Atmospheric Pollution Research最新文献

{"title":"Differential impacts of the 2015–2020 El Niño/El Niño Modoki on seasonal ozone levels across China","authors":"Xiaohong Wang ,&nbsp;Qingheng Lu ,&nbsp;Shiyuan Zhong ,&nbsp;Yinchen Chen ,&nbsp;Zunli Dai ,&nbsp;Lejiang Yu","doi":"10.1016/j.apr.2025.102449","DOIUrl":"10.1016/j.apr.2025.102449","url":null,"abstract":"<div><div>Utilizing daily data from nearly 1500 ground stations within a nationwide air-quality monitoring network spanning 2015 to 2020, this study identifies three primary spatiotemporal modes of ozone (O₃) concentration anomalies and explores the sensitivity of surface O₃ to both Eastern Pacific El Niño and Central Pacific El Niño (El Niño Modoki) across distinct Chinese regions and seasons. Results reveal limited sensitivity during spring and winter, wherein negative (positive) O₃ anomalies predominate across China during the positive (negative) phase of either ENSO type, with spring magnitudes approximately doubling those observed in winter. In contrast, during summer and autumn, O₃ anomalies exhibit significant variations depending on El Niño type and geographical location. Positive anomalies are notably pronounced in summer and autumn, particularly during El Niño Modoki in eastern China, while negative anomalies concentrate in western China during autumn, with a scattered distribution in summer. On average, magnitudes of O₃ anomalies during El Niño Modoki surpass those during El Niño thoroughly, with the most pronounced differences in magnitude during summer for positive anomalies. The differences in O₃ anomalies between El Niño and El Niño Modoki are attributed to variations in anomalous atmospheric circulations, wherein El Niño Modoki stands out with stronger anomalous 850-hPa highs and lows, along with stronger associated anomalous circulations, as well as larger extents and magnitudes of anomalous precipitation and solar radiation. These variations induce changes in low-level wind directions that influence regional O₃ transport, and alterations in solar radiation and precipitation, impacting both O₃ generation and removal processes.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102449"},"PeriodicalIF":3.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419417","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 composition, source distribution and health risk assessment of PM2.5 and PM10 in Beijing","authors":"Shaosong Zhen ,&nbsp;Min Luo ,&nbsp;Futao Xin ,&nbsp;Lingling Ma ,&nbsp;Diandou Xu ,&nbsp;Xiaomeng Cheng ,&nbsp;Yang Shao","doi":"10.1016/j.apr.2025.102448","DOIUrl":"10.1016/j.apr.2025.102448","url":null,"abstract":"<div><div>Beijing's air quality has seen significant enhancements owing to the successful implementation of China's emission control measures. However, air pollution incidents continue to occur, and more attention should be paid to continuous air quality monitoring and control. Here, the PM_2.5 and PM₁₀ samples collected during the air pollution days in Beijing in 2022 were analyzed to study the air quality situation and understand the changes in air pollution sources. The average concentration of PM_2.5 was 84.3 μg/m³ and PM₁₀ was 128.7 μg/m³. NO₃⁻, SO₄²⁻ and NH₄⁺ were the primary constituents of water-soluble inorganic ions, with concentrations of 18.8 μg/m³, 7.9 μg/m³, 7.4 μg/m³ in PM_2.5, and 20.5 μg/m³, 9.3 μg/m³, and 8.1 μg/m³ in PM₁₀. The enrichment factor values for Sn, Sb, and Cd in PM_2.5 exceeded 100, indicating severe anthropogenic pollution. Five pollution factors for PM_2.5 and PM₁₀ were obtained from the analysis of PMF model: vehicle emissions and dust, industrial emissions, secondary inorganic aerosols, coal combustion, and electronic manufacturing. The highest contributing factors were vehicle emissions and dust (28 % for PM_2.5 and 34 % for PM₁₀). According to the health risk assessment, Mn presented a non-carcinogenic risk to humans. Cd, As, Ni, and Cr (VI) showed a low level of carcinogenic risk within the acceptable range. The backward trajectory analysis showed that air masses from nearby cities exhibited stronger pollutant capabilities. Combining the potential source contribution function and concentration weight trajectory diagrams, the main potential source areas of Beijing are in Hebei, Tianjin, Shanxi and Henan.