Atmospheric Pollution Research最新文献

{"title":"Relationship between synoptic meteorology and daily surface O3 variation over China","authors":"Lihua Zhou ,&nbsp;Yong Luo ,&nbsp;Jianbin Huang ,&nbsp;Like Ning ,&nbsp;Huihui Yuan","doi":"10.1016/j.apr.2025.102642","DOIUrl":"10.1016/j.apr.2025.102642","url":null,"abstract":"<div><div>The diurnal variation of ozone (O₃) in China is severely affected by weather processes. In this study, the influence mechanism was further extracted through the coherent wave analysis (CWA) and multivariate empirical orthogonal function (MEOF) methods. The multi-factor time series correlation indicates that there is a significant correlation between the daily O₃ and meteorological factors variability within 1–3 weeks. Considering the high-altitude circulation, O₃ pollution often occurs behind the trough and in front of the ridge. Under this circulation pattern, hot and dry, less cloudy weather often occurs, which leads to an increase in the level of solar radiation reaching the ground. Higher temperatures and solar radiation promote photochemical reactions, and dry weather is not conducive to the removal of O₃ either. These conditions are all conducive to the generation and accumulation of O₃ in terms of dynamics, thermodynamics and photochemistry, etc. This further explains that the fluctuations of the mid-latitude westerlies have guided this change process. Atmospheric circulation drives the near-surface weather patterns, which further affect the near-surface O₃ patterns. This composite pattern further dominated the diurnal variations in the four key polluted areas. The dominant effect of the T/RH pattern on the diurnal variation of O₃ is greater than that of the dynamic field. The leading four PCs of the T/RH/O₃ field explain 57.4 %, 43.6 %, 32.9 % and 39.6 % of the NCP, YRD, PRD, and SCB O₃ variability, respectively. However, the leading four PCs of the SP/W/O₃ field explain 30.3 %, 36.7 %, 12.4 %, and 23.7 % of them, respectively.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102642"},"PeriodicalIF":3.9,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604158","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":"Investigating the role of meteorological parameters in the transport of air pollutants from LPG tank trailer explosion in Jaipur, India","authors":"Gourav Suthar ,&nbsp;Amit Singh Chandel ,&nbsp;Saurabh Singh","doi":"10.1016/j.apr.2025.102639","DOIUrl":"10.1016/j.apr.2025.102639","url":null,"abstract":"<div><div>Air pollution is a growing concern, especially during episodic events that significantly impact air quality and public health. This study examined the impact of air pollutants from an Liquefied Petroleum Gas (LPG) tank trailer explosion in Jaipur, focusing on pollutant transport and the role of meteorology in air quality changes in Jodhpur. The air quality across three phases Pre-Event, During-Event, and Post-Event was assessed by examining variations in pollutant (i.e., PM_2.5, PM₁₀, CO, NH₃) concentrations and their relationships with meteorological parameters. During the Pre-Event, PM_2.5 was low, while PM₁₀ were moderate. During the Event period, PM_2.5 and PM₁₀ concentrations surged severely to 380 μg/m³ and 430 μg/m³, respectively. CO peaking at 18.3 mg/m³, and NH₃ at 17.2 μg/m³, reflecting severe air quality deterioration. The Air Quality Index (AQI) level was 372 in the Pre-Event and reached 435 during the Event. Air Pollutant concentrations and AQI improved post-event due to wind and atmospheric mixing. Meteorological factors, including humidity, boundary layer height, and wind speed, played a critical role in the transport and dispersion of pollutants, with their combined effect contributing significantly to pollutant behavior and air quality fluctuations. This study supports Sustainable Development Goals <strong>(SDG) 3</strong> by addressing air pollution health risks, SDG 11 by emphasizing sustainable urban air quality management, and SDG 13 by examining meteorological impacts on pollution dispersion.</div><div>Overall, the study underscores the importance of meteorological conditions in shaping pollutant dispersion and highlights the need for targeted air quality management strategies to mitigate health risks from episodic pollution events.