Let’s start with a joke:

Lenin, Stalin, Khrushchev and Brezhnev are travelling together on a train. Unexpectedly the train stops. Lenin suggests: “Perhaps, we should call a subbotnik, so that workers and peasants fix the problem.” Kruschev suggests rehabilitating the engineers, and leaves for a while, but nothing happens. Stalin, fed up, steps out to intervene. Rifle shots are heard, but when he returns there is still no motion. Brezhnev reaches over, pulls the curtain, and says, “Comrades, let’s pretend we’re moving.” (Apologies to regulars for the repeat.)

The Soviet approach would be funny, if it weren’t the hottest new trend in climate policy. The latest installment is a Breakthrough article, The emerging climate technology consensus. An excerpt:

The twenty-year effort to create a single global pollution framework to reduce carbon emissions is in a state of collapse. …

Meanwhile, a new climate policy consensus is emerging, one which prioritizes direct investment in technology innovation. This consensus begins with the recognition that the root cause of the failure of the pollution paradigm was the technology and price gap between fossil fuels and their alternatives. No nation — not even the wealthiest in Europe — is willing to price carbon enough to cover the difference. Until the technology gap is closed, little will be done to accelerate the transition to a low-carbon economy.

…

In fact, the goal of a climate energy technology framework must be to make clean energy cheaper in unsubsidized terms — a radically different strategy than today’s energy-subsidy or carbon-pricing frameworks. …

I’ll grant the first point – that emissions agreements are in bad shape and have a long way to go before they’re effective. It’s also evident that no nation is currently willing to price carbon high enough to make a difference, at least unilaterally. I’ve been a critic of long-term targets as the core mechanism for emissions control myself, and I’m no great fan of cap & trade.

But does it follow that an R&D-led policy is the way to go? Enhanced R&D investment is likely a good idea, but does it stand on its own? Is it a viable substitute for significant emissions pricing, or just an illusion of movement, while delay in fact worsens our predicament?

I’ve already outlined some reasons to think that climatetech alone is not a robust strategy:

• The dynamics of R&D and learning suggest that it may be hard to reach cost parity for low carbon energy, and even if we do, there are long delays and strong positive feedbacks in capital and infrastructure to overcome
• While a low emissions price can fund public R&D, it does little for private R&D or deployment.
• Technology is just one leg of four complementary areas (prices, technology, rules, preferences) in which change is needed. Innovation is about more than devices; it’s a rich interaction between society, economy, and technology that takes decades to play out. R&D subsidies focus narrowly on technology and ignore the huge potential for reinvention of the economy and lifestyles.
• Low carbon energy sources aren’t just more expensive, they’re different. They have different geographic and temporal availability, power density, storage issues, and other attributes. Making them work is not just about making them cheap.
• It’s hard to design a low-emissions economy in a low-price, high-emissions environment, and governments (and indeed all organizations) are bad at picking winners.  R&D would be more productively pursued in a decentralized fashion with the guidance of prices.
• Absent emissions prices, rebound effects eat up technical gains in many areas.
• Some technologies, like CCS, are inherently thermodynamically inferior to their carbon-emitting equivalents, and therefore will never be deployed without emissions pricing.

Maybe we’ll get lucky, and the Breakthrough strategy will work. The problem is, if it doesn’t, by the time we find out it will be too late to do much about it. We’ll have committed to another 2 or 3 decades of emissions growth, with little to show for it. From an option value perspective, that’s a stupid way to proceed. I didn’t make “failure to account for delays” one of my top seven deadly sins of managing complex systems, but I probably should have. R&D is better than nothing, but I think its main attraction is that it ingratiates its proponents to current leaders who’d rather not change.

Breakthrough’s text and Q&A illuminates some strange thinking that led them to this point.

Even so, many continue to misunderstand the reasons for a technology-centered climate policy framework, and how it would work. Some, such as New York Times columnist Thomas Friedman, continue to imagine that carbon pricing will result in radical technological innovation, badly garbling the history of the digital revolution, which depended on direct government investment in things like R&D and military procurement — not an analogue tax, or a cap on typewriters.

