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Numerical Simulation Of The Sources And Sinks Of CO2in China

Posted on:2013-03-20Degree:MasterType:Thesis
Country:ChinaCandidate:F H YunFull Text:PDF
GTID:2231330371484557Subject:Ecology
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Since the Industrial Resolution, the increase of CO2emission resulted from human activities, has aroused extensive attention of the scholars home and abroad due to its role in global warming. This paper studies the sources, sinks, spatial and temporal distribution of CO2using the simulation methods in order to provide basis for our country to cope with global warming more effectively.In this study, the CarbonTracker mode, which has been widely used by Europe and America scholars, is incorporated the computer platform built by the Greengases Team of the Chinese Academy of Meteorological Sciences. The treatment of downscaling and finement of CarbonTracker mode in China region was completed by the two-way nested atmospheric chemistry model TM5. By doing this, it improved the resolution of the mode in China region, and obtained CO2concentrations in the global solution of3°×2°and those in Asian resolution of1°×1°, as well as the flux results in the resolution of1°×1°. On the basis of long-term CO2observation results in the four background stations in China (Waliguan Global Background Station in Qinghai Province, Shangdianzi Background Station in Beijing, Mt.Longfeng Background station in Heilongjiang Province, and Li’an Background Station in Zhejiang Province), the simulation results were validated by the CO2observation data, and the sources, sinks, spatial and temporal distribution of CO2then were analyzed.The main findings of this papers are as follows:(1) The validation between CO2concentration of four background stations in China region and simulation results shows that there is a good agreement between simulation results and observation data, with the correlation coefficients above0.70. In the four stations, simulation results of CO2concentration in Shangdianzi show the best agreements with observation data. The correlation coefficient in Shangdianzi Background Station between simulation results in the resolution1°×1°and observation data of CO2concentration is as high as0.91. In the exception of Waliguan, the correlation coefficient of simulation results in resolution of1°×1°are higher than those in the resolution of3°×2°in the other3stations, which indicates that the accuracy of simulation is improved with the improvements of resolution.(2) The CO2concentration and fluxes in every station show apparent annual variations, seasonal variations, and daily variations. During the ten years, the CO2concentration suggests an increase trend year by year, with the minimum growth rate in Waliguan,20.27μmol/mol per year, the maximum growth rate in Shangdianzi,27.89μmol/mol per year. The CO2concentration and fluxes in each stations show an obvious seasonal variation as well, with higher concentration in winter and spring, lower concentration in summer and fall. The seasonal variation of CO2concentration in Mt. Longfeng has largest seasonal differences14.7μmol/mol. Besides, the CO2concentration and fluxes have daily variation, and the daily variation trends in different season are not the same. The daily variations in summer and fall are bigger, with minimum concentration at noon, while the daily variations in spring and winter are not very obvious.(3) In the four stations, all the fossil fuel combustion and fire fluxes are carbon sources, but the biosphere flux changes with seasons. Biosphere flux serves as carbon source in winter and spring, and as carbon sinks in summer and fall. The total flux of fossil fuel combustion in China region during the period shows an increasing trend, from0.766Pg C in2000to1.663Pg C in2009, that is an increase of117.13%. But the biosphere flux during the same period shows an irregular variation, with the minimum value in2003, merely-0.094Pg C, the second minimum value in2005,-0.195Pg C, and maximum value in2006,-0.399Pg C. The contributions of fire flux are relatively small, ranging from1%-2%of the total flux. The total flux of biosphere in China Region from2000to2009is-0.27±0.08Pg C/yr, the amounts of CO2absorbed by different ecosystems, however, vary from one to another. Grass/shrub absorb the most CO2, which is-0.13Pg C/yr,48.4%of the total amount, while the percentage of CO2amount absorbed by the mixed forests, coniferous forests and crops/human settlements account for14.9%,14.8%,12.9%of the total amount, respectively.(4) Carbon dioxide and flux of high-value area are concentrated in the economically developed eastern areas, especially in east of Sichuan, west east of Chongqing, south of Shanhai, Jiangsu, Hebei, north of Henan,Beijing, Tianjing, northeast, the highest of carbon dioxide is420umol/mol. carbon dioxide is low in Xinjiang, Xizang, west of Qinghai. carbon dioxide and flux are low in summer, while high in winter. The biosphere flux has the same character that its flux is high in summer and low in winter. The significant carbon sinks takes place in summer, and the carbon sink in eastern region is higher than western region. Fossil fuel burning flux gradually decreased from east to west, and the change of fossil fuel burning flux is not obvious in different seasons. The ocean flux is carbon sink in all seasons, and the carbon sinks in spring and winter is greater than in summer and autumn. Carbon dioxide emissions caused by fire is not obvious following season change.(5)As the impact of turbulent diffusion, the concentration of carbon dioxide in air reduces with the increasing of height. In4300m the following, the discrepancy of concentration is greatly at the same time in different stations. In4300above, the discrepancy of concentration is little difference in the range of about384-386μmol/mol. At the different time in same station, the change of concentration is greatly in830m the following, and the concentration is not change over time above830m. The variation tendency is not completely same in different seasons.
Keywords/Search Tags:CarbonTracker, numerical simulation, CO2, concentrations and fluxes, spatial andtemporal characteristics
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