Posts Tagged ‘Covid-19’

The Mexican Wave: Covid19 in Australia to October

November 2, 2020

Postscript: For more detailed information and graphs that support/ augment/ supersede my analysis, see https://www.health.gov.au/news/health-alerts/novel-coronavirus-2019-ncov-health-alert/coronavirus-covid-19-current-situation-and-case-numbers

In Queensland we refer to people in the southern states as “Mexicans” (because they’re from “south of the border, down Mexico way” as sung by Gene Autry, Patsy Kline, Patti Page and many others.)

Read on to find why I describe the Australian Covid19 experience from June to October as the Mexican wave.

Worldometers has these plots illustrating the Australian experience:

Figure 1:  Daily new cases

There were (apparently) two waves in Australia.

Figure 2: Cumulative death toll

In four months the death toll increased by 803- more than 770 %! 

We know what went wrong, but the following plots might illustrate it more clearly.

These plots are from statistics from State government websites, such as this one from Victoria: https://www.dhhs.vic.gov.au/victorian-coronavirus-covid-19-data .

All are correct as of 31 October.  They speak for themselves so I will keep my comments to a minimum.

The next figure compares seven day averages of Victorian and all Australian new cases from 25 July to 6 August, at the peak of the “second wave”.

Figure 3: National and Victorian new cases

Until 5 June, Victoria had 1,681 cases.  From then, the new cases began increasing, adding another 18,666 cases to 31 October.  92% of Victorian cases were in this period.

Comparing all states:

Figure 4:  Total cases

Figure 5:  Mortality:

I estimated population figures from March ABS figures.  With almost zero overseas net immigration and very little interstate migration, natural growth remains, which does not change the rates per million by very much at all.

If Victoria was a separate country, its case rate per million would rank it at 127th, just ahead of Bangla Desh.   

Figure 6:  Case Rate per million people

Its Death Rate per million would rank it at 76th, just ahead of Turkey.

Figure 7:  Mortality Rate per million people

The next figure shows Case Fatality Rate, the number of deaths per total cases, which is not complete until the pandemic is over.  These figures are for the CFRs to 31 October.

Figure 8: Covid19 Case Fatality Rate

CFR is affected by whether the virus gets into nursing homes and hospitals which have high proportions of vulnerable people.  There was an outbreak of Covid19 in hospitals in northern Tasmania which affected the Tasmanian CFR.

 4.03% of all Victorian cases so far resulted in death.

The figure for all of Australia is 3.29%.

The figure for Australia excluding Victoria is 1.22%.

The virus first entered Australia via overseas travellers, then spread by local transmission.  The next plot compares infections acquired overseas with those acquired locally in Victoria.

Figure 9: Victorian overseas and locally acquired infections

The contrast is stark.  Victoria compares most unfavourably with other states with over 95% of all cases locally acquired. (Data not available for Tasmania and Territories.)

Figure 10:  Percentage of local transmission in larger states

And Victoria has more than 90% of total national local transmission.

Figure 11:  Percentage of national local transmission

Therefore it can be clearly seen that Australia’s “second wave” was really all about Victoria.  This was easily avoidable with strict hotel quarantine and better contact tracing.  There was no second wave in other states, with small outbreaks mostly due to travellers from Victoria.

Perhaps “Mexican” should from now on describe the government of Victoria, but not their long suffering people, and not governments of NSW, Tasmania, or South Australia.

The Mexican Wave is not something we wish to see repeated.

First Wave Covid19 Mortality in Context

October 22, 2020

Key takeaway points:

  • It is likely that the real Covid19 death toll was at least double the official tally, and possibly hundreds more.
  • Despite this, there were 1,457 fewer deaths in the first six months of this year than last year.
  • The first lockdown worked- until the Victorian fiasco.

In this post I use the most recent Mortality data (released 1 October 2020) from the Australian Bureau of Statistics (ABS), up to 30 June 2020, and the most recent ABS Population data, to examine the effect of the Covid19 pandemic on Australian deaths.  This period covers the whole of the first wave of the pandemic and gives interesting insights.  Future data releases covering the second wave (with another 800 Covid19 deaths) will provide further illumination.

The ABS advises that the data are provisional and not complete as deaths subject to coroners’ inquests are not included, but with completeness percentages in the high 90s “meaningful comparison with historic counts” may be made.

