July 2008 Archives

Oilman T. Boone Pickens made a splash last week by announcing plans to build a wind farm with 4,000 megawatts worth of generating capacity.  The Pickens Plan calls the U.S. the Saudi Arabia of oil wind, and he notes that, "At current oil prices, we will send $700 billion dollars out of the country this year alone — that's four times the annual cost of the Iraq war."  His logic in making this investment is pretty straightforward:

Building wind facilities in the corridor that stretches from the Texas panhandle to North Dakota could produce 20% of the electricity for the United States at a cost of $1 trillion. It would take another $200 billion to build the capacity to transmit that energy to cities and towns.

That's a lot of money, but it's a one-time cost. And compared to the $700 billion we spend on foreign oil every year, it's a bargain.

Great -- the more energy we generate at home, the more we can invest in rebuilding the U.S. economy and infrastructure.  Somewhat less obvious is the logic of his suggestion that this electricity be used to free up natural gas now burned to provide ~20% of US electricity, and instead use that gas to power cars.

There are very few natural gas powered cars in this country, and it would take an enormous investment to either retrofit existing vehicles or replace a large fraction of the existing fleet in less time than the present ~13 year life cycle.  Moreover, burning natural gas in large turbines is way more efficient than burning it in small car engines, so it is actually better used to produce electricity for the grid.  It would seem to make more sense to just use the added electricity generation capacity from wind to directly offset petroleum use.

Why not just replace or retrofit the fleet with plug-in hybrids that substantially increase the efficiency of cars regardless of their fuel type?  Then you could be agnostic about the specific engine technology and fuel, but still know you could potentially double the mileage of any given vehicle by recharging from the electricity grid?  Here, for example, is a story at Wired News by Chuck Squatriglia in which Andy Grove, the CEO of Intel, calls for converting 10 million cars and trucks in the U.S. to plug in hybrids over the next four years.  The story quotes John Dabels, CEO of conversion start-up EV Power Systems, as saying his company can provide an $11,000 conversion kit that bolts onto the transmission of existing cars and trucks and delivers a 30-40% increase in liquid fuel efficiency.  Google has evidently been running a fleet of plug-in Priuses and Escapes with a 50% improvement over the standard hybrid.  These are early numbers.  Efficiencies are bound to increase as better batteries and electric motors enter the market.

Pair plug-in hybrids with microbial biofuel synthesis -- oh, alright, and even cellulosic ethanol -- and suddenly you get way more out of your feedstock and thereby reduce pressure on food prices.  Not that I am biased or anything.

The Future of China's Economy

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It's hot and damp in southeastern China this time of year.  So reports a relative of mine working in the area who called to chat a few days ago.  He was suffering through another day without air conditioning, in the middle of yet another regional power outage due to a shortage of coal.  This occurrence is evidently not uncommon.  We hear a great deal in the U.S. about the unstoppable juggernaut of the Chinese economy, but sometimes I wonder if the Chinese aren't setting themselves up for a stumble or two.

(Update: For more on resource demands, see my subsequent post "More on China's Economy, Food Production, and Food Demand".)

Many of the signs point to inevitable economic superiority.  The Carnegie Endowment for International Peace released a report last week that projects China's economy will overtake that of the U.S. by 2035 (Yahoo News). "China's Economic Rise--Fact and Fiction", by Albert Keidel, concludes that China's economy is now dominated by internal growth rather than exports, and that China's economy will be twice that of the U.S. by 2050.  Keidel gives the nod to financial and bureaucratic tangles as the primary threats to growth, but does not appear particularly concerned about environmental damage and pollution. He argues that:

The record for several other East Asian economies argues that pollution is unlikely to undermine China's growth in the coming decades. In particular, Japan, South Korea, and Taiwan all passed through similar periods of serious pollution associated with rapid industrialization. In these cases, policy responses were also delayed but eventually reduced pollution levels that in some dimensions were worse than China's today.

Maybe so, but, depending on how you look at the numbers, the cost of pollution may be wiping out all of China's GDP growth.

