JoNova

A science presenter, writer, speaker & former TV host; author of The Skeptic's Handbook (over 200,000 copies distributed & available in 15 languages).


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Love those 30 year old coal and nuclear plants — nothing gives cheaper electricity

The gold-plated stars of our national grid are the old coal plants we’ve built and paid off.

A US report (thanks Lance) shows how fantastically cheap and bountiful old coal and nuclear plants are. The LCOE or the Levelized Cost of Electricity includes the costs of the concrete, turbines, car parks and coal, plus the maintenance and salaries. It reveals that thirty year old, and even fifty year old coal plants, are the gift from past generations — enormous infrastructure, built and paid for, and ready to churn out bargain electrons. Or in crazy-land, ready to be blown up.

Look how long it takes to pay off the capital cost of building them (the red sector in the graph), and look how wonderfully cheap that electricity is from a 30 year old plant. Watch the pea. All those “investigative news stories” that compare the cost of building new coal to the cost of solar or wind are hiding the most brilliant and essential assets on our grid. Reopen Hazelwood now. (!)

Both sides of politics are choosing to destroy the family jewels in the hope of controlling global weather.

LCOE, Coal Plant, EIA, Graph.

….

From the report by Stacy and Taylor, of the Institute for Energy Research (IER):   

Most existing coal, natural gas, nuclear, and hydroelectric generation resources could continue producing electricity for decades at a far lower cost than could any potential new generation resources.

If anyone sees a 30 year old nuclear plant on ebay please call Josh Frydenberg:

LCOE, Nuclear Power, Graph, EIA.

…LCOE, Nuclear Power, Graph, EIA.

These old plants just go and go

Below, see the real world data on capacity factors (this is a reflection of how well that plant keeps working as it ages). There is very little decline, and maintenance costs are small (especially compared to fixing gears and wings in giant towers in windy locations far out to sea and that break after just a few years.)

These old US plants keep kicking along for decades without a loss of capacity:

Capacity Factor Graph, electrical generation, nuclear, gas, coal, hydro.

In the US,  these plants keep working as they age.

Old coal plants in Australia are working at even higher capacity factors

The cheap old brown coal plants in Victoria were running at 90% capacity year in, year out. Though here, the capacity factor partly reflects pagan energy policies. The carbon tax dinted the capacity factor of brown coal in 2012-2014. The RET takes a growing bite.

In the US coal competes with nuclear plants and cheap shale gas. In Australia, nothing bar anything, competes with Victorian brown coal (at least in a free market) which is why it is run virtually flat out all the time.

Hazelwood is a national treasure.

Thanks to commenter Lance.

Keep reading  →

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BOM homogenization errors are so big they can be seen from space

It’s just not cricket. And in so many ways.

Shame to let a perfectly good dataset go to waste… Australian data comes from some of the longest stations running in the Southern Hemisphere; it could be useful. Instead we get more evidence here that the BOM’s magical and secret homogenization adjustments can take poor data and spread false signals into better data. Homogenisation errors are already visible in a site-by-site analysis, but this shows the problems may be so big they affect averages across the whole of Australia, and we can detect them with satellites.

Tom Quirk continues comparing the satellite record of Australia with the BOM surface version. Previously, he (and for the record, Ken Stewart in 2015) showed that some discrepancies are due to the effect of heavy rain or drought. But now he looks further and finds that not-so-coincidentally, the largest gaps and most “inexplicable” differences occur in the mid nineteen-nineties, the same years the BoM shifted from using old large Stevenson screens to electronic thermometers. Around the same time, the large screens were often also swapped for much smaller ones too — like double jeopardy for data. Oddly, spookily, the BOM makes many adjustments to data during those same years that are vaguely referred to as “statistical” adjustments (rather than specifically called site moves or screen changes), and it is exactly these kinds of adjustments that are implicated here. (All together now with the cliche du jour: hullo lies, damned lies and “statistics”?)

The big clue comes from correlations – on a yearly average the two datasets look very similar, but it’s artificial — on a monthly scale a few key correlations fall apart.

