To elucidate the molecular composition and sources of organic aerosols in Central Asia, carbonaceous compounds, major ions, and 15 organic molecular tracers of total suspended particulates (TSP) were analyzed from September 2018 to August 2019 in Dushanbe, Tajikistan. Extremely high TSP concentrations (annual mean ± std: 211 ± 131 μg m⁻³) were observed, particularly during summer (seasonal mean ± std: 333 ± 183 μg m⁻³). Organic carbon (OC: 11.9 ± 7.0 μg m⁻³) and elemental carbon (EC: 5.1 ± 2.2 μg m⁻³) exhibited distinct seasonal variations from TSP, with the highest values occurring in winter. A high concentration of Ca²⁺ was observed (11.9 ± 9.2 μg m⁻³), accounting for 50.8% of the total ions and reflecting the considerable influence of dust on aerosols. Among the measured organic molecular tracers, levoglucosan was the predominant compound (632 ± 770 ng m⁻³), and its concentration correlated significantly with OC and EC during the study period. These findings highlight biomass burning (BB) as an important contributor to the particulate air pollution in Dushanbe. High ratios of levoglucosan to mannosan, and syringic acid to vanillic acid suggest that mixed hardwood and herbaceous plants were the main burning materials in the area, with softwood being a minor one. According to the diagnostic tracer ratio, OC derived from BB constituted a large fraction of the primary OC (POC) in ambient aerosols, accounting for an annual mean of nearly 30% and reaching 63% in winter. The annual contribution of fungal spores to POC was 10%, with a maximum of 16% in spring. Measurements of plant debris, accounting for 3% of POC, divulged that these have the same variation as fungal spores.

Air pollution has become a major issue in China, especially for traffic-related pollutants such as nitrogen dioxide (NO₂). Current studies in China at the national scale were less focused on NO₂ exposure and consequent health effects than fine particulate exposure, mainly due to a lack of high-quality exposure models for accurate NO₂ predictions over a long period. We developed an advanced modeling framework that incorporated multisource, high-quality predictor data (e.g., satellite observations [Ozone Monitoring Instrument NO₂, TROPOspheric Monitoring Instrument NO₂, and Multi-Angle Implementation of Atmospheric Correction aerosol optical depth], chemical transport model simulations, high-resolution geographical variables) and three independent machine learning algorithms into an ensemble model. The model contains three stages: (1) filling missing satellite data; (2) building an ensemble model and predicting daily NO₂ concentrations from 2013 to 2019 across China at 1×1 km² resolution; (3) downscaling the predictions to finer resolution (100 m) at the urban scale. Our model achieves a high performance in terms of cross-validation to assess the agreement of the overall (R² = 0.72) and the spatial (R² = 0.85) variations of the NO₂ predictions over the observations. The model performance remains moderately good when the predictions are extrapolated to the previous years without any monitoring data (CV R² > 0.68) or regions far away from monitors (CV R² > 0.63). We identified a clear decreasing trend of NO₂ exposure from 2013 to 2019 across the country with the largest reduction in suburban and rural areas. Our downscaled model further improved the prediction ability by 4%–14% in some megacities and captured substantial NO₂ variations within 1-km grids in the urban areas, especially near major roads. Our model provides flexibility at both temporal and spatial scales and can be applied to exposure assessment and epidemiological studies with various study domains (e.g., national or citywide) and settings (e.g., long-term and short-term).

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.

PM₂.₅ (particulate matter having aerodynamic diameter ≤2.5 μm) samples were collected during wintertime from two polluted urban sites (Allahabad and Kanpur) in the central Indo-Gangetic Plain (IGP) to comprehend the sources and atmospheric transformations of light-absorbing water-soluble organic aerosol (WSOA). The aqueous extract of each filter was atomized and analyzed in a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). Water-soluble organic carbon (WSOC) and WSOA concentrations at Kanpur were ∼1.2 and ∼1.5 times higher than that at Allahabad. The fractions of WSOC and secondary organic carbon (SOC) to total organic carbon (OC) were also significantly higher ∼53% and 38%, respectively at Kanpur compared to Allahabad. This indicates a higher abundance of oxidized WSOA at Kanpur. The absorption coefficient (bₐbₛ₋₃₆₅) of light-absorbing WSOA measured at 365 nm was 46.5 ± 15.5 Mm⁻¹ and 73.2 ± 21.6 Mm⁻¹ in Allahabad and Kanpur, respectively, indicating the dominance of more light-absorbing fractions in WSOC at Kanpur. The absorption properties such as mass absorption efficiency (MAE₃₆₅) and imaginary component of refractive index (kₐbₛ₋₃₆₅) at 365 nm at Kanpur were also comparatively higher than Allahabad. The absorption forcing efficiency (Abs SFE; indicates warming effect) of WSOA at Kanpur was ∼1.4 times higher than Allahabad. Enhancement in light absorption capacity was observed with the increase in f44/f43 (fraction of m/z 44 (f44) to 43 (f43) in organic mass spectra) and O/C (oxygen to carbon) ratio of WSOA at Kanpur while no such trend was observed for the Allahabad site. Moreover, the correlation between carbon fractions and light absorption properties suggested the influence of low-volatile organic compounds (OC3 + OC4 fraction obtained from thermal/optical carbon analyzer) in increasing the light absorption capacity of WSOA in Kanpur.

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.

Nitrous acid (HONO), an essential precursor of hydroxyl radicals (OH) in the troposphere, plays an integral role in atmospheric photochemistry. However, potential HONO sources remain unclear, particularly in rural areas, where long-term (including seasonal) measurements are scarce. HONO and related parameters were measured at a rural site in the North China Plain (NCP) during the winter of 2017 and summer and autumn of 2020. The mean HONO level was higher in winter (1.79 ± 1.44 ppbv) than in summer (0.67 ± 0.50 ppbv) and autumn (0.83 ± 0.62 ppbv). Source analysis revealed that the heterogeneous conversion (including photo-enhanced conversion) of NO₂ on the ground surface dominated the daytime HONO production in the three seasons (43.1% in winter, 54.3% in summer, and 62.0% in autumn), and the homogeneous reaction of NO and OH contributed 37.8, 12.2, and 28.4% of the daytime HONO production during winter, summer, and autumn, respectively. In addition, the total contributions of other sources (direct vehicle emissions, particulate nitrate photolysis, NO₂ uptake and its photo-enhanced reaction on the aerosol surface) to daytime HONO production were less than 5% in summer and autumn and 12.0% in winter. Unlike winter and autumn, an additional HONO source was found in summer (0.45 ± 0.21 ppbv h⁻¹, 31.4% to the daytime HONO formation), which might be attributed to the HONO emission from the fertilized field. Among the primary radical sources (photolysis of HONO, O₃, and formaldehyde), HONO photolysis was dominant, with contributions of 82.6, 49.3, and 63.2% in winter, summer, and autumn, respectively. Our findings may aid in understanding HONO formation in different seasons in rural areas and may highlight the impact of HONO on atmospheric oxidation capacity.