Consumer green energy default choice is sticky

“Non-monetary incentives that encourage pro-environmental behaviour can contribute to combating climate change. Here, we investigated the effect of green energy defaults in the household and business sectors. In two large-scale field studies in Switzerland of over 200,000 households and 8,000 enterprises, we found that presenting renewable energy to existing customers as the standard option led to around 80% of the household and business sector customers staying with the green default, and the effects were largely stable over a time span of at least four years. Electricity consumption had only a weak effect on default acceptance. Our data do not indicate moral licensing: accepting the green default did not lead to a disproportionate increase in electricity consumption. Compared with men, women in both the household and business sectors were slightly more likely to accept the green default. Overall, non-monetary incentives can be highly effective in both the household and business sectors.” in nature human behvaiour.

What should UK innovation, ARIA, look at

Weird manifesto for UK ARPA or ARIA

My ideas:

-Progress Studies (including social progress and creativity)

-Basic Climate research

-How creativity happens

-Productivity schedules (sleep, diet, schedules)

-Educational Mastery

-Building Speed (how to do big projects fast[er])

-Healthcare speed, innovation, public health challenge trials,


The UK is creating a £800m sciency agency based on the US ARPA* an innovation agency. The UK agency will be called ARIA, Advanced Research and Invention Agency. This idea had considerable backing from former special adviser Dominic Cummings (see his lengthy blogs on this, links end*). While it has received criticism and isn’t a novel idea in innovation circles, we have it. So let’s make the most of it.


What is ARPA?

In brief at ARPA, around 100 program managers (PMs) with ~5 year appointments create and run programs to pursue high-level visions, for instance - what would make electric planes or hydrogen heating systems.


There is much written on what makes US DARPA work with a decent focus on having brilliant PMs. Also the similarities and differences on how IARPA (intelligence focused) and ARPA-E (energy focused) have also worked. So, I won’t dwell on that. 


UK’s ARIA is likely to be given the freedom to choose what it works on. Let’s put aside the debates on ARIA and the long history of innovation policy experts here and posit what we think ARIA should work on.

I’d like to float some weird and not so weird ideas I think a UK ARIA should focus on. I have a touch of weirdness about me so that fully qualifies me (tongue in cheek).

These ideas support areas which would have large public goods benefits (and some private sector benefits) but for various incentive/time horizon problems are not well suited to private actors.

I have 3 large buckets but with some off sub-buckets.

  •  Basic Climate research

  •  Progress Studies (after Cowen & Collinson)

  •  Healthcare (life extension and quality of life extension)


Basic Climate research: Trees and Seas 

While this falls under “net zero” area, my idea under basic climate research is more foundational than eg tackling hydrogen based systems for making carbon neutral steel.


There are several areas here, where - it seems to me - we simply do not understand the state of the world and its system but we might now have the technology and research to do this.

For instance, what is the true state of our forests, jungles and trees over the globe? Data and the interpretation of that data is unclear. Where are trees disappearing, where are we planting and how is it going?


Bill Gates is dismissive of trees as a climate solution*. The UN FAO has data, visualised by World in Data*, but other attempts to assess trees are contradictory.

This is due to problems of classifying types of trees (shrubs, types of trees etc.) and the aerial data needed. And there are problems with losing old trees (especially primary rain forest) and replacement of new trees.


I am far away from the literature and no expert but I sense a programme here and maybe one specific to UK and UK peat lands, tree afforestation etc. would be very useful in basic research.  Essentially, the same argument for seas and oceans and their contribution to carbon sinks.

Basic climate research is not super weird. But I think there are big basic knowledge gaps here which could be very valuable and items like trees are not best suited to private actors.

Progress Studies

  • How innovation happens, how to make it better. Same for social and ethical progress. Also,

  • Creativity, flow, educational mastery


This is weirder although Tyler Cowen, Patrick Collinson et al is making it a lot less weird.


This would need to go beyond “Cities and innovation clusters show agglomeration affects” (known and somewhat trite, IMO, in that difficult for policy to seeming build upon) but can we drive real insights here? Small teams? Big teams? Collaboration from cross-disciplines which are neither too far, nor too close. The impacts from regulation (are the de-regulation cries correct in all respects? ). 

There will be a tendency to look at this in the hard sciences and the inventions, innovations etc. there (and there is a literature here). And I think understanding that will be useful especially eg in medical science, software and the like, but my weird question is what about social progress?