(Update 25 July, 2008: Here is a video feed from Fora.tv of a panel discussion at the Carnegie Endowment for International Peace discussing the "Fact and Fiction" report.  I haven't watched the whole thing yet...)

Attempting to Account for the Costs of Pollution

For most of the last decade, China's government has downplayed the cost of environmental damage to the country's GDP.  However, according The Economist, in March of 2008, Pan Yue, a deputy minster at the State Environmental Protection Agency (SEPA), publicly estimated that environmental damage reduces GDP by as much as 13%.  As recently as May, 2006, the official estimate was only 3% of GDP for 2004, a tally contained in the first and only "green audit" of the economy.

The direct costs to human life are substantial, but official estimates are also variable.  A study by SEPA and The World Bank, published last year, "The Cost of Pollution in China", estimates that pollution is directly responsible for at least 750,000 deaths a year, while in a 2006 speech Mr. Pan stated that approximately 70% of China's two million annual cancer deaths were caused by pollution.

The disparity in these figures is evidently caused by political tension between different parts of the Chinese government.  Both the health findings and the future of the "green GDP audit" were evidently compromised by political infighting between state scientists, regional leaders, and officials in other ministriesThe New York Times reported that:

The official explanation was that the science behind the green index was immature. Wang Jinnan, the leading academic researcher on the Green G.D.P. team, said provincial leaders killed the project. "Officials do not like to be lined up and told how they are not meeting the leadership's goals," he said. "They found it difficult to accept this."

Here is the point: Even a 10% reduction in Chinese GDP would, in effect, zero out the overall growth of the economy.  Viewed this way, despite its role in the global economy, any "wealth creation" and growth in China may be accounted for entirely by the cost of degrading the local environment and increasing human disease and death.  You can understand how government officials might be uneasy about publicizing this figure.

According to officials at The World Bank, its "Cost of Pollution" report was similarly abridged for political reasons; "China's environmental agency insisted that the health statistics be removed from the published version of the report, citing the possible impact on 'social stability'."  As a result, one-third of the document was reportedly withheld from publication.  The tension between open communication and central control, and between development and damage, is evident in a press release from Gov.cn, the Government's official web site:

Even though the economic growth characterized by "high consumption, high pollution and high risk" is of its own historical significance in China, China's economy has been in the bottleneck period of resources and energy today and it cannot bear any risks of resources exhaustion.

Meanwhile, Chinese society has also entered the period with various conflicts protruding in which per capita GDP is about 1,000-3,000 US dollars, which cannot bear up any social problems caused by environmental pollution.

The government is clearly aware of the social and economic threats of environmental damage.  As reported by the Shanghai Daily, the most recent five year plan; "Requires energy consumption per unit of GDP to decline by 20 percent from the previous planning period.  The total amount of major pollutants discharged will be reduced by 10 percent, and forest coverage will be raised from 18.2 percent to 20 percent."

In an effort better address environmental concerns, in March of 2008 the State Council upgraded SEPA to a full Cabinet-level ministry.  To gather, "Accurate and high-quality data [of] pollution sources," the government launched in the first pollution census in February 2008.  And yet even while the central government attempts to close illegal and polluting coal mines and coal burning plants, journalists regularly report that local and regional authorities either ignore or explicitly condone the reopening of those facilities (1, 2, 3).

It does not appear that China's reliance on coal is going to decrease any time soon.  China has recently been building coal-fired plants at the rate of one every 7 to 10 days, with plans to build 500 more over the next decade.  The fraction of newly built power plants that burn coal has increased from 70% to 90% since 2000.  Thus, without either a more unified approach to reducing pollution or a substantially stronger response to that end by the central government, environmental damage will continue to directly plague both the economy and human health.

