Atmospheric Research最新文献

{"title":"Construction and analysis of atmospheric visibility and fog-haze datasets in China (2001−2023) based on machine learning models","authors":"Haifeng Xu ,&nbsp;Wenhui Luo ,&nbsp;Jinji Ma ,&nbsp;Bing Dong ,&nbsp;Cheng Wan ,&nbsp;Shijie Zhao ,&nbsp;Cheng Dai ,&nbsp;Rui Qian ,&nbsp;Zhengqiang Li","doi":"10.1016/j.atmosres.2025.108160","DOIUrl":"10.1016/j.atmosres.2025.108160","url":null,"abstract":"<div><div>Research on atmospheric visibility and haze events is vital for human health and sustainable societal development. This study aims to construct long-term daily-scale visibility and fog-haze datasets for China using machine learning models, analyze their spatiotemporal evolution characteristics, identify key influencing factors of visibility. The results show that the LightGBM model achieves high accuracy (R² = 0.79, RMSE = 4.03 km), representing a 7.04 % improvement in R² and 0.6 km reduction in RMSE compared to the baseline model, while maintaining robust stability across both seasonal (R² = 0.77–0.79, RMSE = 3.83–4.18 km) and spatial scales (R² = 0.58–0.76, RMSE &lt;4 km). Atmospheric visibility showed an initial decline followed by an upward trend from 2001 to 2023, reaching its lowest point in 2015 (20.77 km) and recovering to 21.26 km by 2023. Visibility was lowest in winter (20.33 km) and highest in summer (22.32 km), with low-value areas concentrated in eastern and central city clusters. Overall, a declining trend was observed, with an annual average decrease of 0.03–0.08 km. From 2000 to 2013, the annual average visibility decreased by 0.09–0.13 km, with the decline area accounting for 22.56 %–55.38 %. From 2013 to 2023, the annual average visibility increased by 0.03–0.13 km, with the increase concentrated in the central and eastern regions (area ratio of 12.7 %–39.1 %), while the western regions continued to show a downward trend (area ratio of 8 %–35.3 %). SO₂, relative humidity, and surface pressure are the most important variables affecting atmospheric visibility, with contributions of 17.43 %, 13.29 %, and 10.58 %, respectively. The thresholds for these variables are 11.4 μg/m³, 74.9 %, and 998 hPa. The frequency of haze in China increased from 9.97 days in 2001 to 20.3 days in 2013 and then decreased to 11.03 days by 2023. Overall, there is an average annual decrease of 0.5 days, with the spatial pattern showing a decline in the eastern and central regions, and an increase in the western region. Specifically, light haze and alert haze decreased by 0.75 and 0.2 days per year, respectively, while mild haze increased by 0.32 days per year. The area without haze has continuously decreased by 11.89 %, while the area with low-frequency haze has increased by 12.91 %. The area with high-frequency haze first increased and then decreased, showing an overall reduction of 1.03 %, mainly concentrated in city clusters in the eastern and central regions. From 2001 to 2013, the area of high-frequency haze increased by 5.68 %, while it decreased by 6.71 % from 2013 to 2023. The research results provide important references for a deeper understanding of atmospheric environmental changes, while also offering data support and scientific basis for atmospheric environment research and effective management.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108160"},"PeriodicalIF":4.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Observational study of a quasi-stationary mesoscale convective system during extreme rainfall on 8 August 2022 in Korea","authors":"Hee-Ae Kim ,&nbsp;Chang-Hoi Ho ,&nbsp;Jinwon Kim ,&nbsp;Eun-Kyoung Seo ,&nbsp;Seon Ki Park","doi":"10.1016/j.atmosres.2025.108159","DOIUrl":"10.1016/j.atmosres.2025.108159","url":null,"abstract":"<div><div>On 8 August 2022, a quasi-stationary mesoscale convective system (MCS) produced prolonged extreme rainfall (&gt; 100 mm h⁻¹) over the Seoul metropolitan area, Republic of Korea. These organized convective systems, primarily composed of convective components with interspersed stratiform elements, are characterized by the successive local generations of convective cells. This study analyzes data from multiple observational platforms to understand the formation of the MCS and its microphysical evolution. The convective cells were initiated just off the west coast near Seoul, along the boundary between warm and cold air masses. Low-level convergence and favorable environmental conditions, including low lifting condensation level, level of free convection, and large convective available potential energy, facilitated the triggering of these cells. As the cells moved inland, they intensified rapidly due to the land-sea surface-friction contrast. Radar data show that as the MCS matured, reflectivity increased and the differential reflectivity decreased downward above the melting level, indicating the growth of ice crystals and graupels. The evolution of microphysical structure led to increases in both the mean diameter (<em>D</em>_<em>m</em>) and the number concentration (<em>N</em>_<em>T</em>) of raindrops. This observation also suggests that the rainfall intensity was more closely related to the increase in <em>N</em>_<em>T</em> than <em>D</em>_<em>m</em> during the period of heavy downpours. This study improves our understanding of the mesoscale processes related to extreme rainfall in Korea, critical for forecasting local heavy rainfall.