The influence of regional transport on aerosol pollution has been explored in previous studies based on numerical simulation or surface observation. Nevertheless, owing to inhomogeneous vertical distribution of air pollutants, vertical observations should be conducted for a comprehensive understanding of regional transport. Here we obtained the vertical profiles of aerosol and its precursors using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) at the Nancheng site in suburban Beijing on the southwest transport pathway of the Beijing-Tianjin-Hebei (BTH) region, China, and then estimated the vertical profiles of transport fluxes in the southwest-northeast direction. The maximum net transport fluxes per unit cross-sectional area, calculated as pollutant concentration multiply by wind speed, of aerosol extinction coefficient (AEC), NO₂, SO₂ and HCHO were 0.98 km⁻¹ m s⁻¹, 24, 14 and 8.0 μg m⁻² s⁻¹ from southwest to northeast, which occurred in the 200–300 m, 100–200 m, 500–600 m and 500–600 m layers, respectively, due to much higher pollutant concentrations during southwest transport than during northeast transport in these layers. The average net column transport fluxes were 1200 km⁻¹ m² s⁻¹, 38, 26 and 15 mg m⁻¹ s⁻¹ from southwest to northeast for AEC, NO₂, SO₂ and HCHO, respectively, in which the fluxes in the surface layer (0–100 m) accounted for only 2.3%–4.2%. Evaluation only based on surface observation would underestimate the influence of the transport from southwest cities to Beijing. Northeast or weak southwest transports dominated in clean conditions with PM₂.₅ <75 μg m⁻³ and intense southwest transport dominated in polluted conditions with PM₂.₅ >75 μg m⁻³. Southwest transport through the middle boundary layer was a trigger factor for aerosol pollution events in urban Beijing, because it not only directly bringing air pollutants, but also induced an inverse structure of aerosols, which resulted in stronger atmospheric stability and aggravated air pollution in urban Beijing.

Various precursor emissions and chemical mechanisms for secondary organic aerosol (SOA) formation were incorporated into a regional air quality model system (RAQMS) and applied to investigate the distribution, composition, and source contribution of SOA over east China in summer 2018. Model comparison against a variety of observations at a national scale demonstrated that the model was able to reasonably reproduce meteorological variables, O₃ and PM₂.₅ concentrations, and the model simulated SOA concentration generally agreed with observations, with the overall NMB of 7.0% and R of 0.4 in 10 cities over east China. The simulated period-mean SOA concentrations of 4–15 μg m⁻³ were mainly distributed over the North China Plain (NCP), the middle and lower reaches of the Yangtze River and Chongqing district. SOA dominated organic aerosol (OA) over China in summertime (90%). The percentage contributions to SOA from ASOA (SOA produced from anthropogenic volatile organic compounds (AVOC)), BSOA (SOA produced from biogenic volatile organic compounds (BVOC)), DSOA (SOA produced from aqueous uptake of glyoxal and methylglyoxal) and S/I-SOA (SOA produced from semi-volatile and intermediate volatile organic compounds) were estimated to be 48.3%, 28.6%, 14.3%, and 8.8% respectively, over east China in summertime. In terms of domain and period average, ASOA contributed most to SOA (59%) in north China, while BSOA contributed most to SOA (37.3%) in northeast China. The percentage contribution of DSOA to SOA reached 21.5% in southwest China. S/I-SOA accounted for approximately 10% of SOA in most areas of east China. This study reveals that while AVOC dominates SOA formation on average over east China, the SOA source contributions differ considerably in different regions of China. BVOC makes the same contribution to SOA formation as AVOC in northeast China and southwest China, where forest coverage and BVOC emission are higher and anthropogenic emissions are relatively low, highlighting the significant role of BVOC in summer SOA formation in China.

Organic aerosol (OA) emitted from biomass burning (BB) impacts air quality and global radiation balance. However, the comprehensive characterization of OA remains poorly understood because of the complex evolutionary behavior of OA in atmospheric processes. In this work, smoke particles were generated from rice straw combustion. The effect of OH radicals photooxidation on size distribution, light absorption, and molecular compositions of smoke particles was systematically investigated. The results showed that the median diameters of smoke particles increased by a factor of approximately 1.2 after photooxidation. In the particle compositions, although both non-polar fractions (n-hexane-soluble organic carbon, HSOC) and polar fractions (water-soluble organic carbon, WSOC) underwent photobleaching after aging, the photobleaching properties of HSOC (1.87–2.19) was always higher than that of WSOC (1.52–1.33). Besides, the light-absorbing properties of HSOC were higher than that of WSOC, showing a factor of approximately 1.75 times for mass absorption efficiency at 365 nm (MAE₃₆₅). Consequently, the simple forcing efficiency (SFE) caused by absorption showed that HSOC has higher radiation effects than WSOC. After photooxidation, the concentration of 16 PAHs in HSOC fractions significantly decreased by 15.3%–72.5%. In WSOC fractions, the content of CHO, CHONS, and CHOS compounds decreased slightly, while the content of CHON compounds increased. Meantime, the variations in molecular properties supported the decrease in light absorption of WSOC fractions. These results reveal the aging behavior of smoke particles, then stress the importance of non-polar organic fractions in particles, providing new insights into understanding the atmospheric pollution caused by BB smoke particles.