The Future Cost of the Building Boom

Here is something I don't see discussed in the press: where are the Chinese going to get all the coal to fire all the new power plants, especially when they are already facing supply shortfalls?  (Update: To clarify, I am less concerned here with the amount of coal in the ground than supply chain issues.  If they are already having trouble moving coal quickly enough to existing plants, how will they manage the increased demand?)  And while they may have the coal in the ground, how much will it cost to mine it with labor costs rising all across the country? And what about the costs of additional transportation infrastructure?

This brings us back to my father-in-law, sweltering away in Xiamen, and one of stumbling blocks the Chinese may be literally building for themselves.  As reported by The New York Times:

Each year for the past few years, China has built about 7.5 billion square feet of commercial and residential space, more than the combined floor space of all the malls and strip malls in the United States, according to data collected by the United States Energy Information Administration.

Chinese buildings rarely have thermal insulation. They require, on average, twice as much energy to heat and cool as those in similar climates in the United States and Europe, according to the World Bank. A vast majority of new buildings -- 95 percent, the bank says -- do not meet China's own codes for energy efficiency.

All these new buildings require China to build power plants, which it has been doing prodigiously. In 2005 alone, China added 66 gigawatts of electricity to its power grid, about as much power as Britain generates in a year. Last year, it added an additional 102 gigawatts, as much as France.

Damn.  So not only is China building enormous power generation capacity, but their underlying infrastructure is inherently inefficient.  This kind of systemic inefficiency is often attributed to, excused, or even just written off as a characteristic of a particular "stage of economic development" (see Keidel for one example).  It is certainly true that the U.S., Japan, and Europe all went through periods when the focus was on generating jobs and building wealth, only later to be followed up by mining inefficiencies to squeeze more product out of each unit of water and energy.

But all of China's infrastructure, all that housing and commercial space, is brand new.  So here are more questions: Is the government's plan to replace inefficient buildings over the next couple of decades?  Will labor remain so inexpensive that Chinese infrastructure is, in effect, disposable?  What are the secondary costs of maintaining that construction boom (e.g., energy, pollution, materials)?

It would seem that without a truly radical change in energy production, China is setting itself up to rely on dirty coal for many decades to come.  And so I wonder: How it is that the country will escape continued environmental damage that is equivalent to China's GDP growth?  You can't put off dealing with those costs forever.

The U.S. is borrowing cash from China to buy petroleum, and we have to sort that out as soon as possible.  But the Chinese are using their health, and thus their future productivity, as collateral for present growth. Even if they don't stumble, they may have to pause to catch their breath.

Ineffective Export Controls for US Technology

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In the context of my ongoing skepticism about the effectiveness of regulation for improving biosecurity, here is a quick note on the utility of export controls for restricting transfer of sensitive technology.

Over at Wired News, Noah Shachtman has a post pointing to an article in Mother Jones about all the US weapons that are winding up in the hands of Iran.  Re-sale by third parties seems to be the short answer, but read the article to get the full story.

With experience comes skill and efficiency.  That is the theory behind "learning" or "experience curves", which I played around with last week for DNA sequencing.  As promised, here are a few thoughts on the future of DNA synthesis.  Playing around with the synthesis curves a bit seems to kick out a couple of quantitative metrics for technological change.

For everything below, clicking on a Figure launches a pop-up with a full sized .jpg.  The data come from my papers, the Bio-era "Genome Synthesis and Design Futures" report, and a couple of my blog posts over the last year.

carlson_DNA_synthesis_learning_curve_june_08.jpg
Figure 1.

The simplest application of a learning curve to DNA synthesis is to compare productivity with cost.  Figure 1 shows those curves for both oligo synthesis and gene synthesis (click on the figure for a larger pop-up).  These lines are generated by taking the ratios of fits to data (shown in the inset).  This is necessary due to the methodological annoyance that productivity and cost data do not overlap -- the fits allow comparison of trends even when data is missing from one set or another.  As before, 1) I am not really thrilled to rely on power law fits to a small number of points, and 2) the projections (dashed lines) are really just for the sake of asking "what if?".
 

