Monday, June 23, 2014
But if the world is serious about tackling climate change, these fantastic engineering achievements are not enough. Whereas, in the year 2000, aviation contributed 2% of global carbon dioxide emissions, it is projected that by 2050, aviation's growth will increase its carbon emissions five-fold, even allowing for continued improvements in efficiency. Moreover, today's planes emit other greenhouse gases whose effect on climate is estimated to be between two and four times greater than their carbon dioxide emissions.
The Longitude Prize 2014 Flight Challenge sets a new goal for aviation: to design and demonstrate a near-zero-carbon aircraft, which travels fast (though not necessarily as fast as a jet), which has a substantial range (at least London to Edinburgh!), and which is significantly more energy-efficient than a 747. There is no simple solution to this demanding set of constraints, but there are promising approaches that fulfill some of these requirements.
We intend the Challenge to be accessible to small creative teams. Here I've described four current activities that indicate the wide range of perspectives from which the Flight Challenge might be approached. I'm confident the Flight Challenge will stimulate brilliant inventors to develop other exciting ideas for the future of aviation.
See also: 2014 Longitude prize WATER Challenge
Voting for the Longitude Prize Challenge closes at 7.10pm on June 25th 2014.
David MacKay FRS is a member of the 2014 Longitude Committee. He is the Chief Scientific Advisor at the Department of Energy and Climate Change, and Regius Professor of Engineering at the University of Cambridge. He is well known as author of the popular science book, Sustainable Energy — without the hot air.
Frequently asked questions...
David MacKay FRS
Saturday, May 24, 2014
Energia sostenibile - senza aria fritta [Italian translation of Sustainable Energy - without the hot air!]
I'm very grateful to volunteers Alessandro Pastore, Javier Oca, Valentina Rossi, Alberto Marcone, Paolo Errani, and Simone Gallarini for completing the Italian translation of Sustainable Energy - without the hot air.There is an announcement of the translation, and a synopsis, at this link, and the first draft of the translation is available on the book's translation page.
Energia sostenibile - senza aria fritta — Nel caso ci fossero sfuggite delle imperfezioni o errori, all'indirizzo email: email@example.com, saremo ben lieti di riceverne segnalazione. Il libro in italiano può essere scaricato liberamente da internet all'indirizzo http://www.withouthotair.com/translations.html.
Saturday, February 22, 2014
I'm aiming to make a highly interactive presentation in which we will try to crowd-source an "IET consensus pathway" in the UK's 2050 Calculator. To help the discussion go well, I'd like to encourage people who are planning to be in the audience, before the lecture, to play with the calculator, and to identify the levers they would most like to discuss during the lecture. Please use the comments area at the foot of this blog-post now as a discussion area. Please feel free also to discuss your preferred pathways or preferred settings of individual levers, and to discuss particular issues or trade-offs that you think should be part of a useful conversation using the calculator.
The outcome - Here is the pathway that we got to after one hour - I will write a few notes and propose possible tweaks in a moment. Top things that needed doing: (a) check which fuel mix for the CCS power stations works best; (b) check which choice of fuel from bioenergy works best; (c) explore space-heating options - the audience asked for a 15:25:60 mix of fuel-in-home (eg gas boilers):district-heating:heat-pumps, and the "CD" heating mix doesn't match this perfectly. Thank you to the audience for a fun evening!
Update - After the lecture I made a few adjustments to the above pathway which I think the audience would have been content with. The resulting final IET London pathway (March 2014) is here. The changes I made were as follows: (a) I checked which choice of CCS power station fuel (solid/gas) was best for emissions, and selected "D". (b) I checked which "type of fuels from biomass" was best for emissions, and selected "B" (mainly solid). (c) I adjusted the commercial heating choice to "D,A" so as to make the overall heating mix for homes and commercial closer to the heating mix that the audience voted for. (d) I double-checked whether choices (a, b) were still optimal. The resulting pathway achieves a 77% reduction in emissions on 1990 levels (pretty close to the 2050 target of at least 80%), and requires no backup generation in mid-winter when the wind doesn't blow.
Wednesday, December 11, 2013
|My attention was recently drawn to an impressively fuel-efficient turboprop aircraft, the ATR72-600, which is claimed to be about one third more energy efficient than Bombardier's Q400 turboprop, which I featured on page 35 of SEWTHA.|
|I've consequently written an update on turboprops, celebrating this achievement, but in the interests of balance I feel I should also nominate the advertisers of the ATR72-600 for this year's Hot Air Oscar for the most misleading "green" infographic, for this astonishing picture [at left] showing the difference between the fuel consumption of the ATR 72 and the Q400 on a 250-nautical-mile journey. As the numbers in the picture show, the ATR 72's fuel consumption is 70% of the Q400's, but the volume of the three-dimensional blue barrel shown is 30% of the volume of the orange barrel — a 2.3-fold exaggeration!|
In fact, I doubted Hughes's assertions from the moment I first read his study, since they were so grossly at variance with the data.
