Search Results (316)

Accurate, large-scale maritime traffic monitoring supports marine spatial planning, fishery regulation, and ecological conservation. Medium-resolution optical satellite imagery, such as Sentinel-2A/B, provides a cost-effective complement to incomplete Automatic Identification System (AIS) data. Detecting small vessels in coastal waters remains challenging due to target size, complex backgrounds, and class imbalance. This study presents a robust end-to-end framework for small vessel detection and traffic density mapping using optical remote sensing imagery. A high-quality dataset of 8123 manually annotated vessels was constructed from 14 Sentinel-2 scenes across three marine environments in Fujian, China. An overlapping sliding-window cropping strategy, area truncation filtering, and negative sample preservation improved training efficiency and balance. Experiments compared top-of-atmosphere reflectance with surface reflectance (L2R) from the ACOLITE atmospheric correction (AC) algorithm, showing L2R mitigates aerosol scattering and nearly doubles vessel edge sharpness. YOLO-based detectors were evaluated, with YOLO26m achieving the best localization: F1-score 0.8461, mAP50 0.8979, mAP50–95 0.5536. Using this framework, 1 × 1 km traffic heatmaps for the Fujian coast in 2025 captured seasonal variations influenced by logistics and fishery moratoriums. Results demonstrate that integrating atmospherically corrected imagery with optimized deep learning strategies enhances sub-pixel ship detection, offering a scalable solution for intelligent maritime governance. Full article

Fluorescent aerosol particles (FAPs) are widely used as a real-time proxy for primary biological aerosol particles; however, their seasonal characteristics and size-resolved distributions in office environments remain poorly understood. In this study, FAPs were measured in ten office spaces located in four distinct regions of Japan during summer and winter using a real-time Bioaerosol Sensor. Indoor and outdoor FAP concentrations, indoor/outdoor ratios, and the size-resolved FAP fraction were evaluated. Indoor FAP concentrations were generally below 100 particles per liter (p/L), although peak concentrations of 140 p/L in summer and 195 p/L in winter were observed. Significant seasonal differences were detected in most offices, with several buildings showing higher concentrations in winter. Many offices exhibited relative humidity levels below 40% during winter, suggesting that dry indoor conditions may have promoted particle resuspension and contributed to elevated FAP concentrations. Indoor–outdoor comparisons suggested contributions from both indoor sources and outdoor infiltration. The size-resolved FAP fraction increased markedly with particle size, with median indoor values reaching 40–74% for 2.0–5.0 μm particles and 96–100% for particles > 5.0 μm. These findings indicate that FAPs in office environments are strongly associated with coarse particles and exhibit substantial seasonal and building-dependent variability. Full article

As part of the ACTRIS research infrastructure, a six-month study (May–October 2024) was conducted at the CNR-IMAA Atmospheric Observatory (CIAO, Southern Italy) to characterize non-refractory submicron aerosol (NR-PM₁). Measurements were conducted in real time using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and highlighted the predominant presence of organic aerosol (OA), with values reaching 49.5 µg m⁻³. During the study period, nitrate and ammonium concentrations remained below 2 µg m⁻³ on average, while sulfate concentrations showed normal variation during the analysis period (maximum value of 11.70 µg m⁻³). The daily variability of concentrations was influenced by both boundary layer dynamics and local emission variations. The calculated charge and mass balances allowed us to study the good neutralization of PM₁ in the atmosphere. The composition of the organic aerosol was dominated by oxygenated species, with a small contribution from biomass combustion. Ultimately, these results provide an excellent starting point for understanding the aerosol chemical composition and seasonal variability at the site, ahead of future analyses and comparisons within the ACTRIS of which the observatory is part. Full article

This study explores the three-dimensional structure of dust aerosols over the Qaidam Basin using CALIPSO satellite observations from 2007 to 2022. The results show that polluted dust is the dominant aerosol type in this region. Dust activity peaks in spring, with its vertical extent reaching nearly 10 km. Dust Aerosol Optical Depth (DAOD) is relatively high in the northwest and central parts of the basin, with a spring peak of 0.25 and an autumn minimum of 0.12. DAOD has shown a notable decreasing trend over the past 16 years. In terms of vertical structure, dust aerosols are mainly concentrated below 4 km AGL, especially within the near-surface layer of 0–2 km, and their occurrence frequency declines as altitude increases. The dust layer thickness exhibits obvious seasonal variations, which are primarily controlled by changes in layer top height. The average thickness decreases from 1.53 km in spring to 0.61 km in winter, while the layer’s bottom height remains fairly stable. Analysis based on the LASSO-SHAP model indicates that potential evapotranspiration and friction velocity are the major factors affecting DAOD, highlighting the vital roles of surface dryness and near-surface dynamic forcing. Furthermore, investigation of typical dust events reveals distinct vertical stratification of dust transport. Low-level dust movement is restricted by basin terrain, whereas upper levels are governed by the westerlies. This study improves our understanding of the three-dimensional structure, seasonal evolution, and transport processes of dust aerosols in high-altitude arid basins. Full article

