Human activities emit nitrogen oxides (NOx ≡ NO + NO2; with source emissions approximated as nitric oxide (NO)), potent air pollutants and short-lived climate forcers, through direct and indirect pathways. Unlike direct releases, however, indirect NOx emissions remain poorly understood and inadequately quantified. Here, by synthesizing available observations across global terrestrial ecosystems, we show that soil moisture and pH strongly affect the ratio of annual background NO to nitrous oxide (N2O) emissions ( R NO / N 2 O ), with a critical threshold at 46% water-filled soil pore space. Combining soil moisture-stratified R NO / N 2 O modeled by machine learning with known indirect N2O emission factors, global indirect NOx emission factors ( EF 4 N O x ) are derived, yielding an aggregated median of 1.59% (95% confidence interval (CI): 0.45%-2.41%) and significantly higher (p < 0.01) disaggregated values of 1.77% (95% CI: 1.49%-2.61%) for wet climates ( EF 4 , WC N O x ) than those of 0.89% (95% CI: 0.45%-1.28%) for dry climates ( EF 4 , DC N O x ). We further estimate that the global indirect NOx emissions resulting from atmospheric deposition of nitrogen released by all anthropogenic sources amounted to approximately 886 (95% CI: 314-1639) Gg N year-1 (1 Gg = 109 g) in 2015, with fertilization, animal husbandry, and other human activities contributing about 25%, 26%, and 49%, respectively. Crucially, without soil moisture stratification, the global indirect NOx emissions would be underestimated by approximately 16% (p < 0.001), while the associated uncertainty would be about 1.5 times as large. Our novel R NO / N 2 O -based framework provides a robust approach for quantifying indirect NOx emissions in regional, national and global inventories, thereby supporting targeted strategies to mitigate air pollution and climate change.

Increased nitrogen (N) availability resulting from N addition may modify N turnover and nitrous oxide (N2O ) emissions in regions experiencing freeze-thaw cycles, where relatively high N2O emissions from soils are frequently reported during freeze-thaw periods. However, the response of soil N2O emissions during freeze-thaw periods to N addition remains unclear. In this study, we compiled 675 paired observational cases from 36 peer-reviewed articles to perform a meta-analysis assessing the effects of N addition on N2O emissions during freeze-thaw periods and to identify the associated key factors. Our results indicated that N additions increased the available soil N pool, thereby enhancing N2O emissions ( (ln R ')over bar was 0.795 with a range of 0.7-0.89 at a 95% confidence interval) primarily associated with denitrification processes during freeze-thaw periods. N additions during the previous fall had the most significant impact on increasing N2O emissions during the subsequent freeze-thaw periods. The application of manure and NO3- fertilizer has been shown to significantly enhance N2O emissions compared to other fertilizer types. The rate of N addition directly contributed positively to N2O emissions during freeze-thaw periods. Altitude was identified as the primary factor influencing N2O emissions in response to N addition. Along the altitudinal gradient, the increase in N2O emissions resulting from N addition was more pronounced at lower altitudes (<3000 m) compared to middle and high altitudes (>3000 m). Our meta-analysis elucidates the stimulatory effects of N addition on N2O emissions during freeze-thaw periods, identifying denitrification and soil N availability as primary drivers. Crucially, our findings indicate that projected increases in anthropogenic N inputs, when coupled with the climate-induced intensification of freeze-thaw cycles and snow cover reductions, could substantially amplify non-growing season N2O pulses. This synergistic interaction constitutes a critical, yet potentially underestimated, positive feedback mechanism in global N2O budgets and climate projections.

