It seems this legislation is likely to be passed sometime this week and according to many pundits the big winner will be wind farms.  

Wind is available now, is relatively cheap, and could snap up all the relevant concessions under the new legislation before emerging technologies like geothermal and solar thermal are ready for rolling out. 

Is this good news? 

According to the following article… wind farms in South East Australia are unlikely to supply any significant power output that system operators can rely upon, rather they will load the distribution system with sudden variations in power that are not predictable and are of a size that is ten times larger than the random variations of user demand. 

Wind Farming in South East Australia
By Andrew Miskelly and Tom Quirk

IT is often claimed by their advocates that wind farms can be a reliable source of electrical power if they are dispersed over a sufficiently wide area. The wind will be blowing somewhere, it is claimed. There is now a sufficient number of wind farms in South Australia, New South Wales, Victoria and Tasmania for an assessment of the value of wind farms as a source of reliable electricity generation..

This analysis is based on the performance of 11 wind farms listed in the table below for June 2009. The data was sourced from the Australian Energy Market Operator (AEMO formerly NEMMCO) website. The power output is recorded in 5 minute intervals and this allows the performance of the wind farms to be examined in detail. An example of the behaviour of two South Australian wind farms and the summed behaviour of all six South Australian wind farms is shown in the above chart.

These curves show that, for example, 80 percent of the time, all SA windfarms provided more than 8 percent of rated output, and that 8 percent of the time they provided just 80 percent or more of their rated output.

These power curves are representative of the general behaviour of wind farms. The performance of all the wind farms is given in the following table. 

The capacity factor, the average output relative to the installed capacity shows an overall average of 30 per cent for a total installed capacity of 833 Mw. The capacity factor varies from month to month throughout the year and varies from year to year. But these values are indicative of the performance to be expected from new wind farms as they are brought on line. A modest decline in the capacity factor for new farms might be expected if the best sites have already been taken.

The 90 per cent reliability figure represents the amount of energy that can be relied on for 90 per cent of the time. It is given as a percentage of the installed capacity so that comparative performance can be assessed. 90 per cent reliability for conventional coal fired power stations or gas turbine generators is greater than 90 per cent of the rated output. It is clear that the one benefit of grouping wind farms is that the 90 per cent reliability point is increased from 6 per cent for SA, 5 per cent for Victoria, to 10 per cent overall. Again this figure should be expected to vary from month to month and from year to year.

One of the most important details of this analysis is the geographical separation of the wind farms. This is shown in the map below. In fact the windfarms extend over 900 km North-South and East-West. This separation can be used to investigate if any significant benefit is gained by such a spread of wind farms. 

The next three figures show the June 2009 performance of the wind farms in NSW, Victoria and Tasmania compared to that of South Australia. South Australian wind power generation has been used as the standard as it is the largest sample and despite having 6 wind farms added together performs as if it were one farm despite a spread of some 500 km.  

It is clear that the responses in each area are correlated. The correlation of South Australia with Victoria is the clearest example. This has been refined in the next three figures that show a measure of this correlation. This is a running correlation with a sliding 24 hour window that shows the extensive variations over time.  

These figures show the strong positive correlation of South Australia with Victoria. However it is important to note that the other two states do not provide any significant comfort from their geographical separation: that is they show no significant inverse of the South Australian-Victorian correlation.

Another demonstration of this general wind correlation is to look at the total wind power profile and compare that to a profile assuming equal installed capacity in all four states.

The figure below shows that no great change occurs and the geographical spread does not enhance performance. 
 
The conclusion is that the only benefit from a large geographical spread is an increase in the 90 per cent reliability point from typically 5 per cent to 10 per cent

The other issue that can be examined is the short term fluctuations in the outputs of wind generators. These fluctuations add to the difficulties of maintaining voltage and frequency in the power system. Sudden changes in the demand for power raise similar problems but long experience with the daily load curve enables system operators to prepare for these changes. Fluctuations in output from the wind generators are, contrariwise, completely unpredictable. 

