Atmospheric Pollution Research最新文献

{"title":"Real-time nowcasting of NO2 products from geostationary environment monitoring spectrometer using a conditional generative adversarial network","authors":"Jeong-Eun Park ,&nbsp;Yun-Jeong Choi ,&nbsp;Goo Kim ,&nbsp;Sungwook Hong","doi":"10.1016/j.apr.2025.102631","DOIUrl":"10.1016/j.apr.2025.102631","url":null,"abstract":"<div><div>In East Asia, megacities like Seoul, Tokyo, and Shanghai frequently recording high nitrogen dioxide (NO₂) concentrations due to traffic and industrial activity require urgent efforts to enhance short-term monitoring and forecasting systems. This research presents a deep-learning (DL) model for nowcasting atmospheric NO₂ concentration products derived from the geostationary environment monitoring spectrometer (GEMS) on the Geo-Kompsat-2B satellite from 1-h to 3-h. The DL model utilizes pairs of GEMS NO₂ products as input and output datasets. The nowcasting DL model was developed using a data-to-data (D2D) translation method incorporating conditional generative adversarial network techniques. The D2D-nowcast NO₂ model was trained and tested for 1, 2, and 3-h predictions. The test results of the D2D model demonstrated excellent statistical performance, including a correlation coefficient of 0.805, a root-mean-square error of 0.162 ⨉ 10¹⁶ molecules/cm², and a bias of 0.046 ⨉ 10¹⁶ molecules/cm² for the 3-h prediction. Furthermore, the D2D-nowcast NO₂ concentrations were validated using the Tropospheric Monitoring Instrument and Pandora NO₂ measurements, demonstrating high agreement. Consequently, this study aims to support real-time operational monitoring by supplementing temporal gaps in satellite observations without relying on numerical models and provides valuable supplements for decision-making by air quality forecasters.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102631"},"PeriodicalIF":3.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329527","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":"Reconstructing top-down global black carbon emissions using remote sensing and models","authors":"Shuo Wang ,&nbsp;Luoyao Guan ,&nbsp;Jason Cohen ,&nbsp;Kai Qin","doi":"10.1016/j.apr.2025.102633","DOIUrl":"10.1016/j.apr.2025.102633","url":null,"abstract":"<div><div>Black Carbon (BC) is both an absorbing component and air pollutant that significantly impacts environment, climate, and human health. Currently, the monitoring of BC emissions relies primarily on bottom-up inventories, which often lack spatial and temporal validation or verification from satellite-based observational platforms. This gap limits our understanding of BC's concentration and variability over time and space. This study reconstructs a BC emission inventory based on separate bottom-up and top-down Kalman Filter estimations from 2002 to 2009 yielding a variable enhancement factor in different areas. EOF (Empirical Orthogonal Function) is employed to identify 9 unique BC source regions contributing over 77 % of the variance, in alignment with climatological patterns of NO₂ and UVAI (Ultraviolet Aerosol Index) observations during this period. Simplified inversion emission estimation provides a medium to high confidence inventory that effectively captures both geographic and temporal variations of BC across different regions and percentiles. The emission difference between our inversion and a priori estimation is not uniform, with BC emissions globally underestimated by a factor of 1.8–4.0. Urban and rapidly developing regions including Europe, China, United States, and India are highly underestimated in the a priori inventory.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102633"},"PeriodicalIF":3.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313082","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":"Characteristics and sources of volatile organic compounds and their impacts on ozone formation in a coastal city of southeastern China","authors":"Chende Gai ,&nbsp;Chuanyou Ying ,&nbsp;Xugeng Cheng ,&nbsp;Fei Jiang ,&nbsp;Jing Lin ,&nbsp;Zhixiong Chen ,&nbsp;Lei Shu ,&nbsp;Jun Hu ,&nbsp;Dongsheng Jiang ,&nbsp;Mengmiao Yang ,&nbsp;Jane Liu","doi":"10.1016/j.apr.2025.102632","DOIUrl":"10.1016/j.apr.2025.102632","url":null,"abstract":"<div><div>Ozone (O₃) pollution is a severe environmental issue, highlighting the critical role of volatile organic compounds (VOCs), a precursor of O₃, in urban air pollution