Atmospheric Environment最新文献

{"title":"Enhancing real-time PM2.5 forecasts: A hybrid approach of WRF-CMAQ model and CNN algorithm","authors":"Yi-Ju Lee ,&nbsp;Fang-Yi Cheng ,&nbsp;Hsiao-Chen Chien ,&nbsp;Yuan-Chien Lin ,&nbsp;Min-Te Sun","doi":"10.1016/j.atmosenv.2024.120835","DOIUrl":"10.1016/j.atmosenv.2024.120835","url":null,"abstract":"<div><div>As fine particulate matter (PM_2.5) poses significant environmental and human health risks, there is an urgent need for accurate forecasting systems. In Taiwan, the current air quality forecasting (AQF) system based on the Weather Research and Forecasting meteorological model and Community Multiscale Air Quality model provides essential predictions but is limited by biases and computational complexities. This study introduces a convolutional neural network (CNN)-based PM_2.5 forecasting model to enhance prediction accuracy. The CNN model incorporates hourly PM_2.5 concentrations from surface observations and the AQF system, along with synoptic weather patterns (SWPs), to predict PM_2.5 levels up to 72 h in advance. Three CNN models were developed: CNN-BASE (without SWPs), CNN-SWP (with SWPs), and CNN-SWPW (with SWPs and a weighted loss function). Performance assessment reveals a significant reduction in the mean RMSE of 72-h PM_2.5 prediction, from 10.48 μg/m³ with the AQF system to 6.88 μg/m³ with the CNN-BASE model. However, CNN-BASE showed the lowest prediction accuracy for high PM_2.5 concentrations (only 26.2%) due to a small subset of samples. Including SWPs improves the model's ability to capture meteorological influences, enhancing predictions of high PM_2.5 concentrations. Furthermore, CNN-SWPW incorporates a weighted loss function to address imbalanced sample size distributions, further enhancing the accuracy of high PM_2.5 predictions. This study demonstrates the potential of CNNs in operational air quality forecasting.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120835"},"PeriodicalIF":4.2,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315741","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":"Evolution of ozone formation regimes during different periods in representative regions of China","authors":"Juan Zhang ,&nbsp;Ao Shen ,&nbsp;Yinbao Jin ,&nbsp;Yinping Cui ,&nbsp;Yifei Xu ,&nbsp;Xiao Lu ,&nbsp;Yiming Liu ,&nbsp;Qi Fan","doi":"10.1016/j.atmosenv.2024.120830","DOIUrl":"10.1016/j.atmosenv.2024.120830","url":null,"abstract":"<div><p>Ozone (O₃) is produced by photochemical reactions of NO_X and VOCs in the troposphere under sunlight. The column densities of formaldehyde (HCHO) and nitrogen dioxide (NO₂), derived from satellite data, serve as indicators of VOCs and NO_X emissions in the troposphere. Through analyzing the unique characteristics of the threshold range for the HCHO/NO₂ ratio (FNR), the mechanisms of O₃ formation across different regions over a prolonged period can be identified. In this study, we utilized the Empirical Orthogonal Function (EOF) technique to characterize O₃ patterns during the warm season (April to October) spanning 2013–2019. This period is divided into three stages: 2013–2014, 2015–2016, and 2017–2019. Using the third-order fitting model, we assessed the FNR values across different regions in China: BTH (Beijing-Tianjin-Hebei), YRD (Yangtze River Delta), GD (Guangdong), and CY (Chuan-Yu). The FNR value ranges for these regions are as follows: ([1.2,2.0], [1.3,2.1], [2.4,3.2], [1.4,2.2]) during 2013–2014, ([1.1,1.9], [1.2,2.0], [2.0,2.8], [1.2,2.0]) during 2015–2016, and ([1.0,1.8], [1.0,1.8], [1.7,2.5], [1.1,1.9]) during 2017–2019, respectively. Ultimately, our research indicates a shift in certain regions from a VOC-limited regime towards a transitional regime. This shift correlates with a significant decline in anthropogenic NO_X emissions, attributed to the stringent emission control strategies extensively implemented between 2013 and 2019. The spatial expansion of the transitional regime aligns with increasing O₃ concentrations, simultaneously offering guidance for the development of effective emission reduction strategies.