Atmospheric Pollution Research最新文献

{"title":"Spatiotemporal variations of tropospheric formaldehyde and its potential sources over Pakistan based on satellite remote sensing","authors":"Ayesha Mariam ,&nbsp;Ushna Bint E. Ishfaq ,&nbsp;Asim Daud Rana ,&nbsp;Syeda Adila Batool ,&nbsp;Shahid Parvez ,&nbsp;Munawar Iqbal","doi":"10.1016/j.apr.2025.102483","DOIUrl":"10.1016/j.apr.2025.102483","url":null,"abstract":"<div><div>Formaldehyde (HCHO) is a trace gas that harms the atmospheric environment and human health. Therefore, it is essential to analyze the spatial dynamic characteristics of HCHO, potential sources, and the associated health risks. To do so, the current study utilized the TROPOspheric Monitoring Instrument (TROPOMI) HCHO observations to analyze the spatiotemporal variations of HCHO in Pakistan from 2019 to 2023. Moreover, the potential source areas of HCHO are also identified using the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) technologies. The results indicate an annual average HCHO concentration increase in Pakistan from 114 μmol/m² (in 2019) to 117 μmol/m² (in 2023) with a 0.3% growth rate. The average HCHO concentration in Punjab (177 μmol/m²), Sindh (138 μmol/m²), and KPK (121 μmol/m²) provinces is above the country average (105 μmol/m²). Lahore, Gujranwala, and Peshawar are the top HCHO emitters in Pakistan with mean HCHO of 204.25 ± 18.85 μmol/m², 202.51 ± 8.14 μmol/m², and 201.65 ± 13.66 μmol/m², respectively. The study found the industrial sector as the main contributor to HCHO emissions in Pakistan, followed by the residential and transportation sectors. The findings of the spatial correlation of HCHO with Normalized Difference Vegetation Index (NDVI) (R² = 0.5) and Land Surface Temperature (LST) (R² = 0.7) indicate the positive influence of NDVI and LST on HCHO concentration. Moreover, the CWT and PSCF analyses suggest that in addition to local emissions, transboundary air pollution from India, Afghanistan, Iran, and Arabian Sea airflow also contributed to the transport of HCHO in Pakistan.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102483"},"PeriodicalIF":3.9,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551748","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 inventory and distribution characteristics of NH3 from agricultural fertilizers in Hunan, China, from 2012 to 2021","authors":"Lili Lu ,&nbsp;Lin Yuan ,&nbsp;Zhiyuan Cai ,&nbsp;Jing Fu ,&nbsp;Genyi Wu","doi":"10.1016/j.apr.2025.102479","DOIUrl":"10.1016/j.apr.2025.102479","url":null,"abstract":"<div><div>Fertilization is the main source of NH₃ emissions from agricultural ecosystems. Based on fertilization activity data and NH₃ emission factors, we aimed to develop an NH₃ emission inventory for fertilization in Hunan Province from 2012 to 2021. Additionally, we analyzed the historical trends in, spatial distributions of, and contributions of various districts and counties to NH₃ emissions in Hunan. The results showed that the highest emissions were estimated to be 112.69 Gg in 2012, which decreased to 84.11 Gg in 2021, with an average annual decline rate of approximately 3.17%. Additionally, NH₃ emissions from paddy fields were greater than those from drylands, and NH₃ emissions from nitrogen fertilizer were greater than those from compound fertilizer. During the study period, the NH₃ emission intensity of fertilization remained below 0.5 t km⁻² in Hunan Province. The areas with greater NH₃ emissions were mainly distributed in the northern, northeastern, and central regions. The cities with high emissions mainly included Changde, Hengyang, Yueyang, and Yongzhou. Zhangjiajie had the lowest NH₃ emissions and emission intensity in Hunan Province. Hanshou and Anxiang counties had substantial contributions to NH₃ emissions in Changde, with contribution rates of 17.86–19.1% and 18.9–19.24%, respectively. Huarong County had the greatest contribution to NH₃ emissions in Yueyang, with a contribution rate of 21.49–24.35%; Hengnan County had the greatest contribution to those in Hengyang, with a contribution rate of 20.38–23.62%; and Nan County had the largest contribution to those in Yiyang, with a contribution rate of 33.58–35.36%.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102479"},"PeriodicalIF":3.