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102639"},"PeriodicalIF":3.9,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522400","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 application of a land-use regression model to investigate the effect of urban greenbelts on ambient PM10 and PM2.5 mitigation during seasons of light and heavy pollution","authors":"Y.M. Sun ,&nbsp;Y.L. Guan ,&nbsp;A. Przybysz ,&nbsp;C.Y. Zhu","doi":"10.1016/j.apr.2025.102641","DOIUrl":"10.1016/j.apr.2025.102641","url":null,"abstract":"<div><div>Greenbelts located close to traffic pollution sources can significantly attenuate air pollution by intercepting and assimilating the pollutants on a lasting basis. However, the impact of greenbelts can be affected by neighbouring land use. This paper investigated the effects of urban greenbelts on the mitigation of ambient PM₁₀ and PM_2.5 in Wuhan, China using a land-use regression (LUR) approach. Traffic-related pollution emissions had a crucial impact on PM₁₀ and PM_2.5 levels. The effect of greenbelts on PM₁₀ and PM_2.5 mitigation can be decreased by adjacent traffic pollution sources, but enhanced by increasing the width of the greenbelt. In addition, meteorological factors had a variable impact on PM levels during the seasons of light and heavy pollution. According to the LUR model, the combined effects of the greenbelt, traffic PM sources and meteorological factors were characterized by the threshold impact of greenbelt width on PM mitigation, with a width of 40 m having a significant and positive effect on PM levels. In addition, these effects varied with thresholds in different pollution conditions, and were less evident in the heavily polluted season. The combined effect of urban greenbelt on PM reduction should be explored in real-life conditions, which will have important practical significance for urban planning and construction.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102641"},"PeriodicalIF":3.9,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535910","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":"Health impacts and drivers of long-term ozone and nitrogen dioxide exposure in urban China","authors":"Zhaoli Yang ,&nbsp;Fangliang Li ,&nbsp;Rongmin Ye ,&nbsp;Huiping Ge ,&nbsp;Hongyu Li ,&nbsp;Shulian Zhang ,&nbsp;Jiaxin Wang ,&nbsp;Yuan Zhao ,&nbsp;Hong Gao ,&nbsp;Tao Huang ,&nbsp;Jianmin Ma","doi":"10.1016/j.apr.2025.102640","DOIUrl":"10.1016/j.apr.2025.102640","url":null,"abstract":"<div><div>Air pollution is a significant global health hazard and a major risk factor for mortality. Like many regions experiencing rapid economic development and urbanization, China continues to face persistent air pollution, with increasing O₃ levels and NO₂ as critical pollutants. This study analyzed the spatiotemporal distribution of O₃ and NO₂ in urban China from 2015 to 2020 using online monitoring data. Concentration-response functions (CRFs) were employed to assess health impacts. The result reveals that, while NO₂ pollution has declined during the six-year period, its level was still above air quality standard, and O₃ levels have escalated. The study identified a 62,100 increase in combined O₃- and NO₂-related deaths in 2020 compared to 2015, with the highest health burdens occurring in Central China. Critically, a major factor increasing health risks from air pollution is population aging, since the elderly exhibit heightened biological susceptibility to pollutant exposure. This underscores a growing challenge not only for China but also for aging societies worldwide. Taking the vulnerability of the aging population into account, new age-sensitive air quality standards and measures to mitigate health consequences of criteria air pollutants become imperative.