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"325 ","pages":"Article 108159"},"PeriodicalIF":4.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Key characteristics and statistical investigation of new particle formation events at a Mediterranean site","authors":"Maria Triantafyllaki,&nbsp;Sofia Eirini Chatoutsidou,&nbsp;Mihalis Lazaridis","doi":"10.1016/j.atmosres.2025.108157","DOIUrl":"10.1016/j.atmosres.2025.108157","url":null,"abstract":"<div><div>New particle formation (NPF) events were investigated at a coastal suburban site (Chania, Greece) in eastern Mediterranean during May 2022–April 2023. The particle number size distribution was measured together with particulate matter (PM₁₀) and gaseous pollutants (NO, NO₂, O₃). 16 NPF events (8 Class I and 8 Class II) were observed with higher occurrence on May (5 events), whereas no NPF event took place on winter months. On the other hand, 15 undefined events were identified with a higher number of events present in February. Increased frequency on warm months was associated with enhanced biogenic and photochemical activity. The average condensation sink, the formation and growth rate for all events was 0.007 s⁻¹, 0.16 cm⁻³ s⁻¹ and 2.60 nmh⁻¹ respectively, without statistically significant differences between Class I and Class II events. The formation and growth rates were higher during the warm period. Nucleation particles (14 nm – 25 nm) preserved no seasonal variations but were significantly increased on periods with NPF activity. NPF activity was enhanced by the presence of condensable sinks that favored nanoparticle formation. Both the growth and the formation rates were positively correlated with solar radiation, temperature and wind speed. Two main factors were identified during NPF events: atmospheric conditions (solar radiation, temperature, wind speed and condensation sinks) and the urban environment (NO). NO₂, O₃ and PM₁₀ were not associated with nucleation particles and NPF activity.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108157"},"PeriodicalIF":4.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"25-Year analysis of tropical cirrus clouds: insights from ground and space-based LIDAR observations","authors":"P. Riya Mol ,&nbsp;M. Venkat Ratnam ,&nbsp;C. Sudheesh","doi":"10.1016/j.atmosres.2025.108158","DOIUrl":"10.1016/j.atmosres.2025.108158","url":null,"abstract":"<div><div>In this study, we used a two-and-a-half-decade dataset (1998–2023) of cirrus cloud properties obtained from a ground-based LIDAR located at the National Atmospheric Research Laboratory (NARL), Gadanki (13.5°N, 79.2°E), India. The percentage occurrence of cirrus clouds during the observational period is 42 %, and the most probable altitude is around 14.2 km. Significant seasonal variability in cirrus clouds is observed, with the highest frequency (74 %) during the monsoon season and the lowest (31 %) in winter. A detailed analysis was conducted on cirrus macro-physical, thermodynamic, and optical properties. Additionally, we investigated the long-term trends of the Tropical Tropopause Layer (TTL) to better understand its relationship with cirrus cloud properties. We observed a significant increasing trend in TTL thickness (0.003 ± 0.0005 km year⁻¹) and Cold point Tropopause Height (CPH) (0.003 ± 0.0003 km year⁻¹) while cirrus base (−0.003 ± 0.001 km year⁻¹), top (−0.005 ± 0.001 km year⁻¹), and geometrical thickness (−0.01 ± 0.0005 km year⁻¹) showed a decreasing trend over the observational period. We also analysed long-term trends of sub-visible, thin and thick cirrus clouds. A significant decreasing trend was found in the mid-cloud altitudes of sub-visible (−0.003 ± 0.001 km year⁻¹), thin (−0.006 ± 0.0009 km year⁻¹), and thick cirrus (−0.008 ± 0.0009 km year⁻¹) clouds, along with an increasing trend in mid-cloud altitude temperatures (0.035 ± 0.008 km year⁻¹_, 0.03 ± 0.007 km year⁻¹_, 0.05 ± 0.009 km year⁻¹) over the last 25 years. Additionally, a significant decreasing trend was noted in the geometrical thickness of sub-visible cirrus clouds and in the optical thickness of thin and thick cirrus clouds. The ground-based climatology obtained from the NARL lidar was compared with 18 years (2006–2023) of data obtained from the Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP) satellite. Both datasets generally exhibit good agreement but differ in the magnitudes of several cirrus cloud properties, an important factor for understanding the radiative impacts of these cirrus clouds.