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527386","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 short-term forecasting of surface dust concentration in Northern China: Integrating machine learning with multi-numerical models","authors":"Ziwei Yi ,&nbsp;Zhaoliang Zeng ,&nbsp;Yaqiang Wang ,&nbsp;Weijie Li ,&nbsp;Bihui Zhang ,&nbsp;Hailin Gui ,&nbsp;Bin Guo ,&nbsp;Wencong Chen ,&nbsp;Huizheng Che ,&nbsp;Xiaoye Zhang","doi":"10.1016/j.apr.2025.102480","DOIUrl":"10.1016/j.apr.2025.102480","url":null,"abstract":"<div><div>Sand and dust storms (SDSs) are among the most significant extreme weather and climate events impacting northern China, exerting substantial influences on global climate change, the ecological environment, socioeconomic systems, and public health. Traditional dust numerical models often exhibit considerable uncertainty due to the chaotic nature of the atmosphere, inaccuracies in initial conditions, and challenges in parameterizing physical processes. Therefore, a multi-model ensemble forecasting model (ML-SDC) for surface dust concentration was developed based on machine learning with multi-numerical models across northern China. The results demonstrate that the ML-SDC model exhibits significant improvements over single dust numerical models, traditional ensemble methods, and individual machine learning models during the 0–72 h forecast period with the average correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) for surface dust concentration reached 0.78, 91.49 μg/m³ and 36.91 μg/m³ respectively. Additionally, the ML-SDC model has a strong spatiotemporal correction ability for dust concentration, dispersion, and transport. This finding enhances the accuracy of short-term forecasts for extreme weather, offering a valuable tool for the identification and quantitative forecasting of dust weather, while supporting improved preparedness and mitigation strategies for SDS-related impacts and advancing research in climate modeling, air quality management, and environmental sustainability.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102480"},"PeriodicalIF":3.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579997","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 formation of microplastic aerosols and their dispersion in urban environments: A comparative physical modelling study of aerosol and gas dispersion","authors":"Hana Chaloupecká ,&nbsp;Jan Suchánek ,&nbsp;Jan Wild ,&nbsp;Milan Mamula ,&nbsp;Radka Kellnerová ,&nbsp;Václav Nevrlý ,&nbsp;Michal Dostál ,&nbsp;Zdeněk Zelinger","doi":"10.1016/j.apr.2025.102481","DOIUrl":"10.1016/j.apr.2025.102481","url":null,"abstract":"<div><div>Aerosols are present in almost all aspects of everyday life. Aerosols affect climate and health and arise in hazardous situations such as industrial accidents. In this study, we examined the generation of microplastic aerosols from polypropylene pipes used in drinking water systems and their dispersion in a simulated accident scenario using wind tunnel modelling. We compared aerosol and gas dispersion from a ground-level point source in a street canyon in a central European town. The results show that 185-nm UVC light generated stable microplastic aerosols (predominantly &lt;1 μm) from the polypropylene. Although both the aerosol and gas dispersions exhibited recirculation and ventilation regions characteristic of an isolated roughness flow regime, their dispersion patterns differed. Vertically, the main gas dispersion field resembled an ellipse, whereas the main aerosol particles dispersion field resembled an anvil. Horizontally, gas was dispersed primarily perpendicular to the buildings, whereas aerosol particles were dispersed both perpendicular and parallel to the buildings.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102481"},"PeriodicalIF":3.