23 5 2 0 0 3 9 QUATERNARY SCIENCES Vol. 23, No. 5 September, 2003 3 S. Frolking B. Moore W. Salas R. Sass (, Durham, NH 03824, ;, 100081 ;, 100081 ;, 100085 ;, 100101 ;, 100029 ;, 410128 ;,Houston, Texas 77252-1892, ), 1. 33, 3, (CO 2 ) (CH 4 ) (N 2 O) - ( ) CO 2,CH 4 N 2 O, (DNDC), DNDC (C) (N),,DNDC 1990 CO 2 95 C/ CH 4 9. 2 C/ N 2 O 1. 3 N/ ( GWP), N 2 O CO 2 CH 4 1980 2000, 20,,DNDC CH 4 1980 12 2000 7, CH 4 20 CH 4 CO 2 15 % 80 %, C N 2 O, N 2 O,, DNDC : 61 E2mail :changsheng. li @unh. edu (NSF) ( EPA) (NASA) (CNSF) (CAAS) (TECO) ( EOS) CNSF - 39790100 2003-05 - 22,2003-06 - 10 3
494 2 0 0 3,,,,, (CO 2 ) (CH 4 ) (N 2 O),, ( Intergo2 vernmental Panel for Climate Change IPCC),1997 ( The Kyoto Protocol),, CO 2,CH 4, N 2 O, (C) (N) C CO 2, CH 4 N N, N,N 2 O, CO 2,CH 4 N 2 O,, [1 5 ] (DNDC) 1989,, 8, 10, 20,DNDC CO 2, CH 4 N 2 O [4,6 13 ]1) DNDC, DNDC 1 DNDC (field scale) DNDC ( ) ( ph Eh ), C,N DNDC,,, DNDC,, ( ) 1) Cai Z, Sawamoto S, Li C et al. Field validation of the DNDC model for greenhouse gas emissions in East Asian cropping systems. 2003
5 : :,, ;, ( GIS), ;,, GIS, 2 483 GIS 1990 / 610 (National Center for Atmospheric Research) ; E. A. Holland [14 ] ; ph [15 ] ;, 1990, [16 19 ] ; / [20 1984 ], 1990, ( ) GIS,DNDC 3 (library database) :, DNDC ;, DNDC, ;,, DNDC Visual C ++ DNDC DNDC, -, CO 2,CH 4 N 2 O,CO 2 CO 2, ; ;,3 DNDC, GIS ( ArcView, ArcInfo,Idrisi) 2 DNDC, (scale up), ( ) -,,, ( ),,,,, 495
496 2 0 0 3, -, CO 2 N 2 O [21,22, CH 4 ] ph CH 4, 1 DNDC CH 4 :, CH 4, DNDC, ( ) CH 4 ; ( ), CH 4 CH 4,, CH 4, CH 4 80 %,,,, DNDC, CO 2,CH 4 N 2 O 1 CH 4 Fig. 1 Sensitivity analysis for CH 4 emissions from a paddy rice field at Yiyang County, Hunan Province in China 3 1990, DNDC 2 483 1. 33 CO 2,CH 4 N 2 O
5 : 20 49, DNDC, ( CO 2,N 2 O CH 4 ) ( ), DNDC : DNDC, 0 30cm, C 2 900 8 900 1990, 270 320 C, 260 300 C 31 37 C 291 337 C, 70 82 C, 100 % 15 % ( ) C 110, ( ) CO 2 140 390 C, (DOC) 2. 9 8. 2 C 1990 CH 4 6. 4 12. 0 CH 4 C, C ( DOC CO 2 ) C CH 4 ( 80 %) C C, 1990 C 29-220 C C CO 2, - 29 220 C/, 95 C/ ( ), C C ( 1) C ( C > 2. 5 ) C, 1990 0. 3 DNDC CH 4 6. 4 12. 0 C/, 9. 2 C/, 1. 5 C, 16 % ; 0. 5 C ( 1), CH 4 65 % 1990 N 2 O 0. 6 2. 0 N, 1. 3 N (0. 374 N), N 2 O 28 % ; 0. 05 N ( ), [23 ], N 2 O CO 2,CH 4 N 2 O 3 (radiative forcing), 3, [24 (net effect) IPCC ], 100,1kg CH 4 1kg CO 2 21, 1kg N 2 O 1kg CO 2 310 (global warming potential, GWP) 3 GWP : GWP = fco 2 / 12 44 + fch 4 / 12 16 21 + fn 2 O/ 28 44 310 (1) fco 2 CO 2 (kgco 2 2C) 497
498 2 0 0 3 fch 4 CH 4 (kgch 4 2C) fn 2 O N 2 O (kgn 2 O2N) 1 DNDC 1990 3 Table 1 DNDC2modeled emissions of net CO 2, CH 4 and N 2 O from croplands of China in 1990 CO 2 / C CH 4 / C N 2 O / N / 10 6 km 2 0. 003-0. 11 0. 08-0. 01 0. 004 0. 005 0. 004 0. 001 0. 002 0. 001 0. 005-0. 11 0. 08-0. 01 0. 016 0. 017 0. 016 0. 001 0. 002 0. 001 0. 064-1. 17 3. 17 1. 00 0. 026 0. 028 0. 027 0. 010 0. 026 0. 018 0. 046-0. 44 2. 76 1. 16 0. 003 0. 003 0. 003 0. 007 0. 019 0. 013 0. 087-2. 61 30. 85 14. 12 0. 021 0. 034 0. 027 0. 025 0. 231 0. 128 0. 045-1. 07 9. 60 4. 26 0. 138 0. 180 0. 159 0. 017 0. 086 0. 052 0. 057 2. 64 21. 79 12. 21 0. 101 0. 