Atmospheric Pollution Research最新文献

{"title":"Impact of sea-land breezes on a severe ozone pollution episode over the western Pearl River Estuary","authors":"Jianhua Mai ,&nbsp;Lingling Yu ,&nbsp;Tao Deng ,&nbsp;Yiheng Li ,&nbsp;Shenxiao Zhi ,&nbsp;Chengman Cai","doi":"10.1016/j.apr.2025.102611","DOIUrl":"10.1016/j.apr.2025.102611","url":null,"abstract":"<div><div>In this paper, the role of sea-land breezes in a severe ozone (O₃) pollution episode was studied. The analysis revealed that under the control of the periphery of Typhoon Nanmadol, Zhongshan City on the western coast of the Pearl River Estuary experienced severe O₃ pollution on 16 September 2022, with the daily maximum 8-h average O₃ concentration reaching 274 μg m⁻³. From morning to noon, rapid O₃ accumulation under intense solar radiation and weak northerly winds produced the first peak. During early evening hours, sea breezes occurred and initiated convergence with northerly synoptic winds over central Zhongshan. The recirculation factor of the V-component of ground winds decreased from 1.0 to 0.52, accompanied by an 86 % increase in net O₃ influx compared to the midday level. Concurrently, ventilation index below 1000 m altitude dropped by 58 %, driving secondary O₃ peaks at both ground level and boundary layer heights. After the occurrence of sea breezes, dominant updrafts generated negative vertical O₃ flux at ground. However, the vertical flux removal accounted for merely 4–13 % of horizontal O₃ influx, leading to the accumulation of ground O₃. Concurrent upward transport caused significant O₃ increases at 300 m and 400 m altitude by 49 μg m⁻³ and 45 μg m⁻³ respectively, markedly exceeding the concentration variations at 500–800 m layers.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102611"},"PeriodicalIF":3.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of machine learning algorithms in predicting indoor residential PM2.5 concentrations","authors":"Renato Camilleri ,&nbsp;Roy M. Harrison ,&nbsp;Noel J. Aquilina","doi":"10.1016/j.apr.2025.102609","DOIUrl":"10.1016/j.apr.2025.102609","url":null,"abstract":"<div><div>Recently Machine Learning (ML) has been amply used in environmental research for prediction purposes, but only a limited number of studies have been employed to predict indoor residential fine particulate matter, PM_2.5 concentrations. PM_2.5 can penetrate deep into the lungs and has been linked to respiratory and cardiovascular problems, with long term exposure associated with increased morbidity and mortality. The use of ML can provide a better estimate of residential PM_2.5 concentrations which usually is a significant contributor to personal exposure, especially for the elderly and those with pre-existing health conditions who tend to spend most of their time inside their homes. This study used ML algorithms (General Linear Model (GLM) with Lasso regularisation and Tree-based algorithms, RF and XGBoost) to predict indoor PM_2.5 concentrations at six-hourly averages in the Maltese Islands using outdoor residential PM concentrations and several meteorological parameters. Continuous PM sampling using aerosol spectrometers was carried out at six non-smoking residences in Malta and Gozo. A repeated 10-fold cross-validation was carried out on the training dataset, with hyperparameter tuning using grid search. Hyperparameter tuning used the Root Mean Square Error (RMSE) as the evaluation metric. Five sampling sites showed low indoor PM contributions and the GLM for these sites showed good performance indicators for the testing data, but serial correlation at lag-1 was recorded. For these sites, RF and XGBoost showed very good performance indicators with an Index of Agreement (IOA) of 0.92 and 0.93, respectively, with the most important predictor variable being the outdoor PM₁ fraction. The RF regression model gave the lowest RMSE (30.65 μg m⁻³) and the highest index of agreement (IOA) (0.66) when the models were tested with the data from all sampling sites, which included a site with a PM_2.5 I/O ratio of 5.2, where the high indoor PM generation was primarily associated with emissions from cooking and the indoor relative humidity was suggested as a good predictor variable for such a scenario. This study showed the significant impact of outdoor PM₁ on indoor PM_2.5 levels at sites with limited indoor fine PM sources. At sites with significant indoor generation from cooking, indoor PM_2.5 was 3.6 times the short-term (24-h) AQG of the WHO, indicating that regulations on extraction systems for domestic kitchens would minimise very high exposures of home dwellers to indoor fine PM.