The current inventory framework of the Intergovernmental Panel on Climate Change (IPCC) relies on a single generalized default direct emission factor (EF), which inadequately captures the substantial heterogeneity in nitric oxide (NO) emissions from managed soils and may therefore lead to systematic biases in nitrogen oxides (NOx) inventories across vegetation types and environmental conditions. To address this limitation, and given that soil-emitted NOx is predominantly released as NO, we synthesized global field observations of direct EFs for NO to develop an updated methodological framework for Tier 1- and Tier 2-based inventories of national and global direct NOx emissions from managed soils. For Tier 1, our synthesis yielded 0.49% (95% confidence interval: 0.41%–0.58%), 1.66% (1.17%–2.15%), 0.10% (0.05%–0.17%), and 0.11% (0.06%–0.18%) as aggregated EFs for managed soils (I) growing upland vegetation types other than tea plantations (EF1,O(NOx)), (II) utilized for tea plantations (EF1,Tea(NOx)), (III) cultivated with flooded rice (EF1,FR(NOx)), and (IV) receiving urine and dung deposition by grazing animals (EF3(NOx)), respectively. Significant differences in direct EFs were observed among major cropping systems, with the highest, intermediate and lowest values occurring in types II, I and III, respectively (p = 0.001). For type I, soil organic carbon (SOC) content was identified as the most robust factor regulating direct EFs of NO (p = 0.001). Accordingly, for one Tier 2 option, this type was further disaggregated into two SOC-based subcategories, with direct EFs of 0.31% (0.25%–0.37%) for SOC ≤1% (EF1,O,SOC≤1%(NOx)), and 0.62% (0.49%–0.75%) for SOC >1% (EF1,O,SOC>1%(NOx)). These newly developed direct EFs would enable more accurate inventories of NOx emissions from managed soils and better support targeted mitigation strategies.

Within the methodology framework of the Intergovernmental Panel on Climate Change on national emission inventories, process-oriented modelling is referred to as Tier 3 approach. This framework covers the climatically/environmentally important nitrogen (N) gases, including ammonia (NH3), nitrogen oxides (NOx) and nitrous oxide (N2O), from managed soils. Dynamical inventories of these gases with fine resolutions are urgently needed to well elucidate the responses of coupled air pollution and climate change to human activities, e.g., heavy use of N fertilizers. Here we report a case study dynamically and synchronically inventorying the national direct emissions of NH3, NOx and N2O from croplands of China mainland, using the CNMM-DNDC which is a high-resolution, process-oriented hydro-biogeochemical model, to meet Tier 3 needs. The model performed robustly in validation against observations at 17 field sites across diverse climatic zones, showing normalized root mean square errors of 46%, 23% and 31% and Nash-Sutcliffe Index values of 0.73, 0.97 and 0.95 for the three gases, respectively. Summing up the 3-hour and 30-second simulations, the national annual direct emissions due to application of synthetic nitrogen fertilizers in 2015 were estimated at 4.66 ± 1.49 (NH3), 0.152 ± 0.041 (NOx) and 0.188 ± 0.047 (N2O) in Tg N (1 Tg = 1012 g). Logically, the simulated NH3 emissions hot-spotted in the North China Plain and peaked in May and October while NOx and N2O emissions in subtropical provinces such as Hunan and Hubei in June and October. The background emissions from croplands were equivalent to about 4%, 19% and 25% of the national direct NH3, NOx and N2O emissions, respectively. The model simulations also resulted in aggregated annual direct emission factors at logical levels for the national widely applied synthetic N fertilizers in 2015, which were on average 15.67% for NH3, 0.56% for NOx and 0.84% for N2O. This study implicates that the applied model not only acts as a reliable and robust Tier 3 approach to generate dynamic national direct emission inventories of the three N gases with fine resolutions, but also possesses the profoundly distinguished capacity in predicting direct emission factors of the gaseous species for complex/extensive conditions where field observation is impracticable.

