Tag Archives: Technology

Reading between the lines

… on another incoherent Breakthrough editorial:

The Creative Destruction of Climate Economics

In the 70 years that have passed since Joseph Schumpeter coined the term “creative destruction,” economists have struggled awkwardly with how to think about growth and innovation. Born of the low-growth agricultural economies of 18th Century Europe, the dismal science to this day remains focused on the question of how to most efficiently distribute scarce resources, not on how to create new ones — this despite two centuries of rapid economic growth driven by disruptive technologies, from the steam engine to electricity to the Internet.

Perhaps the authors should consult the two million references on Google scholar to endogenous growth and endogenous technology, or read some Marx. Continue reading

Technology first?

The idea of a technology-led solution to climate is gaining ground, most recently with a joint AEI-Brookings proposal. Kristen Sheeran has a nice commentary at RCE on the prospects. Go read it.

I’m definitely bearish on the technology-first idea. I agree that technology investment is a winner, with or without environmental externalities. But for high tech to solve the climate problem by itself, absent any emissions pricing, may require technical discontinuities that are less than likely. That makes technology-first the Hail-Mary pass of climate policy: something you do when you’re out of options.

The world isn’t out of options in a physical sense; it’s just that the public has convinced itself otherwise. That’s a pity.

The emerging climate technology delusion

What do you do when feasible policies aren’t popular, and popular policies aren’t feasible?

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: Continue reading

R&D – crack for techno-optimists

I like R&D. Heck, I basically do R&D. But the common argument, that people won’t do anything hard to mitigate emissions or reduce energy use, so we need lots of R&D to find solutions, strikes me as delusional.

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:

R&D funding

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:

R&D future 4x

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.

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.

Stop talking, start studying?

Roger Pielke Jr. poses a carbon price paradox:

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:

Pielke Loops

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:

PielkeLoopsSF

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. Continue reading

California EPA’s LEED platinum HQ

I’m usually quick to point out the limitations of technology for reducing environmental and other problems. But that doesn’t mean it’s not important. Yesterday I took a tour that hilighted how big the opportunities can be when technology and slight lifestyle changes team up. The tour was of CalEPA’s LEED platinum skyscraper – evidently the first of its kind, but now a few years old. Interestingly, it was initially designed as an ordinary building, and design changes were introduced late in the game, which gives hope that most of the same innovations could be implemented as retrofits on older buildings.

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.

Four Legs and a Tail

I’m continuously irked by calls for R&D to save us from climate change. Yes, we need it very badly, but it’s no panacea. Without other signals, like a price on carbon, technology isn’t going to do a lot. It’s a one-legged dog. True, we might get lucky with some magic bullet, but I’m not willing to count on that. An effective climate policy needs four legs:

  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.

Dangerous Assumptions

Roger Pielke Jr., Tom Wigley, and Christopher Green have a nice commentary in this week’s Nature. It argues that current scenarios are dangerously reliant on business-as-usual technical improvement to reduce greenhouse gas intensity:

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:

18 country emissions intensity

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.

Emissions intensity trend for 18 major emitters

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.

6 country emissions intensity

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.