There is consensus today that slavery is bad. I think that counts as social progress. But how does that happen? What role does “culture” play?

I think society is increasingly valuing eg autistic thinking and (while there is much further to go), we have given some more rights and some more status to the spectrum of autistic thinking and other areas like this.

I think some rigorous work here would be insightful and useful. If the productivity or progress can be raised in these areas there could be strong benefits.

Running along side this, I’d be interested in rigorous work on Team and Individual productivity progress.

There could be an enormous win if robust findings could be confirmed here.

For example, Paul Graham (extremely successful in the start-up founder and investment space) has argued that maker time and manager time are very different schedules.

Essentially, maker time requires good lengths of the day devoted to the creative projects  (in my view, related to what we know about flow) whereas manager time needs shorter chunks of meeting time.

Where manager time interferes with maker time, you get a huge negative impact to maker productivity.


If this is correct and if we can guide for it, this could improve productivity and be of general benefit. Would this be progress? I think so, and of general public good. Why are there so many time management books? Tyler Cowen amongst others often asks about people’s “personal productivity function” ?  Can we actually discover anything robust here?

Let’s go one step further, we seem to have some tentative ideas about sleep and productive circadian rhythms of the day for certain people (eg night owls).

We have tentative ideas about intermittent fasting or diet and potential health benefits.

Is there any work on trying to combine these factors or ideas? 


If you current have poor productivity, but what you should do is change to a nightowl, maker schedule on an intermittent fasting schedule - could your productivity significantly increase?


And then how about combining this within teams? There is work on psychological safety*, and some thoughts as to  innovation seems to happen when teams understand each other’s work but are not too close or not too far away - but can we combine any of these possible insights?


From this can we create even more builder teams, like the Tesla’s, Stripes., etc of the world.


Perhaps it is too abstract and too difficult to do rigorously, but I think this would be a weirdly good area for UK ARPA to examine.

As extension, I’d look in to how we foster creativity. Specifically, I’d be interested in extending the work around “flow” and any rigorous study on the structure of “story” or “narratives”. And also an examination of forms of “educational mastery” 


Flow

Why flow? There is some suggestion that flow can significantly increase creative productivity (although there might be downsides in using flow to enter practice states that don’t lead to new development). Rigourous work around here that might be more widely applied could have strong benefits. Same for overall creativity.

Mihaly Csikszentmihalyi (Creativity: Flow and the Psychology of Discovery and Invention, 2013) has done work here but can it be extended and made wider known? If it can raise the creativeness of our top 20% (or anyone) could there be huge gains?

Drama and story

The basis of most (western) dramatic structure was written by Aristotle in his poetics around 330 BCE - so over 2300 years ago. While we have had some incremental changes and Shakespeare arguably stepped up this form there are a couple of way of thinking about this. One is that drama and story has been stagnating for a long time but another is that there is something fundamental about story structure that has persisted over centuries (maybe something Lindy? As Taleb might say)


Given the way that story/narrative/myth seems to really impact human behaviour (intersubjective myth for instance) and in world where humans might benefit being resistant to mis-information - I think there could be good gains from a rigourous study here.


Thinkers like Ray Dalio put strong weight on the hero quest story arcs in life and my weird suggestion is that a study around what we know about “story” as a social science exercise  would be insightful. 

This is probably too leftfield for them, but my next idea could be more mainstream and that is an examination of “educational mastery” especially in the context of online or Khan academy type innovations.

Educational Mastery

Patrick Collinson writes: “Educational psychologist Benjamin Bloom found that one-on-one tutoring using mastery learning led to a two sigma(!) improvement in student performance. The results were replicated. He asks in his paper that identified the "2 Sigma Problem": how do we achieve these results in conditions more practical (i.e., more scalable) than one-to-one tutoring?

In a related vein, this large-scale meta-analysis shows large (>0.5 Cohen's d) effects from direct instruction using mastery learning.

Is this a true effect and can we do more about it? Can it scale using online methods? 1-1 video ? Or if not, is there value to eg. randomly (or not) selecting some students and giving them mastery type learning. If just these small groups have two sigma improvements - could we see some significant gains?

I think ARPA could well study something in this area.  Nintil* did a thorough research round up suggesting the Bloom effect was not as large. But, 1-1 teaching did have a very robust effect. 

We could find a number of people willing to give 1-1 teaching as extra and maybe a number of students (across high performing or medium/low performing groups). If 1-1 can dramatically improve performance would this be worth studying or working on?

