IS THE UK READY TO RENEGE ON EU CLIMATE TARGETS?
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April 7, 2017 at 06:30PM
IS THE UK READY TO RENEGE ON EU CLIMATE TARGETS?
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April 7, 2017 at 06:30PM
Harrabin’s Latest Renewables Disinformation
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By Paul Homewood
h/t Philip Bratby
From Roger Harrabin:
The world added record levels of renewable energy capacity in 2016, according to the UN.
But the bill was almost a quarter lower than the previous year, thanks to the plunging cost of renewables.
Investment in renewables capacity was roughly double that in fossil fuels, says the report from UN Environment.
It follows news that the cost of offshore wind power has fallen by around a third since 2012 – far faster than expected.
But the report’s authors sound the alarm that just as costs are plunging, some major nations are scaling back their green energy investments.
This, they say, reduces the likelihood of meeting the Paris climate agreement.
The paper is published in conjunction with Frankfurt School-UNEP Collaborating Centre and Bloomberg New Energy Finance.
Ulf Moslener, a co-author, told BBC News: “Things are heading the right way, and the learning and technical costs of renewables have done a large part of their job. But investments are not yet there to meet the structural change agreed in Paris."
The report finds that wind, solar and other renewables added 138.5 gigawatts to global power capacity in 2016 – up 8% from 2015. The added capacity roughly equals that of the world’s 16 largest existing power producing facilities combined, it says.
Recent figures from the International Energy Agency cited the switch to renewables as one main reason for greenhouse gas emissions staying flat in 2016 even though the global economy grew by 3.1 per cent.
As usual with Harrabin, it is what he forgets to tell you that matters. For instance:
1) He always like to talk in terms of capacity, which as we know grossly overstates the contribution of renewables.
The UN report states:
The proportion of global electricity provided by renewables rose from 10.3% in 2015 to 11.3% in 2016.
This figure excludes large hydro. They do not offer a split, but according to BP wind and solar only contributed 4.5% of electricity in 2015, the last year figures are available for.
If the UN numbers are correct, this would suggest that the remaining 5.8% came from burning biomass, small scale hydro, geothermal and marine.
Whenever he writes about renewables, Harrabin always tries to give the impression that we are really talking about wind/solar. This is backed up by photos of windmills and solar panels. (When was the last time he showed a picture of devastated forests, logs on the way to pellet mills, and backlit images of “black steam” coming out of Drax?)
I suspect that if he had quoted the figures for wind and solar, his readers would have been distinctly unimpressed!
2) Another convenient omission is that electricity only accounts for about 15% of total energy consumption.
Renewables therefore only contribute about 2% of total energy.
3) The report also shows the amount of new generating capacity from other sources:
Added capacity from coal and gas is 91GW, almost as great as renewables. Given that modern fossil fuel plants are capable of running at above 80% loading, this new capacity will probably produce twice as much electricity as renewables.
In fact, the new capacity of gas and coal is greater than shown on the graph, as the UN report explains:
Of course, the new coal plants did not directly replace the closed ones. Most of the new ones are in developing countries in Asia and elsewhere, whereas the ones shutting will tend to be in Europe and the US.
4) Investment in renewable energy has been falling for years. Last year, the biggest reduction was in China, India and Brazil – the very countries that are supposed to be leading the way!
In particular, the UN report states that renewable investment in China has fallen by almost a third.
The claim that this is due to lower costs is ridiculous – if costs really were falling so fast, countries would be lining up to increase investment.
5) By far the biggest drop in investment has been in solar power, which makes a nonsense of claims that it is one of the cheapest forms of new power.
And the only reason why investment in wind power has not fallen as much is the subsidies thrown at it by governments in Europe:
Investment in renewables did not drop across the board. Europe enjoyed a 3 per cent increase to $59.8 billion, led by the UK ($24 billion) and Germany ($13.2 billion). Offshore wind ($25.9 billion) dominated Europe’s investment, up 53 per cent thanks to mega-arrays such as the 1.2 gigawatt Hornsea project in the North Sea, estimated to cost $5.7 billion.
