Adopting a Beneficial Carbon Farming in the Cropping Pattern using an Optimization Technique: A Case Study
Abstract
Plants can capture CO 2 from the air and sequester it in the leaves through photosynthesis. Even additional carbon sequestration could be achieved by allowing higher cropping intensity on the same piece of land in a single cropping season. There is a growing demand that agricultural developers and practitioners consider carbon farming in the design of cropping patterns in order to intensify carbon sequestration and trade it as a carbon credit for extra financial benefits. However, adopting a sustainable carbon farming while respecting the farmer’sneeded income and food security may seem a difficult task. Nevertheless, this fundamental challenge can be addressed using an optimization technique such as simplex linear programming (SLP). The Microsoft Excel program includes a SLP solver tool, which can easily be accessed from the Excel program Data menu after activating the Add-Ins part of the Excel Options. In this study, seven scenarios were developed to be analyzed by the SLP to investigate the various options of adopting carbon farming into the cropping pattern while maximizing either the individual or the combined benefits of farmer’sincome and farmer’sfood security for the Mekabo irrigation scheme in Ethiopia. The result shows that the optimized cropping pattern in scenario seven best satisfies the farmer’sfood security and farmer’sincome while still stimulating extra financial benefits from carbon farming. Alley cropping, multi-species-cover cropping, and no-till planting in scenario seven could encourage the highest rate of additional carbon sequestration so it could better contribute to the alleviation of global warming. This paper will discuss how the SLP is developed and applied leading to the attainment of an optimized cropping pattern while the financial benefit is maximized.
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Introduction
With the growing threat of global warming, it is expected the industries that can not halt releasing Carbon Dioxide (CO ) into 2 the atmosphere, at least try to offset their emissions through partnering with carbon mitigators who can remove CO from the air 2 on their behalf. This process has triggered the birth of carbon credit exchange (CCX) in the global market and is still rising. Crops cultivated in the agricultural lands are known to be a consistent driver for capturing CO from the air and sequestering it 2 into different forms of carbon through photosynthesis. Even additional carbon sequestration could be achieved by allowing higher cropping intensity on the same piece of land in a single cropping season. Crops cultivated in the millions of ha of agricultural lands in any given country can significantly contribute to the massive carbon sequestration in the plants and soils. Accordingly, there is a growing demand that agricultural developers and practitioners accommodate carbon farming in the cropping pattern as an integrated part of their agricultural practices for both its positive environmental impact and financial benefits from selling the carbon credit in the CCX market.
The land-based carbon sequestration is measured in metric tons per hectare and one metric ton earns one carbon credit. In California – the only state in the US with a full-fledged cap-and-trade program – the current value of a carbon credit is around $12 to $13. Alberta, which has the most robust carbon market in Canada rewards several agricultural practices with carbon credits of up to $30 per credit [1]. According to the global pricing of various types of carbon credits, the current carbon credit produced from plantation ranges from $US 2.2 to 20+ depending on the project type, size, location, and other determining factors [2].
Adopting carbon farming in the cropping pattern while several agronomic and environmental constraints should also be considered may seem a challenging task. However, an optimization technique such as the Simplex Linear Programming (SLP) can assist to tackle this complex issue. The SLP quantifies an optimal way of integrating the constraints to optimize crop production, financial profits, and carbon farming. Favorably, the Microsoft Excel includes a Linear Programming Solver, which could be applied to solve this optimization problem. The principal objective of this paper is to use the SLP as a case study example to investigate different carbon sequestration scenarios to define the best beneficial option.
Conclusion
Seven scenarios were developed, and a simplex linear programming (SLP) was utilized to study various options of adopting carbon farming into the cropping pattern while maximizing either the individual or the combined benefits of farm income, farmer’sfood security, and additional carbon sequestration in the Mekabo irrigation scheme. The Solver tool from Microsoft Excel program was used to run the SLP. The results show that additional carbon farming increased the amount of carbon sequestration and created the potential for extra financial benefits from selling carbon credits. Figure 5 compares the total financial benefits and the rate of additional carbon sequestered in all scenarios. Among the scenarios, there is no additional carbon sequestration in scenarios 1, 2, and 6. However, among the remaining scenarios, scenario 7 has the highest rate of additional carbon sequestration (1.2 ton/ha/year). Because there are no meaningful financial benefit differences among scenarios 3, 4, 5, and 7; therefore, it could be concluded that scenario 7 is the most beneficial scenario because it has the highest rate of additional carbon sequestration while satisfies the benefit of farmer’sfood security and still generates relatively a good farming income. Alley cropping, multi-species-cover cropping, and no-till planting in scenario 7 could encourage the highest rate of additional carbon sequestration so it could have abetter role in the alleviation of global warming. 6.00 400,000 d 347,300 ere ts e u q e S n o bra C la n oitidg nim ra F n o bra C o t e u D )ra e y / a h / n o T ( 1 2 3 4 5 . . . . . 0 0 0 0 0 0 0 0 0 0 176,974 230,06 1 2 .00 251,48 1 6 .00 245,39 1 4 .00 177,411 244,7 1 8 . 9 20 5 1 1 2 2 3 3 0 0 5 0 0 5 5 , 0 0 0 0 0 0 0 , , , , , ,0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 g n id u lc n I stifen e B la toT g nim ra F n o bra C )ra e y / a h / rriB T E ( d A 0.00 0.00 0.00 0.00 0 1 2 3 4 5 6 7 o o o o o o oira ira ira ira ira ira iran n n n n n n e e e e e e e c S S S c S c S c S c S Scenarios Additional Carbon Sequestred Due to Carbon Farming (Ton/ha/year)
Total Financial Benefits Including Carbon Sequestration Benefits (ETBirr/ha/year)
FIGURE 5. Comparison of total financial benefits and the additional carbon sequestration