Atmospheric Environment最新文献

{"title":"The transport pathways and sectoral potential source areas of PM2.5 in Tangshan, a typical heavy industrial city in the Beijing-Tianjin-Hebei region","authors":"Aifang Gao ,&nbsp;Xi You ,&nbsp;Zhao Li ,&nbsp;Qixian Liu ,&nbsp;Aiguo Li ,&nbsp;Zhao Liang ,&nbsp;Aibin Kang ,&nbsp;Baojun Zhang ,&nbsp;Hongliang Zhang","doi":"10.1016/j.atmosenv.2026.121799","DOIUrl":"10.1016/j.atmosenv.2026.121799","url":null,"abstract":"<div><div>This study investigated the transport pathways and sectoral potential source areas of PM_2.5 in Tangshan in January, April, July, and October of 2020. Utilizing the HYSPLIT model upon MeteoInfo software, cluster analysis was conducted on the backward trajectories of airflow at different starting heights and times. The sectoral potential source areas of PM_2.5 in Tangshan were determined by calculating the weighted potential source contribution function (WPSCF) and weighted concentration-weighted trajectory (WCWT) while examining pollution transport pathways. The findings are as follows: Firstly, the higher PM_2.5 concentration carried by pollution trajectories in January (114.8 μg m⁻³) and October (110.7 μg m⁻³) is mainly due to the impact of short-distance transport through Hebei and Tianjin, trajectory 1 (950 hPa) accounts for 30.52 % (124.8 μg m⁻³) of the contaminated airflow. Secondly, the potential source area for PM_2.5 pollution in Tangshan during January has the highest value of WPSCF and WCWT. WCWT high-value areas exceeding 90 μg m⁻³ were distributed in the Langfang, parts of Tianjin, Beijing, and the junction of the Hebei Beijing Tianjin. Thirdly, the contribution of various sector sources to Tangshan's PM_2.5 concentration varies across different months, with industrial and residential sources being the primary contributors. Fourthly, the airflow trajectories at 500 m and 1000 m heights were consistent. 24-h PM_2.5 was more concentrated, and the potential source area (24/72-h) results indicated the high-value areas were industrially dense areas. These findings underscore the importance of regional collaborative efforts and sector collaborative management to mitigate PM_2.5 pollution in Tangshan.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121799"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973910","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":"Isoprene emissions in monocots from Okinawa Island, Japan, and parameterization of the G93 formula","authors":"Hirosuke Oku ,&nbsp;Masashi Inafuku ,&nbsp;Shigeki Oogai ,&nbsp;Ishmael Mutanda","doi":"10.1016/j.atmosenv.2025.121771","DOIUrl":"10.1016/j.atmosenv.2025.121771","url":null,"abstract":"<div><div>Monocotyledonous plants (monocots) are gaining recognition as a major source of biogenic isoprene, but are massively understudied and underrepresented in current isoprene emission inventories. In addition, very scarce leaf observational studies have been conducted to evaluate their emission flux response to environmental variables to date, representing a major gap in current models. Here, we screened isoprene emissions flux from ten monocots growing on the Ryukyu Island, Okinawa, Japan. We further evaluated their leaf-level emission flux response under varying photosynthetic photon flux density (PPFD) and temperature and applied the “Ping-Pong” method to iteratively optimize temperature (<em>C</em>_<em>T</em>) and light (<em>C</em>_<em>L</em>) parameters of the G93 algorithm. The ten monocots studied were <em>Arenga engleri</em>, <em>Dypsis lutescens</em>, <em>Livistona chinensis</em>, <em>Mascarena verschaffeltii</em>, <em>Phoenix roebelenii</em>, <em>Satakentia liukiuensis</em>, <em>Pandanus boninensis</em>, <em>Arundo donax</em>, <em>Ravenala madagascariensis</em>, and <em>Dracaena fragrans</em>. Eight were found to emit isoprene, and among these, six are being reported for the first time. Plants were treated with increasing PPFD and temperature to a maximum value (ascending phase), followed by a stepwise decrease (descending phase). Their emission response to this treatment resembled a characteristic pattern observed in plants that experienced prolonged hot weather, which is poorly captured by both the default and optimized G93 algorithms. To improve model performance, we applied the separate optimization approach, where the ascending and descending phases were optimized separately. In all species, the optimized <em>C</em>_<em>T</em> parameter (<em>C</em>_<em>T1</em>) and <em>C</em>_<em>L</em> parameter (α) of the ascending phase were higher than that of the default G93 or that of the descending phase. Basal emission rate (BER) at standard conditions (30 °C and 1000 μmol m⁻² s⁻¹ PPFD) of <em>A. donax</em> was the highest emitter among the monocots. The BERs of monocots reported here were lower than those of dicots under comparative hot weather conditions. These results add to isoprene emission inventories for monocot species, as well as expand our knowledge of variability in monocot isoprene emission flux response to environmental variables.