151 0. 126 0. 044 0. 191 0. 117 0. 138 13. 22 66. 80 40. 01 0. 182 0. 268 0. 225 0. 139 0. 610 0. 374 0. 003 0. 03 0. 31 0. 17 0. 095 0. 150 0. 122 0. 002 0. 003 0. 003 0. 050-0. 28 5. 03 2. 38 0. 771 1. 211 0. 991 0. 018 0. 040 0. 029 0. 020-0. 92 0. 91-0. 01 0. 389 0. 730 0. 560 0. 016 0. 029 0. 023 0. 060-1. 11 4. 13 1. 51 0. 456 1. 129 0. 792 0. 017 0. 042 0. 029 0. 014-0. 50 1. 32 0. 41 0. 170 0. 262 0. 216 0. 011 0. 025 0. 018 0. 034-1. 59 2. 23 0. 32 0. 556 1. 092 0. 824 0. 024 0. 054 0. 039 0. 085-3. 02 6. 92 1. 95 0. 050 0. 061 0. 055 0. 020 0. 055 0. 038 0. 082-2. 51 7. 52 2. 50 0. 143 0. 340 0. 241 0. 014 0. 045 0. 029 0. 047-1. 29 2. 58 0. 64 0. 405 1. 138 0. 772 0. 018 0. 031 0. 024 0. 043-2. 76 0. 20-1. 28 0. 550 1. 144 0. 847 0. 022 0. 043 0. 032 0. 029-1. 81 1. 46-0. 18 0. 468 0. 859 0. 664 0. 023 0. 039 0. 031 0. 033-1. 91 5. 75 1. 92 0. 256 0. 667 0. 462 0. 020 0. 061 0. 040 0. 115-3. 89 11. 12 3. 62 1. 264 1. 827 1. 545 0. 057 0. 107 0. 082 0. 037-3. 09 1. 73-0. 68 0. 096 0. 197 0. 146 0. 011 0. 022 0. 016 0. 047-3. 68 3. 74 0. 03 0. 081 0. 156 0. 119 0. 015 0. 038 0. 026 0. 003-0. 91 0. 27-0. 32 0. 000 0. 000 0. 000 0. 001 0. 006 0. 004 0. 055-1. 29 5. 42 2. 06 0. 064 0. 115 0. 089 0. 007 0. 036 0. 022 0. 053-2. 50 5. 77 1. 63 0. 002 0. 002 0. 002 0. 005 0. 031 0. 018 0. 006-1. 47 0. 08-0. 69 0. 000 0. 000 0. 000 0. 001 0. 005 0. 003 0. 013-0. 57 0. 39-0. 09 0. 003 0. 002 0. 003 0. 001 0. 004 0. 003 0. 042-4. 13 14. 28 5. 08 0. 027 0. 051 0. 039 0. 005 0. 082 0. 043 0. 007-0. 17 2. 46 1. 14 0. 104 0. 204 0. 154 0. 004 0. 015 0. 010 1. 323-29. 02 218. 75 94. 85 6. 441 12. 023 9. 23 0. 556 1. 98 1. 265, 1990 GWP 344 2 102 CO 2, 1 222. 55 CO 2 3,N 2 O GWP,
5 : 50 %;CO 2, 29 %;CH 4, 21 % GWP 10 ( 2) 2000 2 1990 ( GWP) Table 2 Global warming potential ( GWP) values for the provinces in China in 1990 [25 ], GWP/ CO 2 CO 2 550 /, CH 4 12 /, 1990 CO 2 17 %, CH 4 78 % N 2 O,, N 2 O,, 4 DNDC,, ( mitigation scenario ) 20 80, 3 CO 2 CH 4 N 2 O 0. 07 1. 15 0. 61-0. 08 0. 11 0. 88 0. 44 1. 55 0. 99-0. 05 0. 26 0. 59 1. 19 25. 09 13. 17 0. 28 0. 03 0. 66 1. 89 19. 43 10. 68 0. 40 0. 00 0. 59 3. 12 226. 44 114. 78 0. 45 0. 00 0. 54 8. 38 81. 97 45. 17 0. 35 0. 06 0. 56 33. 98 177. 06 105. 50 0. 42 0. 02 0. 54 121. 33 549. 48 335. 38 0. 44 0. 01 0. 54 3. 76 6. 94 5. 32 0. 12 0. 36 0. 24 29. 54 71. 68 50. 59 0. 17 0. 31 0. 28 15. 38 38. 09 26. 71 0. 00 0. 33 0. 41 16. 99 67. 16 42. 05 0. 13 0. 30 0. 34 8. 23 24. 32 16. 27 0. 09 0. 21 0. 54 21. 25 64. 99 43. 09 0. 03 0. 30 0. 44 0. 25 53. 88 27. 06 0. 26 0. 03 0. 68 1. 46 59. 01 30. 21 0. 30 0. 13 0. 47 15. 28 56. 39 35. 86 0. 07 0. 34 0. 33 16. 10 53. 56 34. 81-0. 13 0. 38 0. 45 17. 43 48. 18 32. 78-0. 02 0. 32 0. 45 9. 82 69. 48 39. 65 0. 18 0. 18 0. 50 48. 74 144. 12 96. 43 0. 14 0. 25 0. 41-3. 55 22. 74 9. 60-0. 26 0. 24 0. 83-4. 13 36. 47 16. 14 0. 01 0. 12 0. 79-2. 82 3. 92 0. 57-2. 05 0. 00 3. 05 0. 66 40. 67 20. 64 0. 37 0. 07 0. 51-6. 60 36. 32 14. 86 0. 40 0. 00 0. 59-5. 13 2. 52-1. 33 1. 92 0. 00-0. 92-1. 53 3. 47 0. 99-0. 34 0. 04 1. 27-12. 20 93. 59 40. 70 0. 46 0. 02 0. 52 4. 32 22. 23 13. 27 0. 32 0. 18 0. 36, 343. 65 2 101. 9 1 222. 55 0. 29 3 3 3 3 3 0. 21 GWP 3 3 0. 50 499 3 3
