Search Results (65)

Aerosols play a critical role in modulating the land–atmosphere energy balance, influencing regional climate dynamics, and affecting air quality. Xinjiang, a typical arid and semi-arid region in China, frequently experiences dust events and complex aerosol transport processes. This study provides a comprehensive analysis of the spatiotemporal evolution and potential source regions of aerosols in Xinjiang from 2005 to 2023, based on Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (MCD19A2), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) vertical profiles, ground-based PM_2.5 and PM₁₀ concentrations, MERRA-2 and ERA5 reanalysis datasets, and HYSPLIT backward trajectory simulations. The results reveal pronounced spatial and temporal heterogeneity in aerosol optical depth (AOD). In Northern Xinjiang (NXJ), AOD exhibits relatively small seasonal variation with a wintertime peak, while Southern Xinjiang (SXJ) shows significant seasonal and interannual variability, characterized by high AOD in spring and a minimum in winter, without a clear long-term trend. Dust is the dominant aerosol type, accounting for 96.74% of total aerosol content, and AOD levels are consistently higher in SXJ than in NXJ. During winter, aerosols are primarily deposited in the near-surface layer as a result of local and short-range transport processes, whereas in spring, long-range transport at higher altitudes becomes more prominent. In NXJ, air masses are primarily sourced from local regions and Central Asia, with stronger pollution levels observed in winter. In contrast, springtime pollution in Kashgar is mainly influenced by dust emissions from the Taklamakan Desert, exceeding winter levels. These findings provide important scientific insights for atmospheric environment management and the development of targeted dust mitigation strategies in arid regions. Full article

This study addresses the challenges of characterizing aerosol optical depth (AOD) dynamics from satellite observations, which are often hindered by data gaps and variability. A long short-term memory (LSTM) network was trained on an extended AOD dataset from Sicily to capture temporal patterns. The trained model was then applied to AOD data from distinct geographical regions: Cluj-Napoca and the central Mediterranean Sea. While the LSTM effectively captured general seasonal trends, it tended to smooth extreme AOD events. To mitigate this, a post-processing algorithm was developed to enhance the representation of AOD peaks and valleys. This enhancement method refines the characterization of historical AOD, providing a more accurate representation of observed atmospheric variability, particularly in capturing high and low AOD episodes. The results demonstrate the efficacy of the hybrid approach in improving the characterization of AOD dynamics across different regions. Full article

Long-term investigations of Aerosol Optical Depth (AOD) across Asia are crucial for understanding its regional impacts on the global climate system. However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. The resulting integration yields a high-resolution, seamless daily AOD dataset for Asia spanning the period from 2001 to 2024. The fused dataset demonstrates significant improvements over the original MERRA-2 AOD, with an increase in the coefficient of determination (R²) by 0.1065 and a reduction in root mean square error (RMSE) by 0.0369. Spatio-temporal analysis, conducted using Empirical Orthogonal Function (EOF) decomposition, reveals that AOD concentrations across Asia are strongly influenced by anthropogenic factors, including industrial activities, transportation emissions, and biomass burning. The results indicate a generally increasing trend in AOD from 2001 to 2014, followed by a declining trend from 2015 to 2024. Notably, EOF results show a marked rise in AOD levels in Mongolia after 2020, likely attributable to an uptick in dust storm activity. This research offers valuable insights into the spatiotemporal trends of aerosols across Asia, underscoring the need for sustained air quality measures to mitigate pollution and protect public health. Full article

Historical archives hold untapped potential for understanding long-term biodiversity change. This study introduces computational approaches to historical ecology, combining archival research, text analysis, and spatial mapping to reconstruct past biodiversity patterns. Using the 1845 Bavarian Animal Observation Dataset (AOD1845), a comprehensive survey of vertebrate species across 119 districts, we transform 5400 prose records into structured ecological data. Our analyses reveal how species distributions, habitat associations, and human–wildlife interactions were shaped by land use and environmental pressures in pre-industrial Bavaria. Beyond documenting ecological baselines, the study captures early perceptions of habitat loss and species decline. We emphasise the critical role of historical expertise in interpreting archival sources and avoiding anachronisms when integrating historical data with modern biodiversity frameworks. By bridging the humanities and environmental sciences, this work shows how digitised archives and computational methods can open new frontiers for conservation science, restoration ecology, and Anthropocene studies. The findings advocate for the systematic mobilisation of historical datasets to better understand biodiversity change over time. Full article