You might think that changing instruments should be no big deal — the BoM just has to run both types of instrument side by side for a couple of years and analyze and adjust accordingly. But as we’ve heard before, they claim they do that, but they won’t publish it, and when skeptics like Bill Johnston ask, they admit they’ve deleted the data. Instead of using this simple, obvious approach, the BoM “corrects” the record by getting data from another statistically selected thermometer which may be hundreds of kilometers away and which may also have been changed/shifted/degraded/watered/cleared or had a ten-lane highway installed next door.Edit

Tom Quirk implies homogenization is a process that can be improved but I think it should be thrown away — we need to start from scratch. We need a proper historical, documentary analysis of each and every site first (and a full independent audit of the BoM). There is no point blending bad data with good. False signals are smeared across real data. Homogenization is vandalism.

If the Australian Bureau of Meteorology’s work was a million-dollar scandal involving celebrities breaching international rules and hiding secrets down their pants, they’d be on every news talk show and problems would’ve been fixed ten years ago. Instead it’s a billion dollar scandal, international guidelines are blitzed, and meh.

Jo

h/t to both Tom and Barry C for the cricket scandal comparison.

————————————————————————————–

Guest Post by Tom Quirk

Comparison UAH and BOM temperatures and homogenization Part II

(Part I: Mystery solved: Rain means satellite and surface temps are different.)

Near-ground temperatures in Australia have been subject to a process called homogenization. This process adjusts temperatures at a given location to take into account nearby temperature measurements as preparation for area estimates of temperature. Fortunately the satellite measurements of the lower troposphere (UAH) provide an opportunity to audit the Australia-wide near surface measurements of the BOM. Figure 1 shows a comparison with a correlation coefficient of 83 +/- 5 % which is very respectable.

Graph, UAH, temperatures, Australia, BOM.

Figure 1: UAH and BOM Australian annual temperatures where the BOM anomalies have been normalized to the same mean value as that of the UAH measurements

However when the comparison is made on a monthly basis the correlation coefficient falls to 68 +/- 2 %. That detail is shown in Figure 2.

Graph, UAH, temperatures, Australia, BOM.

Figure 2: UAH – BOM Australian monthly temperature anomaly correlation for a 13 month sliding average correlation coefficient.


The range of values for the correlation coefficient is from a maximum of 91% to a minimum of -8%. Curiously, the loss of correlation occurs in the period 1995 to 1998 at the same time as the automatic weather stations were introduced.

This loss of correlation will be examined firstlyon a year by year basis and then on a month by month basis from 1979 to 2017.

12 monthly measurement correlations

The first test is to look at the 12 monthly measurement correlations year by year to see if any particular years stand out. Figure 3 shows extremes from a high correlation coefficient of 88% in 1999 to a low of 12% in 1996. The average 12 month correlation coefficient is 64% to be compared with the correlation coefficient of 83% for the 39 year annual time series.

Graph, UAH, temperatures, Australia, BOM.

Figure 3: 12 month correlation coefficients on a year by year basis. The correlation coefficient for the 39 year time series is 68%


The temperature anomalies for the two years with the lowest correlation coefficient, 1996 and 1997 are shown in Figure 4. There are very large temperature anomaly differences of between 1 and 2°C.

Graph, UAH, temperatures, Australia, BOM.

Figure 4: Temperature anomalies for the two years with the lowest correlation coefficient, 1996 and 1997

1979 to 2017 measurement correlations month by month
The second test is to look at the 39 year measurement correlations month by month to see if there are particular months where the two datasets diverge. This can be seen in Figure 5 Left and shows most months have a decent correlation coefficient above 70%, peaking at 88% in September. But things come apart in February and December when correlations fall to 40%. In the ten year periods of 2007 to 2017 and 1979 to 1989, the December correlation falls to -40% (Figure 5 Right).

 

Graph, UAH, temperatures, Australia, BOM.

Figure 5: Left 39 year measurement correlations month by month and Right correlations split for 1979 – 1988 and 2008 – 2017

 

Scatter plots of low-correlation months also show some significant differences (Figure 6). Note that there are quite different trend lines for December as shown in Figure 6 Right that reflect the positive and negative correlation coefficients in December shown in Figure 5 Right.

Graph, UAH, temperatures, Australia, BOM.

Figure 6: Scatter plots and trend lines for low correlation months.  Left February and March and Right December 1979 – 1988 and 2008 – 2017.


Source of low correlations from ACORN-SAT data

The Australia-wide temperature is constructed using ACORN-SAT temperatures. ACORN-SAT is the official dataset used to report on climate variability and change by the Australian government, CSIRO, and also university researchers.  Adjustments are made as step-changes, which are promulgated backwards in time. Temperature measurements are homogenised, that is to say, adjusted by reference to nearby temperature measurements.

