Soil MMV and the Uncertainty Principle

In its submission to the Garnaut Review, the Carbon Coalition contended that the demands for precision of measurement made of soils go far beyond the exactitude demanded of other sinks.

This is because policy makers have ‘framed’ the question the wrong way. The question should not be: “How can we measure soil carbon with exactitude that matches other forms of carbon sinks or offsets?” The question should be: “How can we construct a measurement system that will satisfy buyers of offsets and make the trade in soil carbon?”

MMV stands for Measurement Monitoring and Verification. It is the process through which greenhouse gas accounting is conducted. It suits trees (above the groundline). But it doesn’t suit soils because soil carbon is subject to “Flux”.

Carbon ‘cycles’ in and out of its ‘sinks’ – soil, ocean, vegetation, and atmosphere (as well as mineral forms in geological deposits, such as coal and diamonds). The movement between atmosphere and soil takes place by several processes: photosynthesis, methane emissions from rotting microbes and dead vegetation, etc. The soil and vegetation “breathes” during the day: breathes out Oxygen during the day and CO2 during the evening. So a measurement taken at midday would be different to one taken at midnight.

However, this is not a barrier to estimating the amount of Carbon in a paddock. Water ‘fluxes’ into and out of the human body. But if your body is 70% water today it is likely to be 70% water tomorrow and next year – unless you change the muscle/fat ratio (the body management style).

US scientists are questioning the importance of ‘flux’ and demanding that soil scientists come into the real world and find solutions:

• Dr John Kimble: "It is often pointed out that soils have a large amount of variability, but with knowledge of soil sciences and landscapes, variability can be described and sampling protocols can be developed to deal with this," writes Dr John Kimble. "One reason I feel people say that soils vary and SOC cannot be measured is that we soil scientists focus on showing variability, not on showing what we know about the variability.” Dr Kimble recently retired from the US Department of Agriculture, National Resources Conservation Service, National Soil Survey Centre, Lincoln, Nebraska. "We too often focus on this [variability], worry about laboratory precision and field variation and do not look at the real world where most things are based on averages and estimated data. We tend to focus on finding variation and not on using our knowledge of soil science to describe what we know. All systems vary, but in soils we focus on a level of precision and accuracy that may not have any relevance to the real world because we can take so many samples and look at the variation."

• Dr Rattan Lal: “While techniques of measuring concentration of C in soils, methodologically sampled and carefully prepared for laboratory analysis, are well known, the principal challenge to soil scientists lies in: (i) upscaling the point data to landscape, farm, watershed or a region comprising 100,000-200,000 ha (ii) evaluating changes in soil C with reference to a baseline for cultivated land unit comprising a large farming community, and (iii) verifying that the C thus sequestered is permanent and not re-emitted because of changes in land use or management practices… Soil and tillage researchers must be pro-active in this important theme.”

The Carbon Coalition contends that the entire Kyoto Protocol process is entangled in uncertainties, and that these uncertainties and ambiguities have been addressed to achieve practical outcomes. We believe soil has been subject to discrimination and hyper-exactitude.

Uncertainty and Forests as C Sinks

Uncertainty afflicts forests as tradable sinks:

• “In soils we can go to a 100m2 field and sample every square meter and look at the differences we find. But if you sample every tree in a large area you would see a similar variability,” says Dr Kimble.

• The Australian Academy of Science stated that “accounting for the carbon contained in forests is difficult. The amount of carbon in forest soils, forest litter and the trees themselves needs to be measured. Different types of trees store different amounts of carbon when growing on different types of soils in different climates. In addition, we might expect natural year-to-year variations in carbon stored, related to climate variations.”

Scientists have accused the Kyoto solution for forests as being riddled with uncertainties: More than 50% of the carbon stored in a forest can be found beneath the ground. Yet it is not counted. This is dangerous because the changes in below ground C-stocks can be in the opposite direction from the changes above ground upon a change in land use.
• “A decline in soil C has been observed in NSW for pastures planted to radiata pine. There are several other examples in the literature of soil C-content being lower under trees than under matched pasture sites and indeed a process-modelling study of pastures in south-central USA planted to pine plantation predicted a decline in soil organic C down to 1m depth over 50 years. Thus if changes in soil C are not included with the estimate of the above ground plantation sink, that plantation sink will be wrongly estimated.”
• “It is possible for a forest to be a source of emissions rather than a sink…. The soil organic pool is a large carbon reservoir: in a mature forest it commonly contains at least 50% of the total forest carbon stock. .. When agricultural land is reforested there may be significant losses from the soil carbon pool… Soil carbon is likely to decrease initially, as a result of a decline in pasture litter inputs in the early phase of plantation establishment, and then increase as litter input from the forest is added to the system. The decline in soil carbon is usually temporary: as the plantation grows, soil carbon will be replenished from litter fall and root turnover, usually restoring soil carbon stock to original levels within 30 years (Paul et al., 2002). If the site being reforested has a high concentration of readily decomposable soil carbon, such as may occur under a heavily fertilised, irrigated pasture, then the soil carbon stock may not reach the level under the previous pasture system. There is some evidence that soil carbon stock is lower under pine plantations than eucalypts (Guo and Gifford, 2002; Paul et al., 2002). …Significant losses of soil carbon after reforestation are most likely in soils that are high in labile carbon, such as where new plantations are established into pastures that have been heavily fertilised, and enhanced productivity has elevated the soil carbon above native levels. … It would be prudent, in predicting forest carbon sequestration, to assume a decline in soil carbon stock for reforestation of pasture soils”

