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The substantial amount of pollutants produced by crop burning leads to particulate matter (PM 2.5) formation through chemical reactions in the atmosphere. In this study, we quantitatively examined the characteristics of PM 2.5 component concentration changes and the production mechanism of sulfate (SO 4 2−) due to crop burning in China, during a period of high PM 2.5 concentrations in South Korea. Crop burning emissions were obtained from the Fire INventory from NCAR (FINN), and simulations were conducted using the Community Multi-scale Air Quality (CMAQ) model. The concentrations of PM 2.5 , nitrate, ammonium, organic carbon, and elemental carbon caused by crop burning were the highest in Northeast China, while the SO 4 2− concentration was higher in the Shandong Peninsula and the Yellow Sea. SO 4 2− was mainly produced through the oxidation reaction by hydrogen peroxide (H 2 O 2) (H 2 O 2 + S(IV) = S(VI) + H 2 O) (1.44 μg/m3, 80.49%). H 2 O 2 that contributed to SO 4 2− production was primarily produced through the self-reaction of hydroperoxy radical (HO 2). Moreover, HO 2 , which contributed to the production of H 2 O 2 , was mainly formed through the decomposition of peroxynitric acid (PNA), which is produced by nitric oxide (NO x) emissions from crop burning. SO 4 2− in the Yellow Sea was reported to be predominantly produced by the oxidation of sulfur dioxide (SO 2) by hydroxyl radical (OH) (OH + SO 2 = SULF + HO 2); however, our study suggests that the PNA formed by NO x emissions from crop burning could contribute to an increase in H 2 O 2 , which subsequently promotes SO 4 2− production. The produced SO 4 2− was then transported across the Yellow Sea, impacting the elevated PM 2.5 concentrations in Jeju Island, a suburban area of South Korea. These findings demonstrate that the mechanisms of SO 4 2− production by crop burning emissions differ from those of anthropogenic emissions. [Display omitted] • Characteristics of transboundary transport of SO 4 2− concentrations induced by crop burning were investigated. • The SO 4 2− due to crop burning was primarily produced by the reaction of H 2 O 2 with S(IV), differing from that by anthropogenic emissions. • The H 2 O 2 was produced through the self-reaction of HO 2 , which was formed by the decomposition reaction of PNA. • The transported SO 4 2− contributed to an increase in the proportion of SO 4 2− in the PM 2.5 concentrations in South Korea. [ABSTRACT FROM AUTHOR]

Persistent and intensive wildland dense-fires (DFs) release substantial amounts of airborne pollutants, resulting in a sharp increase in emissions and leading to serious impacts on the environment and human health over extensive geographical areas. It is challenging to thoroughly investigate patterns of fire occurrence and fire distribution for predicting wildfire behaviour, and it is especially difficult to distinguish the characteristics of human-caused and climate-driven fires. Here, we identify and assess dense-fire (DF) from the perspective of spatiotemporally integrated processes using a machine-learning method based on a density-based clustering algorithm with noise constraint ratio. DFs represent collections of fires with homogenous behaviour and therefore allow the study of their internal features, which can reveal fixed patterns of fire occurrence and distribution as well as the evolution of fires over time. We estimated and labelled thousands of fire clusters on the Indochina Peninsula between 2010 and 2020, most of which occurred between December and May. For large-scale DFs, the number of fires contained and amount of atmospheric pollutants emitted were accounted for throughout most of the region, and the time, location and scale of their occurrence each year were relatively stable and predictable. Furthermore, the results of a secondary cluster analysis of fire interactions over the past decade showed two extreme fire events, labelled"north" and"south" groups, whose activities significantly impacted the atmospheric environment of the Indochina Peninsula. Additionally, we predicted their start/end dates and daily emissions. The study also found that the recurrence of high-density fires and the correlation between the DF edge and administrative border suggested a positive anthropogenic influence. To the authors' knowledge, this study is the first to analyze fires in a spatiotemporal Euclidean space by using density-based clustering, with high-density fires as independent subjects to study fire behaviour. The method proposed in this study can provide a reference for wildfire prediction and emission forecasting and fire control work. [Display omitted] • Propose a new concept for studying high-density fires based on density algorithm. • Indicate the predictability of large-scale dense-fire distributions and emissions. • Anthropogenic influence is one of the important factors in fire distribution. • Two large-scale intensive fires dominate the emissions in the Indochina Peninsula. [ABSTRACT FROM AUTHOR]