Search Results (1,366)

Cyprus is located between Europe, Asia and Africa, and its location is vulnerable to dust transport from the Sahara Desert, wildfire smoke particles from surrounding regions, and other anthropogenic emissions caused by several factors, mostly due to business activities on harbor areas. Moreover, the country suffers from heavy traffic conditions caused by the limited public transportation system in Cyprus. Therefore, taking into consideration the country’s geographic location, heavy commercial activities, and lack of good public transportation system, Cyprus is exposed to dust episodes and high anthropogenic emissions associated with multiple health and environmental issues. Therefore, continuous and qualitative air quality monitoring is essential. The Department of Labor Inspection of Cyprus (DLI) has established an air quality monitoring network that consists of 11 stations at strategic geographic locations covering rural, residential, traffic and industrial zones. This network measures the following pollutants: nitrogen oxide, nitrogen dioxide, sulfur dioxide, ozone, carbon monoxide, particulate matter 2.5, and particulate matter 10. This case study compares and evaluates the agreement between Copernicus Atmosphere Monitoring Service (CAMS) air quality products and ground-truth data from the DLI air quality network. The study period spans from January to December 2024. This study focuses on the following three pollutants: particulate matter 2.5, particulate matter 10, and ozone, using Ensemble Median, EMEP, and CHIMERE near-real-time model data provided by CAMS. A data analysis was performed to identify the agreement and the error rate between those two datasets (i.e., ground-truth air quality data and CAMS air quality data). In addition, this study assesses the reliability of assimilated datasets from CAMS across rural, residential, traffic and industrial zones. The results showcase how CAMS near-real-time analysis data can supplement air quality monitoring in locations without the availability of ground-truth data. Full article

This study investigates the atmospheric concentrations, spatiotemporal distribution, the associated health risks and the ozone formation potential of benzene, toluene, ethylbenzene and xylenes (BTEX) across 33 monitoring sites of Greece over a one-year period. Samples were collected using passive diffusive samplers and analyzed by gas chromatography–mass spectrometry (GC-MS). The highest BTEX concentrations were detected during winter and autumn, particularly in urban and industrial areas such as in the Attica and Thessaloniki regions, likely due to enhanced emissions from combustion-related activities and reduced atmospheric dispersion. Health risk assessment revealed that hazard quotient (HQ) values for all compounds were within the acceptable limits. However, lifetime cancer risk (LTCR) for benzene exceeded the recommended limits in multiple regions during the colder seasons, indicating notable public health concern. Source apportionment using diagnostic ratios suggested varying seasonal emission sources, with vehicular emissions prevailing in winter and marine or industrial emissions in summer. Xylenes and toluene exhibited the highest ozone formation potential (OFP), underscoring their role in secondary pollutant formation. These findings demonstrate the need for seasonally adaptive air quality strategies, especially in Mediterranean urban and semi-urban environments. Full article

Air quality is a vital factor for safeguarding public and environmental health. Particulate matter (i.e., PM2.5 and PM10) and nitrogen dioxide are among the most harmful air pollutants leading to severe health risks such as respiratory and cardiovascular diseases, while also affecting the environment negatively by contributing to the formation of acid rains and ground level ozone. The European Union has introduced new thresholds on those pollutants to be met by the year 2030, taking into consideration the guidelines set by the World Health Organization, aiming for a healthier environment for humans and living species. Cyprus is an island that is vulnerable to those pollutants mostly due to its geographic location, facilitating shipping activities and dust transport from Sahara Desert, and the methods used to produce electricity which primarily rely on petroleum products. Furthermore, the country suffers from heavy traffic conditions, making it susceptible to high levels of nitrogen dioxide. Thus, the projection of air pollutants according to different scenarios based on regulations and policies of the European Union are necessary towards clean air and better practices. The Screening for High Emission Reduction Potential on Air (SHERPA) is a tool developed by the European Commission which allows the simulation of emission reduction scenarios and their effect on the following key pollutants: NO, NO₂, O₃, PM2.5, PM10. This study aims to assess the potential of the SHERPA simulation tool to support air quality related decision and policy planning in Cyprus to ensure that the country will remain within the thresholds that will be applicable in 2030. Full article

