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1. Underestimation of Future Agricultural Soil N ₂ O Emissions and Abatement Needs

   https://doi.org/10.1111/gcb.70919  

   Lu, Chaoqun; Li, Linchao; Winiwarter, Wilfried; Canadell, Josep G; Liu, Weihang; Tian, Hanqin (May 2026, Global Change Biology)

   ABSTRACT Agricultural soils are the largest human‐induced source of nitrous oxide (N₂O) due to the extensive fertilizer use in crop production. Despite progress made in global N₂O budget accounting, using the IPCC‐derived static emission factors (EF) limits our capability to project future changes in agricultural N₂O emissions and identify cost‐effective mitigation strategies. Here, we use a physics‐informed AI‐driven dynamic EF modeling framework to project direct agricultural soil N₂O emissions induced by mineral fertilizer additions under various climate and nitrogen (N) regulation policy scenarios. Compared to projections based on static EF, our study yields higher future N₂O emissions by 0.3–1.1 Tg N year⁻¹across scenarios by 2050, implying greater abatement needs to combat climate change. The gap between static and dynamic EF approaches is projected to widen to 29%–34% by mid‐century. Under moderate‐ to high‐ambition N regulation policies, we project that a 25% emission reduction can be reached before 2050, while a 45% reduction is only attainable under high‐ambition N policies and strong climate action. The potential for N₂O mitigation due to a policy shift varies substantially among regions, with seven top source regions contributing 76%–87% of global N₂O reduction. Adopting N₂O reduction technologies in hotspot areas would significantly accelerate the timeline for achieving the 25% reduction goal. Improving fertilizer management on croplands can provide climate benefits comparable to, or even exceeding, those of enhancing soil carbon sequestration, particularly in regions with low nitrogen use efficiency. Our findings highlight the higher mitigation potential of targeting N₂O emission hotpots and the urgency of implementing policy shifts. 

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2. Global dynamic emission factors for estimating direct nitrous oxide emissions associated with synthetic fertilizer inputs under different scenarios

   https://doi.org/10.6084/m9.figshare.26384401  

   Li, Linchao; Lu, Chaoqun; Winiwarter, Wilfried; Tian, Hanqin; CANADELL, Josep G; Ito, Akihiko; Jain, Atul K; Kou-Giesbrecht, Sian; Pan, Shufen; Pan, Naiqing; et al (July 2024, figshare)

   This dataset contains yearly projections of emission factors (EFs) for fertilizer-induced direct nitrous oxide (N2O) emissions across the global agricultural lands with a spatial resolution of 0.5° × 0.5° from 1990 to 2050. Emission factor (EF) is defined as the amount of N2O emitted per unit of nitrogen (N) fertilizer applied, expressed in percentage (%). They are developed from a hybrid modeling framework, Dym-EF (more details can be found in Li et al., 2024). The framework integrates machine learning approaches with an ensemble of eight process-based models from The Global N2O Model Intercomparison Project phase 2 (NMIP2) to learn the relationship between EF dynamics and multiple environmental factors, such as climate, soil properties, nitrogen fertilizer input, and other agricultural management practices. After the hybrid modeling framework was extensively validated, we applied it to develop EF projections under different nitrogen management policies and climate change scenarios, including future climate data from 37 Global Climate Models (GCMs). The annual median and standard deviation (SD) of EF under each scenario represent the projection median and variability derived from climate input data using the 37 GCMs.The dataset filenames follow the structure: 'Scenario'_'N regulation'_'Median/SD', where 'Scenario' corresponds to the different nitrogen management and climate scenarios (e.g., INMS1, INMS2, and INMS3), 'N regulation' corresponds to the different nitrogen management levels (e.g., BAU, LowNRegul, and MedNRegul), and 'Median/SD' indicates whether the file contains the median (Median) or standard deviation (SD) of the projections. All relevant data and further details can be found in the supplementary materials and the cited references.INMS1: Business-as-usual, Land use regulation: Medium, Diet: Meat & dairy-rich, Ambition level: LowINMS2: Low-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: LowINMS3: Medium-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: ModerateINMS4: High-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: HighINMS5: Best-case, Land use regulation: Strong, Diet: Low meat & dairy, Ambition level: HighINMS6: Best-case “Plus”, Land use regulation: Strong, Diet: Ambitious diet shift and food-loss/waste reductions, Ambition level: HighINMS7: Bioenergy, Land use regulation: Strong, Diet: Low meat & dairy, Ambition level: HighWe developed this data using the “ranger” package in R 4.1.1, which is accessible at https://cran.r-project.org/web/packages/ranger/. The optimization of the two hyperparameters (ntree and mtry) was performed using the ‘caret’ package, available at https://topepo.github.io/caret/.This database is developed by Li, L., C. Lu, W. Winiwarter, H. Tian, J. Canadell, A. Ito, A.K. Jain, S. Kou-Giesbrecht, S. Pan, N. Pan, H. Shi, Q. Sun, N. Vuichard, S. Ye., S. Zaehle, Q. Zhu. Enhanced nitrous oxide emission factors due to climate change increase the mitigation challenge in the agricultural sector Global Change Biology (In Press) 