Building faster

Lastly, in this area it would be useful to examine why we seemed to be able to build infrastructure and certain other items faster 50 years ago. First, how true is this? UK managed to build Olympic sites in a moderately fast time frame but not eg. the tube extensions. This might not exactly be an ARPA area, but I think it could under pin a lot of innovation. (cf again Cowen, Collinson).

I think there’s an enormous amount that we do better, but can we learn from where we had speed before. Are there robust findings here? Or it just a nice to think venture capital thing.

My last huge area is on healthcare. 

Healthcare progress

I would also suggest there is work done on studying healthcare progress. Now there is a huge literature here, but I see less in a cross-disciplinary nature. This is intersectional with some other ideas here, but it would be what discoveries have most improved human health and how can we have more of them? What are the barriers or not.

Hand washing, weight control, diet, exercise and other low cost interventions are known but how best to synthesise this and can it be combined with newer technolofy and how intersectional with the social determinats of health?

This area will be a focus areas coming off the pandemic, but there is - to my reading - limited work on synthesing how best human health can be improved and the barriers to it.


And this is because of the incentives of where the private sector will focus its innovation and capture public good improvements or not. 


There are potentially very strong and perhaps moderately easy wins here. Two areas would be cost/benefits of areas of drug regulation. The UK has a particular opportunity here.


For instance, it could use EMEA and US  regulatory equivalence but go further and decide to approve certain medications quicker than those regulators. ( I think patient choice could be interesting here, post phase II and/or safety studies)

The UK could extend ideas it has started on “challenge trials” to see if this could significantly speed up areas of therapy development. There are areas probably more areas suitable for challenge trials and areas less suitable and not only COVID. ARIA could run a programme assessing and potentially funding some of this.  

Where would the cost/benefits of challenge trials help the UK/World in certain disease areas?


ARIA could go beyond narrow areas of regulation and even challenge trials but try an synthesis areas of public health.


Can robust work be done on how eg digital health data combined with preventative interventions could make huge, inexpensive, health interventions.   I think this could be a huge area. Many pilot trials have started (eg see a lot of the work Optum do) but some rigorous programmes here could be of enormous value.


In sum, we have ARIA. Let it explore some weird ideas. A few more transformational weird ideas would be a good thing and won’t displace all the other R&D things we are doing.


Links:

Dominic Cummings blog

On trees, World in Data but here on the conflicts in the data and conflicting data here.

Paul Graham, maker time

On Flow: Mihaly Csikszentmihalyi. Creativity: Flow and the Psychology of Discovery and Invention, 2013

Nintil on educational mastery

Patrick Collinson, fast things. And Cowen and Collinson on Progress Studies. 

Policy Exchange: https://policyexchange.org.uk/wp-content/uploads/Visions-of-Arpa.pdf

ON ARPA https://benjaminreinhardt.com/wddw


Bill Gates, Wired, on invest vs divest

Institutions deploying capital – banks and pension funds – are going to be crucial in this process. There's a lot of rhetoric at the moment with businesses claiming to be purpose-driven. How can we best measure the actions large investment funds are making, and keep big organisations honest about their actions?

Most of that’s all bullshit. The return on a bond for a wind farm is no different than the return on a bond from a natural gas plant, so it's nonsense. The people who put money into Breakthrough Energy Ventures [the venture arm of Gates’ organisation Breakthrough Energy that’s working towards net zero], that's real. The governments that raise their energy R&D budget and manage to spend it well, the near-billion dollars put into TerraPower [Gates’ nuclear company] to see if this fourth-generation fission reactor can be part of the solution... Those things are real.

All this other stuff like, we're gonna make companies report their emissions. The idea that some financial metric reporting thing or some degree of divestment – how many tonnes? You’ve got 51 billion tonnes [of CO2 that needs to be removed]: when you divested, how many of those 51 billion tonnes went away?

You’ve got to invest not divest. And the notion that you just happen to own equities or bonds related to the easy things that are already economic, such as solar farms or wind farms... Whenever somebody says there's something called green finance, I say let's be numeric here: is the risk premium for clean investing lower than the risk premium for non-green investing? The answer is: just look at the numbers.

The idea that banks are going to solve this problem or that these metrics are going to solve this problem, I don't get that. Are they going to make the electricity network reliable? Are they gonna come up with sustainable aviation fuel? It's just disconnected from the problem and allows people to go off and blather as though something's happening.

