Atmospheric Environment最新文献

{"title":"Effects of climate and air quality on RSV infection hospitalization among children in Guangzhou from 2017 to 2023","authors":"Lihong Sun ,&nbsp;Xiaolong Ou ,&nbsp;Zhihong Zhai ,&nbsp;Yingtong Ye ,&nbsp;Zhaosong Fang","doi":"10.1016/j.atmosenv.2025.121436","DOIUrl":"10.1016/j.atmosenv.2025.121436","url":null,"abstract":"<div><div>This study aimed to explore the link between hospitalizations due to RSV infection and factors such as climate and air quality among children in Guangzhou. We included RSV infection cases from January 2017 to October 2023 in a tertiary hospital in Guangzhou, China, and then collected daily meteorological data including air temperature and relative humidity as well as air pollutant data including PM_2.5, PM₁₀, SO₂, CO, O₃, and NO₂. Finally, we established a distributional lag nonlinear model (DLNM) to investigate the association of hospitalization for RSV infection with meteorological factors and air quality. Of the 1922 reports of RSV infection collected, 96.31 % of the infections were under 5 years of age. Our study revealed a correlation between reductions in air temperature and relative humidity and the rise in hospitalizations due to RSV infection. With respect to air quality, high concentrations of PM_2.5, O₃, and NO₂ increase the risk of RSV infection, with the relative risk increasing with pollutant concentration. In addition, a 3-week exposure to moderate concentrations of PM_2.5 (17-23 <span><math><mrow><mi>μ</mi><mi>g</mi><mo>/</mo><msup><mi>m</mi><mn>3</mn></msup></mrow></math></span>) also increased the risk of RSV infection. For other air pollutants, there is no obvious pattern found.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121436"},"PeriodicalIF":4.2,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Unmasking Emissions: Tracing organic aerosols around a coal-fired power plant in India","authors":"Chen Luo ,&nbsp;Sayantan Sarkar ,&nbsp;Fanny Gesmond ,&nbsp;Megha Anand ,&nbsp;Kalpana Munnuru Singamshetty ,&nbsp;Joyanto Routh","doi":"10.1016/j.atmosenv.2025.121428","DOIUrl":"10.1016/j.atmosenv.2025.121428","url":null,"abstract":"<div><div>Coal-fired thermal power plants (TPP) are projected to be a major energy source in India for the foreseeable future. Their continued operation and planned expansion will increase emissions, further degrading the air quality in the Indo-Gangetic Plains and undermining long-term sustainability. In this study, we collected for one-year particulate matter (PM_2.5) at an upwind and downwind site from a super-category TPP and analyzed polycyclic aromatic hydrocarbons (PAH), n-alkanes, and levoglucosan. The annual mean of PM_2.5 level was about 2.5 times the Indian National Ambient Air Quality Standards (NAAQS) (40 μg/m³) and 40 times the WHO standard (5 μg/m³). The annual mean of benzo[<em>a</em>]pyrene concentration was over five times the NAAQS level (1 ng/m³) and 40 times the European Environment Agency reference level (0.12 ng/m³, assuming an acceptable risk of additional lifetime cancer risk of 1 in 100,000). Diagnostic PAH ratios and n-alkane indices indicated the primary emission sources. n-Alkanes were mainly derived from petrogenic sources, while pyrogenic sources were the main contributor to PAHs. Levoglucosan indicated more biomass burning during winter and post-monsoon, with higher emissions at the downwind rural site compared to the upwind suburban site. We also used backward trajectory modeling, including clustering and concentration-weighted trajectories, to identify emission hotspots. They revealed elevated benzo[<em>a</em>]anthracene, benzo[<em>b</em>]fluoranthene, and dibenz[<em>a,h</em>]anthracene levels due to TPP emissions.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121428"},"PeriodicalIF":4.2,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Sustained PM2.5 decline in Shenzhen confronts emerging challenges: Strengthening regional governance and secondary aerosol mitigation","authors":"Kejin Tang ,&nbsp;Xing Peng ,&nbsp;Lingyan He ,&nbsp;Yu Han ,&nbsp;Yuqi Liu ,&nbsp;Sizhe Liu ,&nbsp;Tingting Yao ,&nbsp;Xiaofeng Huang","doi":"10.1016/j.atmosenv.2025.121437","DOIUrl":"10.1016/j.atmosenv.2025.121437","url":null,"abstract":"<div><div>Long-term observation at different environmental sites is crucial for accurately tracking PM_2.5 trends and formulating effective pollution control strategies. This study conducted PM_2.5 sampling and component