Atmospheric Pollution Research最新文献

{"title":"Impacts of cool roofs on urban heat island and air quality in Dhaka, Bangladesh: A case modeling study during a heat wave","authors":"Abeda Tabassum ,&nbsp;Kyeongjoo Park ,&nbsp;Seong-Ho Hong ,&nbsp;Jong-Jin Baik ,&nbsp;Beom-Soon Han","doi":"10.1016/j.apr.2025.102549","DOIUrl":"10.1016/j.apr.2025.102549","url":null,"abstract":"<div><div>This study investigates the impacts of cool roofs on the urban heat island (UHI) and air quality in Dhaka, Bangladesh during an extreme heat wave event occurring in April 2021. A simulation with conventional roofs having an albedo of 0.2 and a simulation with cool roofs having an albedo of 0.8 are conducted using the Weather Research and Forecasting (WRF) model. Cool roofs reduce the 2-m temperature by 0.57 °C in the afternoon (1200–1700 LST) and cause the urban cool island in the daytime. In the afternoon, cool roofs reduce the planetary boundary layer height by 265 m and greatly suppress the urban breeze, reducing the 10-m wind speed by 0.8 m s⁻¹. As a result, the near-surface passive tracer (carbon monoxide) concentration increases by 45 ppb (52 %) in the afternoon. Cool-roof effects on the UHI and air quality are overall more pronounced in hotter areas. Cool roofs lead to statistically significant decreases in Humidex (−0.19), discomfort index (0.22), and heat index (−0.36 °C) in the afternoon, but all indices remain within the same stress levels. This suggests that additional measures such as urban greenery and other climate-sensitive urban designs are required along with cool roofs for an effective mitigation of urban extreme heat in Dhaka.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102549"},"PeriodicalIF":3.9,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855451","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":"Emission characteristics and removal efficiencies of SO2, NOx, particulate matter, and dioxins in iron ore sintering after ultra-low emission transformation","authors":"Yuhao Zhang ,&nbsp;Peiqiang Zhao ,&nbsp;Dahai Yan ,&nbsp;Mingli Li ,&nbsp;Xinglin Zhang ,&nbsp;Changhao Cui ,&nbsp;Chao Chen","doi":"10.1016/j.apr.2025.102543","DOIUrl":"10.1016/j.apr.2025.102543","url":null,"abstract":"<div><div>Iron ore sintering, as the dominant pollutant source in China's iron and steel industry, is responsible for substantial emissions of SO₂, NO_x, particulate matter (PM), and dioxins, posing critical challenges to air quality. This study evaluated the performance of ultra-low emission transformation, a nationwide initiative to further restrict industrial emissions through advanced air pollution control technologies, in controlling multi-pollutant emissions from sintering flue gas. The results demonstrated that ultra-low emission transformation significantly reduced the concentrations of SO₂, NO_x and PM, in sintering flue gas, with emission factors after transformation plummeting to 0.007, 0.005, and 0.002 kg/t-iron ore, respectively, representing reductions of 98.8–99.2 % compared to pre-transformation scenario. The electrostatic precipitator showed a multi-pollutant controlling ability, exhibiting 34.1 %, 93.1 %, 93.0 %, and 93.8 % of SO₂, PM, dioxins mass concentration and dioxins I-TEQ removal efficiency, respectively. Meanwhile, the semi-dry flue gas desulfurization achieved81.7 % and 82.3 % dioxins removal efficiency. Notably, the unexpected increase in dioxin emissions across selective catalytic reduction, attributed to temperature-dependent catalytic reformation, provides critical insights for optimizing air pollution control device configurations to avoid trade-offs in multi-pollutant control. This work provides industrial-scale evidence supporting China's ultra-low emission transformation policy in iron ore sintering, offering a technically available pathway to reconcile emission reduction targets with sustainable steel production.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102543"},"PeriodicalIF":3.9,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838225","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":"Temporal dynamics and source characteristics of fine particulate matter using Positive Matrix Factorization (PMF)","authors":"Vikas Kumar ,&nbsp;Manoranjan Sahu ,&nbsp;Basudev Biswal ,&nbsp;Jai Prakash ,&nbsp;Shruti Choudhary ,&nbsp;Ramesh Raliya ,&nbsp;Tandeep S. Chadha ,&nbsp;Jiaxi Fang ,&nbsp;Pratim Biswas","doi":"10.1016/j.apr.2025.102539","DOIUrl":"10.1016/j.apr.2025.102539","url":null,"abstract":"<div><div>The temporal granularity of data in receptor models plays a key role in identifying emission patterns and episodic pollution events, which are essential for robust source apportionment. Low-time resolution measurements may overlook short-term variations, leading to an incomplete representation of pollution sources. This study investigated the source characteristics and contributions of PM_2.5 across different time resolutions (1-h, 2-h, 4-h, 8-h, 12-h, and 24-h) and seasons, using multi-time-season-resolved chemical composition data collected at Major Dhyan Chand National Stadium in Delhi from May 2019 to February 2020. Positive