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"323 ","pages":"Article 108158"},"PeriodicalIF":4.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the dynamics of 2024 extreme heat event in India: Spatial variability, hydrometeorological impacts, and model evaluation","authors":"Akash Verma ,&nbsp;Leena Khadke ,&nbsp;Sachin Budakoti","doi":"10.1016/j.atmosres.2025.108154","DOIUrl":"10.1016/j.atmosres.2025.108154","url":null,"abstract":"<div><div>Heatwaves are becoming more intense, frequent, and prolonged due to global warming, posing significant risks to ecosystems and human societies. Despite their profound impact, detailed regional assessments of extreme heat events remain limited, particularly in India. This study addresses the gap by systematically investigating the 2024 extreme heat event in India. We evaluated the performance of various land surface schemes in simulating heat extremes using the Weather Research and Forecasting model and also assessed the accuracy of Global Forecast System (GFS) forecasts. Our analysis reveals a strong co-occurrence of drought and heat stress during the extreme heat event. This combination results in increased fire risk and negative impacts on vegetation productivity in regions affected by both drought and heat stress highlighting the severe consequences of this compound event. We compare different land surface models (RUC, Noah, Noah-MP, Noah-MP with dynamic vegetation, CLM) against India Meteorological Department (IMD) observations. We observe that Noah is optimal for reducing bias and RMSE, while Noah-MP with dynamic vegetation is most accurate for simulating extreme heat, with the highest hit rate and threat score for the 90th percentile threshold. Additionally, GFS maximum temperature forecasts for 1–3 day lead times perform well at short lead times, especially in Southern India but overestimate temperatures in heatwave-prone regions like the Indo-Gangetic Plains. Our findings highlight the importance of enhancing land surface models and forecasting systems to better predict extreme heat events, which is crucial for localized hazard and risk assessments and improving disaster management efficiency.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108154"},"PeriodicalIF":4.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of different El Niño events on winter snowfall over the Tibetan Plateau","authors":"Lihong Wei ,&nbsp;Qinglong You ,&nbsp;Zhiyan Zuo ,&nbsp;Ruonan Zhang ,&nbsp;Shichang Kang","doi":"10.1016/j.atmosres.2025.108156","DOIUrl":"10.1016/j.atmosres.2025.108156","url":null,"abstract":"<div><div>The El Niño-Southern Oscillation (ENSO) and snowfall over the Tibetan Plateau (TP) are key factors influencing interannual climate variability, and the relationship between ENSO and TP snowfall exhibits interdecadal variability. However, the types of El Niño events have undergone changes around 2000s, and it remains unclear whether these changes in El Niño event types influence the relationship with snowfall. In this study, we examine the relationship between El Niño events and winter snowfall over the TP using HadISST, and ERA5 reanalysis datasets as well as numerical experiments. Our results show the eastern Pacific El Niño (EPE) events are typically linked to positive winter snowfall anomalies over the TP, while the mixed-type El Niño (MPE) events are associated with negative anomalies, whereas the response of winter snowfall during the central Pacific El Niño (CPE) events exhibits considerable uncertainty. EPE events are associated with an anomalous deepening of the East Asian winter trough, while MPE events typically induce an anomalous atmospheric circulation wave pattern from the North Pacific to the TP, thereby altering the winter temperature structure and winter snowfall over the TP. This study highlights the impact of EPE and MPE events on TP snowfall and provides insights into the underlying atmospheric processes, offering a foundation for future research on their broader climatic implications.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108156"},"PeriodicalIF":4.