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527417","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":"Numerical investigation of building gap effects on traffic pollutant dispersion in urban networks with intersecting streets","authors":"Yiqi Wang,&nbsp;Ke Zhong,&nbsp;Jin Cheng,&nbsp;Jiajia Xu,&nbsp;Jiajian He,&nbsp;Yanming Kang","doi":"10.1016/j.apr.2025.102475","DOIUrl":"10.1016/j.apr.2025.102475","url":null,"abstract":"<div><div>Wind passing through the gaps between street-facing buildings has the effects of accelerating the natural removal of air pollutants in street canyons, with wider gap conventionally leading to better air quality. However, previous studies oversimplify the canyons by modeling them as isolated systems with only two rows of buildings, neglecting the blocking effects of surrounding building complexes. This leads to an overestimation of the gap flow's ability to flush out traffic pollutants. In this study, to better represent real urban configurations, a typical network with two crossing streets bounded by four complexes is investigated numerically, where one of the streets is parallel and another is perpendicular to the incoming wind. The gap layouts with different street continuities (<em>SC</em> = 0.483–1, building-to-street length ratio) are considered. Results show that for the parallel street, the air quality improves in a linear trend as the gap width is increased. However, the relationship between the gap width and air quality is not linear for the perpendicular street. The worst air quality in the street occurs at an intermediate gap width of <em>SC</em> = 0.759, while the air quality is good for both cases when the building gap width is significant (<em>SC</em> = 0.483) or can be neglected (<em>SC</em> = 1, no gaps between buildings). This finding challenges the conventional understanding and highlight the need to reassess the impacts of building gaps on urban air environments.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102475"},"PeriodicalIF":3.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562363","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 of volatile organic compounds from industrial and stationary combustion sources in the Ili River Valley core area, China","authors":"Feng Tian ,&nbsp;Yingying Liu ,&nbsp;Chunmei Geng ,&nbsp;Dianzeng Jia ,&nbsp;Wen Yang","doi":"10.1016/j.apr.2025.102474","DOIUrl":"10.1016/j.apr.2025.102474","url":null,"abstract":"<div><div>One hundred and fifteen types of volatile organic compounds (VOCs), mass concentrations, composition profiles, and emission factors (EFs) for industrial processes and stationary combustion sources in the core area of the Ili River Valley were investigated using the GC-MS analytical method. This is of great significance for VOC emissions in northwest China. The results show that benzene (25.5%), ethylene (20.8%), 2-butanone (11.3%) and tetrahydrofuran (10.2%) were the most abundant species in the coal-based synthetic natural gas (SNG) industry. Oxygenated VOCs (OVOCs) were the most important chemical group in the pharmaceutical manufacturing (PM) and the manufacture of other condiments and fermented products (MOCFP). Acetaldehyde, acetone and 2-butanone are the tracers for these two industries. Acetylene and vinyl chloride accounted for 84.3% of the weighted share of emissions from polyvinyl chloride synthetic resin (SYR). M/p-xylene, 1,2,4-trimethylbenzene, toluene, acetylene, and o-xylene accounted for 31.7% of the total VOC species in stationary combustion. Two SNG plants have the highest VOC emissions with 2804.5 and 559.8 t/a respectively. PM is the second largest VOCs emitting industry (218.5 t/a), with acetone being the most abundant species. The EF of PM was the largest (13.54 g/kg product), and the EFs of SNG, SYR, and MOCFP were 0.48, 0.145, and 0.45 g/kg product, respectively. The VOC EF of stationary combustion was the lowest (2.12E-05 g/kg coal). However, the average source reactivity (SR) was highest for stationary combustion and SNG. OVOCs, aromatics and alkenes were the main VOC groups to be prioritised for ozone pollution control.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102474"},"PeriodicalIF":3.