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102609"},"PeriodicalIF":3.9,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air pollution prediction with advanced preprocessing and deep ensemble learning","authors":"Gaurav Narkhede ,&nbsp;Mustafa Poonawala ,&nbsp;Atharva Sonawane ,&nbsp;Anil Hiwale ,&nbsp;Arvind R. Singh","doi":"10.1016/j.apr.2025.102610","DOIUrl":"10.1016/j.apr.2025.102610","url":null,"abstract":"<div><div>The research presented investigates the impact of model selection and preprocessing techniques on air pollution prediction performance, particularly pertaining to achieving Sustainable Development Goals (SDGs). Accurate training of predictive models necessitates effective handling of missing or null values in environmental datasets. To address this challenge, Probabilistic Principal Component Analysis (PPCA) and the Extra Tree Regressor for data imputation are employed, followed by scaling using Robust Scaler, Min-Max Scaler, and Standard Scaler. A thorough comparison of these preprocessing methods revealed that PPCA is the most suitable choice for imputing missing values in air quality datasets, while the Robust Scaler provided the most reliable and accurate scaling. Additionally, Stochastic Gradient Descent (SGD) is integrated as an optimization technique to enhance model performance. The Weighted Average ensemble method, combining PPCA imputation and Robust Scaler, demonstrated superior predictive capabilities. This research highlights the potential for further improvements through additional ensemble techniques and model optimization strategies, opening avenues for future research focused on improving prediction precision and advancing the achievement of Sustainable Development Goals linked to environmental sustainability.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102610"},"PeriodicalIF":3.9,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chemical characteristics and source apportionment of water-soluble ions in precipitation in Harbin, China","authors":"Pengyu Chen ,&nbsp;Xiaoyu Qu ,&nbsp;Zihan Song ,&nbsp;Zhaoyang Jia ,&nbsp;Fuxiang Zhang ,&nbsp;Song Cui","doi":"10.1016/j.apr.2025.102604","DOIUrl":"10.1016/j.apr.2025.102604","url":null,"abstract":"<div><div>Precipitation can effectively scavenge atmospheric pollutants, making precipitation chemistry a crucial indicator for tracing anthropogenic impact on air quality. In this study, we collected a total of 99 precipitation samples in Harbin, a megacity in Northeast China, spanning the period from November 2021 to October 2023, and analyzed precipitation pH as well as concentrations of elemental carbon (EC) and major water-soluble ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, NH₄⁺, NO₃⁻, SO₄²⁻, Cl⁻, and F⁻). Our findings revealed that the equivalent concentrations of total water-soluble ions ranged from 40.0 to 1225.2 μeq·L⁻¹, with a volume weighted mean (VWM) concentration of 264.9 μeq·L⁻¹. NO₃⁻, Ca²⁺, NH₄⁺, and SO₄²⁻ were identified the dominant ions in precipitation, collectively accounting for 86.7 % of the total water-soluble ions. The concentrations of most ions in precipitation were elevated by a factor of 1.2–3.6 during the heating period compared to those in the non-heating period. The sources of water-soluble ions were determined through combined analyses involving enrichment factors, positive matrix factorization (PMF), and backward trajectories, which revealed that Ca²⁺, K⁺, and Mg²⁺ were primarily originated from crustal sources, Na⁺ and Cl⁻ from marine sources, and SO₄²⁻ and NO₃⁻ from anthropogenic sources. Furthermore, contributions to water-soluble ion levels in precipitation were attributed to crustal dust deposition (29.8 %), biomass combustion and agricultural activities (26.0 %), as well as fossil fuel combustion (22.0 %). The potential source regions of water-soluble ions in precipitation were identified as cities and regions located northwest, southwest, and south of Harbin. The knowledge gained from this study provides critical information necessary for formulating future pollution control policies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102604"},"PeriodicalIF":3.