This research aims to estimate long-term aerosol radiative effects by combining radiation and Aerosol Optical Depth (AOD) observations in Barcelona, Spain. Aerosol Radiative Forcing and Aerosol Forcing Efficiency (ARF and AFE) were estimated by combining shortwave radiation measurements from a SolRad-Net CM-21 pyranometer (level 1.5) and AERONET AOD (level 2), using the direct method. The shortwave AFE was derived from the slope between net solar radiation and AOD at 440, 675, 879, and 1020 nm, and the ARF was computed by multiplying the AFE by AOD at six solar zenith angles (20°, 30°, 40°, 50°, 60°, and 70°). Clear-sky conditions were selected from all-skies days by a quadratic fitting. The aerosol was classified to investigate the forcing contributions from each aerosol type. The aerosol classification was based on Pace and Toledano’s thresholds from AOD vs. Ångström Exponent (AE). The GRASP inversions were performed by combined AOD, radiation, Degree of Linear Polarization (DoLP) by zenith angles from the polarized sun–sky–lunar photometer and the elastic signal from the UPC-ACTRIS lidar system. The long-term AFE and ARF are both negative, with an increasing tendency (in absolute value) of +24% (AFE) and +40% (ARF) in 14 years. The yearly AFE varied from −331 to −10 Wm⁻²τ⁻¹, and the ARF varied from −64 to −2 Wm⁻², associated with an AOD (440 nm) from 0.016 to 0.690. The three types of aerosols on clear-sky days are mixed aerosols (61%), desert dust (10%), and urban/industrial-biomass burning aerosols (29%). Combined with Gobbi’s method, this classification clustered the aerosols into four groups by AE analysis (two coarse- and two fine-mode aerosols). Then, the contribution of the aerosol types to the ARF showed that the desert dust forcing had the largest cooling effect in Barcelona (−61.5 to −37.4 Wm⁻²), followed by urban/industrial-biomass burning aerosols (−40.4 to −20.4 Wm⁻²) and mixed aerosols (−31.8 and −24.0 Wm⁻²). Regarding the comparison among Generalized Retrieval of Atmosphere and Surface Properties (GRASP) inversions, AERONET inversions, and direct method estimations, the AFE and ARF had some differences owing to their definitions in the algorithms. The DoLP, used as GRASP input, decreased the ARF overestimation for high AOD. Full article

This study presents the longest time series of aerosol optical properties and Precipitable Water Vapor (PW) from two AERONET sites in the Indo-Gangetic Plains (IGP). Analyzing 22 years of data (2001–2022) from Kanpur and 16 years (2007–2023) from Gandhi College, the study focuses on Aerosol Optical Depth (AOD), Ångström Exponent (α), Single Scattering Albedo (SSA), and Precipitable Water Vapor (PW). Significant variability in aerosol properties is observed across monthly, seasonal, and annual scales. The highest mean AOD₅₀₀ values, coupled with higher α_440–870 during post-monsoon and winter, indicate the dominance of fine-mode aerosols. A decrease in SSA with wavelength during these seasons further highlights the absorbing nature of these fine-mode aerosols, driven by fossil fuels and biomass burning. In contrast, summer and pre-monsoon have relatively lower mean AOD₅₀₀, lowest α_440–870, and increased SSA with wavelength, suggesting the dominance of coarse-mode scattering dust aerosols. PW exhibits a seasonal cycle, reaching its peak during the monsoon due to moisture transport from the Arabian Sea and Bay of Bengal, then decreasing post-monsoon as drier conditions prevail. Long-term annual trends reveal increasing aerosol concentrations, with AOD₅₀₀ rising by 18% at Kanpur and 29% at Gandhi College, suggesting faster aerosol loading at the latter. Sub-period analysis indicates a slowdown in AOD₅₀₀ increase during 2012–2023 at Kanpur, indicating potential stabilization post-industrialization, while Gandhi College’s more pronounced AOD₅₀₀ and α_440–870 increase underscores the growing impact of fine aerosols in rural IGP areas. Kanpur shows a sustained SSA increase, though at a slower rate in recent years, indicating dominant scattering aerosols. In contrast, Gandhi College has transitioned from moderate SSA increases to declines at longer wavelengths, suggesting enhanced fine-mode absorbing aerosols. At Gandhi College, the decline in PW reduces atmospheric moisture, limiting wet scavenging and likely contributing to the rise in fine-mode aerosols, especially during the monsoon and post-monsoon seasons. Our findings highlight the evolving aerosol sources in the IGP, with Kanpur stabilizing and rural areas like Gandhi College seeing continued increases in pollution. Full article