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 4","pages":"Article 102448"},"PeriodicalIF":3.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143331263","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":"3DVAR meteorological data assimilation and aerosol impact on the simulation of heat wave 2022 over Haryana using WRF-Chem","authors":"Paushali Deb ,&nbsp;S.K. Panda ,&nbsp;Unashish Mondal ,&nbsp;Sushil K. Dash ,&nbsp;Devesh Sharma","doi":"10.1016/j.apr.2025.102440","DOIUrl":"10.1016/j.apr.2025.102440","url":null,"abstract":"<div><div>The rising frequency of heat waves in India presents significant risks to public health, agriculture, and the economy. In March 2022, temperatures reached a record-breaking 33.10 °C, the highest in 122 years resulting in two major heat wave events: March 11–21 and March 26–31, which claimed 33 lives. This study delves into the impact of anthropogenic emission/aerosols and meteorological data assimilation on model-predicted surface meteorological variables using “Weather Research and Forecasting (WRF) model” coupled with Chemistry (WRF-Chem). Four distinct simulation scenarios namely, WRF, WRFDA (WRF with meteorological Data Assimilation), WRF-Chem, and WRF-ChemDA (WRF-Chem with meteorological Data Assimilation) were executed across the Haryana domain to assess the sensitivity of model outputs. Analyses within the WRFDA and WRF-ChemDA frameworks utilized a 6-hourly cyclic 3-Dimensional Variational (3DVAR) Data Assimilation (DA) of NCEP ADP Surface Observational Fields. Most critically, the incorporation of aerosols and DA techniques markedly improved forecasts of key meteorological variables, including 2 m Temperature (T2), 2 m Relative Humidity (RH2), Planetary Boundary Layer Height (PBLH), and Outgoing Longwave Radiation (OLR). Skill assessment metrics, including the Heidke Skill Score (HSS ∼ 0.5), Accuracy (ACC &gt;0.9), and Probability of Detection (POD ∼ 1), demonstrate that WRF-ChemDA outperformed other models, especially during heat wave events. Conclusively, this study advocates for the meticulous selection of modeling approaches to accurately simulate heat wave events, ensuring that selected models adeptly capture the intricate dynamics and complexities of extreme temperature phenomena.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 4","pages":"Article 102440"},"PeriodicalIF":3.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377854","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":"A novel hybrid model based on dual-layer decomposition and kernel density estimation for VOCs concentration forecasting considering influencing factors","authors":"Fan Yang,&nbsp;Guangqiu Huang,&nbsp;Xin Jiao","doi":"10.1016/j.apr.2025.102439","DOIUrl":"10.1016/j.apr.2025.102439","url":null,"abstract":"<div><div>Accurate VOCs concentration prediction is essential for air pollution control and ecosystem stability. Due to multiple factors such as climatic conditions and photochemical reactions, VOCs monitoring data exhibits high randomness, which poses a challenge for prediction precision. Current decomposition integration models mainly focus on modelling the target variables and pay insufficient attention to the uncertainty of the prediction results. To solve these problems, an innovative VOCs prediction model is proposed by considering multiple external factors and combining dual-layer decomposition and nonlinear integration. Firstly, random forest (RF) is used for feature selection and a dual-layer decomposition method combining complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved variational mode decomposition (IVMD) is proposed to reduce the data complexity. Next, K-means clustering is applied to reconstruct the decomposed subsequences to balance computational efficiency and model complexity, and the reconstructed subsequences is fed into long short-term memory (LSTM) optimized by grey wolf optimization (GWO) for prediction. Then, the predicted values are integrated by support vector regression (SVR) to minimize error accumulation. Finally, construct the prediction intervals based on kernel density estimation (KDE) to capture the fluctuation range of VOCs concentration. In the empirical study with total VOCs concentration data from two monitoring stations, the proposed model exhibits the lowest prediction error, with the root mean square error reduced by a maximum of 85.59% and 86.97%, respectively. The prediction intervals have high coverage and narrow interval width, proving that the proposed model can provide reliable VOCs concentration point and interval prediction.