Atmospheric Pollution Research最新文献

{"title":"Source apportionment of primary and secondary fine particulate matter in Eskisehir/Türkiye using conventional and dispersion-normalized positive matrix factorization","authors":"Akif Ari ,&nbsp;Pelin Ertürk Ari ,&nbsp;Eftade O. Gaga","doi":"10.1016/j.apr.2025.102653","DOIUrl":"10.1016/j.apr.2025.102653","url":null,"abstract":"<div><div>In this study, the organic and inorganic components of atmospheric fine particulate matter (PM_2.5) were monitored daily in Eskisehir City/Türkiye, for one year, and the contributions of primary and secondary sources to the PM mass were investigated. A total of 94 components were characterized in PM_2.5 samples, including 5 anions, 46 trace elements, Organic and Elemental Carbon (OC &amp; EC), 16 Polycyclic Aromatic Hydrocarbons (PAHs), 26 n-alkanes, levoglucosan, and 8 carboxylic acids to obtain a more holistic mass closure. In addition, the principal sources of PM_2.5 were apportioned by the Conventional and Dispersion-Normalized Positive Matrix Factorization (C-PMF and DN-PMF) to assess dispersion/dilution characteristics of local meteorological conditions on source contributions of PM. The main sources of PM were classified into 8 factors. A significant seasonal variation was observed in combustion-related PM_2.5 constituents, which increased in the winter, while the contribution of Secondary Organic Carbon (SOC) enhanced during the summer period. In addition, a visual effect of seasonal atmospheric dilution/dispersion conditions on measured pollutant levels was observed as a function of Ventilation Coefficients (VC). The mass percent of SOC in PM_2.5 varied between 2.3 % and 13.0 %, and the annual mean contribution was over 7.5 %.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102653"},"PeriodicalIF":3.9,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633947","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":"The input-optimized and supplemented MEGAN improves biogenic volatile organic compounds estimation accuracy in China","authors":"Bin Cai ,&nbsp;Haomiao Cheng ,&nbsp;Tianfang Kang ,&nbsp;Yu Wang ,&nbsp;Wentao Han ,&nbsp;Wei Wang","doi":"10.1016/j.apr.2025.102650","DOIUrl":"10.1016/j.apr.2025.102650","url":null,"abstract":"<div><div>To reduce the uncertainty in biogenic volatile organic compound (BVOC) emission estimates by MEGAN model, this study introduces targeted optimizations in the input conditions driven by plant functional types (PFTs), emission factors (EFs), and leaf area index (LAI), and supplements the missing BVOC emissions from urban green spaces (U-BVOC emissions). To verify the optimization effect of the input-improved MEGAN, the study conducted a comparative validation of the estimated BVOC emission levels in representative regions of northern and southern China using formaldehyde vertical column densities and accumulation-based estimates through stock volume conversion. The results indicate that the input-improved MEGAN can provide more reasonable BVOC estimates with a more notable improvement in the southern region, and the estimated isoprene emissions show better spatiotemporal correlation with formaldehyde vertical column densities. The optimization of PFT + EF and LAI input conditions both effectively improve the model's estimation accuracy. Although the U-BVOC emissions are significantly lower than the BVOC emissions from non-urban environment, the newly added U-BVOC emission inventory is expected to help improve the performance of existing air quality models in simulating O₃ and particulate matter pollution in urban areas.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102650"},"PeriodicalIF":3.9,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703477","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":"Effects of altitude on light gasoline vehicles: fuel consumption and air pollution","authors":"Yanxu Ren,&nbsp;Wenhan Yu,&nbsp;Lijun Hao,&nbsp;Yunshan Ge","doi":"10.1016/j.apr.2025.102652","DOIUrl":"10.1016/j.apr.2025.102652","url":null,"abstract":"<div><div>Driven by the global carbon neutrality goal and emission regulations, gasoline vehicles' fuel consumption and emission characteristics in the plateau environment have received extensive attention. In this paper, the running resistance of light gasoline vehicles in a