Atmospheric Environment最新文献

{"title":"Functional data analysis of air quality time series in Madrid Using FPCA and splines","authors":"Joaquín Sancho Val,&nbsp;Carlos Cajal Hernando,&nbsp;Lourdes Martínez de Baños","doi":"10.1016/j.atmosenv.2025.121741","DOIUrl":"10.1016/j.atmosenv.2025.121741","url":null,"abstract":"<div><div>Urban air pollution requires analytical tools that capture complex temporal dynamics while remaining interpretable for policy purposes. This study applies Functional Principal Component Analysis (FPCA) to hourly concentrations of NO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>, PM₁₀, and PM_2.5 measured in 2024 at eight monitoring stations in Madrid. By transforming high-dimensional time series into smooth functional data, FPCA identifies dominant modes of variability and reveals structural differences among sites.</div><div>Across all pollutants, the first three components explained more than 85% of total variance. PC1 represented the main seasonal cycle, PC2 reflected short-term fluctuations driven by traffic and meteorology, and PC3 captured episodic peaks. The score plots highlighted consistent clustering: background stations (Casa de Campo, Sanchinarro) showed low levels and weak seasonality; traffic-oriented stations (Plaza Elíptica, Cuatro Caminos, Escuelas Aguirre) displayed high concentrations and stronger cycles; and intermediate sites (Castellana, Plaza Castilla, Méndez Álvaro) exhibited mixed patterns.</div><div>These findings confirm FPCA as an efficient diagnostic framework for air quality assessment, offering both dimensionality reduction and interpretability. Beyond methodological value, the approach enables classification of monitoring sites and supports targeted mitigation strategies. FPCA thus provides a transferable tool for urban air quality management and a solid basis for functional data analysis in environmental policy contexts.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121741"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787890","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":"PM10 and PM2.5 bound PAHs and associated health risks from Northeast India-first report from shifting cultivation sites","authors":"Mebaaibok L. Nonglait,&nbsp;Nicholas Khundrakpam,&nbsp;Pratibha Deka","doi":"10.1016/j.atmosenv.2025.121753","DOIUrl":"10.1016/j.atmosenv.2025.121753","url":null,"abstract":"<div><div>In the hilly areas of Northeast India, extensive forest cover is cleared and burned to prepare the land for shifting cultivation. A monitoring campaign was undertaken in shifting cultivation areas of West Garo Hills District of Meghalaya in Northeast India to assess the contribution of biomass burning to particulate matter (PM) bound polycyclic aromatic hydrocarbons (PAHs). The study was conducted across three stages viz., pre-burning, burning, and post-burning, corresponding to the timing of the burning activities of shifting cultivation. During the burning stage of shifting cultivation, there was a substantial rise in atmospheric total PAHs levels. PM₁₀ bound PAH averaged at 1098 ± 482 ng m⁻³ and PM_2.5 bound PAH at 854 ± 330 ng m⁻³, marking an increment of 16–17 times, respectively, compared to the pre-burning stage. Subsequent rainfall events reduced total PAHs levels during the post-burning stage by 30 and 25 times, respectively for PM₁₀ and PM_2.5 bound PAHs compared to the burning stage. Diagnostic ratios of specific PAH isomers suggested biomass burning as the major contributor to PM loading in the study area. Other sources include long-range transport of vehicle emissions, soil, and dust from surface mineral. Multiple Pathway Particle Dosimetry model indicated that inhaling smoke from biomass burning in the area increased PM deposition in the alveolar region by 9–10 times compared to non-burning stage. The study highlights shifting cultivation as a significant source of PAHs in the study site along with their health risk on the exposed population.