摘要
甲烷(CH_(4))作为短寿命、高增温潜势的温室气体,了解其浓度分布和变化对我国实现“双碳”目标至关重要.本研究利用Google Earth Engine平台和德国Bremen大学分别基于TROPOMI卫星生产的甲烷浓度产品,系统分析我国华北地区甲烷浓度的分布情况和变化规律,并对两种数据的质量进行对比分析.结果表明,自2019年至2023年,华北地区的甲烷浓度呈上升趋势,其中Offline Methane数据从1850.25×10^(-9)上升到1899.15×10^(-9),增长48.90×10^(-9);Level 2XCH_(4)数据从1860.13×10^(-9)上升到1909.60×10^(-9),增长49.47×10^(-9);天津市和河北省的甲烷浓度相对较高,内蒙古自治区的甲烷浓度相对较低;甲烷浓度异常高值主要分布在河北省和山西省;两种数据之间具有较高的相关性(r为0.92),与香河站数据的相关性均大于0.85,两种数据均能较好地反映地面甲烷浓度.Offline Methane数据可提供可视化下载和高空间分辨率,但数据缺失较多,实际应用中可以采用数据融合等方法进行插补;Level 2XCH_(4)数据空间分辨率较低但覆盖度高,可以根据研究区大小进行网格化处理,适合大区域研究.
Methane(CH_(4)),as a short-lived and high-warming potential greenhouse gas,understanding its concentration distribution and changes is crucial for China to achieve its“Dual Carbon”goal.This study systematically analyzed the distribution and changing pattern of methane concentration in North China utilizing methane concentration products produced by the Google Earth Engine platform and the University of Bremen,Germany,based on the TROPOMI satellite data,and conducted a comparative analysis of the quality of the two datasets.The results demonstrate that the methane concentrations in North China exhibited an increasing trend from 2019 to 2023.Specifically,the Offline Methane data rose from 1850.25×10^(-9) to 1899.15×10^(-9),representing an increase of 48.90×10^(-9),while the Level 2XCH_(4) data rose from 1860.13×10^(-9) to 1909.60×10^(-9) with an increase of 49.47×10^(-9).The methane concentration was relatively high in Tianjin and Hebei Province,while that in the Inner Mongolia Autonomous Region was relatively low.The anomalously high methane concentrations were mainly distributed in Hebei and Shanxi provinces.A strong correlation between the two datasets was observed(r=0.92).Both datasets demonstrated a correlation greater than 0.85 with data from the Xianghe station,indicating that both datasets can effectively reflect the ground-level methane concentration.The Offline Methane data can provide visual downloads and high spatial resolution,but there are many data gaps.In practical applications,data fusion and other interpolation methods can be employed to fill these missing observations.The Level 2XCH_(4) data has lower spatial resolution but higher coverage,and can be processed by gridding based on the size of the study area,making it suitable for large-scale research.
作者
李梦圆
李军
陈伟
解北京
张成业
丁雅欣
黄月军
LI Meng-yuan;LI Jun;CHEN Wei;XIE Bei-jing;ZHANG Cheng-ye;DING Ya-xin;HUANG Yue-Jun(Inner Mongolia Research Institute,China University of Mining and Technology-Beijing,Erdos 017010,China;College of Geoscience and Surveying Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China;College of Emergency Management and Safety Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China;Guoneng Beidian Shengli Energy Co.,Ltd.,Xilinhot 026000,China)
出处
《中国环境科学》
北大核心
2025年第10期5378-5389,共12页
China Environmental Science
基金
鄂尔多斯市科技计划项目(YF20250255)
丝绸之路经济带创新驱动发展试验区、乌昌石国家自主创新示范区科技发展计划项目(2023LQY02)
教育部“春晖计划”国际合作项目(202201628)
中央高校基本科研业务费项目(2023ZKPYDC10)。
