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Natural 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. The 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. The Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N 2 O emissions, and CH 4 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. The 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 CO 2 -eq, 116.3 Tg CO 2 -eq, 35.2 Tg CO 2 -eq, and 74.4 Tg CO 2 -eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO 2 -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. Our 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. [Display omitted] • Estimating net greenhouse gas emissions (NGHG) reduction potentials of agriculture. • IPCC recommended tier 3 method was applied for seven cropping systems in China. • The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq. • 80% of NGHG mitigation can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. • The priority NCS was identified for different crops and regions. [ABSTRACT FROM AUTHOR]

Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO 2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO 2 -emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO 2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO 2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down. [Display omitted] [ABSTRACT FROM AUTHOR]

Promoting technology development co-operation is particularly relevant while addressing global climate change or regional pollution. Investors may contribute to increasing environmental-related patents, which may help to improve the quality of the environment as long as supported by proper regulations and policies. In the quest towards a cleaner environment via the mitigation of climate change, this study investigates the relationship between technological innovation, income level, renewable energy and carbon emissions in both the United States and China. Applying the dynamic auto-regressive distributive lag (DARDL) simulation method revealed varying impacts of regressors on CO 2 emissions in the short-run and long-run. Accordingly, this study empirically confirms that (i) technological innovation reduces carbon emissions in the United States but it is not statistically significant in China. (ii) Renewable energy reduces carbon emissions in both countries. (iii) The impact of income level on emissions decreases from short-run to long-run in both countries. Decision-makers in China should stimulate more effective environmental-related innovations to decrease CO 2 emissions and should permit easy access to environmental-related patents together with reducing its cost of registration. • Investigates the role of green technological innovation in decreasing CO 2 emissions. • Applies the novel Dynamic ARDL simulation. • Green technological innovation reduces CO 2 emissions in the U.S. Only. • Confirms that renewable energy mitigates CO 2 emissions both in the U.S. and China. [ABSTRACT FROM AUTHOR]