Search Results (357)

This study investigates the long-term variability and evolution of particulate matter with an aerodynamic diameter of <2.5 µm (PM_2.5) sources in Vilnius, Lithuania, during the period 2013–2021. Source apportionment was performed using Positive Matrix Factorization (PMF) based on elemental composition data obtained through particle-induced X-ray emission (PIXE) analysis. The results revealed substantial year-to-year variability in the chemical profiles of the identified sources. Crustal/mineral dust was characterized by high contributions of lithogenic elements, including Si, Ca, Ti, and Fe, while soil dust exhibited elevated proportions of Al, Ca, and Fe. Traffic non-exhaust emissions were marked by elevated Cu, Zn, and Pb in 2013–2015, whereas exhaust emissions in 2019–2021 were characterized by sulfur-rich aerosols. Industrial and oil combustion sources showed enhanced contributions of Ni, V, and Cr, particularly in 2016, 2018, and 2020. Biomass/wood burning represented a major seasonal source, reaching peak intensity in 2018–2019 and characterized by elevated K and Zn contributions. A notable long-term trend was the increasing importance of soil-derived particles, as reflected by Al contributions rising to 91.2% by 2021. Overall, the major PM_2.5 source categories remained relatively stable, while their chemical fingerprints and relative importance exhibited substantial temporal variability. 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

The atmospheric air quality is one of the crucial factors determining people’s health, duration and quality of life. The importance of ammonia (NH₃) and ethylene (C₂H₄) is due to the fact that they are precursors of secondary organic aerosols (SOA) and phytotoxicants, which significantly affect air quality, cause human diseases and damage plants. The Fourier Transform Infrared (FTIR) spectrometry is a powerful tool for long-term monitoring of the atmospheric gas composition, including toxic gases. The paper presents the results of atmospheric FTIR measurements of NH₃ and C₂H₄ at the St. Petersburg State University observational site (59.88° N, 29.83° E, 20 m above sea level) located in a suburb of greater Saint Petersburg. This work demonstrates the applicability of the ground-based atmospheric FTIR spectroscopy to long-term monitoring of air pollution in urbanized areas and in particular to provide information on the NH₃ and C₂H₄ abundance in the atmosphere, including the analysis of their annual cycle, long-term trends, and positive anomalies. It was shown that for NH₃ and C₂H₄, a statistically significant decrease in column-averaged dry-air mole fraction values (X_NH3 and X_C2H4) was observed, amounting to (−2.3 ± 0.2)%/year for the 2009–2025 period and with the rate (−2.2 ± 0.4)%/year for the 2016–2025 period, respectively. Periodically recorded X_NH3 anomalies indicate the presence of intensive emission sources in the region, subjecting ecosystems in adjacent areas to constant exposure to NH₃ concentrations exceeding the critical level. Anomalously high values of X_NH3 and X_C2H4 were recorded simultaneously only once—on 17 October 2017. Using data on HCN total column (as a forest fire indicator) and the results of atmospheric dispersion modeling, it was shown that this pollution event was caused by the influence of biomass burning products emitted from wildfires located approximately 250 km to the north-west from the observational site in the Helsinki area (Finland). Full article

Biomass burning is a major source of atmospheric pollution. However, rapid and quantitative assessment of particulate matter in smoke plumes remains challenging, owing to the physical uncertainties, limited coverage, and labor-intensive quality control of conventional monitoring approaches. Existing image-based deep learning methods typically address either smoke detection or air quality assessment separately. To address this gap, we develop a Unified Smoke Detection and Aerosol Estimation Framework (SDAF), a three-stage deep learning approach evaluated using a smoke-rich airborne dataset. The framework integrates smoke localization with PM₁ estimation by combining a YOLOv11-based detector with an optimized convolutional neural network. The model achieves high accuracy under in-plume conditions (R² of 0.985). However, its performance degrades under out-of-plume conditions due to substantial differences in visual features between the two domains. Consequently, direct across-domain transfer performs poorly, whereas region of interest (ROI)-level fine-tuning substantially improves performance for out-of-plume images (R² of 0.621). Despite these promising results, fundamental limitations remain. Image-based PM₁ estimation is intrinsically ill-posed due to the non-unique mapping between visual observations and particle mass. Overall, the framework enables an integrated workflow from smoke localization to quantitative PM₁ estimation using image data alone, offering a scalable solution for biomass burning monitoring and air quality assessment while highlighting the fundamentally indirect nature of image-based PM₁ inference relative to spatially resolved retrievals. Full article