control. In this study, we analyzed continuous hourly measurements of VOCs and O₃ in 2022 in a coastal city of southeast China, Fuzhou, to characterize VOC seasonal variations and sources, as well as their contributions to O₃ formation in the region. The results show that the annual mean concentrations of VOCs is 18.3 ± 10.4 ppbv, which is much lower than cities in northern and central China. According to the emission ratios, VOCs in Fuzhou are significantly impacted by liquefied petroleum gas and natural gas (LPG/NG) (30.6 %), but are less affected by vehicle exhaust emissions (20.9 %) than those in Chinese megacities, because of the consumption of clean energy increased to 30 % in Fuzhou. Seasonally, VOC sources exhibit a higher proportion of the solvent source in summer, driven by increased production from the agricultural fertilizers, integrated circuits, and beverage production. In autumn, the elevated industrial VOC emissions, including cement and petrochemical industries, contribute a high proportion of 23.1 % to the total VOC. The proportion of LPG/LPG source in winter is higher than in other seasons, mainly due to the growth in VOCs emissions and the increase in emissions from burning sources. The LPG/NG and vehicle exhaust source are the primary contributors to O₃ formation potential (OFP) throughout the year, except in summer when vehicle and solvent emissions become the leading contributors to OFP. Finally, we identified multiple elevated O₃ events associated with increases in VOCs. We conservatively estimate that on average of these events, a 59.4 % increase in VOCs and a 37.3 % increase in NO₂ could lead to a rise of 38.5 % in O₃ concentrations on the following day under comparable local meteorological conditions. This study provides policymakers with new scientific references to formulate effective VOC control measures for curbing O₃ pollution in southeastern China.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102632"},"PeriodicalIF":3.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321623","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":"Atmospheric deposition of anthropogenic microfibers in different indoor environments of Chennai, India","authors":"A Angel Jessieleena ,&nbsp;Iniyan K.E. ,&nbsp;Amit Singh Chandel ,&nbsp;Sancia Verus D’Sa ,&nbsp;Nilofer M. ,&nbsp;Indumathi M. Nambi","doi":"10.1016/j.apr.2025.102629","DOIUrl":"10.1016/j.apr.2025.102629","url":null,"abstract":"<div><div>Microplastics, particularly microplastic fibers, are one of the emerging pollutants of concern. However, recent studies emphasized the predominance of artificial and natural microfibers over microplastic fibers. Despite this, research focusing on all types of microfibers, commonly grouped as anthropogenic microfibers (MFs) remains limited, especially in residential indoor environments. Therefore, this study explored the indoor MFs deposition in the residential homes of Chennai, India, a first such study in the country. Additionally, workplaces, including offices, laboratories, and hostel rooms, were examined. Bedrooms (16,736 ± 7,263 MF/m²/day) and student hostels (5,572 ± 2,898 MF/m²/day) recorded highest contamination in respective categories, and this could be attributed to the abundance of textile products in both the rooms. MFs&lt;500 μm dominated in both residential (78.8 %) and workplace (65.9 %) samples. The observed diameter of MFs (2.02–36.4 μm) indicate their potential to penetrate human lungs. μ-FTIR analysis revealed the distribution of semi-synthetic (48.2 %), natural (29.3 %) and synthetic (22.5 %) MFs, underscoring the need to consider all categories of MFs. Further classification revealed textiles (rayon - 94.5 ± 6.40 %, cotton - 68.1 ± 6.12 %, and polyethylene terephthalate (PET) - 48.1 ± 11.5 %) as a significant source of contamination. The detection of black rubber/latex MFs indicates additional contributions from road dust. Surface morphological analysis further highlighted the primary role of indoor/local sources in MFs contamination. Overall, the study emphasizes the need to monitor all categories of MFs and calls for comprehensive investigations into the impact of various sources on indoor MFs contamination.