Search Results (134)

Madinah, Saudi Arabia, is a hot-desert pilgrimage city receiving millions of religious visitors annually, yet its fine particulate matter (PM_2.5) has not been chemically characterized. The city whose population is periodically influx by millions of religious visitors, generating concentrated increases in vehicular activity while simultaneously exposing a large transient population to ambient air pollution. Despite this, its fine particulate matter (PM_2.5) has not been chemically characterized. Twenty-four-hour PM_2.5 samples were collected at five urban sites between December 2014 and February 2016 and analyzed for black carbon, water-soluble inorganic ions, and trace elements; sources were resolved by enrichment factors and positive matrix factorization (PMF), and screening-level inhalation risks estimated for eight PM_2.5-bound metals. Site means ranged from 37.7 ± 20.5 µg m⁻³ at Uhad to 103 ± 50.7 µg m⁻³ at Al-Awali, exceeding the World Health Organization 24-h guideline of 15 µg m⁻³ at all sites in every season. Observed site–cycle means ranged from 37.7 ± 20.5 µg m⁻³ at Uhad to 103 ± 50.7 µg m⁻³ at Al-Awali, with concentrations exceeding the World Health Organization 24-h guideline of 15 µg m⁻³ across the monitored site–cycle datasets. Reconstructed mass was dominated by organic matter (53–80.5%) and crustal material (15–53%). Sulfate was the dominant water-soluble ion, but secondary inorganic aerosols contributed only 1–22% of mass, resembling rapidly urbanizing arid cities rather than Asian or European megacities. PMF resolved five sources: crustal dust, industrial mixed dust, oil combustion, vehicular emissions, and secondary aerosols. Hazard quotients remained below unity and cumulative carcinogenic risks below 10⁻⁶, principally from chromium and nickel. Because these measurements precede the Vision 2030 urban-transformation program, they establish a chemically resolved reference state for evaluating future air-quality change in Madinah. Full article

Atmospheric aerosol absorption is a key parameter for assessing aerosol effects on air quality and climate, yet the comparability of absorption measurements obtained with attenuation-based and offline filter-based techniques remains uncertain under real-world conditions. This issue is particularly relevant in complex urban coastal environments, where aerosols are influenced by traffic, shipping, industrial emissions, and marine air masses. Here, we investigate this methodological comparability through a multi-wavelength field intercomparison of the AE33 Aethalometer with two independent filter-based techniques, the Multi-Wavelength Absorption Analyzer (MWAA) and the Broadband Light Analyzer of Complex Aerosols (BLAnCA), at the Multedo urban coastal site in Genoa, Italy. The three techniques showed strong correlations across the ultraviolet, visible, and near-infrared spectral regions (R² = 0.93–0.99), with the closest agreement observed between MWAA and BLAnCA. AE33 reproduced the temporal variability in aerosol absorption well but systematically reported higher absorption coefficients than the two offline techniques, with differences of approximately 12–22% depending on wavelength. This systematic offset indicates that the default AE33 multiple-scattering correction may not fully represent the optical characteristics of the aerosol population sampled at this site. Absorption Ångström Exponent values derived independently from the three techniques remained close to unity, consistently suggesting a substantial influence of primary combustion emissions during the investigated campaign. Overall, the combined comparison of real-time and filter-based multi-wavelength techniques provides field-based evidence of their relative consistency and identifies a systematic AE33 bias that is relevant for improving the harmonization of aerosol absorption measurements in urban coastal monitoring environments. Full article

The increasing complexity of environmental analysis requires new approaches for interactive-scale simulation across indoor and urban spaces. While computational fluid dynamics (CFD) models provide detailed representations of gas dispersion and aerosol transport, they are often computationally intensive for interactive environmental analysis and integration into digital twin platforms. This pilot study presents a GPU-accelerated voxel simulation framework for modeling three-dimensional gas dispersion and aerosol transport using structured voxel representations derived from BIM, LiDAR, GIS, and other 3D built-environment datasets. The framework provides physically informed, CFD-inspired simulation at sub-meter to meter-scale spatial resolutions while maintaining interactive runtime performance suitable for building management, ventilation analysis, environmental monitoring, hazard assessment, and emergency response applications. Transport dynamics are modeled using a discretized advection–diffusion formulation incorporating airflow-driven advection, diffusion, source emissions, and voxel-level sink mechanisms. A key contribution is the development of a voxel-native GPU-parallel computational architecture implemented in Python 3.10.20 using Taichi kernels. Prototype simulations and comparative validation against a benchmark ANSYS Fluent 20.1 simulation demonstrate stable transport behavior, encouraging agreement with the CFD solution, browser-based three-dimensional visualization, and efficient execution on commodity GPU hardware. Experimental scenarios include a voxelized three-story Industry Foundation Classes (IFC) building model comprising approximately 34.5 million active voxels ($582\times 382\times 155$ voxels) and an urban-scale 3D city model spanning approximately $300\times 300\times 150$ m and containing up to 13.9 million active voxels. Simulations containing tens of millions of voxels were completed within minutes on a single consumer-grade GPU, demonstrating the scalability of the framework. These results demonstrate that the proposed framework provides an efficient voxel-based approximation of gas dispersion suitable for interactive environmental analysis and can support future integration with digital twin and AI-assisted environmental simulation systems. Full article

