Model simulations of C and N dynamics, based on country-specific agricultural and environmental conditions, can provide information for compiling national greenhouse gas (GHG) inventories, as well as insights into potential mitigation options. A multi-pool dynamic model, `ECOSSE' (v5 modified), was used to simulate coupled GHGs and soil organic carbon (SOC) stock changes. It was run for an equivalent time frame of 8 years with inputs from conventionally-tilled arable land cropped with spring barley receiving N fertilizer as calcium ammonium nitrate at 135-159 kg N ha(-1) and crop residues (3 t ha-1 yr-1). The simulated daily N2O fluxes were consistent with the measured values, with R-2 of 033 (p < 0.05) and the total error and bias differences were within 95% confidence levels. The measured seasonal N2O losses were 0.39-0.60% of the N applied, with a modelled estimate of 0.23-0.41%. In contrast, the measured annual N2O loss (integrated) was 0.35% and the corresponding simulated value of 0.45% increased to 0.59% when the sum of the daily fluxes was taken into account. This indicates intermittent gas samplings may miss the peak fluxes. On an 8-year average the modelled N2O emission factor (EF) was 0.53 0.03%. The model successfully predicted the daily heterotrophic respiration (RH), with an R-2 of 0.45 (p <0.05) and the total error and bias differences were within the 95% confidence intervals. The simulated and measured total RH (3149 versus 3072 kg C ha(-1) yr(-1)) was within the cropland average values previously reported. The total measured CH4 fluxes indicated that the unfertilized treatments were a small source (-2.29 g C ha(-1) yr(-1)), whilst the fertilized treatments were a sink (+3.64). In contrast, the simulated values suggested a sink (26.61-31.37 g C ha(-1) yr(-1)), demonstrating fertilizer-induced decreases in CH4 oxidation. On average, based on the simulated SOC content a loss of 516 kg C ha(-1) yr(-1) was indicated, which is within the uncertainty range for temperate regions. Results suggest that the model is suitable for estimating the GHG balance of arable fields. However, further refinements and analyses to fully determine and narrow down the uncertainty ranges for GHG estimates are required. (C) 2013 Elsevier Ltd. All rights reserved.