The variations have been assessed by looking at the difference of wind farm output from one 5 minute interval to the next. By sampling over some 8,000 5 minute intervals it is possible to build up a measure of the performance of all wind farms and their aggregate output, rather like calculating a standard deviation(1) .  This can be extended to looking at differences 10 minutes apart and so with increasing separation it is possible to see the time development of wind variations. A complete picture, extending over seven days, is shown below. It has been standardised to the installed capacity of the wind farms as it a measure of the wind’s behaviour, not the behaviour of the wind farm.

The conclusion from this is that the wind has some consistency for up to about 48 hours but with increasing fluctuations. Beyond that time the fluctuations are some 25 per cent of the installed capacity. This does not imply that the wind varies smoothly. On the contrary, this is the average performance of a generator with greatly varying output.

The general conclusion from this analysis is that wind farms in South East Australia are not likely to supply any significant power that can be relied upon, and thus system operators will have to schedule generators as if there were no wind power at all. Wind farms will load the distribution system with variations in power that are not predictable and are ten times larger than the random variations of user demand.

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1.

Tom Quirk has analysed variations within and between these data sets and concludes there is 1. Substantial general agreement between the data sets, 2. Substantial short-term variation in global temperature in all data sets and 3. No data set shows a significant measurable rise in global temperature over the twelve year period since 1997.

Global Temperature Revisited
by Tom Quirk

One of the most vexing things about climate change is the endless debate about temperatures. Did they rise, did they fall or were they pushed? At times it seems like a Monty Python sketch of either the Dead Parrot or the 5 or 10 Minute Argument.

However it is possible to see some of the issues by looking at the four temperature series that are advanced from:

GISS – Goddard Institute for Space Studies and home of James Hansen,
Hadley Centre – British Meteorological Office research centre
UAH – The University of Alabama, Huntsville, home of Roy Spencer with his colleagues including John Christy of NASA and
RSS – Remote Sensing Systems in Santa Rosa, California, a company supported by NASA for the analysis of satellite data.

The first two groups use ground based data where possible with a degree of commonality. However since 70% of the surface of the earth is ocean and it is not monitored in a detailed manner, various procedures with possibly heroic assumptions and computer modelling, are followed to fill the ocean gap.

The last two groups use satellite data to probe the atmosphere and with the exception of the Polar Regions which are less than 10% of the globe, they get comprehensive coverage.

One question is of course are the two groups measuring the same temperature? After all the satellite looks down through the atmosphere, while the ground stations are exactly that.

There is an important distinction to be made between measuring the temperature and measuring the change in the temperature. Since the interest is in changing temperatures then what is called the global temperature anomaly is the starting point. The issue of measuring absolute temperatures should be put to one side.

Data from 1997 to 2009 was drawn from the four group websites on the 28 April 2009. When data for 1997 to early 2008 was compared to data acquired in early 2008 differences were found as shown in the first table.

This is evidence of substantial reprocessing and re-evaluation of data. This is not unusual with complicated analysis systems but there is so much interest in the results that adjustments are regarded with great suspicion. This is the fault of those publishing the temperature data as they fail to make the point that monthly and even yearly measurements are about weather and not climate.

The latest series of temperature anomalies are shown in the graph where the monthly data has been averaged into quarters. All statistical analysis that follows is on the monthly data unless stated otherwise.

From inspection, there is substantial agreement over the years 1997 to 2008. This can be statistically measured through correlations. This is a measure of how closely related the series may be. A value of 0 implies independent series while a value of 1 implies complete agreement. The correlation in turn indicates the degree of commonality in the comparison.

This is remarkable agreement given the two very different techniques used.

It is important to note that the two satellite analysis groups draw measurements from the same satellites. So the differences in temperatures are a result of analysis procedures that are not simple. In fact corrections to the data have been the subject of exchanges between the two groups.

The ground based measurements also have a common data base but it is clear and acknowledged that the two groups have different analysis procedures. While the satellite analysis procedures have converged to reduce their differences over the last thirty years, this has not been the case for the ground based procedures.