Accurate spectral and radiometric calibration is critical for precise Solar Spectral Irradiance (SSI) and Aerosol Optical Depth (AOD) retrievals in ground-based observations. This study introduces a pixel-based real-time noise deduction method and evaluates its performance using laser sources, Fraunhofer dark lines, and an improved Langley plot calibration. The proposed approach addresses challenges in long-term field SSI monitoring, including spectral noise variation and frequent calibration requirements for wavelength and responsivity corrections. The pixel-based noise deduction method effectively suppresses spectral dark noise to 0 ± 0.890, outperforming temperature-based corrections by 0.6%. Wavelength accuracy tests with laser sources and Fraunhofer dark lines demonstrate high consistency, with δλ < 0.3 nm, while spectral calibration uncertainty is assessed at 0.195 nm to 0.299 nm. The improved Langley plot achieves spectral responsivity differing by only 0.80% from the standard Langley plot and enhances AOD correlation with CE318 by 0.9–2.7% (RMSE: 0.002–0.003), significantly improving AOD observation accuracy. This work advances the development of field SSI hyperspectral observation and calibration, improving the accuracy of SSI and AOD measurements and contributing to the study of environmental changes and climate dynamics. Full article

Aerosol vertical stratification significantly influences the Earth’s radiative balance and particulate-matter-related air quality. Continuous vertically resolved observations remain scarce compared to surface-level and column-integrated measurements. This work presents and makes available a novel, long-term (2016–2022) aerosol dataset derived from continuous (24/7) vertical profile observations from three selected stations (Aosta, Rome, Messina) of the Italian Automated Lidar-Ceilometer (ALC) Network (ALICENET). Using original retrieval methodologies, we derive over 600,000 quality-assured profiles of aerosol properties at the 15 min temporal and 15 metre vertical resolutions. These properties include the particulate matter mass concentration (PM), aerosol extinction and optical depth (AOD), i.e., air quality legislated quantities or essential climate variables. Through original ALICENET algorithms, we also derive long-term aerosol vertical layering data, including the mixed aerosol layer (MAL) and elevated aerosol layers (EALs) heights. Based on this new dataset, we obtain an unprecedented, fine spatiotemporal characterisation of the aerosol vertical distributions in Italy across different geographical settings (Alpine, urban, and coastal) and temporal scales (from sub-hourly to seasonal). Our analysis reveals distinct aerosol daily and annual cycles within the mixed layer and above, reflecting the interplay between site-specific environmental conditions and atmospheric circulations in the Mediterranean region. In the lower troposphere, mixing processes efficiently dilute particles in the major urban area of Rome, while mesoscale circulations act either as removal mechanisms (reducing the PM by up to 35% in Rome) or transport pathways (increasing the loads by up to 50% in Aosta). The MAL exhibits pronounced diurnal variability, reaching maximum (summer) heights of >2 km in Rome, while remaining below 1.4 km and 1 km in the Alpine and coastal sites, respectively. The vertical build-up of the AOD shows marked latitudinal and seasonal variability, with 80% (30%) of the total AOD residing in the first 500 m in Aosta-winter (Messina-summer). The seasonal frequency of the EALs reached 40% of the time (Messina-summer), mainly in the 1.5–4.0 km altitude range. An average (wet) PM > 40 μg m⁻³ is associated with the EALs over Rome and Messina. Notably, 10–40% of the EAL-affected days were also associated with increased PM within the MAL, suggesting the entrainment of the EALs in the mixing layer and thus their impact on the surface air quality. We also integrated ALC observations with relevant, state-of-the-art model reanalysis datasets (ERA5 and CAMS) to support our understanding of the aerosol patterns, related sources, and transport dynamics. This further allowed measurement vs. model intercomparisons and relevant examination of discrepancies. A good agreement (within 10–35%) was found between the ALICENET MAL and the ERA5 boundary layer height. The CAMS PM₁₀ values at the surface level well matched relevant in situ observations, while a statistically significant negative bias of 5–15 μg m⁻³ in the first 2–3 km altitude was found with respect to the ALC PM profiles across all the sites and seasons. Full article

