Observation Constrained Aromatic Emissions in Shanghai, China. Issue 6 (18th March 2020) - Wang, Hongli; Yan, Rusha; Xu, Tingting; Wang, Yuhang; Wang, Qian; Zhang, Tianqi; An, Jingyu; Huang, Cheng; Gao, Yaqin; Gao, Yang; Li, Xiang; Yu, Chao; et al.
Abstract: Aromatics in the atmosphere are a large contributor to ozone and secondary organic aerosol formation and have an adverse impact on human health. Observation‐based emissions are urgently needed for air quality management and decision making due to the large uncertainties in the emissions inventories. Atmospheric aromatics were continuously observed at one urban site in Shanghai of China in 2015, which were compared with the simulations of the Community Multiscale Air Quality (CMAQ) model. Large differences were found in the temporal variations between the model and measurements, corroborating with previous studies that the current bottom‐up emission inventories are highly biased. We corrected the aromatic emissions biases of the emission inventories using the observations with the CMAQ simulations, with the assumption that the response relationship of the emissions input and aromatic concentrations was reasonable on a monthly basis in CMAQ simulations, suggesting that the results are dependent on the model performance. The resulting aromatic emissions exhibited clear monthly variations, increasing from 5.5 ± 2.1 Gg month −1 in February to 17.4 ± 7.7 Gg month −1 in July, being different from the flat monthly pattern in the current bottom‐up emissions inventory. Toluene, xylenes, and ethylbenzene dominated aromatic emissions, accounting for 74% on average but with considerable monthly variations, which was different from the nearly uniform value of 77% throughout the whole year in the emissions inventory. These highly temporally resolved and speciated in situ aromatics measurements provide observation‐based constraints on aromatic emissions, which cannot be obtained from satellite measurements. This study proposes a top‐down emission estimation method constrained by ambient measurements. Key Points: Differences were found in aromatics characteristics between model simulations and measurements Observation‐constrained aromatic emissions were estimated in Shanghai Aromatic emissions exhibited clear monthly variations