Detection of Chinese Spring Festival in Beijing using in-situ CO2 observations and atmospheric inversion

Abstract

Anthropogenic CO2 emissions inventories in urban areas are highly uncertain and lack fine-scale temporal information. Here, we use atmospheric CO2 observations from 6 sites and an ensemble-based "top-down" inversion system to estimate the spatiotemporal dynamics of CO2 emissions in the world's largest urban agglomeration of Beijing-Tianjin-Hebei (JJJ). Relative to the period before the Chinese Spring Festival (CSF) in 2019, we showed, for the first time, a 13.9% reduction and a 14.3% increase in emissions during and after the CSF, respectively, which is missed by a monthly emissions inventory. Moreover, the emissions reduction occurred in most of the JJJ areas. The exact timing of emissions dynamics inferred from the CO2 observations is consistent with a NO2 observation and a near-real-time daily “bottom-up” estimate. Here, we showed the advantages of "top-down" inversion on a fine temporal scale (e.g., daily to weekly) emissions assessment and its potential applications in refined emissions management and reductions.