(from Wired)

but also - (from Bloomberg Green)

“In 2019, I divested all my direct holdings in oil and gas companies, as did the trust that manages the Gates Foundation’s endowment,” Gates writes in the book, noting that he hadn’t held coal company shares for “several years.” Public filings of the Gates Foundation’s holdings show that, as of the end of 2019, more than $100 million remained invested in stocks and bonds of oil and gas companies, including Exxon Mobil Corp., Chevron Corp. and BP Plc. The foundation does not specifically disclose its total fossil-fuel investments.

“Bill decided to sell all of his direct holdings in oil and gas companies in 2019,” a Gates family spokesperson said in response to questions about the divestment process. “We do work with third-party investment managers for a very small portion of the stock and bond holdings. They act independently and Bill does not direct those investments.” 

… In his book, he evokes the economic criticism of divestment to explain why he didn’t do so sooner. The theory is that dumping a company’s stock, for whatever reason, isn’t likely to have any real impact on the share’s price because someone else is likely to snap up the cheap shares and take home the gains anyway.

“I didn’t see how divesting alone would stop climate change or help people in poor countries,” Gates writes. “It is one thing to divest from companies to fight apartheid, a political institution that would (and did) respond to economic pressure. It’s another thing to transform the world’s energy system—an industry worth roughly $5 trillion a year and the basis for the modern economy—just by selling the stocks of fossil-fuel companies.”

Activists argue that divestment is needed to send a strong signal. “It’s mainly to take away the social license of fossil-fuel companies,” said Henn. “It is to show that the business models of these companies is in direct contradiction to our efforts to meet the goals of the Paris Agreement.” The accord strives to keep the increase in global temperatures below 1.5 degrees Celsius from pre-industrial levels.

On a large enough scale, divestment can have a real financial impact. Royal Dutch Shell Plc acknowledged in its 2017 annual report that it “could have a material adverse effect on the price of our securities and our ability to access equity capital markets.” Coal companies are already struggling to raise financing for projects around the world.

Gates says that he ultimately made the decision for moral reasons. “I don’t want to profit if their stocks prices go up because we don’t develop zero-carbon alternatives,” he writes. “I’d feel bad if I benefited from a delay in getting to zero [emissions].”

Theory of change, depression drugs, fossil fuel divestment

In much of science practice, scientists form ideas and models and then test these models in the world. The more credible the model to other thinkers and the more the model can explain empirical results and - even better - predict new results that be tested then the more useful the model and the more weight we can give it in our thinking.


Many models can not fully explain what we observe in the world. 

Many observations have no good models for them.


How should we think about decision making faced with forward looking uncertainties? I argue we should put more weight on when we have plausible models. This is harder in social sciences than physical sciences but still should be considered. That said empirical data can guide where models seem inadequate.


I’m going to think about these cases and what they might say:


  • -Anti-depression drugs and their effectiveness or lack

  • -Germ and virus theory and mask wearing

  • -Fossil Fuel divestment , social political change strategies

  • -Quantitative Easing by central banks

  • -ThenDoBetter grants - catalyzing change


Anti-depression drugs and their effectiveness or lack of.

Prozac, known as fluoxetine, is a serotonin re-uptake inhibitor or SSRI and it was designed as an anti-depression drug based on a model for depression that scientists developed.


The basic model is called the monoamine hypothesis of depression and this theory s proposes that patients with depression have depleted concentrations of serotonin, norepinephrine (noradrelanline), and dopamine. 


It was conceived due to at least one line of evidence on the effects of reserpine on serotonin and catecholamines. Reserpine, an alkaloid extracted from the Rauwolfia serpentina, was utilized as a treatment for hypertensive vascular disease in the 1950s; however, reserpine was found to precipitate depression in some patients. The depression produced by reserpine was reversed after the treatment was terminated and following either rest or electric shock therapy (Additionally, reserpine was found to produce depressive-like effects in animals Reserpine was found to inhibit vesicular monoamine transporter, and as a result, depletes brain monoamines (i.e. serotonin and catecholamines), which provided evidence for the role of serotonin, norepinephrine, and dopamine in depression.  


Since its original formulation, scientists can see that this hypothesis can not explain many other observations (for instance that healthy patients who deplete monoamines do not become depressed).

Still, SSRIs were invented  as the NHS website suggests:

“ It's thought that SSRIs work by increasing serotonin levels in the brain.