500 2 0 0 3,,,, 90, 2000 DNDC,, 8. 6 16. 0 CH 4 / ;, 3. 5 11. 6 CH 4 /, 1980 2000,, CH 4 5 20,, CO 2,CH 4 N 2 O 20 80 :CO 2 N 2 O, CH 4,,, 20 CH 4 CH 4, CH 4 [22 ] 50 100 CH 4, CH 4 [26 10 % 20 %, CH 4 ] 20 % [27 ], CH 4 CH 4 C,,,, C [28 ], CO 2 (sequestration), DNDC, C 15 % 80 %, C ( - 95 C/ ) ( + 80 C/ ), 95 CO 2 2C 80 CO 2 2C C, (N mineralization), N 20 % [29 ] N 2 O, (, ) N 2 O, DNDC,, N 2 O 1997 IPCC [30 ] N 2 O, N 2 O (16 N/ ) (8. 5 N/ ) IPCC, N 2 O DNDC, N 2 O ( 1. 3 N/ ) (2. 1 N/ ) [23 ] DNDC :, ; ph, N, N 2 O,
5 :,, N 2 O, N,,,,, 1 Li C, Frolking S, Frolking T A. A model of nitrous oxide evolution from soil driven by rainfall events : 1. Model structure and sensitivity. Journal of Geophysical Research, 1992, 97 :9 759 9 776 2 Li C, Frolking S, Harriss R C. Modeling carbon biogeochemistry in agricultural soils. Global Biogeochemical Cycles,1994, 8 : 237 254 3 Li C. Modeling trace gas emissions from agricultural ecosystems. Nutrient Cycling in Agroecosystems, 2000, 58 :259 276 4 Zhang Y, Li C, Zhou X et al. A simulation model linking crop growth and soil biogeochemistry for sustainable agriculture. Ecological Modeling, 2002, 151 :75 108 5. DNDC.,2001,21 (2) :89 99 6 Smith P, Smith J U, Powlson D S. A comparison of the performance of nine soil organic matter models using datasets from seven long2term experiments. Geoderma, 1997, 81 :153 225 7 Li C, Frolking S, Croker GJ et al. Simulating trends in soil organic carbon in long2term experiments using the DNDC model. Geoderma, 1997, 81 :45 60 8 Plant R A J, Veldkamp E, Li C. Modeling nitrous oxide emissions from a Costa Rican banana plantation. In : Plant R A J ed. Effects of Land Use on Regional Nitrous Oxide Emissions in the Humid Tropics of Costa Rica. Veenendaal : Universal Press, 1998. 41 50 9 Frolking S, Mosier A R, Ojima D S. Comparison of N 2 O emissions from soils at three temperate agricultural sites : Simulations of year2round measurements by four models. Nutrient Cycling in Agroecosystems, 1998, 52 :77 105 10 Xu W, Hong Y, Chen X et al. Agricultural N 2 O emissions at regional scale : A case study in Guizhou, China. Science in China, 1999, 29 :5 11 Stange F, Butterbach2Bahl K, Papen H et al. A process2oriented model of N 2 O and NO emission from forest soils 2, sensitivity analysis and validation. Journal of Geophysical Research, 2000, 105(4) : 4 385 4 398 12 Smith W N, Desjardins R L, Grant B et al. Testing the DNDC model using N 2O emissions at two experimental sites in Canada. Canada Journal of Soil Science, 2002, 82 :365 374 13 Brown L, Syed B, Jarvis S C et al. Development and application of a mechanistic model to estimate emission of nitrous oxide from UK agriculture. Atmospheric Environment, 2002, 36 : 917 928 14 Holland E A, Braswell B H, Lamarque J F et al. Variations in the predicted spatial distribution of atmospheric nitrogen deposition and their impact on carbon uptake by terrestrial ecosystems. Journal of Geophysical Research, 1997, 102 :15 849 15 866 15.. :, 1986. 