The reasons for the temperature adjustments for the period 1979 to 2017 are listed below with the number of changes made for each class of adjustment. Note that there is no supporting observational evidence for the changes when they are described as “statistical” adjustments.

Adjustment

 

Statistical

 91

Move

 80

Merge

 52

Move/screen

  2

Screen

  2

Site env

  3

AWS

  2

Total

232

In addition there are seasonal adjustments in 65 of the 232 all-year adjustments:

Seasonal changes

Summer

Autumn

Winter

Spring

Dec Jan Feb

Mar Apr May

Jul Jun Aug

Sept Oct Nov

Total

20

11

14

20

Statistical

3

1

1

3

 

The years in which adjustments are made is shown in Figure 7. The period 1993 to 1998 shows a peaking in adjustments and this is the period when the UAH – BOM 12 monthly correlations are at a low…

Graph, UAH, temperatures, Australia, BOM.

Figure 7: Years in which adjustments are made and the type of adjustment.


The period 1993 to 1998 is when the automatic weather stations (AWS) replaced mercury and alcohol thermometers. Consequently sites were moved and time series merged.

This would explain the loss of correlation between lower troposphere and near surface temperatures.

The month in which adjustments are made is shown in Figure 8. The changes are made on the first of the month so the temperature adjustment appears in the previous month. So a 1st January change in 1995 is added to all preceding days, months and years starting at 31st December 1994.

Graph, UAH, temperatures, Australia, BOM.

Figure 8: Months in which adjustments are made and the type of adjustment.


The monthly distribution of adjustments explains the loss of correlation in December (Figure 5). Looking at the years when adjustments were made (Figure 7), there are no statistical adjustments for the period 2008 to 2017, and the correlation coefficient for December is similar to the earlier months (Figure 5 Right). But there are 58 statistical adjustments from 1989 to 2006, all of which will reduce the December correlation found for 1979 to 1988, and in that period there are a further 33 statistical adjustments and the correlation coefficient falls to -40% (Figure 5 Right). However the low correlation coefficient for February increases from February to July due to the interaction of rainfall with evaporative cooling lowering the surface temperatures over a period of months, and thus lowering the correlation coefficient for the UAH – BOM comparison.

The years in which seasonal changes are made is shown in Figure 9. There is a peaking of adjustments in the period 1993 to 1998 when the automatic weather stations (AWS) replaced mercury and alcohol thermometers.

Graph, UAH, temperatures, Australia, BOM.

Figure 9: Years in which seasonal adjustments are made and the seasons


This would add to the loss of correlation between lower troposphere and near surface temperatures.

Conclusion

There is a clear connection between the loss of correlation between UAH and BOM temperatures and increasing adjustments seen in the ACORN-SAT temperatures. The sources of the differences are likely to be due toinstrument changes and particularly statistically derived temperature step changes.

The analysis shows that the homogenization process applied to the construction of the Australia wide temperature is probably adding to the flaws in the datasets rather than correcting for them.

It would be useful to see whether improvements are possible by excluding statistically derived shifts and with a careful approach to step changes. Further a comparison with the USA 48 states near ground and troposphere temperatures might give rise to some further improvements.

BACKGROUND:

The BOM trend is higher than UAH but the difference is not significant (as seen in the last post on this topic last week)

BOM annual temperatures are averaged from 1979 to 2017 and normalized to UAH average, a -0.33 °C adjustment. The temperature increases are:

UAH   0.176 +/- 0.036 °C per 10 years

BOM   0.154 +/- 0.048 °C per 10 years

There is no significant difference in trends at 0.022 +/- 0.030 °C per 10 years.

It should not come as any surprise,
That Met. Offices homogenize,
To let data read high,
So that temps. will comply,
With what governments authorize.

–Ruairi

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Satellite going AWOL at 28,000km/hr — tracking that Chinese stray machinery

The ESA blog has this trajectory “prediction” (below). Given that the window of reentry stretches across a day and the object in question is doing 28,000 km per hour, we can say for sure this will hit Earth. (Or rather, some small part of the satellite that survives the burning up process will touchdown somewhere). Two weeks ago Roy Spencer predicted it will probably hit “the ocean” and explained why it is so difficult to estimate the actual impact point. It is circling the Earth every 89 minutes.