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102640"},"PeriodicalIF":3.9,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501232","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 integrated modeling framework for PM2.5 source apportionment in the Yangtze River Delta using WRF-CMAQ and ISAM","authors":"Qianqian Li ,&nbsp;Youliang Chen ,&nbsp;Hamed Karimian ,&nbsp;Qin Fan ,&nbsp;Raihan Abbasi","doi":"10.1016/j.apr.2025.102637","DOIUrl":"10.1016/j.apr.2025.102637","url":null,"abstract":"<div><div>With the increasing complexity of the PM_2.5 pollution problem and the diversity of emission sources, source apportionment analysis has become an important tool to better understand the nature of PM_2.5 pollution. In this study, the PM_2.5 emission sources in the Yangtze River Delta (YRD) urban agglomeration were analyzed using a two-layer nested the Weather Research and Forecasting (WRF) model and the Community Multiscale Air Quality (CMAQ) model, combined with the Integrated Source Apportionment Method (ISAM) pollution source analysis module. Based on a comprehensive analysis of sectoral PM_2.5 source data for the autumn and winter seasons, key characteristics emerged: Nanjing was dominated by industrial sources, Hangzhou was prominent in residential sources, Hefei had a relatively complex pollution composition, and Shanghai saw a significant decrease in contributions from transportation sources in autumn. From a seasonal perspective, the overall PM_2.5 concentration was higher in winter than in autumn. This was particularly marked by increased contributions from agricultural, industrial, and power generation sources, indicating either greater emission intensity or poorer atmospheric dispersion conditions during winter. By tracking the transport pathways across the Yangtze River Delta (YRD) urban agglomeration in both seasons, we found the following: In winter, the contribution percentages from local sources, intra-regional transport, and extra-regional transport were 15.05 %–36.3 %, 35.60 %–62.10 %, and 16.9 %–36.23 %, respectively. In autumn, the respective contributions were 26.00 %–45.13 %, 31.51 %–56.44 %, and 17.56 %–27.59 %. Overall, compared to autumn, the contribution of local sources to PM_2.5 decreased during winter, while the proportion from long-range transport increased.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102637"},"PeriodicalIF":3.9,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522401","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":"Particulate matter and carbonaceous content in aerosols from Haiphong and Hanoi cities, Northern Vietnam","authors":"Catherine Guigue ,&nbsp;Pauline L. Martinot ,&nbsp;Sandrine Chifflet ,&nbsp;Léa Guyomarc'h ,&nbsp;Pamela A. Dominutti ,&nbsp;Jean-Luc Jaffrezo ,&nbsp;Thanh Ngo-Duc ,&nbsp;Van Hoi Bui ,&nbsp;Cam Tu Vu ,&nbsp;Gaëlle Uzu ,&nbsp;Marc Tedetti ,&nbsp;Xavier Mari","doi":"10.1016/j.apr.2025.102638","DOIUrl":"10.1016/j.apr.2025.102638","url":null,"abstract":"<div><div>Airborne particulate matter (PM) and its carbonaceous content (elemental carbon, EC and organic carbon, OC, including polycyclic aromatic hydrocarbons, PAHs) were investigated in Haiphong and Hanoi, two major cities in the Northern Vietnam, aiming at elucidating the relative importance of local and regional atmospheric pollution. The monthly average ranges of PM_2.5 were 14–37 μg m⁻³ in Haiphong, and 35–102 μg m⁻³ in Hanoi, respectively, during the period 2020–2023. EC, OC and PAH concentrations annually averaged 2.1 ± 1.3 μg m⁻³, 4.9 ± 3.1 μg m⁻³ and 4.4 ± 2.6 ng m⁻³ in Haiphong PM₁₀ from Oct. 2012 to Oct. 2013, and 1.3 ± 0.9 μg m⁻³, 9.1 ± 6.2 μg m⁻³ and 5.9 ± 5.8 ng m⁻³ in Hanoi PM_2.5 from Oct. 2019 to Dec. 2020, respectively. Seasonal variations were observed, with higher values during the dry season (winter) compared to the wet season (summer), as expected according to monsoon meteorological conditions. However, spatial variations and correlations between EC, OC, and PAHs, along with other markers of human activities (such as levoglucosan, secondary inorganic aerosols and metals), emphasized city-specific influence of local emission sources <em>versus</em> those transported from distant locations. Hanoi, highly urbanized, appeared to be yearly dominated by the local emissions while Haiphong, less urbanized and located near the sea, allowed to highlight seasonal variations in emission origin. While PM values exceeded up to 15 times international air quality recommendations, health risk assessment related to inhaled PAHs, in line with previous results relying on metals, remained low to moderate.