Aerosols emitted by biomass burning represent one of the largest sources of uncertainty in our current understanding of the Earth’s radiative balance. We investigate the climatic influence of biomass burning aerosols emitted from six key regions of biomass burning by using GEOS-Chem coupled with the rapid radiative transfer model. We evaluate our model using AERONET observation, with the model reproducing data with 87% observed spatial and seasonal variability with a low negative bias of 7%. The radiation sensitivity is generally highest for North Asia (NAS) and for North America (NCC); lowest for South America (SAM) and South and Southeast Asia (SSA); and moderate for Africa (AFR) and Oceania (OCE). These regional differences are related to the main burning types of the regions. When we consider the global radiation influence, AFR dominates the global picture due to the comparatively large biomass burned. We estimate the global mean radiation influence of biomass burning aerosol is −0.116 W m⁻². For monthly features, in summer, due to higher incident energy obtained in NAS and NCC, high negative radiation sensitivity of biomass burning, biomass burning aerosols, and biomass burning organic aerosol are shown in these regions. Meanwhile, the radiation sensitivity peak of black carbon for these two regions occurs earlier in late spring (NAS) or early summer (NCC), when large incident energy and large high reflectance snow cover coexist in these two high-latitude regions. A significant yearly difference in radiation influence, rather than radiation sensitivity, is found, with the relative difference between the maximum year and minimum year reaching 90% of the maximum radiation influence year. Specifically, two regions affected by El Niño (OCE and SSA) have the most significant yearly variation in all factors, with anomalies occurring in El Niño years. Full article

Aerosol optical depth (AOD) and Ångström exponent (AE) are critical parameters for characterizing atmospheric aerosols, playing a pivotal role in atmospheric environmental monitoring and climate change studies. This study addressed the imperative need for a systematic evaluation of mainstream reanalysis products by conducting a comprehensive multi-scale assessment of the CAMS and MERRA-2 datasets (2003–2023), encompassing data quality verification, spatiotemporal pattern analysis, and trend evolution investigation. The following key findings emerge: (1) Both AOD data exhibited the best performance observed in low–mid latitudes. CAMS AOD (AODC) showed a slightly better correlation, while MERRA-2 AOD (AODM) demonstrated superior robustness. Both AE data performed similarly, and MERRA-2 AE (AEM) was superior. Both AE data performed better in low latitudes and near Europe. (2) CAMS and MERRA-2 showed good performance in annual and seasonal variations, with significant fluctuations and biases in the annual cycle. Both models achieved the highest AE performance in summer. MERRA-2 AOD demonstrated better hourly performance during daytime. The hourly stability of AE was slightly worse than AOD, with notably degraded performance during midday hours. (3) The distribution and trends of AOD over land showed spatial consistency. The distribution of AEM was generally lower than AEC’s. After ensemble empirical mode decomposition (EEMD), all datasets showed monotonically decreasing trends except for AEM. This study provides valuable insights into the strengths and limitations for CAMS and MERRA-2 and suggests possible areas for improvement in future data assimilation and parameterization. Full article

This study focuses on the search and determination of organic pollutants in aerosol particles (PM_2.5) collected in Arkhangelsk, the largest urban agglomeration in the Arctic, during winter and summer periods. Thermal desorption gas chromatography coupled with high-resolution mass spectrometry was applied for non-targeted screening of atmospheric aerosols, enabling the detection of compounds at low concentrations ranging from 10 pg/m³ to several ng/m³. Representatives of various chemical classes were detected in samples from both seasons, including CHO compounds (with phthalates as the predominant subgroup), nitrogen-containing compounds (e.g., pyridines, quinolines, nicotine), phenols and monoaromatics, as well as polycyclic aromatic hydrocarbons and their oxygenated derivatives. In winter, PAHs and oxy-PAHs significantly predominated, likely due to increased combustion of fossil fuels and biomass for heating purposes. A total of approximately 300 compounds were identified via non-targeted screening, of which 32 were confirmed and quantified using authentic reference standards across six chemical classes. Seasonal variations in both the composition and concentration levels highlight the impact of local emission sources and atmospheric conditions on the organic aerosol profile in this arctic urban environment. Full article