UPDATE: This was China’s first space station. Launched in 2011. It has two sleeping spots for astronauts, and was visited twice.  View this as a mark of the rise of China. Though it also says something that China lost control/contact with it in March 2016. Tiangong-1 is only 8,500 kg. The Russian space station Mir was 120,000kg.

UPDATE #2: 3pm  Watch the LIVE track at N2Yo (overloaded)  or at SATview or  Heavens Above.

UPDATED #3: Narrowing the risk map.  Dr Marco Langbroek‏ 

Aerospace estimate is April 2 at 02:00 UTC ± 7   0:18 UTC ± 2 hours.  (Current UTC time is 5:10pm, so seven-ish hours to go, more or less.)  USA and Australia now unlikely. Twitter discussion is @Tiangong1
 
UPDATE #4: With the new estimates of UTC 0:30 (Aerospace) and UTC 0:56 (satview) it may have already come down, or not. Langbroek warns people not to rely on the tracking sites which are calculating the orbit path, but will continue to show the satellite for several hours after it is gone. Apparently actual data on the satellite is a bit rare! There are some other satellites which are watching for the infra red signature, but if Tiangong goes down in a remote location we may not know for a few hours. The absence of a sighting may be the first confirmation. People in Ukbekistan/Turkmenistan should have seen it in the last half hour? Does anyone there have twitter?
UPDATE #5: Rakesh‏ @densaer  At this point we can refer to #Tiangong1as “Schrodinger’s Space Station.” Since nobody knows whether it’s up or not at this point, it has entered a superposition only resolves when someone puts eyeballs or radar on it.
UPDATE #6: China’s official news and the US Joint Force Space Component Command are reporting that it went down at 0:15UTC over the Southern Pacific (about an hour ago). The crash zone was expected to cover 2,000km, but apparently none of the 7 billion people on Earth saw it. And if you thought you might get 30 minutes warning that space junk was about to hit your town…
Risk Map. Tiangong.

Possible last orbital routes are likely along these tracks.

Keep reading  →

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And a Happy Easter to you

 

Wishing everyone good health and good times…

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Surprise: Australia closed a cheap coal generator and electricity got 85% more expensive

Last year one of our largest coal power plants suddenly closed, with only five months warning, catching the market by surprise and taking out 5% of our cheapest generation. (This kind of improbable anti-free-market feat shows just how screwed our national market is). The Australian Energy Regulator (AER) has looked at the effect the closure of Hazelwood had on electricity prices and concluded that closing cheap brown-coal plants and replacing them with black coal and gas will make electricity prices rise. This will come as no surprise to anyone who can count to 100.

Dan Harrison at the ABC reports:

A year on from the closure of the 1600 megawatt-sized plant in the Latrobe Valley, the report from the Australian Energy Regulator found wholesale prices in Victoria were up 85 per cent on 2016.

Because electricity retailers use hedging for wholesale prices, the rise in retail prices is still feeding through. In the wash, the wholesale increase is expected to add 16% to retail prices this financial year compared to last year. After that, through some miracle, the AEMC expects prices to come back down from Exorbitant to Slightly Lower Than Exorbitant in the next two years thanks to an increase in renewables.

For most of the history of the Australian National Grid prices averaged $30-$40/MWh. Now they are twice that. (A drought caused the bump in 2007, the carbon tax caused the hump from 2012-2014.)

Quarterly spot prices, Australian national Grid since 1999

Quarterly spot prices, Australian national Grid since 1999 | Source: AER. The arrow marks the spot after Hazelwood closed.

We learn a few things about the seismic jump in prices in Australia that occurred last year:

In the Australian national grid the prices for everyone are set by the highest successful bidder. Without enough brown coal fired generation to set the price, the price jumped up to the next highest bidders. The remaining brown coal generators were working flat out, no more to give, so Australians needed to draw on supplies from the more expensive black coal and gas to set the final bid prices. (And most electricity generators can’t have been too unhappy about that.) In addition, the commodity price of both black coal and gas jumped — in part surely due to the extra demand for these to replace the brown coal that would have been burned — and prices became, not just a bit higher, but a lot higher.  We can blame those commodity prices but if we’d had the flexibility to use cheap brown coal instead, who cares?

Whole flows changed: Victoria used to be a powerhouse, but stopped being a net exporter of electricity and started to be a net importer. Luckily, South Australia produced so much wind power it became a net exporter of electricity for the first time in years. Yet somehow, despite that gift of all this “free” and subsidized wind electricity,  prices still went up. Go figure. ;-)

SA Wind generation 2015,2016,2017, AER, Graph.

