Atmospheric bacteria and fungi are key components of urban bioaerosols, and their community structures are closely related to urban air quality, bioaerosol concentration, and environmental driving factors. However, the temporal dynamics and environmental drivers of bacterial and fungal community structures remain poorly characterized in megacities such as Shanghai, China. From November 2024 to November 2025, we conducted a year-long, cross-seasonal bioaerosol sampling and high-throughput DNA sequencing campaign to investigate the seasonal and diel variations, environmental covariation, and meteorological responses of atmospheric bacteria and fungi in Shanghai. The results show that seasonal transitions cannot significantly alter the α-diversity of bacterial or fungal communities, but significantly shift their community compositions, exhibiting a stronger differentiation for fungi than bacteria (PERMANOVA R2 = 0.133 vs. 0.054, p = 0.001). At the diel scale, bacterial communities exhibit weak diurnal variation, whereas fungal communities display significantly higher nocturnal Chao1 richness and Shannon diversity, along with distinct compositional separation. Cladosporium and Alternaria are enriched during the day, while saprotrophic basidiomycetes such as Irpex and Trametes are more abundant at night. Fungal composition covaries most strongly with meteorological gradients governed by boundary layer height, clear-sky surface downward solar radiation, temperature, relative humidity, atmospheric pressure and visibility, whereas bacterial–environment associations are weaker. The Relative Exposure-Relevant Proportion (RERP), dominated by Cladosporium and Alternaria, is higher during daytime and negatively associated with relative humidity (β = −0.23, q = 0.001). During a strong cold-air event, bacterial communities shifted rapidly following immediate air mass replacement and high wind shear before stabilizing, whereas fungal communities underwent a more gradual and cumulative turnover. The RERP also elevated during this event, accompanied by a greater contribution from Talaromyces. These findings reveal contrasting dynamics between airborne bacteria and fungi under both background and transient synoptic disturbances, providing crucial observational insights for bioaerosol modeling and risk prediction in urban environments.

This study employs the GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) to simultaneously retrieve aerosol optical properties and chemical components from ground-based sun photometer observations in Tianjin during the period 2014-2024. Component-derived aerosol optical depth (AOD) showed very good agreement with ground-based sun photometer measurements (R2 approximate to 1; RMSE <= 0.01), confirming the reliability of the inversion algorithm. Correlation analysis between aerosol components and optical properties reveal that fine-mode aerosols are the primary drivers of AOD variability. Black carbon (BC) dominates aerosol absorption across all wavelengths, while brown carbon (BrC) and absorbing dust (CAI) exhibit significant absorption only at shorter wavelengths. Aerosol components present distinct seasonal patterns: BC peaks in winter; CAI and scattering dust (CNAI) increase obviously in spring, consistent with frequent dust transport; fine-mode soluble salts (FNAS) and water content (FAWC) rise in summer due to enhanced photochemical activity and high humidity, whereas their coarse-mode counterparts decline due to wet scavenging. Fine-mode aerosol components in Tianjin have decreased significantly, which is driven by policy interventions. In contrast, coarse-mode components show greater variability, likely regulated primarily by natural processes. Furthermore, columnar BC concentrations and dust concentrations show strong temporal coherence with near-surface PM2.5 and PM10, respectively, further validating the applicability of the GRASP/Component approach for long-term monitoring of regional aerosol loading and chemical components.

Abstract The mixing state of light‐absorbing particles critically influences aerosol optical properties, thereby affecting global radiative forcing. This study focuses on non‐volatile particulate matter (NV‐PM)—the fraction remaining after thermal denudation at 300°C—has received limited attention. Using observations in Shanghai, we show that ambient aerosols exhibit a bimodal size distribution, with the larger mode strongly correlated with NV‐PM (R2 ∼ 0.83), suggesting that NV‐PM acts as seed particles. We propose an S/L‐mode mixing‐state classification that separates small and large diameter modes and apply a core–shell optical model using retrieved refractive indices for NV‐PM and coatings. Modeled absorption at 530 nm agrees with observations and reproduces the mean absorption enhancement (Eabs ∼ 2.80 vs. 3.28 observed). Our analysis attributes about one‐third of absorption to brown carbon. This work advances the understanding of aerosol mixing state and absorption mechanisms, supporting more accurate estimates of aerosol radiative forcing in climate models.