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102629"},"PeriodicalIF":3.9,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321622","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":"Year-long variability of the mixing layer height at an urban Mediterranean location and association with air pollution levels","authors":"K. Petrinoli ,&nbsp;D.G. Kaskaoutis ,&nbsp;A. Bougiatioti ,&nbsp;E. Liakakou ,&nbsp;G. Grivas ,&nbsp;P. Kalkavouras ,&nbsp;N. Mihalopoulos","doi":"10.1016/j.apr.2025.102612","DOIUrl":"10.1016/j.apr.2025.102612","url":null,"abstract":"<div><div>This study examines the planetary boundary layer characteristics and the association with atmospheric pollutants in Athens, aiming to assess the effects of boundary-layer dynamics on pollution levels. Ceilometer (CL31) profiles of backscatter coefficient (BSC) were used to compute the mixing layer height (MLH) based on the gradient method under cloudless conditions, revealing higher values in summer (mean: 955 m) and lower in winter (mean: 556 m). The annual mean MLH displayed a pronounced diurnal pattern depending on season with a mean value of 902 ± 337 m at noon, decreased to 525 ± 336 m at midnight. The MLH maximized at 15:00 (UTC+2) (mean: 1293 ± 337 m) closely related to surface heating and turbulent mixing conditions. MLH variations are interrelated with the local wind patterns, with stronger winds mostly from northeast directions during May–September, facilitating higher MLH and dispersion of pollutants. PM_2.5, Black Carbon (BC) and NO_x concentrations were strongly linked to variations of MLH, exhibiting negative correlations with it, while O₃ exhibited a similar diurnal pattern with MLH (maximizing during early afternoon) due to its photochemical production and possible intrusion from upper atmospheric levels. Apart from changes in the emission sources due to domestic heating during wintertime, the shallow MLH along with stable atmospheric conditions, further exacerbate the accumulation of pollutants near the surface, with emphasis on BC. Two case studies regarding enhanced BC levels due to residential wood burning and transported smoke plumes were analyzed to assess the impacts of MLH variations on pollutant concentrations.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102612"},"PeriodicalIF":3.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281084","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":"Widening cost-benefits gap of emission control measures in India from 2017 to 2022","authors":"Mengyuan Zhang ,&nbsp;Shuai Wang ,&nbsp;Zhiwei Han ,&nbsp;Chenliang Tao ,&nbsp;Yuan Wang ,&nbsp;Mano N. Kumar ,&nbsp;Sunil Dahiya ,&nbsp;Peng Wang ,&nbsp;Hongliang Zhang","doi":"10.1016/j.apr.2025.102615","DOIUrl":"10.1016/j.apr.2025.102615","url":null,"abstract":"<div><div>The Indian government has implemented stricter emission reduction policies to alleviate pollution in recent years, though their impact on air quality remains uncertain. This study uses the Community Multiscale Air Quality (CMAQ) model to simulate PM_2.5 and O₃ concentrations in India from 2017 to 2022, assessing the response of pollutant emissions and evaluating effects on air quality and public health. We assess the total costs of emission reduction policies and potential lives saved through improved air quality, providing a preliminary estimate of policy effectiveness. While emissions of SO₂, PM_2.5, PM₁₀, and black carbon declined, emissions of NH₃, VOC, and organic carbon increased, with CO and NOx remaining stable. The total cost of emission reductions increased from $31.9 billion in 2017 to $47.4 billion in 2022, with NO_x reductions accounting for over 70 % of the total. Despite these efforts, PM_2.5 and maximum daily 8-h average (MDA8) O₃ concentrations generally rose in most years, showing a synchronized pattern. This contributed to an increase in premature deaths, from 2.1 million to 2.4 million, with cardiovascular diseases due to PM_2.5 exposure accounting for over 40 % of these deaths. The increasing costs of emission reductions, excluding a brief decline in 2020, led to negative health benefits and a widening cost-benefit gap. By 2022, net benefits were recorded at -$126.7 billion, marking a 14 % decrease from 2018. These findings highlight the need for future policies to improve cost-effectiveness and maximize health benefits for sustainable air quality improvements.