Key statistics from the ABS:

  • 68,986 doctor certified deaths occurred between 1 January 2020 and 30 June 2020.
  • Numbers of deaths have been below historical averages since mid May and below baseline minimums since the week ending 9 June.
  • Deaths from respiratory diseases and heart diseases were below historical minimum counts throughout June.

Figure 1:  ABS chart of deaths and Covid19 infections

The peak of new coronavirus infections was in the week ending 31 March, with 2,428 new infections in that week (Week 13), and the peak in all mortality also occurred in that week.  The following plot shows official Covid19 mortality (from Worldometers) peaking in Week 14.

Figure 2:  Covid19 first wave deaths

The ABS says that the World Health Organisation (WHO) early in 2020 “directed that the new coronavirus strain be recorded as the underlying cause of death, i.e. the disease or condition that initiated the train of morbid events, when it is recorded as having caused death……..

……. Deaths due to COVID-19 are included in the total for all deaths certified by a doctor. They are not included in deaths due to respiratory diseases or any of the other specified causes.”

The first reported Covid19 death was on 1 March, (Week 9).  In Week 14, one week after the peak in new infections, the peak in the first wave deaths occurred.  In this post I define the first wave of the pandemic as Weeks 9 to 21.  (The second wave commenced in Week 24.)  Figure 3 shows Covid19 deaths in context.  The duration of first wave deaths is indicated by the horizontal red line.

Figure 3: Covid19 and total deaths

Note the increase in total deaths in Weeks 12 to 15, and the insignificance of official Covid19 mortality by comparison.  (Australia closed borders on 16 March- Week 11- and began restricting movement in the days following.)

The next graph compares 2020 mortality so far with the five previous years.

Figure 4: Total Australian deaths 2015 – 2020

This year’s peak in deaths also occurred in Weeks 12 to 15, at the height of the first wave infections.

You will also note Australia’s 2020 mortality levelled off well below previous years’ figures, which usually continue rising to peak in Winter and early Spring.  Mortality figures for Weeks 27 to 52 will be very interesting.  There was an unusual early surge in 2019, and a very large increase in deaths in Winter and Spring of 2017.

I now look at excess deaths.  The ABS says:

Measuring ‘excess’ deaths

Excess mortality is an epidemiological concept typically defined as the difference between the observed number of deaths in a specified time period and the expected numbers of deaths in that same time period. Estimates of excess deaths can provide information about the burden of mortality potentially related to the COVID-19 pandemic, including deaths that are directly or indirectly attributed to COVID-19.

… counts of deaths for 2020 are compared to an average number of deaths recorded over the previous 5 years (2015-2019). These average or baseline counts serve as a proxy for the expected number of deaths, so comparisons against baseline counts can provide an indication of excess mortality. “

However, Australia’s population has increased by nearly two million from March quarter 2015 to March quarter 2020 (from 23,745,629 to 25,649,985).  This has a large impact on calculations.  Mortality rate per 1,000 head of population is a better measure. Figure 5 shows mortality rates for recent years.

Figure 5:  Australian mortality rates, 1st 26 weeks, 2015 – 2020

The method I have used is different from the ABS methodology because of the population increase and is based on mortality rates rather than absolute numbers of deaths. 

I have calculated the mortality rate per 1,000 people for each of the 2015-2019 years (using the population for the March quarters of those years), and similarly for the 2020 data.  I then multiply the average of the 2015-2019 mortality rates by the 2020 March quarter population to obtain an estimate of predicted deaths for 2020.  Subtracting this from the actual 2020 number gives an estimate of excess deaths.  An excess death figure of zero indicates the mortality rate is no different from previous years.  The next figure shows plots of actual and expected deaths for the first half of 2020.

Figure 6:  Predicted and actual deaths

Figure 7 is my plot of excess deaths to 30 June.

Figure 7: Estimated Excess Mortality

Excess and actual deaths peaked in Weeks 12 to 15, with weeks 13 and 14 nearly 200 above the expected level- but there were only 56 official Covid19 deaths in those weeks.  Officially, Covid19 was involved in 29 deaths in Week 14, 12 each in Weeks 13 and 15 and only 3 in Week 12.  It is possible that Covid19 deaths were being vastly under-reported in March. 