Polar Stratospheric Clouds (PSC) have been observed by the lidar observatory at Concordia station since 2014. The Concordia lidar is one of a few primary lidar stations in Antarctica of the Network for the Detection of Atmospheric Composition Change (NDACC). The lidar system was deployed at McMurdo from 2004 to 2010 and has been upgraded before its installation at Concordia. Concordia station is one of the most favourable locations for the observation of polar stratospheric clouds, due to the limited cloud cover by tropospheric clouds and the ubiquitous presence of PSCs throughout the Antarctic winter. The PSCs observations have been synchronized with the overpasses of satellite borne lidars, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite from 2014 to June 2023, and the Atmospheric Lidar (ATLID) on the EarthCARE (Earth, Cloud, Aerosol and Radiation Explorer) mission since September 2024. A modified v2 algorithm, used for the detection and classification of PSCs as observed by CALIOP, has been used to determine detection limits and classification criteria. This facilitates comparison with CALIOP PSC profiles during quasi-coincident overpasses of the CALIPSO with respect to Concordia station. A local PSC climatology has been produced, with typically more than 150 profiles per PSC season. Considerable inter-annual variations have been observed, mostly depending on the local temperature. The data have been used to infer a decadal trend of PSC occurrences, although the large inter-annual variability renders such an approach difficult. The occurrences of the different PSC types show a strong correlation with the local temperature and depend on the formation processes and the formation temperatures of the different PSCs. Full article

Amidst rapid urbanization, fine particulate matter (PM_2.5) has emerged as a critical environmental challenge in China, posing substantial health risks due to its complex composition and diverse sources. This study provides a seasonally resolved analysis of PM_2.5 composition and multi-faceted toxicity in Hefei, a major Chinese manufacturing center. PM_2.5 samples collected across four seasons were chemically characterized for water-soluble ions, carbonaceous components, metals, and polycyclic aromatic hydrocarbons (PAHs) and derivatives. Their toxicological effects were evaluated through oxidative potential (OP), cytotoxicity, and reactive oxygen species (ROS) generation in the human bronchial epithelial cell line BEAS-2B. The results reveal significant seasonal variations in PM_2.5 concentration and composition. Winter exhibited the highest PM_2.5 levels (68.31 ± 17.12 μg/m³), with enrichment of secondary inorganic aerosols (SIAs), toxic metals (Pb, Cd, As), and high-molecular-weight PAHs. Spring showed elevated crustal elements (Al, Fe, Mn), while summer had the lowest pollutant concentrations. Toxicity assays reflected the following patterns: winter PM_2.5 demonstrated the highest OP (0.1423 ± 0.0368 nmol DTT/min/μg), strongest cytotoxicity (51.85% cell viability), and greatest ROS induction (2.28-fold increase). Statistical analyses identified distinct toxicity drivers: OP was associated with SIA (NO₃⁻, NH₄⁺) and redox-active metals (Cu, Zn); cytotoxicity correlated with toxic metals and PAHs; whereas ROS showed weaker compositional correlations. This integrated “composition–toxicity” assessment reveals that the elevated health risk in winter stems from a synergistic mix of secondary aerosols and combustion-derived toxicants, urging a shift toward component-specific, risk-based air quality management strategies. Full article

Although the organic fraction of PM_2.5 has been extensively studied, there is a considerable gap in understanding the organic fraction of coarse particles with diameters between 2.5 and 10 µm. We investigate the composition of coarse organic aerosol (OA) across rural, suburban, and urban areas of Switzerland. Using Aerosol Mass Spectrometer analyses of water-soluble OA extracted from collected filter samples (one entire year, 441 samples per size fraction), we identified two distinct classes of coarse OA. The first class, which constitutes 41–81% of coarse organic carbon (OC), is associated with primary biological organic carbon (PBOC). PBOC is characterized by specific marker ions (e.g., C₂H₅O₂⁺) and exhibits pronounced seasonal variation, with peak concentrations observed in the summer. This seasonal trend correlates with that of molecular markers such as arabitol and mannitol, as well as the fraction of biological particles determined by automated scanning electron microscopy coupled to energy dispersive X-ray spectroscopy of individual particles. The second class, contributing 7.9–17.8% to OC_coarse, is denoted as sulfur-containing organic carbon (SCOC) due to the presence of sulfur-containing ions such as CH₃SO₂⁺. Elevated concentrations of SCOC in urban environments near roadways suggest a strong influence from non-exhaust traffic emissions and resuspended dust. While the overall variation in coarse OC between rural and urban areas is approximately 10%, PBOC concentrations are 1.4 times higher in rural areas, whereas SCOC concentrations are 1.5 times higher in urban settings. Overall, our study shows that although OC_coarse concentrations in Switzerland are relatively consistent across site types, major water-soluble sources, particle properties and composition vary considerably geographically and seasonally. Full article