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121753"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837189","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":"Chemical and morphological characterisation of soot particles emitted by medium-duty gasoline compression ignition transport engine","authors":"Avinash Kumar Agarwal,&nbsp;M. Krishnamoorthi","doi":"10.1016/j.atmosenv.2025.121657","DOIUrl":"10.1016/j.atmosenv.2025.121657","url":null,"abstract":"<div><div>Diesel engines are highly efficient and proven workshorse for heavy-duty automotive applications globally. However, they face challenges in controlling particulate matter emissions. Gasoline compression ignition technology simultaneously controls engine-out particulate matter and nitrogen oxide emissions. This study employed gasoline compression ignition technology using a 70:30 % (v/v) gasoline-diesel blend (G70) as a low-reactivity test fuel and an optimised fuel injection strategy. An open electronic control unit operated the engine in gasoline compression ignition mode. Tests were performed at different engine speeds (1500–2500 rev/min) and loads (5 and 10-bar brake mean effective pressure). The engine was also operated using a stock electronic control unit in baseline conventional diesel combustion mode. Particle numbers and soot mass were measured for all test cases. Soot morphology and nano-structures were analysed using scanning and transmission electron microscopy. Raman spectroscopy was used to investigate the soot particle's graphene layer. Trace metal elements and polycyclic aromatic hydrocarbons in the soot were assessed using inductively coupled plasma-mass spectrometry and gas chromatography-mass spectrometry. The results concluded that gasoline compression ignition emitted a lower PM mass than the baseline diesel. Diesel soot showed larger primary particles and compact aggregates, whereas chain-like soot aggregates were seen in the G70 soot. The primary particle diameter increased with engine speed but decreased with engine load. Twenty-seven trace elements and 13 polycyclic aromatic hydrocarbons were detected in the soot sample, accounting for ∼6.64–8.85 % (w/w) of the particulate matter mass.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121657"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837190","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":"Tracing local and long-range aerosol emission areas using multi-method and multi-site analyses in central Europe","authors":"Shubhi Arora ,&nbsp;Laurent Poulain ,&nbsp;Radek Lhotka ,&nbsp;Jaroslav Schwarz ,&nbsp;Petr Vodička ,&nbsp;Saliou Mbengue ,&nbsp;Naděžda Zíková ,&nbsp;Jakub Ondráček ,&nbsp;Petra Pokorná ,&nbsp;Vladimír Ždímal ,&nbsp;Hartmut Herrmann","doi":"10.1016/j.atmosenv.2025.121733","DOIUrl":"10.1016/j.atmosenv.2025.121733","url":null,"abstract":"<div><div>Atmospheric aerosols significantly influence air quality, climate and human health, making detailed source attribution and transport characterization essential. This study integrates multiple advanced techniques-air mass cluster analysis, Concentration Weighted Trajectory (CWT) analysis and Conditional Bivariate Probability Function (CBPF) analysis; to investigate aerosol emission sources and transport pathways at three Central European measurement stations: Melpitz (MEL, Germany), Frýdlant (FRY, Czech Republic) and Košetice (NAOK, Czech Republic). Online measurements of non-refractory submicron aerosols (NR-PM₁) using aerosol mass spectrometer, combined with equivalent black carbon (eBC) and brown carbon (BrC) data from aethalometers, enabled detailed characterization of aerosol composition and sources during winter (February–March 2021) and summer (July–August 2021) campaigns. In winter, the highest PM₁ mass concentrations were recorded at NAOK (13.2 μg/m³), followed by FRY (6.4 μg/m³) and MEL (6.3 μg/m³), with organic aerosol (OA) and nitrate as major components. Diurnal trends revealed strong nighttime enhancements, especially at NAOK, indicating residential heating influence. Cluster analysis identified eastern continental air masses as dominant contributors to elevated PM levels at all sites. CWT analysis showed significant source regions for eBC, BrC and secondary inorganic aerosols in Poland and the Czech Republic, particularly for MEL and FRY. In contrast, CBPF analysis indicated local sources as the primary contributors to high OA, eBC, and BrC levels at NAOK, especially under low wind conditions (&lt;2 m/s), suggesting biomass burning and residential heating as key sources. During summer, PM₁ concentrations were more uniform across sites, with slightly higher values at MEL (8.6 μg/m³) compared to NAOK (7.3 μg/m³) and FRY (6.5 μg/m³). Enhanced biogenic emissions and photochemical activity led to increased organic fractions, with NAOK exhibiting the highest proportion (75 % of PM₁ mass). This study demonstrates the advantages of integrating multiple analytical techniques to distinguish between local and long-range sources, assess seasonal variability, and characterize long-range transport patterns, providing key insights for air quality management in Central Europe.