Atmospheric pollution is associated with microbial community stability and functional diversity in river ecosystems.

Spatiotemporal non-stationarity and heterogeneity in atmospheric aerosol pollution regulation by subtropical urban green space: A GTNNWR-Based study in Shenzhen, China.

Legacy perfluoroalkyl acids and emerging perfluoroalkyl ether carboxylic acids in the atmosphere of Laizhou Bay estuaries: Occurrence, gas-particle partitioning, and potential sources.

Decomposition and forecasting of concentrations of highly volatile atmospheric pollutants in plateau cities based on the VMD-CNN-BiLSTM framework

18–26 years: A critical window for synergistic reduction of atmospheric pollutant and greenhouse gas emissions

Explosive PM2.5 growth and health effects during extreme haze in Shanghai, China: Insights from surface and vertical observations.

ABSTRACT Mineralogical and textural characterization of the natural stone in Cádiz Cathedral reveals a diverse range of carbonate lithologies with varying fabrics, porosity and decay susceptibility. The white oolitic limestone was identified as the most vulnerable material, particularly in upper structural elements such as vaults and roofs. Results confirm a significant marine influence on weathering processes, evidenced by the ubiquitous presence of halite, trona, gypsum, and nesquehonite across all lithologies and mortars. These salts drive granular disintegration, exfoliation, and crust formation. Their origin is attributed to a combination of marine spray, capillary rise, and the historical use of brackish water in mortar preparation. Analysis of pink crusts and saline efflorescences indicates complex interactions between environmental factors, atmospheric pollutants, and previous restoration materials. Mortar samples display high heterogeneity; modern interventions notably utilized Portland-type cements and historical pigments like lead white, which are often incompatible with original substrates. In the short term, the integration of microclimatic sensor networks with materials analysis will facilitate data-driven decision-making for the building’s preservation and, continued sampling will be essential to monitor salt dynamics in response to shifting temperature and humidity trends associated with climate change and the influx of tourists to the monument.

The accumulation of atmospheric and industrial pollution of high-voltage insulators is one of the frequent problems and a pattern of failures in transmission systems. In this paper, a two-phase approach based on deep learning is proposed for the detection of pollution of high-voltage insulators. The proposed approach automatically detects three types of pollution (salt, soot and excrement) based on UAV images. In addition to detection, the classification of pollution is automatically done into three levels (low, medium and high pollution). In the first phase, the You Only Look Once (YOLO) detector is used for precise detection and isolation of insulators, where an average accuracy of mAP@0.5 of 93.75% is achieved. The model was trained on a Merged Public Insulator Dataset (MPID) database containing over 5000 insulators. The second phase utilizes the Zenodo dataset, which contains over 14,000 synthetic insulator images. In the second phase, the model was trained using the EfficientNet-B0 convolutional network to classify the type and level of pollution. In order to solve the problem of real data, fine-tuning was done for all 10 classes. The results show that the accuracy is 88% on a partial classification of 10 levels of pollution. When using 4 levels of pollution, the model achieves an accuracy of 91%. Additional automation was achieved with priority metrics, which by analyzing 100 images showed 24% of critical cases. The system determines the cleaning priority based on the pollution intensity, ensuring that critical cases are addressed first. A comparative analysis was performed when the model was trained with MobileNetV2, ResNet16 and VGG. The results show that the proposed model with the highest recall minimizes the risk of missed critical insulators. For example, in real-world applications, MobileNetV2 has a larger difference, which means too many false positives, while ResNet18 has a smaller difference, which means more false negatives which is a security risk.

Sulfur dioxide (SO2) is a major atmospheric pollutant as well as an indispensable chemical raw material for the synthesis of sulfuric acid and fine chemicals. From the perspectives of efficiency, ecology, and economy, the catalytic SO2 conversion into high value-added chemicals is particularly fascinating, while developing robust catalysts capable of efficiently activating and converting SO2 remains extremely challenging. Herein, we report the rational construction of a single-site Cu(II)-anchored covalent-organic framework (COF), COFbpy-CuBr2, for the highly efficient catalytic conversion of SO2. The COFbpy-CuBr2 showed multiple favorable SO2 adsorption sites within the framework, including OSO···Cu, O2S···π, and OSO···N contacts, thus exhibiting remarkable SO2 selectivity and excellent SO2 adsorption capacity of 10.98 mmol/g at 298 K and 1 bar. The strong Cu-SO2 interactions promoted the enrichment of SO2 at the catalytic center, further facilitating the SO2 insertion in the coupling with aryl diazoniums and alcohols, thus enabling the highly efficient conversion into sulfonate esters. Moreover, COFbpy-CuBr2 could be applied to the late-stage functionalization for the gram-scale synthesis of a biologically active coumarin derivative. Mechanism investigations revealed a Cu(II)-catalyzed radical pathway for this catalytic process. This work provides a novel paradigm for the rational construction of next-generation COFs to achieve highly efficient and selective SO2 catalytic conversion.

