基于碳卫星数据的区域人为碳排放优化计算方法研究

The increase of atmospheric CO2 caused by human activities is the main cause of recent global warming. Accurate quantification of anthropogenic carbon emissions helps to verify the implementation of emission reduction policies in different regions. Existing emission inventory data based on socioeconomic statistics such as energy suffer large uncertainty in different regions. Carbon assimilation system based on atmospheric observation data provides an effective technical way for the optimization calculation of anthropogenic carbon emissions. The research on optimizing anthropogenic carbon emissions with carbon assimilation system has just started, and there are still many technologies to be developed. This project intends to develop the method of assimilating multi-source CO2 data from ground, aircraft and satellites by improving the high-resolution regional carbon assimilation system based on Lagrange atmospheric model, introduce atmospheric CO data and high-resolution anthropogenic carbon emission inventory for China, and developing the method of optimizing regional anthropogenic carbon emission fluxes by jointly assimilating atmospheric CO2 and CO data. The rationality of optimized carbon fluxes will be evaluated against existing global carbon assimilation results, anthropogenic carbon emission inventory statistics, ecosystem carbon flux simulation and estimation, surface remote sensing indicators and meteorological reanalysis data. This study will be of great scientific significance and national demand to promote scientific research on carbon cycle and climate change, international negotiations on carbon mitigation and the development of carbon trading market in China.

人类活动造成的大气CO2浓度增高是近年来全球变暖的主要原因。准确计算人为碳排放对全球不同地区减排政策落实情况起到核查作用。现有根据能源等统计数据推算的排放清单数据具有较大的不确定性，而基于大气观测数据的碳同化系统为人为碳排放的优化计算提供了一种有效的技术途径。利用其优化人为碳排放的研究刚刚起步，尚有许多技术需要发展。本项目拟通过改进基于拉格朗日型大气模式的高分辨率区域碳同化系统，发展同化地基、飞机和卫星多源CO2数据的方法；引进大气CO数据与针对我国区域的高分辨率人为碳排放清单，发展联合同化大气CO2和CO数据优化计算区域人为排放碳通量的方法；结合多种现有全球碳同化结果、人为碳排放清单统计数据、生态系统碳通量模拟估算、地表遥感指标和气象再分析资料，评价碳通量优化计算结果的合理性。本研究将对促进我国碳循环及气候变化科学研究、国际谈判与促进碳交易市场发展具有重要的科学意义和重大的国家需求。

人为碳排放的准确估算对于减缓大气CO2浓度上升及其气候变化影响的政策制定至关重要，是落实“碳达峰、碳中和”目标的重要前提。然而，当前区域尺度人为碳排放估算具有很大的不确定性。基于大气CO2浓度数据、特别是碳监测卫星数据的大气反演有望改善区域人为碳排放估算的准确性。本项目开展了包括GOSAT和OCO-2碳卫星XCO2数据在内的多源数据同化研究，估算了中国陆地碳汇大小和分布，揭示了其在生长季峰期和年度的不同空间分布规律，阐明了同化卫星数据对区域碳汇估算及其大尺度干旱影响模拟的改进作用；开展了我国地面大气CO2观测站点的拉格朗日大气传输足迹模拟，利用地基CO2浓度数据评价了现有“自下而上”碳排放清单对我国人为碳排放的估算效果，论证了利用污染气体（CO和NOx）示踪法估算人为碳排放的可行性；发展了可同化碳卫星XCO2数据和优化人为碳排放的区域碳同化系统，利用大气NOx数据优化估算了中国区域人为碳排放，揭示了我国人为碳排放时空分布特征。结果表明，排放清单总体低估了我国人为碳排放强度，但有明显的地区差异；利用NOx示踪反演的方法可以有效改善我国区域人为源CO2排放估算。发展碳卫星数据同化和基于污染气体优化计算人为碳排放的方法能够提高区域尺度碳源汇反演估算精度。研究成果有助于提高我们对中国区域碳源汇大小及分布规律的认知，并为相关政策制定和落实提供科学数据支撑。

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