[A-AS11] Atmospheric Chemistry

[AAS11-P24] Examination of anthropogenic CO₂ emission inventories using ground-based observations and high-resolution model simulations over the Tokyo Megacity

*Zhenglun Yang¹, Yukio Terao¹, Thomas Lauvaux², Charbel Abdallah², Tomohiro Oda^3,4, Masahide Nishihashi⁵, Makoto Saito¹, Shigeyuki Ishidoya⁶, Hirofumi Sugawara⁷, Motoki Sasakawa¹, Yasunori Tohjima¹ (1.National Institute for Environmental Studies, Japan, 2.Université de Reims-Champagne Ardenne, France, 3.Universities Space Research Association (USRA), USA, 4.University of Maryland, USA, 5.Meteorological Research Institute, Japan, 6.National Institute of Advanced Industrial Science and Technology (AIST), Japan, 7.National Defense Academy of Japan, Japan)

Keywords:CO2 emissions, WRF-Chem, atmospheric modeling, emission inventories

Metropolitan areas, characterized by dense populations, intensive industrial activities, and heavy vehicular traffic, are the largest contributors to global anthropogenic CO₂ emissions. Quantifying and tracking CO₂ emissions from megacities are crucial for climate change mitigation, but it remains challenging due to the complexity of urban CO₂ dynamics and the lack of emission information. In this study, we aim to establish a framework to monitor CO₂ emissions from the Greater Tokyo Area (GTA) using atmospheric observations and a high-resolution atmospheric model. As a first step, we examine the model reproducibility of CO₂ variations observed from our high-precision ground-based observations using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). We also examine the sensitivity of emission inventories that prescribe the WRF-Chem model using five global and local inventories.

We implement WRF-Chem simulations for atmospheric CO₂ concentrations using a two-domain nested configuration with grid spacings of 3 km and 1 km. We prescribe the runs using five anthropogenic CO₂ emissions inventories including global datasets (ODIAC2023, EDGARv8.0, CAMS-GLOB-ANTv6.2, and GCP-GridFEDv2023.1) and a locally constructed emission dataset (MOSAIC). Monthly emission estimates from the five emissions inventories are refined to hourly emissions. The simulated CO₂ concentrations are compared to CO₂ observations from four continuous monitoring sites in the Tokyo metropolitan area (Tokyo Skytree and Yoyogi) and in the Tokyo suburbs (Tsukuba and Yokosuka). The CO₂ concentrations are measured using the cavity ring-down spectrometer (CRDS) (Picarro G2401). We confirm that our simulations replicate the temporal atmospheric CO₂ variations in demonstrating its capability in resolving CO₂ in the urban atmosphere. However, in densely populated areas, all five emission inventories consistently overestimated near-surface CO₂ concentrations, suggesting potential biases in emission estimates or atmospheric transport and boundary layer processes in the model. Our initial results underscore the importance of high-resolution modeling and observational constraints for robustly monitoring urban CO₂ emissions.