It is also clear looking at the measurements that there are substantial short-term, say less than 2 years, variations over the period 1997 to 2009. In fact, while the overall monthly variations show a scatter with standard deviation of 0.2⁰C, the month to month variations are 0.1⁰C. This is a measure of features that are clear in the data. The short run sequences of temperature movement are a reflection of variability in the atmosphere from events such as El Ninos (1997-98) and La Ninas.

Looking for a simple trend by fitting curves through a highly variable series is both a problem and a courageous exercise. The results on an annual rather than a monthly basis are given in the third table. The problem of dealing with real short term variations was resolved by ignoring them.

So for twelve years there has been a rise 0.1⁰C with a 140% error, in other words, no significant measureable temperature rise. You can play with the data. If you omit 1998 then you can double the change. But 1998 was an El Nino year followed in 1999 by a La Nina. If we omit both years then the results are unchanged.

However the lesson from this is to look at the detail.

There is so much variability within the 12 year period that seeking a trend that might raise the temperature by 2⁰C over 100 years would not be detectable. On the other hand there are clearly fluctuations on a monthly and yearly scale that will have nothing to do with the predicted effects of anthropogenic CO2.

The twelve year temperature changes from the data of the four analysis centres reveal some possible differences. Since there is a high degree of commonality amongst the results, any differences may be systematic. Both the GISS and Hadley series show a larger temperature increase then the satellite measurements. This may be due to urban heat island effects.

Finally, if you are looking for temperature increases from CO2 in the atmosphere, then you should choose the satellite approach of measuring temperatures in the atmosphere!

Short term, less than thirty years, temperature series are not the place to seek evidence of human induced global warming.

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Tom Quirk lives in Melbourne, Australia. 

To read more from Dr Quirk click here  http://jennifermarohasy.com/blog/author/tom-quirk/

The photograph is from Anthony Watt’s website that details his program of photographically surveying every one of the 1221 USHCN weather stations in the USA which are used as a “high quality network” to determine near surface temperature trends in the USA, read more here http://wattsupwiththat.com/test/ .

“Most CO2 from fossil fuels is emitted in the northern hemisphere and it takes at least six months to spread to the southern hemisphere, which means that concentrations in the northern hemisphere should go up before they do in the southern hemisphere. In fact, they go up simultaneously, which suggests that manmade CO2 emissions are not the only contributor to the rise in global CO2 and there must be some other source.”

The new research paper published in the journal ‘Energy and Environment’ explains that given 95 percent of CO2 from fossil fuel is emitted in the northern hemisphere then some time lag might be expected due to the sharp year-to-year variations in the estimated amounts left in the atmosphere.

“A tracer for CO2 transport from the northern to the southern hemisphere was provided by radioactive CO2 with the isotope Carbon-14. A sharp rise in radioactive carbon was created by nuclear weapons testing in the 1960’s.  Analysis of Carbon-14 in atmospheric CO2 showed that 50 percent of the CO2 was transported from the northern to the southern hemisphere within a year and it took some five years for exchanges of CO2 between the hemispheres before the Carbon-14 was uniformly distributed,” said Dr Quirk. 

“A simple model, with a one year mixing time, showed a delay of six months for CO2 changes in concentration in the northern hemisphere to appear in the southern hemisphere.”

“However, the measurements of CO2 show no time difference between the hemispheres.  This suggests that the annual increases in atmospheric carbon dioxide may be coming from a global or equatorial source. This could result from the action of the world’s oceans with changing temperatures or their phytoplankton or could flow from global changes to forests and savannahs,” explained Dr Quirk.

“Dr Quirk’s findings generate almost more questions than they answer, but then again that is the nature of good science.  The findings are radical because they challenge a key premise of the current consensus.  But just because they are not mainstream, doesn’t mean they are wrong,” said Dr Marohasy.

“It is certainly premature for the federal government to be pressing ahead with its Emissions Trading Scheme given we understand so little about climate and climate change,” concluded Dr Marohasy.  