This study reports a combined morphological, surface chemical, and mineralogical characterization of fine particulate matter (PM_2.5) collected at three coastal sites—Northern (Abhour), Middle (Alhamraa), and Southern (Alkhomra)—in Jeddah, Saudi Arabia, during the summer (15 June–15 September 2017). The work complements a companion trace-element study of the same campaign by adding scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS/EDX mapping), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD), thereby linking bulk concentrations to particle morphology, surface oxidation state, and crystalline phase. Mean PM_2.5 concentrations were 22.2, 18.9, and 14.2 µg m⁻³ at the North, Middle, and South sites, respectively. Because samples were collected on borosilicate glass-fibre filters, the SEM images are dominated by the intrinsic fibrous matrix of the substrate; the collected aerosol is resolved as discrete sub-micrometre particles and agglomerates decorating the fibres, and the morphological interpretation is framed accordingly. XPS confirmed that surface metals (Fe, Al, Ca, and traces of Pb, Cu, Zn) occur predominantly in oxidized states, with the Middle urban site showing the strongest Fe and Pb signals. XRD identified quartz, calcite, gypsum, hematite/magnetite, and aluminum oxides, with additional Pb and Cu phases at the Middle and South sites. Principal component analysis (PCA) resolved four sources—mixed marine–crustal, terrigenous/industrial (Fe–Ti–Mn), oil combustion and shipping (V–Ni–Cu), and combustion/legacy-traffic (Pb–Zn)—consistent with prior Jeddah and Red Sea studies. The integrated approach provides surface-speciation and mineralogical details not available from bulk elemental analysis alone and establishes baseline information relevant to source management and health-risk assessment in arid coastal cities. Full article

Atmospheric deposition in industrial basins of Central Asia is strongly influenced by local emissions and wintertime dispersion conditions. This study characterized snowpack at 63 sampling stations across Ust-Kamenogorsk, Kazakhstan, including operational background station 1, on 24–26 February 2025 after a 116-day accumulation period. Major ions were determined in a spatially distributed exploratory subset of 16 samples, and trace elements were measured in samples from all 63 stations by means of inductively coupled plasma mass spectrometry and optical emission spectrometry. Mean meltwater pH and total dissolved solids were 6.55 ± 0.34 and 37.3 ± 18.0 mg L⁻¹, respectively. Charge-balance errors for the 16 hydrochemical samples ranged from −0.3% to +0.7%. Using the contamination index based on exceedances of the current Kazakhstan water-quality thresholds, 48 stations had CI < 1, seven had CI = 1–3, and eight had CI > 3; the highest value (60.21) occurred at station 26. Principal component analysis showed that the first three components explained 53.6% of the variance and separated a broad mineral/industrial aerosol association from a Pb–Cd–Zn association consistent with non-ferrous metallurgy and mixed urban sources. Cadmium was therefore interpreted as the principal contributor to the MPC-normalized index at the most affected stations, rather than as the dominant component by absolute concentration. The dissolved fraction can be mobilized during spring melt, indicating a potential pathway to soils and receiving waters, although direct ecological or human-health risk was not quantified. Station-level point mapping and projection along the NW–SE axis showed localized multi-element maxima rather than a monotonic citywide gradient. Full article

