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Abstract: Air pollution caused by biomass burning has been a major concern over east China in recent decades. The distinct radiative effects of biomass burning aerosol due to its strong absorption also bring great uncertainty to the regional climate change. Therefore, it is urgent to investigate the spatial, temporal and vertical distribution of biomass burning aerosols over eastern China. In this paper, machine learning and multi-threshold method were used to identify biomass burning aerosol. We used a random forests model to identify biomass burning aerosols based on multi-source data includes Himawari-8 with high temporal resolution. The validated method would provide a basis for the study of aerosol radiation effect in China. This study is also useful to monitor smoke pollution in eastern China. [ABSTRACT FROM AUTHOR]

Open biomass burning (OBB) has significant impacts on air pollution, climate change and potential human health. OBB has gathered wide attention but with little focus on the annual variation of pollutant emission. Central and eastern China (CEC) is one of the most polluted regions in China. This study aims to provide a state-of-theart estimation of the pollutant emissions from OBB in CEC from 2003 to 2015, by adopting the satellite observation dataset - the burned area product (MCD64Al) and the active fire product (MCD14 ML) - along with local biomass data (updated biomass loading data and high-resolution vegetation data) and local emission factors. The successful adoption of the double satellite dataset for long-term estimation of pollutants from OBB with a high spatial resolution can support the assessing of OBB on regional air quality, especially for harvest periods or dry seasons. It is also useful to evaluate the effects of annual OBB management policies in different regions. Here, monthly emissions of pollutants were estimated and allocated into a 1×1 km spatial grid for four types of OBB including grassland, shrubland, forest and cropland. From 2003 to 2015, the emissions from forest, shrubland and grassland fire burning had an annual fluctuation, whereas the emissions from crop straw burning steadily increased. The cumulative emissions of organic carbon (OC), elemental carbon (EC), methane (CH4), nitric oxide (NOx), non-methane volatile organic compounds (NMVOCs), sulfur dioxide (SO2), ammonia (NH3), carbon monoxide (CO), carbon dioxide (CO2) and fine particles (PM2:5) were 3:64×103, 2:87×102, 3:05×103, 1:82×103, 6:4×103, 2:12×102, 4:67×102, 4:59×104, 9:39×105 and 4:13×103 Gg in these years, respectively. Crop straw burning was the largest contributor for all pollutant emissions, by 84%-96%. For the forest, shrubland and grassland fire burning, forest fire burning emissions contributed the most, and emissions from grassland fire were negligible due to little grass coverage in this region. High pollutant emissions concentrated in the connection area of Shandong, Henan, Jiangsu and Anhui, with emission intensity higher than 100 tons per square kilometer, which was related to the frequent agricultural activities in these regions. Peak emission of pollutants occurred during summer and autumn harvest periods including May, June, September and October, during which ~ 50% of the total pollutant emissions were emitted in these months. This study highlights the importance of controlling the crop straw burning emissions. From December to March, the crop residue burning emissions decreased, while the emissions from forest, shrubland and grassland exhibited their highest values, leading to another small peak in emissions of pollutants. Obvious regional differences in seasonal variations of OBB were observed due to different local biomass types and environmental conditions. Rural population, agricultural output, economic levels, local burning habits, social customs and management policies were all influencing factors for OBB emissions. [ABSTRACT FROM AUTHOR]

Biomass burning is a main source for primary carbonaceous particles in the atmosphere and acts as a crucial factor that alters Earth's energy budget and balance. It is also an important factor influencing air quality, regional climate and sustainability in the domain of Pan-Eurasian Experiment (PEEX). During the exceptionally intense agricultural fire season in mid-June 2012, accompanied by rapidly deteriorating air quality, a series of meteorological anomalies was observed, including a large decline in near-surface air temperature, spatial shifts and changes in precipitation in Jiangsu province of East China. To explore the underlying processes that link air pollution to weather modification, we conducted a numerical study with parallel simulations using the fully coupled meteorology-chemistry model WRFChem with a high-resolution emission inventory for agricultural fires. Evaluation of the modeling results with available ground-based measurements and satellite retrievals showed that this model was able to reproduce the magnitude and spatial variations of fire-induced air pollution. During the biomass-burning event in mid-June 2012, intensive emission of absorbing aerosols trapped a considerable part of solar radiation in the atmosphere and reduced incident radiation reaching the surface on a regional scale, followed by lowered surface sensible and latent heat fluxes. The perturbed energy balance and re-allocation gave rise to substantial adjustments in vertical temperature stratification, namely surface cooling and upper-air heating. Furthermore, an intimate link between temperature profile and small-scale processes like turbulent mixing and entrainment led to distinct changes in precipitation. On the one hand, by stabilizing the atmosphere below and reducing the surface flux, black carbonladen plumes tended to dissipate daytime cloud and suppress the convective precipitation over Nanjing. On the other hand, heating aloft increased upper-level convective activity and then favored convergence carrying in moist air, thereby enhancing the nocturnal precipitation in the downwind areas of the biomass-burning plumes. [ABSTRACT FROM AUTHOR]