By the end of June estimated excess deaths were at minus 349, 11.5% below the expected number for Week 26.  Actual deaths in the first half of the year were 1,457 fewer than for the same period in 2019.

States and Territories:

Figure 8 shows actual numbers of deaths for all states and territories.

Figure 8:  2020 mortality numbers for each state

Mortality figures are dominated by New South Wales, followed by Victoria and Queensland.  Figure 9 shows excess deaths.

Figure 9:  Excess mortality by states

Smaller states had smaller changes in excess mortality, although Western Australia had a peak of 54 excess deaths in Week 13.   Figure 10 shows excess deaths for the larger states only.

Figure 10:  Excess deaths in the large eastern states

Peaks in excess deaths occurred between Weeks 9 to 17, but note earlier peaks in New South Wales and Queensland 7 or 8 weeks before the pandemic peak, with Queensland much higher than New South Wales, largely counteracted by Victoria, and a peak in Victoria in Weak 11, counteracted by New South Wales.  There was a third peak in Weeks 17 to 19, coinciding with another peak in Covid19 deaths.  Remember these numbers are additional to Covid19 deaths.  And officially Queensland had only seven Covid19 deaths, almost certainly due to under-reporting.

Age at death

Figure 11 shows the ages at which excess deaths occurred.

Figure 11:  Excess mortality by age

People aged from 0 to 44 years were not affected by the large changes in death rates in older age groups, but there was an increase in excess deaths in the 45 to 64 age bracket in Week 13, at the height of Covid19 infections, as Figure 12 shows.  That looks suspicious, but may be chance.

Figure 12:  Excess deaths for younger cohorts

The majority of excess deaths were in older age groups, as Figure 13 shows.

Figure 13:  Excess deaths for older Australians

There was a peak of 132 excess deaths in those 85 years and over in Week 14, but in Week 13 there were 146 excess deaths in those aged 65 to 84.  There were additional substantial peaks in earlier weeks as well.  It was not a good first half of the year for senior citizens, but excess deaths for all age groups were well below expected numbers by June.

Cause of death

  A death certificate lists all causes of death, and with elderly people these can be three or more.  It is very likely that a person over 85 may die of pneumonia (classified as a respiratory illness), but may also have any or all of dementia, diabetes, cerebrovascular disease, ischaemic heart disease, and cancer.  However, the ABS asks doctors to report the (one) underlying cause of death, and since earlier this year, Covid19 as the underlying cause “when it is recorded as having caused death.

 Figure 14 compares all respiratory deaths with Covid19.

Figure 14:  Covid19 and respiratory deaths

Influenza and pneumonia are subsets of respiratory illness, and the next figure shows interesting excess mortality data for 2020.

Figure15:  Excess deaths due to respiratory causes

Note the peak in respiratory deaths at the height of pandemic infections, but an earlier peak some four weeks previously.  It is likely that Covid19 was not correctly reported to the ABS by all doctors until Week 14 or 15- doctors are human too.  Since the first wave and the increase in personal hygiene, social distancing and little travel, deaths have remained well below previous years.

Figure 16:  Ischaemic heart and cerebrovascular disease excess deaths

This plot illustrates the advances in medicine:  ischaemic heart disease in 2020 had fewer deaths than expected for all of the first six months apart from a peak in Week 7.  Cerebrovascular disease (chiefly strokes) also had fewer deaths than expected except for Week 14 (so was potentially related to Covid19), and another peak in Week 24. 

Figure 17 plots excess deaths caused by the common co-morbidities of Covid19, dementia and diabetes.

Figure 17:  Excess deaths caused by dementia, diabetes, and Covid19

Diabetes and Dementia excess deaths were also higher than expected during the first wave, but there was another large surge in excess deaths with dementia as a cause weeks earlier.

Conclusions:

With the caveat that the ABS mortality figures are provisional, and putting together figures for various states, ages, and causes of death, some conclusions may be drawn:-

Either a mystery respiratory illness or undiagnosed Covid19 was widespread in the eastern states amongst elderly people weeks before the peak of first wave deaths, possibly arriving from cruise ships.

There were probably many more Covid19 deaths and infections than reported.  It is likely that the real Covid19 death toll was at least double the official tally, and possibly hundreds more.

