Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China.
National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
Environ Res. 2024 Dec 15;263(Pt 2):120169. doi: 10.1016/j.envres.2024.120169. Epub 2024 Oct 16.
With China's proposed carbon reduction goals, many carbon monitoring pilot city projects have been launched, involving greenhouse gas (GHG) inverse estimate analysis based on GHG observations. For the evaluation of emissions estimates in a targeted urban area, the contributions of extra-urban fluxes on urban GHG observations must be excluded, especially for core cities within urban agglomerations, which face more severe emission interference from adjacent cities. In this study, we quantified the impact of external emissions on urban carbon dioxide (CO) mole fraction observations across different seasons in the central downtown area of Zhengzhou, a core city of the Central Plains Urban Agglomeration in China. Results showed that 60% of the CO enhancement from the 500-km square area including the city originated outside the core urban area in autumn and winter, predominantly originating from far-field sources (>50 km) in the northeast, west, and northwest of Zhengzhou. To design an optimal monitoring network that accurately accounts for CO mole fractions entering the urban domain of interest, three different selection methods (distance, meteorological trajectory, and multiple regression) were used to select background station locations, and the resulting background values were evaluated through the application of observing system simulation experiments, including synthetic flux inverse estimate. Results indicated that the background stations selected by meteorological trajectories more effectively captured CO variability, introducing the smallest errors to inverse estimate flux (-8%). This study provides a valuable reference for designing background monitoring stations in dense urban agglomerations, thereby improving the accuracy of high-resolution urban GHG emission inverse estimates.
随着中国提出的碳减排目标，许多碳监测试点城市项目已经启动，涉及基于温室气体（GHG）观测的温室气体逆估计分析。对于目标城市区域排放估计的评估，必须排除城市外通量对城市温室气体观测的贡献，特别是对于城市群内的核心城市，这些城市面临着来自相邻城市更严重的排放干扰。在这项研究中，我们量化了外部排放对中国中原城市群核心城市郑州市中心区不同季节城市二氧化碳（CO）摩尔分数观测的影响。结果表明，在秋季和冬季，包括城市在内的 500 公里见方区域的 CO 增强有 60%来自核心城区以外的地区，主要来自郑州东北、西部和西北部的远场源（>50 公里）。为了设计一个能够准确考虑进入感兴趣城市区域的 CO 摩尔分数的最佳监测网络，我们使用了三种不同的选择方法（距离、气象轨迹和多元回归）来选择背景站位置，并通过应用观测系统模拟实验（包括综合通量逆估计）来评估所得背景值。结果表明，气象轨迹选择的背景站更有效地捕捉 CO 的变化，将对逆估计通量的最小误差引入（-8%）。这项研究为在密集城市群中设计背景监测站提供了有价值的参考，从而提高了高分辨率城市温室气体排放逆估计的准确性。