Talk about a badly garbled history! Did the government set out to create a dotcom world? No. The digital revolution is emerging from the confluence of many distributed public and private opportunities, driven by a variety of signals (profit, fun, deliberate R&D investment). Achieving price parity in low-carbon energy sources is a narrower, and therefore more predictable task, but it may not work as advertised. What we need is the emissions equivalent of the digital revolution: a set of loosely-coordinated changes across many areas of society, which we can’t predict at the moment. That kind of change has to be decentralized. It’s a social revolution, not a Manhattan Project.

Once we set a price for carbon, won’t private firms have an incentive to invest in technology innovation to make clean energy technologies cheap?

There is little evidence that pricing carbon will drive the kind of energy technology revolution that will be necessary to achieve substantial reductions of global carbon emissions. Carbon pricing proponents often note that economies, such as Denmark and Japan, that have high energy prices and high gas or carbon taxes have lower carbon intensity than the United States. But those economies, in virtually every case, had lower carbon intensity prior to the imposition of high carbon and gas taxes. There is no evidence that the imposition of carbon taxes or gas taxes resulted in substantial shifts in economic behavior or technology innovation.

This strikes me as a simple denial of much of economics. If price and profit are not motives, why is there any private R&D at all? I’ve looked at lots of cross sectional studies of energy and pollution intensity, and don’t recall seeing any that supported this view.

Are you denying that Europeans drive smaller cars because of higher fuel prices?

There is some evidence that higher energy prices drive modest conservation through both behavior changes and more efficient use of energy. But the situations in which this has been the case have typically involved dramatic spikes in energy prices — such as those that occurred after the Arab oil embargo — that dwarf the magnitude of proposed carbon pricing….

But isn’t that just because the higher prices were not long-term?

No. Denmark has had a carbon tax in place since the early 1990’s. Danes drive small, fuel efficient cars today — just as they did prior to the imposition of the carbon tax. They are not, however, driving electric cars. At the same time, Denmark has significantly shifted its power sector to renewables, primarily wind. But the primary driver of that shift has been direct government subsidies for wind powered energy that dwarf the carbon tax in the magnitude of the incentive to deploy wind energy.

But don’t the economic models show carbon pricing resulting in technology innovation?

Combined climate and economic models don’t actually demonstrate that carbon pricing will lead to dramatic energy innovation. Rather they simply assume both robust technological innovation and the existence of a generic “backstop technology” – which will become available at a predetermined carbon price in unlimited quantities – and then purport to demonstrate that emissions are reduced dramatically in response to the carbon price signal. In fact, virtually all economic modeling of the costs associated with reduced carbon emissions conclude that the pace of technological innovation will be the most important factor determining the cost of reducing carbon emissions.

How do we know that investments in better energy technologies will result in reduced emissions?

We don’t.

No policy — regulation, tax or investment-focused — can guarantee emissions reductions. What we can safely predict is that as long as clean energy technologies cost substantially more than conventional energy technologies, efforts to cap, price, or otherwise regulate carbon emissions will fail. Public investments in clean energy technology are a necessary precondition, not a guarantee, of reduced global carbon emissions.

Our choice is not, as proponents of staying the current course would suggest, between acting to cap (or price) carbon emissions, and delay. It is between continuing to demand impossible actions or investing intelligently to overcome the primary obstacle to progress — the inadequacy of today’s low carbon energy technologies. It is our hope that the world will soon make the rational choice.

The latest example to cross my desk (via the NYT) is the new American Energy Innovation Council’s recommendations,

	Create an independent national energy strategy board.
	Invest $16 billion per year in clean energy innovation.
	Create Centers of Excellence with strong domain expertise.
	Fund ARPA-E at $1 billion per year.
	Establish and fund a New Energy Challenge Program to build large-scale pilot projects.