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121771"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882717","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":"Indoor air quality and health exposure in an educational campus in Western India","authors":"Anuj Shrivastava ,&nbsp;David Konwar ,&nbsp;Deepika Bhattu","doi":"10.1016/j.atmosenv.2026.121790","DOIUrl":"10.1016/j.atmosenv.2026.121790","url":null,"abstract":"<div><div>This study investigates six indoor micro-environments on a residential university campus to assess the impact of sources/activities, occupancy, and ventilation on aerosol properties. Particle number concentration and size distributions were measured using an aerodynamic particle sizer (APS), along with CO₂ levels, and volatile organic compounds (VOCs). Average PM₁₀ concentrations were within WHO limits (45 μg m⁻³), with a 2-fold increase in PM mass in the administrative office due to higher occupancy. PM mass also increased by 2–5 times in naturally ventilated spaces compared to mechanically ventilated classrooms and hostel rooms. Similar patterns were observed in mess and canteen areas, where fine aerosol levels were higher. Although cooking activity in the kitchen led to high VOC concentrations (∼7 ppm), this did not significantly affect particle mass due to sub-micron dominance. Furthermore, infiltration of outdoor aerosol was evident in hostel rooms and classrooms, where the loss rates of coarser particles were higher. Despite the hostel room's larger room surface area-to-volume ratio and lower ventilation, the total PM concentration was higher than in the classrooms due to additional indoor sources. The highest PM exposure and respiratory deposition occurred in environments affected by outdoor infiltration, such as hostel rooms and classrooms with open windows. Based on International Commission on Radiological Protection (ICRP) model, the highest mass deposition occurred in the head airways (71–81 %), followed by the pulmonary (12–22 %) and the lung (6–7 %) airways. Our findings highlight that PM concentration and deposition are influenced by multiple factors in each micro-environment, emphasizing the need for comprehensive IAQ assessments in building design.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121790"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023277","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":"Ambient air pollution and neuropsychiatric disorders: Mediating genetic signatures uncovered by integrated multi-omics Mendelian randomization","authors":"Qineng Wang ,&nbsp;Danna Jia ,&nbsp;Haitong Zhe Sun ,&nbsp;Yuming Guo ,&nbsp;Keding Lu","doi":"10.1016/j.atmosenv.2025.121743","DOIUrl":"10.1016/j.atmosenv.2025.121743","url":null,"abstract":"<div><div>Air pollution is linked to neuropsychiatric disorders, but causal evidence and underlying mechanisms remain insufficiently established. To investigate the causal association between air pollutant (PM_2.5, PM₁₀, coarse PM, and NO₂) exposure and neuropsychiatric outcomes, this study employed Mendelian randomization (MR) and identified biomarkers and biological pathways implicated in neuropsychiatric disorders. We found causal associations between air pollutants and 7 disorders. Furthermore, two-step MR integrating inflammatory factor, immune cell phenotypes, and CSF metabolomics identified 25 potential mediators linking air pollution to neuropsychiatric diseases. MR analysis integrated with pathway enrichment revealed that pollutant exposure may induce neurotoxicity by 3 core mechanisms, including the activation of inflammatory pathways (e.g., Janus kinase-signal transducer and activator of transcription (JAK-STAT) and phosphoinositide 3-kinase-Akt (PI3K-Akt)) and dysregulation of lipid metabolism (e.g., arachidonic acid and α-linolenic acid metabolism). Notably, transforming growth factor-α (TGF-α), SSC-A on HLA-DR + CD8⁺ T cells, and arachidonate (20:4n6) showed substantial mediation effects, accounting for 14.8 %, 17.5 %, and 21.6 % of the associations between PM_2.5 and Alzheimer's disease (AD), PM_2.5 and schizophrenia, and NO₂ and autism spectrum disorder (ASD), respectively. These biomarkers represent potential targets for early detection and intervention, highlighting increased risk associated with long-term exposure to air pollution. Collectively, our findings provide novel causal and mechanistic evidence that may inform both air quality regulation and the allocation of neuropsychiatric healthcare resources in high-risk populations.