Air quality is crucial for public health and the environment, which makes it important to both monitor and forecast the level of pollution. Polluted air, containing harmful substances such as particulate matter, nitrogen oxides, or ozone, can lead to serious respiratory and circulatory diseases, especially in people at risk. Air quality forecasting allows for early warning of smog episodes and taking actions to reduce pollutant emissions. In this article, we review air pollutant concentration forecasting methods, analyzing both classical statistical approaches and modern techniques based on artificial intelligence, including deep models, neural networks, and machine learning, as well as advanced sensing technologies. This work aims to present the current state of research and identify the most promising directions of development in air quality modeling, which can contribute to more effective health and environmental protection. According to the reviewed literature, deep learning–based models, particularly hybrid and attention-driven architectures, emerge as the most promising approaches, while persistent challenges such as data quality, interpretability, and integration of heterogeneous sensing systems define the open issues for future research. Full article

Investigating atmospheric volatile organic compounds (VOCs) is critical for understanding their sources, chemical reactivity, and impacts on air quality, climate, and human health, especially in remote regions like the Tibetan Plateau where baseline data remains scarce. In this study, ambient VOCs species were simultaneously measured at four remote background sites on the Tibetan Plateau (Nyingchi, Namtso, Ngari, and Mount Everest) from 2012 to 2014 to investigate their concentration, composition, sources, and chemical reactivity. Weekly integrated samples were collected and analyzed using a Gas Chromatograph-Mass Spectrometer/Flame Ionization Detector (GC-MS/FID) system. The total VOC mixing ratios exhibited site-dependent variability, with the highest levels observed in Nyingchi, followed by Mount Everest, Ngari and Namtso. The VOC composition in those remote sites was dominated by alkanes (25.7–48.5%) and aromatics (11.4–34.7%), followed by halocarbons (19.1–28.1%) and alkenes (11.5–18.5%). A distinct seasonal trend was observed, with higher VOC concentrations in summer and lower levels in spring and autumn. Source analysis based on correlations between specific VOC species suggests that combustion emissions (e.g., biomass burning or residential heating) were a major contributor during winter and spring, while traffic-related emissions influenced summer VOC levels. In addition, long-range transport of pollutants from South Asia also significantly impacted VOC concentrations across the plateau. Furthermore, reactivity assessments indicated that alkenes were the dominant contributors to OH radical loss rates, whereas aromatics were the largest drivers of ozone formation potential (OFP). These findings highlight the complex interplay of local emissions and regional transport in shaping VOC chemistry in this high-altitude background environment, with implications for atmospheric oxidation capacity and secondary pollutant formation. Full article

Currently, ozone (O₃) has become one of the primary air pollutants in China, underscoring the importance of analyzing ozone formation sensitivity (OFS) for effective pollution control. Ozone sensitivity indices serve as effective tools for OFS identification. Among them, the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NO_x)—such as the formaldehyde-to-nitrogen dioxide ratio (FNR, defined as HCHO/NO₂, where HCHO represents VOCs and NO₂ represents NO_x)—is one of the most widely used satellite-based indicators. Recent studies have highlighted glyoxal (CHOCHO) as another critical ozone precursor, prompting the proposal of the glyoxal-to-nitrogen dioxide ratio (GNR, CHOCHO/NO₂) as an alternative metric. This study systematically compares the performance of FNR and GNR across four major urban agglomerations in China: Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Chengdu–Chongqing (CY) region, by integrating satellite remote sensing with ground-based observations. Results reveal that both indices exhibit consistent spatial trends in OFS distribution, transitioning from VOC-limited regimes in urban centers to NO_x-limited regimes in surrounding suburban areas. However, differences emerge in threshold values and classification outcomes. During summer, FNR identifies urban areas as transitional regimes (or VOC-limited in regions such as YRD and PRD), while suburban areas are classified as NO_x-limited. In contrast, GNR, which shows heightened sensitive to anthropogenic VOCs (AVOCs), exhibits a more restricted spatial extent in the transition regimes. By autumn, most urban areas shift toward VOC-limited regimes, while suburban regions remain NO_x-limited. Thresholds for both VOCs and NO_x increase during this period, with GNR demonstrating stronger sensitivity to NO_x. These findings underscore that the choice between FNR and GNR directly influences OFS determination, as their differing responses to biogenic and anthropogenic emissions lead to different conclusions. Future research should focus on integrating the complementary strengths of both indices to develop a more robust OFS identification method, thereby providing a theoretical basis for formulating effective ozone control strategies. Full article