Let’s look at the meat of this – $16 billion per year in energy innovation funding. Historic funding looks like this:

Total public energy R&D, compiled from Gallagher, K.S., Sagar, A, Segal, D, de Sa, P, and John P. Holdren, “DOE Budget Authority for Energy Research, Development, and Demonstration Database,” Energy Technology Innovation Project, John F. Kennedy School of Government, Harvard University, 2007. I have a longer series somewhere, but no time to dig it up. Basically, spending was negligible (or not separately accounted for) before WWII, and ramped up rapidly after 1973.

The data above reflects public R&D; when you consider private spending, the jump to $16 billion represents maybe a factor of 3 or 4 increase. What does that do for you?

Consider a typical model of technical progress, the two-factor learning curve:

cost = (cumulative R&D)^A*(cumulative experience)^B

The A factor represents improvement from deliberate R&D, while the B factor reflects improvement from production experience like construction and installation of wind turbines. A and B are often expressed as learning rates, the multiple on cost that occurs per doubling of the relevant cumulative input. In other words, A,B = ln(learning rate)/ln(2). Typical learning rates reported are .6 to .95, or cost reductions of 40% to 5% per doubling, corresponding with A/B values of -.7 to -.15, respectively. Most learning rate estimates are on the high end (smaller reductions per doubling), particularly when the two-factor function is used (as opposed to just one component).

Let’s simplify so that

cost = (cumulative R&D)^A

and use an aggressive R&D learning rate (.7), for A=-0.5. In steady state, with R&D growing at the growth rate of the economy (call it g), cost falls at the rate A*g (because the integral of exponentially growing spending grows at the same rate, and exp(g*t)^A = exp(A*g*t)).

That’s insight number one: a change in R&D allocation has no effect on the steady-state rate of progress in cost. Obviously one could formulate alternative models of technology where that is not true, but compelling argument for this sort of relationship is that the per capita growth rate of GDP has been steady for over 250 years. A technology model with a stronger steady-state spending->cost relationship would grow super-exponentially.

Insight number two is what the multiple in spending (call it M) does get you: a shift in the steady-state growth trajectory to a new, lower-cost path, by M^A. So, for our aggressive parameter, a multiple of 4 as proposed reduces steady-state costs by a factor of about 2. That’s good, but not good enough to make solar compatible with baseload coal electric power soon.

Given historic cumulative public R&D, 3%/year baseline growth in spending, a 0.8 learning rate (a little less aggressive), a quadrupling of R&D spending today produces cost improvements like this:

Those are helpful, but not radical. In addition, even if R&D produces something more miraculous than it has historically, there are still big nontechnical lock-in humps to overcome (infrastructure, habits, …). Overcoming those humps is a matter of deployment more than research. The Energy Innovation Council is definitely enthusiastic about deployment, but without internalizing the externalities associated with energy production and use, how is that going to work? You’d either need someone to pick winners and implement them with a mishmash of credits and subsidies, or you’d have to hope for/wait for cleantech solutions to exceed the performance of conventional alternatives.

The latter approach is the “stone age didn’t end because we ran out of stones” argument. It says that cleantech (iron) will only beat conventional (stone) when it’s unequivocally better, not just for the environment, but also convenience, cost, etc. What does that say about the prospects for CCS, which is inherently (thermodynamically) inferior to combustion without capture? The reality is that cleantech is already better, if you account for the social costs associated with energy. If people aren’t willing to internalize those social costs, so be it, but let’s not pretend we’re sure that there’s a magic technical bullet that will yield a good outcome in spite of the resulting perverse incentives.

The carbon price paradox is that any politically conceivable price on carbon can do little more than have a marginal effect on the modern energy economy. A price that would be high enough to induce transformational change is just not in the cards. Thus, carbon pricing alone cannot lead to a transformation of the energy economy.