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 4","pages":"Article 102439"},"PeriodicalIF":3.9,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394621","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":"Ability of typical greening tree species to purify NO2 under different environmental factors","authors":"Jiaxing Fang ,&nbsp;Shaoning Li ,&nbsp;Mengxue Wang ,&nbsp;Na Zhao ,&nbsp;Xiaotian Xu ,&nbsp;Bin Li ,&nbsp;Junjie Zhang ,&nbsp;Chen Liu ,&nbsp;Qin Zhang ,&nbsp;Shaowei Lu","doi":"10.1016/j.apr.2024.102357","DOIUrl":"10.1016/j.apr.2024.102357","url":null,"abstract":"<div><div>Trees can uptake nitrogen dioxide(NO₂) and purify atmosphere, but the complex variation of environmental factors affects the ability of trees to purify NO₂. In this study, we conducted a one-time fumigation experiment on four typical greening tree species in China, including Japanese pagoda tree (Styphnolobium japonicum), Ginkgo (Ginkgo biloba), Manchurian red pine (Pinus tabuliformis), and Bunge's pine (Pinus bungeana), to analyze the impact of environmental factors on the ability of the trees to remove NO₂ from the air by quantifying their performance under different conditions of temperature, relative humidity, and wind speed. The results showed the following: (1) Broadleaf trees were more effective at purification compared with coniferous trees. (2) With the increase of temperature, the average purification rate of each tree species showed a decreasing and then increasing trend; except Bunge's pine, the purification amount per unit leaf area of each tree species showed an increasing and then decreasing trend. (3) With increasing relative humidity, the purification of NO₂ per unit leaf area in coniferous trees increased, while the trend in broadleaf trees decreased and then increased; the average purification rate of all the tree species, except Ginkgo, also decreased and then increased. (4) Temperature inhibited plant NO₂ purification capacity, relative humidity promoted plant NO₂ purification capacity, and wind speed had less ability to influence. (5) Multiple linear regression equations were successfully established to predict the ability of trees to purify NO₂ under different environmental factors. The study provides an important reference to purify atmosphere.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102357"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131200","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":"An exploratory study on the association between air pollution and health problems (ICD-10) with an emphasis on respiratory diseases","authors":"Ronan Adler Tavella ,&nbsp;Julia Oliveira Penteado ,&nbsp;Rodrigo de Lima Brum ,&nbsp;Alicia da Silva Bonifácio ,&nbsp;Meister Coelho San Martin ,&nbsp;Elizabet Saes-Silva ,&nbsp;Aline Neutzling Brum ,&nbsp;Romina Buffarini ,&nbsp;Washington Luiz Félix Correia Filho ,&nbsp;Diana Francisca Adamatti ,&nbsp;Rosália Garcia Neves ,&nbsp;Edmilson Dias de Freitas ,&nbsp;Simone Georges El Khouri Miraglia ,&nbsp;Flavio Manoel Rodrigues da Silva Júnior","doi":"10.1016/j.apr.2024.102377","DOIUrl":"10.1016/j.apr.2024.102377","url":null,"abstract":"<div><div>Air pollution is a growing public health concern, with diverse impacts on human health. This study aimed to conduct an exploratory analysis of the associations between air pollutants (O₃, PM_2.5, and PM₁₀) and health outcomes, using ICD-10 Chapters, across 24 cities with different dimensions in the state of Rio Grande do Sul, Brazil. Three models were developed for both annual and monthly data: one encompassing all 24 cities (Model 1), another with medium and small-sized cities (Model 2), and the last exclusively focusing on small cities (Model 3). Multiple linear regression analyses were conducted with air pollutants and meteorological variables as independent variables, and hospitalization rates within each ICD-10 Chapters and specific respiratory diseases as dependent variables. Our analysis revealed significant positive associations among diverse chapters of the ICD-10 and air pollutants, with Model 3 exhibiting the most robust and significant positive