high-altitude environment laboratory is corrected by coasting resistance tests to ensure the accuracy of laboratory tests. Finally, a constant speed fuel consumption test and a New European Driving Cycle emission test were carried out in the high-altitude environment laboratory. The results of fuel consumption characteristics show that at low-to-medium speeds (below 5,000m altitude), fuel efficiency generally improved with increasing altitude. For the high-speed range, air resistance becomes more prominent below 5000m, which reduces overall fuel consumption. However, once the altitude approaches 5000m, all speed ranges show an upward trend in fuel consumption. Fuel consumption at high speeds enters an upward trend earlier (at relatively low altitudes). The results of emission characteristics show that the emission of CO and THC increases significantly with the increase of altitude due to combustion deterioration. The contribution of the cold start-up phase increased significantly (77.1 % CO and 66.3 % THC), which became the core factor of the increase in emissions. Due to the game between the combustion temperature and the efficiency of the three-way catalytic converter (TWC), NOx emission shows a trend of first decreasing and then increasing. Its instantaneous emission characteristics are not stable because of the gradual decline of TWC performance. In general, these results can be used to drive vehicle energy efficiency and emission reduction targets.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102652"},"PeriodicalIF":3.9,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695222","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":"Long-term evolution and synoptic meteorological modulation of PM2.5 and PM10 in Seoul","authors":"Wooseok Jang ,&nbsp;Simon Wang ,&nbsp;Hyun Cheol Kim ,&nbsp;Jee-Hoon Jeong ,&nbsp;Changhyun Yoo ,&nbsp;Jin-Young Choi ,&nbsp;Jin-Ho Yoon","doi":"10.1016/j.apr.2025.102649","DOIUrl":"10.1016/j.apr.2025.102649","url":null,"abstract":"<div><div>Addressing particulate matter (PM) pollution in megacities like Seoul is crucial for public health and environmental sustainability, necessitating a comprehensive understanding of its long-term evolution and meteorological drivers. This study investigated the key factors affecting long-term PM concentrations in Seoul, South Korea, from 2000 to 2021, with a focus on the winter (DJF) and spring (MAM) seasons. To address the gap in PM research caused by the shorter observation period of PM_2.5 compared with PM₁₀, we used an extended PM_2.5 dataset. This enabled a detailed analysis of PM_2.5 and its relationship with PM₁₀, which, despite some differences, generally displayed similar variability. Both PM_2.5 and PM₁₀ exhibited decreasing trends in winter as well as spring, although the rate of decline slowed in the last decade (2011–2020) compared with the earlier decade (2000–2010). Both seasons exhibited a strengthened interannual correlation between PM_2.5 and PM₁₀ in the last decade. Daily PM_2.5 and PM₁₀ levels generally fluctuated in a similar pattern in both seasons, which can be attributed to synoptic-scale meteorological systems, particularly migratory systems from Northwest China, which can remain stationary over Korea for several days, particularly in winter. This pattern continues into spring, albeit with a lower intensity. These findings provide valuable insights into PM_2.5 variability and its correlation with PM₁₀ over time, which may inform future PM_2.5 mitigation strategies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102649"},"PeriodicalIF":3.9,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703476","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 influencing factors of ambient ozone pollution in Hangzhou in the relative humidity range with high ozone levels","authors":"Yu Lu ,&nbsp;Lingdong Kong ,&nbsp;Jiandong Shen ,&nbsp;Beibei Liu ,&nbsp;Yixuan An ,&nbsp;Yuwen Wang ,&nbsp;Jie Tan ,&nbsp;Lin Wang","doi":"10.1016/j.apr.2025.102648","DOIUrl":"10.1016/j.apr.2025.102648","url":null,"abstract":"<div><div>With the rapid economic growth and urbanization, despite improvements in particulate matter (PM_2.5) pollution control, ozone (O₃) pollution has emerged as a pressing environmental issue in China. This study systematically investigates O₃ pollution