Carbon dioxide (CO2), the primary contributor to global warming, significantly impacts global climate change. Remote sensing is an effective approach for monitoring atmospheric CO2 concentrations. However, the commonly used satellite's full-physics Optimal Estimation (OE) method is time-consuming and requires advanced equipment. Additionally, traditional deep learning algorithms for satellite CO2 retrieval suffer from limitations in accuracy and an inability to extrapolate effectively to unseen high values, caused by the gradually increasing concentrations over time. Balancing both efficiency and extrapolation capabilities is a critical task, especially for the next generation of large-swath carbon satellite with a significant increase in data volumes, such as Tansat-2. In this study, we first employed the OCO-2 data from 2020 to construct a Transformer-based structure and integrate prior constraint and hierarchical features injection mechanism for high precision CO2 retrieval, and achieved an outstanding result with the R, RMSE, and MAPE of 0.939, 0.746 ppm, and 0.132 %. Based on the model, we evaluated its extrapolation capability using OCO-2 data from 2021 to 2024, demonstrating a robust performance and strong generalization ability (R = 0.938-0.951, RMSE = 1.083-1.310 ppm, MAPE = 0.208-0.256 %). Finally, we assessed the transferability of this model using simulated Tansat-2 data (August 18, 2020), achieving metrics of R = 0.657, RMSE = 1.299 ppm, and MAPE = 0.239 %, indicating the model's effective transfer capabilities. The proposed model has the potential to provide a feasible solution for rapidly retrieving high-precision CO2, especially for the next generation of large-swath carbon satellites.

Aerosol optical depth (AOD) is a key parameter for evaluating climate change and air quality, yet ground-based AOD observations in China remain limited, and satellite data often suffer from acquisition gaps due to cloud cover. Surface visibility (VIS) offers a promising alternative for AOD retrieval, but the relationship between VIS and AOD is complex and shaped by multiple factors such as meteorological conditions, the vertical distribution of aerosols, topography, and population density. This study systematically explored the influence of these factors on the hourly VIS-AOD relationship, using over similar to 2300 automatic VIS measurements and Himawari-8 satellite-retrieved AOD data collected across China from 2016 to 2021. The results reveal significant spatiotemporal variations in the VIS-AOD relationship, with stronger diurnal aerosol fluctuations in eastern China compared to the west, and a consistent inverse correlation between VIS and AOD. The correlation peaks in the late afternoon and reaches a seasonal maximum during winter. These relationships are influenced not only by regional meteorological thresholds but also by constraints from aerosol vertical distribution patterns and geographical conditions. Crucially, adjusting the AOD by incorporating the planetary boundary layer height markedly improves its correlation with VIS, underscoring the importance of daily planetary boundary layer dynamics. These findings offer valuable insights for refining hourly AOD retrieval methods from VIS, thereby enhancing the understanding of aerosol behavior across China.

Convective weather events accompanied by multiple tornadoes are rare. However, on 29 August 2019, a typhoon-induced squall line produced three tornadoes on Hainan Island. This rare event provides a valuable opportunity to investigate the microphysical characteristics and cloud-to-ground (CG) lightning activity during tornado periods. This research employed data from S-band dual-polarimetric Doppler weather radar and a VLF/LF three-dimensional lightning location system. Results showed that during the first tornado (developing stage), hydrometeor particles were sparse and dispersed, resulting in minimal CG lightning activity. In contrast, during the second tornado (mature stage), hydrometeor particles were abundant and concentrated, leading to the most active CG lightning. During the third tornado (dissipating stage), hydrometeor particles began to dissipate, though CG lightning activity remained higher than during the first tornado. The characteristics of hydrometeor particles and CG lightning in tornadoes were consistent with the concurrent developmental phase of the squall line. The rapid rise in the top altitude of the 40 dBZ echoes was a significant indicator of tornado formation. Furthermore, dry graupel, wet graupel, and dry snow particles exhibited strong correlations with CG lightning activity. These findings enhance our understanding of the microphysical and electrification mechanisms associated with tornadoes and provide valuable insights for improving tornado prediction.