6) It is claimed that the cost of renewable energy is plunging. The renewable lobby has of course been arguing this for years, and using it as a justification for further subsidies.
However, quite apart from the extra costs of connection, Harrabin utterly fails to understand that he is not comparing like with like.
Wind and solar power can only provide electricity intermittently, and to a large extent unpredictably. As such, the power they provide is intrinsically worth less then reliable power provided by fossil fuels and nuclear power.
Cost comparisons are therefore totally meaningless.
It is the job of the BBC to report all of the facts, not just the few that support their agenda.
But we have been here before, haven’t we?
Source
The full UN report can be downloaded here:
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April 7, 2017 at 10:30AM
A beneficial climate change hypothesis
via Climate Etc.
https://judithcurry.com
by Rud Istvan
A novel hypothesis on the role of CO2 in the technological transition from hunter/gatherers to sedentary agriculture.
This guest post has been formulating for several weeks. It summarizes a fascinating hypothesis in a guest post by Don Healy at WUWT some weeks ago, albeit posted for a different purpose. Credit where due; this is not my idea. It is merely my formal hypothesis formulation of his original insight, involving a lot of casual research outside my wheelhouse. Yet another Climate Etc. learning experience.
Abstract
It has been known for decades from archeology that the incredibly important technological transition from small bands of hunter-gatherers to sedentary agriculture (wherever possible) took place about 10,000 years ago. This transition eventually enabled specialization of labor, towns, cities, and all of modern civilization. This technological transition happened all over the world, in many ecosystems, with people geographically isolated, so independently developed. It was spontaneous, similar, roughly simultaneous, and ‘finished’ by about 9000 years ago. There are many archeological hypotheses as to how, why, and most importantly for this post, when. None satisfactorily explain the rough global similarity and simultaneity. We know from ice cores that the atmospheric CO2 level was ~180-190ppm at the last glacial maximum (LGM). We know that it was ~280ppm preindustrial, and that that level had persisted for millennia in the present Holocene interglacial. The natural ocean mediated rise in CO2 from near plant starvation levels to pre-industrial levels fully explains the similar and roughly simultaneous emergence of sedentary agriculture globally, as a simple function of plant primary productivity, foodshed dimensions and natural human behaviors.
Hunter/gatherer to sedentary agriculture transition
There are many aspects to this crucial transition, backed by thousands of science papers. There is no simple, single narrative, although I develop an overarching one here at the risk of oversimplification.
Domesticated dogs (Canis familiaris) emerged from wolf progenitors (Canis lupus), probably twice. First domesticated in Europe about 16000 before the current era (BCE, and note this term itself conveys inherent timing uncertainty). And then, based on DNA evidence, dogs were domesticated a second time in Asia about 14000BCE. Both times likely as a result of scavenging cohabitation, with domestication many millennia before sedentary agriculture emerged.
It is also likely that at least some animal domestication occurred before true sedentary agriculture emerged. This is easy to envision with grazing animals. Cattle were domesticated from wild aurochs perhaps 11000BCE in Meospotamia. Sheep were domesticated from wild mouflons about 11000BCE—and new genetic studies suggest not once, but twice, once in Asia and once in Mesopotamia, both about the same time BCE. (Pig domestication follows as an example of animal domestication as a consequence of sedentary agriculture.) All that was necessary is that the ecological foodshed was within a reasonable distance of ‘home base’ for the shepherds tending the grazers. Domestication would have proceeded in two steps. First, simply taming wild animals so they weren’t dangerous to humans. This is easy to imagine by capture near birth while hunting the mother for meat. Second, selecting for desirable domesticate traits (like docile, else eaten). So animal domestication is a process. Jarod Diamond says it took place before (grazing) or in parallel with (pigs) the development of sedentary agriculture and domesticated crops.