Carbonaceous aerosols pose significant climatic impact, however, their sources and respective contribution to light absorption vary and remain poorly understood. In this work, filter-based PM₂.₅ samples were collected in winter of 2021 at three urban sites in Yibin, a fast-growing city in the south of Sichuan Basin, China. The composition characteristics of PM₂.₅, light absorption and source of carbonaceous aerosol were analyzed. The city-wide average concentration of PM₂.₅ was 87.4 ± 31.0 μg/m³ in winter. Carbonaceous aerosol was the most abundant species, accounting for 42.5% of the total PM₂.₅. Source apportionment results showed that vehicular emission was the main source of PM₂.₅ during winter, contributing 34.6% to PM₂.₅. The light absorption of black carbon (BC) and brown carbon (BrC) were derived from a simplified two-component model. We apportioned the light absorption of carbonaceous aerosols to BC and BrC using the Least Squares Linear Regression with optimal angstrom absorption exponent of BC (AAEBC). The average absorption of BC and BrC at 405 nm were 51.6 ± 21.5 Mm⁻¹ and 17.7 ± 8.0 Mm⁻¹, respectively, with mean AAEBC = 0.82 ± 0.02. The contribution of BrC to the absorption of carbonaceous reached 26.1% at 405 nm. Based on the PM₂.₅ source apportionment and the mass absorption cross-section (MAC) value of BrC at 405 nm, vehicle emission was found to be the dominant source of BrC in winter, contributing up to 56.4%. Therefore, vehicle emissions mitigation should be the primary and an effective way to improve atmospheric visibility in this fast-developing city.

Lipids are important biogenic markers to indicate the sources and chemical process of aerosol particles in the atmosphere. To better understand the influences of biogenic and anthropogenic sources on forest aerosols, total suspended particles (TSP) were collected at Mt. Changbai, Shennongjia, and Xishuangbanna that are located at different climatic zones in northeastern, central and southwestern China. n-Alkanes, fatty acids and n-alcohols were detected in the forest aerosols based on gas chromatography-mass spectrometry. The total concentrations of aliphatic compounds ranged from 15.3 ng m⁻³ to 566 ng m⁻³, and fatty acids were the most abundant (44–95%) followed by n-alkanes and n-alcohols. Low molecular weight- (LFAs) and unsaturated fatty acids (UnFAs) showed diurnal variation with higher concentrations during the nighttime in summer, indicating the potential impact from microbial activities on forest aerosols. The differences of oleic acid (C₁₈:₁) and linoleic acid (C₁₈:₂) concentrations between daytime and nighttime increased at lower latitude, indicating more intense photochemical degradation occurred at lower latitude regions. High levels of n-alkanes during daytime in summer with higher values of carbon preference indexes, combining the strong odd carbon number predominance with a maximum at C₂₇ or C₂₉, implied the high contributions of biogenic sources, e.g., higher plant waxes. In contrast, higher concentrations of low molecular weight n-alkanes were detected in winter forest aerosols. Levoglucosan showed a positive correlation (R² > 0.57) with high- and low molecular weight aliphatic compounds in Mt. Changbai, but such a correlation was not observed in Shennongjia and Xishuangbanna. These results suggest the significant influence of biomass burning in Mt. Changbai, and fossil fuel combustion might be another important anthropogenic source of forest aerosols. This study adds useful information to the current understanding of forest organic aerosols at different geographical locations in China.

Rapid economic growth, industrialization, and urbanization have caused frequent air pollution events in East Asia over the last few decades. Recently, aerosol data from geostationary satellite sensors have been used to monitor ground-level particulate matter (PM) concentrations hourly. However, many studies have focused on using historical datasets to develop PM estimation models, often decreasing their predictability for unseen data in new days. To mitigate this problem, this study proposes a novel real-time learning (RTL) approach to estimate PM with aerodynamic diameters of <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) using hourly aerosol data from the Geostationary Ocean Color Imager (GOCI) and numerical model outputs for daytime conditions over Northeast Asia. Three schemes with different weighting strategies were evaluated using 10-fold cross-validation (CV). The RTL models, which considered both concentration and time as weighting factors (i.e., Scheme 3) yielded consistent improvement for 10-fold CV performance on both hourly and monthly scales. The real-time calibration results for PM₁₀ and PM₂.₅ were R² = 0.97 and 0.96, and relative root mean square error (rRMSE) = 12.1% and 12.0%, respectively, and the 10-fold CV results for PM₁₀ and PM₂.₅ were R² = 0.73 and 0.69 and rRMSE = 41.8% and 39.6%, respectively. These results were superior to results from the offline models in previous studies, which were based on historical data on an hourly scale. Moreover, we estimated PM concentrations in the ocean without using land-based variables, and clearly demonstrated the PM transport over time. Because the proposed models are based on the RTL approach, the density of in-situ monitoring sites could be a major uncertainty factor. This study identified that a high error occurred in low-density areas, whereas a low error occurred in high-density areas. The proposed approach can be operated to monitor ground-level PM concentrations in real-time with uncertainty analysis to ensure optimal results.