Nitrogen dioxide (NO₂) drives ozone and secondary aerosol formation and harms human health. Chongqing, a mountainous megacity of 32 million people, lacks a fine-scale satellite assessment of its NO₂ evolution. We analyzed tropospheric NO₂ vertical column density (VCD) over Chongqing for 2019–2024. The analysis used Sentinel-5P TROPOMI observations. We computed monthly, seasonal, and annual composites at 5.5 km resolution. Trends were quantified with the Theil–Sen slope and, at the pixel level, the Seasonal Mann–Kendall (SMK) test applied to the full 72-month series. A MODIS land-cover mask separated urban built-up from non-urban pixels. NO₂ concentrated in the central districts and along the Yangtze valley. The core exceeded the mountainous counties by a factor of 3 to 4. TROPOMI resolved the Wanzhou and Yongchuan–Jiangjin hotspots as separate features. The record was divided into three phases. The 2020 lockdown produced the minimum, 31% below the prior February. Rebound emissions produced the 2021 maximum of 5.6 × 10¹⁵ molecules cm⁻² under near-normal dispersion conditions, with ERA5 (the European Centre of Medium-range Weather Forecasts Reanalysis v.5) showing the January 2021 boundary layer 4.3% deeper than its climatological norm. Thereafter the regional mean stabilized: the area-weighted SMK slope was +0.042 × 10¹⁵ molecules cm⁻² yr⁻¹ and not significant (p = 0.14), because emission controls in the core and rising county emissions canceled in the average. Trends diverged sharply in space. The nine core districts declined (median urban Sen slope −0.11 × 10¹⁵ molecules cm⁻² yr⁻¹), whereas 41% of peripheral pixels rose significantly (p < 0.05). The urban-to-rural ratio narrowed from 3.0 in 2019 to 2.3 in 2024 (annual means). This convergence was robust to the built-up threshold (30–50%). Industrial relocation and county urbanization explain the peripheral rise. The results support extending vehicle and industrial emission standards from the core to the receiving counties. Full article

Fine particulate matter (PM_2.5) is studied for the first time at ground level in different sites of Greater Rosario (GR), an urban and industrial area of central-eastern Argentina. Twelve sites were selected according to land use, and 87 samples were analyzed during winter 2021 and summer 2022. The spatial and temporal distribution of PM_2.5 was examined, comparing results among sites and with global data. Ground-based data were complemented with satellite-derived Aerosol Optical Depth (AOD) and nitrogen dioxide vertical column density (NO₂ VCD). During winter, the highest PM_2.5 was obtained at an industrial site in northern GR, while in summer, maximum values were observed in the center of Rosario. Summer rain events could contribute to the wet deposition of suspended particles, resulting in lower PM_2.5 concentrations. Satellite data indicate higher average AOD in summer (attributable to forest fires in NE Argentina) and higher NO₂ VCD in winter, coinciding with burning events in the Paraná Delta islands and reflected in some PM_2.5 peaks. This analysis represents the first approach to assessing the air quality of Rosario and its surroundings, with on-site data collected in association with land use. Full article

Cooking oil fumes (COFs) are major pollutants generated during thermal food processing, with emissions rising rapidly due to urbanization and the expanding catering industry, posing significant risks to indoor air quality and human health. This review systematically examines the formation mechanisms, physicochemical properties, and environmental and health impacts of COFs. Their formation involves primary processes such as thermal oxidation, cracking, Maillard reactions, and water vaporization, alongside secondary reactions where volatile organic compounds (VOCs) contribute to ozone (O₃) and secondary organic aerosol (SOA) formation. COFs exhibit complex gas–liquid–solid coexistence and contain hazardous components including polycyclic aromatic hydrocarbons (PAHs), benzene compounds, aldehydes, and ultrafine particles (Dp ≤ 0.1 μm). Based on reported data, emission factors under typical cooking conditions range from 17.966 to 71.923 mg/(min·kg oil) for VOCs, 0.016 to 1.710 mg/(min·kg oil) for benzene compounds, and 0.458 to 1.820 mg/(min·kg oil) for formaldehyde. This highlights the variability in cooking fume emissions and associated health risks. Despite growing research attention, challenges remain in emission characterization and health risk assessment. By synthesizing current knowledge, this review provides a scientific basis for developing precise mitigation strategies and guiding future regulatory standards, with implications for improving food processing practices and indoor air quality management. Full article

