Carbon projects are expensive. A lot of that is due to the complexity of the governance and measurement requirements involved. Choosing the right software to use is all about ROI and reducing this cost. When a user develops a soil carbon project, they must take a series of steps to comply with registration. These include:
– Defining the legal land boundaries and project boundaries.
– Excluding any areas that are not going to be used in the project.
– Stratifying an area and determining the locations to sample.
– Conducting soil sampling and calculating the total carbon over the project area, and the carbon’s change across the life of the project
While these steps may sound simple, if you’re a carbon developer you know each step involves complex, time consuming tasks. For example, under the Australian Clean Energy Regulator protocol a developer must use over 20 equations to calculate the amount of carbon across a project area for a sample round. Project developers must also confirm legal land titles, manually draw exclusion areas within those geographic boundaries and then attempt to stratify based on land forming factors.
Often, the entire process takes days, requiring back and forth with the land manager, sifting through government databases to determine boundaries and finding the latest satellite imagery to develop strata. Finally, before carbon offsets are issued, there needs to be an audit by an independent auditor. All of the above steps and logic around how the project was developed is sifted through and questioned.
We estimate the total amount of time spent by a carbon developer per sample round (which occurs every 3 years) to register a farmer and manage a project is about 60 hours per year.
This is purely to get the project registered and managed, and doesn’t include all the hours spent working with the farmer to help get them trained on new practices required to improve carbon.
Where possible, software should be used to automate and streamline processes. That’s why FarmLab has introduced soil science best practices (such as that developed by CSIRO and the FAO on how to measure and map carbon), alongside state-of-the-art geospatial software, to reduce the cost and complexity of carbon projects. Here’s how much time we think it saves:
Developing a project sample plan, 5+ hours per sample round when compared to legacy techniques. FarmLab gives its users tools to automatically generate exclusion areas using tree cover. In a soil carbon project, any areas with >20% canopy cover need to be excluded. Using the software, clients can automatically remove tree cover from their project. For more information check out our guide on removing tree cover from projects. Once exclusion areas have been determined, users can quickly and easily stratify by soil type (or any other parameters they believe drive carbon) and generate sample points against those locations. This is again done with the click of a button, and for a full explanation on how this is done see our stratification guide.
Project registration and audits, 10+ hours per sample round.
Using the sharing and export features in the software, users can share their sample plan with the regulator. If the FarmLab mobile app is used for sample collection (usually with an integration with a handheld GPS for accuracy), then a complete audit trail is developed – meaning complete integrity for the carbon offsets generated. FarmLab are currently working with global carbon auditors GHD to streamline audit services and ultimately reduce their cost using the platform. Clients can even share their farms as ‘read only’ to buyers and consumers looking for transparency around farm sustainability.
Soil Sampling, 10 hours per sample round + 15% improvement in data accuracy.
Under the Clean Energy Regulator protocol, soil samplers must conduct their sampling in a specific manner to ensure various data points are collected in the field, and the protocol is followed. This includes recording the depth of each sample, removing it as a full core before splitting it into two sections, and recording data associated with that core. If any of this is mismanaged, it can jeopardise the results – and the entire project. Fortunately, we built the FarmLab mobile app to streamline soil sampling, and by introducing specific fields related to carbon sampling, such as core length and diameter, we’re able to force the capture of the necessary data points while out in the field. Because all of this can be recorded in the mobile app, alongside the barcode and geolocation of a soil sample, users don’t have to double-handle datasets or upload results after the day has finished. Also, if the GPS is linked directly to the mobile device, our clients can automatically update their planned sample location with their ‘actual location’, meaning no more manually updating locations back in the office.
Calculating the amount of carbon and accuracy across a project area, 5 hours per sample round.
This is one of the most important parts of any project, but it’s also the part where we see the most mistakes. At the end of the project a developer must calculate the amount of carbon, often in tonnes to specified depths, across the project area. This is not as easy as it sounds and involves multiple calculations determined by the market regulator. If done correctly, the user will end up with two numbers: the amount of carbon across the project, and the variance of carbon based on the sample points (used to indicate sampling accuracy later on). Because FarmLab has worked closely with the Australian Clean Energy Regulator and experts in the industry to build these calculations directly into the software, once samples have been collected and results returned, a client only needs to run the calculations across their strata to get those answers. It’s hard to quantify how much time this saves, as many developers will have their own spreadsheets, but therein lies another problem. With many spreadsheets, and many developers inputting data their own way, there can often be large errors between them. By working from one source code, that’s approved by the regulator, we solve a lot of those errors. By solving the back and forth, as well as replacing excel spreadsheets that continuously need updating with the new methodology, we estimate time-saving here is equivalent to about 5 hours per sample round.
Total cost savings
If we sum up the average cost saving per sample round, we reach about 30 hours. An average sample round occurs every 3 years, so we’re looking at about 10 hours a year on average. At a consulting rate of $180 p/h, this assumes a $1,800 per annum in savings per project per year.
But we wouldn’t be much of a software company if the license we charged offset the cost of the savings would we?! We have a guiding principle about our software – it has to be cheap but powerful. To back this up we offer low cost plans for clients who want to run projects. On a basic plan our clients can run 5 x projects (at approx. 1,000ha a project) for as low as $250 per month. That’s $600 per farm, per year – about 30% of the savings generated just by using it. In fact, it pays for itself 3 times over!
While there are many assumptions that drive this cost-benefit analysis that are going to vary by developer, it’s important to emphasise the ‘qualitative’ side to choosing the right software too. By collecting data in an auditable, clear fashion with FarmLab, project developers can ensure data is available to be shared with clients, auditors and market regulators when they need it. This not only helps project compliance, but helps build the reputation of the market, supporting the generation of transparent carbon offsets and the story of sustainability across the supply chain.