Put another way:

Advocates for a response to climate change based on increasing the costs of carbon-based energy skate around the fact that people react very negatively to higher prices by promising that action won’t really cost that much. … If action on climate change is indeed “not costly” then it would logically follow the only reasons for anyone to question a strategy based on increasing the costs of energy are complete ignorance and/or a crass willingness to destroy the planet for private gain. … There is another view. Specifically that the current ranges of actions at the forefront of the climate debate focused on putting a price on carbon in order to motivate action are misguided and cannot succeed. This argument goes as follows: In order for action to occur costs must be significant enough to change incentives and thus behavior. Without the sugarcoating, pricing carbon (whether via cap-and-trade or a direct tax) is designed to be costly. In this basic principle lies the seed of failure. Policy makers will do (and have done) everything they can to avoid imposing higher costs of energy on their constituents via dodgy offsets, overly generous allowances, safety valves, hot air, and whatever other gimmick they can come up with.

His prescription (and that of the Breakthrough Institute)  is low carbon taxes, reinvested in R&D:

We believe that soon-to-be-president Obama’s proposal to spend $150 billion over the next 10 years on developing carbon-free energy technologies and infrastructure is the right first step. … a $5 charge on each ton of carbon dioxide produced in the use of fossil fuel energy would raise $30 billion a year. This is more than enough to finance the Obama plan twice over.

… We would like to create the conditions for a virtuous cycle, whereby a small, politically acceptable charge for the use of carbon emitting energy, is used to invest immediately in the development and subsequent deployment of technologies that will accelerate the decarbonization of the U.S. economy.

…

Stop talking, start solving

As the nation begins to rely less and less on fossil fuels, the political atmosphere will be more favorable to gradually raising the charge on carbon, as it will have less of an impact on businesses and consumers, this in turn will ensure that there is a steady, perhaps even growing source of funds to support a process of continuous technological innovation.

This approach reminds me of an old joke:

Lenin, Stalin, Khrushchev and Brezhnev are travelling together on a train. Unexpectedly the train stops. Lenin suggests: “Perhaps, we should call a subbotnik, so that workers and peasants fix the problem.” Kruschev suggests rehabilitating the engineers, and leaves for a while, but nothing happens. Stalin, fed up, steps out to intervene. Rifle shots are heard, but when he returns there is still no motion. Brezhnev reaches over, pulls the curtain, and says, “Comrades, let’s pretend we’re moving.”

I translate the structure of Pielke’s argument like this:

Implementation of a high emissions price now would be undone politically (B1). A low emissions price triggers a virtuous cycle (R), as revenue reinvested in technology lowers the cost of future mitigation, minimizing public outcry and enabling the emissions price to go up. Note that this structure implies two other balancing loops (B2 & B3) that serve to weaken the R&D effect, because revenues fall as emissions fall.

If you elaborate on the diagram a bit, you can see why the technology-led strategy is unlikely to work:

First, there’s a huge delay between R&D investment and emergence of deployable technology (green stock-flow chain). R&D funded now by an emissions price could take decades to emerge. Second, there’s another huge delay from the slow turnover of the existing capital stock (purple) – even if we had cars that ran on water tomorrow, it would take 15 years or more to turn over the fleet. Buildings and infrastructure last much longer. Together, those delays greatly weaken the near-term effect of R&D on emissions, and therefore also prevent the virtuous cycle of reduced public outcry due to greater opportunities from getting going. As long as emissions prices remain low, the accumulation of commitments to high-emissions capital grows, increasing public resistance to a later change in direction.

Emissions embodied in the capital stock create powerful learning, network, and scale effects (orange). As long as the emissions price is low, every unit of high-emissions capital installed moves high-emitting capital producers down the learning curve, while low-emitting producers languish. Also, the infrastructure, like roads and fueling stations for conventional vehicles, remains locked in to a high emissions mode. These are extremely powerful positive feedbacks, and they can prevent implementation of new technologies even where they are intrinsically better than existing ones. They’re matched by a similar set of loops on the social side (not shown) that reinforce high-emissions lifestyle preferences.