Uncertainty and the Global Greenhouse Gas Protocol

The unavoidable uncertainty the typifies all Climate Change activities is acknowledged in the Greenhouse Gas Protocol developed by the World Resources Institute and the World Business Council for Sustainable Development.

It identifies two types of uncertainty in estimating emissions or sinks:
- scientific uncertainty and
- estimation uncertainty.
The latter is further divided into
- model uncertainty and
- parameter uncertainty. (See Appendix 3)
• Scientific uncertainty arises when the science of the actual emission and/or removal process is not completely understood. For example, many direct and indirect factors associated with global warming potential (GWP) values that are used to combine emission estimates for various GHGs involve significant scientific uncertainty. Analyzing and quantifying such scientific uncertainty is extremely problematic and is likely to be beyond the capacity of most company inventory programs.
• Estimation uncertainty arises any time GHG emissions are quantified. Therefore all emissions or removal estimates are associated with estimation uncertainty. Estimation uncertainty can be further classified into two types: model uncertainty and parameter uncertainty. Model uncertainty refers to the uncertainty associated with the mathematical equations (i.e., models) used to characterize the relationships between various parameters and emission processes. For example, model uncertainty may arise either due to the use of an incorrect mathematical model or inappropriate input into the model. As with scientific uncertainty, estimating model uncertainty is likely to be beyond most company’s inventory efforts;
• “…uncertainty estimates for corporate GHG inventories will, of necessity, be imperfect.”
• “For these reasons, almost all comprehensive estimates of uncertainty for GHG inventories will be not only imperfect but also have a subjective component and, despite the most thorough efforts, are themselves considered highly uncertain.”
• “... a reduction in air travel would reduce a company’s scope 3 emissions. This reduction is usually quantified based on an average emission factor of fuel use per passenger.
• “Generally, as long as the accounting of indirect emissions over time recognizes activities that in aggregate change global emissions, any such concerns over accuracy should not inhibit companies from reporting …

Uncertainty and the National Greenhouse Gas Inventory

Uncertainty is a key aspect of greenhouse emission estimates produced for publication in the National Greenhouse Gas Inventory. The Inventory is compiled from data from a range of sources, and in many cases represents a ‘scaling up’ of sample, experimental or case study results (much in the way Lal recommends). There is an active process of continual improvement underway — but AGO is open about the fact that some estimates are likely to be more reliable than others. For the 2003 NGGI, the AGO estimates an uncertainty band for the estimated national emissions outcome of 550 Mt CO2e ±5.2%.

“Uncertainty over agricultural emissions makes a relatively strong contribution to uncertainty regarding the overall national emissions outcome —particularly with respect to estimates for agricultural soils, savanna burning, forestry and land clearing. However, the reported uncertainties appear to be primarily associated with uncertainty about activity levels rather than the complex and variable biological processes that generate greenhouse gases… The AGO reports that ‘… uncertainty in the reported cattle numbers was the most significant contributor to the overall uncertainty’

Let this be noted and the question be put: Why, if the AGO has access to calculators for at least 5 sectors in Agriculture, have these calculators been delayed in deployment, if the reason given – difficulty in measuring biological processes – is no longer the case?

The methods employed by the AGO to reconcile uncertainties with the Roth C Modelling system reveal an acceptance of a transitional model that reflected Dr John Kimble’s appeal for “real world” science.

“Development of the NCAS was undertaken with the clear understanding that data would be imperfect, but that the significance of data limitations could be assessed only in a functional integrated system.”

The AGO took a ‘fix it in the mix’ approach – making no attempt at ‘precision’: “The tacit acceptance of variability in data provided for a proper focus on matters of accuracy and bias, rather than on potentially unachievable precision.”
The Carbon Coalition welcomes this flexibility and looks forward to the same open-minded, “can do” attitude in its future dealings with Government agencies.