Aromatic compounds are abundant in urban and industrial environments and potentially serve as one of the primary precursors for new particle formation (NPF). Pi-pi stacking is a distinctive weak interaction observed between aromatic compounds. Aromatic oxygenated organic molecules (AOOM) are key products of atmospheric oxidation of aromatic compounds; however, the role of pi-pi stacking in their involvement in atmospheric new particle formation (NPF) remains unclear. This study used quantum chemical calculations to reveal the nucleation mechanism of AOOM through pi-pi stacking and hydrogen bonding. The results indicate that the contribution of pi-pi stacking to nucleation in aromatic compounds is primarily determined by the stacking area. For aromatic hydrocarbons with 1–2 phenyl groups, the Gibbs free energy (ΔG) of dimolecular clusters formed solely by pi-pi stacking is positive. In contrast, for polycyclic aromatic hydrocarbons with three or more phenyl groups, the ΔG of these clusters decreases significantly and becomes negative. Single-phenyl AOOM primarily participates in the NPF process through hydrogen bonding with sulfuric acid molecules. In this work, an explanation is provided for observations and laboratory findings of the appearance of aromatic-ring-retaining species in nanoparticles. The discovery of pi-pi stacking also completes the variety of atmospheric nucleation weak interactions. The oxidation and nucleation mechanisms of aromatic compounds should be reassessed, considering the effects of pi-pi stacking, especially polycyclic aromatic hydrocarbons. These findings have important implications for sustainable urban air-quality management. By clarifying the role of pi-pi stacking, particularly in polycyclic aromatic hydrocarbons, this study may improve predictions of new particle formation, refine secondary organic aerosol modeling, and inform targeted emission-control policies to protect public health and mitigate climate impacts. Full article

Ammonia (NH₃) is an important alkaline gas and a key precursor to secondary inorganic aerosol. In the Fen River valley, coking plants are concentrated due to transportation advantages, while NH₃ emissions from coking processes have received limited attention despite their potential importance. In this study, atmospheric NH₃ was sampled by OGAWA samplers in a typical coal coking industrial park in Taiyuan during autumn and winter of 2024–2025, and its nitrogen isotopic composition was used for source apportionment. The results showed that the NH₃ concentration in the industrial park was 27.4 ± 3.8 μg m⁻³, significantly higher than that in the urban area (9.3 ± 4.2 μg m⁻³) and higher than winter levels reported for North China cities. The δ¹⁵N-NH₃ was −29.7 ± 1.6‰ and increased to −14.7 ± 1.6‰ after correcting for passive sampling bias. Source apportionment further indicated that NH₃ in the industrial park was dominated by non-agricultural sources (80.7%), with ammonia slip as the largest contributor (34.2 ± 20.1%), followed by coal combustion (25.8 ± 16.5%), traffic emissions (20.7 ± 11.6%) and agricultural sources (19.3 ± 11.6%). Therefore, some measures should be taken to reduce the NH₃ emissions from ammonia slip and traffic during autumn and winter. Full article

This study employed Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth data meteorological data, Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), and ground monitoring data for particulate matter (PM2.5) to construct a model for estimating the PM2.5 concentration in Yangquan City, Shanxi Province, from 2015 to 2024. The spatial and temporal changes in the PM2.5 concentration were analyzed. The results revealed the following: (1) The random forest model was more accurate than the multiple linear regression model. The spring model R² increased by 38.7%, and the Root Mean Square Error (RMSE) decreased by 92.6%. The summer model R² increased by 65.1%, and the RMSE decreased by 92.5%. The autumn model R² increased by 2.7%, and the RMSE decreased by 83.4%. The winter model R² increased by 25.4%, and the RMSE decreased by 95.5%. (2) The PM2.5 concentration in Yangquan City showed an upward trend from 2015 to 2017, and then a downward trend from 2018 to 2024, with an average decrease of 18.3 μg/m³. The highest concentration of PM2.5 was 55–85 μg/m³ in winter, and the lowest concentration of PM2.5 was 25–40 μg/m³ in summer. In terms of spatial distribution, the PM2.5 concentration in Yangquan City exhibits a pattern of being lower in the northwest and higher in the southeast. The high values are primarily concentrated in the central urban areas and major industrial zones in the southeast. Full article

Volatile organic compound (VOC) emissions from industrial parks are a crucial source of urban air pollution. This study assessed VOC emissions and their impact on secondary pollution from three key industries—packaging and printing, pharmaceutical manufacturing, and furniture manufacturing—in a typical industrial park in the Guanzhong region of China. The results revealed considerable variation in organized outlet VOC concentrations between the different industries, with the highest level observed in furniture manufacturing (3449.9 ± 437.6 µg/m³) and the lowest level discovered for pharmaceutical manufacturing (410.9 ± 205.5 μg/m³). The VOCs were mainly aromatics (40.7%) and alkanes (21.8%), with pentane, isopentane, xylene, and ethylbenzene the most abundant species. Although organized emissions (1151.6 t/y) constituted the primary source of emissions, fugitive emissions (358.1 t/y) remained a major contributor and primarily contributed aromatics and alkanes. Critically, reactivity-based assessment demonstrated that alkenes and aromatics were the principal contributors to the ozone formation potential (>80%). With regard to the secondary organic aerosol formation potential, aromatics were overwhelmingly dominant, accounting for approximately 87% of the total potential, with xylene and ethylbenzene in furniture manufacturing alone contributing 72.9%. The findings highlight the importance of prioritizing controls on highly reactive alkenes and aromatics. Fugitive emission management during storage, mixing, and curing stages should be enhanced and solvents should be substituted to effectively control VOC emissions in industrial parks. Full article

