regression model;
geographical information system (GIS);
nitrogen;
soil moisture;
temperature;
D O I:
10.1016/S1352-2310(01)00441-1
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
A spatial inventory of N2O emissions from agricultural and non-agricultural soils in Great Britain was prepared using a simple regression model within a GIS framework. The regression model was based on published N2O data from soils of temperate climates. It describes emissions as a function of N input (N), water filled pore space (WFPS), soil temperature (T-s) and land use (A): In (N2O)(kgNha(-1) y(-1)) = -2.7 + 0.60ln N (kgN ha(-1) y(-1)) + 0.61ln WFPS (%)+ 0.035 T-s (degreesC) - 0.99A. The regression model predicted the highest fluxes of 6- 21 kg N ha(-1) y(-1) from grazed grasslands. On tilled land, predicted N2O emissions did not exceed 6kg N ha(-1) y(-1), while fluxes below 0.1 kg N ha(-1) y(-1) were estimated for semi-natural land. N2O emissions from soils in spring and summer were a factor of 2-3 higher than in the remaining part of the year. Total N2O emissions for Great Britain were estimated at 127 kt N2O-N y(-1). Distribution maps of annual and seasonal N2O emissions outlined the areas with the largest fluxes as those of intensive livestock farming in wet western regions of Britain. The annual emissions predicted by this study were much higher for agricultural soils than those suggested by the IPCC emission factor of 1.25% (0.25-2.25%) of N input, which range between 3 and 9 kg N ha(-1) y(-1) for grasslands and 2 and 3 kg N ha(-1) y(-1) for tillage crops and predict a total emission from agricultural sources of 56 kt N2O-N y(-1). Main uncertainty of the linear regression model is caused by scaling from published short-term N2O emission data to annual averages. (C) 2002 Elsevier Science Ltd. All rights reserved.