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121743"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023278","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":"Contrasting pathways of spring black carbon pollution in Northeastern Sichuan basin: Biomass burning transport versus local fossil fuel accumulation","authors":"Pei Tang ,&nbsp;Shiyong Shao ,&nbsp;Jie Zhan ,&nbsp;Liangping Zhou ,&nbsp;Zhiyuan Hu ,&nbsp;Yuan Mu ,&nbsp;Liwen Ye","doi":"10.1016/j.atmosenv.2025.121765","DOIUrl":"10.1016/j.atmosenv.2025.121765","url":null,"abstract":"<div><div>Liangping District, located in the northeastern part of the Sichuan Basin (SCB), is a representative site for studying black carbon (BC) aerosol pollution within the basin. Field measurements of BC mass concentration were conducted continuously from March to May 2021 using an Aethalometer (AE33). The mean BC mass concentration was determined to be 2.4 μg m⁻³. The aerosol optical properties were derived through application of the Aethalometer model, yielding an average absorption coefficient of 36.7 ± 20.1 Mm⁻¹ at 520 nm with a corresponding absorption Ångström exponent (AAE) of 1.40 ± 0.12. During the observation period, two six-day pollution events (designated as Event Mar and Event May) were recorded, with PM_2.5 concentrations exceeding the first-class ambient air quality standards threshold of 35 μg m⁻³. The maximum AAE was 1.70 during Event Mar compared to 1.43 during Event May. The elevated AAE value in Event Mar suggested increased biomass burning constituted a significant pollution source, whereas the lower AAE during Event May reflected a mixed source dominated by fossil fuel combustion. Non-parametric wind regression (NWR) analysis revealed that high BC concentrations were spatially concentrated in the southwestern region during Event Mar, whereas during Event May, elevated BC levels originated from multiple directions. Concentration-weighted trajectory (CWT) analysis indicated that during Event Mar, long-range transport played a more dominant role, whereas local emissions were the primary pollution source during Event May. The study of the two pollution events identified the primary sources of BC, providing a method for analyzing the characteristics of aerosol pollution in SCB and offering a basis for developing pollution control measures.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121765"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145876725","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":"Response of future near-surface ozone extremes in Europe to changes in precursor emissions and climate","authors":"Rodrigo Crespo-Miguel ,&nbsp;Carlos Ordóñez ,&nbsp;Ricardo García-Herrera ,&nbsp;Steven T. Turnock","doi":"10.1016/j.atmosenv.2026.121774","DOIUrl":"10.1016/j.atmosenv.2026.121774","url":null,"abstract":"<div><div>This study examines the separate roles of emissions and climate on the future evolution of high European ozone events in atmosphere-only simulations of UKESM1 (United Kingdom Earth System Model version 1). These include the historical simulation (ending in 2014), the reference scenario ssp370SST (2014–2099) – with steady increases in near-surface temperature, global population and atmospheric methane concentrations – and several variations thereof. For this purpose, we have identified local ozone extremes, connected them into large episodes (spatiotemporal aggregates with a minimum duration of three days) and calculated the episode sizes as the accumulated areal extents during their life cycles. Despite decreases in precursor emissions over most of Europe under ssp370SST, the number of local extremes and the sizes of ozone episodes would increase across the continent throughout the 21st century because of soaring methane levels. The southeast of Europe and Turkey could experience even larger increases due to rising regional emissions. Mitigation strategies targeting emissions of regional precursors, global methane and, more importantly, the combination of both would effectively decrease ozone pollution below present-day values. On the other hand, climate warming enhances biogenic emissions, reduces dry deposition fluxes and increases atmospheric humidity. Overall, this leads to moderate increases in the occurrence of local ozone extremes, but with some remarkable regional differences and a negligible impact on the sizes of ozone episodes when averaged over the whole continent. Moreover, as future ozone episodes become more common under ssp370SST, the associated circulation anomalies are expected to weaken in the future.