Social distancing, good hygiene, and travel restrictions have caused a large decrease in mortality in May and June by restricting the spread of many common illnesses.  The first lockdown worked- until the Victorian fiasco.

The net effect of the first wave of the Covid19 pandemic on Australian mortality was negative.  Covid19, and public health responses to it, resulted in a lower death toll in the first half of 2020.  This lower death toll was not just in relative (mortality rate) terms but also in absolute terms: there were 1,457 fewer deaths in the first six months of this year than last year.

ABS data for the second half of the year will be released around April 2021 and will provide much better information about excess mortality for all states (and Victoria in particular), for all age groups, and for all causes.

I include an appendix with raw mortality data for 2015 -2020.

Appendix:  Raw mortality data for all causes 2015 – 2020.

Figure 18:  Respiratory mortality

Note the typical winter and spring surge in respiratory deaths, mainly due to influenza outbreaks in cold months.  There was an early surge in 2019 and a very large surge in 2017 which will skew means for those weeks.  Median mortality rate may be more appropriate than means.

Figure 19:  Ischaemic heart disease mortality

Heart disease mortality has been below previous years for most of the first 26 weeks.

Figure 20:  Cerebrovascular disease mortality

Cerebrovascular disease (stroke) deaths peaked during the first wave of Covid19 but have been mostly near the bottom of the range of previous years, with a second peak in June.

Figure 21:  Dementia mortality

Deaths with dementia as a cause have increased over the years.  A peak in dementia deaths coincided with Covid19 but deaths have been in the normal range since then.

Figure 22:  Diabetes mortality

A peak in diabetes deaths coincided with the peak in Covid19 infections and deaths, and was much higher than expected.  At the end of June deaths were in the range of previous years.

Figure 23:  Cancer mortality

Cancer deaths have increased over the years and 2020 remains within the expected range.  You may note there is no winter increase in cancer mortality.

CO2vid Watch: August

September 10, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for August is now published: 412.55 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is still 2.61 ppm above the figure for August last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to August 2020- Mauna Loa

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Figure 3 shows the 12 month change in CO2 concentration since the record began.

Fig. 3:  12 month change in CO2 concentration since 1958 to August 2020- Mauna Loa

Annual growth has been above zero since the mid 1970s, and has not been below 1 ppm since 2011. The annual rate of change is increasing, in other words CO2 concentration growth is accelerating.

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down. And there won’t be!

This paper by J. Reid explains why.

http://blackjay.net/?p=1021%20%3Chttp://blackjay.net/?p=1021%3E

CO2 growth appears to be an entirely natural process.

Unless something dramatic happens, I don’t think I will continue this series any longer. There’s nothing to see.

CO2vid Watch: July

August 7, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

The CO2 concentration number for July is now published: 414.38 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.61 ppm above the figure for July last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to July 2020- Mauna Loa

Notice the amount of 12 month change has increased a bit more.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes continue to remain firmly in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

CO2vid Watch: June

July 13, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

(In a coming post I will update my expectations for the end of the year and next year.) 

The CO2 concentration number for June is now published: 416.39 p.p.m. (parts per million).  The seasonal drawdown of CO2 has begun, but CO2 concentration is 2.47 ppm above the figure for June last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to June 2020- Mauna Loa

Notice the amount of 12 month change has increased a little.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes are in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

Covid-19 and Global Warming: Two Problems, Two Responses

June 24, 2020

Skeptics have often faced the argument, “You trust medical experts, so you should trust the climate experts”.  The science, after all, is settled.

That argument is nonsense- there is no comparison between them.

Medical researchers, in the fight against Covid-19, are using the time honoured scientific method used for decades in the search for treatments, vaccines, or cures for a host of crippling and deadly diseases- cancer, diabetes,  HIV, to name a few.

This usually involves years of careful examination of patient data and all existing information and literature, forming an hypothesis to test, designing studies, writing protocols, implementing and evaluating laboratory trials, designing and conducting animal trials, designing and conducting clinical trials, analyzing results, and then reporting findings.  It is a continuous process built on past and current evidence. 

The sought-after treatment or vaccine must pass the tests of safety and efficacy.  Doctors are enjoined: First, do no harm.  As well, the treatment must be effective.  There are many examples of trials that were stopped because they were causing higher risk of harm or were showing no benefit. 