a) Histogram of average annual load factors of wind farms at age 10 years. For comparison, the blue vertical line indicates the assertion from the Renewable Energy Foundation's study that "the normalised load factor is 15% at age 10."
b) Histogram of average annual load factors of wind farms at age 11 years.
c) Histogram of average annual load factors of wind farms at age 15 years. For comparison, the red vertical line indicates the assertion from the Renewable Energy Foundation's study that "the normalised load factor is 11% at age 15." At all three ages shown above, the histogram of load factors has a mean and standard deviation of 24% ± 7%.
Moreover, by January 2013 I had figured out an explanation of the underlying reason for Hughes's spurious results. I immediately wrote a technical report about this flaw in Hughes's work, and sent it to the Renewable Energy Foundation, recommending that they should retract the study.
I would like to emphasize that I believe the Renewable Energy Foundation and Gordon Hughes have performed a valuable service by collating, visualizing, and making accessible a large database containing the performance of wind farms. This data, when properly analysed in conjunction with detailed wind data, will allow the decline in performance of wind turbines to be better understood. Iain Staffell and Richard Green, of Imperial College, have carried out such an analysis (in press), and it indicates that the performance of windfarms does decline, but at a much smaller rate than the "dramatic" rates claimed by Hughes. The evidence of decline is strongest for the oldest windfarms, for which there is more data. For newer windfarms, the error bars on the decline rates are larger, but Staffell and Green's analysis indicates that the decline rates may be even smaller.
I will finish this post with a graphical explanation of the flaw that I identified (as described in detail in my technical report) and that I believe underlies Hughes's spurious results.
The study by Hughes modelled a large number of energy-production measurements from 3000 onshore turbines, in terms of three parameterized functions: an age-performance function "f(a)", which describes how the performance of a typical wind-farm declines with its age; a wind-farm-dependent parameter "ui" describing how each windfarm compares to its peers; and a time-dependent parameter "vt" that captures national wind conditions as a function of time. The modelling method of Hughes is based on an underlying statistical model that is non-identifiable: the underlying model can fit the data in an infinite number of ways, by adjusting rising or falling trends in two of the three parametric functions to compensate for any choice of rising or falling trend in the third. Thus the underlying model could fit the data with a steeply dropping age-performance function, a steeply rising trend in national wind conditions, and a steep downward trend in the effectiveness of wind farms as a function of their commissioning date (three features seen in Hughes's fits). But all these trends are arbitrary, in the sense that the same underlying model could fit the data exactly as well, for example, by a less steep age-performance function, a flat trend (long-term) in national wind conditions, and a flat trend in the effectiveness of wind farms as a function of their commissioning date.
Monday, November 18, 2013
Now, I'm always interested in powers per unit area of energy-generating and energy-converting facilities, so I worked out the average power per unit area of all three of these, using the estimated outputs available on the internet. Interestingly, all three power stations are expected to generate about 8.7 W/m2, on average. This is at the low end of the range of powers per unit area of concentrating solar power stations that I discussed in Chapter 25 of Sustainable Energy - without the hot air; Andasol, the older cousin of Solana in Spain, is expected to produce about 10 W/m2, for example.Solar energy in the context of energy use, energy transportation, and energy storage in the Phil Trans R Soc A Journal earlier this year, and these three new data points lie firmly in the middle of the other data that I showed in that paper's figure 8 (original figures are available here). .
These data should be useful to people who like to say "to power all of (some region) all we need is a solar farm the size of (so many football fields, or Greater Londons, or Waleses), if they want to get their facts right. For example, Softbank Corporation President Masayoshi Son recently alleged that "turning just 20% of Japan’s unused rice paddies into solar farms would replace all 50 million kilowatts of energy generated by the Tokyo Electric Power Company". Unfortunately, this is wishful thinking, as it is wrong by a factor about 5. The area of unused rice paddies is, according to Softbank, 1.3 million acres (a little more than 1% of the land area of Japan). If 20% of that unused-rice-paddies area were to deliver 8.7 W/m2 on average, the average output would be about 9 GW. To genuinely replace TEPCO, one would need to generate roughly five times as much electricity, and one would have to deliver it when the consumers want it.
Maybe a better way to put it (rather than in terms of TEPCO) is in national terms or in personal terms: to deliver Japan's total average electricity consumption (about 1000 TWh/y) would require 13,000 km2 of solar power stations (3.4% of Japan's land area), and systems to match solar production to customer demand; to deliver a Japanese person's average electricity consumption of 21 kWh per day, each person would need a 100 m2 share of a solar farm (that's the land area, not the panel area or mirror area). And, as always, don't forget that electricity is only about one third or one fifth of all energy consumption (depending how you do the accounting). So if you want to get a country like Japan or the UK off fossil fuels, you need to not only do something about the current electricity demand but also deal with transport, heating, and other industrial energy use.