The Mon Valley near Pittsburgh, Pennsylvania, consistently reports some of the poorest air quality in the United States. Recent studies have linked air pollution in this region to poor asthma outcomes but did not examine the impact on other respiratory conditions or vulnerable populations. This retrospective study examined the relationship between the air quality index (AQI) and respiratory exacerbations of asthma, bronchitis and chronic obstructive pulmonary disease (COPD) in the Mon Valley between January 2018 and February 2020. We linked daily Air Quality Index (AQI) values for ozone, PM_2.5, SO₂ and NO₂, plus temperature and wind speed to healthcare utilization for these conditions. Using a Poisson generalized linear model, we quantified the association between pollutant levels and same-day exacerbation rates, stratified analyses by age, sex and insurance type to identify vulnerable subgroups. Results indicated that higher AQI scores, driven primarily by PM_2.5 and SO₂, were significantly associated with increased asthma exacerbations on the day of exposure. Children and individuals with public insurance experienced the greatest impact. Bronchitis exacerbations showed a delayed response to SO₂. Our findings affirm PM_2.5 and SO₂ as key drivers of acute asthma events in the Mon Valley and extend this observation to include impacts on bronchitis and vulnerable populations. They also demonstrate the AQI’s value for public health surveillance and underscore the importance of tailored interventions such as issuing timely air quality alerts, strengthening emissions regulations and improving access to preventive care to protect at-risk populations from adverse air pollution effects. Full article

Air pollution critically impacts global health, climate change, and ecosystem balance. In Türkiye, rapid population growth, urban expansion, and industrial activities lead to significant land use and cover changes, negatively affecting air quality. This study examined the relationship between land use and land cover changes and six key pollutants (sulfur dioxide, ozone, aerosol index, carbon dioxide, nitrogen dioxide, and formaldehyde) using TROPOMI/Sentinel-5P and European Space Agency Climate Change Initiative data between 2018 and 2024. Satellite-based remote sensing techniques, MODIS data, land surface temperature, and Normalized Vegetation Index analyses were employed. The findings revealed that nitrogen dioxide and carbon dioxide emissions increase with urban expansion and traffic density in metropolitan areas (Istanbul, Ankara, Izmir), while agriculture and deforestation increase aerosol index levels in inland areas. Additionally, photochemical reactions increased surface ozone in the Mediterranean and Aegean regions. At the same time, sulfur dioxide and formaldehyde concentrations reached high levels in highly industrialized and metropolitan cities such as Istanbul, Ankara, and Izmir. This study highlights the role of green infrastructure in improving air quality and provides data-based recommendations for sustainable land management and urban planning policies. Full article

The densely populated city of Athens has been facing air pollution problems over the past few decades due to the high population density associated with an intense emission load constrained by the local topography causing poor ventilation. In this study, the evolution of the interannual and seasonal variation in primary and secondary gaseous as well as particulate urban air pollution in Athens was examined for the 2001–2023 period and for the following pollution parameters: SO₂, CO, NO₂, NO_x (NO + NO₂), O₃, O_x (O₃ + NO₂), PM₁₀, and PM_2.5. For this purpose, the annual and monthly averages from the Athens air pollution monitoring stations of Peireas (SO₂, CO, NO₂, NO_x), Patission (SO₂, CO, NO₂, NO_x), Aristotelous (PM₁₀, PM_2.5), Lykovrissi (PM₁₀, PM_2.5, O₃, O_x), and Liossia (O₃, O_x) in the selected periods of 2001–2004 and 2020–2023 were examined. There was a clear reduction in most air pollution parameters at all stations during the period examined, relative to the average values. The ozone and O_x values, presenting a high interannual variability, remained generally unchanged. The smallest reductions are observed for NO₂ and NO_X (about −10% to −20%), while the highest reductions are observed for SO₂, CO, and PM₁₀ (about −50% to −60%). The change in pollutant concentrations for every month of the year between the 2001–2004 and 2020–2023 time periods is also examined, and the observed seasonal differences are discussed. Full article

