基于多因子联合法的大气CO2源汇信息提取及其长期变化趋势分析-以青海瓦里关14年大气CO2观测资料为例

Long-term continuous observation of atmospheric CO2 could reflect changes of CO2 sources and sinks over a regional or global scale. Using the observed data, uncertainties in estimating carbon sources and sinks could be reduced, as would be significant for understanding and predicting climate change in the future. In this study, we propose to develop a method for distinguish sources and sinks information from atmospheric CO2 time series by taking the CO2 dataset observed at Waliguan, Qinghai during 1995-2008 as an example, as would be based on multifactor combined, including using horizontal wind data, back trajectory analysis (Hysplit model), CO tracer method, using synchronous vertical CO2 data from tower at the site, by examine the characteristics of CO2 diurnal variation and applying statistical methods. The new developed method would be more accurate and reasonable by comparing with previous approaches which are only based on single factor. The applicability and reasonability will also be examined by comparing with the flask data at the site as well as the synchronous data from other sites over the globe. Finally, we will estimate and imply changes of CO2 emissions and sinks in western China from the selected elevated and sequestered CO2 episodes under rapid economic development and land use changes. Also, the inter-annual changes, seasonal cycles and the driving factors will be disclosed by investigating the selected background data. The proposed study aims to advance understanding in changes of CO2 sources and sinks and to provide basic for further studies related to climate change.

大气CO2浓度的长期观测可实时反映区域及更大尺度的CO2源汇动态变化。利用这些资料可减小碳源汇估算的不确定性，对全面理解与预测气候变化意义重大。本研究拟以尺度更新的我国时间序列最长的青海瓦里关大气CO2浓度资料（1995-2008）为例，考虑和诊断多个因子（包括同期地面风资料和Hysplit后向轨迹模型分析，同期CO、黑碳和梯度CO2观测资料诊断，以及多种统计方法平滑拟合等），建立一种基于多因子联合的大气CO2源汇信息提取方法，旨在提高以往仅使用单一因子进行CO2本底值筛选的准确性。并与同期瓶采样和国际同类站点资料互比，探讨其适用性和科学性。利用提取的源汇信息揭示随着经济的快速发展导致的过去14年我国西部地区CO2排放源和吸收汇的变化；利用筛分的本底数据研究大气CO2浓度年际间波动、季节规律，揭示其驱动因子。期望为进行温室气体源汇估算及全球气候变化相关领域的深入研究奠定基础。

大气CO2浓度的长期观测可实时反映区域及更大尺度的CO2源汇动态变化。利用这些资料可减小碳源汇估算的不确定性，对全面理解与预测气候变化意义重大。本项目利用利用尺度更新的大气CO2浓度资料时间序列（1995-2008年），结合瓦里关站同期地面风资料、气象资料及Hysplit大气长距离输送模型、同期CO资料以及多种统计学方法（如傅立叶红外变换、局部近似回归、移动平滑法等）等，同时根据大气CO2多年日变化以及短期波动规律，建立了一种基于多因子联合的大气CO2资料源汇信息提取方法提高了以往仅使用单一因子进行CO2本底值筛选的准确性。进一步，该项目将应用多因子联合和仅考虑单个因子所获得的大气CO2源汇筛分结果进行比对研究，并与国际上同纬度高海拔类似站点所获得的大气CO2浓度长期变化本底特征（季节变化、年际变化及逐年增长率等）进行了比较，研究和探讨了该新方法的适用性和科学性。 最后，利用提取的源汇信息揭示了随着经济的快速发展导致的过去14年我国西部地区CO2排放源和吸收汇的变化及其驱动因子。本项目的研究成果期望为进行温室气体源汇估算及全球气候变化相关领域的深入研究奠定基础。