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121774"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922709","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":"Monsoon-driven circulation modulates the composition and loading of black carbon aerosol in a tropical coastal city","authors":"Renhao Xu ,&nbsp;Qibin Lao ,&nbsp;Chunqing Chen ,&nbsp;Xin Zhou ,&nbsp;Fajin Chen","doi":"10.1016/j.atmosenv.2025.121768","DOIUrl":"10.1016/j.atmosenv.2025.121768","url":null,"abstract":"<div><div>Since the Industrial Revolution, human activities have significantly increased atmospheric black carbon (BC) aerosols, harming air quality, human health, and regional climate. Although the research on the characteristics and sources of atmospheric BC has expanded, understanding of its cross-sea transport remain limited. Zhanjiang city, located on the coast of the northern South China Sea, experiences pronounced monsoon influences and has heavy industries. However, this region maintains good air quality. We hypothesize that monsoon circulation may significantly influence BC pollution. To verify this hypothesis, aerosol samples were continuously collected in Zhanjiang from 2018 to 2019. Results showed clearly seasonal variations in BC concentration and its carbon isotopic values, indicating they are not primarily influenced by local emission sources, as local emissions remain relatively constant. Instead, lower values in summer and higher values in other seasons align closely with monsoon transitions, suggesting that a significant role of monsoon circulation in driving these variations. Backward trajectory model (HYSPLIT) and the potential source contribution factor analysis model (PSCF) further revealed distinctly different air mass pathways between summer (ocean air masses) and other seasons (terrestrial air masses). A Bayesian mixing model indicated that the combustion of fossil fuels (58 %, including 30 % of liquid fuel and 28 % of coal) is the predominant source of BC entering Zhanjiang with air masses. Correlation analyses with water-soluble inorganic ions revealed that BC exhibited significantly weaker associations with terrestrial pollution compared to TC, due to substantial contributions from secondary aerosols to TC during long-range transport. This study suggested that monsoon-driven circulation plays a critical role in aerosol transport and composition in the coastal region, providing new insights into atmosphere–ocean carbon exchange.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121768"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922712","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":"Diagnosing the underperformance of satellite-based surface NO2 estimation using geostationary observations: Insights for improvement from station-type and temporal analyses in South Korea","authors":"Seonyeong Park ,&nbsp;Wonei Choi ,&nbsp;Hanlim Lee","doi":"10.1016/j.atmosenv.2026.121775","DOIUrl":"10.1016/j.atmosenv.2026.121775","url":null,"abstract":"<div><div>The accurate estimation of surface nitrogen dioxide (NO₂) from satellite observations is essential for regional air quality management using spaceborne sensors. However, estimation performance can vary significantly under different local and temporal conditions. This study investigates specific conditions causing satellite-based surface NO₂ estimators underperformance. We developed a machine-learning model using hourly NO₂ vertical column densities from the Geostationary Environment Monitoring Spectrometer (GEMS), along with meteorological and land-use data for December 2021 to November 2022. The model was trained and validated using observations from 614 ground-based monitoring stations across South Korea and demonstrated strong overall performance (R = 0.88). The model accuracy varied by station type and temporal conditions. Higher performance was observed at urban and roadside stations (R = 0.83–0.87). Contrastingly, national background and rural stations exhibited lower correlations (R = 0.66–0.68); and port stations showed moderate performance (R = 0.74). Seasonally, the performance peaked in winter (R = 0.89) and declined in summer (R = 0.82). Diurnally, better performance was observed between 09:45 and 14:45 Korea Standard Time (KST) when higher number of GEMS observations were available. The combined analysis further showed that urban and roadside sites maintained a consistently high performance during winter. These results indicate strong influence of spatial and seasonal factors on model accuracy. Therefore, local NO₂ levels, boundary layer data, and land–sea corrections should be considered to improve satellite-based surface NO₂ estimation. The findings of this study provide practical guidance on the spatiotemporal limits of geostationary monitoring, which can be adopted, with improvements, in establishing geostationary satellites as reliable tools for operational air quality policies development and public health assessments.