[A-AS09] Atmospheric Chemistry

[AAS09-07] China's black carbon, CO, and CO2 emissions from integrated analysis of the Regional Air Quality Model (CMAQ) and EMeRGe-Asia aircraft observations during early spring 2018

*Phuc Thi Minh Ha¹, Yugo Kanaya¹, Kazuyo Yamaji², Takashi Sekiya¹, Maria Dolores Andrés Hernández³, John Philip Burrows³, Hans Schlager⁴, Michael Lichtenstern⁴, Mira Poehlker⁵, Bruna Holanda⁵, EMeRGe-Asia science team - (1.Research Institute for Global Change, JAMSTEC, Yokohama, 236-0001, Japan, 2.Graduate School of Maritime Sciences, Kobe University, Kobe, Hyogo, 658-0022, Japan, 3.Institut für Umweltphysik, Universität Bremen, Otto-Hahn-Allee 1, Bremen 28359, Germany, 4.DLR Oberpfaffenhofen, Institut fuer Physik der Atmosphaere, 82234 Wessling, Germany, 5.Max Planck Institute for Chemistry, Multiphase Chemistry Department, Hahn-Meitner-Weg 1, 55128 Mainz, Germany)

Keywords:bottom-up emission inventories, aircraft measurement, Chinese emissions, forest fires

Accurate emissions estimations of SLCFs (short-lived climate forcers) and greenhouse gases are required to mitigate climate change efficiently. However, estimates of SLCF emissions from Asia are still associated with large uncertainties. In this study, we used a combined model-observation approach based on the Community Multiscale Air Quality (CMAQ) model and the EMeRGe-Asia aircraft observations during March–April 2018 to estimate China's emissions of combustion-related SLCFs of black carbon (BC) and carbon monoxide (CO). The aircraft observations from near-surface to about 1-2 km altitudes provided an excellent dataset over the Asian continental outflow region, giving insights into emission information regarding those from biomass burning in the Indochina Peninsula and from anthropogenic sources in Japan, the Philippines, and China. The model's superior performance in predicting peak timings confirmed the suitability of the used emission in distribution patterns and the transport representation, while the gaps between the observed and simulated concentrations were ascribed to the biases in the emissions assumed for simulations: GFEDv4.1 inventory for fire emissions, although the anthropogenic emissions for Japan (JEI-DB) and the Philippines (REASv2.1) underestimated BC and CO concentrations. The HTAPv2.2z (MEICv1.0) inventory could not fully reproduce China's peaks on BC, CO concentrations, and BC/CO ratio measured by the aircraft, showing evident biases (at most +1.62 ng m^-3 BC, -400 ppbv CO) which were consistent with our previous analysis based only on the surface observations. The BC/CO emission ratio of 3.5 ng m^-3 ppb^-1 for the Chinese air mass previously observed at a ground-based station was confirmed for the first time by the aircraft data at ~0.3 – 1 km. While noting the small footprint of the observed Chinese air masses and associated uncertainty, China's country total emissions were estimated by linearly scaling the original emissions (BC regarding HTAPv2.2z) with the derived emission correction factor. This has resulted in 0.63±0.19 Tg BC, which translated to 160±49 Tg CO, and 11.6±3.5 Pg CO₂, when using the observed BC/CO and CO/CO₂ emission ratios. Besides random and systematic uncertainties (~30%), the estimations from aircraft data might be influenced by the used model performance in simulating vertical profiles; this was estimated to be ~20%. Even when allowing such uncertainties, this study strongly suggests a reduction of ~ 50% in China's bottom-up BC emission with HTAPv2.2z and an increase of ~ 20% in CO emission were required to minimize the discrepancy with the aircraft-measured data, corroborating the conclusion from the ground-based data analysis.