The previous paragraph on grazing domestication introduced the idea of a foodshed. It is central to this climate/agriculture hypothesis, and borrowed from the idea of a woodshed, central to planning dimension lumber and plywood mill capacity in the forest products industry. A ‘shed’ is like a river catchment basin. The foodshed concept is quite simple. A hunter/gatherer band has to forage over an area that during a year (seasonality) provides enough food to sustain that band. A typical band might have been <30-50 individuals based on present day hunter/gathers. The poorer the productivity in the surrounding environment, the larger the band’s foodshed area was. Lower plant productivity means not just lower plant food availability for humans, it means less hunted animal meat from herbivores from other plants.
As a familiar foodshed example, the Neolithic Plains Indians were hunter/gatherers because the conditions for sedentary agriculture never emerged despite agriculture being practiced in the American Southwest, the Mississippi River valley, and the East Coast. The high North American plains blossom in spring from winter snowmelt. But by late summer they are brown, desiccated, dormant grasslands. The bison that grazed those plains had to keep moving to find sufficient food year round since it only grew in spring/early summer. So did the Plains Indians that depended primarily on bison for food, shelter (teepee hides) and dung fire fuel. Their foodshed was very large. Their nomadic ways evolved technical innovations such as the travois and the teepee. But not sedentary agriculture, despite almost certain cultural exposure to it.
Sedentary agriculture transition
About 11,000 year ago, things started changing all over the world. Sedentary agriculture began to to emerge. The most interesting thing is when the first wave of this fundamental technological revolution ‘ended’ with clearly domesticated suites of plants, animals, implements, and permanent settlements. Globally that was about 9000BCE. We will provide specifics in what follows.
The ‘end’ at about 9000 BCE is of course subject to many uncertainties. The definition of plant domestication isn’t precise (following paragraphs give examples). The archeological indicia of domestication are subject to interpretation. For example, is that Neolithic stone tool the cutting edge of a scythe? Is that a grain storage container or just another big pot? (In north China, the archeological evidence is incontrovertible. At Cishan, storage pits were unearthed containing 50,000kg of domesticated common millet radiocarbon dated to between 10,300 and 8700BCE.)
Taming/domestication of grazing animals is only a partial agricultural indicator, for reasons already discussed. The domestication of plants is a better indicator, and also one more archeologically certain. In general, like animals, neolithic plant domestication took two identifiable steps.
The first was indehiscense. That means formerly foraged wild plants lost their ability for natural seed dispersal. Taking a plant category as an example, it meant the grains derived from grasses like emmer (wheat) did not shed their seeds as readily to natural wind and rain when ripe. This indehiscent property would have emerged and strengthened naturally. Hunter/gatherers gleaning what was left of ripe wild emmer would only have gathered seeds from plants already inclined to be indehiscent; the rest was more readily already lost. And every year, human driven selection would have increased that indehiscent tendency.
The second was human selection for productivity. Larger seed size is the typical archeological example. The extreme is maize, human selected from wild progenitor teosinte. Some examples are illustrated below. An exception was the Papau New Guinea domestication of bananas, where larger fruit size was also human selected for smaller seed size.
Simultaneous transitions
At several places around the world, the evidence points to the initial transition to sedentary agriculture being ‘completed’ about 9000BCE—despite completely different ecosystems. In Mesopotamia, wheat and barley. In China, millet and rice. In the New Guinea Highlands, taro and bananas. In Mexico, maize from teosinte. In southern Peru/northern Bolivia, the potato.
Take the example of the crop ‘trinity’ of central and north America, maize (corn), beans, and squash. Nutritionally, these together provide all 20 essential amino acids. So, from a modern nutritional perspective, the ‘three sisters’ explain the huge population growth of Peruvian Incans, Yucatan Mayans, and Mexican Aztecs without an abundance of domesticated animals for meat.
Modern genetic analysis proves beyond doubt that maize originated from the Mexican highland C4 grass teosinte, the original domestication transition finishing about 9000BCE. This is the most famous phenotypical human selected change of a wild type precursor plant.