dynamics in Hangzhou (2021–2023) in the relative humidity (RH) range with high ozone levels using observational data and generalized additive modeling (GAM). Key findings reveal distinct temporal patterns: diurnal O₃ peaks at 14:00 (lagging solar radiation by about 2 h), seasonal maxima in summer (157.58 μg m⁻³) driven by temperature-photochemistry coupling, and non-monotonic annual trends (116.21–123.77 μg m⁻³) despite NO_x decline, reflecting transitional chemical regimes. Alkenes (36.94 %) and oxygenated VOCs (OVOCs, 36.54 %) dominated O₃ formation potential, with acetaldehyde, ethylene, and 1-butene as top contributors, highlighting the significant contributions of industrial and vehicular emission sources to O₃ formation. GAM analysis identified temperature as the primary driver, exhibiting exponential O₃ enhancement above 30 °C. In particular, NO₂ and peroxyacetyl nitrate showed synergistic effects, suggesting their dual roles as both precursors and indicators of radical cycling efficiency under the RH range. The 40 %–60 % RH range optimizes hydroxyl radical production while minimizes aerosol hydration, establishing it as a critical threshold for photochemical O₃ generation. These findings emphasize the importance of considering specific RH ranges and precursor reactivity in formulating refined O₃ pollution control strategies, providing a new theoretical basis for O₃ pollution control in the Yangtze River Delta region.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102648"},"PeriodicalIF":3.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597291","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":"Improving PM2.5 simulations using LSTM: a study on spatiotemporal generalization","authors":"Xingtian Chen ,&nbsp;Yuhang Zhang ,&nbsp;Kai Cao ,&nbsp;Dongxing Li ,&nbsp;Qizhong Wu","doi":"10.1016/j.apr.2025.102647","DOIUrl":"10.1016/j.apr.2025.102647","url":null,"abstract":"<div><div>Deep learning models, particularly long short-term memory (LSTM) networks, have shown strong potential for bias correction in air quality simulations. Although LSTM-based models have demonstrated success in improving PM_2.5 simulations during specific periods such as winter months or heavy pollution events, their ability to generalize across varying temporal intervals and geographical locations remains underexplored. This study systematically investigates the spatiotemporal generalization capabilities of LSTM-based (LSTM_Local, LSTM_Regional, LSTM_Regional-idx, LSTM_Regional-sub) models across 12 monthly intervals and 34 monitoring sites in Beijing. Benchmark comparisons with alternative deep learning models (RNN, GRU, BPNN, CNN) demonstrate the superiority of LSTM-based model in improving predictive performance. Seasonal analysis reveals that the LSTM_Local and LSTM_Regional-sub model achieved modest gains during summer half-year (May to October) but achieved significant improvements during winter half-year (November to April), with average RMSE reductions of −5.89 % (November), −17.40 % (December), −6.37 % (January), 0.36 % (February), −5.87 % (March) and −1.57 % (April). Spatially, urban sites show moderate gains, but suburban sites exhibit greater improvement, with average RMSE of −5.14 % (Center), −2.26 % (South-East), −7.05 % (North-East), −8.39 % (South-West) and −12.37 % (North-West). These findings highlight the robust spatiotemporal generalization of LSTM-based models and support their applicability for real-time bias correction, long-term forecasting, and air quality dataset enhancement at fine spatial and temporal resolutions.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102647"},"PeriodicalIF":3.9,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686007","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":"Comparison of MERRA-2 black carbon aerosols and ground observation at a high-altitude mountainous site in southern China","authors":"Cheng Liu ,&nbsp;Lichen Deng ,&nbsp;Aijun Yan ,&nbsp;Xinjie Liu ,&nbsp;Jiening Huang ,&nbsp;Xinrui Miao ,&nbsp;Yue Qian ,&nbsp;Renguo Zhu ,&nbsp;Xiaozhen Fang ,&nbsp;Wei Guo","doi":"10.1016/j.apr.2025.102644","DOIUrl":"10.1016/j.apr.2025.102644","url":null,"abstract":"<div><div>Black carbon (BC) is an important light-absorbing component of atmospheric aerosols and plays a crucial role in regional/global climate