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121733"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145920696","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":"Three-dimensional pollutant dispersion in tree-lined urban canyons: Combined wind-tunnel and LES analysis","authors":"Sofia Fellini ,&nbsp;Dipanjan Majumdar ,&nbsp;Pietro Salizzoni ,&nbsp;Maarten van Reeuwijk","doi":"10.1016/j.atmosenv.2025.121748","DOIUrl":"10.1016/j.atmosenv.2025.121748","url":null,"abstract":"<div><div>Vegetation is increasingly used in urban areas to improve microclimate and reduce pollutant exposure, yet its effect on pollutant dispersion within street canyons remains complex. This study combines high-resolution wind tunnel experiments and Large-Eddy Simulations (LES) using uDALES to provide a detailed three-dimensional characterization of airflow and pollutant concentration along the canyon.</div><div>Special attention is given to the consistent scaling of velocity and scalar fields, using friction velocity and canyon geometry as reference quantities, and to the role of tree drag length in aligning the aerodynamic resistance of physical and numerical vegetation. The simulations reproduce key mean-flow structures, including large-scale recirculations, but tend to underestimate turbulent kinetic energy and local scalar fluxes.</div><div>By jointly analyzing high-resolution wind-tunnel experiments and LES, we (i) confirm the spanwise and longitudinal concentration patterns observed experimentally, (ii) assess their sensitivity to the modeled tree drag, (iii) provide the first detailed experimental–numerical comparison of rooftop mean and turbulent mass fluxes, showing that bulk canyon ventilation exhibits no systematic dependence on tree number or drag intensity, and (iv) identify the specific strengths and limitations of each approach. This integrated analysis offers novel insights into the interplay between trees, turbulence, and boundary-layer forcing, informing strategies for modeling urban ventilation and pollutant dispersion in tree-lined streets.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121748"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787871","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":"Deciphering aerosol impacts: Unravelling long-term AOD trends and radiative forcing across key regions","authors":"Gopika Gupta ,&nbsp;B.L. Madhavan ,&nbsp;M. Venkat Ratnam","doi":"10.1016/j.atmosenv.2025.121693","DOIUrl":"10.1016/j.atmosenv.2025.121693","url":null,"abstract":"<div><div>Assessing long-term changes in Aerosol Optical Depth (AOD) together with Aerosol Radiative Forcing Efficiency (ARFE, defined as radiative forcing per unit visible AOD) provides critical insight into the evolving role of different aerosol species in regional climate forcing. In this study, we analyse two decades of AOD trends (2001–2020) across eight climatically diverse regions using a multivariate regression framework, and quantify species-specific radiative effects with the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The regions were chosen to represent contrasting trends in total AOD. Our results show that sulfate aerosols, which account for the largest share of AOD over India (∼36–45 %), are the primary driver of increasing AOD and associated atmospheric warming. Black carbon (BC), although contributing only a minor fraction to total AOD (2–10 %), emerges as the dominant warming agent across most regions, with particularly strong forcing signals over the Middle East. In contrast, sea-salt (SS) aerosols exert the largest cooling influence, most prominently over the Southern African (SAF) region, partially offsetting warming from absorbing species. Europe, despite an overall decline in AOD, exhibits a slight increase in SS that sustains a regional cooling effect. These findings demonstrate that species composition, vertical distribution, and optical properties govern ARFE more strongly than the total AOD magnitude alone. By linking AOD trends with species-resolved radiative forcing efficiency across multiple regions, this study advances the interpretability of ARFE as a climate indicator and highlights its potential to inform policy-relevant assessment of aerosol-driven warming and cooling.