Modern genetic analysis of the common bean (P. vulgaris, another of the Amerindian ‘trinity’ of maize, beans, squash) shows it emerged at least two separate times (and possibly three) nearly simultaneously. Domesticated P. vulgaris began independently in Peru, (landrace kidney beans), in Mexican highlands (landraces pinto and red beans), and probably once more in lowland MesoAmerica (landraces black and navy beans), all around 9000BCE (depending on archeological site and landrace, anything between 10000BCE and 8000BCE). These landraces are all genetically similar, varying mostly in phenotype. How the phenotypes could vary so much without much underlying genetic differentiation is now understood thanks to growing knowledge of epigenetics.
The third of the Amerindian trinity, squash (C.papo, predecessor to the pumpkin) was also domesticated before 8000 BCE.
As a final near simultaneous timing example, hogs (pigs) are non-foraging so have to be fed domesticated plants. The pig was domesticated from the Eurasian wild boar (Sus scrofa) of which there are several subspecies that can be distinguished by variation in mitochondrial (maternal) DNA. Based on analysis of present day wild and domestic types, domestication happened independently in the Near East and in China from at least two separate wild boar subspecies at about the same time ~9000BCE. The dating is quite solid since based on mDNA mutation rates (a new standard ‘clock’ method). Darwin knew there were two basic domestic pig types, but not why. The Asian domestics were introduced into Europe for further cross breeding in the 18th and 19th centuries (the ‘subsequent introgression’ part of the linked paper title).
Similar domestication timing around the world despite very different ecosystems and agricultural crops cannot be a coincidence. Nor can it be from cultural diffusion of agricultural knowledge; at that time, these areas were geographically isolated.
Archeological explanations for the transition
There are several ‘explanations for this Neolithic revolution in technology. Wiki has a decent overview.
The ‘oasis’ theory has largely been discredited.
The ‘hilly flanks’ theory might explain Mesopotamia, but not Borneo.
The ‘stable Holocene climate’ theory is falsified by the Younger Dryas.
The ‘Younger Dryas’ theory might explain Mesopotamia. But not Bolivia or Borneo.
The ‘it wasn’t simultanous’ theory depends heavily on dogs and grazing animals while overlooking much of the solid evidence for near simultaneity in plants and foddered animals like hogs or chickens.
In short, it appears no one had provided a good explanation for simultaneity before Don Healy’s post.
CO2 explanation for Simultaneous Transitions
Ice cores suggest that the CO2 concentration at the last glacial maximum (LGM ~21,000BCE) was 180-190ppm. That compares to ~280 ppm pre-industrial and ~400 ppm now (with noticeable greening over the past 35 years). The change in CO2 concentration from the LGM to the Holocene is easily explained based on Henry’s Law and reduction in warming ocean dissolved CO2. The ice cores show that the CO2 rise lagged temperature rise by about 800 years, the period of the thermohaline circulation.
For C3 photosynthetic pathway plants, that LGM CO2 level is quite low, hindering their productivity. About 85% of all plant species are C3. All trees, fruits, vegetables, and most food crops are C3. The only C4 food crop exceptions are maise, millet, sorghum, and sugarcane. There is an excellent long review paper by Gerhard in New Phytologist (2010) on this general topic. The paper describes experiments with various C3 plants over a growing season at the pre-industrial CO2 280ppm and at 150ppm, below the LGM level. On average, at 150ppm the primary C3 plant productivity was reduced an average 92% as measured by dry weight biomass.
So at LGM CO2 levels, foodsheds would have necessarily been quite large, since plant photosynthetic productivity was low. Sedentary agriculture would have been impossible. As CO2 concentrations rose, foodsheds shrank. Eventually they would have shrunk to the point that permanent settlements with food storage became possible compared to nomadic temporary shelters, with food resources perhaps within just a couple days walk. At that point, the near simultaneous emergence of sedentary agriculture around the world–despite very different ecosystems–became inevitable.
That has proven to be very beneficial. Climate change increased natural atmospheric CO2, which in turn enabled agricultural technology development. Which in turn enabled modern civilization. Which enabled exploitation of fossile fuels. Which further raised beneficial atmospheric CO2. The current further greening documented by NASA is also beneficial, with crop yields rising while needing less water. The opposite of alarming.