It would be too much to expect automatic success from any of the programs under way around the world to find a safe and effective Covid-19 vaccine.

The same approach is not used in climate science:-

It is assumed that the patient (the world) has an unusually high and increasing temperature, even though patient records indicate periods of higher temperature in the past.

It is assumed that this will continue and will worsen.

It is assumed that this is dangerous and must be treated.

It is assumed that we know the cause, because of an untested hypothesis that increasing concentrations of greenhouse gases in the atmosphere, caused by the burning of fossil fuels, lead to increasing temperatures.

It is assumed that “the science is settled”, (and, even more dangerously, conflicting opinions have been actively suppressed.)

Based on these assumptions, all manner of treatments have been rushed into service, with no testing and no thought for safety or efficacy.   Unwanted and dangerous side-effects have been ignored.  Enormously expensive treatments with no proven or even possible benefit have been implemented, while other treatments (e.g. nuclear energy) are beyond consideration.

Why do I trust medical experts?

When discussing a cancer diagnosis, I trusted my specialist because he showed me the evidence, welcomed a second opinion, discussed the benefits and side-effects of different treatments (and none), gave me research papers on the safety and efficacy of the recommended treatment, and gave me time to think about it.  Nearly three years later the treatment is (so far) successful.

Thank God climate experts are not involved in the search for a Covid-19 vaccine- or cancer treatment.

CO2vid Watch: May

June 8, 2020

I have been wondering whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

Earlier I concluded:  “I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

(In a coming post I will update my expectations for the end of the year and next year.) 

The CO2 concentration number for May is now published: 417.07 p.p.m. (parts per million).  That’s an increase of 0.86 ppm over the April figure, and 2.41 ppm above the figure for May last year.  Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March.

Fig. 1:  12 month change in CO2 concentration since 2015 to May 2020- Mauna Loa

Notice the amount of 12 month change has decreased a little.

Figure 2 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 2:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Note that so far this year, 12 month changes are in the normal or even upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

CO2vid Watch: April

May 7, 2020

In my last post I wondered whether the largest real-life science experiment in history will show whether atmospheric carbon dioxide concentrations will decrease as a result of the Covid19-induced economic slowdown.

I concluded:  I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.”

 Figure 1 shows the 12 month change in CO2 at Mauna Loa since 2015-that is, January to January, February to February, March to March (as in Figure 6 of my previous post):

Fig. 1:  12 month change in CO2 concentration since 2015- Mauna Loa

The CO2 concentration number for April is now published: 416.21 p.p.m. (parts per million).  That’s an increase of 1.71 ppm over the March figure, and 2.89 ppm above the figure for April last year.  Figure 2 is the April update on Figure 1.

Fig. 2:  Updated 12 month change in CO2 concentration since 2015- Mauna Loa

Notice the amount of 12 month change has increased, despite at least two months of downturn in China and at least a month in most other countries.

Figure 3 is a monthly update for 2020 I will show as each month’s CO2 figures become available (and 2021 if necessary):

Fig. 3:  Updated 12 month changes in CO2 concentration for 2020- Mauna Loa

Figure 4 shows the range of 12 month changes for each decade since the record began in 1958:

Fig. 4:  Updated 12 month changes in CO2 concentration all decades- Mauna Loa

Figure 5 shows the same, but just since 2000:

Fig. 5:  Updated 12 month changes in CO2 concentration since 2000- Mauna Loa

Note that so far this year, 12 month changes are in the upper range, and there is no sign of any slow down.

Watch for next month’s update, and enjoy the ride!

Will Covid-19 Affect Carbon Dioxide Levels?

May 2, 2020

The Coronavirus pandemic has already caused a huge downturn in many industries world-wide- especially tourism, manufacturing, and transport.  Prices of oil and thermal coal have fallen dramatically.  The first impact was on China, as this plot from the World Economic Forum shows:

Fig. 1:  Industrial production in China

Industrial production has fallen by 13.5% in January and February, and exports have dropped by 17%.  While China may be recovering from the virus, the rest of the world is not and knock-on effects from low Chinese production of essential inputs will hold back recovery in other countries.

So the question is: if atmospheric concentrations of carbon dioxide and other greenhouse gases are largely a product of fossil fuel emissions, and if fossil fuel emissions decrease, will we see a reduction in the rate of increase of CO2, and if so, how much?