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finding optimal Noah-MP parameterizations for the characterization of surface heat fluxes in the Iberian Peninsula","authors":"David Donaire-Montaño ,&nbsp;Matilde García-Valdecasas Ojeda ,&nbsp;Nicolás Tacoronte ,&nbsp;Juan José Rosa-Cánovas ,&nbsp;Yolanda Castro-Díez ,&nbsp;María Jesús Esteban-Parra ,&nbsp;Sonia Raquel Gámiz-Fortis","doi":"10.1016/j.atmosres.2025.108143","DOIUrl":"10.1016/j.atmosres.2025.108143","url":null,"abstract":"<div><div>Land surface models (LSMs) play a crucial role in the characterization of land-atmosphere interactions by providing boundary conditions to a regional climate model (RCM). This is particularly true over the Iberian Peninsula (IP), a region where a water-limited regime governs most of the territory. This work aims to optimize the Noah LSM with multiparameterization options (Noah-MP) configuration for characterizing heat fluxes in the IP when the Weather Research and Forecasting (WRF) model v3.9.1 is used as RCM. To do that, a set of 70 experiments with a 1-year length has been completed using 35 combinations of Noah-MP parameterizations, both for a year with dry conditions in the IP (2005 year) and for a year with wet conditions (2010 year). Land surface heat fluxes and soil moisture simulated with Noah-MP coupled to WRF (WRF/Noah-MP) have been evaluated using as reference the available FLUXNET station data and CERRA-Land reanalysis data. In general, the results indicate that WRF/Noah-MP accurately simulates soil moisture and surface heat fluxes over the IP, especially for wetter climate conditions. The clustering method has presented an optimal configuration from 10 groups (Clusters from A to J), which showed that the WRF/Noah-MP parameterizations with the greatest influence on the simulation of surface heat fluxes over the IP are canopy stomatal resistance (CRS), surface exchange coefficient for heat (SFC), soil moisture factor controlling stomatal resistance (BTR), runoff and groundwater (RUN), and surface resistance to evaporation/sublimation (RSF). In addition, dynamic vegetation (DVEG) seems to influence simulations. Although several clusters/configurations showed reasonable results, experiment s27I in Cluster I with Jarvis CRS, Chen97 SFC, CLM-Type BTR, BATS RUN, and Adjusted Sellers to decrease RSURF for wet soil for RSF seem to be more adequate to simulate surface heat fluxes in the IP.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"323 ","pages":"Article 108143"},"PeriodicalIF":4.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical and particulate properties of dust aerosols in El Paso, Texas","authors":"German Rodriguez Ortiz ,&nbsp;Manisha Mehra ,&nbsp;Mackenzie Ramirez ,&nbsp;Sujan Shrestha ,&nbsp;Sascha Usenko ,&nbsp;James Flynn ,&nbsp;Rebecca J. Sheesley ,&nbsp;Thomas E. Gill","doi":"10.1016/j.atmosres.2025.108127","DOIUrl":"10.1016/j.atmosres.2025.108127","url":null,"abstract":"<div><div>We characterized optical properties (absorption, scattering, and backscattering coefficients, Ångström exponents, single scattering albedo) of aerosols during dust events at an urban site in El Paso, Texas using in-situ, real-time measurements. Simultaneous measurements of particulate matter (PM₁₀, PM_2.5) and wind data from an adjacent Texas Commission on Environmental Quality Continuous Ambient Monitoring Station are used in this study. Data from both sites was obtained at 5-min resolution. Twenty-seven dust events (15 synoptic, 12 mesoscale) occurred during 24 days from April–June 2021. HYSPLIT and STILT back-trajectories indicated many dust events (∼46 %) originated from the west-southwest (favoring transport across dust source areas in the Chihuahuan Desert). Mean absorption Ångström exponent values of El Paso dust (1.19 and 1.15 for synoptic and mesoscale events) were lower than published values for “pure” dust at other locations (generally accepted as greater than 2). Single scattering albedo values averaged 0.94 during synoptic and mesoscale dust events, confirming the scattering nature of mineral dust in the region. PM₁₀ and PM_2.5 concentrations averaged 191 and 41 μg/m³ during dust event periods versus 28 and 8.7 μg/m³ during non-event (background) periods. Absorption / scattering Ångström exponent ratios of dust event aerosols were representative of large particles-black carbon mixture rather than a “pure” dust, suggesting mixing with urban aerosols, while many observations during non-event periods fall into the large particles-black carbon mixture and large particles-low absorption categories, suggesting that dust is a constant key component of the aerosols in El Paso. The 5-min time resolution revealed the evolution of complex aerosol events (e.g., brown carbon followed by dust, multiple dust events within one day, fireworks, advection of low-absorption gypsum dust from White Sands. New Mexico), emphasizing the importance of detecting and quantifying high intensity, short-duration events “lost” in 24-h or hourly air quality data.