All the extra wind power in late 2017 …   | Graph: Jan 2015 to Jan 2018, GWh

The signs are not good that there is some loophole or tweak that will fix this mess. Ominously, the AER did not find much volatility in pricing. The high averages were not due to freak high spikes, but were caused by relentlessly higher averages. Also ominously, even though the states pay separate rates, the interconnectors “worked so well”, that losing a cheap plant in Victoria affected the price in all the states. Queenslanders paid more because of choices made by distant people they didn’t elect. In this conglomerate market influenced by five state and one federal government the incentives fold like an origami wallet.

Naturally, if any state was free to dump the RET and stop the market-destroying effect of the renewables subsidies, investors might be able to inject some cheap energy back into the grid. At the moment, the screaming Banshee price signals that call for cheap generators have been sealed in bureaucratic bunkers.

On the upside, the ABC reports that the closure of Hazelwood has “slashed” a piddling 4.1 mT of carbon “pollution” which might otherwise have improved our crop yields. At a cost of billions, this will keep the world 0.00 degrees cooler.

Victorian gas shortage only going to get worse

Victoria, which now doesn’t profit from exporting electricity, cannot profit from increasing gas exports at the new higher gas prices either. Victorian gas fields are running out and the government has banned people from exploring for new ones.

In a separate report, the Australian Energy Market Operator (AEMO) predicts there will be a shortfall of gas in Victoria, due to the depletion of offshore gas fields in Gippsland and Port Campbell.

AEMO expects the state’s gas production to decline from 435 petajoules in 2017 to 187 petajoules in 2022, resulting in a shortfall of 19 petajoules for that year.

 Victoria is thus, the new “crash-test-dummy” of renewable-government.

The AER report on the closure of Hazelwood:

The problem isn’t that complicated — less of the cheap stuff means more of the expensive stuff.

The increased output of gas and black coal fired generators coincided with increased fuel costs for some of these generators. As highlighted in our NSW report11 , NSW generators’ black coal costs increased from late 2016, particularly under short term contracts. NSW coal fired generators were also facing problems with coal supply during 2017, which drove higher offers from these generators. At the same time, there have been increases in gas prices in recent years affecting gas-fired generators. Our review also found that brown coal plant set the electricity spot price in Victoria far less often following the closure of the Hazelwood power station. Higher fuel cost generators set the price more often, in particular gas fired and hydro generation, while NSW and Queensland black coal generation continued to set the price a significant proportion of the time, but at much higher prices. Our key finding therefore is that the exit of Hazelwood removed a significant low fuel cost generator which was largely replaced by higher cost black coal and gas plant – at a time when the input costs of black coal and gas plant were increasing. These factors in turn drove significant increases in wholesale electricity prices. Annual average wholesale electricity prices in Victoria in 2017 were the highest they have been since the commencement of the NEM. South Australian average prices were also consistently high.

 

Graph, AER, Electricity prices, set by gas, black coal, hydro in 2018.

Graph, AER, Electricity prices, set by gas, black coal, hydro in 2018.

 Significant? Ho yes. Australia changed net generation type and flow:

Victoria changed from being a net exporter of relatively cheap brown coal generation, to being a net importer. Flows from Queensland into NSW (and then through to Victoria) increased significantly as Queensland black coal generators increased output in 2017. South Australia also became a net exporter to Victoria, where previously it was a net importer. More generally, the interconnectors between the regions were constrained less often, resulting in greater price alignment between regions

What a difference a small deficit in brown coal generation makes

After Hazelwood (see the lighter columns) Australians had to rely on a different form of generation to set the price.

Ownership in the South Australian and Victorian markets is concentrated, with a few, largely vertically integrated participants controlling a significant proportion of capacity..

 The AER did not find evidence that the players were gaming the system much or doing “opportunistic” bidding or withholding generation. But there was less bidding at under $50/MWh, and more bidding at $90-$100. In the past it was spikes of high wholesale prices that drove averages up, this time there was less volatility, and more just plain old constant high prices. I don’t think this can be fixed any other way than the utterly obvious.