While a low emissions price can fund public R&D, it does little for private R&D. Without a significant price, there’s little profit motive for developing low-emissions technology (red, outer). You can’t get financing for a project that relies on prices in the far future. It could be worse than that, especially for demand side technologies, because technical gains get eaten up by rebound effects, which is what has happened to vehicle fuel economy in the last few decades. Furthermore, it’s hard to design a low-emissions economy in a low-price, high-emissions environment; R&D would be more productively pursued in an environment where the cost of emissions was visible (red, inner). It might be possible to mitigate the waste of resources by focusing on basic research, but that makes the delay between conception and application longer (green).

The net effect of the low-price strategy is that we’re likely to find ourselves in 2030 with a greater emissions commitment than we have today – more roads, McMansions, etc. – and no more will to reduce. We might have more options, but then again the options looked really good for energy efficiency in the 70s, and things aren’t much different today.There’s no way we’d be on track to hit 2C or 50% by 2050 or any other low-climate-impact goal. Sure, we might get lucky, and invent low-emissions energy supply technologies that are quickly deployable on a massive scale – but counting on that is not a robust strategy.

So, why is the technology-led strategy so persistent and popular, in spite of the fact that research and empty talk are often equated in the public mind? I think that one underlying mental model is, “the stone age didn’t end because we ran out of stones.” In other words, it only makes sense to abandon our high-emissions mode when the low-emissions alternative becomes intrinsically better in every respect. This is a strange standard – in effect, it says that there simply won’t be any solution to the public goods problem (negative environmental externalities) that doesn’t rely on strictly private benefits, without any intervention to internalize the externality. This is either an ultra-pessimistic view (people are too perverse to act to better their collective long-term interest) or an ultra-libertarian view (the loss of liberty from government action to internalize the externality is worse than the underlying problem).

The second mental model is the economist’s rational view of the world, i.e. that if people oppose emissions pricing, they must have perfectly good reasons, as in, “it would logically follow the only reasons for anyone to question a strategy based on increasing the costs of energy are complete ignorance and/or a crass willingness to destroy the planet for private gain.”  The real situation isn’t that stark. In fact, there is very solid evidence that even technically sophisticated people don’t understand the accumulation dynamics of the climate, and that agency problems and externalities around emissions are widespread. Thus it isn’t really very surprising that locally, boundedly rational people  oppose policies that would actually be in their best interest over the long haul.

So, what’s my alternative prescription? Pielke’s low emissions price is not a bad start, even though $5/TonCO2 or even $25/TonCO2 is basically a joke compared to the social cost of carbon at fair discount rates or what it takes to motivate behavior change. Apart from the direct benefits of doing this, it creates the infrastructure for higher prices in the future. We part ways on the details, I think. First, it’s crucial that we not advertise the investment of emissions revenue in R&D as a solution, because it’s not – it’s just a piece of the puzzle. Second, some of the money should go back to the public as rebates or tax and deficit reductions, because that will need to happen at higher prices. Third, there needs to be a credible commitment to higher prices in the future, to provide the incentive for deployment and private innovation over longer horizons. Fourth, to unlock innovation potential, old regulatory frameworks that hinder innovation, including environmental policies and building codes, need to be reformulated in more flexible ways; this should be popular even absent climate concerns. Fifth, markets need to be created or altered to solve the landlord-tenant problem and other institutional obstacles to deployment; the higher the carbon price, the more opportunity people will see in such changes. To the extent that we can’t do all of this now, we don’t sit on our hands and pretend, we build the basis for action in the future by improving mental models that currently constrain action. That doesn’t mean social engineering; it’s a process of making models and data accessible and transparent enough for people to discover that current policies don’t result in a good outcome along the dimensions that they value for various possible futures.

[Update - afterthought: where the low-emissions-price scenario might make a lot of sense is in small regions. Then, it would generate a useful revenue stream without causing enough pain to cause significant leakage of emissions out of the jurisdiction. It would probably be easier to keep the tech $ in-region in early stage R&D than it would be later, during deployment, when manufacturing would be susceptible to offshoring. Still, you'd have to think of it as a stepping stone, not a solution.]