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562362","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":"Exploring PM2.5 pollution in a representative Northern Chinese county: Insights for air quality management","authors":"Jian Ma ,&nbsp;Philip K. Hopke ,&nbsp;Xiaojing Zhu ,&nbsp;Qingping Song ,&nbsp;Fangxin Zhao ,&nbsp;Xiaoxia Hu ,&nbsp;Lijing Wang ,&nbsp;Xin Zhang ,&nbsp;Yuanxun Zhang","doi":"10.1016/j.apr.2025.102470","DOIUrl":"10.1016/j.apr.2025.102470","url":null,"abstract":"<div><div>Counties have served as fundamental administrative units in China since the Qin Dynasty (221–206 BC), a tradition that continues today with hundreds of millions of residents living in county-level cities. Unlike higher-level cities such as municipalities and prefecture-level cities, counties differ significantly in size, development level, and development model, which can lead to distinct PM_2.5 pollution patterns. This study focuses on Yishui County, a representative county in northern China, to explore its PM_2.5 pollution characteristics and source contributions over a one-year period. Furthermore, the study compares Yishui's pollution profile with those of higher-level cities to provide insights into the relationship between development models and air quality. The annual average PM_2.5 concentration in Yishui was 67.8 μg/m³. Source apportionment using Discretized Normalized Positive Matrix Factorization (DN-PMF) identified six primary sources: dust (28.3%), secondary inorganic aerosols and residential coal combustion (SIA/RCC, 25.7%), vehicle emissions (24.6%), coal combustion (10.3%), industrial processes (9.1%), and biomass burning (2.0%). Dust was the dominant contributor, a notable divergence from patterns in higher-level cities. This disparity is likely attributed to Yishui's heavy reliance on real estate development as a primary economic driver, which significantly increases construction dust emissions. These results emphasize the impact of urbanization and economic structure on PM_2.5 pollution, indicating that other counties in northern China undergoing similar development stages may face comparable air quality challenges.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 6","pages":"Article 102470"},"PeriodicalIF":3.9,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579999","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 straw and straw-derived biochar applications with equivalent straw input on ammonia volatilization and N leaching in an alternate wetting and drying paddy ecosystem","authors":"Haixia Liu ,&nbsp;Taotao Chen ,&nbsp;Dongxia Liu ,&nbsp;Qing Zhao ,&nbsp;Daocai Chi ,&nbsp;Shu Wang","doi":"10.1016/j.apr.2025.102478","DOIUrl":"10.1016/j.apr.2025.102478","url":null,"abstract":"<div><div>Contrasting effects of straw and biochar with equivalent straw input on ammonia volatilization and N leaching under alternate wetting and drying irrigation (I_AWD) in paddy ecosystems are limited. A 2-yr paddy buried pot experiment was conducted with annual rice straw and single biochar applications with equivalent straw input under continuously flooded irrigation (I_CF) and I_AWD. Four treatments comprising no amendment under I_CF (I_CFA₀), no amendment under I_AWD (I_AWDA₀), rice straw (29.41 t ha⁻¹ yr⁻¹) under I_AWD (I_AWDA_S) and biochar (20 t ha⁻¹ applied once) under I_AWD (I_AWDA_B) were arranged in a randomized complete block design. I_AWD did not significantly alter ammonia volatilization, but increased N leaching. Compared with I_CFA₀ and I_AWDA₀, I_AWDA_S significantly increased ammonia volatilization by 7.92–52.71% and decreased yield by 22.98–31.87% in both years, but increased N leaching by 31.18% in 2021 only. I_AWDA_B increased ammonia volatilization, N leaching and reactive N losses in 2021 but significantly decreased reactive N losses in 2022 compared with no amendment. I_AWDA_B reduced grain yield due to the increased reactive N losses in 2021. Both I_AWDA_S and I_AWDA_B improved soil total N. I_AWDA_B had higher yield and N uptake, and lower reactive N losses than I_AWDA_S. Overall, biochar is a more effective strategy for reducing reactive N losses in I_AWD paddy systems over time. Direct straw return could take longer for its decomposition or be annually applied at a lower rate to address its higher reactive N losses and lower grain yield after a 2-yr consecutive annual application.