Matrix Factorization (PMF) identified eight consistent factors across all time resolutions and seasons: two solid fuel combustion sources (SFC1 and SFC2), an S-rich source, traffic (exhaust and non-exhaust), dust, and three anthropogenic industrial/combustion plume events (Cl-Br, Pb-Se, and Cu-Cd). The comparison of source profiles and contributions at different time resolutions revealed that SFC1 exhibited the highest temporal variability across all seasons, followed by Cl-Br, traffic, Pb-Se, and Cu-Cd, while S-rich and dust factors remained relatively stable. The variation in source profiles over time, influenced by species mixing, posed challenges for source identification. A sensitivity analysis using the coefficient of divergence (CoD) showed that heterogeneity in source profiles increased with coarser time resolution, indicating the need for high-resolution data to capture dynamic source variations. Given these findings, a rolling-PMF approach with high-resolution data could improve real-time source apportionment by updating source profiles at regular intervals to reflect ever-changing emissions sources better. This study highlights the importance of high-resolution data in achieving accurate and temporally resolved source apportionment, essential for air quality management and policy development.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102539"},"PeriodicalIF":3.9,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865138","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":"Spatiotemporal distribution and hotspot positioning of odors in an industrial area: A case study on identifying potential emission sources using a mobile micro-sensing vehicle","authors":"Yu-Lun Tseng ,&nbsp;Chung-Shin Yuan ,&nbsp;Chiu-Ying Pan ,&nbsp;Wen-Hsi Cheng","doi":"10.1016/j.apr.2025.102542","DOIUrl":"10.1016/j.apr.2025.102542","url":null,"abstract":"<div><div>This study utilized a micro-sensing device to identify the spatiotemporal distribution of sulfide (H₂S), ammonia (NH₃), and total volatile organic compounds (TVOCs) in an industrial park located at southern Taiwan. These devices were installed on a mobile vehicle and integrated with geographic information systems (GIS) and global positioning systems (GPS) for real-time environmental monitoring. The monitoring data were used to plot concentration contours with a SURFER mapping software for tracking emission sources. There was a composting facility to the northwest and two livestock farms to the north of the industrial park, which were estimated to be the sources of the high concentrations of H₂S (360–600 ppb) and NH₃ (840–1500 ppb) in the northeastern region of the industrial area. Additionally, two large solvent recovery treatment factories in the northwest are emitting VOCs (180–1200 ppb), contributing to the odorous source of organic pollutants. The results successfully confirmed that the locations of odor complaints were highly correlated with the odor detection hotspots. Therefore, the mobile intelligent vehicle equipped with micro-sensing device can accurately position the locations of odor pollution and further assist environmental inspection agencies for pollution prevention.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102542"},"PeriodicalIF":3.9,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834125","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":"Machine learning analysis of drivers of differences in PAH content between PM1 and PM10 in Zagreb, Croatia","authors":"Nikolina Račić ,&nbsp;Gordana Pehnec ,&nbsp;Ivana Jakovljević ,&nbsp;Zdravka Sever Štrukil ,&nbsp;Francesco Mureddu ,&nbsp;Michael Forsmann ,&nbsp;Mario Lovrić","doi":"10.1016/j.apr.2025.102541","DOIUrl":"10.1016/j.apr.2025.102541","url":null,"abstract":"<div><div>Particulate matter (PM) is a critical component of air pollution, with its size fractions, PM₁ and PM₁₀, posing varying risks to human health. Among its constituents, polycyclic aromatic hydrocarbons (PAHs) are of particular concern due to their toxicity and ability to affect respiratory health. PM₁ particles, being smaller, can penetrate deeper into the respiratory system, making the distribution of PAHs across PM₁ and PM₁₀ especially relevant. This study examines the seasonal patterns and factors influencing PAH concentrations in PM₁ and PM₁₀ collected in Zagreb, Croatia. A combination of machine learning (ML) techniques, including Random Forest (RF) regression and Principal Component Analysis (PCA), and statistical approaches like t-tests and Cohen's d, were applied to explore these relationships. Post-hoc interpretation using SHapley Additive exPlanations (SHAP) clarified the contribution of various predictors in the models. Results indicated that PAH concentrations contributions were higher in PM₁ than PM₁₀, posing greater health risks associated with finer particles. Seasonal trends showed increased PAH levels during winter and spring, primarily driven by heating activities and temperature inversions. The study also highlighted the \"J_Curve_Day\" variable as the most critical predictor in RF regression models, capturing the influence of seasonal changes on PAH