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102615"},"PeriodicalIF":3.9,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144290835","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":"Observations of surface CO2 at an urban station in Wuhan, Central China: temporal variations, sources, and sinks","authors":"Wei Liu ,&nbsp;Huang Zheng ,&nbsp;Feng Ding ,&nbsp;Junying Zhang ,&nbsp;Yongchun Zhao ,&nbsp;Zhuo Xiong ,&nbsp;Qian Wu ,&nbsp;Linjun Li","doi":"10.1016/j.apr.2025.102614","DOIUrl":"10.1016/j.apr.2025.102614","url":null,"abstract":"<div><div>Observation of atmospheric carbon dioxide (CO₂) is important to understand its temporal variations, sources, and sinks, which ultimately help mitigate its climate effects. While most CO₂ observations are conducted in background or remote regions, fewer studies focus on urban areas. This study reported a one-year continuous observation of CO₂ at an urban site in Wuhan, Central China. In 2023, the average CO₂ concentration at this site was 459 ± 23.5 ppm, which was 5.53 % higher than mean values collected from other urban stations. Using the moving average filtering method, the CO₂ concentrations were filtered as a pollution source, background, and absorption sink with mean concentrations of 494 ± 21.1 ppm, 455 ± 16.1 ppm, and 434 ± 9.61 ppm, respectively. Temporal variations of these components showed similar monthly trends but different diurnal patterns, reflecting the influences of terrestrial ecosystems and human activities. Model simulations from Carbon Tracker indicated that fossil fuel combustion was the primary source, increasing CO₂ levels by 125 ppm. The ocean and biosphere acted as CO₂ sinks, reducing concentrations by 31.6 ppm and 31.2 ppm, respectively. The conditional bivariate probability function results suggested that urban CO₂ levels were influenced by local emissions and regional transports. Combined with backward trajectory analysis and CO₂ emission inventory, the local and regional contributions were further quantified with percentages of 81.9 % and 18.1 %, respectively. This study enhances our understanding of greenhouse gas behaviors and contributes to efforts to achieve carbon neutrality in urban areas.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102614"},"PeriodicalIF":3.9,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281082","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":"Impacts of Russia-Ukraine War on air pollution over the Black Sea Region due to changes in maritime transport","authors":"Muhittin Gunes Onay ,&nbsp;Serra Saracoglu ,&nbsp;Elif Pehlivanoglu ,&nbsp;Burcak Kaynak","doi":"10.1016/j.apr.2025.102613","DOIUrl":"10.1016/j.apr.2025.102613","url":null,"abstract":"<div><div>The Russia-Ukraine war, which began on February 24, 2022, has affected maritime transport in the Black Sea, leading to significant changes in air pollution levels in addition to other social and environmental impacts. This study examines the impact of reduced maritime activity on air pollution levels in the Black Sea by analyzing TROPOMI NO₂ and SO₂ as well as COBRA algorithm SO₂ retrievals from two years: 2019 (pre-war) and 2022 (war) along with 2019–2022 interval. To determine spatio-temporal variations, retrievals were spatially and temporally matched with EMODnet route density (RD) data. The pollution levels in the study region, over major shipping routes, and ports were examined.</div><div>The results indicated that maritime traffic declined sharply around Ukrainian ports (Odessa, Kherson, and Yuzhny), while it increased in the eastern Black Sea, particularly near Russian ports (Novorossiysk and Tuapse). This shift in shipping patterns influenced NO₂ concentrations, with significant increases in the eastern regions where maritime activity intensified and decreases in the northwestern regions. In contrast, SO₂ levels showed a more complex response due to additional influences and uncertainties on SO₂ retrievals. These results highlighted the importance of satellite-based measurements in evaluating air quality impacts at offshore maritime regions with no ground-based monitoring. The study showed the complex effects of the Russia-Ukraine war on regional air pollution, demonstrating that while reduced maritime traffic led to lower pollutant concentrations in some areas, alternative shipping routes, military activities, and other factors contributed to increased pollution in others.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102613"},"PeriodicalIF":3.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254382","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":"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}