associations with 12 chapters of the ICD-10 (Chapters: II, V, VI, VII, IX, X, XI, XII, XIV, XVI, XVII, XVIII, XIX, and XXI), highlighting the broad impact of pollution on human health beyond traditional respiratory and cardiovascular concerns. Moreover, positive associations were identified with specific respiratory diseases, including asthma, pneumonia, bronchiolitis, and acute bronchitis. Temperature, precipitation, and wind speed emerged as the meteorological factors most frequently associated with multiple health outcomes and ICD chapters. Notably, our findings reveal distinct patterns in associations across cities with different population sizes, highlighting the importance of considering contextual factors, such as city size, when assessing the health impacts of air pollution.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102377"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131201","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":"A self-designed pyrolysis-gasification-combustion pilot plant for rural solid waste disposal: The elucidation of emission factors","authors":"Wei Jiang ,&nbsp;Dian Li ,&nbsp;Hui Cai ,&nbsp;Jiahui Yan ,&nbsp;Yuanyao Ye ,&nbsp;Jianxiong Kang ,&nbsp;Qian Tang ,&nbsp;Yongzheng Ren ,&nbsp;Songlin Wang ,&nbsp;Dongqi Liu ,&nbsp;Zizheng Liu ,&nbsp;Yiqun Chen","doi":"10.1016/j.apr.2024.102372","DOIUrl":"10.1016/j.apr.2024.102372","url":null,"abstract":"<div><div>The research group developed a pyrolysis-gasification-combustion pilot plant (PGCP) to treat rural solid waste (RSW). Based on the study of previous operating conditions, this study further explored the characteristics of potential secondary pollutants in the plant, such as slag, fly ash and flue gas. In the present study, X-ray fluorescence (XRF), X-ray diffraction (XRD) and scanning electron microscope (SEM) were used to analyze slag and fly ash. Besides, the leaching toxicity, content and morphology distribution of heavy metals (e.g., Cu, Pb, Cd, Zn and Cr) in the slag of PGCP were also studied as well as the emission characteristics of various pollutants in flue gas. Results show that slag mainly contains CaCO₃ and SiO₂, while CaCO₃ is mainly contained in fly ash. Moreover, the leaching toxicity of heavy metals in the slag did not exceed the limit value of the standard in China. The present study could provide technical support and data for optimizing the operation of plant-scale pyrolysis of RSW.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102372"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131202","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":"Unraveling the complexities of ozone and PM2.5 pollution in the Pearl River Delta region: Impacts of precursors emissions and meteorological factors, and effective mitigation strategies","authors":"Yating Chen ,&nbsp;Liye Zhu ,&nbsp;Sihui Wang ,&nbsp;Daven K. Henze ,&nbsp;Tzung-May Fu ,&nbsp;Lin Zhang ,&nbsp;Xiaoling Wang","doi":"10.1016/j.apr.2024.102368","DOIUrl":"10.1016/j.apr.2024.102368","url":null,"abstract":"<div><div>Ozone (O₃) and fine particulate matter (PM_2.5) are known to be interconnected due to shared precursor compounds. While numerous studies have examined the impact of precursors and meteorological factors on compound pollution events, few have proposed effective mitigation strategies tailored to specific regions. In this study, we conducted simulations of two types of O₃ and PM_2.5 pollution events in the Pearl River Delta (PRD) region during 2018 using the GEOS-Chem model. We applied a multiple linear regression model to quantify and distinguish the contributions of precursor emissions and meteorological factors to these events. Our findings highlight the predominant role of precursor emission factors in driving these pollution events. Notably, reducing NO_x emissions in the Pearl River Estuary (PRE) region was found to exacerbate O₃ pollution during specific periods, while reducing emissions of C4 alkanes (ALK4), lumped C3 alkenes (PRPE) and NH₃ in proportion to their respective contributions emerged as an effective strategy to mitigate combined O₃ and PM_2.5 pollution. This research elucidates the mechanisms underlying O₃ and PM_2.5 compound pollution in the PRD region and presents a practical and significant approach to managing air pollution in this area.