Vertical observations were used to explore the explosive growth (EG) of PM2.5 in Shanghai in 2018 to investigate the rapid evolutionary mechanisms and health effects of a highly severe haze episode. The EG is defined as the net increase in PM2.5 concentration by more than 100 µg/m3 within 6 or 9 h. The average PM2.5 concentration during EG was 118.1 µg/m3, dominated by NO3-, NH4+, SO42- (SNA), and organic matter (OM), with a proportion of 31.1 %, 15.1 %, 14.8 %, and 18.8 %, respectively. In addition to being affected by chemical reactions, regional transport was the main influencing factor for OM, but local emissions were the main factor for SNA. Vertical observation results showed that EG events were influenced commonly by local emission, regional transport, and chemical reactions with a different proportion. Moreover, the heterogeneous reaction could possibly cause more severe pollution. The daily average nonaccidental mortality for EG [13.9 (95 % CI: 5.5, 25.0)] was about 4.0 times higher than that in Clean Days (CDs) [3.5 (1.4, 6.3)], and EG episodes caused a more severe effect on cardiovascular disease compared with respiratory disease. Moreover, local emissions and secondary gas-phase oxidation exhibited crucial factors for human health during EG, but regional transport during CDs. To sum up, ground-level observation could not fully explain the process of atmospheric pollution, but the vertical measurements help to understand the regional transport influence on the EG process. In the future, it is recommended that vertical observation should play a vital role in investigating regional heavy pollution episodes.

The role of meteorological factors in regulating gross primary productivity (GPP) is well‐recognized. However, the attribution of GPP trends predominantly focus on interannual timescales, potentially obscuring the differences in dynamic seasonal responses of GPP to meteorological variations. Here, a machine learning model to invert GPP in China's drylands using meteorological data including temperature, solar radiation, and precipitation from 2001 to 2020 was developed. The model was subsequently used to quantify the contributions of these meteorological factors to GPP trends and their regional variations. Results showed that declining solar radiation caused an average GPP decrease of 0.13 gC m −2 yr −1 , whereas increased precipitation contributed to an average GPP increase of 0.11 gC m −2 yr −1 , partially offsetting the radiation‐induced loss. Temperature effects were relatively minor due to seasonal compensations, with spring and autumn warming enhancing photosynthesis but summer warming suppressing vegetation growth. The combined effects of these three meteorological factors led to a slight decline of approximately 0.03 gC m −2 yr −1 in annual mean GPP across China's drylands. Spatially, GPP variations reflected the dominance of temperature in the Tibetan Plateau, precipitation in North China, and solar radiation in Northeast China. The Tibetan Plateau's low baseline temperature allowed warming to enhance GPP throughout the year. In Northeast China, the significant decline in solar radiation and the radiation sensitivity of forest canopies explained the observed GPP reduction. In North China, pronounced wetting trends established precipitation as the dominant controlling factor. These findings enhance our understanding of climate‐GPP relationships in dryland ecosystems.

The vertical distributions and optical properties of aerosols over Shanghai were analyzed using data from ground-based observation, space remote sensing and trajectories. Measurements of spectral aerosol optical depth (AOD) were carried out at Shanghai using a hand-held multi-band sun photometer MICROTOPS II from November 2009 to October 2010. AODs were almost in low level during the entire experiment, especially in the period of the World Exhibition/Exposition (EXPO) 2010. And, the daily-averaged AODs showed a clear pattern of seasonal variation, with maximum 0.69 in November and minimum 0.24 in August. Angstrom exponents were commonly exceeding 1.30, indicating that fine particles mainly contributed to aerosol loading except springtime. Based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO/CALIOP) retrieval and air back-trajectory modeling, the vertical distribution of aerosols were examined and classified into near-surface, mixed and multilayer transport types. The results denote the effects of aerosols from local sources or/and transported from remote sources on aerosol loadings. Comparison of AODs derived from CALIOP with those from ground observation revealed a reliable agreement with a correlative coefficient of 0.59. The variety of the aerosol types of Shanghai probably is the main contributor of the uncertainties.