Short-term grazing prohibition (STGP) is a common practice to restore degraded alpine meadows. But its effects on emissions of greenhouse gas (GHG) and reactive nitrogen gases remain ambiguous, particularly regarding year-round dynamics and net climate impacts. Here, we address these knowledge gaps by investigating STGP ' s influence on methane (CH4), nitrous oxide (N2O) and nitric oxide (NO) in an alpine meadow on the Tibetan Plateau with a field trial comparing the conventionally grazed and short-term-ungrazed treatments. Using static opaque chamber methods, we year-roundly measured dynamical fluxes of these gases in the second full year of grazing prohibition. However, the net climate impact of STGP remains uncertain due to the lack of diurnal flux measurements and concurrent CO2 exchange data. The STGP practice significantly (P < 0.001) increased CH4 uptake by (4)8 % annually and by 51 % in growing season. It significantly (P < 0.001) raised N2O emissions by 124 % annually and by 191 % in non-growing season while obviously (P < 0.05) reducing NO emissions by about 63 % in growing season. Notably, the STGP-stimulated N2O emissions surged by 288 % during freeze-thaw periods (P < 0.001). In addition, STGP tended to reduce temperature sensitivity for CH4 uptakes in non-growing season and for N2O and NO emissions in growing season. Notably, the CO2-equivalent balance reveals a trade-off: while the aggregate of CH4 and N2O remained a net sink at the 20-year horizon, it shifted to a source at the 100-year horizon, with STGP increasing the net positive emission by nearly 5-fold. This suggests that the climate benefit of enhanced CH4 uptake could be offset by intensified N2O emissions over the long term. However, the net climate impact of STGP still remains uncertain due to methodological constraints, including the use of static opaque chambers (which exclude diurnal and plant-mediated fluxes) and the lack of simultaneous CO2 exchange measurements. Future studies integrating complementary methods and longer-term monitoring are needed to fully quantify STGP ' s impact on net ecosystem GHG balance.

Abstract Increased nitrogen (N) availability resulting from N addition may modify N turnover and nitrous oxide (N 2 O) emissions in regions experiencing freeze–thaw cycles, where relatively high N 2 O emissions from soils are frequently reported during freeze–thaw periods. However, the response of soil N 2 O emissions during freeze–thaw periods to N addition remains unclear. In this study, we compiled 675 paired observational cases from 36 peer-reviewed articles to perform a meta-analysis assessing the effects of N addition on N 2 O emissions during freeze–thaw periods and to identify the associated key factors. Our results indicated that N additions increased the available soil N pool, thereby enhancing N 2 O emissions ( ln R ′ ― was 0.795 with a range of 0.7–0.89 at a 95% confidence interval) primarily associated with denitrification processes during freeze–thaw periods. N additions during the previous fall had the most significant impact on increasing N 2 O emissions during the subsequent freeze–thaw periods. The application of manure and NO 3 − fertilizer has been shown to significantly enhance N 2 O emissions compared to other fertilizer types. The rate of N addition directly contributed positively to N 2 O emissions during freeze–thaw periods. Altitude was identified as the primary factor influencing N 2 O emissions in response to N addition. Along the altitudinal gradient, the increase in N 2 O emissions resulting from N addition was more pronounced at lower altitudes (<3000 m) compared to middle and high altitudes (>3000 m). Our meta-analysis elucidates the stimulatory effects of N addition on N 2 O emissions during freeze–thaw periods, identifying denitrification and soil N availability as primary drivers. Crucially, our findings indicate that projected increases in anthropogenic N inputs, when coupled with the climate-induced intensification of freeze–thaw cycles and snow cover reductions, could substantially amplify non-growing season N 2 O pulses. This synergistic interaction constitutes a critical, yet potentially underestimated, positive feedback mechanism in global N 2 O budgets and climate projections.

The Taihang Mountains, an important ecological security barrier in northern China with a fragile ecology, face dual pressures from environmental changes and rapid urbanization.However, the changes in vegetation Carbon Use Efficiency (CUE) and Water Use Efficiency (WUE) in this region and their driving factors remain unclear. This study employed trend analysis, multiple regression residual analysis, and the XGBoost-SHAP method to examine the spatiotemporal variations in CUE and WUE, as well as their responses to environmental changes and human activities. The key findings are as follows:(1) During the observation period (2002-2022), the Taihang Mountains region showed significant increasing trends in Gross Primary Productivity (GPP), Net Primary Productivity (NPP), and Evapotranspiration (ET), with respective rates of 10.98 g C m-2 yr-1, 4.84 g C m-2 yr-1, and 7.24 mm yr-1. In contrast, both CUE and WUE displayed significant decreasing trends, with decadal reduction rates of 0.09 decade-1 and 0.09 g C m-2 mm-1 decade-1, respectively. Spatially, pixel-based trend analysis revealed that the proportions of significant decline for CUE and WUE were 27.53% and 43.73%, respectively. (2) Significant differences in CUE and WUE were identified among land-use types. Forests had the lowest values (CUE: 0.51; WUE: 1.06 g C m-2 mm-1), significantly lower than those of grasslands (CUE: 0.56; WUE: 1.16 g C m-2 mm-1) and croplands (CUE: 0.57; WUE: 1.20 g C m-2 mm-1).(3) This study revealed that the drivers of CUE and WUE exhibited significant nonlinear relationships and threshold effects. Temperature, DEM, and Vapor Pressure Deficit (VPD) were key controls on CUE, while precipitation and temperature dominantly regulated WUE across ecosystems. (4) Environmental factors predominantly exerted negative influences on CUE (71.46%) and positive contributions to WUE (81.21%), whereas anthropogenic activities presented limited positive impacts on CUE (31.64%) and predominantly adverse effects on WUE (86.79%), with distinct spatial patterns in their contributions.