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120830"},"PeriodicalIF":4.2,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271699","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":"Molecular insights into the formation of Criegee intermediates from β-hydroxyperoxy radicals","authors":"Long Chen ,&nbsp;Yu Huang ,&nbsp;Yonggang Xue ,&nbsp;Zhihui Jia","doi":"10.1016/j.atmosenv.2024.120828","DOIUrl":"10.1016/j.atmosenv.2024.120828","url":null,"abstract":"<div><p>Organic peroxy radicals (RO₂) and Criegee intermediates (CI, carbonyl oxides) are key reactive species in atmospheric chemistry, and can proceed various reactions influencing the recycling of radicals and the formation of aerosol particles. Carbonyl oxides have recently detected in the OH-initiated autoxidation reactions of unsaturated hydrocarbons. However, their formation mechanisms remain elusive. Herein, the <em>β</em>-hydroxyperoxy radicals (HO-RO₂) are selected as the model compounds to study the mechanism of their transformation to carbonyl oxides. Potential formation pathways of carbonyl oxides, including unimolecular decomposition, bimolecular reactions with OH radicals, HO-RO and HO-RO₂ radicals, are studied by using quantum chemical methods. The results show that the unimolecular decomposition of HO-RO₂ radicals undergoes through the direct cleavage of C-C bond to produce carbonyl oxides, but they are strongly endothermic. For the reactions of HO-RO₂ with OH radicals, the preferable pathway is the barrierless formation of ROOOH on the single PES, and their stability increases with increasing the number of methyl substituents. On the triplet PES, the formation of carbonyl oxides from H-abstraction reaction in the –CH_x group is favorable for the unsubstituted and a methyl substituted HO-RO₂ radicals. For the reactions of HO-RO₂ with HO-RO radicals, the dominant pathway is the barrierless formation of ROOOR on the singlet PES, with dissociation back to the separate reactants being the lowest-energy pathway. The formation of carbonyl oxides is preferable on the triplet PES, and the methyl substitution is beneficial for decreasing the reaction barriers. The barrier for the formation of carbonyl oxides from the self-reaction of HO-RO₂ radicals significantly decrease with increasing the number of methyl substituents. The self-reaction of dimethyl substituted HO-RO₂ radicals forming (CH₃)₂COO is able to compete effectively with the bimolecular reactions with HO₂ radicals. These findings enhance our understanding of the formation of carbonyl oxides from the photochemical oxidation of alkenes.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120828"},"PeriodicalIF":4.2,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271606","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":"Comparison of CAMS and CMAQ analyses of surface-level PM2.5 and O3 over the conterminous United States (CONUS)","authors":"Jared A. Lee ,&nbsp;Stefano Alessandrini ,&nbsp;Ju-Hye Kim ,&nbsp;Scott Meech ,&nbsp;Rajesh Kumar ,&nbsp;Irina V. Djalalova ,&nbsp;James M. Wilczak","doi":"10.1016/j.atmosenv.2024.120833","DOIUrl":"10.1016/j.atmosenv.2024.120833","url":null,"abstract":"<div><p>To reduce economic and health impacts from poor air quality (AQ) in the U.S., the National Air Quality Forecasting Capability (NAQFC) at the National Oceanic and Atmospheric Administration (NOAA) produces forecasts of surface-level ozone (O₃), fine particulate matter (PM_2.5), and other pollutants so that advance notice and warning can be issued to help individuals and communities limit their exposure. The NAQFC uses the U.S. Environmental Protection Agency (EPA) Community Multiscale Air Quality (CMAQ) model for operational forecasts. This study is a first step in proposing a potential upgrade to the current operational NAQFC bias-correction system, by examining potential candidates for a gridded analysis (“truth”) dataset.</p><p>In this paper, we compare the performance of the “analysis” time series over the period of August 2020–December 2021 at EPA AirNow stations for both PM_2.5 and O₃ from raw Copernicus Atmosphere Monitoring Service (CAMS) reanalyses, raw CAMS near real-time forecasts, raw near real-time CMAQ forecasts, bias-corrected CAMS forecasts, and bias-corrected CMAQ forecasts (CMAQ FC BC). This 17-month period spans two wildfire seasons, to assess model “analysis” performance in high-end AQ events. In addition to determining the best-performing gridded product, this process allows us to benchmark the performance of CMAQ forecasts against other global datasets (CAMS reanalysis and forecasts). For both PM_2.5 and O₃, the bias correction algorithm employed here greatly improved upon the raw model time series, and CMAQ FC BC was the best-performing model “analysis” time series, having the lowest RMSE, smallest bias error, and largest critical success index at multiple thresholds.