analysis at urban and suburban sites in Shenzhen in 2014, 2019, and 2024, using machine learning models to assess the impact of meteorological and source emission changes on PM_2.5 trends and receptor model to identify PM_2.5 sources. The results show that Shenzhen's PM_2.5 levels declined by 47 % from 2014 to 2024, mostly due to long-term emission cuts, with meteorological impacts accounting for a minor 11.9 % of the change. Urban PM_2.5 concentrations consistently surpass suburban ones, with both experiencing approximately 30 % declines in Phase I (2014–2019), whereas in Phase II (2019–2024), the urban site shows a greater 29 % drop compared with a 17 % drop at the suburban site, narrowing their gap. The source apportionment results show that in Phase I, the urban site's PM_2.5 decline stemmed mainly from reduced vehicle emissions and secondary sulfate, while the suburban site's drop resulted from decreased secondary sulfate, ship emissions, and secondary organic aerosols. In Phase II, fugitive dust reduction is the primary driver of PM_2.5 declines at both sites, though other sources also play a contributing role. Emission reductions from sources in Phase II are smaller than those in Phase I, coupled with a narrowed concentration gap between the two sites and a rising relative contribution from secondary sources, highlighting Shenzhen's need for stronger regional coordination and secondary pollutant control to lower PM_2.5 levels.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121437"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 oxidation of long chain aldehydes: OH and Cl reactivity, mechanisms and environmental impact","authors":"Fabricio Aguirre ,&nbsp;Pedro L. Lugo G ,&nbsp;Vianni G. Straccia C ,&nbsp;Mariano A. Teruel ,&nbsp;M. Belén Blanco","doi":"10.1016/j.atmosenv.2025.121429","DOIUrl":"10.1016/j.atmosenv.2025.121429","url":null,"abstract":"<div><div>The relative-rate technique has been used to obtain the rate coefficients for the reactions of the saturated aldehydes (SA): Octanal (OCT) CH₃(CH₂)₆C(O)H and Nonanal (NON) CH₃(CH₂)₇C(O)H with OH radicals and Cl atoms at (298 ± 3) K and atmospheric pressure. The experiments were performed in an environmental chamber using <em>in situ</em> FTIR spectroscopy detection to monitor the decay of the aldehydes relative to different reference compounds. The following room temperature rate coefficients (in units of cm³ molecule⁻¹ s⁻¹) were obtained: <em>k</em>_<em>1</em> (OH + CH₃(CH₂)₆C(O)H) = (3.13 ± 0.50) × 10⁻¹¹, <em>k</em>_<em>2</em> (Cl + CH₃(CH₂)₆C(O)H) = (2.80 ± 0.31) <strong>×</strong>10⁻¹⁰, <em>k</em>_<em>3</em> (OH + CH₃(CH₂)₇C(O)H) = (2.81 ± 0.40) × 10⁻¹¹ and <em>k</em>_<em>4</em> (Cl + CH₃(CH₂)₇C(O)H) = (3.10 ± 0.30) × 10⁻¹⁰. In addition<strong>,</strong> product studies were performed in similar conditions of the kinetic experiments by the SPME-GC-MS technique. Heptanal, hepta-1-ol, octanoic acid, octanal, 1-octanol, octanoyl chloride, 1-chlorooctane and formaldehyde were identified as reaction products.</div><div>The atmospheric implications of the studied reactions were assessed by the estimation of the tropospheric lifetimes of OCT and NON concerning their reaction with OH radicals and Cl atoms to be 9, 10 h and 30, 27 h, respectively. The relatively short residence in the atmosphere of the SA studied will have a local impact with restricted transport. High tropospheric ozone creation potential of 68 and 66 were estimated for OCT and NON, respectively.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121429"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Cumulative exposure to the chemical components of PM2.5 and the prevalence of Anemia: Insights from a large group of workers in South China","authors":"Xinyue Li ,&nbsp;Zhiqiang Li ,&nbsp;Yongqing Sun ,&nbsp;Man Zhang ,&nbsp;Meimei Zhong ,&nbsp;Yueqian Wu ,&nbsp;Xudan Chen ,&nbsp;Xurui Sun ,&nbsp;Dan Chen ,&nbsp;Huanle Cai ,&nbsp;Guanghui Dong ,&nbsp;Hui Tang ,&nbsp;Zhibing Chen ,&nbsp;Shimin Chen ,&nbsp;Tong Guo ,&nbsp;Tian Tian ,&nbsp;Shenghao Wang ,&nbsp;Wenjing Wu ,&nbsp;Yuqin Zhang ,&nbsp;Yongshun Huang ,&nbsp;Shijie Hu","doi":"10.1016/j.atmosenv.2025.121432","DOIUrl":"10.1016/j.atmosenv.2025.121432","url":null,"abstract":"<div><div>Although the association between PM_2.5 and anemia is biologically plausible, involving the iron regulation disruption by chronic systemic inflammation following particle exposure, existing epidemiological evidence is limited, especially among workers or considering particle components.