摘要
CO_(2)是主要的温室气体之一,它对全球变暖的作用很大。自工业化以来,CO_(2)浓度在全球范围内大幅增加。为实现碳减排目标,迫切需要监测大气中的CO_(2)浓度并分析其时空分布特征。随着温室气体观测卫星的发射,利用碳卫星可以大范围地观测和分析大气中的CO_(2)浓度。本研究基于GOSAT-2卫星数据,利用克里金插值技术分析了2020年6月至2021年5月中国陆地区域的CO_(2)柱浓度(XCO_(2))的时空变化特征。结果表明,全国范围内XCO_(2)的平均值从2020年的413.86 ppm增加到2021年的419.59 ppm,增加了5.73 ppm。其中,XCO_(2)的最低值和最高值分别出现在冬季和春季。进一步的分析表明,XCO_(2)在空间分布上不一致,在人口密度较高的东南部区域浓度较高,而在人口稀少的西北部较低。此外,大城市及其周边地区的XCO_(2)普遍高于其他地区,表明人为因素导致城市地区的XCO_(2)增加过快。本文的分析结果可为碳源与碳汇的研究提供重要的基础数据和参考依据。
CO_(2) is one of the main greenhouse gases,which plays a great role in global warming.Since industrialization,the concentration of CO_(2) has increased substantially worldwide.In order to achieve the target of carbon reduction,it is urgent to monitor the concentration of CO_(2) in the atmosphere and analyze its spatial and temporal distribution characteristics.With the launch of greenhouse gas observation satellites,carbon satellites can be used to observe and analyze atmospheric CO_(2) concentration on a large scale.Using GOSAT-2 satellite data and Kriging interpolation technique,the spatial and temporal variation of CO_(2) column concentration(XCO_(2))over China's land area from June 2020 to May 2021 is analyzed.The results show that the nationwide average XCO_(2) has increased from 413.86 ppm in 2020 to 419.59 ppm in 2021(an increase of 5.73 ppm).The lowest and highest values of XCO_(2) appear in winter and spring,respectively.The further analysis shows that XCO_(2) is spatially inconsistent,with higher concentration in the densely populated southeast region and lower concentration in the sparsely populated northwest region.In addition,XCO_(2) in large cities and their surrounding areas are generally higher than that in other areas,indicating that human factors cause XCO_(2) in urban areas to increase too quickly.The analysis results can provide important basic data and reference for the study of carbon sources and sinks.
作者
侯欣言
哈斯巴干
特日格勒呼
HOU Xin-yan;HASI Ba-gan;TE Teri-gelehu(School of Environmental and Geographical Sciences,Shanghai Normal University,Shanghai 200234,China)
出处
《红外》
CAS
2023年第8期42-48,共7页
Infrared
基金
上海市科技计划项目(22010503600)。