The Beijing–Tianjin–Hebei (BTH) region is a critical political and economic hub in China, which has long faced challenges related to atmospheric conditions. Traditional aerosol optical depth (AOD) monitoring methods suffer from issues of data discontinuity and gaps, limiting the ability for continuous long-term observation of aerosols. Aerosols have significant impacts on climate change and air quality, with AOD serving as a key indicator for characterizing atmospheric particulate concentration. Therefore, this study applied a machine learning model to improve all-day AOD estimation based on ground-level air quality and meteorological data, generating a long-term dataset spanning from 2018 to 2023. The results of the all-day AOD estimation method were evaluated through comparisons with Himawari-8, the Aerosol Robotic Network (AERONET), and the Copernicus Atmosphere Monitoring Service (CAMS). The estimated AOD demonstrated good agreement with AHI data, achieving an annual R² greater than 0.96 and RMSE less than 0.1. Spatially, the estimated AOD also showed strong consistency with AHI, AERONET, and CAMS. Additionally, the annual, seasonal, and hourly distribution characteristics of AOD from 2018 to 2023 were analyzed. Two typical cases of aerosol variation in the BTH region were selected and examined: a dust storm event in 2023 and changes during the Spring Festival in 2021. This method provides continuous data support for air pollution monitoring and control in the BTH region and offers valuable references for pollution prevention efforts. Full article

Long-term particulate matter (PM) chemical composition measurements were performed in Cyprus at two different sites (an urban/traffic site (“LIMTRA”) and a remote/background site (“AGM”)) in an effort to assess (i) the spatial and temporal variability of fine (PM2.5) particulate matter in the eastern Mediterranean; (ii) the main sources contributing to their levels and their relationship with the characteristics of the sampling location; and (iii) the enhancement effect of local anthropogenic and natural biogenic sources on PM levels. To this end, the simultaneous determination of 118 individual Secondary Organic Aerosol (SOA) components (carboxylic acids, organosulfates, and organonitrates) was performed. The “AGM” station showed average SOA yields more than three times higher than those at the “LIMTRA” station (15 ng∙m⁻³ and 4.4 ng∙m⁻³, respectively), whilst the organonitrate levels were higher at “LIMTRA” than at “AGM” (3.3 ng∙m⁻³ and 1.8 ng∙m⁻³, respectively). The most abundant SOA species were hydroxy-acetone sulfate, glycolic acid sulfate, and lactic acid sulfate (21 ng∙m⁻³ at “LIMTRA” and 84 ng∙m⁻³ at “AGM”). The highest SOA load was observed in spring at “AGM” (18 ng∙m⁻³) and in summer at “LIMTRA” (6.8 ng∙m⁻³). Two statistical factorization tools, Principal Component Analysis and Positive Matrix Factorization, were applied to extract common patterns and point to possible SOA sources and SOA formation pathways; the different categorization approaches produced similar results. Full article

The abrupt COVID-19 lockdown in early 2020 offered a unique natural experiment to examine vegetation productivity responses to sudden declines in human activity. Although vegetation often responds to environmental changes with time lags, how such lags operate under short-term, intensive disturbances remains unclear. This study combined multi-source environmental data with an interpretable machine learning framework (XGBoost-SHAP) to analyze spatiotemporal variations in net primary productivity (NPP) across the Beijing-Tianjin-Hebei region during the strict lockdown (March–May) and recovery (June–August) periods, using 2017–2019 as a baseline. Results indicate that: (1) NPP showed a significant increase during lockdown, with 88.4% of pixels showing positive changes, especially in central urban areas. During recovery, vegetation responses weakened (65.31% positive) and became more spatially heterogeneous. (2) Integrating lagged environmental variables improved model performance (R² increased by an average of 0.071). SHAP analysis identified climatic factors (temperature, precipitation, radiation) as dominant drivers of NPP, while aerosol optical depth (AOD) and nighttime light (NTL) had minimal influence and weak lagged effects. Importantly, under lockdown, vegetation exhibited stronger immediate responses to concurrent temperature, precipitation, and radiation (SHAP contribution increased by approximately 7.05% compared to the baseline), whereas lagged effects seen in baseline conditions were substantially reduced. Compared to the lockdown period, anthropogenic disturbances during the recovery phase showed a direct weakening of their impact (decreasing by 6.01%). However, the air quality improvements resulting from the spring lockdown exhibited a significant cross-seasonal lag effect. (3) Spatially, NPP response times showed an “urban-immediate, mountainous-delayed” pattern, reflecting both the ecological memory of mountain systems and the rapid adjustment capacity of urban vegetation. These findings demonstrate that short-term removal of anthropogenic disturbances shifted vegetation responses toward greater immediacy and sensitivity to environmental conditions. This offers new insights into a “green window period” for ecological management and supports evidence-based, adaptive regional climate and ecosystem policies. Full article