When you walk up to the building, there’s no indication that there’s anything unusual about it. If anything, it’s massive (salvaged) stone decorative features lead one to think it could easily be an extravagant energy hog. That impression continues on the inside, with elegant and tasteful lighting and finishes. No hairy unwashed treehuggers freezing in the dark here.

Yet, the building uses a third the energy (per sq ft) of its peers nearby, even with a big datacenter on one floor that consumes a third of the energy in the 25-story structure. The big heroes are an efficient skin, with low-e windows and detailing to reduce solar gain on the south and west sides, coupled with an advanced HVAC system. Climate control combines 10,000 sensors with three different sizes of chiller unit and variable-speed motor controls. That way, equipment always operates near its optimum load. Soon, a retrofit will use groundwater (which has to be pumped out anyway) to aid cooling. Heating and cooling costs are lower, yet comfort is improved by the advanced controls.

The occupants certainly contribute a lot to efficiency. Over 80% use bikes or transit to commute, aided by a beautiful bicycle parking garage in the basement (complete with air compressor and lockers). Most prefer motion-sensitive task lights, so area lighting stays off. They adopted double-side network printers to reduce paper waste, and recycle assiduously. Worm-bin composting is a popular office activity. As a result the building managers have to haul trash only twice a month instead of the typical twice a week. Because staff don’t have to spend as much time with regular garbage, they have more energy to figure out how to recycle used computers and other unusual materials.

Sometimes the benefits are unexpected. To reduce nighttime lighting loads, most of the leaning in the building happens during the day. Side effects include greatly reduced reports of theft and workers’ comp claims, better cooperation on cleaning and recycling (aided by the low waste flow), and greater occupant satisfaction. It turns out that it’s easier to like someone you see on a daily basis. Materials have side benefits too. Zero-VOC paints mean that occasional repairs don’t stink up the place and needn’t be confined to weekends. Low-volatile, recyclable carpet tiles turn out to be extremely durable and repairable, and permit creative design.

The amazing thing is that most of the features paid for themselves in under two years, with correspondingly huge ROIs. None takes a radical change in workstyle, but there’s lots of synergy among them. It wasn’t easy to pull this off, in the sense that it took a lot of thinking, but if you think thinking is fun, then you wouldn’t call it hard either.

1. Prices
2. Technology (the landscape of possibilities on which we make decisions)
3. Institutional rules and procedures
4. Preferences, operating within social networks

When I wrote that list down, it reminded me of Dana Meadows’ list of leverage points in systems. I’m a bit of a heretic, in that I don’t agree with the ordering of the list. In fact, I’m not even sure that it’s possible to come up with a general ordering for nonlinear dynamic systems. Nevertheless, I find it very useful in practice for pondering whether the solutions proposed for a problem are operating at the right level. In the case of climate, I think the reason we don’t have much of 1 through 4 above is that we don’t have much of 4 through 1 below:

Leverage points to intervene in a system (in increasing order of effectiveness)
12. Constants, parameters, numbers (such as subsidies, taxes, standards)
11. The size of buffers and other stabilizing stocks, relative to their flows
10. The structure of material stocks and flows (such as transport network, population age structures)
9. The length of delays, relative to the rate of system changes
8. The strength of negative feedback loops, relative to the effect they are trying to correct against
7. The gain around driving positive feedback loops
6. The structure of information flow (who does and does not have access to what kinds of information)
5. The rules of the system (such as incentives, punishment, constraints)
4. The power to add, change, evolve, or self-organize system structure
3. The goal of the system
2. The mindset or paradigm that the system — its goals, structure, rules, delays, parameters — arises out of
1. The power to transcend paradigms

Most of climate policy and public perception as I see it is operating near #12, trying to preserve economic growth (#7), facilitated by deficiencies in #6 to ignore #9. Integrated Assessment Models focus on prices and technology, largely neglecting a variety of institutional factors that obstruct the response to carbon and energy prices and constrain the adoption of technology. They take preferences as a given and thus neglect the possibility of social change complementing (or driving) technical and institutional change.