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Notes

Tom Quirk has a Master of Science from the University of Melbourne and Master of Arts and Doctor of Philosophy from the University of Oxford.   His early career was spent in the UK and USA as an experimental research physicist, a University Lecturer and Fellow of three Oxford Colleges.

Jennifer Marohasy has a BSc and PhD from Queensland University and is Chair of the Australian Environment Foundation.

‘Sources and Sinks of Carbon Dioxide’, by Tom Quirk, Energy and Environment, Volume 20, pages 105-121

This paper was previously discussed at this blog here: http://jennifermarohasy.com/blog/2009/03/the-available-evidence-does-not-support-fossil-fuels-as-the-source-of-elevated-concentrations-of-atmospheric-carbon-dioxide-part-1/

This is a media release from the Australian Environment Foundation; a not-for-profit, membership-based environment organisation having no political affiliation.  The AEF is a different kind of environment group, caring for both Australia & Australians.  Many of our members are practical environmentalists – people who actively use and also care for the environment.  We accept that environmental protection and sustainable resource use are generally compatible. For more information about the AEF, visit www.aefweb.info .

Tom Quirk has tested this assumption including through an analysis of the time delay between northern and southern hemisphere variations in carbon dioxide.  In a new paper in the journal Energy and Environment he writes:

“Over the last 20 years substantial amounts of CO2 derived from fossil fuel have been released into the atmosphere. This has moved from 5.0 gigatonnes of carbon in 1980 to 6.2 gigatonnes  in 1990 to 7.0 gigatonnes in 2000…  Over 95% of this CO2 has been released in the Northern Hemisphere…

“A tracer for CO2 transport from the Northern Hemisphere to the Southern Hemisphere was provided by 14C created by nuclear weapons testing in the 1950’s and 1960’s.The analysis of 14C in atmospheric CO2  showed that it took some years for exchanges of CO2 between the hemispheres before the 14C was uniformly distributed…

“If 75% of CO2 from fossil fuel is emitted north of latitude 30 then some time lag might be expected due to the sharp year-to-year variations in the estimated amounts left in the atmosphere. A simple model, following the example of the 14Cdata with a one year mixing time, would suggest a delay of 6 months for CO2 changes in concentration in the Northern Hemisphere to appear in the Southern Hemisphere.

“A correlation plot of …year on year differences of monthly measurements at Mauna Loa against those at the South Pole [shows]… the time difference is positive when the South Pole data leads the Mauna Loa data. Any negative bias (asymmetry in the plot) would indicate a delayed arrival of CO2 in the Southern Hemisphere.

“There does not appear to be any time difference between the hemispheres. This suggests that the annual increases [in atmospheric carbon dioxide] may be coming from a global or equatorial source.”

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Notes

‘Sources and Sinks of Carbon Dioxide’, by Tom Quirk, Energy and Environment, Volume 20, pages 103-119.  http://www.multi-science.co.uk/ee.htm

The abstract reads:

THE conventional representation of the impact on the atmosphere of the use of fossil fuels is to state that the annual increases in concentration of CO2 come from fossil fuels and the balance of some 50% of fossil fuel CO2 is absorbed in the oceans or on land by physical and chemical processes. An examination of the data from:  i) measurements of the fractionation of CO2 by way of Carbon-12 and Carbon-13 isotopes; ii) the seasonal variations of the concentration of CO2 in the Northern Hemisphere; and iii) the time delay between Northern and Southern Hemisphere variations in CO2, raises questions about the conventional explanation of the source of increased  atmospheric CO2. The results suggest that El Nino and the Southern Oscillation events produce major changes in the carbon isotope ratio in the atmosphere. This does not favour the continuous increase of CO2 from the use of fossil fuels as the source of isotope ratio changes. The constancy of seasonal variations in CO2 and the lack of time delays between the hemispheres suggest that fossil fuel derived CO2 is almost totally absorbed locally in the year it is emitted. This implies that natural variability of the climate is the prime cause of increasing CO2, not the emissions of CO2 from the use of fossil fuels.