Seasonal fluctuations in the chemical composition of fine particulate matter (PM_2.5) are known to influence its toxicological properties; however, their integrated biological effects remain incompletely understood. In this study, PM_2.5 was continuously collected over two consecutive years at a single urban site in Japan and classified by season. The samples were comprehensively characterized for ionic species, metals, carbonaceous fractions, and polycyclic aromatic hydrocarbons (PAHs), and their pulmonary effects were evaluated in vivo following intratracheal administration in mice. Seasonal PM_2.5 exhibited pronounced compositional differences, with higher levels of secondary inorganic aerosol components in summer and enrichment of PAHs and mineral-associated components in winter. These seasonal differences translated into distinct biological responses. Reactive oxygen species (ROS) production (1.6–2.7-fold increase) and bronchoalveolar lavage (BAL) neutrophil infiltration were strongly associated with PAH-rich PM_2.5, whereas interleukin-1α (IL-1α) showed robust positive correlations with mineral components, including K⁺, Ca²⁺, and Mg²⁺, which were predominantly enriched in winter PM_2.5. In contrast, secondary inorganic aerosol species displayed a limited capacity to induce IL-1α. Compared with summer samples, winter PM_2.5 induced significantly higher levels of ROS production and IL-1α (approximately 1.5–2.6-fold increase). Using TLR2- and TLR4-deficient mice, we further demonstrated that PM_2.5-induced increases in BAL cell counts, ROS, IL-6, and TNF-α were partially attenuated in TLR4 knockout mice, indicating a contributory but not exclusive role for TLR4 signaling in PM_2.5-driven pulmonary inflammation. Collectively, these findings demonstrate that seasonal variations in PM_2.5 composition, not particle mass alone, critically shape oxidative stress and innate immune responses in the lungs. In particular, winter PM_2.5 enriched in mineral-associated components preferentially activates IL-1α-mediated alarmin pathways, underscoring the importance of the particle composition in determining seasonal air pollution toxicity. Full article

Water-soluble inorganic ions (WSIIs) are major components of PM_2.5 and play a prominent role in atmospheric acidification. Previous studies have mainly focused on urban areas, whereas research pertaining to county-level cities remains comparatively limited. To fill this gap, PM_2.5 samples were collected from March 2018 to February 2019 in Botou, a county-level city in the Jing–Jin–Ji region. Seasonal variation of WSII were studied, and their sources was apportioned by Positive Matrix Factorization (PMF) model. Annual PM_2.5 concentrations were 79.15 ± 48.44 mg/m³, which is 2.26 times of the Level II standard limit specified the National Ambient Air Quality Standard. Nitrate (NO₃⁻) was the most abundant ion, followed by ammonium (NH₄⁺) and sulfate (SO₄²⁻). The secondary inorganic aerosols (SIA, i.e., SO₄²⁻, NO₃⁻, and NH₄⁺) constituted 35.1± 4.7% of PM_2.5 mass. PM_2.5 mass, SO₄²⁻, NO₃⁻, NH₄⁺, K⁺, and Cl⁻ showed highest concentrations in winter. Ammonium salts were existed as ammonium sulfate ((NH₄)₂SO₄) and ammonium nitrate (NH₄NO₃) in spring, summer, and autumn, while it also can be existed as ammonium chloride (NH₄Cl) in winter. PMF analysis shows that the sources of WSIIs dominated by secondary source and followed by biomass burning. These results highlight the need for improved controls on gaseous precursors (NH₃, NO₂ and SO₂) and biomass burning to effectively reduce PM_2.5. Full article