Global soil nitrous oxide emissions since the preindustrial era estimated by an ensemble of terrestrial biosphere models: Magnitude, attribution, and uncertainty

Abstract

Our understanding and quantification of global soil nitrous oxide (N2O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO2 concentration, on global soil N2O emissions for the period 1861–2016 using a standard simulation protocol with seven process‐based terrestrial biosphere models. Results suggest global soil N2O emissions have increased from 6.3 ± 1.1 Tg N2O‐N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N2O‐N/year in the recent decade (2007–2016). Cropland soil emissions increased from 0.3 Tg N2O‐N/year to 3.3 Tg N2O‐N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N2O emissions since the 1970s. However, US cropland N2O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N2O emissions appear to have decreased by 14%. Soil N2O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N2O‐N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO2 concentration reduced soil N2O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N2O emissions, this study recommends several critical strategies for improving the process‐based simulations.

Weakened growth of cropland‐N2O emissions in China associated with nationwide policy interventions

“…China is a large country with contrasting crop production systems, climate, and soil types, where the patterns of N 2 O emissions are poorly understood compared to some developed countries (Yue et al, ; Zhou et al, ; Zou, Lu, & Huang, ). In the last decade, process‐based models (e.g., DNDC, DAYCENT, DLEM), used to produce Tier 3 IPCC estimates, simulated global and regional cropland‐N 2 O emissions using subnational N inputs from China (Li et al, ; Tian et al, ; Yue et al, ). These models are arguably more realistic than the Tier 1 approach because they account for climatic and soil variabilities.…”

“…These models are arguably more realistic than the Tier 1 approach because they account for climatic and soil variabilities. Although multimodel ensemble may reduce some errors across individual models through a broader integration of model processes (Tian et al, ), these individual models have rarely been validated by observations across contrasting environmental and management‐related conditions (Ehrhardt et al, ), leading to large uncertainties not only in estimating emission trends, but also in identifying underlying drivers.…”

“…agricultural management, agricultural soils, emission inventory, flux upscaling, land surface model, nitrous oxide, policy analysis, temporal trend used to produce Tier 3 IPCC estimates, simulated global and regional cropland-N 2 O emissions using subnational N inputs from China (Li et al, 2001;Tian et al, 2019;Yue et al, 2019). These models are arguably more realistic than the Tier 1 approach because they account for climatic and soil variabilities.…”

Global Nitrous Oxide Emissions From Pasturelands and Rangelands: Magnitude, Spatiotemporal Patterns, and Attribution

“…Quantifying these uncertainties is complex due to the variety of N forms and microbial processes that need to be considered (Butterbach‐Bahl et al, ; Davidson, ). In addition, climate, soil conditions, vegetation type, and soil management practices (fertilization and manure application) can modify N 2 O fluxes due to complex interactions among different environmental factors resulting in large temporal and spatial variations (Bouwman et al, ; Ehrhardt et al, ; Tian et al, ). One of the largest uncertainty sources for N 2 O fluxes comes from management practices that includes livestock excreta N deposition in pasturelands and rangelands and manure/fertilizer N application in pasturelands (Steinfeld, Gerber, et al, ; Tubiello et al, ).…”

“…and intensities (different levels of fertilizer/manure N input). In addition, as process‐based models that simulate N 2 O emissions at subdaily and daily time step are becoming increasingly available (Tian et al, ), model intercomparison of N 2 O fluxes at different experimental sites (Ehrhardt et al, ) and application of such models at regional and global scales (Tian et al, ) can help to constrain global estimates of N 2 O emissions and reduce uncertainties due to model structure and their internal variability. Both experimental studies and process‐based model intercomparison are required not only to constrain current estimates of N 2 O fluxes but also to simulate variations in future emissions in response to different climate and land use/management scenarios.…”