Data drawn from the website http://cdiac.ornl.gov/trends/co2/contents.htm  .

Tom Quirk has a Master of Science from the University of Melbourne and Master of Arts and Doctor of Philosophy from the University of Oxford.   His early career was spent in the UK and USA as an experimental research physicist, a University Lecturer and Fellow of three Oxford Colleges.

In response to a question following this post about the real temperature fluctuations on a monthly basis, Tom calculated the the standard deviations from a covariance analysis, Table 3.

“The last two rows are from averaging the ground based results and averaging the satellite results and then making a comparison.

Table 3

The temperature and common fluctuations on the ground based constructs must be around 0.09 0C for the standard deviation.

GISS has a larger standard deviation so 0.09 0C would be easily accommodated along with the manipulations for the extra total standard deviation.

Finally the satellite data has a different and larger standard deviation to the ground based results. Perhaps the atmosphere is more turbulent than the oceans that must have a soothing effect on temperature fluctuations, as they have the largest heat memory of the components, land, sea and air.

Tom Quirk
Melbourne”

However it is possible to see some of the issues by looking at the correlation of the five temperature series that are advanced by the uppers or the downers.

The five groups are:
1. GISS, The Goddard Institute, home of James Hansen,
2. NCDC, The National Climate Data Center, a part of NOAA (as is GISS), the National Oceanographic and Atmosphere Administration.
3. BMO/UEA, The British Meteorological Office and the University of East Anglia.
4. UAH, The University of Alabama, Huntsville, home of Roy Spencer with his colleagues including John Christy of NASA and
5. RSS, Remote Sensing Systems in Santa Rosa, California, a company supported by NASA for the analysis of satellite data.

The first three groups use ground based data where possible with a degree of commonality. However since 70% of the surface of the earth is ocean and it is not monitored in a detailed manner, various recipes are followed to fill the ocean gap, if that is the best way of putting it.

The last two groups use satellite data to probe the atmosphere and with the exception of the Polar Regions which are less than 10% of the globe, they get comprehensive coverage.

One question is of course are the two groups measuring the same temperature? After all the satellite looks down through the atmosphere, while the ground stations are exactly that.

One of the ways to probe this is to look over time at the degree of correlation achieved in the measurements of the “global temperature anomaly

The results of such a comparison are given in Table 1 for the monthly time series from 1979 to 2008. There is the Pearson correlation coefficient extracted from the data. A value of 1.00 shows the compared values move in step with each other while a value of 0.00 would give complete independence. (A value of-1.00 is also possible.) “Commonality”, the square of the correlation coefficient is interpreted as showing what proportion of one measurement series is covered by the other series. Note that correlation does not imply connection or causality except that we know there is some commonality with ground based measurements.

Table 1.

First a check of the land based measurements shows that two groups are closely aligned, the difference reflecting the different processing to get the global result.

GISS is more problematic with less commonality which must be a reflection of quite different processing assumptions to that of NCDC or BMO/UEA.

For land based measurements we are faced with a “Judgement of Paris” and it is not clear who gets the Golden Apple.

Finally the satellite measurements have a high internal commonality but a commonality of some 50% with the land based measurements.

None of this should be surprising. The land measurements are on the land and subject to a number of uncertainties, such as heat island effects and lack of extensive ocean measurements while the satellites probe the atmosphere but not ground level.

So for the last 8 years the results are in Table 2

Table 2.

It is surprising to see the agreement achieved by two quite independent approaches.

However we should be aware that none of this is simple.

Tom Quirk
Melbourne

The following are a simple and a sophisticated test of modelling the atmosphere.

First an analysis of regions with enhanced sensitivity to changes in CO2 concentration. These are found by comparing regions of varying concentrations of water vapour but constant CO2 concentration where changes in green house gases vary the amount of radiation directed downwards from the atmosphere to the surface. This should show changes in surface temperature as the global CO2 concentration increases with time.

This is followed by a test of the latest GCM models against measurements.

The amount of CO2 in the atmosphere has risen substantially in the last fifty years but it has been difficult to isolate its contribution to the world temperature rise that has occurred in that time.