</div><div>We selected 372,290 workers in Guangdong Province in 2020 and used the yearly PM_2.5 concentrations and its chemical components’ annual concentrations around their workplaces as the exposure. We employed the use of mixed-effects models to assess the associations of PM_2.5 and its components with hemoglobin and anemia, further investigating the interaction between stratified variables (demographic characteristics and occupational variables) and the five components on anemia.</div><div>For each interquartile range increase in the concentration of PM_2.5 and its components (BC, NH₄⁺, NO₃^-, SO₄^2-, OM), the hemoglobin concentration decreased by 0.993 (95 %CI: 0.927, 1.059), 0.747 (0.681, 0.812), 0.939 (0.871, 1.007), 1.237 (1.167, 1.306), 0.982 (0.916, 1.047), and 0.798 (0.735, 0.862) g/L, respectively. Except for BC, PM_2.5 and the other components were associated with a significant increase in the prevalence of anemia, with ORs ranging from 3.0 % to 14.8 % per IQR increase in the exposure. NO₃^- had the most significant effect on both outcomes. In addition, we found that interactions between stratifying variables and concentrations of the five components were predominantly significant for the prevalence of anemia (<em>P</em> for interaction &lt;0.05), with different susceptibilities observed across age groups, genders, and subgroups of occupational variables.</div><div>The study offers an in-depth examination of the potential impact of PM_2.5 and its components on the prevalence of anemia among workers.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121432"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Estimating global anthropogenic carbon dioxide emissions using satellite observations and machine learning methods","authors":"Farhan Mustafa ,&nbsp;Ming Xu","doi":"10.1016/j.atmosenv.2025.121423","DOIUrl":"10.1016/j.atmosenv.2025.121423","url":null,"abstract":"<div><div>Several countries are working to reduce their anthropogenic CO₂ emissions to meet the goals of the Paris Agreement. However, evaluation of the carbon reduction efforts is hindered by the larger uncertainties in the currently available datasets. Therefore, it is imperative to explore new efficient and reliable methods to estimate carbon emissions accurately. This study proposed a novel method to estimate global gridded anthropogenic CO₂ emissions using satellite datasets. The methodology included the development and integration of two machine learning models, i.e., RXCO₂ (Reconstruct XCO₂) and REMI (Reconstruct EMIssion), to achieve the objective. RXCO₂ utilized the CO₂ products from the Copernicus Atmosphere Monitoring Service (CAMS) model and the Orbiting Carbon Observatory 2 (OCO-2) satellite to produce a daily global long-term regular gridded column-averaged dry-air model fraction of CO₂ (XCO₂) dataset with a spatial resolution of 1°. The predicted XCO₂ dataset was thoroughly validated against the ground-based and satellite-derived XCO₂ observations, and good consistency was observed among the datasets. Further, the XCO₂ anomalies were derived using the predicted XCO₂ dataset and were utilized in the second model (REMI) along with tropospheric NO₂ column, nighttime light, and population density to predict annual gridded anthropogenic CO₂ emissions at a spatial resolution of 1° for 2021 and 2022. The model achieved high accuracy with a coefficient of determination (R²) of 0.96 and a root mean squared error (RMSE) of 10^0.3 tons. The predicted results were comprehensively compared with the anthropogenic CO₂ emissions provided by established inventories and good agreement was observed among the datasets.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121423"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Changes in gas-to-aerosol-phase partitioning ratio of semi-volatile products affect secondary organic aerosol formation from α-pinene photooxidation","authors":"Shijie Liu ,&nbsp;Xinbei Xu ,&nbsp;Si Zhang ,&nbsp;Rongjie Li ,&nbsp;Zheng Li ,&nbsp;Can Wu ,&nbsp;Rui Li ,&nbsp;Feiyong Chen ,&nbsp;Guiqin Zhang ,&nbsp;Gehui Wang","doi":"10.1016/j.atmosenv.2025.121427","DOIUrl":"10.1016/j.atmosenv.2025.121427","url":null,"abstract":"<div><div>α-Pinene is one of the most important precursors of secondary organic aerosols (SOA). The formation of α-pinene derived SOA is strongly affected by NOx. However, the effects of NOx on α-pinene derived SOA