Modeling study of PM_2.5 pollution episode of early spring 2019 in Hokkaido, Japan caused by biomass burning in Northeast China

¹ Department of Life and Environment Engineering, The University of Kitakyushu, Kitakyushu, Japan
² Graduate School of Engineering, Division of Sustainable Energy and Environmental Engineering, Osaka University, Suita, Japan
³ Nagoya City Institute for Environmental Sciences, Nagoya, Japan
⁴ KANSO TECHNOS CO. LTD., Osaka, Japan
⁵ National Institute for Environmental Studies, Tsukuba, Japan

^* Corresponding author: uranishi@kitakyu-u.ac.jp

Abstract

Biomass burning (BB), in particular agricultural waste burning (Agri-BB), occurs at random locations, scales, and times. These factors make it challenging to detect Agri-BB accurately through satellite observations. Thus, the BB emission inventories using satellite observation data have uncertainties for their emission estimation approach and cause poor model performance for air pollutants including PM_2.5. We utilized the two BB emission inventories, GFEDv4.1s and FINNv2.5 with the CMAQ model to simulate the PM_2.5 heavy pollution episode in Hokkaido 2019. To estimate Agri-BB contributions, we conducted three simulation cases for each BB emission inventory: with and without Agri-BB emission, and the boosted Agri-BB emission cases. The baseline simulation failed to capture the temporal and spatial variation patterns of PM_2.5. Meanwhile, the boosted Agri-BB case could show favorable performance for PM_2.5 concentrations. These results indicated that the two BB emission inventories underestimated Agri-BB emissions. In the two boosted Agri-BB cases, the PM_2.5 contributions from Agri-BB accounted for more than 50% during the episode. Moreover, high PM_2.5 emissions were found in Northeast China and its surrounding regions similar to the two boosted Agri-BB cases. Consequently, the results revealed that Agri-BB emissions during the episode were significantly derived from the agricultural areas in Northeast China.