Serotonin is a neurotransmitter (a messenger chemical that carries signals between nerve cells in the brain). It's thought to have a good influence on mood, emotion and sleep.

After carrying a message, serotonin is usually reabsorbed by the nerve cells (known as "reuptake"). SSRIs work by blocking ("inhibiting") reuptake, meaning more serotonin is available to pass further messages between nearby nerve cells.”

Without going into too much more detail, we know empirically that SSRIs relieve depression in a good number of people and can help prevent relapse. But we also know that they don’t work in  a good number of people and that they stop working for a good number of people. And we are not exactly certain why.


There is much we simply do not understand about depression and brain function.


So how does relate to masks?


We have a pretty good theory about how viruses are transmitted. They travel in aerosol droplets from the nose and mouth - from sneezing and coughing and breathing - and they are then breathed in by others. They can also go from nose to hand to someone else’s hand to nose, or from hand to object back to someone else’s hand. Although there is debate as to how long viruses can survive on objects and how easily this transmission occurs.


Scientists have a consensus on this. And so when thinking about mask use to prevent transmission it’s surprising with hindsight that this did not feature more prominently.


Of course now we can look back and also note how many Asian countries had mask wearing and how European and America seemed initially reluctant. Still, I think it would have been much better if those in policy making or decision making roles could have case back to whether there was an underlying model for whether mask wearing should work and then assess risk/benefit.


Here the model was and is very useful, but didn’t seemed to make an impact.


Central Banks have engaged in what economists call quantitative easing or QE. These are large scale purchases of asserts by central banks. Economists are debating as to how QE actually works in the real economy and they are unsure. At least I can say scientists are much more sure on how germ theory works than on how quantitative easing works.


It’s perhaps in the same area of dispute as depression drugs. There’s some empirical evidence but the totality of it can not be explained by one model we have. And the three models posed by QE are not universally agreed upon.  (Segmented Market, Preferred Habitat and Signalling theory).


There’s - to my sense - maybe more agreement amongst depression scientists about what can or can not be explained then there is amongst economists. I note this as important as the Bank of England publishes an in-depth report into QE - https://www.bankofengland.co.uk/independent-evaluation-office/ieo-report-january-2021/ieo-evaluation-of-the-bank-of-englands-approach-to-quantitative-easing


This brings me to fossil fuel divestment strategies and thoughts on activism.


In biology, scientists call the SSRI mechanism as a mechanism of action. It’s how we best think the SSRIs are working biologically.


In social science, scientists often talk about a “theory of change”. 


“A theory of change is a description of why a particular way of working will be effective, showing how change happens in the short, medium and long term to achieve the intended impact.”


Supposedly a good theory of change needs to be testable. THis is in common with good theories of biological mechanisms of action - but are often much harder to assess in social science.


To my mind - a purported biological mechanism of action - such as the SSRI one - has much in common with a theory of change mechanism.


I come across some activists who have not really thought about their theory of change. And if the conversation allows, I will suggest they do think about it. I will often stress I do not know myself what theory of change is correct because many of the social science ones can not be supported either way by the evidence.


Still - when you think about the theory of change around divesting as opposed to the theory of change around engagement and persuasion of a company - you end up with very different theories.


This was summarised in Ellen Quigley et al’s report for Cambridge University (H/T Dominic Burke).    


The divestment social-political theory of change:


“The political case for divestment rests on expectations that it will accelerate the pace of legislation in favour of an energy transition away from fossil fuels. It does so both through creating a political

environment more favourable to legislation and by weakening the political power of the fossil fuel industry.”


This to use a policy term “moves the Overton window” - this changes the range of policies acceptable to the general public to be enacted by governments.


It’s quite far away from anything involved with investing (Although there are separate arguments for financial risks and theories such as influencing cost of capital).


One can argue this makes the movement more of a moral movement - one that you can align with women rights, minority rights, and slavery abolition and mperhaps more recently apartheid campaigns.


Using aparthied in South Africa is a complex and interesting parallel. Many factors (some with parallels to engagement and diplomacy and some with parallels to embargoes and divestments) are impossible to disentangle with cause and effect in the outcomes.


As strict financial theorists would argue most fossil fuel financing is not made by trading shares but by primary financial capital raising from bank or government loans or share issuance, and such that trading in secondary equities.


Thus the theory of change for engagement or within system workers is to persuade companies to change models and change strategies and this is more effectively done via share votes and engagement. And it is to invest in primary innovation and primary capital formation for companies making the most positive impact.


