THIS POST IS A CRITICAL EVALUATION OF AN ARTICLE ON EUREKALERT BY THE KARLSRUHER INSTITUT FÜR TECHNOLOGIE THAT FOUND THAT THE GLOBAL CO2 EMISSION REDUCTION OF THE CORONA VIRUS PANDEMIC DID NOT SLOW DOWN THE RISE IN ATMOSPHERIC CO2 CONCENTRATION. LINK TO SOURE DEOCUMENT: https://www.eurekalert.org/pub_releases/2020-09/kift-cce092120.php

RELATED POST:  AN EXCLUSIVE RELIANCE ON FOSSIL FUEL EMISSIONS OVERLOOKS NATURAL CARBON FLOWS. [LINK]  

PART-1: WHAT THE SOURCE DOCUMENT SAYS

1. Corona-induced CO2 emission reductions are not yet detectable in the atmosphere. Effects of the pandemic will be detected in the atmosphere much later – To reach the Paris climate goals, decade-long measures are needed.
2. Restrictions of social life during the corona pandemic can be predicted to lead to a reduction of worldwide carbon dioxide emissions by up to 8% in 2020. According to the IPCC, cumulative reductions of about this magnitude would be required every year to reach the goals of the Paris Agreement by 2030.
3. Recent measurements by researchers of Karlsruhe Institute of Technology (KIT) revealed that concentration of carbon dioxide (CO2) in the atmosphere has not yet changed due to the estimated emission reductions. The results are reported in Remote Sensing (DOI: 10.3390/rs12152387). The corona pandemic has changed both our working and our private lives. People increasingly work from home, have video conferences instead of business trips, and spend their holidays in their home country. The lower traffic volume also reduces CO2 emissions. Reductions of 8% are estimated for 2020.
4. In spite of the reduced emissions, our measurements show that CO2 concentration in the atmosphere has not yet decreased,” says Ralf Sussmann from the Atmospheric Environmental Research Division of KIT’s Institute of Meteorology and Climate Research (IMK-IFU), KIT’s Campus Alpine, in Garmisch-Partenkirchen. “To reduce CO2 concentration in the atmosphere in the long run, restrictions imposed during the corona pandemic would have to be continued for decades. But even this would be far from being sufficient.”
5. To prove this, researchers additionally studied a long-term scenario that can be controlled well with atmospheric measurements: The goal of the Paris Climate Agreement to limit global warming to 1.5 degrees Celsius can only be reached by an immediate significant reduction of CO2 emissions and a further decrease down to zero by 2055. “The restrictions imposed during the corona crisis, however, are far from being sufficient. They have just resulted in a one-time reduction by eight percent. To reach zero emissions in the coming decades, cumulative reductions of the same magnitude would be required every year, i.e. 16 percent in 2021, 24 percent in 2022, and so on. For this, political measures have to be taken to directly initiate fundamental technological changes in the energy and transport sectors,” Sussmann says.
6. For the study, the team used data from the Total Carbon Column Observing Network (TCCON). It measured the concentrations in different layers of the atmosphere above Garmisch-Partenkirchen and at other places around the globe. “High-tech infrared spectrometers are applied, which use the sun as a light source. The measurement method is highly precise, uncertainties are in the range of a few thousandths.
7. Long Life of CO2 Prevents Early Detection: According to the researchers, the long life of CO2 and the high background concentrations that have accumulated since the start of industrialization prevent the changes in the atmosphere from being detected. “But also natural impacts make early detection difficult: Anthropogenic emissions, the main cause of the long-term increase in atmospheric CO2, are superposed by annual fluctuations of the growth rate due to natural climate variabilities of ocean sinks and land vegetation,” Sussmann says. Successful emission reduction, hence, is hard to detect by atmosphere measurements.
8. For their study, the researchers compared the TCCON measurements with the prognoses of the atmospheric growth rate for 2020 – with and without corona restrictions. “Precision analysis of atmosphere measurements revealed that the impacts of COVID-19 measures on the atmosphere might be measured after little more than six months, if the reference state without COVID-19 would be predicted precisely,” the climate researcher explains. “In any case, we would be able to find out within presumably two and half years, whether global political and social measures will help us find viable alternatives of fossil fuels and reach the goals of the Paris Climate Agreement.”