Based on the data of China’s agricultural greenhouse gas (GHG) emissions from previous national GHG inventories, the Food and Agriculture Organization (FAO) of the United Nations database and related literature, this paper systematically analyzes recent trends in China’s total agricultural GHG sources, sinks and emissions intensity from multiple perspectives. The results show that from 2005 to 2021, China’s annual agricultural GHG emissions increased from 859 million to 931 million tons of carbon dioxide equivalent (MtCO2e), while the net carbon sequestration in agricultural soils grew from 41 MtCO2e to 106 MtCO2e. Specifically, agricultural methane (CH4) emissions accounted for 68%–73% of the total agricultural emissions, higher than agricultural nitrous oxide (N2O) emissions. By sector, livestock production contributed 49%–54% toward total agricultural emissions, exceeding emissions of crop production. According to FAO data, the GHG emissions intensity of China’s agricultural sector is lower than that of developed countries and regions. Furthermore, this paper summarizes China’s mitigation potential in feed and livestock production, manure management, fertilizer application, irrigation and tillage practices, as well as challenges faced by China in implementing existing measures and policies for agricultural carbon mitigation and sequestration. Finally, recommendations for future policies and measures are proposed from technological, institutional, and managerial perspectives.

Alpine ecosystems on the Tibetan Plateau are characterized by different soil hydrothermal conditions and vegetation composition across the elevation gradient, and contribute differently to the net landscape methane (CH4) budget. However, the spatiotemporal variation of CH4 fluxes from alpine ecosystems remains poorly understood, underpinning the uncertainty of upscaling the regional and global CH4 budgets. Here, we investigated the spatial and temporal patterns and environmental controls of CH4 fluxes over two years across a Tibetan alpine landscape spanning different elevations (spanning 3200-3500 m above sea level) and major ecosystem types (including alpine meadow, steppe, forest and wetland). On the annual scale, all alpine upland (meadow, steppe and forest) ecosystems consistently functioned as soil CH4 sinks, ranging between 1.12 and 2.49 kg C ha(-1) yr(-1), whereas alpine wetlands emitted 17.2-34.3 kg C ha(-1) yr(-1) to the atmosphere. Non-growing season CH4 fluxes accounted for 29-46 % of the annual budgets, underscoring its significant contribution that was often neglected in previous studies. Our study also demonstrated that for individual alpine upland and wetland ecosystems, soil water content and soil temperature were the main factors regulating the seasonal patterns of CH4 fluxes. While across all alpine ecosystems, soil water content outweighed temperature as the primary control on the landscape patterns of CH4 fluxes and higher wetland CH4 emissions were associated with increased soil inorganic N availability. Despite their small area contribution to the landscape, alpine wetlands emitted disproportionate amounts of CH4, weakening the landscape CH4 sink. The resulting net landscape CH4 balance was a weak sink of 0.72 kg C ha(-1) yr(-1). Overall, the multiple parameters and insights gained from our study provide valuable information for better predicting the role of alpine ecosystem CH4 carbon-climate feedbacks in high-altitude regions.