1 55 16 Liu J Y. Investigations and Dynamics of Chinese Environment and Natural Resources Through Remote Sensing Analysis. Beijing : Chinese Science and Technology Press, 1996. 1 353 17 Xiao X, Boles S, Frolking S et al. Landscale2scale characterization of cropland in China using vegetation and landsat TM images. International Journal of Remote Sensing, 2002, 23 :3 579 3 594 18 Xiao X, He L, Salas W et al. Quantitative relationships between field2measured leaf area index and vegetation index derived from VEGETATION images for paddy rice fields. International Journal of Remote Sensing, 2002, 23 :3 595 3 604 501
502 2 0 0 3 19 Frolking S, Qiu J, Boles S et al. Combining remote sensing and ground census data to develop new maps of the distribution of rice agriculture in China. Global Biogeochemical Cycles, 2002, 16(4) : 1 091(doi :10. 1029/ 2001GB001425, 2002) 20.. :,1984. 1 42 21 Li C, Narayanan V, Harriss R. Model estimates of nitrous oxide emissions from agricultural lands in the United States. Global Biogeochemical Cycles, 1996, 10 :297 306 22 Li C, Qiu J, Frolking S et al. Reduced methane emissions from large2scale changes in water management in China s rice paddies during 1980 2000. Geophysical Research Letters, 2002, 29 (20) : 331 334(doi :10. 1029/ 2002GL015370, 2002) 23 Li C, Zhuang Y H, Cao M Q et al. Comparing a national inventory of N 2O emissions from arable lands in China developed with a process2based agro2ecosystem model to the IPCC methodology. Nutrient Cycling in Agroecosystems, 2001, 60 :159 175 24 Ramaswamy V, Boucher O, Haigh J et al. Radiative forcing of climate change. In : IPCC ed. In Climate Change 2001 : The Scientific Basis( IPCC Third Assessment Report). UK and New York, NY, USA : Cambridge University Press, 2001. 212 25.. :,2000. 5 26 Ehhalt D, Prather M, Dentener F et al. Atmospheric chemistry and greenhouse gases. In : IPCC ed. In Climate Change 2001 : The Scientific Basis( IPCC Third Assessment Report). UK and New York, NY, USA : Cambridge University Press, 2001. 127 27 FAOSTAT. Food and Agriculture Organization of the UN. http :/ / apps.fao. org/, 2002 28. :.,2000, 20 (4) :345 350 29 Li C, Zhuang Y, Frolking S et al. Modeling soil organic carbon change in croplands of China. Ecological Applications, 2003, 13 (2) :327 336 30 IPCC. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories : Workbook (Volume 2), Agriculture. Paris : Published by IPCC National Greenhouse Gas Inventories Programme ( IPCC2NGGIP), 1997. 1 63 GREENHOUSE GAS EMISSIONS FROM CROPLANDS OF CHINA Li Changsheng Xiao Xiangming S. Frolking B. Moore W. Salas Qiu Jianjun Zhang Yu Zhuang Yahui Wang Xiaoke Dai Zhaohua Liu Jiyuan Qin Xiaoguang Liao Bohan R. Sass ( Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, NH 03824, USA ; Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081 ; Institute of Agro2 Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081 ; Research Center for Eco2Environmental Sciences, Chinese Academy of Sciences, Beijing 100085; Institute of Geography and Natural Resources, Chinese Academy of Sciences, Beijing 100101; Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029; Agro2Environmental College, Hunan Agricultural University, Changsha 410128; Life and Evolution Department, Rice University, Houston, Texas 7725221892, USA) Abstract China possesses cropland of 1. 