Differential immediate and long-term effects of nitrogen input on denitrification N₂O/(N₂O +N₂) ratio along a 0–5.2 m soil profile

High nitrogen (N) input to soil can cause higher nitrous oxide (N2O) emissions, that is, a higher N2O/(N2O+N2) ratio, through an inhibition of N2O reductase activity and/or a decrease in soil pH. We assumed that there were two mechanisms for the effects of N input on N2O emissions, immediate and long-term effect. The immediate effect (field applied fertilizer N) can be eliminated by decreasing the N input, but not the long-term effect (soil accumulated N caused by long–term fertilization). Therefore, it is important to separate these effects to mitigate N2O emissions. To this end, soil samples along a 0–5.2 m profile were collected from a long-term N fertilization experiment field with two N application rates, that is, 600 kg N ha-1 year-1 (N600) and no fertilizer N input (N0). External N addition was conducted for each subsample in the laboratory incubation study to produce two additional treatments, which were denoted as N600+N and N0+N treatments. The results showed that the combined immediate and long-term effects led to an increase in the N2O/(N2O+N2) ratio by 6.8%. Approximately 32.6% and 67.4% of increase could be explained by the immediate and long-term effects of N input, respectively. Meanwhile, the long-term effects were significantly positively correlated to soil organic carbon (SOC). These results indicate that excessive N fertilizer input to the soil can lead to increased N2O emissions if the soil has a high SOC content. The long-term effect of N input on the N2O/(N2O+N2) ratio should be considered when predicting soil N2O emissions under global environmental change scenarios. </p

Significance of inhibitor volume in on-farm mitigation of nitrous oxide emission from dairy cattle urine patches

Technologies are being developed for the targeted mitigation of nitrogen (N) losses from livestock urine patches using urease and nitrification inhibitors (UIs and Nls). In our earlier study, we identified a major limitation for inhibitor efficiency, specifically, the application of a 40 mL volume of inhibitor solution to a 2L of urine patch (i.e., 1:50, based on New Zealand recommended dicyandiamide [DCD] application rate of 10 kg DCD dissolved in 800 L water ha-1).This ongoing research evaluates the effect of inhibitor treatments by varying the inhibitor: urine volume ratio from 1:50 to 1:10 (200 mL of inhibitor to the 2L of urine patch) on nitrous oxide (N2O) mitigation of five nitrification inhibitors: DCD, 3,4-dimethylpyrazole phosphate (DMPP), 2-chloro-6-(trichloromethyl) pyridine (nitrapyrin), and two confidential compounds (named A and C, provided by AgResearch). These inhibitors were applied 24 hours after creating 2L simulated urine patches (within 0.5 m2 chambers) in two dairy-grazed pasture soils with contrasting drainage (poorly vs well drained). Results showed that the N2O emissions reduction efficiency from urine patches was the highest (35.8%–46.7%) with DCD followed by inhibitor C (26.9%–27.9%). The reductions in emission from the other inhibitors were not significant (11.0%–23.0% with DMPP and nitrapyrin, respectively; and 1.5%–15.6% with inhibitor A). In this study, diluting the inhibitor solutions resulted in retention of only 3% to 18% of the NIs by the pasture canopy compared with up to 59% (with 1:50) in our previous study. This dilution increases the amount of inhibitor reaching the soil, offering a potential option for effectively reducing N2O emissions from cattle urine patches. However, dilution may result in concentrations below threshold levels of DMPP, nitrapyrin and inhibitor A, compromising their effectiveness. These results warrant further research to optimise inhibitor application rate and volume and measure inhibitor residues for developing best practice for targeted application of inhibitors to urine patches while addressing unintended food and human health risks.</div

Spatio-temporal variation of net anthropogenic nitrogen inputs (NANI) from 1991 to 2019 and its impacts analysis from parameters in Northwest China

At present, excessive nutrient inputs caused by human activities have resulted in environmental problems such as agricultural non-point source pollution and water eutrophication. The Net Anthropogenic Nitrogen Inputs (NANI) model can be used to estimate the nitrogen (N) inputs to a region that are related to human activities. To explore the net nitrogen input of human activities in the main grain-producing areas of Northwestern China, the county-level statistical data for the Ningxia province and NANI model parameters were collected, the spatio-temporal distribution characteristics of NANI were analyzed and the uncertainty and sensitivity of the parameters for each component of NANI were quantitatively studied. The results showed that: (1) The average value of NANI in Ningxia from 1991 to 2019 was 7752 kg N km-2 yr-1. Over the study period, the inputs first showed an overall increase, followed by a decrease, and then tended to stabilize. Fertilizer N application was the main contributing factor, accounting for 55.6%. The high value of NANI in Ningxia was mainly concentrated in the Yellow River Diversion Irrigation Area. (2) The 95% confidence interval of NANI obtained by the Monte Carlo approach was compared with the results from common parameters in existing literature. The simulation results varied from -6.4% to 27.4% under the influence of the changing parameters. Net food and animal feed imports were the most uncertain input components affected by parameters, the variation range was -20.7%-77%. (3) The parameters of inputs that accounted for higher proportions of the NANI were more sensitive than the inputs with lower contributions. The sensitivity indexes of the parameters contained in the fertilizer N applications were higher than those of net food and animal feed imports and agricultural N-fixation. This study quantified the uncertainty and sensitivity of parameters in the process of NANI simulation and provides a reference for global peers in the application and selection of parameters to obtain more accurate simulation results. </p