 Spot the problem — 3500MW of coal closed down and was replaced with 2500MW of unreliable wind and solar:

In the five years prior to Hazelwood closing there has been around 5000 MW of capacity withdrawn from the NEM, 3500 MW of which was coal generation. In NSW around 1900 MW was withdrawn mainly due to Wallerawang and Munmorah power stations (1600 MW combined capacity). In South Australia the Northern and Playford B power stations exited (740 MW combined capacity), while in Victoria Energy Brix and Anglesea (355 MW combined capacity). Over the same period there has been around 2500 MW of new capacity added to the NEM, 2100 MW of wind and 240 MW of solar. Around 1600 MW of this wind capacity is in Victoria and South Australia along with a 100 MW battery.

The capacity factor for wind is about 30% and for solar is about 20ish percent, meaning the real capacity added was more like 600MW, plus or minus 2000MW.

Curiously, about 750MW of previously uneconomic withdrawn power, which was mostly gas plants, made a comeback.

Look at these interesting graphs: What’s the cost of brown coal, black coal and gas power?

It’s difficult to say exactly what generation costs, but these graphs show the amount of time these different power sources were setting the price and what that price was. Worth an eyeball. Hazelwood closed at the end of Q1 2017. Prior to that, note the incredibly cheap winning bids from dirty, brown, outdated coal, which has “no future” (in a market controlled by the tooth fairy).

AER Graph, 2018, prices set by black coal power.

Bayswater coal plant used to be able to win bids at $40/MWh (or it used to have to bid that low to win). Thanks to the RET (Renewable Energy Target) destroying some of the cheapest power, that’s not happening any more. Costs are up and competition is down.

AER Graph, 2018, prices set by brown coal power.

One gas plant. Not cheap to start. Not cheap to finish.

AER Graph, 2018, prices set by gas power.

Hydro costs are up too:

AER Graph, 2018, prices set by gas power.

Unreliable wind and solar must be backed up by something and cheap brown coal is punished by pagan aims to control the weather. Thus it is inevitable that the more wind and solar we add, the more we need gas, black coal or hydro, code for “expensive”.

The AER report also noted that Victoria and SA have only three big “vertically integrated” players. That’s another story, but with convoluted incentives we can be sure all three are taking advantage of the perversity on offer.

h/t  Dave B

 

When warmist politicians distort,
The truth about climate, they thwart,
A grid’s power supply,
It’s then costly to buy,
Making many Australians go short.

–Ruairi

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Another way to destroy a grid: add a million electric vehicles

New electric vehicles have big fat batteries, which will help solve the problem known as “charge anxiety” (let’s call that the Flat-Bat-Fear).

The new fat-batteries, however, have the small catch that they need two days to trickle charge. Hmm. Then there is the other catch that each slow charger (7KW) is equivalent to adding nearly three houses to the grid.     ur Energy Minister Josh Frydenberg predicts there will be one million electric cars on Australian roads by 2030.

You might think this is slow motion train wreck, but we might avoid this if households opt for fast 50KW chargers. In that case we can do the train-wreck at top speed.

Each fast charger will apparently be “like” adding the equivalent of 20, count them, 20 homes.

This is fearmongering obviously — no one is going to want a fast charger when they could leave the car in the garage for 48 hours instead.

New Zealand report claims new generation electric vehicles threaten the power network

Ben Packham, The Australian

New Zealand’s biggest energy distributor, Vector, warned electric vehicle chargers “put a large electrical load on the network”, with even 2.4kW “trickle” chargers adding the equivalent of one additional home to the grid.

Vector’s electric vehicle network integration green paper said the shift to larger batteries would encourage drivers to opt for faster chargers, to avoid a two-day charge. A “slow” 7kW charger would add the equivalent of 2.8 homes to the grid, while a “rapid” 50kW charger would add the equivalent of 20 homes.

It said New Zealand’s power grid could require a $NZ530 million ($500m) upgrade if 7kW chargers were used, and one in four cars on the road were electric vehicles.

 Can someone calculate the cost per EV in NZ? Thanks…

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Thin sunscreen layer to *save reef from bleaching* for first time in twenty million years

Coral reef, photo.

Scientists are suggesting that a thin layer of floating calcium carbonate can cut sunlight over reefs by 30% and save some high value reefs from bleaching.

This should work well on all the reefs that evolved in the last fifty years and which don’t have moving water.

But half of the coral genera around today have been around since the Oligocene (23-34 million years ago) and for most of that time the oceans were warmer.  (Lucky human civilization evolved just in time to save all these reefs from extinction.)