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between air pollution and obstructive sleep apnea in terms of respiratory event frequency and lung-to-finger circulation time","authors":"Rachel Chien ,&nbsp;Zhihe Chen ,&nbsp;Peizheng Wang ,&nbsp;Wen-Te Liu ,&nbsp;Ying-Ying Chen ,&nbsp;Yen-Ling Chen ,&nbsp;Arnab Majumdar ,&nbsp;Jiunn-Horng Kang ,&nbsp;Kang-Yun Lee ,&nbsp;Wun-Hao Cheng ,&nbsp;Yi-Chih Lin ,&nbsp;Cheng-Jung Wu ,&nbsp;Yi-Chun Kuan ,&nbsp;Hsin-Chien Lee ,&nbsp;Cheng-Yu Tsai","doi":"10.1016/j.apr.2025.102603","DOIUrl":"10.1016/j.apr.2025.102603","url":null,"abstract":"<div><div>Air pollutant exposure has been shown to exacerbate obstructive sleep apnea (OSA) manifestations, such as increased respiratory episodes and intermittent oxygen desaturation. However, most studies have focused on episode frequency rather than duration. This study investigated the associations between air pollution and OSA manifestations using both frequency-based indices and the duration-based marker lung-to-finger circulation time (LFCT). Polysomnography data from 820 individuals with suspected OSA (mild-to-moderate: n = 224; severe: n = 596) were analyzed. Sleep disorder indices included the apnea–hypopnea index (AHI), oxygen desaturation index (ODI), arousal index, and mean LFCT. A novel composite metric, respiratory event response time area (RERTA), defined as the square root of the product of LFCT and AHI, was introduced to evaluate the interplay between frequency and duration. Air pollutant exposure was estimated using data from monitoring stations within 4 km of the registered residences of the study cohort. Multivariable Poisson regression models were employed to assess short-term (1-month) and long-term (1-year) exposure effects. Short-term PM_2.5 and NO₂ exposure were significantly associated with increased AHI, ODI, arousal index, and reduced LFCT. Long-term exposure to PM_2.5, PM₁₀, and NO₂ was associated with increased AHI and ODI, while PM_2.5 and PM₁₀ were linked to reduced LFCT. Both short- and long-term O₃ exposure were associated with increased AHI and ODI. PM_2.5 and O₃ (short-term) were positively associated with RERTA. These findings suggest that air pollution exacerbates OSA by increasing episode frequency and accelerating compensatory responses, thereby elevating cardiopulmonary burden as reflected by RERTA.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102603"},"PeriodicalIF":3.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidating size-resolved levels, characteristics, and processes of carbonaceous aerosols (CA) in an urban atmosphere","authors":"Yasarapu Sathish ,&nbsp;Abhishek Chakraborty ,&nbsp;Shruti Tripathi","doi":"10.1016/j.apr.2025.102602","DOIUrl":"10.1016/j.apr.2025.102602","url":null,"abstract":"<div><div>An Anderson Cascade Impactor (ACI) was utilised in an urban coastal area of Mumbai to collect size-resolved particulate matter (PM) during winter and summer. This study aims to provide insights into size-resolved composition, characteristics and processes of organic aerosols in a coastal and tropical environment, which is scarce in the available literature. Collected samples were analysed for organic (total and soluble) and elemental carbon levels, and volatility using thermal-optical and total carbon analyzers. OC peaked at 0.65–1.1 μm in both seasons, indicating formation via gas-to-particle condensation. EC showed a peak at 0.43–0.65 μm, characteristic of vehicular emissions. Peak OC concentrations were 12.22 ± 3.65 μg/m³ in winter and 3.14 ± 2.87 μg/m³ in summer. For EC, peak concentrations were 3.39 ± 1.14 μg/m³ in winter and 3.14 ± 1.87 μg/m³ in summer. Most samples showed OC/EC ratios &gt;2, indicating significant secondary organic carbon (SOC) contribution to OC. The SOC/OC ratio in PM2.1 was higher in