Mitigation of CO2 and N2O emission from cabbage fields in Korea by Optimizing Tillage Depth and N-Fertilizer Level: DNDC model simulation under RCP 8.5 Scenario

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Abstract

In this study, we applied the Denitrification and Decomposition model to predict the greenhouse gas (GHGs; CO2 and N2O) emissions and cabbage yields from 8072 cabbage fields in Korea in the 2020s and 2090s. Model outputs were evaluated as a function of tillage depth (T1, T2, and T3 for 10, 20, and 30 cm) and fertilizer level (F1, F2, and F3 for 100, 200, and 400 kg N ha-1) under the Representative Concentration Pathways 8.5 climate change scenario. For both time periods, CO2 emissions increased with tillage depth, and N2O emissions were predominantly influenced by the level of applied N-fertilizers. Both cabbage yields and GHGs fluxes were highest when the T3F3 farming practice was applied. Under current conventional farming practices (T1F3), cabbage yield was projected at 64.5 t ha-1 in the 2020s, which was close in magnitude to the predicted cabbage demand. In the 2090s, the predicted cabbage supply by the same practice far exceeded the projected demand at 28.9 t ha-1. Cabbage supply and demand were balanced and GHGs emissions reduced by 19.6% in the 2090s when 94% of the total cabbage farms adopted low carbon-farming practices (e.g., reducing fertilizer level). Our results demonstrate the large potential for Korean cabbage farms to significantly contribute towards the mitigation of GHGs emissions through the adoption of low-carbon farming practices. However, in order to incentivize the shift towards sustainable farming, we advise that lower yield and potential economic losses in farmlands from adopting low-carbon practices should be appropriately compensated by institutional policy.

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APA

Hwang, W., Park, M., Cho, K., Kim, J. G., & Hyun, S. (2019). Mitigation of CO2 and N2O emission from cabbage fields in Korea by Optimizing Tillage Depth and N-Fertilizer Level: DNDC model simulation under RCP 8.5 Scenario. Sustainability (Switzerland), 11(21). https://doi.org/10.3390/su11216158

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