What can we learn from the figure?  First, the two lines cover different periods of time.  Thus it isn't completely kosher to compare them directly.  But with that in mind, we come to the second point: even the simple cost data in the inset makes clear that the commercial cost of synthetic genes is rapidly approaching the cost of the constituent single-stranded oligos. This is the result of competition, and is almost certainly due to new technologies introduced by those competitors.

Assuming that commercial gene foundries are making money, the "Assembly Cost" is probably falling because of increased automation and other gains in efficiency.  But it can't fall to zero, and there will (probably?) always be some profit margin for genes over oligos.  I am not going to guess at how low the Assembly Cost can fall, and the projections are drawn in by hand just for illustration.

carlson_synth_organism_learning_curve_june_08.jpg

Figure 2.

It isn't clear that a couple of straight lines in Figure 1 teach us much about the future, except in pondering the shrinking margins of gene foundries.  But combining the productivity information with my "Longest Synthetic DNA" plot gives a little more to chew on.  Figure 2 is a ratio of a curve fitted to the longest published synthetic DNA (sDNA) to the productivity curve.

In what follows, remember that the green line is based on data.

First, the caveat: the fit to the longest sDNA is basically a hand hack.  On a semilog plot I fit a curve consisting of a logarithm and a power law (not shown).  That means the actual functional form (on the original data) is a linear term plus a super power law in which the exponent increases with time.  There isn't any rationale for this function other than it fits the crazy data (in the inset), and I would be oh-so-wary of inferring anything deep from it.  Perhaps one could make the somewhat trivial observation that for a long time synthesizing DNA was hard (the linear regime), and then we entered a period when it has become progressively easier (the super power law).  I should probably win a prize for that.  No?  A lollipop?

There are a couple of interesting things about this curve, along which distance represents "progress".  First, so far as I am aware, commercial oligo synthesis started in 1992 and commercial gene foundries starting showing up in 1999.  The distance along the curve in those seven years is quite short, while the distance over the next nine years to the Venter Institute's recent synthetic chromosome is substantially larger.

This change in distance/speed represents some sort of quantitative measure of accelerating progress in synthesizing genomes, though frankly I am not yet settled on what the proper metric should be.  That is, how exactly should one measure distance or speed along this curve?  And then, given proper caution about the utility of the underlying fits to data, how seriously should one trust the metric?  Maybe it is just fine as is.  I am still pondering this.

Next, while the "learning curve" is presently "concave up", it really ought to turn over and level off sometime soon.  As I argued in the post on the Venter Institute's fine technical achievement, they are already well beyond what will be economically interesting for the foreseeable future, which is probably only 10-50 kilobases (kB).  It isn't at all clear that assembling sDNA larger than 100 kB will be anything more than an academic demonstration.  The red octagon (hint!) is positioned at about 100 MB, which is in the range of a human chromosome.  Even assembling something that large, and then using it to fabricate an artificial human chromosome, is probably not technologically that useful.  I reserve a bit of judgement here in the event it turns out that actually building functioning human chromosomes from smaller pieces is problematic.  But really, why bother otherwise?

carlson_longest_sDNA_vs_gene_cost_june_08.jpg
Figure 3.

Next, with the other curves in hand I couldn't help but compare the longest sDNA to gene assembly cost (beware the products of actual free time!).  (Update: Can't recall what I meant by this next sentence, so I struck it out.) Figure 3 may only be interesting because of what it doesn't show.  Note the reversed axis -- cost decreases to the right.

The assembly cost (inset) was generated simply by subtracting the oligo cost curve from the gene cost curve (see Figure 1 above) -- yes, I ignored the fact that those data are over different time periods.  There is no cost information available for any of the longest sDNA data, which all come from academic papers.  But the fact that gene assembly cost has been consistently halving every 18 months or so just serves to emphasize that the "acceleration" in the ratio of sDNA to assembly cost results from real improvements in processes and automation used to fabricate long sDNA.  I don't know that this is that deep an observation, but it does go some way towards providing additional quantitative estimates of progress in developing biological technologies.

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