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120833"},"PeriodicalIF":4.2,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271605","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":"Extracting regional and temporal features to improve machine learning for hourly air pollutants in urban India","authors":"Shuai Wang ,&nbsp;Mengyuan Zhang ,&nbsp;Hui Zhao ,&nbsp;Peng Wang ,&nbsp;Sri Harsha Kota ,&nbsp;Qingyan Fu ,&nbsp;Hongliang Zhang","doi":"10.1016/j.atmosenv.2024.120834","DOIUrl":"10.1016/j.atmosenv.2024.120834","url":null,"abstract":"<div><p>India is suffering from severe particulate matter (PM, including PM_2.5 and PM₁₀) pollution, while limited ground observations are insufficient to support a comprehensive understanding of its health risks. Machine learning (ML) has the potential to improve the estimation of PM distribution and exposure efficiently. Regional transport as well as accumulation and dispersion processes of PM and its components, which have significant impacts on PM concentrations, are crucial when building ML models, especially for sparsely observed regions like India. Here, geographic and temporal-rolling weighting methods were used to separately extract regional and temporal features for improving the performance of the ML model. The incorporation of temporal and regional features into the ML model significantly improved ML model performance, with root mean square error (RMSE) reduced by 21 % and 19% for PM_2.5 and PM₁₀ estimation, as well as an improvement in model underestimation for the heavy pollution scenarios. The spatial-temporal model shows out-of-sample test CV coefficients of determination (R²) of 0.87 and 0.88 for hourly PM_2.5 and PM₁₀. The ML model predicts an annual nationwide concentration of 68.3 μg/m³ for PM_2.5 with a north (high, especially in Indo-Gangetic Plain) to south (low) distribution, which is consistent with high satellite aerosol optical depth (AOD) values. Boundary layer height is identified as the main meteorological factor influencing PM_2.5 concentrations in winter. Characterizing the regional transport and cumulative dispersion processes of pollutants by extracting features can help in machine learning training, and this method can be further improved and applied to other studies.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120834"},"PeriodicalIF":4.2,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271696","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":"Effect of cloud chemistry on seasonal variations of sulfate and its precursors in China","authors":"Jianyan Lu ,&nbsp;Chunhong Zhou ,&nbsp;Jian Zhang ,&nbsp;Lei Zhang ,&nbsp;Shuhua Lu ,&nbsp;Sunling Gong","doi":"10.1016/j.atmosenv.2024.120820","DOIUrl":"10.1016/j.atmosenv.2024.120820","url":null,"abstract":"<div><div>Cloud chemistry is of paramount importance in the secondary production of atmospheric aerosols, influencing the spatial-temporal distribution of gases and aerosols in the atmosphere. Using WRF/CUACE (China Meteorological Administration Unified Atmospheric Chemistry Environment), this study assesses the seasonal impacts of cloud chemistry on the concentrations of SO₂, sulfate, as well as two oxidizers, H₂O₂ and O₃, in the most east-central areas of China, including four key pollution zones (the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Sichuan Basin (SCB)). Near the surface, H₂O₂-oxidation was the dominant pathway for cloud chemistry in four key pollution zones in four seasons. H₂O₂ consumption is most pronounced in summer, especially in the SCB and NCP, while O₃ consumption peaks in autumn, particularly in the PRD and southeastern coastal areas. While at higher altitudes, oxidation by O₃ and H₂O₂ is compatible with the cloud chemistry process. Near the surface, cloud chemistry consumes SO₂ ranging from approximately 0.1 ppb–5.0 ppb, resulting in the generation of about 6.0–25.0 μg m⁻³ of sulfate. Higher SO₂ reduction and sulfate increase are in both summer and winter, especially for the SCB and NCP in summer, and the SCB in winter. Vertically, the cloud chemistry process primarily concentrates its influence on SO₂ and sulfate concentrations below 5 km, particularly within the turbulent zone of the troposphere below 2 km in all the four pollution zones and four seasons. The most notable seasonal variation occurs in the NCP compared to other zones. This study also shows that cloud chemistry effectively improves the seasonal simulation accuracy of SO₂ and sulfate, resulting in improved correlation and a notable reduction in RMSE.