Atmospheric heavy metals are persistent, bioaccumulative, and toxic pollutants capable of long-range transport, posing significant ecological and public health risks. This review synthesizes five decades of research (1973–2024) on emission sources, transport mechanisms, deposition pathways, and monitoring approaches, supported by a bibliometric analysis of 1642 Scopus-indexed articles. Anthropogenic activities, including industrial operations, mining and smelting, vehicular emissions, and agricultural inputs, remain dominant contributors, while volcanic eruptions, geothermal activity, sea-spray aerosols, and soil-dust resuspension constitute important natural sources. Once emitted, metals associate with particulate matter (e.g., PM2.5, PM10), undergo atmospheric circulation, and are deposited through dry and wet processes, enabling transfer from urban centers to agricultural systems and remote environments. Urban areas exhibit the highest deposition loads, agricultural landscapes show substantial foliar uptake, and remote ecosystems display clear signatures of transboundary transport. Advances in analytical and biomonitoring techniques, including Atomic Absorption Spectroscopy, Inductively Coupled Plasma Mass Spectrometry, X-Ray Fluorescence, and moss-based bioindicators, have improved detection sensitivity. Mosses enhance sensitivity by acting as natural, long-term integrators of atmospheric deposition: their high surface-area-to-mass ratio, absence of cuticles and root systems, and direct uptake from precipitation and aerosols enable efficient accumulation of trace metals, revealing low-level and chronic deposition signals often missed by short-term instrumental air sampling. Bibliometric results reveal exponential growth in publications and strong collaboration networks centered in Asia, Europe, and North America, with underrepresentation in Africa, South America, and Central Asia. Key research gaps include limited long-term health assessments; insufficient real-time and low-cost monitoring technologies; low-resolution source apportionment; and minimal attention to emerging contaminants globally.

Asthma is one of the most prevalent chronic respiratory diseases in childhood, representing a major global public health challenge. It results from complex interactions between genetic predisposition and environmental factors, particularly exposure to air pollutants. This study aimed to review the scientific evidence on the pathophysiology, clinical manifestations, and environmental determinants of childhood asthma, emphasizing its relationship with atmospheric pollution in Santos, São Paulo. A narrative literature review was conducted, complemented by secondary epidemiological data from DATASUS, CETESB, and municipal epidemiological bulletins. The analysis integrated international and national findings, highlighting the influence of fine particulate matter (PM₂.₅ and PM₁₀) and ozone (O₃) on the frequency and severity of asthma exacerbations. Evidence indicates that air pollution acts as a major aggravating factor, contributing to higher rates of hospitalization and decreased quality of life in children. The study reinforces the importance of preventive environmental policies and continuous monitoring of air quality to mitigate the burden of pediatric asthma.

Urban green infrastructure is increasingly recognized as a core component of urban sustainability, providing regulating ecosystem services (ES) that support climate resilience, environmental quality, and long-term urban livability. However, empirical evidence on the long-term stability of ecosystem services (ES) in rapidly urbanizing cities remains limited. Despite widespread assumptions that urbanization inevitably leads to irreversible ecological decline, few studies have quantitatively examined whether ES can persist, or even recover, over multi-decadal time horizons relevant to sustainable urban development. This study investigates the long-term trajectories of eight urban ES in Seoul, South Korea, across nearly five decades (1978–2025) and eight congressional districts, providing one of the longest temporal assessments of urban ES in East Asia. Using i-Tree Canopy and high-resolution aerial imagery across four benchmark years (1978, 1989, 2010, 2025), this study quantified standardized indicators for carbon sequestration (CSeq), avoided runoff (AVRO), and removal of six atmospheric pollutants (O3, NO2, SO2, CO, PM10, PM2.5). Paired-sample t-tests and Cohen’s dz (effect size) were used to assess within-district temporal shifts and the magnitude of ecological change. Results reveal a pronounced period of early ecological stress during rapid industrialization (1978–1989), with negative standardized effect sizes across all services (dz between −0.65 and −0.72). However, these early losses were not sustained. Structural services such as CSeq and AVRO exhibited long-term functional stability, with effect sizes converging toward zero and the 1978–2025 change in CSeq showing no statistical difference (p = 0.784). Pollutant removal services followed an early-decline–followed-by-recovery trajectory, exemplified by CO removal shifting from a large early decline (dz = −0.72) to a modest positive effect in later decades dz = 0.31). These findings indicate that Seoul’s sustained urban greening and environmental policies were effective in preventing further deterioration and maintaining core ecological functions, even if they produced stabilization rather than significant long-term gains in ES delivery.

