Site selection and effects of background towers on urban CO₂ estimates: A case study from central downtown Zhengzhou in China

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 (CO₂) 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 CO₂ 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 CO₂ 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 CO₂ 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.