Emerging contaminants (ECs) comprise diverse pollutant classes that are increasingly detected in remote environments due to their persistence and long-range transport potential. In cold regions, atmospheric cold-trapping processes favour their accumulation in high-altitude and high-latitude snow and ice, which act as sensitive archives and secondary sources of contamination. While previous studies have addressed individual environmental compartments (e.g., snowpack, glacier ice, meltwater), focusing on specific contaminant classes, a systematic review integrating the occurrence, behaviour and impacts of major EC groups in polar and alpine snow and ice is still lacking. To fill this gap, this work synthesised current knowledge on the environmental fate of three key EC categories in the cryosphere: metals and metalloids (MMs), industrial chemicals and by-products (ICBs), and pharmaceuticals and personal care products (PPCPs). PRISMA guidelines were accurately followed for research, which was based on a Google Scholar search combining keywords on cryospheric matrices (snow, firn, ice cores), geographical regions (Arctic, Antarctic, Alps, high mountains), and contaminant classes. Of 350 records initially identified, 300 met the eligibility criteria (post-industrial snow, firn, or ice cores studies) after excluding studies focused on aerosol or meltwater-only, method-focused papers, pre-industrial datasets, urban-only investigations, and duplicates. Risk of bias was qualitatively assessed through manual screening, evaluating matrix eligibility, temporal consistency, analytical methods, detection limits, and duplicate data, with particular attention to inconsistencies in ECs classification. Strict operational definitions were therefore applied to ensure methodological coherence. Concentration data were harmonised into a standardised database, and findings were synthesised through a structured narrative supported by tabulated datasets organised by matrix and site. Overall, the evidence indicates widespread occurrence of ECs in the global cryosphere, with spatial variability linked to emission sources, long-range transport pathways, and snow physicochemical properties. Climate-change-driven alterations of snow dynamics, glacier retreat and permafrost thaw are expected to modify partitioning equilibria and enhance the secondary release of legacy and contemporary contaminants. However, significant limitations persist, including geographical gaps, variability in analytical sensitivity, lack of long-term monitoring for certain EC classes, and inconsistencies in contaminant classification frameworks. Despite these constraints, the synthesis highlights consistent emerging patterns and underscores the need to strengthen existing environmental protocols to mitigate potential risks to ecosystems and human health. Full article

Driven by factors such as meteorology, topography, and industrial structure, the concentrations of volatile organic compounds (VOCs) exhibit significant spatial heterogeneity. Investigating the characteristics and sources of VOCs in different regions is therefore crucial for formulating targeted strategies to mitigate their contributions to fine particulate matter (PM_2.5) and ozone (O₃) pollution. This study comprehensively investigated—for the first time—the concentration characteristics, sources, and contributions to secondary organic aerosol (SOA) and O₃ formation of VOCs at an urban background site in Ganzhou, a southern Chinese city, based on hourly observations of VOCs during 2023. Analyses included ozone formation potential (OFP), secondary organic aerosol formation potential (SOAFP), and positive matrix factorization (PMF) source apportionment. The influence of photochemical loss was assessed using a photochemical age parameterization method. The results showed an annual average total VOC concentration of 22.6 ± 13.17 ppbv, with higher levels in winter and lower in summer. Alkanes were the dominant species (45.76%). After correcting for photochemical loss, the initial concentration of VOCs (IC-VOCs) was approximately 60% higher than the observed concentration of VOCs (OC-VOCs), with alkenes becoming the dominant group in IC-VOCs (≈72%). OFP analysis indicated that the OFP calculated using initial VOC concentrations (IC-OFP) was substantially higher (by 320 μg/m³) than the values calculated using observed VOC concentrations (OC-OFP), primarily due to the increased contribution of alkenes. SOAFP was higher in spring and winter, and lower in summer and autumn, with aromatic hydrocarbons being the dominant contributors (>85%). PMF results based on month-case studies identified combustion and industrial process sources as the major contributors (>20%) in August, while combustion and vehicle exhaust dominated in January. Photochemical loss significantly influenced source apportionment, particularly leading to an underestimation of biogenic emissions during a warm month (August). These findings underscore the necessity of accounting for photochemical aging and offer a scientific basis for refining targeted VOC control measures in Ganzhou and similar regions. 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