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121693"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651835","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":"Assessment of Pandora and S5P/TROPOMI observations for investigating tropospheric NO2 vertical column densities in Thailand","authors":"Worapan Kanchanachat","doi":"10.1016/j.atmosenv.2025.121738","DOIUrl":"10.1016/j.atmosenv.2025.121738","url":null,"abstract":"<div><div>This study examines tropospheric nitrogen dioxide (NO₂) vertical column densities (VCDs) over Thailand using ground-based Pandora observations in Bangkok and S5P/TROPOMI satellite data at the national scale. Pandora measurements reveal distinct diurnal and weekly cycles, with sharp rush-hour peaks and lower weekend values, reflecting strong anthropogenic influence. Monthly and seasonal analyses show that NO₂ is highest in winter and lowest during the monsoon, influenced by the height of the boundary layer, precipitation, and photolysis rates. A comparison of Pandora and S5P/TROPOMI monthly averages shows strong temporal agreement while revealing a consistent low bias in S5P/TROPOMI. A seasonal breakdown shows the highest agreement in summer, moderate agreement in winter, and the poorest performance during the rainy season. At the national scale, the highest NO₂ levels are concentrated in central Thailand, especially Bangkok (5.59 × 10¹⁵ molec/cm²). Elevated column amounts also appear across the Bangkok Metropolitan Region and the Eastern Economic Corridor, consistent with urban–industrial sources, while Lampang exhibits a distinct hotspot associated with emissions from the Mae Moh power plant. The seasonal variation of aerosol optical depth (AOD) also follows the NO₂ pattern, with high AOD corresponding to elevated NO₂ levels during winter in central Thailand and during summer in northern Thailand. In contrast, both AOD and NO₂ decrease substantially during the rainy season due to enhanced wet deposition and more efficient atmospheric cleansing. These results highlight the dominant influence of traffic, industry, and power generation on Thailand's NO₂ burden.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121738"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734458","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":"Urbanization, air pollution, associated islands, and health hazards across six IGP cities","authors":"Asmita Mukherjee,&nbsp;Jagabandhu Panda,&nbsp;Debjyoti Roy,&nbsp;Geo Tom,&nbsp;Ankan Sarkar","doi":"10.1016/j.atmosenv.2025.121716","DOIUrl":"10.1016/j.atmosenv.2025.121716","url":null,"abstract":"<div><div>Uncontrolled urbanization has deep-rooted impacts on the environment, including weather, climate, and pollution, threatening the sustainability of cities. The current study focuses on six cities of the Indo-Gangetic Plain (IGP), which act as hotspots of air pollution across the country. Machine learning (ML) algorithms were utilized to analyze and forecast four major air pollutants, viz., NO₂, SO₂, O₃, and PM_2.5. The model performances based on RMSE, MAE, and R² values suggested that Linear Regression (LR) outperformed other models considered, and was more accurate in short-term prediction. In most of the considered cities, the overall trends (Mann-Kendall test) of four selected air pollutants are expected to remain unaltered in coming years, except for Delhi and Ludhiana. The PM_2.5 concentrations exhibit a strong increasing trend both during the observed and forecasted period, except for Chandigarh-Mohali. Notably, Kolkata exhibited an increasing trend for all four air pollutants while demonstrating higher values of PM_2.5 (200–450 μg/m³), which were greatly impacted by the pollution from nearby land and transport pathways over neighboring oceans. The analysis and forecasting (using ConvLSTM model) of urban land use was done to further associate urbanization with air pollution. Strong correlation signatures were noticed in all cities, either at the core or near the periphery (except for Chandigarh-Mohali), when the interplay was assessed through urban heat and pollution islands. Therefore, with prolonged exposure to air pollutants, the urban population is at higher risk of several pulmonary ailments, as the estimated mortality associated with PM_2.5 for cardiovascular, respiratory, and lung infections indicated a constant increase over the years.