Bleaching has probably been going on for millions of years longer than we have been scuba diving with cameras to film it. We only discovered coral bleaching in the 1980s. Not surprisingly, marine life has ways to adapt to heatwaves by chucking out the symbionts that don’t thrive in higher temperatures and replacing them with new inhabitants that do.

Yes, let’s  cover our most diverse and important reef systems with an artificial layer that cuts incoming sunlight by a third — What could possibly go wrong?

Ultra-fine film possible saviour for Great Barrier Reef

Scientists from the Australian Institute of Marine Biology say tests of a floating “sun shield” made of calcium carbonate show it could protect the reef from the effects of bleaching.

“It’s designed to sit on the surface of the water above the corals, rather than directly on the corals, to provide an effective barrier against the sun,” Great Barrier Reef Foundation managing director Anna Marsden said.

The trials, headed by the scientist who developed the country’s polymer bank notes, on seven different coral types found that the protective layer decreased bleaching of most species, cutting off sunlight by up to 30%.

Marsden said it was impractical to suggest that the “sun shield” – made from the same material found in coral skeletons – could cover the entire 348,000 square-kilometre reef.

“But it could be deployed on a smaller, local level to protect high value or high-risk areas of reef,” she added.

It’s not like the whole ocean is at one temperature and one constant pH

There is and always has been constant turbulence in the oceans and marine life is used to it. Ocean acidification happens every day in some places — no biggie. There is a large daily swing after sunset in pH over many reefs. Far from that being a problem, fish seem to behave better when artificial tanks mimic these natural swings. Indeed a bit less alkalinity is better for hundreds of species. Some coral reefs thrive in a more acidic ocean, and we appear to have a pretty big safety margin: farmed fish seem to cope fine with CO2 levels that are even fifty times higher than today.

The story of life on Earth is that everything keeps shifting and biology adapts. In one situation, when trapped, salt water fish evolved to become freshwater fish in just fifty years*. In private, NOAA experts will admit they can’t name one single place that is affected by ocean acidification.

While some estimates said 90% of the Great Barrier Reef was bleached recently, other studies said it was more like 5%. Even the head of the Great Barrier Reef Marine Park Authority has said that activists are distorting and exaggerating the threats.  The Great Barrier Reef is recovering faster than scientists expected.  Possibly because it is 3,000 kilometers long and has over a hundred tough spots that survive and replenish the rest.

Other ideas to save the reef include putting shade cloth over the Great Barrier Reef to save it from climate change or using giant fans to stop bleaching.

Coral reefs first became widespread about 200 million years ago. It takes some kind of delusional hubris to think they suddenly can’t survive without human help, or that we have any idea what we are doing messing with a complex well developed system.

Of course, if you work at an Australian university and say that, you too could face misconduct charges, like Peter Ridd.

Image: Wikimedia, author Wise Hok Wai Lum: Flynn Reef 2014.

*Error corrected. This originally said “six astomishing months” but should have said “fifty years”, which on evolutionary time frames is still incredibly fast.

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EarthHour: largest global movement for environment. “Millions participate” and like every carbon scheme, nothing happens

Earthhour is “The Largest Global Movement for the Environment”*

SBS tells us that it started in Australia (sorry), is observed by millions, and now occurs in 187 countries. (Since only one person has to turn off one light to qualify, I want to know which seven countries didn’t?)

To mark Earth Hour this year, WWF asked the public to make a “promise for the planet” – a small step in their own lives to help reduce their environmental footprint – such as refusing plastic cutlery or carrying a reusable coffee cup.  While these promises are small individually, WWF stated that “millions of people taking these actions together will have a massive, powerful impact”.

Which day was EarthHour Day in Australia –  Spot the difference:

Was this EarthDay?

The Australian National Electricity Grid last weekend.

 

Or this?

Electricity use, Australia, Earth Hour.

The Australian National Electricity Grid last weekend (the other day).

Source: Aneroid 24th March and Aneroid 25th March.

Notice the Earth-saving electricity dip at 8:30pm when millions turn off their lights!

Megagrams of carbon was saved. (Maybe.)

Take it from WWF  — this is the sum total effect of all the voters that care about climate change.

There were similar successes in California (WUWT) and in the UK (Paul Homewood).

The word you are looking for is “noise”.

Like every carbon scheme…

PS: The top graph was Earth Hour Day in Australia.

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*It must be true, the website says so.

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Weekend Unthreaded

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