formation, especially the enhancing effect of NOx on SOA yield, are still not comprehensively understood. A series of α-pinene photooxidation experiments were performed at different NOx concentrations through an atmospheric chamber in this study. The yields of α-pinene SOA initially increased with rising NOx concentrations but subsequently decreased at higher levels. The maximum SOA yields were 8.0 % and 26.2 % in 115 ppb and 250 ppb α-pinene experiments, respectively. It is found that the fitted curves of SOA mass concentration (M₀) versus SOA yield shift downward with increasing NOx, which means the volatility of the oxidation products gradually increases. However, the higher SOA yields observed with the increasing M₀ during each photooxidation process, which were attributed to the enhanced gas-to-aerosol-phase partitioning ratio. The relationship of SOA yields with M₀ for different NOx experiments shows that, under low-NOx conditions, the elevation in M₀ which was driven by enhanced VOC consumption would still promote SOA yield with increasing NOx concentrations, despite the position of the Odum curve shift downward. That is to say, the change of M₀ leading to the variation gas-to-aerosol-phase partitioning ratio should be taken into account in the facilitation of NOx on SOA yield. The relation of nitrogen-containing organic compound (NOCs) concentrations with NOx was also quantified in this study. The rapid increase in NOCs formation under low NOx conditions is another factor contributing to the increase of SOA yields. This study greatly enhances our understanding of the mechanisms by which NOx promotes SOA yields, and provides crucial information for improving the accurate simulation of SOA formation.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121427"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 exposure to air pollution and lung cancer incidence in the Danish Nurse Cohort study","authors":"Sophie MA. Effing ,&nbsp;Jiawei Zhang ,&nbsp;Stéphane Tuffier ,&nbsp;Thomas Cole-Hunter ,&nbsp;Marie Bergmann ,&nbsp;George Maria Napolitano ,&nbsp;Rina So ,&nbsp;Jørgen Brandt ,&nbsp;Matthias Ketzel ,&nbsp;Steffen Loft ,&nbsp;Jaime E. Hart ,&nbsp;Youn-Hee Lim ,&nbsp;Zorana Jovanovic Andersen","doi":"10.1016/j.atmosenv.2025.121430","DOIUrl":"10.1016/j.atmosenv.2025.121430","url":null,"abstract":"<div><h3>Background</h3><div>Although the link between air pollution and lung cancer is well established, recent evidence from low-pollution areas is mixed. We investigated the association of long-term exposure to air pollution with lung cancer incidence in Denmark.</div></div><div><h3>Methods</h3><div>We analyzed data from 28,731 female nurses in the Danish Nurse Cohort, followed from 1993/1999 until 2020 for lung cancer incidence. We estimated residential annual mean concentrations of particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), and ozone (O₃) using the DEHM/UBM/AirGIS modelling system. Time-varying Cox regression models evaluated the associations between these exposures and lung cancer incidence.</div></div><div><h3>Results</h3><div>After excluding participants who did not meet the criteria for our study, we were left with 23,706 participants, 450 of whom developed lung cancer during the study period. The mean PM_2.5, PM₁₀, NO₂, BC, and O₃ concentrations at the participants' baseline addresses were 14.65, 21.02, 20.25, 0.92, and 50.77 μg/m³, respectively. Our study found no association between the pollutants investigated and lung cancer incidence. Hazard ratios (HRs) and 95 % confidence intervals for lung cancer incidence associated with 5-year moving average exposures to PM_2.5, PM₁₀, NO₂, BC, and O₃ were 0.95 (0.75–1.20) per 2.68 μg/m³, 0.93 (0.78–1.12) per 2.81 μg/m³, 0.95 (0.83–1.08) per 7.98 μg/m³, 0.96 (0.86–1.08) per 0.34 μg/m³, and 1.05 (0.90–1.21) per 7.04 μg/m³, respectively, in the fully adjusted model. These findings were robust across various statistical models and sensitivity analyses.</div></div><div><h3>Discussion</h3><div>We found no association between long-term air pollution exposure and lung cancer incidence in Danish female nurses, contrasting with established links in other contexts but aligning with recent studies in low-exposure settings.