ABOUT KIT: Sussmann, R., and Rettinger, M.: Can We Measure a COVID-19-Related Slowdown in Atmospheric CO2 Growth? Sensitivity of Total Carbon Column Observations, Remote Sens., 12, 2387, 2020. doi:10.3390/rs12152387: Being “The Research University in the Helmholtz Association”, KIT creates and imparts knowledge for the society and the environment. It is the objective to make significant contributions to the global challenges in the fields of energy, mobility, and information. For this, about 9,300 employees cooperate in a broad range of disciplines in natural sciences, engineering sciences, economics, and the humanities and social sciences. KIT prepares its 24,400 students for responsible tasks in society, industry, and science by offering research-based study programs. Innovation efforts at KIT build a bridge between important scientific findings and their application for the benefit of society, economic prosperity, and the preservation of our natural basis of life. KIT is one of the German universities of excellence

PART-2: CRITICAL COMMENTARY

The issue here is not the time span but the uncertainty in carbon cycle flows that are an order of magnitude larger (around 100+ gigatons of carbon per year each with uncertainties of {+/-} 10 gigatons as for example in the flows from atmosphere to photosynthesis, atmosphere to ocean, ocean to atmosphere, respiration to atmosphere, and so on.

We show in related posts, that when these uncertainties are ignored and certainty is assumed, the data verify the so called “retained fraction” of about 50% assumed by climate science and standardized by the IPCC. However, when these uncertainties are included, no relationship between fossil fuel emissions and changes in atmospheric composition can be detected.

RELATED POST#1: A MONTE CARLO SIMULATION OF THE INSERTION OF FOSSIL FUEL EMISSIONS INTO THE CARBON CYCLE: LINK: https://tambonthongchai.com/2020/06/10/a-monte-carlo-simulation-of-the-carbon-cycle/

Here we find that the contribution of fossil fuel emissions of 37 gigatons of CO2 is estimated as a “retained fraction” of 17.5 gigatons of CO2, close to the 50% retained fraction used by climate science and the IPCC. When uncertainties in carbon cycle flows are ignored, the retained fraction used in climate science is confirmed.

However, when the uncertainty in carbon cycle flows is not ignored, the retained fraction amount of 17.5 gigatons of CO2 is found to contain an uncertainty given by a standard deviation of 46.5 gigatons. The corresponding t-statistic is t=0.375 with a p-value close to the pure ignorance in the middle of the normal distribution.

The large uncertainty in the estimate of the retained fraction implies an absence of information meaning that given the large uncertainties in carbon cycle flows it is not possible for us to know the effect on atmospheric composition of relatively low flows of fossil fuel emissions – approximately 10% of carbon cycle flows. To ignore these uncertainties and estimate the impact of fossil fuel emissions on atmospheric composition in terms of the estimated 17.5 gigatons as a 50% retained fraction is a form of confirmation bias and circular reasoning explained in a related post on this site: LINK to confirmation bias post: https://tambonthongchai.com/2018/08/03/confirmationbias/

This uncertainty condition is confirmed with a second Monte Carlo simulation using a different computational method in another related post at this site: LINK https://tambonthongchai.com/2018/05/31/the-carbon-cycle-measurement-problem/ . The results are summarized below.

CHART-1: TABULATION OF RESULTS

CHART-2: GRAPHICAL REPRESENTATION OF RESULTS

In the Monte Carlo simulation we assigned different levels of uncertainty to the flows for which no uncertainty data are available from the IPCC and test the null hypothesis that the flows balance with Anthropogenic Emissions (AE) included and again with AE excluded. If the flows balance when AE are included and they don’t balance when AE are excluded then we conclude that the presence of the AE can be detected at that level of uncertainty. However, if the flows balance with and without AE then we conclude that the stochastic flow account is not sensitive to AE at that level of uncertainty because it is unable to detect their presence. If the presence of AE cannot be detected no role for their effect on climate can be deduced from the data at that level of uncertainty in natural flows. The balance is computed from the atmospheric perspective as Balance=Input-Output where Input is flow to the atmosphere and Output is flow from the atmosphere. The p-values for hypothesis tests for uncertainties in the natural flows from 1% of mean to 6.5% of mean are presented as a tabulation in CHART-1 and graphically in CHART-2.

CHART-1 shows the assumed percent standard deviation in the natural flows for which no uncertainty information is available in the IPCC reports. In the base case, the blanket statement by the IPCC that the uncertainty is 20% is interpreted to mean that the width of the 95% confidence interval is 20% of the mean and the corresponding standard deviation computed as (20/2)/1.96. The data in each row shows the p-values of two hypothesis tests labeled as WITH and WITHOUT. The WITH column shows p-values when the AE are included in the balance computation. The WITHOUT column shows the p-values when the AE are left out of the balance computation.

We use a critical p-value of alpha=0.1 for the test of the null hypothesis that Balance=0. Balance=0 means that the stochastic flow account is in balance. If the p-value is less than apha we reject the null hypothesis and conclude that the stochastic flow account is not in balance. If we fail to reject the null then we conclude the stochastic flow account is in balance. The p-values for WITH and WITHOUT in each row taken together tell us whether the stochastic flow system is sensitive to AE, that is whether the relatively small AE flow can be detected in the context of uncertainty in much larger natural flows.