Sources: NREL; abengoa.com; NREL; solarserver.com; and google planimeter.
Monday, October 14, 2013
Sunday, June 9, 2013
One interesting thing I figured out while working on this graph is that, while the average power consumption per unit land area of the world is 0.1 W/m2, 78% of the world's population lives in countries where the average power consumption per unit land area of the world is greater than 0.1 W/m2 — much as, in a town with some crowded buses and many empty buses, the average number of passengers per bus may be small, but the vast majority of passengers find themselves on crowded buses.
Please follow this "Map of the World" link to see multiple versions of the graph, and to download high-resolution originals, which everyone is welcome to use.
My "Map of the World" graphs are published this year in two journal papers, which I will blog about shortly.
|David J C MacKay (2013a) Could energy-intensive industries be powered by carbon-free electricity? Phil Trans R Soc A 371: 20110560. http://dx.doi.org/10.1098/rsta.2011.0560||This paper also contains detailed information about the power per unit area of wind farms in the UK and USA, and of nuclear power facilities|
|David J C MacKay (2013b) Solar energy in the context of energy use, energy transportation and energy storage. Phil Trans R Soc A 371: 20110431. http://dx.doi.org/10.1098/rsta.2011.0431||This paper also contains detailed information about the power per unit area of solar farms|
Monday, April 8, 2013
On page 131 I wrote:
... hydrogen gradually leaks out
of any practical container. If you park your hydrogen car at the railway
station with a full tank and come back a week later, you should expect to
find most of the hydrogen has gone.
Both of these statements are incorrect.
First, while hydrogen is a very leaky little molecule, it is possible to make practical containers that contain compressed hydrogen gas for long durations. It's just necessary to have sufficient thickness of the right type of material; this material may be somewhat heavy, but practical solutions exist. The technical term used in the hydrogen community for this topic is "permeation", and it's especially discussed when ensuring that hydrogen vehicles will be safe when left in garages. Hydrogen containers are currently classed in four types, and the metallic containers and containers with metallic liners (Types 1, 2, and 3) have negligible permeation rate. However, hydrogen permeation is an issue for containers with non-metallic (polymer) liners (Type 4) which readily allow the permeation of hydrogen. [Source: P. Adams et al]
Second, when discussing the hydrogen vehicle that is left for 7 days, I incorrectly tarred all hydrogen vehicles with a hydrogen-loss brush that applies only to vehicles that store liquified hydrogen at cryogenic temperatures. There are in fact three types of hydrogen storage: Compressed gas (typically at 350 or 700 bar); Cryogenic (typically at less than 10 bar and at extremely low temperature) and Cryo-compressed (at low temperature and at pressures up to about 350 bar). The hydrogen community discuss the "loss-free dormancy time" and the "mean autonomy time" of a system, which are respectively the time after which the system starts to lose hydrogen, and the time after which the car has lost so much hydrogen it really needs refilling. In the US Department of Energy's hydrogen plans, the targets are for a loss-free dormancy time of 5 days and a mean autonomy time of 30 days. Cryogenic liquid-hydrogen systems (such as the one in the BMW Hydrogen 7, which I featured in my book) do not currently achieve either of these targets. (And the reason is not that the hydrogen is permeating out, it's that heat is permeating in, at a rate of 1 watt or so, which gradually boils the hydrogen; the boiled hydrogen is vented to keep the remaining liquid cold.) However, compressed-gas systems at 700 bar can achieve both of these targets, so what I wrote was unfair on hydrogen vehicles. [Source: EERE 2006 Cryo-Compressed Hydrogen Storage for Vehicular Applications]
I apologise to the hydrogen community for these errors.
I will add a correction to the errata imminently.
Friday, December 14, 2012
Just like the original English book, the French translation is available free on-line, and it can be bought at a reasonable price from your favourite retailers.
Thursday, August 2, 2012
Monday, July 16, 2012
Here is an animation showing the evolution of global temperature and the number of sunspots over the last 129 years.
And in case it doesn't display right, here's the final frame of the animation:
And in case it isn't obvious what I think these data show, the message I get from them is that there is no obvious or strong association at all between sunspot numbers and global temperatures.
(Thanks to Iain Murray for free-software help.)
Thursday, March 29, 2012
Sunday, January 8, 2012
Future costs are uncertain, and there are a range of views of the future costs of key technologies such as building insulation, low-carbon vehicles, nuclear power, wind power, carbon capture and storage, heat pumps, and energy storage technologies, and key fuels such as oil, gas, and energy crops. These ranges are reflected in the calculator's cost sensitivity visualizer by allowing the user to change the costs from the default values to higher or lower values, consistent with the ranges that DECC has found in the expert literature. The user can also visualize the consequences of cost uncertainty by selecting the Uncertain choice for any of the costed items. The calculator then shows the range of possible costs for the user's chosen pathway.