Neither theory can easily be proven with the empirical evidence we have. There are some companies that have changed course. Some climate policies have come into place and some evidence that the overton window has moved - although more easily for innovation policy than for carbon taxes, it seems.


But, it does bring me back to which theory of change is more meaningful or more reasonable to you.


I am asked where do I stand. If there’s time I typically outline a number of these arguments for both sides and because it is complex and unproven, I hold the theories of change lightly. 


But, my theory of change is that it falls - by a complex dance and a good deal of luck and happenstance - that a number of individuals spark the change that leads to systems altering. These individuals lead others.


And so, this is one of the reasons behind my idea on ThenDoBetter grants. The focus is on individual grant giving with a huge dose of luck and happenstance to people who will make that positive change.


As a coda thought. There are no universal theories of autism. The three main ones (central coherence, theory of mind, executive function) can explain certain aspects of autism but fail in many other aspects.  We have (in my view) poor models of autism (although not zero models, thus we can reject “refrigeration” and other catastrophically bad theories) and so we should hold lightly too much strong form advice here.


Quigley report:

https://www.cam.ac.uk/sites/www.cam.ac.uk/files/sm6_divestment_report.pdf 

How effective are anti-depressants:

https://www.ncbi.nlm.nih.gov/books/NBK361016/#:~:text=Studies%20involving%20adults%20have%20shown,within%20one%20to%20two%20years.

Brief history of anti-depressants: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4428540/


Theories on QE

https://www.stlouisfed.org/on-the-economy/2017/november/economic-theory-quantitative-easing


Climate scenarios, worse case + best case unlikely

An assessment of Earth's climate sensitivity using multiple lines of evidence. https://doi.org/10.1029/2019RG000678

“Earth's global “climate sensitivity” is a fundamental quantitative measure of the susceptibility of Earth's climate to human influence. A landmark report in 1979 concluded that it probably lies between 1.5‐4.5°C per doubling of atmospheric carbon dioxide, assuming that other influences on climate remain unchanged. In the 40 years since, it has appeared difficult to reduce this uncertainty range. In this report we thoroughly assess all lines of evidence including some new developments. We find that a large volume of consistent evidence now points to a more confident view of a climate sensitivity near the middle or upper part of this range. In particular, it now appears extremely unlikely that the climate sensitivity could be low enough to avoid substantial climate change (well in excess of 2°C warming) under a high‐emissions future scenario. We remain unable to rule out that the sensitivity could be above 4.5°C per doubling of carbon dioxide levels, although this is not likely.”

And from Bloomberg:

“A major new study of the relationship between carbon dioxide and global warming lowers the odds on worst-case climate change scenarios while also ruling out the most optimistic estimates nations have been counting on as they attempt to implement the Paris Agreement.

A group of 25 leading scientists now conclude that catastrophic warming is almost inevitable if emissions continue at their current rate, even if there’s less reason to anticipate a totally uninhabitable Earth in coming centuries. The research, published Wednesday in the journal Reviews of Geophysics, narrows the answer to a question that’s as old as climate science itself: How much would the planet warm if humanity doubled the amount of CO₂ in the atmosphere?

That number, known as “equilibrium climate sensitivity,” is typically expressed as a range. The scientists behind this new study have narrowed the climate-sensitivity window to between 2.6° Celsius and 3.9°C..

That’s smaller than the current range accepted by  the United Nations-backed Intergovernmental Panel on Climate Change, which has for almost a decade used a spread between 1.5°C to 4.5°C—a reading of climate sensitivity that has changed little since the first major U.S. climate science assessment in 1979. Improving these estimates is “sort of the holy grail of climate science,” says Zeke Hausfather, director of climate and energy at the Breakthrough Institute and one of the study’s authors.”

Short comment:

How many CO2 doublings from preindustrial levels of 285ppm we are going to see?

We are now at 415ppm (0.7 doublings), a likely range is 0.9 to 1.2 doublings by 2100. (RCP8.5 and SSP5-8.5 involve 1.6 to 2.0 doublings, but are not now plausible.)

The worse case 4c + scenarios are now looking unlikely. But so is sub 2.5c. This still argues for action to limt warming to - say - 3c. But it likely means adapatation/mitigation along with innovation could be higher priorities (not that this area is really on govt agendas at all). 

Links:

Paper here.

Bloomberg article here.