Ammonia (NH3) emissions from fertilized soils to the atmosphere and the subsequent deposition to land surface exert adverse effects on biogeochemical nitrogen (N) cycling. The region‐ and crop‐specific emission factors (EFs) of N fertilizer for NH3 are poorly developed and therefore the global estimate of soil NH3 emissions from agricultural N fertilizer application is constrained. Here we quantified the region‐ and crop‐specific NH3 EFs of N fertilizer by compiling data from 324 worldwide manipulative studies and focused to map the global soil NH3 emissions from agricultural N fertilizer application. Globally, the NH3 EFs averaged 12.56% and 14.12% for synthetic N fertilizer and manure, respectively. Regionally, south‐eastern Asia had the highest NH3 EFs of synthetic N fertilizer (19.48%) and Europe had the lowest (6%), which might have been associated with the regional discrepancy in the form and rate of N fertilizer use and management practices in agricultural production. Global agricultural NH3 emissions from the use of synthetic N fertilizer and manure in 2014 were estimated to be 12.32 and 3.79 Tg N/year, respectively. China (4.20 Tg N/year) followed by India (2.37 Tg N/year) and America (1.05 Tg N/year) together contributed to over 60% of the total global agricultural NH3 emissions from the use of synthetic N fertilizer. For crop‐specific emissions, the NH3 EFs averaged 11.13%–13.95% for the three main staple crops (i.e., maize, wheat, and rice), together accounting for 72% of synthetic N fertilizer‐induced NH3 emissions from croplands in the world and 70% in China. The region‐ and crop‐specific NH3 EFs of N fertilizer established in this study offer references to update the default EF in the IPCC Tier 1 guideline. This work also provides an insight into the spatial variation of soil‐derived NH3 emissions from the use of synthetic N fertilizer in agriculture at the global and regional scales.

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Warming can accelerate the decomposition of soil organic matter and stimulate the release of soil greenhouse gases (GHGs), but to what extent soil release of methane (CH4) and nitrous oxide (N2O) may contribute to soil C loss for driving climate change under warming remains unresolved. By synthesizing 1,845 measurements from 164 peer‐reviewed publications, we show that around 1.5°C (1.16–2.01°C) of experimental warming significantly stimulates soil respiration by 12.9%, N2O emissions by 35.2%, CH4 emissions by 23.4% from rice paddies, and by 37.5% from natural wetlands. Rising temperature increases CH4 uptake of upland soils by 13.8%. Warming‐enhanced emission of soil CH4 and N2O corresponds to an overall source strength of 1.19, 1.84, and 3.12 Pg CO2‐equivalent/year under 1°C, 1.5°C, and 2°C warming scenarios, respectively, interacting with soil C loss of 1.60 Pg CO2/year in terms of contribution to climate change. The warming‐induced rise in soil CH4 and N2O emissions (1.84 Pg CO2‐equivalent/year) could reduce mitigation potential of terrestrial net ecosystem production by 8.3% (NEP, 22.25 Pg CO2/year) under warming. Soil respiration and CH4 release are intensified following the mean warming threshold of 1.5°C scenario, as compared to soil CH4 uptake and N2O release with a reduced and less positive response, respectively. Soil C loss increases to a larger extent under soil warming than under canopy air warming. Warming‐raised emission of soil GHG increases with the intensity of temperature rise but decreases with the extension of experimental duration. This synthesis takes the lead to quantify the ecosystem C and N cycling in response to warming and advances our capacity to predict terrestrial feedback to climate change under projected warming scenarios.

SummaryA gradient descent‐based nonlinear observer for surface‐mount permanent magnet synchronous motors with remarkable stability properties was recently proposed. A key assumption for the derivation of the observer is the knowledge of the electrical parameters, which are usually uncertain. In the present paper, we propose a robust adaptive flux observer adding immersion and invariance parameter adaptation algorithms to estimate the stator resistance. Global boundedness of all signals and convergence to a residual set of the flux estimation error is guaranteed. The performance of the new adaptive observer is assessed with realistic simulations. Copyright © 2015 John Wiley & Sons, Ltd.