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108127"},"PeriodicalIF":4.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining machine learning to explore the influence of VOCs and meteorological factors on ozone concentration: A case study of a chemical park in Shenyang, China","authors":"Qi Jiang ,&nbsp;Nan Wang ,&nbsp;Zhenling Jin ,&nbsp;Xuebin Sun ,&nbsp;Jiayin Wang ,&nbsp;Ru Li","doi":"10.1016/j.atmosres.2025.108113","DOIUrl":"10.1016/j.atmosres.2025.108113","url":null,"abstract":"<div><div>Ozone (<span><math><msub><mi>O</mi><mn>3</mn></msub></math></span>) pollution is a pervasive air quality issue, with volatile organic compounds (VOCs) significantly contributing to <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span> formation. Utilizing continuous online monitoring data from a chemical park in Shenyang in 2019, we analyzed variations in VOCs, conventional pollutants, and meteorological conditions, preliminarily determining their apparent effects on <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span>. Results indicated an “M”-shaped monthly average ozone variation, with peaks in summer and troughs in winter, influenced by photochemical reactions and meteorological factors. The daily mean concentrations of alkanes, alkynes, and aromatic hydrocarbons in VOCs displayed clear periodicity, with peaks occurring at 5:00–7:00 and 19:00–20:00, and troughs at 14:00–15:00. The monthly mean concentrations exhibited seasonal trends, with higher levels in fall and winter, and lower levels in spring and summer, demonstrating a pattern opposite to that of <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span>. Using machine learning techniques, we modeled the relationship between key factors and <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span> concentration. The results revealed that the optimized Extreme Gradient Boosting (XGBoost) model achieved the highest correlation coefficient and demonstrated the best performance. Using the feature importance method, we identified the key factors most strongly associated with <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span> concentration. The optimized model was then employed to examine the variation in <span><math><msub><mi>O</mi><mn>3</mn></msub></math></span> concentration across different temperature and humidity conditions. This study provides essential insights for developing effective pollution control strategies and guiding environmental management decisions.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108113"},"PeriodicalIF":4.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of ozone pollution events in Sichuan Basin under the alternating effects of continental high pressure and subtropical high pressure circulation","authors":"Chuanyang Wang ,&nbsp;Xiaoling Zhang ,&nbsp;Jingyi Wang ,&nbsp;Jie Pan ,&nbsp;Jinhui Gao","doi":"10.1016/j.atmosres.2025.108121","DOIUrl":"10.1016/j.atmosres.2025.108121","url":null,"abstract":"<div><div>The Sichuan Basin (SCB), located in Southwest China, often has serious ozone (O₃) pollution due to its special topography, complex meteorological conditions and emissions. The frequent occurrence of extreme high temperature has recently aggravated the biogenic O₃ precursors emission and the O₃ pollution in the SCB. To quantify the O₃ pollution caused by high temperature, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to study the formation mechanism and transport process of the O₃ pollution event in the SCB in July 2022, after updating emission information with TROPOMI satellite data and MEGAN model initial data. The results show that during the pollution period, the SCB was affected by the alternating effects of the circulation changes caused by the eastward movement of the northern continental high pressure and the westward movement of the western Pacific subtropical high pressure. The continuous control of the high pressure formed extremely high temperature, which led to the accelerated generation of O₃ in the SCB. The southeastern continental high pressure and the northwestern subtropical high pressure converged in the SCB, forming a “zigzag”-shaped circulation, which prevented O₃ from being transported out of the SCB. The results of integrated process rate analysis (IPR) show that the negative contribution of horizontal advection accelerates the O₃ output from the cities in the middle of the SCB to the surrounding cities, resulting in the rapid spread of pollution over the SCB, the O₃ accumulation in the high altitude of the basin, and the positive contribution of chemical generation in the south of the SCB.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"322 ","pages":"Article 108121"},"PeriodicalIF":4.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}