If we fail to reject the null hypothesis that Balance=0 in both WITH and WITHOUT columns, the stochastic flow account balances with and without the AE flows. In these cases the stochastic flow account is not sensitive to AE, that is it is unable to detect the presence of the AE flows. This is true for the five rows in which the uncertainty in natural flows is 3% of mean or higher.

For the two lower uncertainty levels of 2% and 1% we find that the null hypothesis Balance=0 is not rejected when AE are included (the stochastic flow account is in balance) but rejected when AE are not included (the stochastic flow account is not in balance). Under these uncertainty conditions, the stochastic flow account is sensitive to the presence of AE, that is the flow account can detect the presence of the relatively small AE flows.

CHART-2 shows that the crossover uncertainty lies somewhere between 2% and 3% and in fact it is found by trial and error that the crossover occurs at 2.3%. Since the IPCC carbon cycle flow uncertainties are greater than 2,3%, our results imply that the carbon cycle stochastic flow balance is not sensitive to the presence of the relatively small flows of fossil fuel emissions.

The underlying issue is that the large natural carbon cycle flows cannot be directly measured and they can only be indirectly inferred. These inferred values contain uncertainties much larger than 2.3% of the mean. It is not possible to carry out a balance of the carbon cycle under these conditions that can detect the relatively small fossil fuel emissions.

In climate science, carbon cycle flows that are an order of magnitude larger than fossil fuel emissions and that cannot be directly measured are inferred with the implicit assumption that the increase in atmospheric CO2 comes from fossil fuel emissions. The flow balance can then be carried out and it does of course show that the increase in atmospheric CO2 derives from fossil fuel emissions. The balance presented by the IPCC with inferred flows thus forces an exact balance by way of circular reasoning.

Therefore, the IPCC carbon cycle balance does not contain useful information that may be used to ascertain the impact of fossil fuel emissions on the carbon cycle or on the climate system.

A confirmation of the findings in the two related posts cited above is provided with with detrended correlation analysis in a third related post at this site. LINK TO CORRELATION ANALYSIS POST: https://tambonthongchai.com/2018/12/19/co2responsiveness/

The data and analysis are summarized graphically in the below.

In charts below we find that no detrended correlation is found, at any of the five time scales tried, to relate observed changes in atmospheric composition to fossil fuel emissions.

Details of these analyses are provided in the related post cited above.

We conclude from the detrended correlation analysis that atmospheric composition specifically in relation to the CO2 concentration is not responsive to the rate of fossil fuel emissions. This finding is a serious weakness in the theory of anthropogenic global warming by way of rising atmospheric CO2 attributed to the use of fossil fuels in the industrial economy; and of the “Climate Action” proposition of the UN that reducing fossil fuel emissions will moderate the rate of warming by slowing the rise of atmospheric CO2. The finding also establishes that the climate action project of creating Climate Neutral Economies, that is Economies that have no impact on atmospheric CO2, is unnecessary because the global economy is already Climate Neutral.

THEREFORE, THE FINDING OF THE  Karlsruhe Institute of Technology (KIT) STUDY THAT ATMOSPHERIC COMPOSITION IS UNRESPONSIVE TO EMISSION REDUCTIONS IMPOSED BY THE COVID PANDEMIC CAN BE UNDERSTOOD IN TERMS OF UNCERTAINTIES IN CARBON CYCLE FLOWS AND WITHOUT THE NEED FOR THE CIRCULAR REASONING AND CONFIRMATION BIAS EXPLANATION OFFERED BY KIT THAT THE OBSERVATION PERIOD WAS BRIEF AND THAT THE ABSENCE OF THE RESPONSIVENESS OF ATMOSPHERIC COMPOSITION TO FOSSIL FUEL EMISSION REDUCTION MUST THEREFORE BE DUE TO THE BREVITY OF THE TIME SCALE AT WHICH IT WAS TESTED BECAUSE WE KNOW DEEP IN OUR HEARTS THAT FOSSIL FUEL EMISSONS CHANGE ATMOSPHERIC COMPOSITION.

RELATED POST ON CONFIRMATION BIAS: LINK: https://tambonthongchai.com/2018/08/03/confirmationbias/

RELATED POST:  AN EXCLUSIVE RELIANCE ON FOSSIL FUEL EMISSIONS OVERLOOKS NATURAL CARBON FLOWS. [LINK]  

FOOTNOTE: IN CLIMATE SCIENCE, THE RESPONSIVENESS OF ATMOSPHERIC CO2 TO FOSSIL FUEL EMISSIONS IS ASSSESSED AT AN ANNUAL TIME SCALE. IT IS NOTED THAT THE COVID EMISSION REDUCTION PERIOD IS LESS THAN A YEAR. THE QUESTIONS RAISED BY BY THE KARLSRUHER INSTITUT AND OTHERS IN THIS REGARD DO NOT MEET THIS TIME SCALE REQUIREMENT.