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102478"},"PeriodicalIF":3.9,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520625","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":"Exploration the effect of air pollution on the incidence of myasthenia gravis: An empirical study from Chengdu","authors":"Rui Zhou ,&nbsp;Tianjun Li ,&nbsp;Keyi Tian ,&nbsp;Lei Huang","doi":"10.1016/j.apr.2025.102477","DOIUrl":"10.1016/j.apr.2025.102477","url":null,"abstract":"<div><div>Myasthenia gravis (MG) is an autoimmune disease caused by antibodies attacking and destroying acetylcholine receptors (AChR) at the neuromuscular junction. Although the exact cause of the incidence of MG is unclear, it is believed to involve abnormal immune system function, certain genetic factors, and environmental influences. However, limited existing studies explore the correlation between the incidence of MG and the atmospheric environment. Therefore, this study aimed to investigate the correlation between the incidence of MG and potential air pollution factors in Chengdu. We used the admission data of MG patients from 2017 to 2023 in a large tertiary general hospital in Chengdu to analyze such correlation with meteorological conditions and air pollution. The data were processed using first-order difference to eliminate the effect of autocorrelation on the regression results. Then we selected the variables using stepwise regression, finding the independent variables who have significant effects on the incidence of MG. Based on this, a multiple linear regression model was established. To solve the problem of multicollinearity among the selected variables, we used ridge regression to amend the model. We also used median regression to reduce the impact of outliers in order to improve the stability of the model. Finally, we assessed variables' importance using random forest and explored causal relationship with causal forest. The results consistently showed a significant positive effect of carbon monoxide (CO) concentration on the incidence of MG, as well as several meteorological conditions and air pollution variables that influenced the incidence of MG to some extent.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 5","pages":"Article 102477"},"PeriodicalIF":3.9,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520303","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 influence of local and regional sources on concentrations of fine particulate matter in Delhi","authors":"Deepchandra Srivastava ,&nbsp;Mohammed S. Alam ,&nbsp;Daniel J. Rooney ,&nbsp;Leigh R. Crilley ,&nbsp;Louisa Kramer ,&nbsp;Supattarachai Saksakulkrai ,&nbsp;Sachin Dhawan ,&nbsp;Mukesh Khare ,&nbsp;Shivan ,&nbsp;Ranu Gadi ,&nbsp;Prashant Kumar ,&nbsp;Sarkawt Hama ,&nbsp;Roy M. Harrison ,&nbsp;Zongbo Shi ,&nbsp;William J. Bloss","doi":"10.1016/j.apr.2025.102476","DOIUrl":"10.1016/j.apr.2025.102476","url":null,"abstract":"<div><div>Delhi is one of the world's most polluted cities, and hence pollution control is a very high priority. A key aspect of a cost-effective strategy is to differentiate emissions from local sources from pollution arising from regional transport. Detailed chemical characterization of atmospheric fine particulate matter (PM_2.5) has been made at two sites in three seasons with a view to source attribution. Chloride ion (Cl⁻) concentrations make an exceptional contribution at both sites in winter, reaching a maximum of 76 and 97 μg m⁻³ during the winter campaign at the central and suburban sites, respectively. Differing diurnal patterns of Cl⁻ were observed between the seasons, indicating contrasts in sources and secondary chemical processes between seasons. Inter-site comparisons show high correlation between secondary inorganics (NO₃⁻, SO₄²⁻, and NH₄⁺) in the winter and pre-monsoon, indicating the influence of regional processes for their formation at both sites, while for Cl⁻ and other measured ions (Na⁺, Ca²⁺, Mg²⁺, PO₄²⁻ and K⁺), local influences were found to be dominant through inter-site comparisons and ventilation coefficient analyses. A significant contribution of local sources to secondary inorganic compounds and Organic Matter mass within PM_2.5 in the post-monsoon period was observed, implying that the regional sources (such as crop residue burning, often indicted as the cause of poor air quality) are not the sole driver for high PM_2.5 loadings in Delhi in autumn, contrary to previous studies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 7","pages":"Article 102476"},"PeriodicalIF":3.9,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768541","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}