All the cost ranges, and the original sources, are explicitly detailed in an open wiki, to which experts are encouraged to contribute updated data. You can click through to the relevant bit of the wiki from any row of the cost-sensitivity page of the calculator. The wiki contains superb interactive visualizations of the cost ranges from the literature. Here's the Offshore Wind Costs Data visualization, for example.
For me, one key message from this tool is the importance of innovation support to bring down the costs of all the technologies that may be important in the future.
Media coverage - The Carbon Plan and the 2050 Calculator have had a little bit of media coverage in the last month, including a nice mention in an editorial in Nature magazine.
Some of the coverage has been so inaccurate, however, that one is forced to conjecture that the authors of two recent pieces in the Telegraph made little effort to check their facts. For example, Christopher Booker perpetuates the twaddle of a blogger who invented the assertion that the 2050 calculator 'had been designed on the assumption that, with wind power, Britain would require much less energy, because we would have become more “energy efficient”, by insulating our homes and so forth'. This is complete twaddle, as anyone who takes the time to actually look at the open-source calculator can confirm. The user is perfectly free to combine any choice of energy-efficiency measures with any choice of energy-supply mix. Yes, the government's published pathways combine "green" energy sources (eg nuclear and wind) with energy-efficiency choices. But the calculator does not 'assume' or 'force' this choice. You can easily make high-fossil-fuel pathways with strong energy-efficiency action, if you want. It's all up to you, as the user. I think it's an awesome piece of "open-source policy development", and I'd like to congratulate the civil servants who did it, and thank all the hundreds of experts and volunteers who have helped them in their work. I really hope this open, factual tool can now be constructively used by politicians and opinion-formers to help public engagement with the issues of long-term energy security and climate-change action.
Wednesday, September 21, 2011
Saturday, March 5, 2011
The panelists and their pathways
Mike Childs: demand highly curtailed and very high renewables
In Mike’s pathway, 20% of primary energy will be imported and emissions will be 80% below 1990 levels in 2050.
Mike’s pathway in more detail
Dustin Benton: demand highly curtailed and high renewables
In Dustin’s pathway, 33% of primary energy will be imported and emissions will be 81% below 1990 levels in 2050.
Dustin’s pathway in more detail
Professor Nick Jenkins: maximum electrification of homes and industry
In Nick’s pathway, 54% of primary energy will be imported and emissions will be 82% below 1990 levels in 2050.
Nick’s pathway in more detail
Mark Brinkley: lots of bioenergy
In Mark’s pathway, 66% of primary energy will be imported and emissions will be 79% below 1990 levels in 2050.
Mark’s pathway in more detail
Duncan Rimmer: mix of CCS, nuclear, renewables and all cars electrified
In Duncan’s pathway, 60% of primary energy will be imported and emissions will be 81% below 1990 levels in 2050.
Duncan’s pathway in more detail
Dr David Clarke: mix of CCS, nuclear and renewables
In David’s pathway, 56% of primary energy will be imported and emissions will be 81% below 1990 levels in 2050.
David’s pathway in more detail
Keith Clarke: high electrification of transport, homes and industry
In Keith’s pathway, 58% of primary energy will be imported and emissions will be 77% below 1990 levels in 2050.
Keith’s pathway in more detail
Mark Lynas: lots of geosequestration
In Mark’s pathway, 78% of primary energy will be imported and emissions will be 80% below 1990 levels in 2050.
Mark’s pathway in more detail
Wednesday, March 2, 2011
My2050 simulator", aimed at engaging a wider audience in this open-source conversation about energy policy.
To celebrate these publications, I'll be on a live Guardian blog on Thursday 3rd March at lunchtime.
Saturday, December 4, 2010
In July 2009 I wrote a post about wind-powered vehicles that travel directly downwind faster than the wind, giving links to videos explaining why this surprising idea is in fact possible.
I've now noticed that in July 2010 a fantastic team of enthusiasts fasterthanthewind.org indeed demonstrated a single-person wind-powered vehicle that goes more than twice as fast as the wind, directly downwind. Don't you just love engineers?!
Friday, December 3, 2010
At the Civil Service Awards last month, the Science, Engineering and Technology Award was won by the DECC 2050 Pathways Team for their work, which I highlighted in July.
From right to left, the photo shows Gus O'Donnell (Cabinet Secretary) giving the award to Katherine Randall, Tom Counsell, Clare Maltby, and James Geddes at Buckingham Palace. (To their left are two staff from the Government Office of Science.)