summer (9.84 ± 3.14) than in winter (4.21 ± 1.45), likely due to enhanced photochemical activity and ozone levels. The most abundant volatility-based OC-EC fractions were OC2, OC4 and EC1, indicating major contribution of vehicular emissions to PM mass. Char-EC/soot-EC ratios varied significantly (1–16) based on size and seasons indicating influence of various sources. Anthropogenic VOCs showed good correlation with SOC at certain sizes and seasons. This study shows that size-resolved carbonaceous aerosol (CA = EC + OM) contributes significantly to all PM sizes and to improve air quality, targeted approach based on various contributing processes and precursors of CA are needed.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102602"},"PeriodicalIF":3.9,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neighborhood ozone estimation in Busan, South Korea: A comparative study of proximity-based ensemble clustering and machine-learning models","authors":"Ahmad Daudsyah Imami ,&nbsp;Jurng-Jae Yee","doi":"10.1016/j.apr.2025.102601","DOIUrl":"10.1016/j.apr.2025.102601","url":null,"abstract":"<div><div>Busan is one of the southernmost metropolitan areas with the highest ozone pollution levels influenced by urban development and specific coastal meteorological conditions. The study present Cluster-Based Ensemble Regression (CBER), which consist of two-stage workflow which are benchmarking stage (Pre-CBER) and operational stage (CBER). During Pre-CBER, six machine-learning algorithms were compared, and multiple unsupervised-learning techniques were evaluated in parallel to cluster stations with similar meteorological characteristics and ozone patterns. Hyper-parameter-tuned XGBoost emerged as the most accurate regressor (RMSE = 3.69 ppb, R² = 0.95). Nine clustering scenarios were assessed with the Silhouette score, ultimately retaining solutions based on both centroid based and density based clustering. In the CBER phase, XGBoost models were trained within each shortlisted cluster scenario and validated through leave-one-station-out tests. KNN based Meteorological Regionalization preserved fine-scale variability, sustaining R² &gt; 0.90 and RMSE &lt;7 ppb in 12 of 14 clusters, while still achieving R² averagely 0.75–0.80 in the emissions-intensive port and mountainous northeast. SHAP interpretation ranked nitrogen dioxide, temperature, solar radiation, and diurnal timing as dominant predictors. The computationally light, transparent pipeline thus converts sparse monitoring into hourly subdistrict ozone maps, providing actionable decision for Busan and other coastal cities with limited AQMS networks.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102601"},"PeriodicalIF":3.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on vehicle evaporative emission characteristics and purge strategy based on China VI measurement methods","authors":"Zihan Chen ,&nbsp;Xin Zhang ,&nbsp;Qiang Chen ,&nbsp;Ren He","doi":"10.1016/j.apr.2025.102608","DOIUrl":"10.1016/j.apr.2025.102608","url":null,"abstract":"<div><div>In this study, several experiments were conducted based on China VI measurement methods to analyze the vehicle evaporative emission characteristics and purge strategy. The results showed that the diurnal breathing emissions from the atmospheric fuel system were 157.2 mg, with 88.5 % of the carbon canister bleeding emissions, and the main species emitted were alkanes. The diurnal breathing emissions from the sealed fuel system were 82.2 mg, with 97.1 % of the permeation emissions, and the main species emitted were aromatic and alkane hydrocarbons. There is a significant negative correlation between the vehicle refueling emission and the adsorption capacity of the carbon canister, but no significant correlation with the purge volume. The carbon canister refueling working capacity (ORVR BWC) is only 53 %–72 % of the regular working capacity (BWC). Tires, interior and exterior trims are the main background emission sources of the vehicle, accounting for 29 % and 25.1 % respectively. Baking pretreatment is an effective way to reduce background emissions. Compared to gasoline vehicles, hybrid electric vehicles (HEVs) equipped with atmospheric fuel systems compensate for the lack of purge time by increasing the purge rate. Vehicles equipped with sealed fuel systems can be freed from reliance on the purge strategy. It is a technological trend for vehicles to be equipped with sealed fuel systems, and future evaporative emission control should focus on permeation emissions, refueling emissions and background emissions.