Climate change has intensified seasonal deluges and droughts, yet their impacts on soil nitrogen losses in complex landscapes remain poorly understood, hindering efforts to achieve UNEP's goal of halving nitrogen losses. This study employed the process-oriented hydro-biogeochemical model (CNMM-DNDC), validated with multi-year observations, to investigate these effects in a subtropical catchment in the upper Yangtze River. The model demonstrated strong performance (Nash-Sutcliffe efficiencies > 0.81) for water flows and nitrogen discharges. Thirty-one scenarios were set by referring to the precipitation records in 1980-2022, categorizing them as normal and seasonal deluges and droughts. Scenario simulations revealed that autumn deluges would increase annual nitrate leaching by 121-164 %, while summer deluges or droughts would significantly alter nitrate and particulate nitrogen discharges (+51 % - +118 % or -29 % - -43 %, respectively). Annual precipitation showed strong positive linear relationships with nitrate and particulate nitrogen discharges with determination coefficients (r2) of 0.95-0.97 in the current year (p < 0.001), while gaseous nitrogen emissions negatively correlated with nitrogen discharges (r(2 )> 0.93, p < 0.001). Annual deluges substantially alter the hysteresis behaviors of nitrate and particulate nitrogen, suggesting that the transport of soil accumulated nitrate via interflow is limited under normal and annual droughts. These findings highlight CNMM-DNDC's utility in linking climate events to nitrogen losses in complex landscapes, offering critical insights for sustainable nitrogen management.

Forest-atmosphere carbon exchanges are crucial yet challenging to quantify accurately due to scaling uncertainties in site observations. Process-based models that mechanistically represent coupled carbon, nitrogen, and water cycling processes are theoretically capable of reducing uncertainties in forest carbon flux quantification, thereby improving predictions of multiple ecosystem variables relevant to achieving the United Nations Sustainable Development Goals (SDGs) by 2030. Thus, we enhanced the CNMM-DNDC model by developing a forest-specific growth module incorporating key processes (photosynthesis, allocation, respiration, mortality, litter decomposition) based on Biome-BGC formulations. Compared with the original model, evaluation against 8-year (2003-2010) eddy covariance data from three Asian forests showed significant improvements in the updated model. At daily and annual scales, normalized root mean square error decreased by 46% and 54% for gross primary productivity (GPP), and 65% and 37% for ecosystem respiration (ER), respectively, though net ecosystem carbon dioxide exchange (NEE) improvements were less pronounced due to error offsetting. Sensitivity analysis identified specific leaf area, fraction of leaf nitrogen in Rubisco and annual leaf and fine root turnover fraction as most influential eco-physiological parameters, with solar radiation, humidity and air temperature as dominant meteorological drivers. The model's ability to capture daily and inter-annual carbon flux variations demonstrates its potential for regional-to-global greenhouse gas assessments, while highlighting the need for component-specific validation to avoid error masking in net flux calculations.

Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHGfp)for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,the hydro-biogeochemical model,CNMM-DNDC,was validated with in situ observations from maize-based cultivation systems at the sites of Yongji(YJ,China),Yanting(YT,China),and Madeya(MA,Kenya),subject to temperate,subtropical,and tropical climates,respectively,and updated to enable life-cycle GHGfp estimation.The model validation provided satisfactory simulations on multiple soil variables,crop growth,and emissions of GHGs and reactive nitrogen gases.The locally conventional management practices resulted in GHGfp values of 0.35(0.09-0.53 at the 95%confidence interval),0.21(0.01-0.73),0.46(0.27-0.60),and 0.54(0.21-0.77)kg CO2e kg-1 d.m.(d.m.for dry matter in short)for maize-wheat rotation at YJ and YT,and for maize-maize and maize-Tephrosia rotations at MA,respectively.YT's smallest GHGfp was attributed to its lower off-farm GHG emissions than YJ,though the soil organic carbon(SOC)storage and maize yield were slightly lower than those of YJ.MA's highest SOC loss and low yield in shifting cultivation for maize-Tephrosia rotation contributed to its highest GHGfp.Management practices of maize cultivation at these sites could be optimized by combination of synthetic and organic fertilizer(s)while incorporating 50%-100%crop residues.Further evaluation of the updated CNMM-DNDC is needed for different crops at site and regional scales to confirm its worldwide applicability in quantifying GHGfp and optimizing management practices for achieving multiple sustainability goals.