The chemical element composition of dust particles was characterized by the ground-based samples collected at Beijing in the spring of 2004. Most of mineral and pollutant element concentrations in particles were elevated in dusty days, about 2-4 times higher than the levels in non-dusty days. Each of Si, Ca, Fe and Al accounted for over 10% of the sums of total 20 elements in mass, for example, Si was in 44.3%, 38.7% for dusty and non-dusty cases, respectively. Si, Fe, Ni or Ti can be used as an indicator of dust outflow, and Cu can be viewed as an evidence of dust particles mixing with anthropogenic contaminants as a result of coagulation processes. Mineral and pollutant elements showed a bimodal distribution in the mass particle-size distributions in both dusty and non-dusty days, but their peak concentrations fell in different size stages. Zn, Cl and Cu were mostly enriched in fine particles, Pb was enriched in intermediate sized particles, but most mineral elements, S and part of Cu were enriched in coarse particles. Mineral elements were dominated by crustal material, and pollutant elements were from non-crustal material including local and remote sources. Among the crustal material, part of Ca was originated from local construction activities. High concentration of Cu was related to the of rapidly increasing vehicles in Beijing, and the replacing of coal with diesel oil for heating fuel. Most of the mineral dust particles sampled at Beijing were originated from the Mongolian sandy soil and the Chinese loess in the spring of 2004. Using Mg/Al ratio element tracer technique method, the aerosol from outside Beijing accounted for 66.3% and 88.6% to the total mineral aerosol during dust event on 10-11 March and 28-30 March 2004, respectively.

Atmospheric electric field (EF) and air ions were measured in Shanghai from December 2014 to December 2015 to examine the influence of particulate pollutants. Fair-weather EF exhibits a diurnal variation of multi-modal oscillations in spring, summer, and autumn. Linear correlation analyses show that the local meteorological conditions of relative humidity, temperature, pressure and wind affect atmospheric electric field, with wind direction exhibiting the highest correlation coefficient. Atmospheric EF is significantly higher in the west compared with that in the east, as the air mass from inland areas carries more polluted aerosols. Air ion concentrations are generally higher in the daytime than at night and correlate with meteorological factors. Atmospheric EF undergoes a substantial fluctuation in polluted periods, but remains flat under clean conditions. Overall, in areas with pollution, the atmospheric EF gradually increases with increased pollution or increased particle loading (e.g., PM2.5), a useful indicator of air pollution. The concentration of PM2.5 is positively correlated with the atmospheric electric field under polluted conditions, because as the concentration of aerosol particles declines, the concentrations of small ions and the atmospheric conductivity decrease accordingly, thus causing an increase in the electric field. Overall, aerosol particles, air ions, and their interactions in the presence of various meteorological parameters can have local effects on the atmospheric electric field.

ABSTRACTAerosol-cloud-precipitation interactions have attracted much more attention for decades, but there still remain many uncertainties in assessing global climate. Long-term ground-based measurements of aerosol, cloud and precipitation in Shanghai were used to examine their inter-annual variations and possible relationships. During 1990–2010, the yearly-averaged total cloud cover (TCC) and low cloud cover (LCC) decrease on average by 0.58% and 2.49% per year. LCC correlates to surface aerosols (e.g., PM10), with a correlation coefficient (R) of 0.67. Aerosol optical depth (AOD), as an indicator of columnar aerosol loading, shows a non-significant correlation with cloud cover. The yearly-aggregated heavy and extreme rain days and their rainfall amount increase gradually. The moderate rain day enhances but its annual rainfall amount declines year by year, while the light rain exhibits an opposite pattern to the moderate rain. These results imply that local aerosols maybe exert somewhat enforcing on low cloud and light rain through possible entrainment or updraft that can bring up surface particles into free troposphere, whereas its influence to total cloud and precipitation is negligible at a small scale. Future studies are needed to ensure whether local aerosols to directly affect low cloud, and to explore how surface aerosols to enter into higher atmospheric layers and impact cloud and precipitation at larger scales.