In recent years, ozone (O₃) pollution has become a prominent air quality concern in the Sichuan Basin (SCB). Based on surface O₃ measurements from 22 cities between 2015 and 2024, this study investigates the evolution of extreme O₃ pollution events and their underlying causes. While the average O₃ concentration, the number of affected cities, and the total O₃ pollution hours have all increased during the past decade, extreme O₃ concentrations have shown a significant decline since 2020. These trends suggest that O₃ pollution in the SCB has become more spatially extensive and less intense. Decomposition analysis attributed ~75% of the post-2020 decline in extreme O₃ concentrations to precursor emission reductions, with meteorological variability explaining the remaining ~25%. Satellite observations of formaldehyde (HCHO) and nitrogen dioxide (NO₂) column densities indicate a regional shift in O₃ formation regimes across the SCB, with many areas transitioning from VOC (volatile organic compound)-limited to transitional or NO_x (nitrogen oxide)-limited conditions. This shift likely contributed to the broader spatial extent and longer duration of O₃ pollution in recent years. Model sensitivity simulations and Integrated Reaction Rate (IRR) analysis demonstrate that reductions in precursor emissions, particularly NO_x, directly weakened daytime photochemical O₃ production and disrupted NO_x-driven radical propagation under transition and NO_x-limited conditions, collectively driving the observed decline in extreme O₃ concentrations. Full article

The increasing presence of synthetic dyes in aquatic environments presents a serious threat to ecosystems and human health. This study investigates the potential of natural biomaterials, specifically fish-derived components extracted from Cyprinus carpio (fish bladder and fish scales), for the simultaneous retention and degradation of a potentially toxic dye: Malachite Green (MG). The biomaterials were characterized using X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, thermogravimetric analysis (TGA), and high-performance liquid chromatography with mass spectrometry detection (HPLC-MS) for degradation monitoring. Batch adsorption experiments were conducted under varying biomaterial dosage, contact time and pH. Results demonstrated that all tested biomaterials exhibited significant adsorption capacities, with fish scales (FS) achieving a maximum removal efficiency of 91.2%, and fish bladder (FB) reaching 82% under optimal conditions. In catalytic ozonation tests, the fish scales impregnated with vanadium (FS-V) catalyst demonstrated significantly higher degradation efficiency, reaching 63.84% at an ozone flow rate of 0.5 g O₃·h⁻¹. The comparative analysis highlights the multifunctionality of these eco-friendly biomaterials, offering both pollutant capture and partial degradation. These findings suggest that low-cost, naturally derived biomaterials can serve as effective alternatives to synthetic adsorbents in water treatment applications, contributing to sustainable environmental remediation strategies. Full article

Advanced oxidation processes (AOPs) utilising a hydroxyl radical (•OH), a strong oxidant, are seen as a promising solution for removing hazardous and recalcitrant pollutants from waste streams. Among AOPs, non-thermal plasmas, especially pulsed corona discharge (PCD), enable the abatement of hazardous volatile organic compounds (VOCs) with high energy efficiency. This study demonstrates the viability of upscaling PCD technology with water sprinkling in degrading the VOC toluene using a semi-pilot scale plasma reactor. A toluene–air mixture was treated with varying gas-phase toluene concentrations (30–100 ppm) and pulse repetition frequencies (25–800 pps), achieving toluene removal of 5–55% in PCD and an additional 10–18% in PCO, as well as excellent toluene removal energy efficiencies from 9.0 to 37.1 g kW⁻¹ h⁻¹. The process design with water sprinkling provides additional advantages compared to dry reactors—the water surface serves as a source of hydroxyl radicals and scrubs the air from degradation by-products resulting from the incomplete oxidation of target pollutants. Transformation products of toluene were identified, and an oxidation pathway via hydroxylation of the aromatic ring was suggested as the major route towards ring-opening reactions. A photocatalytic oxidation reactor with TiO₂ catalyst plates, following PCD as a post-treatment, enabled additional removal of residual contaminants, also converting residual ozone to oxygen. The PCD reactor with water sprinkling and post-plasma photocatalysis shows promising results for upscaling the process. Full article