This study assesses the performance of the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset in estimating ground-level concentrations (GLCs) of aerosols and criteria pollutants across the Himawari-8 observational area, covering China, Indonesia, and Australia, from 2016 to 2023. Ground-based monitoring networks in these regions are limited in scope, making it necessary to rely on satellite-derived aerosol optical depth (AOD) as a proxy for GLCs. While AOD offers broad coverage, it presents challenges, particularly in capturing surface-level pollution accurately during episodic events. CAMS, which integrates satellite data with atmospheric models, is evaluated here to determine its effectiveness in addressing these issues. The study employs square root transformation to normalize pollutant concentration data and calculates monthly–hourly long-term averages to isolate pollution anomalies. Geographically weighted regression (GWR) and Jacobian matrix (dY/dX) methods are applied to assess the spatial variability of pollutant concentrations and their relationship with meteorological factors. Results show that while CAMS captures large-scale pollution episodes, such as the 2019/2020 Australian wildfires, discrepancies in representing GLCs are apparent, especially when vertical aerosol stratification occurs during short-term pollution events. The study emphasizes the need for integrating CAMS data with higher-resolution satellite observations, like Himawari-8, to improve the accuracy of real-time air quality monitoring. The findings highlight important implications for public health interventions and environmental policy-making, particularly in regions with insufficient ground-based data. Full article

The use of satellite data to estimate PM_2.5 is an appropriate approach for long-term, substantial monitoring and assessment. To estimate PM_2.5, the majority of the algorithms now in use utilize the top-of-atmosphere (TOA) reflectance or aerosol optical depth (AOD) derived from scalar satellite data. However, there is relatively little research on the retrieval of PM_2.5 using multi-angle polarized data. With its directional polarimetric camera (DPC), the Chinese new-generation satellite Gaofen 5B (henceforth referred to as GF-5B) offers a unique opportunity to close this gap in multi-angle polarized observation data. In this research, we utilized TOA data from the DPC payload and applied the gradient boosting machine method to simulate the impact of the observation angle, wavelength, and polarization information on the accuracy of PM_2.5 retrieval. We identified the optimal conditions for the effective estimation of PM_2.5. The quantitative results indicated that, under these optimal conditions, the PM_2.5 concentrations retrieved by GF-5B showed a strong correlation with the ground-based data, achieving an R² of 0.9272 and an RMSE of 7.38 µg·m⁻³. By contrast, Himawari-8’s retrieval accuracy under similar data conditions consisted of an R² of 0.9099 and RMSE of 7.42 µg·m⁻³, indicating that GF-5B offers higher accuracy. Furthermore, the retrieval results in this study demonstrated an R² of 0.81 when compared to the CHAP dataset, confirming the feasibility and effectiveness of the use of GF-5B for PM_2.5 retrieval and providing support for PM_2.5 estimation through multi-angle polarized data. Full article

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources. Full article

Reanalysis and satellite retrieval are two primary approaches for obtaining large-scale and long-term Aerosol Optical Depth (AOD) datasets. This study evaluates and compares the accuracy, long-term stability, and error characteristics of the MERRA-2, MODIS combined Dark Target and Deep Blue (DT&DB), and VIIRS DB AOD products globally and regionally. The results indicate that the MERRA-2 AOD exhibits the highest accuracy with an expected error (EE, ±0.05 ± 20%) of 83.24% and mean absolute error (MAE) of 0.056, maintaining a stability of 0.010 per decade. However, since the MERRA-2 AOD ceased assimilating observations other than the MODIS AOD in 2014, its accuracy decreased by approximately 5.6% in the EE metric after 2014. The VIIRS Deep Blue (DB) AOD product, with an EE of 79.43% and stability of 0.016 per decade, is slightly less accurate and stable compared to the MERRA-2 AOD. The MODIS DT&DB AOD demonstrates an EE of 76.75% and stability of 0.011 per decade. Regionally, the MERRA-2 AOD performs acceptably in most areas, especially in low-aerosol-loading regions, with an EE > 86% and stability ~0.02 per decade. The VIIRS DB AOD excels in high-aerosol-loading regions, such as the Indian subcontinent, with an EE of 69.14% and a stability of 0.049 per decade. The performance of the MODIS DT&DB AOD falls between that of VIIRS DB and MERRA-2 across most regions. Overall, each product meets the accuracy and stability metrics globally, but users need to select the appropriate product for analysis based on the validation results of the accuracy and stability in different regions. Full article