The reason we don’t have an effective price on carbon is not that it’s suboptimal to do so. It’s that getting to a price that would actually do something will take a massive paradigm shift – the tail that wags the dog. So, I’ll continue to like #12, but from here on out I’ll be working a lot harder on #6 as a path to #1.

Here we show that two-thirds or more of all the energy efficiency improvements and decarbonization of energy supply required to stabilize greenhouse gases is already built into the IPCC reference scenarios. This is because the scenarios assume a certain amount of spontaneous technological change and related decarbonization. Thus, the IPCC implicitly assumes that the bulk of the challenge of reducing future emissions will occur in the absence of climate policies. We believe that these assumptions are optimistic at best and unachievable at worst, potentially seriously underestimating the scale of the technological challenge associated with stabilizing greenhouse-gas concentrations.

They note that assumed rates of decarbonization exceed reality:

The IPCC scenarios include a wide range of possibilities for the future evolution of energy and carbon intensities. Many of the scenarios are arguably unrealistic and some are likely to be unachievable. For instance, the IPCC assumptions for decarbonization in the short term (2000–2010) are already inconsistent with the recent evolution of the global economy (Fig. 2). All scenarios predict decreases in energy intensity, and in most cases carbon intensity, during 2000 to 2010. But in recent years, both global energy intensity and carbon intensity have risen, reversing the trend of previous decades.

In an accompanying news article, several commenters object to the notion of a trend reversal:

Energy efficiency has in the past improved without climate policy, and the same is very likely to happen in the future. Including unprompted technological change in the baseline is thus logical. It is not very helpful to discredit emission scenarios on the sole basis of their being at odds with the most recent economic trends in China. Chinese statistics are not always reliable. Moreover, the period in question is too short to signify a global trend-break. (Detlef van Vuuren)

Having seen several trend breaks evaporate, including the dot.com productivity miracle and the Chinese emissions reductions coincident with the Asian crisis, I’m inclined to agree that gloom may be premature. On the other hand, Pielke, Wigley and Green are conservative in that they don’t consider the possible pressure for recarbonization created by a transition from conventional oil and gas to coal and tar sands. A look at the long term is helpful:

Emissions intensity of GDP for 18 major emitters. Notice the convergence in intensity, with high-intensity nations falling, and low-intensity nations (generally less-developed) rising.

Corresponding decadal trends in emissions intensity. Over the long haul, there’s some indication that emissions are falling faster in developed nations – a reason for hope. But there’s also a lot of diversity, and many nations have positive trends in intensity. More importantly, even with major wars and depressions, no major emitter has achieved the kind of intensity trend (about -7%/yr) needed to achieve 80% emissions reductions by 2050 while sustaining 3%/yr GDP growth. That suggests that achieving aggressive goals may require more than technology, including – gasp – lifestyle changes.

A closer look at intensity for 6 major emitters. Notice intensity rising in China and India until recently, and that Chinese data is indeed suspect.

Pielke, Wigley, and Green wrap up:

There is no question about whether technological innovation is necessary — it is. The question is, to what degree should policy focus directly on motivating such innovation? The IPCC plays a risky game in assuming that spontaneous advances in technological innovation will carry most of the burden of achieving future emissions reductions, rather than focusing on creating the conditions for such innovations to occur.

There’s a second risky game afoot, which is assuming that “creating the conditions for such innovations to occur” means investing in R&D, exclusive of other measures. To achieve material reductions in emissions, “occur” must mean “be adopted” not just “be invented.” Absent market signals and institutional changes, it is unlikely that technologies like carbon sequestration will ever be adopted. Others, like vehicle and lighting efficiency, could easily see their gains eroded by increased consumption of energy services, which become cheaper as technology improves productivity.