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121716"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734351","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":"Chemical characteristics and source apportionment of free amino acids in the Qinling forest atmosphere of central China","authors":"Xin Zhang ,&nbsp;Rui Wang ,&nbsp;Jianjun Li ,&nbsp;Shuyan Xing ,&nbsp;Lijuan Li ,&nbsp;Yue Lin ,&nbsp;Junji Cao ,&nbsp;Yuemei Han","doi":"10.1016/j.atmosenv.2025.121734","DOIUrl":"10.1016/j.atmosenv.2025.121734","url":null,"abstract":"<div><div>Free amino acids (FAAs) in ambient PM_2.5 samples were investigated at a forest site in the Qinling Mountains region of central China to explore their chemical characteristics, potential atmospheric processes, and sources across four seasons of 2021–2022. A total of 14 FAAs were quantitatively characterized using ultrahigh performance liquid chromatograph coupled with a high-resolution Orbitrap mass spectrometer. The mass concentrations of total FAAs varied from 6.4 to 48.5 ng m⁻³ (mean 23 ± 11 ng m⁻³) over the study periods, with higher levels in spring and summer. The compositional characteristics of total FAAs varied in different seasons. Among them, valine was mostly abundant, accounting for 39 ± 5 % of total FAAs, followed by alanine (14 ± 5 %) and glycine (14 ± 6 %). The correlations of FAAs with oxidants O₃ and NO₂ suggest that atmospheric oxidation capacity promoted their production, but the effects on individual ones varied. The total FAAs correlated negatively with ambient relative humidity but positively with temperature, indicating that meteorology was important factors governing the FAAs formation. Seven sources for PM_2.5 and FAAs, including biomass burning, gasoline vehicles exhaust, biological emissions, coal combustion, secondary formation, dust, and agricultural activities, were resolved from positive matrix factorization analysis. Biological emissions and agricultural activities were found to be the dominant sources of FAAs in this forest atmosphere. The contributions of these sources to individual FAAs varied substantially across different seasons. This study highlights the seasonal variability in the compositional characteristics of FAAs affected by the environmental factors and sources.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121734"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787870","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":"Carbon dioxide (CO2) variations across India: Synthesis of observations and model simulations","authors":"Ravi Kumar Kunchala ,&nbsp;Imran Girach ,&nbsp;Chiranjit Das ,&nbsp;Chaithanya Jain ,&nbsp;Pramit Kumar Deb Burman ,&nbsp;Mahesh Pathakoti ,&nbsp;Prabir K. Patra ,&nbsp;Yogesh K. Tiwari ,&nbsp;M. Venkat Ratnam ,&nbsp;Vinayak Sinha ,&nbsp;Vinu Valsala ,&nbsp;Manish Naja ,&nbsp;S. Venkataramani ,&nbsp;Naveen Chandra ,&nbsp;S Suresh Babu ,&nbsp;Mehul R Pandya ,&nbsp;Haseeb Hakkim ,&nbsp;Savita Datta ,&nbsp;Vaishnavi Jain","doi":"10.1016/j.atmosenv.2025.121746","DOIUrl":"10.1016/j.atmosenv.2025.121746","url":null,"abstract":"<div><div>India is the 3rd largest emitter of fossil fuel carbon dioxide (CO₂), highlighting the critical need to understand CO₂ dynamics for effective carbon management. This study investigates the CO₂ variability and its dynamics over India using ground-based in situ measurements (11 sites), satellite observations and model simulations. The analyses reveal distinct diurnal and seasonal patterns, along with a consistent increasing trend with global-mean CO₂ concentrations. The amplitude of seasonal cycles (SCAs) vary geographically, with deeper SCAs observed in northern India and shallower ones in the south, primarily influenced by the monsoon system and temperature-dependent vegetation dynamics. The lowest SCA is observed over the high-altitude site at Hanle in north India (7.4 ppm), followed by the coastal sites at Pondicherry (8.0 ppm) and Thumba (8.5 ppm) in south India. The deepest SCA of 26.7 ppm is observed at Mohali, with one of the peaks observed in November attributed to crop residue burning in the Indo-Gangetic Plain. We have used an Atmospheric Chemistry Transport Model (ACTM) to understand spatial and temporal variations in CO₂. The model simulates the phase of the SCAs reasonably well at only a few sites, e.g., Thumba, Gadanki, and fails to capture details at most sites. Coarse horizontal resolution of ACTM (2.8^o <span><math><mrow><mo>×</mo></mrow></math></span> 2.8°) limits the reproduction of observed diurnal pattern at the sites near strong fluxes. Satellite observations of total column CO₂ (XCO₂) anomalies (2014–2024) show negative values (indicative of sink) over India during post-monsoon season, and positive values (indicative of source) during premonsoon season. The regional mean XCO₂ SCA (5.45–5.65 ppm), trend (2.44–2.51 ppm y⁻¹) and interannual variability in growth rates (∼1.0–3.9 ppm y⁻¹) are consistently estimated from two satellites during 2009–2024.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"367 ","pages":"Article 121746"},"PeriodicalIF":3.7,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787893","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}