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3. Future projections of agricultural soil nitrous oxide emissions associated with global synthetic fertilizer inputs

   https://doi.org/10.6084/m9.figshare.32194662  

   Lu, Chaoqun; Li, Linchao; Winiwarter, Wilfried; Canadell, Josep G; Tian, Hanqin; Liu, Weihang (May 2026, figshare)

   This database is developed by Lu, C., L. Li, W. Winiwarter, J. G. Canadell, W. Liu, H. Tian. Underestimation of future agricultural soil N₂O emissions and abatement needs. Global Change Biology (In Press)This database provides annual projections of fertilizer-induced direct soil nitrous oxide (N2O) emissions across the global croplands and pasture at a spatial resolution of 0.5° × 0.5° from 2010 to 2050. We use the Dym-EF model (Li et al., 2024) to project how agricultural soil N2O emissions would change under various future climate scenarios and nitrogen regulation policies at different ambition levels. The scenario set is developed by the project “Toward an International Nitrogen Management System (INMS, Kanter et al., 2020)” that combines future changes in climate (SSP scenarios) and N policy interventions with high, moderate, and low ambition levels within the framework of Shared Socioeconomic Pathways. In the sector of crop N input, the scenarios set up different timelines for OECD/non-OECD countries with high/medium or low N use to reach the national-level Nitrogen Use Efficiency (NUE) targets. They include two low-ambition scenarios (Business-as-usual and Low N regulation, INMS1-2), one moderate ambition scenario (INMS3), and four high-ambition scenarios (High N regulation, Best-case, Best-case Plus, and Bioenergy, which are INMS 4-7). Filename: N2OEm_INMS%num%_%year%_%value%.tif INMS%num% refers to scenarios from INMS1 to INMS7 %year% refers annual estimates from 2010-2050 %value%, including median or SD, stands annual for median estimates from 37 simulations using climate data from 37 GCMs under each scenario, and their standard deviation. 

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4. Management alternatives for climate‐smart agriculture at two long‐term agricultural research sites in the United States: A model ensemble case study

   https://doi.org/10.1002/agj2.70146  

   Maas, Ellen_D_v L; Sihi, Debjani (September 2025, Agronomy Journal)

   Abstract Greenhouse gas (GHG) emissions reduction efforts are underway to mitigate climate change worldwide. Climate‐smart agriculture (CSA) practices have been shown to both increase soil organic carbon (SOC) inputs and reduce net greenhouse gas emissions (GHGnet). We evaluated the GHGnet of several management practices with three biogeochemical models (APSIM, Daycent, and RothC) at two sites with contrasting soils, climates, and cropping systems. Additionally, two future climate scenarios (baseline and high‐emissions) provided alternative outcomes of SOC, N₂O, and CH₄by 2050. In Michigan, most biochar and residue retention with no‐till treatments increased SOC stocks; leguminous cover crops, no‐till, and reducing fertilizer input lowered N₂O emissions. The lowest biochar treatment lowered GHGnet in the baseline climate scenario, but all other management treatments increased GHGnet under both baseline and high emissions, and all management scenarios increased a mean of 8.0 Mg CO₂‐equivalent GHG (CO₂e) ha⁻¹from baseline to high emissions. Conversely, in Texas, most treatments increased SOC, and N₂O was relatively constant. Every no‐till treatment reversed GHGnet in both the baseline and high‐emissions climate scenarios but all management scenarios increased a mean of 0.6 Mg CO₂e ha⁻¹under high emissions. At both sites under high‐emissions climate change, cover crops and no‐till resulted in the lowest GHGnet overall. Overall, the study showed that no‐till, especially with residue retention, and cover crops are important CSA practices to lower the GHGnet of agriculture, but there remains much room to find even more effective solutions to adapt to climate change. 

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5. Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

   https://doi.org/10.1111/gcb.17109  

   You, Yongfa; Tian, Hanqin; Pan, Shufen; Shi, Hao; Lu, Chaoqun; Batchelor, William D; Cheng, Bo; Hui, Dafeng; Kicklighter, David; Liang, Xin‐Zhong; et al (January 2024, Global Change Biology)

   Abstract Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO₂) in soil organic carbon (SOC) and emitting non‐CO₂greenhouse gases (GHGs) such as nitrous oxide (N₂O) and methane (CH₄). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC‐sequestered CO₂and non‐CO₂GHG emissions) and the underlying controls. Herein, we used a model‐data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960–2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N₂O and CH₄emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered Tg CO₂‐C year⁻¹in SOC (at a depth of 3.5 m) during 1960–2018 and emitted Tg N₂O‐N year⁻¹and Tg CH₄‐C year⁻¹, respectively. Based on the GWP100 metric (global warming potential on a 100‐year time horizon), the estimated national net GHG emission rate from agricultural soils was Tg CO₂‐eq year⁻¹, with the largest contribution from N₂O emissions. The sequestered SOC offset ~28% of the climate‐warming effects resulting from non‐CO₂GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960–2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO₂levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N₂O emissions represents the biggest opportunity for achieving net‐zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC‐sequestered CO₂and non‐CO₂GHG emissions for developing effective agricultural climate change mitigation measures. 

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