The Efficiency Factor of Soil Carbon Stock Auditing Methods

The University of Sydney

  • Project code: PRO-015072

  • Project stage: Closed

  • Project start date: Saturday, May 29, 2021

  • Project completion date: Tuesday, May 30, 2023

  • National Priority: TIA - Carbon


For carbon markets to work effectively, we need a soil carbon auditing method that maximises grower profitability and gives purchasers confidence that credits translate to actual carbon sequestration on the ground. To maximise profitability for growers we must better understand the tradeoff between the cost and the potential return on investment of the various auditing methods available. The upfront cost of laboratory-based analysis of soil carbon stock has been a barrier to participation in carbon markets, leading some to suggest cheaper methods should be utilised. Unfortunately, it is difficult to quantify soil carbon stock as carbon concentration and soil bulk density vary significantly.. This means that soil carbon stocks cannot be explicitly quantified.. The uncertainty of the soil carbon stock estimate is critical and should not be overlooked. Carbon markets must operate within this uncertainty and advanced markets rely on discount factors based on confidence levels rather than paying on the simple difference between mean estimates before and after sequestration. The cheapest option available is likely not the best, as cheaper methods commonly have higher uncertainty and this may prove costly to future bottom lines. We propose to investigate four soil carbon auditing methods (laboratory analysis, proximal sensing, remote sensing, and process-based modelling) to compare their relative cost and uncertainty to inform the carbon market under which scenarios each is applicable, and which will maximise carbon farming profitability.


Transformative Industry Action

Research Organisation

The University of Sydney