Atmospheric carbon dioxide (CO2) is the primary anthropogenic driver of climate change, accounting for more than half of the total effective radiative forcing (ERF). Active remote-sensing technique using differential absorption light detection and ranging (LiDAR) (DIAL) is recognized as the most promising remote sensing means for atmospheric CO2 measurements. The aerosol and carbon detection LiDAR (ACDL) instrument onboard the DaQi-1 (DQ-1) is dedicated to quantifying the global spatial distribution of atmospheric CO2. To meet the requirement of accuracy and precision, a reasonable averaging scheme for ACDL measurements is needed to minimize the effect of random noise of observations on CO2 retrievals. In this study, three averaging schemes were conducted in the retrieval process: averaging of CO2 columns (AVX), averaging of differential absorption optical depth (AVD), and averaging of signals (AVS). The performances were compared at three representative sites. The experiments were first carried out on simulations. The results show that the optimal size of the averaging window is 50 km, corresponding to an averaging of measurements over 150 pulse pairs. In addition, the AVX and AVD schemes are less affected by altitude variations and can be applied to surfaces with moderate and severe topographic variation, such as hills and mountains, whereas the AVS method is more suitable for surfaces with slight topographic variation, such as oceans, plains, and terraces. Furthermore, the ACDL observations were also retrieved by applying three averaging schemes and validated against ground-based Total Carbon Column Observing Network (TCCON) measurements at the Xianghe station. The AVS scheme exhibits better performance than the AVX and AVD methods with the lowest biases of less than 0.5 ppm, which is consistent with the simulation results.

Atmospheric pollution has been found to modify the hygroscopicity of particles and the ability of aerosols to become cloud condensation nuclei (CCN). Aerosols and the bulk CCN were measured in urban Guangzhou during pollution periods in January 2016, and the particle liquid water content (PLWC) and aerosol acidity (Aero-pH) were calculated to examine their possible effects on aerosols' CCN activation. The results demonstrate that the PLWC and Aero-pH likely play key roles in enhancing aerosol activation during the early stages of pollution episodes. The analysis of the calculated and the observed data shows that CCN, PLWC, Aero-pH and water-soluble inorganic matter (WSIM) are closely linked to each other, particularly at night, and Aero-pH and PLWC act as pre-occurring indicators of activated aerosols and aerosol activity, respectively, during the rapid onset of pollution. In theory, the feedback between chemical reactions, aerosol acidity and particle water content accounts for the changes in aerosol activation accompanying particle accumulation and aging. Our research provides insights into the swift formation of particle pollution characterized by secondary aerosols and suggests a possible approach to tracking or characterizing its effects on the activation of aerosols into CCN without requiring CCN or aerosol number measurements.

AbstractUsing 22‐year ground observations on meteorological variables, we conducted a statistical analysis to reveal fog characteristics at Shanghai Pudong International Airport (SPIA). Fog events were classified by fog types using an objective method. Two types of advection fogs are dominant in fog events at SPIA, followed by radiation fogs. Different fogs have evident annual and monthly variations in frequency. Advection fog mostly appear from February to April, while radiation fog is mainly between November and February. Six synoptic patterns associated with fogs were determine by a self‐organizing maps cluster method, two of which, namely ‘west of marine high pressure’ and ‘inverted trough’, are most favourable for the formation of advection fogs, whereas ‘bottom of weak cold high‐pressure’ is favourable for radiation fogs. The frequency of advection fog occurrence exhibits temporal fluctuations with distinct peaks occurring 2–3 h after sunset, around midnight, and 1–2 h before sunrise, while almost all radiation fog occur in the second half of the night, and favourable conditions for fog onset become more effective with the length of the night. Radiation fog exhibits a longer duration than advection fog and tends to result in lower visibility. The prevalent wind direction for the formation of advection fog is generally from the east to the southeast, whereas radiation fog is typically associated with westerly winds. The temperature and air pressure during the formation of both advection and radiation fogs follow a normal distribution in most seasons. More fog characteristics were categorized by fog types and seasons.