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121430"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Formaldehyde variation in urban Beijing: Levels, sources, budget, and ozone impact","authors":"Ming Wang ,&nbsp;Wenxuan Chai ,&nbsp;Dongyang Liu ,&nbsp;Min Shao","doi":"10.1016/j.atmosenv.2025.121446","DOIUrl":"10.1016/j.atmosenv.2025.121446","url":null,"abstract":"<div><div>As a key precursor of radicals and ozone (O₃), formaldehyde (HCHO) affects the atmospheric oxidative capacity of the troposphere. Herein, we investigated seasonal variation of HCHO levels, sources, sinks, and its impact on O₃ based on 17-month online measurements of HCHO and other trace gases at an urban site in Beijing. The average mixing ratio of HCHO during the warm season was 6.09 ± 3.37 ppbv, marking an increase of approximately 50 % compared to the cold season. During the warm season, HCHO accounted for 26.6 ± 6.9 % of the average mixing ratio and 34.6 ± 8.3 % of the OH reactivity for total volatile organic compounds (VOCs), approximately double the levels observed in 2011. The positive matrix factorization analysis reveals that photochemical production accounted for 71.4 % of the average HCHO level during the warm season, while vehicular exhaust contributed 50.6 % during the cold season. A budget analysis of HCHO production (<em>P</em>_HCHO) and destruction (<em>D</em>_HCHO) rates using a box model based on observations (OBM) shows that during the daytime in the warm season, <em>P</em>_HCHO was close to <em>D</em>_HCHO, suggesting a near closure of the HCHO budget. During the cold season, <em>D</em>_HCHO surpassed <em>P</em>_HCHO, possibly driven by primary emissions. The dominant HCHO production pathways were reactions of alkoxyl radicals with oxygen, while its major destruction processes were the reaction with OH radical and self-photolysis during both seasons. The relative incremental reactivity (RIR) values of nitrogen oxides determined using the OBM were negative during the summer. However, these values showed a significant increase from 2011 to 2022, indicating that while O₃ production in urban Beijing was primarily VOC-limited, the influence of NO titration on O₃ decreased over the decade. The RIR value of HCHO increased by 50 % from 2011 to 2022. Moreover, in 2022, HCHO has become the second most important VOC for O₃ formation, following isoprene. This underscores its crucial role in shaping future O₃ control measures.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121446"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Formation pathways of particulate NO3− and sources of its precursor over the northwest India: Insights through dual isotopes","authors":"Chandrima Shaw ,&nbsp;Neeraj Rastogi ,&nbsp;Ritwick Mandal ,&nbsp;Prasanta Sanyal","doi":"10.1016/j.atmosenv.2025.121426","DOIUrl":"10.1016/j.atmosenv.2025.121426","url":null,"abstract":"<div><div>NO_x plays a vital role in tropospheric ozone formation, OH radical recycling, and acts as a precursor to the formation of particulate nitrate (pNO₃^-), a major reactive nitrogen species. pNO₃^- mainly forms via four pathways: oxidation of NO₂ by OH (P₁), N₂O₅ hydrolysis (P₂), reactions with VOCs (P₃), and ClO (P₄). However, studies on its sources and formation mechanisms are limited. This study uses dual isotopes (δ¹⁸O and δ¹⁵N) of pNO₃^- to explore the sources of NO_x and dominant pNO₃^- formation pathways over Patiala, a semi-urban site in the northwestern Indo-Gangetic Plain (IGP), during a large-scale paddy residue burning. Day-time δ¹⁵N and δ¹⁸O averaged −5.0 ± 2.4 ‰ and 52.1 ± 6.2 ‰, while night-time values were −0.13 ± 5.7 ‰ and 60.0 ± 8.4 ‰, respectively, reflecting enhanced nighttime partitioning due to cooler temperatures. Further, P₁ (79.6 ± 7.2 %) and P₂ (16.1 ± 7.5 %) dominated pNO₃^- formation; P₃ and P₄ were negligible (&lt;5 %). During the study period, the major sources of NO_x were traffic exhaust (38 ± 18 %), biomass burning (29 ± 18 %), followed by emissions from coal-fired power plants (20 ± 11 %) and soil (13 ± 9 %). Our study, the first of its kind over India provide valuable insight into NO_x transformation processes under specific seasonal and emission conditions. While these results improve the understanding of pNO₃^- formation and may aid in refining regional NO_x inventories, they are representative of the particular location and time frame of sampling and may not reflect source contributions in other regions or during periods without episodic biomass burning influence.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"360 ","pages":"Article 121426"},"PeriodicalIF":4.2,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}