levels through its representation of meteorological conditions and atmospheric processes. These insights shows the importance of understanding seasonal variability in PAH distributions within PM to inform air quality management and public health strategies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102541"},"PeriodicalIF":3.9,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838223","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":"Quantitative source apportionment of surface ozone in Liaoning Province, China, under the Asian summer monsoon background","authors":"Ningwei Liu ,&nbsp;Simeng Ma ,&nbsp;Kun Wang ,&nbsp;Sen Yang ,&nbsp;Zhigang Zhang","doi":"10.1016/j.apr.2025.102540","DOIUrl":"10.1016/j.apr.2025.102540","url":null,"abstract":"<div><div>At present, few quantitative study has been carried out on the proportion of local generation and long range transport of ozone in Liaoning, which is the key to reveal regional ozone pollution. Using the Ozone Source Apportionment Technology in the CAMx model, surface ozone concentrations in Liaoning Province, China, were simulated during the warm season of 2023. The contributions of 23 source regions, five industrial sectors, and two chemical precursors to ozone concentrations in 14 cities in Liaoning were determined under the Asian summer monsoon (ASM) background. The major components were lowest in May and increased from June to August, reflecting a significant increase in the northward transport of ozone and its precursors from upstream regions (north and east China) with the onset of the ASM. The contribution of surrounding provinces to Liaoning's ozone embodied the principle of \"proximity and directness\" - the more direct the transport direction of the ASM and the closer the source province to the receptor city, the greater the contribution from source to receptor. Under the ASM background, most ozone was transported from upwind to downwind cities within Liaoning (e.g., Dalian contributed 1.44 % to Anshan, Dandong contributed 1.76 % to Benxi), indicating that the prevailing southwest wind transported ozone and its precursors from upstream cities, contributing to the ozone concentrations in downstream cities. The results may provide reference for regional ozone pollution control.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102540"},"PeriodicalIF":3.9,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828968","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 microplastic deposition in Guilin karst wetlands: Sources and agricultural impact","authors":"Lishan Zhang,&nbsp;Bihong Xu,&nbsp;Zengxian Wei,&nbsp;Xiaolu Liang,&nbsp;Yan Chen,&nbsp;Xuan Ru,&nbsp;Qian Zhang,&nbsp;Shan Zhong","doi":"10.1016/j.apr.2025.102537","DOIUrl":"10.1016/j.apr.2025.102537","url":null,"abstract":"<div><div>Atmospheric deposition of microplastics (MPs) poses a significant threat to natural wetlands. This study investigates the characteristics, distribution, and sources of atmospheric MPs in the Huixian Wetland, focusing on the influence of land use and human activities. The results show an average MP deposition rate of 98.85 ± 43.50 items·m⁻²·d⁻¹, with wet deposition at 110.93 ± 42.67 items·m⁻²·d⁻¹ and dry deposition at 86.17 ± 41.67 items·m⁻²·d⁻¹. Deposition rates were found to be significantly higher in non-wetland park areas compared to wetland parks. MPs smaller than 500 μm comprised 60 % of the total, predominantly fibrous (93 %) and colorless or transparent (83 %). The dominant polymers were PE (31 %) and PP (23 %). The primary source of atmospheric MPs in the Huixian Wetland is local agricultural activity. Cluster analysis indicates that atmospheric MPs serve as a major source of microplastics in other environmental media within the wetland. The geological characteristics of the wetland, coupled with agricultural practices, exacerbate microplastic pollution. Additionally, human activities such as tourism and transportation contribute to the influx of MPs into the wetland. This study provides essential insights for the management and reduction of MP pollution in karst wetlands and protected areas.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102537"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874140","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":"Estimation and impact factor analysis of 24-h near-surface ozone concentration in China using FY-4A/B collaboration and machine learning","authors":"Yixuan Wang ,&nbsp;Bin Chen ,&nbsp;Qia Ye ,&nbsp;Lin Zhao ,&nbsp;Zhihao Song","doi":"10.1016/j.apr.2025.102538","DOIUrl":"10.1016/j.apr.2025.102538","url":null,"abstract":"<div><div>Ozone pollution in China's urban agglomerations poses a significant environmental challenge. Nine machine learning models were constructed based on the Extra Tree (ET) algorithm, utilizing top-of-atmosphere radiation (TOAR) data from Fengyun (FY)-4A and FY-4B Advanced Geosynchronous Radiation Imager (AGRI), to estimate 24-h near-surface ozone concentrations across China from June 2022 to May 2023. Analysis identified five TOAR channels strongly correlated with ozone concentrations: channels 7, 8, and 11–13 for FY-4A, and