To enhance the technical support of soil environmental quality monitoring services for territorial spatial planning and the sustainable development of ecological civilization in the Beijing Municipal Administrative Center， this study systematically investigated the changes in heavy metal contamination status and sources in the soils of Tongzhou District over the past two decades. Using inverse distance weighted （IDW） spatial interpolation， the geo-accumulation index， the single-factor pollution index， and the Nemerow comprehensive pollution index， this study conducted a sectional evaluation of the spatial distribution and accumulation characteristics of eight heavy metal elements （As， Cd， Cr， Cu， Hg， Ni， Pb， and Zn） in the soils of Tongzhou District from 2005 to 2023. Correlation analysis， principal component analysis （PCA）， and the positive matrix factorization （PMF） model were employed to identify the principal components and source contributions of heavy metals. The results showed that the concentrations of Cr， Cu， Ni， Pb， and Zn exhibited minimal variation across the four selected years （2005， 2011， 2018， and 2023）， while the median values of Cd， Hg， and Zn exceeded the background values of Beijing. The concentrations of Cd and Hg in top soil were significantly higher than those in deeper layers， with the proportion of Cd enriched sites showing a decreasing trend over the years， whereas Hg exhibited strong spatial heterogeneity. From 2005 to 2011， Cd， Hg， Cu， and Pb were highly enriched in areas with intense industrial activities， incineration sources， and traffic emissions. In 2018， high concentrations of Cd， Zn， Cu， and Pb were primarily distributed in the central and eastern agricultural lands of the study area. Compared to that in 2005， the enrichment extent of Cd， Hg， Cu， Pb， and Zn in 2023 was significantly reduced. In 2005， As， Cr， Cu， Ni， Pb， and Zn mainly originated from natural/agricultural mixed sources， while in 2011， these elements were primarily derived from natural， traffic， and agricultural mixed sources. Cd was mainly associated with industrial sources in both 2005 and 2011. In 2018 and 2023， As， Cr， Cu， Ni， and Pb were predominantly attributed to natural， traffic， and agricultural mixed sources， whereas Cd and Zn were mainly from industrial sources. Hg in soil across all four years was primarily derived from atmospheric deposition. Key factors influencing variations in source contributions included land development intensity， agricultural fertilization rates， traffic emissions， the scale of industrial pollution enterprises， energy combustion emissions， and overall atmospheric pollution levels.

Halomethanes (CH3X, where X = F, Cl, Br) are potent atmospheric pollutants, and their removal via adsorption on activated carbons (ACs) is a critical remediation strategy. However, the molecular-level influence of AC surface chemistry on adsorption, especially under realistic environmental conditions, is not fully understood. This work utilizes Grand Canonical Monte Carlo (GCMC) simulations to investigate the adsorption of CH3F, CH3Cl, and CH3Br on realistic carbon models, comparing unfunctionalized graphitic surfaces (AC0) with surfaces functionalized with alcohol (AC1), carbonyl (AC2), and carboxyl (AC3) groups. We analyze the process for both pure components and in realistic mixtures (Quarantine and Pre-Shipment concentrations). Our findings reveal a critical inversion in adsorption preference. For pure components, CH3Br adsorption is highest on the unfunctionalized (AC0) surface, driven by strong adsorbate–adsorbate interactions leading to condensation, characterized by a rising isosteric heat of adsorption (Qst≈35–45 kJ/mol) that matches the enthalpy of sublimation. Conversely, in realistic humid mixtures, the pristine surface suffers a capacity collapse (>90% loss). The functionalized surfaces (especially AC3) demonstrate superior performance, exhibiting a thermodynamic selectivity of SCH3Br/Air>100 (compared to S≈15 for AC0) and retaining approximately 60% of their dry-condition affinity. This study elucidates the distinct roles of surface chemistry and intermolecular forces, providing a molecular basis for designing carbon materials optimized for high selectivity in complex environmental gas streams.

The article describes the current state monitoring system in the field of air protection in Ukraine. This monitoring system is aimed at ensuring environmentally friendly air. In the city of Vinnytsia, this system includes the laboratory for monitoring atmospheric air pollution of the Vinnytsia Regional Center for Hydrometeorology, which carries out constant laboratory monitoring of the state of atmospheric air pollution in the city of Vinnytsia at two stationary pollution monitoring posts. The existing network of PSZ does not provide a full assessment of the state of atmospheric air pollution, due to the low frequency of measurements in manual mode. Since 2023, EcoCity air monitoring stations have been installed and started operating in Vinnytsia. These air monitoring stations allow city residents to monitor changes in air quality in the city in real time and maintain a conscious attitude to environmental problems. The work analyzes the operation of the pollutant emission monitoring system in the city of Vinnytsia. Priority measures are proposed to ensure an accessible and environmentally friendly environment for residents of the city of Vinnytsia.

