Fertiliser nitrogen use in Australia has increased from 35 Gg N in 1961 to 972 Gg N in 2002, and most of the nitrogen is used for growing cereals. However, the nitrogen is not used efficiently, and wheat plants, for example, assimilated only 41% of the nitrogen applied. This review confirms that the efficiency of fertiliser nitrogen can be improved through management practices which increase the crop’s ability to compete with loss processes. However, the results of the review suggest that management practices alone will not prevent all losses (e.g. by denitrification), and it may be necessary to use enhanced efficiency fertilisers, such as controlled release products, and urease and nitrification inhibitors, to obtain a marked improvement in efficiency. Some of these products (e.g. nitrification inhibitors) when used in Australian agriculture have increased yield or reduced nitrogen loss in irrigated wheat, maize and cotton, and flooded rice, but most of the information concerning the use of enhanced efficiency fertilisers to reduce nitrogen loss to the environment has come from other countries. The potential role of enhanced efficiency fertilisers to increase yield in the various agricultural industries and prevent contamination of the environment in Australia is discussed.
[1] Soil denitrification fluxes and nitrous oxide (N 2 O) emissions from the soil surface simulated by a Water and Nitrogen Management Model (WNMM), with three different gas modules, are compared to measurement data sets from two irrigated wheat-maize systems at two locations in the North China Plain (NCP) (2 years of measurement at the Luancheng site and 1 year of measurement at the Fengqiu site). The three gas modules are the WNMM gas module, the DAYCENT gas module, and the DNDC gas module. The term gas module used in this paper refers to the model component which simulates N 2 O emission from the processes of soil nitrification and denitrification. Soil water, temperature, organic matter decomposition, other nitrogen (N) transformations, such as mineralization and immobilization, and crop growth are simulated by the WNMM platform. For the 2-year data set from Luancheng, the three gas modules generate similar soil mineral N dynamics in the 0-20 cm topsoil. The daily time step, simply structured WNMM gas module consistently performs the best among the three gas modules for predicting soil denitrification fluxes (R 2 = 0.28, n = 39, p = 0.0006) and N 2 O emissions (R 2 = 0.45, n = 36, p < 0.0001). Up to 73, 43, and 22% of total N 2 O emissions are nitrification-induced as simulated by the DNDC, DAYCENT, and WNMM gas modules respectively, in this well-drained loam soil during the 2-year simulation. When applied to the 1-year data set at the Fengqiu site, the WNMM gas module consistently performs better in estimating N 2 O emissions (R 2 = 0.54, n = 35, p < 0.0001) compared to the other two modules. Simulations using the DNDC and DAYCENT gas modules explain over 40% of the temporal variation of N 2 O emission from the soil. Further testing on different soils and different agroecosystems is needed to confirm the superior performance of the WNMM gas module observed in this simulation study.
Feedlot production of beef cattle results in concentrated sources of gas emissions to the atmosphere. Reported here are the preliminary results of a micrometeorological study using open-path concentration measurements to determine whole-of-feedlot emissions of methane (CH4) and ammonia (NH3). Tunable near-infrared diode lasers were used to measure line-averaged (150–400 m) open-path concentrations of CH4 and NH3. A backward Lagrangian stochastic model of atmospheric dispersion and the software package WindTrax were used to estimate greenhouse gas fluxes from the measured concentrations. We studied typical Australian beef feedlots in the north (Queensland) and south (Victoria) of the continent. The data from a campaign during summer show a range of CH4 emissions from 146 g/animal.day in Victoria to 166 g/animal.day in Queensland and NH3 emissions from 125 g/animal.day in Victoria to 253 g/animal.day Queensland.
Understanding spatial variability of emissions of nitrous oxide (N 2 O) is essential to understanding of N 2 O emissions from soils to the atmosphere and in the design of statistically valid measurement programs to determine plot, farm and regional emission rates. Two afternoon, 'snap-shot' experiments were conducted; one in the summer and one in the autumn of 2004, to examine the statistics and soil variables affecting the spatial variability of N 2 O emissions at paddock scale. Small, static chambers (mini-chambers) were placed at 100 locations over an 8,100 m 2 area of irrigated dairy pasture in northern Victoria, Australia. Chamber headspace was sampled for N 2 O and soil samples taken below each mini-chamber were analysed for soil nitrate (NO 3 -), ammonium (NH 4 + ) and other chemical and physical properties known to affect N 2 O emissions. The experiments took place immediately after the sequence of grazing, urea application and irrigation. Nitrous oxide emissions and soil variables were analysed using classical statistics to investigate the effect of soil variables on N 2 O emissions. Geostatistics were used to investigate spatial patterns of N 2 O emissions and soil variables over the measurement area. Nitrous oxide emissions were extremely variable; 45-765 ng N 2 O-N m −2 s −1 and 20-953 ng N 2 O-N m −2 s −1 for the two experiments with corresponding averages of 165 and 138 ng N 2 O-N m −2 s −1 . Nitrous oxide emissions showed spatial dependence up to 73 and 51 m for the two experiments. Nitrous oxide emissions showed significant correlation with soil nutrients in decreasing order of NO 3 -, NH 4 + and available-P concentrations. There was no significant correlation of N 2 O emissions with measured soil physical properties.
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