and human health. In contrast to the predominant focus on urban BC aerosols in existing literature, this study comprehensively compared and studied the temporal variations of BC concentration at a high-altitude mountainous site (Mt. Lushan) in southern China based on long-term (2008–2022) ground observations and elevation-corrected MERRA-2 reanalysis. Results indicate that both the observed and MERRA-2 annual mean BC concentrations show a downward trend over the years. However, the observed decline rate (−0.115 μg m⁻³ yr⁻¹) is considerably larger than that of MERRA-2 (−0.045 μg m⁻³ yr⁻¹), mainly attributed to MERRA-2's static emission inventory after 2013. Both datasets capture a “V-shaped” monthly variation pattern, but MERRA-2 overestimates winter BC by 68 % and underestimates summer BC by 8 %. Despite notable discrepancies during winter and at night, the diurnal variations of MERRA-2 and observed BC exhibit a consistent unimodal distribution, with its peak occurring between 12:00 and 17:00 local standard time (LST). This pattern contrasts with those observed in urban areas. A comparison reveals that using ground-level MERRA-2 reanalysis against the observation at Mt. Lushan results in larger biases than that using station elevation-matched product. This suggests that station elevation plays a significant role in the temporal variation of BC concentration, and it is preferable to use model-level BC data from MERRA-2 that corresponds to the actual station altitude for comparison at such high-altitude sites. These results could provide a referenced evaluation and promote the understanding on the applicability and accuracy of the MERRA-2 BC variation pattern over high-altitude sites.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102644"},"PeriodicalIF":3.9,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562858","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":"Investigation on vehicle emission factors in urban tunnels through mobile measurements with an optimized estimation method","authors":"Chaowen Jiang ,&nbsp;Chao Lin ,&nbsp;Yu Zhao ,&nbsp;Zhiwen Luo ,&nbsp;Tianyi Zhao","doi":"10.1016/j.apr.2025.102646","DOIUrl":"10.1016/j.apr.2025.102646","url":null,"abstract":"<div><div>Urban traffic pollution, driven by vehicle exhaust emissions, necessitates accurate assessment through Emission Factors (EFs). While tunnel measurements are commonly used, previous studies relied on fixed sampling points near tunnel entrances and exits, making results vulnerable to external influences. This study aims to elucidate the spatial patterns of EFs within tunnels and their influencing factors using multi-season mobile measurements, providing a reference for optimizing the selection of fixed testing points. Through the mobile measurements of Lianhuashan Tunnel in Dalian, real-time particulate matter concentration data were collected during vehicular transit, and variations in EFs at different locations were analyzed. The average EFs in spring, summer, and winter were 3.07 ± 0.84, 0.56 ± 0.12, and 0.90 ± 0.41 (mg/veh/km), respectively. Factors influencing the distribution characteristics of EFs within the tunnel include complex traffic conditions, characteristics specific to the EFs calculation equation employed in mobile measurement, and the influence of natural wind direction at the tunnel exit. Congestion or intermittent movement causes uneven EFs distribution. In cases of short sampling distances, small fluctuations in pollutant concentrations may result in overestimated EFs. Reverse winds at the exit may also inflate EFs due to pollutant accumulation. It is suggested that the optimal locations for fixed measurements lie within the range of 30 %–84 % of the tunnel length from the entrance.