Typhoons are one of the most important weather systems that can cause severe ozone (O3) pollution in eastern China. While the effects of individual typhoons on O3 concentrations have been extensively studied, the effects of consecutive northward typhoons and the underlying mechanisms remain unclear, partly due to the complex processes involved. Here, Typhoons Maysak and Haishen, two consecutive northward typhoons in 2020, are selected to investigate their impact on the O3 pollution in eastern China. The results show that consecutive northward typhoons not only produced and maintained meteorological conditions conducive to O3 generation (e.g., elevated temperatures and intensified solar radiation), but also facilitated local accumulation and cross-regional transport of O3. These factors jointly led to a 30% increase in O3 concentration in eastern China with a prolonged period of O3 pollution. Our work underscores the significance of complex meteorological conditions in O3 pollution occurrences during extreme weather events, advancing our understanding of how consecutive northward typhoons affect air quality.

Aerosol number size distributions between 10 nm and 10 µm were measured from October 2008 to February 2009 in Shanghai, China. The average particle number, surface and volume concentrations were 1.3 × 104 1/cm3, 6.4 × 102 µm2/cm3 and 64 µm3/cm3, respectively. Aitken particles dominated the total number of particles, and accumulated particles were the greatest contributor to particle surface area. Particle number size distributions could be characterized by multi-lognormal functions. The average number size distributions of aerosols revealed a clear diurnal pattern of two peaks within 30–60 nm corresponding to the morning and afternoon traffic rush hours. All size particles had two peaks in mean number concentrations during the rush hours, and 10–20 nm and 20–50 nm particles had one additional peak in late morning. The new particle formation events were found on four days out of 73. The apparent formation rates varied from 0.2 to 0.5 cm3/s, and the growth rates of newly formed particles were 3.3–5.5 nm/h. Overall, the new particle formation events had a significant impact on particle size spectra in the nucleation and Atiken modes, but insignificant effects on particle surface and volume concentrations.

The potential impacts of agricultural fires (agri-fires) on regional air quality over China were examined using active fire products derived from satellite remote sensing and air mass trajectory modeling from 2009 to 2010. Agri-fires were found in most administrative areas. More than 80

The effects of aerosol on clouds are examined over the Yangtze River Delta (YRD) using 3 months of satellite data from the polluted wintertime from December 2013 to February 2014. The relationships between aerosol properties, and cloud micro-and macro-physical parameters are analyzed in detail to clarify the differences in cloud development under various aerosol and meteorological conditions. Complex relationships between the aerosol optical depth (AOD), and the cloud droplet radius (CDR), liquid water path (LWP) and cloud optical thickness (COT) exist in four regions of interest (ROIs). High aerosol loading does not obviously affect LWPs and COTs; in fact, aerosols inhibit development of low-and medium-low clouds over coastal areas-an effect that is more pronounced in low clouds (< 5 km) than high ones. Low aerosol loading plays a positive role in promoting the COT of high-and low-clouds over areas dominated by maritime aerosol. Aerosol loading exerts a significant influence on COTs, LWPs and CDRs in valley and coal industry districts except during high-cloud conditions. The ranges of COTs, LWPs and CDRs in dry-polluted areas are lower than in other places, which suggests that dust aerosol has little effect on cloud properties. Synoptic conditions also strongly impact cloud distribution, in particular, an unstable synoptic condition leads to cloud development on a larger horizontal and vertical scale. Ground pollution enhances the amount of low-level cloud cover even under stable conditions. Aerosol plays an important role in wintertime cloud evolution in the low layers of the troposphere (< 5 km) when the atmosphere is stable.