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102608"},"PeriodicalIF":3.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144221049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methodology development for high-resolution monitoring of emissions in urban road traffic systems","authors":"Edgar Lorenzo-Sáez ,&nbsp;Javier F. Urchueguía ,&nbsp;Miguel García Folgado ,&nbsp;Jose-Vicente Oliver-Villanueva","doi":"10.1016/j.apr.2025.102600","DOIUrl":"10.1016/j.apr.2025.102600","url":null,"abstract":"<div><div>Transport sector is a major contributor to greenhouse gas (GHG) emissions and air pollution, especially in cities. Mitigating these emissions is crucial for both climate change and public health, but current emission quantification methodologies lack sufficient resolution at the urban level to apply efficient measures. This gap is addressed by developing a novel temporal and spatial high-resolution methodology to monitor traffic-related emissions based on real-time traffic data gathered from induction loops installed in road networks.</div><div>The methodology integrates vehicle fleet characteristics, emission factors, and traffic intensity to quantify street-level emissions per hour. This bottom-up approach allows for detailed monitoring of pollutants across specific locations and times.</div><div>Applied to Valencia, Spain, the methodology enabled the identification of emission hotspots and the detailed assessment of local mitigation strategies. As a case study, the impact of a newly implemented bike lane was analyzed, demonstrating the method's effectiveness in evaluating sustainable mobility measures and their influence on traffic emissions. This tool provides city planners and policymakers with a robust, data-driven framework to reduce urban emissions and enhance air quality.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102600"},"PeriodicalIF":3.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144220850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current-use pesticides in ambient air - evaluation of deposition sampling and soil fugacity techniques","authors":"Ludovic Mayer ,&nbsp;Lisa Melymuk ,&nbsp;Jakub Vinkler ,&nbsp;Petr Šenk ,&nbsp;Marek Šudoma ,&nbsp;Petra Přibylová ,&nbsp;Céline Degrendele ,&nbsp;Gerhard Lammel","doi":"10.1016/j.apr.2025.102606","DOIUrl":"10.1016/j.apr.2025.102606","url":null,"abstract":"<div><div>The atmospheric fate of current-use pesticides (CUPs) is incompletely understood, and CUPs' air-surface mass exchange has hardly been investigated. In this study, we evaluated techniques to improve our understanding of CUPs’ depositions and volatilisation from soil. Simultaneous sampling of gas-phase air, particulate phase air, wet and dry depositions, soil, and air equilibrated with soil was conducted during the pesticide application season, followed by analysis of 46 CUPs (22 herbicides, 16 insecticides and 12 fungicides) common in European agriculture. CUP deposition fluxes observed suggest that dry deposition of most CUPs is more effective than wet deposition in central Europe. Potential soil fugacity derived from CUP concentration in soil indicated the significance of soil organic matter on the absorption and retention of CUPs in soil. Using a fugacity meter, empirical evidence for net volatilisation of CUPs including the high-risk pesticides chlorpyrifos and pendimethalin from a non-agricultural soil is found for the first time. This suggests that CUPs can be subject to multiple emission-deposition cycles, which enhances their long-range transport potential. More method refinements and field measurements are needed for a mechanistic understanding of diffusive soil-air exchange processes.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102606"},"PeriodicalIF":3.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}