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102646"},"PeriodicalIF":3.9,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597289","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 the NO2 pollution and its connection with PM2.5 and O3 in Dazhou based on source apportionment","authors":"Xu Liu ,&nbsp;Pulong Chen ,&nbsp;Congwu Huang ,&nbsp;Tijian Wang ,&nbsp;Tao Niu ,&nbsp;Mengmeng Li ,&nbsp;Rong Li ,&nbsp;Hao Wu ,&nbsp;Yawei Qu","doi":"10.1016/j.apr.2025.102645","DOIUrl":"10.1016/j.apr.2025.102645","url":null,"abstract":"<div><div>Dazhou, as one of the key construction cities in the Sichuan-Chongqing economic belt, has experienced accelerated economic development, accompanied by a dense population, extensive infrastructure construction, and rapid industrial growth. Consequently, air pollution has become increasingly severe, with the mass concentration of NO₂, a primary pollutant, being a significant constraint on air quality management in the city. This study utilizes the WRF-CMAQ (Weather Research and Forecasting Model-Community Multi-scale Air Quality) model to quantitatively analyze the main sector sources of NO₂ in Dazhou during different seasons in 2022. The findings reveal that industrial sources contribute the most to NO₂ pollution in spring and winter, while transportation sources dominate in autumn. Additionally, the correlation between PM_2.5, O₃, and NO₂ concentrations, which exhibit significant seasonal variations, was examined. Notably, in summer, a negative correlation between O₃ and NO₂ concentrations was observed, while a positive correlation between PM_2.5 and NO₂ concentrations was evident in winter. Furthermore, the correlation between NO₂, O₃ and PM_2.5 concentrations across different sectors was analyzed using ISAM (The Integrated Source Apportionment Method). In spring, the energy sources of NO₂ and the transportation sources of O₃ are significantly negatively correlated, with a correlation coefficient of −0.94. Additionally, the residential sources of NO₂ are significantly positively correlated with the transportation sources of PM_2.5, with a correlation coefficient of 0.96. In autumn, the energy sources of NO₂ exhibit the most significant correlations with the industrial sources of O₃ and the transportation sources of NO₂ and PM_2.5. In winter, the correlations among various sectors for O₃ pollution are not significant, with correlation coefficients ranging from 0.02 to 0.63. The highest correlation is observed between the industrial sources of NO₂ and the residential sources of PM_2.5, reaching 0.98. This study analyzed the main source sectors of NO₂ in Dazhou City and the correlation with the source sectors of O₃ and PM_2.5 by using the CMAQ-ISAM source apportionment method, revealing the importance of seasonal cooperation in air pollution control in Dazhou and emphasizing its significance for long-term pollution management.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102645"},"PeriodicalIF":3.9,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572821","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":"Reanalysis-based retrieval of near-surface ozone concentrations and its implications for ozone pollution events across China","authors":"Lili Wang ,&nbsp;Xingchuan Yang ,&nbsp;Haili Zhou ,&nbsp;Yang Yang ,&nbsp;Jiantao Dong ,&nbsp;Shuo Dong ,&nbsp;Wenji Zhao ,&nbsp;Minghui Tao ,&nbsp;Pengfei Ma","doi":"10.1016/j.apr.2025.102643","DOIUrl":"10.1016/j.apr.2025.102643","url":null,"abstract":"<div><div>Ozone (O₃) pollution has become a serious environmental issue in China, posing a significant threat to human health. However, existing satellite-based surface ozone concentration retrieval products are often restricted by data gaps and low spatial resolution, which limit their accuracy and applicability. Therefore, this study integrated reanalysis data from the National Centers for Environmental Prediction (NCEP) and ground-based observations, employing the XGBoost machine learning algorithm to estimate near-surface ozone concentrations across China at a high spatial resolution of 1 km. The model performed excellently in sample-based 10-fold cross-validation, achieving an R² of 0.91 and an RMSE of 13 μg/m³. Case studies of ozone pollution in two typical industrial cities (Tianjin and Dongguan) revealed the spatial heterogeneity of ozone pollution, supporting fine-scale regional monitoring. With the advantages of high spatial resolution and full coverage, our dataset successfully captured a prolonged ozone exposure event in eastern China from 12 June to July 15, 2023. This dataset holds great potential for applications in ozone exposure assessment and environmental impact studies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102643"},"PeriodicalIF":3.9,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564025","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}