Enhanced anthropogenic nitrogen (N) inputs to ecosystems may have substantial impacts on microbially mediated soil organic carbon (SOC) cycling. One way to link species-rich soil microbial communities with SOC cycling processes is via soil extracellular enzyme activities (EEAs). However, the effects of N addition on EEAs and the associated driving factors remain poorly understood. By conducting a meta-analysis, we find that N addition increases hydrolytic C-degrading EEAs that target simple polysaccharides decomposition by 12.8%, but decreases oxidative C-degrading EEAs that degrade complex phenolic macromolecules by 11.9%. The net effect of N addition on SOC storage is determined by the shifts between these two types of C-degrading EEAs, and the impacts varied across different ecosystem types. These insights highlight the crucial but understudied roles of hydrolytic and oxidative C-degrading EEAs on SOC dynamics with ongoing enhanced anthropogenic N loading. Understanding the mechanisms behind these C-degrading EEAs could help optimize SOC sequestration and inform climate mitigation strategies across different ecosystems.

Conventional nitrogen fertilization in a maize cropping system enhances the soil’s methane (CH4) sink but exacerbates emissions of nitrous oxide (N2O) and nitric oxide (NO). This study demonstrates that conventional nitrogen application (UN) increased CH4 uptake by 154%, while elevating N2O and NO emissions by 190% and 301%, respectively, compared to zero nitrogen plots (N0). Fertilization fundamentally reconfigured the regulatory mechanisms governing gas fluxes: under UN, fluxes were controlled by a complex interplay of nitrogen substrates, carbon availability, moisture, and temperature, whereas under N0, CH4 uptake exhibited significantly enhanced temperature sensitivity (with Q10 increasing from 1.06 to 7.54) and nitrogen oxide emissions became more dependent on native ammonium and extractable organic carbon. Crucially, nitrogen withdrawal reduced soil ammonium by 37.1% without altering non-nitrogen soil properties, including temperature, moisture, and labile carbon pools. Collectively, these findings are consistent with the concept of nitrogen saturation under conventional fertilization rates. Optimizing these rates presents a significant opportunity to mitigate greenhouse gas emissions and air pollution while improving nitrogen use efficiency, thereby aligning agricultural production with climate goals and public health objectives without destabilizing short-term soil function.

To explore the response of soil greenhouse gas emissions(GHGs) from tropical forest to landuse change in Yunnan, Southwest China, we have conducted a series of studies based on the GHGs monitoring platform established since 2003 in tropical rainforest (TRF) and rubber plantation(RP). The research results indicate that 1) TRF transplanted to RP did not change the annual soil CO2 emissions (TRF, 359 ±91 and RP 352 ±41 mg CO2 m-2 h -1) but decreased soil CH4 uptake significantly (TRF, -0.11 ± -0.18 mg CH4 m -2 h -1; RP, -0.020 ± -0.087 mg CH4 m-2 h-1). (2) The most important influence on soil CO2 and CH4 emissions in the RP was the leaf area index and soil water content, respectively, whereas the soil water content, soil temperature, and dead fine roots were the most important factors in the TRF. Variations in the soil CO2 and CH4 caused by landuse transition were individually explained by soil temperature and fine root growth and decomposition, respectively. (3) The N2O emissions from the fertilized and unfertilized plots in RP were 4.0 and 2.5 kg N ha−1 yr−1, respectively; Annual N2O emissions from the control and no litter input treatments were 0.48 and 0.32 kg N2O–N ha-1 year in TRF, respectively.(4) When entire land area in Xishuangbanna is considered, N2O emissions from fertilized rubber plantations offset 17.1% of the tropical rainforest’s carbon sink. The results show that if tropical rainforests are converted to fertilized rubber plantations, regional N2O emissions may enhance local climate warming. (5) And further, land use change alter the structure and sources of soil organic matter, which in turn feedback to the microbial processes involved in soil greenhouse gas production and alter the mechanisms of soil greenhouse gas emissions.(6) The 15N isotope tracing experiment used isotope tracing technology to distinguish the microbial process of N2O production in tropical rainforest soil, proving that the microbial process of N2O production in tropical rainforest soil during the dry season is a nitrification process; In the future, we will use 13C,14C and 15N isotope and qPCR to study the microbiological mechanisms of land use change on soil greenhouse gas production in the context of climate change, providing scientific basis for quantifying the underground processes of soil greenhouse gas production; Provide mechanism support for accurately estimating soil greenhouse gas emissions to achieve the dual carbon goals in the context of climate change.