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121775"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145923089","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":"Urban pollution effects on warm-cloud microphysics in the central Amazon Basin: A WRF-Chem and GoAmazon2014/5 analysis","authors":"André Luiz dos Reis ,&nbsp;Janaina Nascimento ,&nbsp;Angel L. Vara-Vela ,&nbsp;Dirceu Luis Herdies","doi":"10.1016/j.atmosenv.2026.121788","DOIUrl":"10.1016/j.atmosenv.2026.121788","url":null,"abstract":"<div><div>The impact of emissions from large urban centers on atmospheric chemistry and regional climate is a central issue in atmospheric sciences. This study uses WRF-Chem and GoAmazon2014/5 data to assess how urban and forest emissions interact to influence cloud properties in the Amazon. The region around Manaus, in the central Amazon, provides a unique environment for this study worldwide. During the wet season, clean air masses transported by trade winds interact with urban emissions, altering the atmosphere's chemical composition and impacting clouds microphysical and radiative properties. The interaction between urban emissions from Manaus and emissions from the Amazon rainforest modulates aerosol concentration and size. Polluted clouds exhibit a smaller effective radius (De), while liquid water content (LWC) and cloud droplet number concentration (DNC) are higher. In background areas, the DNC is approximately 50 cm⁻³ and exceeds 150 cm⁻³ under highly polluted conditions. The higher LWC observed in polluted clouds is associated with the increased DNC, while the smaller De may delay the onset of rainfall. The amount of water vapor available in the atmosphere and the level of supersaturation determine how urban emissions influence the microphysical processes of cloud formation. Under low LWC conditions, warm precipitation is suppressed, while for high LWC (above 0.75 g m⁻³), the De increases until reaching levels associated with precipitation. These results highlight that the spatial and temporal variation in CCN concentration, modulated by the interaction between urban emissions and those from the tropical rainforest, plays a significant role in cloud microphysical processes in the central Amazon.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121788"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145923090","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":"An assessment of a CO2 transport model simulations using surface, aircraft and satellite data (2015–2021)","authors":"Chiranjit Das ,&nbsp;Ravi Kumar Kunchala ,&nbsp;Prabir K. Patra ,&nbsp;Naveen Chandra ,&nbsp;Kentaro Ishijima ,&nbsp;Toshinobu Machida","doi":"10.1016/j.atmosenv.2025.121754","DOIUrl":"10.1016/j.atmosenv.2025.121754","url":null,"abstract":"<div><div>Estimation of accurate CO₂ fluxes remains challenging because of limited high-quality data and inaccuracies in atmospheric chemistry-transport models (ACTMs). While satellite observations of total-columns (XCO₂) have improved global data coverage, integration of co-located CO₂ observations from multiple platforms and consistent methodologies are yet to be fully developed for altitude-wise model evaluations. In our study, we used MIROC4-ACTM simulations, surface and aircraft observations (ATom, Amazon, and CONTRAIL projects - considered as ground truth), and Orbiting Carbon Observatory-2 (OCO-2) XCO₂ covering 2015–2021. MIROC4-ACTM and ATom profiles show mean differences of −0.1 ± 0.48 and 0.01 ± 0.3 ppm over land and ocean, respectively (p &lt; 0.05), and those are −0.34 ± 1.07 and −0.2 ± 0.51 ppm for OCO-2 XCO₂ sampled at ATom profile locations. Height-wise analysis shows that CO₂ differences are concentrated in the lower troposphere (0–2 km), where model simulation are strongly influenced by surface fluxes. In Amazon, MIROC4-ACTM inversion does not have CO₂ observation sites and limited vertical coverage of aircraft profiles right above the forest canopy (∼0.15 km) to 4.4 km, leading to poor ACTM–OCO-2 (−0.88 ± 1.02 ppm) and ACTM-aircraft (−0.105 ± 2.58 ppm) agreements mainly due to lower troposphere. Over the airports in Asian megacities (i.e., emission hotspots), the model shows a higher difference with CONTRAIL (−1.06 ± 0.58 ppm) than OCO-2 (−0.15 ± 0.53 ppm). The larger ACTM–CONTRAIL difference reflects ACTM's coarse resolution (approx. 2.8° × 2.8°), which limits its ability to resolve smaller scale urban fossil fuel emissions, while the smaller ACTM–OCO-2 difference likely also results from OCO-2's limited sensitivity below the boundary layer.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"368 ","pages":"Article 121754"},"PeriodicalIF":3.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922707","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}