channels 7, 8, and 12–14 for FY-4B. The all-sky data model demonstrated superior performance in ozone estimation, achieving an R² of 0.91, outperforming models using only cloudy or clear-sky data. Through partial dependency plots and feature importance assessments, key meteorological drivers were identified: relative humidity below 60 % and temperatures between 20 and 35 °C. These findings provide valuable insights for ozone forecasting and pollution control strategies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102538"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828967","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 heat-pollution paradox: understanding the relationship between land surface temperature and air pollution in a heavily polluted megacity","authors":"Manob Das ,&nbsp;Arijit Das ,&nbsp;Suman Singha","doi":"10.1016/j.apr.2025.102531","DOIUrl":"10.1016/j.apr.2025.102531","url":null,"abstract":"<div><div>In rapidly urbanizing megacities, increasing land surface temperature (LST) and acute air pollution present considerable environmental and public health issues. Urban sprawl, industrial discharges, and automotive emissions degrade air quality, while heat-absorbing surfaces exacerbate urban heat island (UHI) phenomena. Comprehending the correlation between LST and air pollution is essential, as elevated temperatures can exacerbate pollutant concentrations via photochemical reactions and meteorological alterations. This study aims to assess the relationship between LST and air pollution during winter and summer in Delhi (India) using Remote Sensing and National Air Quality Monitoring Program (NAMP). The findings showed that the LST in Delhi exhibited seasonal variation, with summer LST reaching a maximum of 31.08 °C (mean: 28.99 °C) and winter LST declining to 16.30 °C (mean: 18.29 °C). Elevated LST were recorded in the northern, eastern, and western regions during the summer season. Air pollution exacerbated in winter, with particulate matter i.e. PM_2.5 and PM₁₀ concentrations attaining 277.13 μg/m³ and 228.33 μg/m³, respectively, whilst O₃ concentrations peak in summer at 41.08 μg/m³. The core areas maintained higher LST than the transitional zones. PM₁₀ exhibited a strong correlation with LST (winter: 0.611, summer: 0.222), affecting heat retention, but CO and O₃ demonstrated weak correlations relationships. Increased winter PM₁₀ levels (0.767) correlated with heightened summer surface UHI (SUHI), underscoring the significance of PM in warming. The study emphasized the necessity of targeted mitigation strategies, such as the expansion of urban natural infrastructure, to mitigate LST and air pollution. Policies should prioritize the integration of heat mitigation measures into city planning, the enhancement of air quality monitoring, and the regulation of winter PM levels.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102531"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855410","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":"Physico-chemical characterization of atmospheric particles during two intense dust storms in the vicinity of Thar Desert","authors":"Mamta Devi ,&nbsp;Sumit Kumar Mishra ,&nbsp;Aravindakshan Jayakumar ,&nbsp;Supreet Kaur ,&nbsp;Vikas Goel ,&nbsp;Vijayan Narayanasamy ,&nbsp;Gounda Abdul Basheed ,&nbsp;Kartika Pandey","doi":"10.1016/j.apr.2025.102532","DOIUrl":"10.1016/j.apr.2025.102532","url":null,"abstract":"<div><div>Particulate Matter (PM₅; aerodynamic diameter ≤5 μm) was collected over the Jhunjhunu region (28°80′N, 75°24′E) in the neighborhood of the Thar Desert, Rajasthan, India. Sample collection was done during two intense Dust Storm (DS) conditions i.e., DS-1 on May 4, 2022 and DS-2 on May 6, 2022. The physico-chemical properties of dust particles collected pre-, during, and post-DS events were studied using X-ray diffraction (XRD), X-ray Fluorescence Spectroscopy (XRF), and Scanning Electron Microscope coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS). The frequency distribution of AR (Aspect Ratio) of particles shows bimodal peaks in the bin range &gt;1.6–1.8 and &gt; 2.00–2.20 during DS-1 and monomodal peak at &gt;1.6–1.8 during DS-2, indicating most of the particles are highly non-spherical. Based on bulk compositional analysis of dust particles obtained using XRF, oxides of different elements were observed in the order of SiO₂&gt; Al₂O₃&gt; CaCO₃&gt;MgO &gt; Fe₂O₃&gt; Cr₂O₃ during both storms. Hematite (Fe₂O₃) which has high absorption potential in visible and near UV Wavelength is found to increase from 1.47 % (pre-DS) to 6.14 % (DS-1) and 5.43 % (DS-2), respectively. For the visible range spectrum (0.38–0.68 μm), it is discovered that the imaginary part of the refractive index (k) value rises from 0.004 to 0.048 during DS-1 and from 0.003 to 0.045 during DS-2. The present work could reduce the uncertainty in the radiation budget estimations of mineral dust over the Thar Desert region.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102532"},"PeriodicalIF":3.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870614","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}