A continuous stream of high quality measurements show the concentration of CO2 in the atmosphere has risen from 316 ppmv in 1959 to 382 ppmv in 2006. This is an increase of 21% in some fifty years. At the same time the global temperature has increased by 0.5 to 1.0 0C.

There are large variations in water vapour in the atmosphere with a maximum at the equator and minima at the poles. In addition there are bands of latitude where the seasonal temperature variations are small as the ocean interacts with the atmosphere. These should be regions where the effects of global changes in CO2 concentration are more obvious in year on year variations as other climate variations are reduced.

The damping of seasonal temperature change can be seen from Figure 1 showing the maximum variations of temperature as a function of latitude averaged over the years 1948 to 2006.

Figure 1

Two latitude bands were selected for analysis, the band 4 to 9 N in the tropics and the band 51 to 56 S in the Southern Ocean.

The tropical band surface is 75% ocean while the Southern Ocean band is 99% ocean. As a comparison, the band 51 to 56 N is only 40% ocean and has substantial seasonal variations.

The mean monthly temperatures are shown below averaged over the years 1948 to 2006 in Figures 2 and 3

Figure 2:

Figure 3

The variations are 0.8 0C in the Tropics and 4.0 0C in the Southern Ocean

The variations in the mean annual humidity are shown below in Figure 4:

There is a 70% reduction in water vapour in moving from the Tropics to the Southern Ocean with a consequent enhancement of the contribution of CO2 to the downward directed radiation from the atmosphere.

The seasonal variations show that humidity remains relatively stable in the two latitude bands chosen for analysis. This is not the case for the equivalent Northern latitude band where there is a factor of five seasonal change in humidity.

Figure 4

The mean annual temperatures for the Tropical band are shown below in Figure 5.

Figure 5

A simple straight line has been fitted to the temperatures although there is clearly some detailed short term structure present such as ENSO. The Southern Ocean temperatures have also been treated in the same way.

The linear gradients from the least squares fits are given in the Table 1

Table 1

The Southern Ocean temperatures are better described by a temperature increase for 1948 to 1976 and then a constant temperature. However as with the Tropical temperatures, there is clearly some short term structure seen in Figure 6.

Figure 6

The analysis shows the tropical temperature increase is substantially larger than the Southern Ocean increase.

The MODTRAN computer programme has been used to give a simple indication of the changes in downward radiation from the atmosphere to the surface. Relative humidity is held constant and temperatures and the water vapour scale adjusted to the measured values.

The temperature increases have been calculated using MODTRAN and assuming a latent energy contribution at the surface. The latent energy term is a function of surface temperature and reduces the temperature rise by a factor of two.

The results are shown in Table.2

Table 2

The calculations show that for increased CO2 there is a larger increase in downward radiation in the Antarctic region compared to the Tropics. This is also the case for a doubling of CO2 concentration in the atmosphere. Feedback effects have been included in the final results shown below in Table 3.

Table 3

Thus a simple calculation gives a larger temperature increase in the Antarctic region over the Tropics. However the atmosphere has energy transfer processes that may explain the apparent contradiction.

General Circulation Models (GCM) take into account many energy transfer processes and are used to forecast climate temperature changes. Many of these models are calibrated against past measurements of a number of atmospheric variables. Two models that offer access to their results have been examined with data taken from the GISS and GFDL websites. Both are members of the IPCC group listed at the LLNL website.

GCM surface temperature profiles for the fifty years from 1950 to 2000 were downloaded and the map longitude-latitude grid point temperatures averaged around latitude circles.

Surface temperature measurements were taken from the NCAR website and for comparison 5 year means have been used with temperatures averaged in latitude bands.

The results of the comparisons are shown below in Figure 7 for the Goddard Institute for Space Studies GCM with a coupled atmosphere-ocean. Data was downloaded for all forcings combined for the 1880-2003 Climate Forcings.

