摘要 :
Land degradation and global warming are currently highly active research topics. Land degradation can both change land cover and surface climate and significantly influence atmospheric circulation. Researches have verified that ca...
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Land degradation and global warming are currently highly active research topics. Land degradation can both change land cover and surface climate and significantly influence atmospheric circulation. Researches have verified that carbon dioxide (CO_2) and methane (CH_4) are major greenhouse gases (CHG) in the atmosphere and are directly affected by human activity. However, to date, there is no research on the spatial distribution of GHG concentrations and also no research on how land degradations affect GHG concentrations in arid and semi-arid regions. In this study, we used GHG data from the ENVlronment SATellite (ENVISAT) and the Greenhouse gases Observing Satellite (GOSAT), the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) data from the MODerate resolution Imaging Spectroradiometer (MODIS) and precipitation data from ground stations to analyze the way land degradation affects GHG concentrations in northern China and Mongolia, which exhibit the most serious land degradation process in East Asia. Our research revealed that the CO_2 and CH_4 concentrations (XCO_2 and XCH_4) increased from 2003 to 2009 and then decreased into 2011. We used geostatistics to predict and simulate the spatial distribution of XCO_2 and XCH_4 and found that the distribution of XCO2 displays a seasonal trend and is primarily affected by plant photosynthesis, soil respiration and precipitation. As the distribution of XCH_4 is mainly affected by the sources' distribution, microbial processes, LST and submarine hydrate, the CH_4 concentration presents no obvious seasonal changes and the high XCH4 values are primarily found in northeast and southeast China. Land degradation increases the concentration of GHG: the correlation coefficient between NDVI and XCO_2 is R~2 = 0.76 (P < 0.01) and the value between NDVI and XCH_4 is R~2 = 0.75 (P < 0.01).
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