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts. Full article

This study presents a novel, satellite-based framework for quantifying the relative contribution of regional transport in biomass burning aerosol (BBA) formation over the South China Sea (SCS). We integrate the biomass burning emission (BBE) rates from potential source regions with a random forest regression model, which is driven by backward trajectory analysis. This approach isolates and evaluates the relative contribution from transported sources. The model demonstrates robust predictive skill for BBA concentrations (R² = 0.78 on an independent test set), using only transport-weighted BBE rates and meteorological data as inputs. Quantitative interpretation via SHAP (Shapley Additive exPlanations) analysis reveals nonlinear relationships and the distinct importance of transport-source features. A key finding is that BBE originating from northern Laos and Thailand contributes 21.23% to the predicted BBA concentrations over the SCS. Furthermore, there is a clear nonlinear positive correlation between the regional BBE rates and downwind BBA concentration, except for transport from Cambodia. Our results pinpoint that the impact of regional transport is paramount, governed by a combination of source emission intensity, transport duration, and trajectory pathway. This study establishes a satellite-driven methodology for attributing aerosol sources and clarifies the dominant controls on BBA concentration variability in a major maritime receptor region. Full article

The black carbon (BC) emission resulting from human activity comes mainly from fossil fuels and solid biomass burning, as well as transport fuels due to incomplete combustion. The biggest sources of BC pollution are currently diesel transport and domestic heating appliances burning solid fossil fuels or biomass. Firewood and pellet fuels were used for this BC research. The study used four domestic heating appliances using wood and agricultural waste pellets, as well as several types of firewood. The tests used a gravimetric particulate analysis method to determine the total amount of particulate matter. In further physical and chemical analyses, the emissions are broken down into components, i.e., substances of known composition that can be separated from the sample and weighed. In our study, the BC emissions varied from 0 to 120 mg/MJ depending on the type of boiler (automatic or manual), the combustion mode (based on oxygen supply), and the type of fuel. Emissions varied from 0–8 mg/MJ in a modern pellet-fired and automatically-controlled boiler, and from 1–25 mg/MJ in a wood-fired water heating boiler, with the highest emissions found for softwood (spruce). In the pellet stove with automatic feeding and control, BC emissions varied between 1 and 120 mg/MJ, with the highest emissions detected for wood pellets, and in the wood-burning fireplace, the emissions varied between 6 and 80 mg/MJ, with the highest emissions detected for birch firewood. Full article

Naphthalene and methylnaphthalene (Nap and MN) are the most abundant polycyclic aromatic hydrocarbons (PAHs) and are important precursors of secondary organic aerosol (SOA) in the atmosphere. 1.2-Phthalic acid (1,2-PhA) and 4-methylphthalic acid (4-MPhA) are usually treated as tracers of SOA from Nap and MN. However, the two tracers also have primary sources, and directly using the tracers to estimate SOA would lead to an overestimation. In this study, we conducted a one-year synchronous observation of the two-ring PAH SOA (SOA_2-rings) tracers at nine sites in the Pearl River Delta (PRD) region. We measured and filtered the suitable emission characteristics of SOA_2-rings tracers for biomass burning, coal combustion, industrial processes and vehicle exhaust sources. Then, we developed a method to distinguish 1,2-PhA and 4-MPhA from primary emissions and secondary formation. The average proportions of 1,2-PhA_pri and 4-MPhA_pri in 1,2-PhA and 4-MPhA were 26.7% and 29.2%, respectively. The direct application of measured 1,2-PhA for estimating SOA_2-rings would lead to an overestimation exceeding 30% in the PRD. Furthermore, we estimated SOA_2-rings using the separated 1,2-PhA_sec and 4-MPhA_sec by the tracer-based method. The average contribution of MN to SOA was around three times that of Nap. In addition, when combined with monocyclic aromatic SOA (SOA_1-ring) and biogenic SOA, the contributions of SOA_1-ring (21%) and SOA_2-rings (25%) to total SOA were comparable. SOA_2-rings was even the largest contributor to total SOA (~44%) in winter. This study revealed that whether to separate the SOA_2-rings tracers for primary emissions and secondary formation is essential in SOA estimation and highlighted that two-ring PAHs make a significant contribution to SOA in the PRD. Full article