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 11","pages":"Article 102638"},"PeriodicalIF":3.9,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562889","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":"PM2.5-bound PAHs in Chinese typical non-ferrous smelting area: appointment and risk assessment associated with specific industrial and biomass sources","authors":"Jianwu Shi ,&nbsp;Xiajiao Wu ,&nbsp;Xinyu Han ,&nbsp;Yaoqian Zhong ,&nbsp;Jian Yang ,&nbsp;Ying Cao ,&nbsp;Senlin Tian ,&nbsp;Ping Ning","doi":"10.1016/j.apr.2025.102635","DOIUrl":"10.1016/j.apr.2025.102635","url":null,"abstract":"<div><div>The non-ferrous smelting industry (NSI) is a key source of atmospheric organic compounds, leading the serious impacts on the surrounding environment and the health of residents over industrial concentration areas. In this study, nine sampling sites were arranged in the NSI aggregation area for seasonal monitoring of PM_2.5-bound PAHs. Our results revealed that total concentration of PM_2.5-bound PAHs was 10.9 ± 4.70 ng/m³. These values reached 49.1 ng/m³ near the NSI, which were 2.8–4.2 times greater than the concentration of the background sample. Seasonal vary caused by sources and meteorology resulted in an average concentration in winter (16.2 ± 2.08 ng/m³) that was 2.6 times higher than that in summer. Based on appointment of specific sources, NSI sources account for 23.5 %–28.5 % of PAHs and biomass burning (BB) contributes significantly to PAHs, up to 28.9 % in spring. The long-range transportation of BB smoke in Southeast Asia is considered the major reason, combined with trajectories and fire spots. Risk assessment showed vehicle and NSI emissions accounted for over 71.1 % of the cancer risk from PM_2.5-bound PAHs exposure. Residents have a higher cancer risk in winter, and the incremental lifetime carcinogenic risk values of adults around the NSI exceed the threshold value (10⁻⁶). The results indicate that residents living near NSI areas face higher health risks, and suggest controlling and managing PAHs emissions related to the NSI.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102635"},"PeriodicalIF":3.9,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518528","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":"Novel algorithm for using the Sky Quality Meter as a night cloud detector and aerosol concentration meter","authors":"S. Cavazzani ,&nbsp;P. Fiorentin ,&nbsp;C. Bertolin ,&nbsp;S. Ortolani ,&nbsp;A. Bertolo ,&nbsp;R. Binotto","doi":"10.1016/j.apr.2025.102636","DOIUrl":"10.1016/j.apr.2025.102636","url":null,"abstract":"<div><div>The measurement of aerosol optical depth (AOD) has great multidisciplinary importance (e.g. climate change, human health, meteorological models). This work describes a novel algorithm for AOD measurement using a Sky Quality Meter (SQM). SQM measures night sky brightness (NSB) and it is mainly used for monitoring light pollution (LP). The algorithm adds the ability to estimate the AOD under clear sky conditions to the already published use of the SQM as a night cloud detector (CD).</div><div>The aerosol concentration meter (ACM) algorithm is applied to two-year measurements (2021–2022) at three sites. Two sites are of astronomical importance, such as the Ekar astronomical observatory (Asiago, Italy) and the La Silla astronomical observatory (Chile). The two sites allow calibration of the algorithm under high-LP and practically no-LP conditions. In addition, the Padua site (Po Valley, Italy) tests the algorithm in critical conditions of atmospheric dust concentration and LP. An accurate error analysis is described, and the algorithm is validated through comparison with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The complexity of the NSB-aerosol interaction in relation to the scattering phenomenon in the three sites of Padua, Ekar and La Silla involves limits on the AOD daily analysis, but SQM-ACM algorithm has its best application in monthly AOD statistics with respective relative errors of 0.10, 0.07 and 0.04.