Climate mitigation potential and economic costs of natural climate solutions for main cropping systems across China

Abstract

CONTEXTNatural climate solutions (NCS) offer immediate and cost-effective ways to tackle the climate crisis by transforming atmospheric carbon to soil carbon or avoiding greenhouse gas emissions. However, the climate mitigation potential and economic costs of NCS for cropping systems in China remain inconclusive. OBJECTIVEThe major objectives of this study are (i) to estimate the NGHG reduction potential across Chinese main cropping systems caused by NCS, (ii) to quantify the economic costs of adopting optimal management with different abatement potentials. METHODSThe Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N2O emissions, and CH4 emissions. After calibration, we ran the DNDC model with derived data at municipality-level. We estimated the NGHG under current management, adopting optimal management individually, and integrated optimal management to project the maximum NGHG reduction potential caused by NCS. We used the marginal abatement cost method to estimate the economic cost. RESULTS AND CONCLUSIONSThe four natural climate solutions, N fertilization management (NFM), straw returning management (SRM), tillage management (TM), and rice irrigation management (RIM) can reduce national NGHG in main cropping systems by approximately 118.8 Tg CO2-eq, 116.3 Tg CO2-eq, 35.2 Tg CO2-eq, and 74.4 Tg CO2-eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO2-eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO2-eq)−1. We further identify the priority NCS for different crops and regions and conclude that nitrogen fertilization management should be the priority NCS at the national level. SIGNIFICANCEOur findings highlight the great potential of NGHG reduction by adopting NCS precisely and the importance of optimizing agricultural management as a whole, and they will help policy makers to develop smart-agriculture in China.