Moderation note: As with all guest posts, please keep your comments civil and relevant.
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April 7, 2017 at 07:23AM
Questions on the rate of global carbon dioxide increase
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Guest essay by Robert Balic
A summary of a problem with estimates of the average concentration of carbon dioxide in the atmosphere and questioning of how it is possible that the rate of increase correlates well with global temperature anomalies.
I saw an interesting plot in the comments of of WUWT a while ago. It was based on the work of Murray Salby who pointed out the strong correlation between the concentration of carbon dioxide in the atmosphere (NOAA ESRL CO2 at Mauna Loa) and the integral of mean global temperature anomalies. How well the CO2 levels correlate with various temperature anomalies can be seen in this plot of the derivative of CO2 levels with respect to time (rate of CO2 level increase) alongside some estimates of global temperature anomalies – HadSSTv3 SH (southern hemisphere sea-surface temperatures) and RSS (lower troposphere temperatures from satellite observations).
The first time that I saw this, I thought that what was meant by “derivative” was an estimate from differences between consecutive months but in ppm per year (as time is in years) so I was twelve times as confident that something was amiss as I should have been. Even after realizing that the results were in ppm per month, I thought that the results were still implausible. That changes in sea surface temperature would have an effect on CO2 levels is plausible but to correlate so well and then to be measured so precisely in order to be able to see the correlation did not seem possible.
In the above plot, the CO2 levels in ppm per month were scaled by 3 to compare with temperature anomalies. If I were to use ppm per year, then I would divide by 4 to do the same comparison iehey are not the same dimensions so the scaling is irrelevant. The data clearly needs to be scaled and also offset to fit each other well so by good correlation I am referring to the way they differ from a line of best fit after scaling to have the same slope.
I have put this out there in comments on blogs and received few replies. One that I need to mention is the claim that the derivative values are some sort of concoction and are so small that they are negligible, about 0.03% of CO2 levels. I don’t know why I need to point this out but an average of 0.125 ppm per month is the rate of change of CO2 estimated using the same method since even Newton was a boy and is equal to 90 ppm per 60 years. Its not negligible but there is the question of whether the uncertainty in measurements are too large to see fine trends over a period of a few years (and you should never multiply the quotient of two values of different dimensions by 100 and call it a percent).
Eyeballing the graph, it appears that the data needs to be very precise in order to see a correlation and a little bit of math makes things clearer. Rather than using the above derivative of smoothed data (12 month moving mean), I took the CO2 levels from woodfortrees.org and the difference between values 13 months apart. Essentially the same with the results being in ppm per year.
There is a good fit to the global temperature anomalies, especially RSS lower troposphere after 1990 (and to HadSSTv3SH before 1990) when the rate of change of CO2 levels is scaled by 0.26 and offset by -0.30. The mean absolute differences between the two is 0.13 and the standard deviation (SD) is 0.17 but varies from 0.08 to 0.2 for blocks of 1 year .
Using the lower value, this is consistent with an uncertainty in GTA of 0.1 K and in monthly CO2 levels as low as 0.34 ppm as calculated using
0.26^2 x 2ΔCO2^2 + ΔT^2 = (2 x 0.08)^2 where ΔCO2^2 and ΔT is the random error of CO2 levels and GTA which would be 2SD of repeat measurements.
This assumes that when differences are at a minimum that it is solely due to random error in the two measurements but its worth remembering that HadSSTv3NH differs much more than this from the rate of CO2 change so there are obviously other errors. Its also a stretch to assume perfect correlation of the real values, especially since its claimed that CO2 levels have increased due to human emissions and the latter have been at a steady rate for the last three years. There is also the question of why such a good correlation with SH sea-surface temperatures and not NH, and why should the correlation be so perfect when things like changes in ocean currents should have a large effect on how much is sequestered into the depths of the oceans.
So unlike I first thought, the precision didn’t need to be ridiculously good to see the correlation but this is still to good to be true.
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April 7, 2017 at 07:01AM