This study examined the temporal changes and dispersion of potential sources of the six criteria air pollutants, namely, particulate matter with an aerodynamic diameter of less than 2.5 and 10 μm (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃), in eastern Xinjiang, China, during the COVID-19 period in summer 2020 (16 July to 29 August ). Compared to the same periods in 2019 and 2021, the mean concentrations of all pollutants, except for SO₂ and O₃, and the air quality index (AQI) were lower in 2020 (relative changes: NO₂ 48.3–54.4%, PM₁₀ 35.8–49.6%, PM_2.5 19.3–43.5%, CO 16.5–34.8%, AQI 17.2–29.4%), which can be attributed to the reduced anthropogenic activities. Compared to the period before the lockdown in 2020 (16 June to 15 July), the mean NO₂ concentration showed the largest decrease during the lockdown (47.9%), followed by PM_2.5 (32.7%), PM₁₀ (37.6%), and CO (15.4%). In contrast, there were only minimal changes in O₃, with the mean concentrations falling slightly by 7.56%, and the mean concentration of SO₂ increased by 10.4%. The decrease in NO_x and the dry climate could have hindered O₃ formation, while vital industrial activities in eastern Xinjiang probably maintained SO₂ emissions. In the subsequent recovery period (30 August to 28 September), the mean NO₂ concentration increased the most at 59.3%, which was due to the rapid resumption of traffic-related emissions. During the lockdown in 2020, the diurnal profiles of PM_2.5, PM₁₀, NO₂, and CO concentrations showed lower peak concentrations in the morning (09:00–11:00) and evening (20:00–22:00), demonstrating a significant reduction in traffic-related emissions. The lower O₃ and higher SO₂ peak concentrations may have resulted from lower NO_x levels and higher electricity consumption due to the “stay-at-home” policy. The analysis of the distribution of potential sources showed that O₃ generally originated from widespread source areas, while the other pollutants mainly originated from local emissions. During the lockdown period, the source areas of PM_2.5 and PM₁₀ were more dispersed, with an enhanced contribution from long-range transport. Full article

Accurate prediction of the air quality index (AQI) is essential for environmental monitoring and sustainable urban planning. With rising pollution from industrialization and urbanization, particularly from fine particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃), robust forecasting tools are needed to support timely public health interventions. This study proposes a hybrid deep learning framework that combines empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) with two recurrent neural network architectures: long short-term memory (LSTM) and gated recurrent unit (GRU). A comprehensive dataset from Xitun District, Taichung City—including AQI and 18 pollutant and meteorological variables—was used to train and evaluate the models. Model performance was assessed using root mean square error, mean absolute error, mean absolute percentage error, and the coefficient of determination. Both LSTM and GRU models effectively capture the temporal patterns of air quality data, outperforming traditional methods. Among all configurations, the EEMD-GRU model delivered the highest prediction accuracy, demonstrating strong capability in modeling high-dimensional and nonlinear environmental data. Furthermore, the incorporation of decomposition techniques significantly reduced prediction error across all models. These findings highlight the effectiveness of hybrid deep learning approaches for modeling complex environmental time series. The results further demonstrate their practical value in air quality management and early-warning systems. Full article

This study couples a carbon quantum dot photocatalyst with a proton relay installed (EDTA-CQDs) for efficient hydrogen peroxide (H₂O₂) production with an ozone (O₃) system. In situ activation of O₃ is achieved by the photogenerated H₂O₂, which integrates the photocatalytic hydrogen peroxide production (PHP) and advanced oxidation processes (AOPs) to form a new photocatalytic peroxone (H₂O₂/O₃) system, achieving highly efficient solar-driven degradation of recalcitrant organic pollutants in landfill leachate without the addition of external H₂O₂. The composite system exhibits efficient degradation ability for various typical pollutants in landfill leachate, among which the degradation percentage of 100 mg L⁻¹ hydroquinone (HQ) reaches 97% within 30 min. This is due to the synergistic effects of O₃ oxidation, photoactivation of O₃, activation of O₃ by EDTA-CQDs, and activation of O₃ by in situ-generated H₂O₂. In the EDTA-CQD-based H₂O₂/O₃ system, free radicals can be dynamically regenerated after the addition of pollutants, achieving sustained and efficient degradation. Therefore, in the treatment of actual leachate, the removal percentages of COD, TOC, and UV254 are nearly 90%, 70%, and 55%, respectively, demonstrating the significant advantage of this system in treating high-concentration recalcitrant organic pollutants in wastewater of complex quality. Full article