In South Asia, smog has become a critical environmental concern that endangers public health, ecosystems, and the regional climate. To determine the primary causes of smog formation in Lahore during peak polluted months (October and November), the current study develops a dual analytical framework that combines cutting-edge machine learning with sector- and pollutant-specific emission analysis. To assess their relationship with Air Quality Index (AQI) and create a high-accuracy predictive model, meteorological factors and emission data from key sectors are used to build Random Forest and extreme gradient boosting (XGBoost) models. The current study evaluates the joint effects of weather and emission loads on AQI variability by integrating atmospheric dynamics with comprehensive emission profiles. The XGBoost model forecasts important pollutants from the transportation, industrial, and agricultural sectors, including carbon dioxide (CO2), oxides of nitrogen (NOx), Volatile Organic Compounds (VOCs), and particulate matter, in the second analytical tier. Particulate matter (PM), NOx, and transport-related pollutants are consistently identified by the models as the primary predictors of AQI, with high prediction performance. Furthermore, a 3-fold split is used for cross-validation, making sure that each fold maintained the data’s chronological order to avoid leakage. The model has modest root mean square error (RMSE) levels (4.32 and 8.14) and high coefficient of determination (R2) values (0.93–0.99). Approximately 90% of Lahore’s annual emissions resulted from the transportation sector. These results offer aid to policymakers to anticipate air quality, identify important emission sources, and execute targeted initiatives to minimize smog and promote a healthier urban environment. The current study also helps in analyzing the causes of atmospheric and sectoral pollution. While the study captures smog dynamics during peak pollution months, its temporal scope is limited, and finer spatial measurements could further improve the generalizability of the results.

Halogen radicals have long been recognized for their role in depleting ozone in the stratosphere and in polar and pristine maritime boundary layers. Over the past 2 decades, an expanding body of research has highlighted the significant influence of halogen radicals on atmospheric chemistry and air quality degradation in anthropogenically impacted maritime and continental regions. This article reviews recent advances in the study of reactive halogens in polluted environments, with a particular focus on China, covering atmospheric observations, emission sources, chemical transformations, and the effects on atmospheric oxidation processes and the levels of ozone and secondary aerosol. Key recent findings include: (1) the widespread detection of photolabile halogen gases such as ClNO2 and dihalogens across various locations; (2) the substantial impact of halogen radicals, particularly those derived from elevated daytime Cl2, on VOC oxidation, the HOx budget, and the concentrations of ozone and secondary aerosol; (3) significant progress in identifying anthropogenic sources and chemical activation pathways for chlorine and bromine; and (4) the underrepresentation of daytime halogen activation processes in mainstream chemical transport models, leading to a likely underestimation of their atmospheric impacts. Future research efforts should include (1) conducting comprehensive and updated field measurements of halogens in diverse and changing environments and targeting emerging halogen, (2) improving understanding of sources and chemical cycles of halogen species, and (3) enhancing the capability of air quality models in simulating reactive halogen impact in polluted regions.

Under the fast development of urbanization, PM2.5 pollution has become a prominent issue affecting the urban ecological environment and residents’ health. To investigate the impact of urban landscape patterns on PM2.5 concentrations, this study applies the Local Climate Zone (LCZ) classification to Shanghai using the World Urban Database and Access Portal Tools (WUDAPT). LCZ-derived landscape metrics are adopted as predictor variables to focus on how urban form and spatial configuration affect PM2.5 distribution and to identify the key landscape categories and types influencing PM2.5 levels. The results reveal notable seasonal and spatial differences in the effects of different LCZ types and landscape metrics on PM2.5 concentrations; on average, over 69% of the spatial variation in PM2.5 across the four seasons can be explained by the Multi-scale Geographically Weighted Regression (MGWR) model. This research demonstrates that the LCZ framework effectively uncovers the seasonal and spatial mechanisms by which urban landscape patterns influence PM2.5 concentrations in Shanghai. It offers a novel perspective for understanding the interplay between urban landscape and atmospheric pollution, and provides scientific guidance for sustainable urban planning and precise air pollution control strategies in other cities.

Global meta-analysis unravels mechanistic shifts in plant growth and physiological adaptability under nitrogen dioxide modulation.

Heating-season dynamics of the airborne microbiome, resistome and mobilome in Belgrade, Serbia.