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GOSAT卫星数据监测中国大陆上空CO2浓度时空变化特征
引用本文:邓安健,郭海波,胡洁,姜成桢,刘培更,荆海峰.GOSAT卫星数据监测中国大陆上空CO2浓度时空变化特征[J].遥感学报,2020,24(3):319-325.
作者姓名:邓安健  郭海波  胡洁  姜成桢  刘培更  荆海峰
作者单位:1.河南理工大学 测绘与国土信息工程学院, 焦作 454000;2.黄河勘测规划设计有限公司, 郑州 450003
基金项目:河南省自然科学基金(编号: 182300410113); 河南理工大学博士基金(编号: B2017-08)
摘    要:中国地区大气CO2浓度对全球气候变化有重要的影响。本文基于日本GOSAT卫星短波红外CO2的长期观测数据,对2010年-2016年中国大陆上空CO2浓度的分布特征和变化趋势进行分析研究。利用高精度的地基TCCON站点CO2观测对GOSAT CO2数据进行精度验证,结果表明,GOSAT CO2具有较高的精度,相对TCCON CO2的偏差为-1.04±2.10 ppm,两者的相关系数高达0.90;利用中国地区7年的GOSAT CO2观测数据分析研究显示,CO2浓度高值主要分布在中国的浙江-江苏-安徽地区、京津冀地区和湖南-湖北-河南-陕西地区;截至2016年,中国大部地区CO2浓度超过400 ppm;中国大陆CO2平均浓度呈现明显的逐年增长趋势,从2010年的387.76 ppm增长到2016年的402.18 ppm,年增长率约为2.31 ppm/a,略高于同期全球平均水平。

关 键 词:CO2浓度  分布模式  CO2年增长率  中国大陆  GOSAT卫星
收稿时间:2018/8/8 0:00:00

Temporal and distribution characteristic of CO2 concentration over China based on GOSAT satellite data
DENG Anjian,GUO Haibo,HU Jie,JIANG Chengzhen,LIU Peigeng,JING Haifeng.Temporal and distribution characteristic of CO2 concentration over China based on GOSAT satellite data[J].Journal of Remote Sensing,2020,24(3):319-325.
Authors:DENG Anjian  GUO Haibo  HU Jie  JIANG Chengzhen  LIU Peigeng  JING Haifeng
Institution:1.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 45400, China;2.Yellow River Engineering Consulting Company with Limited Liability, Zhengzhou 450003, China
Abstract:Atmospheric CO 2 concentration over China has significant effects on the global climate change. To reliably predict the impact of atmospheric CO 2 on global climate change, it is necessary to clarify the distribution and variation of atmospheric CO 2 concentration. Based on long term short-wavelength infrared CO 2 dataset observed by GOSAT, the temporal variation and spatial distribution characteristics and variation trend of atmospheric CO 2 concentration was investigated and analysed over China during 2010 to 2016. To ensure the quality of GOSAT CO 2 dataset used in this paper, the GOSAT XCO 2 dataset was validated with high precise XCO 2 from ground-based TCCON sites. Multi-year mean of XCO 2 was illustrated to show the spatial heterogeneity of CO 2 concentration over China. Interannual variation and annual growth of XCO 2 was also presented and discussed. The results showed that GOSAT XCO 2 dataset was biased by -1.04±2.10 ppm with respect to TCCON XCO 2, and the correlation coefficient was 0.90 between them. Seven years (2010~2016) of GOSAT CO 2 dataset showed that high CO 2 concentrations were mainly located in Zhejiang-Jiangsu-Anhui region, Beijing-Tianjin-Hebei region, and Hunan-Hubei-Henan-Shanxi region in China. The CO 2 concentration reached 400 ppm over most regions in China until 2016. The annual average of CO 2 concentration showed an increase trend year by year over China, increasing from 387.76 in 2010 to 402.18 ppm in 2016. The annual growth rate of CO 2 concentration was evaluated to be 2.31 ppm/a during this period over China, which was slightly higher than the average in the world. This paper shows that the CO 2 concentration observations from satellites could provide some references for the climate change response strategies and atmospheric environment control.
Keywords:CO 2 concentration  distribution pattern  annual growth rate of CO 2  China mainland  GOSAT
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