This is the biggest real life experiment we are ever (I hope) likely to see.

Background:

The concentration of CO2 in the atmosphere is increasing, as in Figure 2.

Fig. 2:  CO2 measurements at Mauna Loa

Cape Grim in Tasmania samples the atmosphere above the Southern Ocean and shows a similar trend, with much smaller seasonal fluctuations:

Fig. 3:  CO2 measurements at Cape Grim

But what we are vitally interested in, is how much we may expect CO2 concentration to change.  We can show change, and remove the seasonal signal, by plotting the 12 month differences, i.e., March 2020 minus March 2019.  Thus we can see how much real variation there is even without an economic downturn.  And it is huge.

Fig.4:  12 month change in CO2 concentration- Mauna Loa

Fig. 5:  12 month change in CO2 concentration- Cape Grim

Not very much smaller at Cape Grim.

However, the Mauna Loa record is the one commonly referred to.  Figure 6 shows the 12 month changes since 2015.

Fig.6:  12 month change in CO2 concentration since 2015- Mauna Loa

We will keenly watch the values for the remaining months of 2020, and then 2021.

My expectation?

I will be very surprised if there is much visible difference from previous years at all, as the following plots show.  Figure 7 shows the time series of annual global CO2 emissions and scaled up atmospheric concentration from 1965 to 2018 (the most recent data from the World Bank):

Fig. 7:  Carbon Dioxide Emissions and Concentration to 2018

Fig. 8:  Carbon Dioxide Emissions as a Function of Energy Consumption to 2018

There is a very close match between emissions and energy consumption of all types- including nuclear, hydro, and renewables.

Fig. 9:  CO2 Concentration as a Function of Carbon Dioxide Emissions to 2018

Again, it is close, they are both increasing, but with some interesting little hiccups….

So what is the relationship between change in atmospheric concentration and change in emissions?

Fig. 10:  Percentage Change in CO2 Concentration as a Function of Percentage Change in Carbon Dioxide Emissions to 2018

Not very good correlation: 0.01.

Fig. 11:  Percentage Change in Energy Use, GDP, and Carbon Dioxide Emissions to 2018

GDP fluctuates much more than energy or emissions, which are very close, and if anything tends to follow them.

Figure 12 is a time series of annual percentage change in energy and emissions and absolute change in CO2 concentration.

Fig. 12:  Percentage Change in Energy Use and Carbon Dioxide Emissions and Absolute CO2 Change to 2018

You will note that during the three occasions (1974, 1980-82, and 2008-09) when global emissions growth went negative (as much as minus two percent), CO2 concentration barely moved, and still remained positive, and on two occasions when CO2 concentration increased by 3 ppm or more (1998 and 2016), emissions increase was much reduced. 

Ah-ha, but that’s because the volume of the atmosphere is so huge compared with the amount of greenhouse gases being pumped out- according to the Global Warming Enthusiasts.

In Figure 10 I showed that there was little relationship between annual change in CO2 emissions and atmospheric concentration.  Figure 13 shows what appears to have a much greater influence on CO2 concentrations: ocean surface temperature. 

Fig. 13:  Annual Change in CO2 Concentration as a Function of Change in Sea Surface Temperature (lagged 1 year)

Remember the correlation of CO2 with emissions in Figure 10 was 0.01.  The correlation between CO2 and lagged SSTs is 0.59.  That’s a pretty devastating comparison.

Figure 14 shows how in most years SST change precedes CO2 change throughout the entire CO2 record.

Fig. 14:  Annual Change in CO2 Concentration and Sea Surface Temperatures

There is little evidence for CO2 increase causing SST increase, while there is evidence that SST change (or something closely associated with it) leads to CO2 change.   The largest changes coincide with large ENSO events.

Conclusion:

Therefore, I expect there may be a small decrease in the rate of CO2 concentration increase, but it won’t be much, and I will be surprised if it turns negative.  A large La Nina later this year will lead to a CO2 increase a few months later, in which case there will be a larger downturn in annual CO2 change in 2021.

However, if the major cause of CO2 increase is fossil fuel consumption, there will be an extra large decrease in CO2 change in 2020 and 2021- and a noticeable jump if the global economy rebounds.

As I said, a very large real life experiment. So watch this space!