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102636"},"PeriodicalIF":3.9,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549382","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":"Potential respiratory hazards of fungal exposure in the residential indoor environment: a systematic review","authors":"Hai Xiao ,&nbsp;Jianghong Yang ,&nbsp;Hongwei Lou ,&nbsp;Mingxin Luo ,&nbsp;Qin Yang","doi":"10.1016/j.apr.2025.102634","DOIUrl":"10.1016/j.apr.2025.102634","url":null,"abstract":"<div><div>As concern over indoor environmental health increases, the health risks associated with microbial exposure have received growing attention. Fungi, as ubiquitous airborne microorganisms, release spores and metabolites that can trigger allergic responses and contribute to the onset or exacerbation of respiratory diseases such as asthma and rhinitis. However, systematic evaluations of the relationship between indoor fungal contamination and respiratory health remain limited, especially under real-world exposure conditions. This review was conducted via comprehensive literature search on Web of Science, PubMed, and Google Scholar, covering studies from 1990 to 2025. A total of 94 studies were included, comprising 31 on fungal sources, 48 on respiratory health impacts, and 15 on prevention strategies in residential environments. Findings show that building deterioration, especially causing Penicillium and Aspergillus proliferation, is a major fungal source, and building materials affect species distribution. Filamentous fungi from various environmental sources are associated with allergic rhinitis, asthma, tonsillitis, adenoid hypertrophy, and impaired lung function. Current mitigation approaches focus on chemical and physical control measures. This review provides an integrated overview of fungal exposure sources in indoor environments, their respiratory health implications, and the underlying mechanisms, offering scientific insights for prevention and control of fungus-related diseases in residential settings.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102634"},"PeriodicalIF":3.9,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501233","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":"Seasonal multisite low-cost sensor measurements to estimate spatial and temporal variability of particulate matter pollution in Nairobi, Kenya","authors":"Ezekiel W. Nyaga ,&nbsp;Michael R. Giordano ,&nbsp;Matthias Beekmann ,&nbsp;Daniel M. Westervelt ,&nbsp;Michael Gatari ,&nbsp;John Mungai ,&nbsp;Godwin Opinde ,&nbsp;Albert A. Presto ,&nbsp;Emilia Tjernström ,&nbsp;V. Faye McNeill ,&nbsp;R. Subramanian","doi":"10.1016/j.apr.2025.102630","DOIUrl":"10.1016/j.apr.2025.102630","url":null,"abstract":"<div><div>Ambient concentrations of fine particulate matter (PM_2.5) in sub-Saharan African cities like Nairobi can vary significantly due to the distribution and intensity of local and regional emission sources. We assess the spatiotemporal variability of PM_2.5 in Nairobi using low-cost sensor and reference instrument data from urban background (2020–2022) sites and from several source-specific sites (June to December 2021). To our knowledge, this work represents the longest and most spatially differentiated dataset for this city.</div><div>Data from urban background sites demonstrates seasonal variation driven by precipitation. PM_2.5 concentrations were higher during the warm-dry (JF, 17.1–18.8 μg m⁻³) and cool-dry (JJAS, 21.0–25.5 μg m⁻³) seasons and lower during the rainy seasons of MAM (14.8–17.0 μg m⁻³) and OND (13.2–17.2 μg m⁻³). Seasonal differences are systematic, and larger than the inter-annual variability. Our analysis of source-specific PM_2.5 measurements (June to December 2021) reveals for the more polluted JJAS season the highest PM_2.5 recorded at traffic/residential sites (28.8–29.1 μg m⁻³), followed by urban background (23.3–24.1 μg m⁻³) and sub-urban background (22.5 μg m⁻³). The traffic/residential impacted sites demonstrate noticeable morning and evening peaks associated with traffic and residential emissions, while diurnal profiles for urban background and sub-urban background sites remain flat during the day but display noticeable evening peaks, pointing again to the impact of residential emissions. At the urban background site and during the JJAS season, an additional midday peak is probably related to residential cooking emissions.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 10","pages":"Article 102630"},"PeriodicalIF":3.9,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572660","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}