Long-term exposure to PM_2.5 pollution increases the risk of cardiovascular diseases, particularly ischemic heart disease (IHD). Current assessments of the health effects related to PM_2.5 exposure are limited by sparse ground monitoring stations and applicable disease research cohorts, making accurate health effect evaluations challenging. Using satellite-observed aerosol optical depth (AOD) data and the XGBoost-PM25 model, we obtained 1 km scale PM_2.5 exposure levels across China. We quantified the premature mortality caused by PM_2.5-exposure-induced IHD using the Global Exposure Mortality Model (GEMM) and baseline mortality data. Furthermore, we employed the Gini coefficient, a measure from economics to quantify inequality, to evaluate the distribution differences in health impacts due to PM_2.5 exposure under varying socioeconomic conditions. The results indicate that PM_2.5 concentrations in China are higher in the central and eastern regions. From 2007 to 2022, the national overall level showed a decreasing trend, dropping from 47.41 μg/m³ to 25.16 μg/m³. The number of premature deaths attributable to PM_2.5 exposure increased from 819 thousand in 2007 to 870 thousand in 2022, with fluctuations in certain regions. This increase is linked to population growth and aging because PM_2.5 levels have decreased. The results also indicate disparities in premature mortality from IHD among different economic groups in China from 2007 to 2022, with middle-income groups having a higher cumulative proportion of IHD-related premature deaths compared with high- and low-income groups. Despite narrowing GDP gaps across regions from 2007 to 2022, IHD consistently “favored” the middle-income groups. The highest Gini coefficient was observed in the Northwest (0.035), and the lowest was in the South (0.019). Targeted policy interventions are essential to establish a more equitable atmospheric environment. Full article

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and reanalysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, captures the nuanced dynamics of Cyprus’s atmospheric conditions. With a temporal resolution of 15 min and a spatial of 0.05° × 0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models’ accuracy but also highlights its proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), ranging from −2 to −4% per decade, have been found in autumn, especially marked in the island’s northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of −2 to −3% per decade, which were found in spring, do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the day light integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data. Full article

Over the past three decades, China has seen aerosol levels substantially surpass the global average, significantly impacting regional climate. This study investigates the long-term and seasonal variations of aerosols in the Huai River Basin (HRB) using MODIS, CALIOP observations from 2007 to 2021, and ground-based measurements. A notable finding is a significant decline in the annual mean Aerosol Optical Depth (AOD) across the HRB, with MODIS showing a decrease of approximately 0.023 to 0.027 per year, while CALIOP, which misses thin aerosol layers, recorded a decrease of about 0.016 per year. This downward trend is corroborated by improvements in air quality, as evidenced by PM2.5 measurements and visibility-based aerosol extinction coefficients. Aerosol decreases occurred at all heights, but for aerosols below 800 m, with an annual AOD decrease of 0.011. The study also quantifies the long-term trends of five major aerosol types, identifying Polluted Dust (PD) as the predominant frequency type (46%), which has significantly decreased, contributing to about 68% of the total AOD reduction observed by CALIOP (0.011 per year). Despite this, Dust and Polluted Continental (PC) aerosols persist, with PC showing no clear trend of decrease. Seasonal analysis reveals aerosol peaks in summer, contrary to surface measurements, attributed to variations in the Boundary Layer (BL) depth, affecting aerosol distribution and extinction. Furthermore, the study explores the influence of seasonal wind patterns on aerosol type variation, noting that shifts in wind direction contribute to the observed changes in aerosol types, particularly affecting Dust and PD occurrences. The integration of satellite and ground measurements provides a comprehensive view of regional aerosol properties, highlighting the effectiveness of China’s environmental policies in aerosol reduction. Nonetheless, the persistence of high PD and PC levels underscores the need for continued efforts to reduce both primary and secondary aerosol production to further enhance regional air quality. Full article