Figure 7

A similar comparison has been made for the Geophysical Fluid Dynamics Laboratory (Princeton) CM2.X Coupled Climate Model. The results are also shown below in Figure 8 and an overall summary is given in Table 4.

Figure 8

Table 4 – Global Temperature Changes

While the global values are consistent with the measurements, in detail the calculations are not supported by measurements. There are different responses at the North and South Poles and a complicated response in the latitudes 60 S to 60 N.

The GCM’s are closer to the measurements than the simple MODTRAN calculation. This demonstrates the importance of many processes other than the CO2 forcing. However the comparisons show that these processes do not seem to have been adequately modelled to date.

The contribution of increasing CO2 concentrations is not detectable with this analysis. This is not to doubt that it has an effect but that there are other processes also at work in the atmosphere ocean system that tend to dominate.

However the confidence with which the future predictions are presented coupled with the obvious mismatches with the past are an echo of the Soviet era Polish saying: “The future is certain only the past is unpredictable”.

Tom Quirk
Melbourne

The disposal of long-lived radioactive waste within Australia could be one of the single biggest contributions we can make to the safety of our region, and even the world.

Domestically, Australia produces about 45 cubic metres – three truckloads – per year of low and intermediate level radioactive wastes. Much of this material is produced in the research reactor at Lucas Heights, then used at hospitals, industrial sites and laboratories around the country.

There are about 3,700 cubic metres of low-level waste stored at over a hundred sites around Australia. Over half of the material is lightly-contaminated soil from CSIRO mineral processing research. In addition there are about 500 cubic metres of long-lived intermediate level waste.

But having dispersed storage is not considered a suitable long-term strategy for the safe storage of waste. So the Federal Government has proposed a consolidation to a single repository site.

The plan is for a disposal area about 100 metres square within a two square kilometres area.
Low-level and short-lived intermediate level wastes would be disposed of in a shallow, engineered repository designed to contain the material and allow it to decay safely to background levels.

Intermediate-level wastes with lifetimes of greater than 30 years would be stored above ground in a facility designed to hold them secure for an extended period and to shield their radiation until a geological repository is eventually established, or alternative arrangements made.

Contrary to popular belief, this proposal is not about the ultimate disposal of high-level radioactive waste from the spent fuel of reactors.

The high level wastes produced by nuclear power stations are not yet a concern. If we are lucky we might have two operating nuclear power stations within 20 years. But we would not then be worrying about waste from them for another 50 years.

Even so, it may be with cheap coal and carbon dioxide burial – what we grandly call geosequestration – that we find conventional power plants are the better buy.

Currently, the concern is about the disposal of industrial waste, an area where governments have had great difficulties in finding acceptable solutions.

So what is the fuss about?

There is a worry about instability caused by earthquakes. Helen Caldicott in ABC News Opinion on Monday expressed concern that the Federal Government’s preferred site for a waste dump experienced recently a quake measuring 2.5 on the Richter scale.

However, an earthquake of this magnitude is classified as detectable but generally not felt. There are about 1,000 earthquakes of this intensity each day all over the earth. It might not even cause a ripple in your café latte.
Enrichment and reprocessing may provide further business opportunities. In this area, Australian scientists have made major technical contributions. But firms require access to large amounts of capital to pursue their development. None of our major mining or energy companies has expressed, at least recently, any desire to enter these markets.

The mining of uranium and the disposal of spent fuel are the largest components of the costs in the uranium fuel cycle. Australia could benefit from providing both services.

Indeed, there could be significant regional demand. Thailand, China and India might find an Australian waste storage facility extremely attractive. Countries that are genuinely earthquake prone, as Japan and Indonesia are, would no doubt welcome an opportunity even more.

Australia provides its reputation, its technical expertise and its high-quality infrastructure for all manner of services to Asia-Pacific region. We should not be blind to the potential of a waste storage facility.

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This piece was first published by ABC Online and is republished here with permission from the author. Tom Quirk is a member of the board of the Institute of Public Affairs and chairman of Virax Holdings Ltd, a biotechnology company. He is a nuclear physicist by original training.