33 million km 2. Cultivation of the cropland not only altered the biogeochemical cycles of carbon (C) and nitrogen (N) in the agroecosystems but also affected global climate. The impacts of agroecosystems on global climate attribute to emissions of three greenhouse gases, namely carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O). Production of the three greenhouse gases in agricultural soils are regulated by many factors ( e. g., climate, soil
5 : properties, crop type, cropping management etc. ). A biogeochemical process model (DNDC) has been developed to predict dynamics of the complex system by integrating the interacting factors. DNDC simulates C and N cycles in agroecosystems as well quantifies fluxes of greenhouse gas emissions from cropland soils. Linked to a GIS databases, DNDC accomplished simulations of greenhouse gas emissions from Chinese croplands in 1990. The results indicated that annual emission rates were 95 Tg C, 9. 2 Tg C and 1. 3 Tg N for CO 2, CH 4 and N 2 O, respectively. Converting the emissions to global warming potentials ( GWP), we found N 2 O emission dominated the impact of Chinese cropland on global warming. The simulations with DNDC also found Chinese agriculture made a significant contribution to mitigation of global greenhouse gases in the time period of 1980 2000. During the 20 years, the CH 4 emissions from Chinese rice paddies decreased from 12 to 7 Tg per year due to change in water management from continuous flooding to midseason drainage. It has been observed that the increase in atmospheric CH 4 concentration has been slowed down since early 1980s. The modeled decrease in CH 4 emissions from Chinese rice paddies is consistent with the globally observed decrease in the atmospheric CH 4 increase rates in the magnitude and time span. The most effective approach for mitigating CO 2 emissions from the Chinese croplands is to change the current management of the crop residue. Increase in the rate of above2ground crop residue incorporated in the soils after harvest from current 15 % to 80 % would reverse the Chinese cropland soil C pool from an atmospheric CO 2 source ( - 95 Tg C/ yr) to a sink (80 Tg C/ yr). Mitigation of the cropland N 2 O emissions in China will rely on precision fertilzation. Over2fertilizing is a common phenomenon in many agricultural regions in China. Determining fertilizer application rates based on modeled soil N mineralization rates will not only decrease N 2 O emissions but also elevating fertilizer use efficiency, maintain optimum yields, and substantially reduce N contamination of surface and ground water bodies in the country. For mitigating greenhouse gas emissions meanwhile obtaining sustainable yields, establishing biogeochemical model/ database approaches is becoming an urgent task to improve agricultural management and policies in China. 503 Key words Chinese agriculture, greenhouse gas, DNDC, biogeochemical model