's in "Fantasy Land"? Is it me, or is it the EIA in their AEO 2018? I'll be providing the reasoning behind my statements in subsequent posts. 

Counterfactual debate: If Congress had not declared war in WW II

David Nieporent has made the amazing claim that, if Congress had voted not to declare war against Japan in World War II, the U.S. still would have been at war with Japan. This boggles my mind. I don't see what the purpose of the Founders writing into the Constitution that only Congress had the power to declare war, if even if Congress blatantly refused to declare war, we would still be at war.

 

This is an invitation to Mr. Nieporent to comment on why he thinks that the U.S. can be at war even if Congress explicitly refuses to declare war.

GDPs with and without climate change

Ed Dolan posted at the Niskanen Center blog on the question of what GDPs would be in 2099 with and without climate change. His graph of GDPs "with" climate change was based on the work of Burke et al. (Nature, 2015), and data published on their website. However, the data published on their website was based on the SSP5 scenario, which is similar to the RCP 8.5 scenario, which has extremely unrealistic (incredibly high) projections of coal usage in the 21st century. Anyway, Ed Dolan's figure looked like the one I recreated below (Ed Dolan's figure appears as an insert in the top-right of my graph).

 

The question is, what would the graph look like for a more realistic scenario, like RCP 4.5? To find out, I performed the following analysis:

1) I obtained the global average temperature increase for the RCP 8.5 scenario and the RCP 4.5 scenario from wonderful Wikipedia. The mean temperature increase is 3.7 degrees Celsius for RCP 8.5 and 1.8 degrees Celsius for RCP 4.5. So the increase in temperature is about half as much for RCP 4.5 as for RCP 8.5. The response of GDP to temperature, from the Burke et al. analysis, indicates an inverted "U" shape, peaking at about 15 degrees Celsius, and sloping away more and more quickly farther from the peak. I therefore assumed that a temperature change of half as much for RCP 4.5 versus RCP 8.5 would have about one-quarter of the effect on GDP for each country as the RCP 8.5 (/SSP5) scenario. The resultant graph looks like this (once again, the original Ed Dolan graph is in the top-right):

I welcome any more-refined analysis based on the work of Burke et al. (Nature, 2015). However, I think my analysis is probably pretty close to what they'd get. Unsurprisingly there is much less effect on GDPs for a global average temperature increase of 1.8 degrees Celsius than a global average temperature increase of 3.7 degrees Celsius.

JULY 27TH UPDATE

I realized I made errors in how I should translate the idea that half the temperature change results in one-quarter of the effect. Here is my new graph for what the GDPs would look like without and with climate change of the magnitude in the RCP 4.5 scenario.

 JULY 28TH UPDATE

I realized I was still making errors in my July 27th analysis and that the "one-quarter effect for one-half temperature change" rule was a bit crude. So I did a more sophisticated analysis. If anyone is interested in the details, contact me. Here are the results of the more sophisticated analysis:

 

 

Here's a table for some selected countries, spanning varying initial temperatures, initial GDPs, and growth rates without climate change.

The "money" columns here are the "Ratio 2099/2010 without CC (climate change)" and the column that shows the ratio of 2099/2010 GDPs for the RCP 4.5 scenario (as calculated by me, based on "more sophisticated analysis." For example, for the United Arab Emirates (one of the hottest countries in the world, and already rich) the ratio of GDP in 2099 to GDP in 2010 is 4.6 without climate change, and 0.3 with climate change at the RCP 8.5 level (both per Burke et al. in Nature 2015). My calculated ratio with climate change at the RCP 4.5 ratio is 2.6. In contrast, for the Russian Federation (a cold relatively poor country) the ratio is 10 without climate change, 50 with climate change at the RCP 8.5 level, and 32 with climate change at the RCP 4.5 level.

Overall, according to my analysis, climate change at the RCP 4.5 level has very little effect on GDPs when compared to no climate change (see the figure directly above).

Mark Bahner vs Wigley and Raper (Science 2001) vs IPCC RCPs

These are comparisons of cumulative global industrial CO2 emissions in the 21st century from three sources:

1) A Wigley and Raper paper in Science in 2001,

2) My response to the Wigley and Raper paper, with my (much better) predictions, published on my blog in 2006, and

3) The IPCC Representative Concentration Pathway (RCP) scenarios, including the "business as usual (see page 43)" RCP 8.5 scenario.

The meaning of the "5%", "50%", and "95%" designations is that there is a 5% chance, a 50% chance, and a 95% chance that the cumulative emissions in the 21st century will be less than the values given.

My 50% probability value was 712 GtC. The Wigley and Raper 50% probability value is 1385 GtC, and the RCP 8.5 "business as usual" is 1932 GtC. Current emissions are about 10GtC per year. If they plateau at this value for the next 10 years, then fall linearly to zero emissions in 2100, the total emissions for this century will be about 600 GtC...very close to my 712 GtC value, and miles away from the Wigley and Raper 1385 GtC value and the RCP 8.5 "business as usual value" of 1932 GtC.

In other words, I'm basically right, and they are way, way wrong. No surprise there. 

P.S. What is surprising to me is that the Wigley and Raper paper was published in Science magazine, and it predicts that there is less than 1 in 20 chance (i.e., a 5% probability) that emissions in the 21st century will be more than 713 GtC. Why was this obviously wrong analysis never corrected? Isn't Science interested in...I don't know...science? Perhaps even more surprising is how in 2009 the RCP 8.5 scenario, with emissions of 1932 GtC, was labeled as "business as usual" and the so-called "scientific community" has never corrected that obvious nonsense.