Widespread degradation of grasslands due to human activities and climate change provides favorable habitats for subterranean rodents, whose subsequent bioturbation such as burrowing and mound building further exacerbates the ongoing degradation, thereby directly and indirectly altering biogeochemical C and N cycles. However, it remains unclear how rodent-induced degradation of grasslands affects soil CH4, N2O and NO fluxes. Here we report two-year field measurements of these trace-gas fluxes and associated environmental controls from different degradation treatments (unaffected or moderately affected meadow, heavily affected meadow with very severe signs of degradation) across three alpine meadow sites at different elevations on the Tibetan Plateau. Our results show that seasonal patterns of these gas fluxes were driven by the variations in soil temperature, moisture and C or N availability, and that non-growing season fluxes contributed 29 %-39 %, 29 %-93 % and 16 %-61 % to the annual CH4, N2O and NO budgets, respectively. Over the multiple site-years, annual CH4 uptake ranged from 1.14-1.49 kg C ha-1 yr-1 for the healthy meadows to 1.42-2.85 kg C ha-1 yr-1 for the degraded meadows, indicating significant increases in CH4 uptake following grassland degradation by rodents. However, the climate benefits of increased CH4 uptake were overshadowed by a significant stimulation of annual N2O emissions following the degradation, resulting in the net non-CO2 greenhouse gas (GHG) fluxes of 48.1-364 kg CO2-eq ha-1 yr-1. Also, grassland degradation by rodents significantly increased annual NO emissions to 0.35-1.19 kg N ha-1 yr-1. Based on estimates of rodent-induced degradation across the Tibetan alpine grasslands, we estimated that degradation increased soil non-CO2 GHG emissions by 2012 Gg CO2-eq yr-1 and stimulated NO losses by 9.54 Gg N yr-1. Our results highlight the important contribution of rodent-induced grassland degradation to regional or global climate change, and point to the urgent need for policy development for the sustainable use of grasslands.

Straw return to agricultural soils is considered as a key strategy to improve soil organic C (SOC) sequestration and crop production. However, changes in SOC can affect soil N-turnover and associated N2O and NO fluxes, as soil biogeochemical C- and N-cycles are strongly coupled. Understanding how and to what extent N-trace gas emissions per unit crop yield respond to changes in SOC following straw return, is critical for balancing food security and climate change mitigation. Here we report on an experiment in a Chinese wheat-maize system designed to understand the effects of long-term (2005–2020) different straw management options (straw return, burning or removal) on SOC stocks and yields, completed by N2O and NO flux measurements over the period 2016–2020. Our results showed that the increase in SOC stocks following straw return tended to level off over time, indicating that SOC saturation is reached after 12–13 years under straw return. Soil N-trace gas emissions showed high inter- and intra-annual variability, which were largely driven by changes in rainfall, soil hydrothermal conditions or soil C- and N-availability. Compared to straw burning or removal, long-term straw return increased annual N2O emissions by 9 %-49 %, to 2.72–2.98 kg N ha−1 yr−1, while NO emissions were decreased by 12 %-28 %, to 0.83–0.90 kg N ha−1 yr−1. The annual N2O emissions roughly offset the total C sink (SOC sequestration and CH4 uptake) by 40 %-46 %, but will override the climate benefits of total C sink as the SOC pool becomes saturated. However, because yields were higher in straw return treatments, yield-scaled annual N2O emissions remained unchanged. Our unique dataset allows for the first time a better understanding of the dynamics between SOC sequestration, yields and N-trace gas emissions, with results calling for action to address the risk of increasing N2O emissions following long-term SOC increases induced by straw return.