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120820"},"PeriodicalIF":4.2,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between airborne PM2.5 acute exposure and blood 25-hydroxy vitamin D concentration in children under 3 years old: A retrospective study","authors":"Yuting Xue ,&nbsp;Pai Zheng ,&nbsp;Yonghua Wu ,&nbsp;Tiancheng Wang","doi":"10.1016/j.atmosenv.2024.120832","DOIUrl":"10.1016/j.atmosenv.2024.120832","url":null,"abstract":"<div><div>The harmful consequences of airborne fine particulate matter (PM_2.5) have become a serious public health matter of universal concern, particularly for youngsters. Exposure to PM_2.5 may interfere with vitamin D metabolism in humans. However, the influences of airborne acute PM_2.5 exposure on the blood 25-hydroxy vitamin D [25-OH vitamin D] of young children remains unclear. In the current research, we investigated the links between PM_2.5 acute exposure and plasma 25-OH vitamin D of youngsters who lived in Beijing, China, between April 2020 and September 2022. A total of 1916 children aged from 0.13 to 3.00 years old were enrolled. We collected daily airborne PM_2.5 data and determined the plasma 25-OH vitamin D of children using LC-MS/MS assay. The association between acute PM_2.5 exposure and plasma 25-OH vitamin D was investigated with the generalized linear mixed model and generalized additive model. Our results demonstrated that the acute exposure to airborne PM_2.5 was a linear negative correlation with the plasma 25-OH vitamin D₃ in infants, each 10 μg/m³ elevate in airborne PM_2.5 on current (lag0), lag1, and lag01 (the moving average concentration) days were related to a 0.139 (95% CI: 0.274–0.004), 0.158 (95% CI: 0.305–0.011) and 0.178 (95% CI: 0.333–0.023) ng/mL decrease in plasma 25-OH vitamin D₃, respectively. The declining tendency of plasma 25-OH vitamin D₃ remained robust after adjusting the airborne PM₁₀ and O₃ in the sensitivity analyses. Our study lends credence that the airborne PM_2.5 acute exposure imposed relatively mild but significant reductions in plasma vitamin 25-OH vitamin D₃ in young children.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120832"},"PeriodicalIF":4.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312646","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":"Volatile organic compounds in typical coal chemical industrial park in China and their environmental and health impacts","authors":"Jieting Zhou ,&nbsp;Min Gao ,&nbsp;Hongmei Xu ,&nbsp;Ruiqing Cai ,&nbsp;Rong Feng ,&nbsp;Kun He ,&nbsp;Jian Sun ,&nbsp;Steven Sai Hang Ho ,&nbsp;Zhenxing Shen","doi":"10.1016/j.atmosenv.2024.120825","DOIUrl":"10.1016/j.atmosenv.2024.120825","url":null,"abstract":"<div><p>The coal chemical industry produces a large amount of volatile organic compounds (VOCs), and the emission characteristics and associated impact on the environment and health of the residents are still unclear. This study determined the VOC concentrations and compositions in the Jinjie Coal Chemical Industry Park which is located in northern China. The average concentrations of total measured VOCs (TVOCs) in the industrial areas in summer and winter were 231.5 and 103.2 μg/m³, which were higher than those in the residential areas (123.7 and 70.3 μg/m³), respectively. Aromatics, Oxygenated volatile organic compounds (OVOCs), and alkanes were the dominant VOC classes in the industrial areas, while halocarbons, OVOCs, and alkenes had higher compositions in the residential areas where were not only affected by industrial emissions and also other anthropogenic sources. OVOCs contributed over 43% of ozone formation potential (OFP), while aromatics contributed over 61% of secondary organic aerosol (SOA) formation in the Park in both seasons. Using the source apportionment method, biogenic emission and anthropogenic source (gasoline production, coking emission, fuel combustion, solvent coating, and vehicle exhaust) were major contributors to VOCs in residential areas. The industrial-related emissions were the main components of anthropogenic source, accounting for 53.5%–58.7% of the overall VOCs. With reliable estimations of the health aspects, exposures to acrolein (HQ: 7.4–126.6) and formaldehyde (ILCR: 5.5 × 10⁻³-5.7 × 10⁻²) posed the highest non-carcinogenic and carcinogenic risks, accounting for 94.3%–98.6% and 55.8%–93.8% of the total HQ and ILCR, respectively. The results demonstrated that substantial environmental and health co-benefits to the residents could be achieved by reducing the industrial emissions from gasoline production, coking process, and diesel-fueled vehicles in the Jinjie Coal Chemical Industry Park. Prioritizing the establishment of efficient air pollution measures and tightening industrial emission standards, especially for hazardous VOCs, are recommended according to the findings of the valuable work.