To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.
Global change is an important scientific issue that concerns the survival and development of all human beings.According to the Fourth Assessment Report of the United Nations Intergovernmental Panel on Climate Change,over 90% of the possibilities of global warming are attributed to greenhouse gases produced by human use of fossil fuels.Carbon dioxide produced by energy consumption has great pushing effects on global climate change.The studies concerning energy consumption and the emission of carbon dioxide have become the academic focus in current energy environment studies,and they are necessary for the security of economic development and diplomatic negotiations of China.In order to promote the sustainable development of economy,energy and environment of China,the paper analyzes the domestic energy consumption and the present status and various emission scenarios of carbon dioxide emissions in China.Firstly,according to the consumption of primary energy in China,the paper summarizes the carbon dioxide emission factors and methods that are adapt to the situation of China.Secondly,it analyzes the primary energy-related carbon dioxide emissions during the period 1995-2006 from different fossil fuels and in different regions.The primary energy-related carbon dioxide emissions present a trend 'first decrease and later increase' from 1995 to 2006.The inflexion of the changes was 2000,the carbon dioxide emissions since 2001 are bigger than those before 2000.The total carbon dioxide emissions increased from 786.78 million tons carbon to 1 469.19 million tons carbon,and the per capita emissions increased from 0.62 tons carbon to 1.12 tons carbon from 1995 to 2006,with an annual rate of 5.84%.The structural difference in the primary energy-related carbon dioxide emissions was relatively great,among which coal accounts for 79%~85%,oil,14%~19%,and natural gas is 1.23%~1.96%.The seven regions and most of provinces(municipalities or autonomous regions) have a similar trend in the total China's carbon dioxide emissions.The average carbon dioxide emissions for North China and Northeast China are the highest among the seven regions of China.The annual amount of carbon dioxide emissions and the growing rates of Liaoning,Shanxi,Hebei,Shandong and Henan are much greater than those of the other provinces(municipalities or autonomous regions).
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