This study investigates the vertical variation and temporal characteristics and indicates the sources of black carbon (BC) and brown carbon (BrC) within particulate matter fraction PM₁ during light (November–December 2024) and heavy (January–February 2025) haze episodes in Bangkok, Thailand, a topic where data are still limited data regarding Southeast Asian megacities. Continuous measurements were conducted at 30 and 110 m above ground level, together with particle size distribution measurement, micrometeorological observations, and backward air mass trajectory analysis. During the haze periods, the highest particle number concentrations occurred in the 0.3–0.4 µm size range, indicating dominant contributions from combustion-related emissions and secondary aerosol formation. Mean PM₁ mass concentrations during the heavy haze episodes were more than 2.5 times higher than those during light haze. BC concentrations increased substantially during heavy haze, while the BC fraction of PM₁ remained relatively constant (~10%). In contrast, the BrC fraction reached nearly 20%, reflecting an increasing influence of biomass burning emissions associated with regional transport. Combined analyses of BC/BrC relationships, wind-direction dependence, and air mass trajectories demonstrate mixed contributions from local fossil fuel combustion and long-range transport of biomass burning aerosols during severe haze events. Full article

Southern Africa is highly sensitive to climate variability associated with the El Niño Southern Oscillation (ENSO), which strongly influences hydroclimate, vegetation dynamics, and atmospheric composition. This study examined the impacts of the 2015/16 El Niño on vegetation, meteorological conditions, and atmospheric emissions over Southern Africa using satellite observations and reanalysis data. Time-lagged cross-correlation analysis of seasonally adjusted time-series was applied to characterize synchronous and delayed interactions among vegetation indices, hydrological variables, meteorological drivers, and air-quality parameters. Bayesian causal impact analysis was further used to quantify El Niño-induced anomalies by comparing observed conditions with counterfactual scenarios representing the absence of the event. The results showed that vegetation greenness responds primarily to concurrent moisture availability, with strong positive associations between NDVI, precipitation, soil moisture, and canopy water. Moisture-related variables exert delayed influences on atmospheric composition, highlighting the role of wet scavenging and dilution. Carbonaceous aerosols (black carbon [BC] and organic carbon [OC]), particulate matter [PM_2.5], and aerosol optical depth exhibit strong synchronous coupling, indicating a dominant biomass-burning source. The causal impact analysis reveals statistically significant and sustained post-2015 increases in fire-related emissions (carbon monoxide [CO], BC, OC, PM_2.5, and aerosol optical depth [AOD]), particularly during austral winter and dry seasons. In contrast, precipitation, soil moisture, evapotranspiration, and vegetation greenness show persistent negative anomalies, reflecting widespread drought stress under elevated temperatures. Overall, the findings demonstrate that the 2015/16 El Niño amplified fire emissions while suppressing ecosystem functioning across Southern Africa, underscoring strong climate–fire–vegetation feedback with important air-quality and environmental implications. Full article

Biomass burning aerosols (BBA) released from large-scale wildfires pose a serious threat worldwide, necessitating a comprehensive understanding of their plume characteristics. To address this challenge, this study used satellite data provided by the Second-generation Global Imager (SGLI) aboard the Global Change Observation Mission-C and regional-scale numerical chemical transport model (CTM) simulations to characterize BBA plumes. The SGLI data and CTM simulations were compared and verified, and the 3D characteristics of BBA plumes, including concentration, diffusion range, spatial variation in optical properties, plume top height, and vertical profile, were subsequently derived. In this study, we focused on large-scale forest fires that occurred in western North America in September 2020 and Indonesia in September 2019. In both cases, Aerosol optical thickness (AOT) and Ångström Exponent (AE) values show a positive correlation with the height of the BBA plume top. The results showed that the higher the BBA plume top, the thicker the plume and the smaller the aerosol size. This point is what we particularly wish to highlight in this study. The SGLI polarization data proved useful for characterizing the upper layers of the BBA plumes. By understanding the detailed characteristics at the top of the plume, it is possible to predict the BBA plume’s advection and lifetime. Full article

Atmospheric aerosols in Southeast Asia, influenced by climate and seasonal circulation, are examined here. This study analyzes the impact of the 2015 El Niño and monsoonal variability on aerosol properties over Penang, Malaysia, from 2015–2019. Aerosol Optical Depth (AOD), Ångström Exponent (AE), Fine Mode Fraction (FMF), and Single Scattering Albedo (SSA) were analyzed using AERONET observations, complemented by satellite-derived fire data and NOAA HYSPLIT back-trajectory analysis. Pronounced seasonal variability was observed, with elevated AOD during the Southwest Monsoon (0.72 ± 0.15) associated with biomass burning and mixed urban aerosols, and lower AOD during the Northeast Monsoon (0.47 ± 0.12) due to cleaner maritime air masses. The inter-monsoon period exhibited the lowest AOD (0.28 ± 0.10), reflecting enhanced wet scavenging and mixed aerosol sources. Interannually, the 2015 El Niño recorded substantially higher aerosol loading, including extreme AOD events (>1.75), driven by intensified regional fire activity under dry conditions. A statistically significant but weak correlation (R² = 0.12, p = 0.047) indicates biomass burning contributed to AOD, though transport processes were the dominant driver. Trajectory analysis confirmed that aerosols originated from fire-affected Sumatra during the Southwest Monsoon and from the South China Sea during the Northeast Monsoon. These results show that climate and winds drive aerosol changes, so regional monitoring and cross-border air management in Southeast Asia are needed. Full article