The Pan-Eurasian Experiment Modelling Platform (PEEX-MP) is one of the key blocks of the PEEX Research Programme. The PEEX MP has more than 30 models and is directed towards seamless environmental prediction. The main focus area is the Arctic-boreal regions and China. The models used in PEEX-MP cover several main components of the Earth's system, such as the atmosphere, hydrosphere, pedosphere and biosphere, and resolve the physical-chemical-biological processes at different spatial and temporal scales and resolutions. This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system, online integrated, forward/inverse, and socioeconomical modelling, and other approaches with a particular focus on applications in the PEEX geographical domain. The employed high-performance computing facilities, capabilities, and PEEX dataflow for modelling results are described. Several virtual research platforms (PEEX-View, Virtual Research Environment, Web-based Atlas) for handling PEEX modelling and observational results are introduced. The overall approach allows us to understand better physical-chemical-biological processes, Earth's system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks, impact, consequences, etc. for population, environment and climate in the PEEX domain. This work was also one of the last projects of Prof. Sergej Zilitinkevich, who passed away on 15 February 2021. Since the finalization took time, the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

Nitric oxide (NO), as a short-lived climate forcer, has direct and indirect detrimental impacts on environmental quality and human health. The amount of nitrogen (N) fertilizer application to agricultural soils is considered a robust predictor of total NO emissions, but the estimates of cropland NO emissions have large uncertainties due to the widely used constant emission factors (EF) as e.g., default values recommended by Intergovernmental Panel on Climate Change (IPCC) methodologies. By compiling 223 field experiments with at least three N-input levels across various croplands, we performed a meta-analysis to determine how soil NO emissions respond to N inputs. Our results showed for the first time that the mean change in EF per unit of additional N input (∆EF) across all available data was significantly higher as compared to zero, indicating that the NO response to N additions increased significantly faster than the assumed linear. On average, upland grain crops showed significantly higher ∆EF than that of horticultural crops or lowland rice. A higher ∆EF was also appeared in sites with mean annual precipitation < 600 mm, mean annual temperature ≥ 15 °C, soil organic carbon ≥ 14 g C kg− 1 or total N ≥ 1.4 g N kg− 1, and where synthetic N fertilizers were usually applied. By assuming various N application rates, the IPCC default (0.7

The reliable observation and accurate estimates of land–atmosphere water vapor (H2O) flux is essential for ecosystem management and the development of Earth system models. Currently, the most direct measurement method for H2O flux is eddy covariance (EC), which depends on the development of fast-response H2O sensors. In this study, we presented a cost-efficient open-path H2O analyzer (model: HT1800) based on the tunable diode laser absorption spectroscopy (TDLAS) technique, and investigated its applicability for measuring atmospheric turbulent flux of H2O using the EC method. We prepared two HT1800 analyzers with lasers that operate at wavelengths of 1392 nm and 1877 nm, respectively. The field performance of the two analyzers was evaluated through inter-comparative experiments with LI-7500RS and IRGASON, two of the most commonly used H2O analyzers in the EC community. Water vapor densities measured by the three types of analyzers had high overall agreement with the reference sensor; however, they all experienced drift. The mean density drifts of HT1800, LI-7500 and IRGASON were 3.7–5.2%, 4.0% and 3.8%, respectively. Even so, the half-hourly H2O fluxes measured by HT1800 were highly consistent with those by LI-7500RS and IRGASON (with a difference of less than 2%), suggesting that HT1800 can obtain H2O fluxes with high confidence. The HT1800 was also proved to be suitable for EC application in terms of data availability, flux detection limit and response to the high-frequency turbulent variation. Furthermore, we investigated how the spectroscopic effect influences the measurements of H2O density and flux. Despite the fact that the 1392 nm laser was much more susceptible to the spectroscopic effect, the fluxes after correcting for this bias showed excellent agreement with the IRGASON fluxes. Considering the cost advantage in laser and photodetector, the HT1800 analyzer using a 1392 nm infrared laser is a promising and economical solution for EC measurement studies of water vapor.