Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M⁻¹), with 1.09 ± 0.83 Tg M⁻¹ and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5^∘ N, 97–110^∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m⁻² at the surface, positive forcing (1.70 ± 1.40 W m⁻²) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m⁻²) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.

Despite the significant impacts of biomass burning (BB) on global climate change and regional air pollution, there is a relative lack of research on the temporal trends and geographic patterns of BB in Northeast China (NEC). This study investigates the spatial–temporal distribution of BB and its impact on the atmospheric environment in the NEC region during 2004 to 2023 based on remote sensing satellite data and reanalyzed data, using the Siegel’s Repeated Median Estimator and Mann–Kendall test for trend analysis, HDBSCAN to identify significant BB change regions, and Moran’s Index to examine the spatial autocorrelation of BB. The obtained results indicate a fluctuating yet overall increasing BB trend, characterized by annual increases of 759 for fire point counts (FPC) and 12,000 MW for fire radiated power (FRP). BB predominantly occurs in the Songnen Plain (SNP), Sanjiang Plain (SJP), Liaohe Plain (LHP), and the transitional area between SNP and the adjacent Greater Khingan Mountains (GKM) and Lesser Khingan Mountains (LKM). Cropland and urban areas exhibit the highest growth in BB trends, each surpassing 60% (p < 0.05), with the most significant growth cluster spanning 68,634.9 km². Seasonal analysis shows that BB peaks in spring and autumn, with spring experiencing the highest severity. The most critical periods for BB are March–April and October–November, during which FPC and FRP contribute to over 80% of the annual total. This trend correlates with spring planting and autumn harvesting, where cropland FPC constitutes 71% of all land-cover types involved in BB. Comparative analysis of the aerosol extinction coefficient (AEC) between areas with increasing and decreasing BB indicates higher AEC in BB increasing regions, especially in spring, with the vertical transport of BB reaching up to 1.5 km. County-level spatial autocorrelation analysis indicates high–high clustering in the SNP and SJP, with a notable resurgence of autocorrelation in the SNP, suggesting the need for coordinated provincial prevention and control efforts. Finally, our analysis of the impact of BB on atmospheric pollutants shows that there is a correlation between FRP and pollutants, with correlations for PM_2.5, PM₁₀, and CO of 0.4, 0.4, and 0.5, respectively. In addition, the impacts of BB vary by region and season, with the most significant impacts occurring in the spring, especially in the SNP, which requires more attention. In summary, considering the escalating BB trend in NEC and its significant effect on air quality, this study highlights the urgent necessity for improved monitoring and strategic interventions.

Chlorine species play a crucial role as precursors to Cl radicals, which can significantly impact the atmospheric oxidation capacity and influence the levels of trace gases related to climate and air quality. Several studies have established a chlorine emission inventory in China in recent years, but the emission remains uncertain and requires further investigation. The Anthropogenic Chlorine Emission Inventory for China (ACEIC) was the first chlorine emission inventory for China based on local data developed in our previous study, which only includes the emissions from coal combustion and waste incineration. In this study, we updated this inventory to include data for a more recent year (2019) and expanded the range of species considered (HCl, fine particulate Cl⁻, Cl₂, and hypochlorous acid (HOCl)) and the number of anthropogenic sources (41 specific sources). Compared with previous studies, this updated inventory considered more anthropogenic sources, used more localized emission factors, and adopted more refined estimation methods. The total emissions of HCl, fine particulate Cl⁻, Cl₂, and HOCl in mainland China for the year 2019 were estimated to be 361 (−18 % to 27 %), 174 (−27 % to 59 %), 18 (−10 % to 15 %), and 79 (−12 % to 18 %) Gg, respectively. To facilitate analysis, we aggregated the chlorine emissions from various sources into five economic sectors: power, industry, residential, agriculture, and biomass burning. HCl emissions were primarily derived from the industry (43 %), biomass burning (38 %), and residential (13 %) sectors. The biomass burning and industry sectors accounted for 74 % and 19 % of the fine particulate Cl⁻ emissions, respectively. Residential and industry sectors contributed 61 % and 29 % of the total Cl₂ emissions. HOCl emissions were predominantly from the residential sector, constituting 90 % of the total emissions. Notably, the usage of chlorine-containing disinfectants was identified as the most significant source of Cl₂ and HOCl emissions in the residential sector. Geographically, regions with high HCl and fine particulate Cl⁻ emissions were found in the North China Plain, northeastern China, central China, and the Yangtze River Delta, whereas the Pearl River Delta, Yangtze River Delta, and Beijing–Tianjin–Hebei regions exhibited elevated levels of Cl₂ and HOCl emissions. Regarding monthly variation, emissions of HCl and fine particulate Cl⁻ were higher during early spring (February to April) and winter (December to January) due to intensified agricultural activities, while Cl₂ and HOCl emissions were higher in the summer months due to increased demand for water disinfection. We incorporated this emission inventory into the chemical transport model and found the simulated concentrations of chlorine species agreed reasonably well with the observations, which suggested the relatively faithful estimations of their emissions. This updated inventory contributes to a better understanding of anthropogenic sources of chlorine species and can aid in the formulation of emission control strategies to mitigate secondary pollution in China.

The concentration changes of aerosols have attracted wide-ranging attention during the COVID-19 lockdown (CLD) period, but the studies involving aerosol optical properties (AOPs) are relatively insufficient, mainly AOD (fine-mode AOD (AODf) and coarse-mode AOD (AODc)), aerosol absorption optical depth (AAOD), and aerosol extinction coefficient (AEC). Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans.

Ozone (O ₃ ) pollution remains a critical issue facing China. Between 2020 and 2024, the proportion of cities exceeding national standards stood at 22.5 % and 24 % respectively, representing an annual increase of 4.8 %. O ₃ –NO _x –VOCs sensitivity analysis is central to ozone pollution control. Satellite observations from the OMI and TROPOMI provide daily HCHO and NO ₂ data but cannot capture hourly ozone variability. In this study, we use hourly observations from the Geostationary Environment Monitoring Spectrometer (GEMS), in combination with locally estimated scatterplot smoothing (LOESS), to investigate the diurnal evolution of ozone formation sensitivity over China during the warm season (April–September) from 2021 to 2023. The results show a strong correlation between the HCHO / NO ₂ ratio and ozone concentrations ( R ² > 0.78), highlighting the complex nonlinear interactions within the O ₃ –NO _x –VOCs chemical system. At the urban agglomeration scale, ozone formation shifts to NO _x -limited or transitional regimes in the Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Sichuan–Chongqing (SC) regions in the afternoon, while it shifts to NO _x -limited in Pearl River Delta (PRD). Further inter-city comparisons reveal distinct controlling mechanisms. Beijing remains VOC-limited in the morning due to high NO _x emissions combined with strong solar radiation. Nanjing exhibits a persistently complex transitional regime. Chengdu maintains a predominantly VOC-limited regime throughout the day. In contrast, Guangzhou, characterized by active VOC emissions, shows a greater tendency to shift toward a NO _x -limited regime. This study provides the first regional-scale characterization of diurnal ozone formation sensitivity, supporting time-resolved and region-specific emission control strategies.