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102368"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131206","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":"Linking sand/dust storms hotspots and land use over Iran","authors":"Mahdi Boroughani ,&nbsp;Rahman Zandi ,&nbsp;Sima Pourhashemi ,&nbsp;Hamid Gholami ,&nbsp;Dimitris G. Kaskaoutis","doi":"10.1016/j.apr.2024.102380","DOIUrl":"10.1016/j.apr.2024.102380","url":null,"abstract":"<div><div>Sand and dust storms (SDS), as a direct consequence of land degradation and wind erosion, is an important environmental challenge in the last two decades, especially in arid and semi-arid areas. Land use changes due to human intervention and soil's susceptibility to erosion are among the most important factors influencing the SDS hotspots. This study aims to explore possible linkage between land use changes and SDS hotspots in Iran during a 20-years period (2001–2022). In this scope, four dust characterization indices based on MODIS observations (BTD₃₁₃₂, BTD₂₉₃₁, NDDI, and D) were employed to identify the SDS hotspots. Then, the land use – land cover (LULC) changes over Iran were mapped using MODIS images, aiming to identify the areas exhibiting large LULC changes and tendency to become SDS hotspots. Finally, the LULC changes were analyzed with respect to SDS hotspots. The results revealed 618 SDS hotspots in the whole Iranian territory, with the largest number of them located in non-vegetated lands, scattered shrubs and rangelands. In addition, Zabol in east Iran presented the highest frequency of SDS, while southwest Iran faced also a large number of SDS. The highest number of SDS was recorded in 2008 in most of the country's stations, following the dust-regime shift in the Middle East due to prolonged drought. Current methodology links SDS hotspots and LULC changes very well and can be helpful for developing mitigation strategies for the consequences of human and climate-induced LULC changes, wind erosion and SDS in arid environments.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102380"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131207","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":"Comparative study on the dispersion and removal efficiency of indoor aerosol particles under various displacement ventilation modes","authors":"Wencheng Liu,&nbsp;Qianfeng Liang,&nbsp;Cheng Yao,&nbsp;Bin Li,&nbsp;Jie Ji,&nbsp;Xianzhuo Wang,&nbsp;Yang Luo,&nbsp;Yuandong Huang","doi":"10.1016/j.apr.2024.102397","DOIUrl":"10.1016/j.apr.2024.102397","url":null,"abstract":"<div><div>The removal of indoor aerosols through ventilation is a critical area of research in indoor air quality management. This study utilized the validated Re-Normalization Group (RNG) <em>k-ε</em> model to simulate the effect of different ventilation methods on the diffusion and distribution of indoor aerosol particles. The analysis encompassed variations in temperature, airflow dynamics, and aerosol dispersion characteristics under both summer and winter conditions. The results indicate significant differences in indoor airflow structures among different ventilation modes, influencing the thermal comfort of indoor occupants distinctly. Furthermore, these ventilation modes had varying impacts on the diffusion of particles of different sizes under different seasonal conditions. In summer, the ceiling-supply and side-return ventilation mode demonstrated outstanding particle removal efficiency, achieving a remarkable 99.2% removal rate after just 50 s of ventilation. Conversely, winter conditions posed challenges for efficient indoor aerosol particle removal, even with similar ventilation modes. During winter, the most effective ventilation mode was the left-upper supply and right-lower return mode, which achieved a particle removal efficiency of 98% at 100 s. These findings highlight the importance of understanding seasonal variations in indoor aerosol distribution and the effectiveness of diverse ventilation methods in improving indoor air quality. Such insights are invaluable for optimizing ventilation systems and the continually improving indoor air quality management.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 2","pages":"Article 102397"},"PeriodicalIF":3.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131624","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}