Clean heating policies were implemented in rural areas of Shaanxi Province in 2017 to alleviate severe air pollution. To evaluate their impacts on bioavailability of PM_2.5-bound metals, the influence of emission sources and aerosol acidity on PM_2.5-bound metal solubility was explored in Xi’an over three policy-defined periods between 2016 and 2021. Results showed that aerosol pH increased progressively from 4.81 ± 1.82 to 5.29 ± 1.79 following policy implementation, closely associated with reductions in SO₂ and NO₂ concentrations due to emission controls. Metal concentrations decreased significantly over the study period. In contrast, metal solubility exhibited clear source-dependent variations. Solubilities of metals associated with coal combustion, biomass burning, and industrial activities (As, Cd, Pb, K and Zn) decreased by 16.6–50.5% with weakening aerosol acidity. In contrast, solubilities of metals related to vehicle exhaust, oil fuel combustion and dust (Cu, V, Ni, Ti and Fe) increased by 38.3–56.8%, indicating enhanced influence of emission processes. Source apportionment demonstrated that mixed contributions of coal combustion, biomass burning and industrial activities to total and water-soluble metals decreased by 12% and 11.2%, respectively, while contribution from secondary atmospheric processes increased by 4% and 3.8%. These findings highlight that clean heating policies reshape both metal sources and atmospheric chemical environments, thereby altering metal dissolution characteristics and bioavailability. Full article

The composition of air pollutants in industrial complexes differs from that of general urban areas, often containing more hazardous substances that pose significant health risks to both workers and residents nearby. In this study, PM_2.5 and its 29 chemical components (eight ions, two carbon species, and 19 trace elements) were measured and analyzed at five monitoring sites adjacent to the Yeosu and Gwangyang industrial complexes from August 2020 to December 2024. Chemical characterization and source identification were conducted. The average PM_2.5 concentration was 18.63 ± 9.71 μg/m³, with notably higher levels observed during winter and spring. A low correlation (R = 0.56) between elemental carbon (EC) and organic carbon (OC) suggests a dominance of secondary aerosols. The charge balance analysis of [NH₄⁺] with [SO₄²⁻], [NO₃⁻], and [Cl⁻] showed slopes below the 1:1 line, indicating that NH₄⁺ is capable of neutralizing these anions. Positive matrix factorization (PMF) identified eight contributing sources—biomass burning (10.4%), sea salt (11.8%), suspended particles (7.1%), industrial sources (4.6%), Asian dust (5.2%), steel industry (21.8%), secondary nitrate (16.4%), and secondary sulfate (22.7%). These findings provide valuable insights for the development of targeted mitigation strategies and the establishment of effective emission control policies in industrial regions. Full article

This study evaluates the effectiveness of air pollution control measures in Xi’an, China, by investigating long-term changes in the concentrations, optical properties, and sources of black carbon (BC) and brown carbon (BrC). Wintertime observations of PM_2.5 carbonaceous aerosols were conducted over multiple years using a continuous Aethalometer. The data were analyzed using advanced aethalometer models, potential source contribution function (PSCF) analysis, and generalized additive models (GAMs) to deconstruct emission sources and formation pathways. Our results revealed a significant decrease in the mass concentration and light absorption coefficient of BC (b_abs-BC) between the earlier and later study periods, indicating successful emission reductions. In contrast, the light absorption from BrC (b_abs-BrC) remained relatively stable, suggesting persistent and distinct emission sources. Source apportionment analysis demonstrated a temporal shift in dominant regional influences, from biomass burning in the initial years to coal combustion in later years. In addition, GAMs showed that the primary driver for liquid fuel-derived BC transitioned from gasoline to diesel vehicle emissions. For solid fuels, residential coal combustion consistently contributed over 50% of BC, highlighting that improvements in coal combustion technology were effective in reducing BC emissions. Furthermore, a substantial fraction of BrC was increased, with nocturnal peaks associated with high relative humidity, emphasizing the aqueous-phase formation influences. Collectively, these findings demonstrated that although certain control strategies successfully mitigated BC, the persistent challenge of BrC pollution necessitates targeted measures addressing secondary formation and primary fossil fuel sources. Full article