Recalculating Worldwide Computing Power

 I previously speculated on why economic growth in the 21st century will be spectacular..My calculations then were based on sales of personal computers and the expected power of each personal computer. It wasn't a very sophisticated analysis, so I was happy to recently learn of this great paper that estimates the total power of graphical processing units (and central processing units) in the world.

That paper calculated the total processing power of all GPUs in 2007 to be 6.4 x 10^18 instructions per second, and that the rate was increasing by 86 percent per year. I translated that into human brain equivalents (HBEs) by assuming that one HBE was equal to 20 quadrillion instructions per second (20 petaflops, or 20,000 teraflops) or 100 trillion instructions per second (0.1 petaflops, or 100 teraflops). The value of 20 petaflops comes from Ray Kurzweil's work, will the value of 100 teraflops was proposed by Hans Moravec.

Anyway, the graph below has two straight lines for those two cases, and one curved line, which represents the results of my earlier calculations. The bottom line is that the curved line representing my earlier calculation is very, very close to the result from the paper, assuming that one HBE is equal to 20 petaflops (20 quadrillion instructions per second). Another bottom line is that we're talking about some pretty stunning numbers very soon. For example, by 2025, the number of HBEs from computers (even using the 20 petaflops value) is approximately 1 billion. And 

A bet offer to Anders (of "ATTP")

I was having a discussion with Anders of the blog And Then There's Physics. He claims that the statement "that future anthropogenic emissions would need to be eliminated in order to stabilize global-mean temperatures" is true.

I'm challenging him to put his money where his mouth is. I bet him the equivalent of 30 U.S. dollars that I can honestly answer the following multiple choice question, and he cannot:

Which of the following statements must be true, in order for global temperatures to be stabilized:

1) Anthropogenic emissions must be eliminated.
2) If anthropogenic emissions are not eliminated, then we must somehow remove as much CO2 from the atmosphere, and sequester it somewhere, as we’re emitting into the atmosphere.
3) Both of the above.

My honest answer to this question is "#2."

If Anders can honestly answer this multiple choice question, I will give him $30.

Jobs vulnerable to artificial intelligence, part 2

I previously posted on the jobs that I think are most vulnerable to artificial intelligence (computers, robots). Here's a table with the number of workers (in millions) in each of the top 15 job categories in 2012, and my predictions for what the employment will be in each of those categories in 2024, 2034, and 2044. I think the two jobs most vulnerable to artificial intelligence are cashiers and truck drivers; I expect about a 90% reduction in their numbers from 2012 to 2044. Other jobs I see as particularly vulnerable are bookkeepers/accountants and material movers (e.g. loading dock workers). But I don't see even one of the top 15 job categories in 2012 as gaining workers by 2044. And overall, I expect about a 50%(!) drop in the number of people in the U.S. employed in the top jobs of 2012 by the year 2044.

Robin Hanson recently had a blog post with the title, "This time isn't different"...relating how previous predictions of job losses due to computers and other machines didn't come to pass. I beg to differ. I think this time most certainly is different. That's because this time we're talking about computers/robots very shortly (in the next 1-2 decades) generally equaling then surpassing the capabilities of a human brain and body.  

Popularity, 2012	Job	Employment relative to 2012 (i.e., 2012 = 1.0)					Percent Change, 2012 - 2044
		2012	2024	2034	2044
1	Retail   Salespeople	1	0.95	0.48	0.29		-71
2	Cashiers	1	0.88	0.53	0.12		-88
3	Office   Clerks	1	0.93	0.71	0.50		-50
4	Fast   food prep and service	1	1.04	0.89	0.59		-41
5	RNs	1	1.00	1.00	0.88		-12
6	Waiters/waitresses	1	1.04	0.78	0.52		-48
7	Customer   Reps	1	1.05	1.00	0.91		-9
8	Material   movers (e.g., loading docks)	1	1.00	0.62	0.14		-86
9	Janitors	1	1.05	0.57	0.19		-81
10	Stock   clerk, order filler	1	1.16	1.26	0.84		-16
11	Secretaries	1	1.06	0.94	0.83		-17
12	Bookkeeping,   accounting	1	1.00	0.56	0.22		-78
13	General   managers	1	1.00	0.94	0.88		-12
14	Tractor   trailer truck drivers	1	1.06	0.56	0.06		-94
15	Elementary   school teachers	1	1.00	0.87	0.53		-47
Totals	Top 15 jobs in   2012	1	1.00	0.76	0.48		-52

Postscript (11/10/15): I should have made it clear that all of these predictions are population-weighted. For example, I have employment in 2044, relative to 2012, for all top 15 jobs, as 0.48 (i.e., a 52% reduction in the number of total jobs in all 15 sectors). But that's a population-weighted number. For example, suppose the total U.S. population increases by 20 percent from 2012 to 2044. Therefore, a population-weighted value of 0.48 would actually look like 1.2 x 0.48 = 0.58. So if the population increases by 20 percent, the absolutely number of jobs would be 0.58 times the 2012 value, rather than 0.48 times the 2012 value. Of course, if the population didn't change at all from 2012 to 2044, the 0.48 value would be appropriate to calculate the total number of jobs relative to 2012.