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120825"},"PeriodicalIF":4.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271697","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":"Seasonal variation and origins of C1–C5 alkyl nitrates: A year-long study at a Hong Kong coastal site","authors":"Hao Sun ,&nbsp;Dasa Gu ,&nbsp;Zijie Xu ,&nbsp;Xin Feng ,&nbsp;Xiangyunong Cao ,&nbsp;Yuchen Mai ,&nbsp;Xin Li ,&nbsp;Ho Wun Lee ,&nbsp;Ka Fung Leung ,&nbsp;Tsz Ching Tse ,&nbsp;Wai Ming Chan ,&nbsp;Sin Ka Mak","doi":"10.1016/j.atmosenv.2024.120824","DOIUrl":"10.1016/j.atmosenv.2024.120824","url":null,"abstract":"<div><div>Alkyl nitrates (RONO₂) are key reactive nitrogen compounds with significant impacts on local and regional air quality. The concentrations of alkyl nitrates can vary significantly across different regions, especially in areas with varying levels of human activity. Long-term observation of alkyl nitrates is necessary to assess the intensity of photochemical reactions and the contributions from different sources. In this study, we present the first continuous year-long monitoring results of eight alkyl nitrates via whole air sample collection and GC-MSD/ECD analysis at a coastal site in Hong Kong. Source apportionment analysis via positive matrix factorization (PMF) revealed distinctive seasonal variations in the source contributions for the eight alkyl nitrate species. Furthermore, increased contributions from biomass combustion were found in autumn and winter, while marine emissions primarily influenced methyl nitrate levels during summer. Our study highlights the significant impact of biomass burning from inland areas on photochemical pollutants in Hong Kong. Cross-regional cooperation in the Greater Bay Area (GBA) is necessary for more comprehensive management of secondary photochemical pollution.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120824"},"PeriodicalIF":4.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312645","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":"A comprehensive analysis of new particle formation across the northwest Atlantic: Analysis of ACTIVATE airborne data","authors":"Soodabeh Namdari ,&nbsp;Taiwo Ajayi ,&nbsp;Yonghoon Choi ,&nbsp;Ewan C. Crosbie ,&nbsp;Joshua P. DiGangi ,&nbsp;Glenn S. Diskin ,&nbsp;Simon Kirschler ,&nbsp;Hongyu Liu ,&nbsp;John B. Nowak ,&nbsp;Michael A. Shook ,&nbsp;Cassidy Soloff ,&nbsp;Kenneth L. Thornhill ,&nbsp;Christiane Voigt ,&nbsp;Edward L. Winstead ,&nbsp;Bo Zhang ,&nbsp;Luke D. Ziemba ,&nbsp;Armin Sorooshian","doi":"10.1016/j.atmosenv.2024.120831","DOIUrl":"10.1016/j.atmosenv.2024.120831","url":null,"abstract":"<div><p>New particle formation (NPF) is a critical source of particles and cloud condensation nuclei, yet there are scarce vertically-resolved measurements addressing NPF across different seasons in marine regions. This study leverages a multi-season set of airborne data from the NASA ACTIVATE mission between 2020 and 2022 to examine NPF characteristics over the northwest Atlantic ranging from the polluted U.S. East Coast to as far downwind (&gt;1000 km) as Bermuda. Using the number concentration ratio above 3 and 10 nm (N₃:N₁₀) as a NPF indicator, we observe the highest ratios in the coldest months and comparable ratios over Bermuda relative to the U.S. East Coast. Within seasons, the highest and lowest ratios are found immediately above cloud tops and at the lowest possible flight altitudes (∼150 m above sea level), respectively. The ratio of (N₃-N₁₀)/N₃ ranges from 0.16 to 0.29 depending on altitude, proximity to clouds, and season. The N₃:N₁₀ and (N₃-N₁₀)/N₃ ratios increase with altitude up to as high as 9 km, with a case study showing favorable conditions around relatively thicker and precipitating cloud systems presumably due to high actinic fluxes and reduced aerosol surface area. Regression modeling reveals that increased N₃:N₁₀ is influenced most by reductions in temperature, relative humidity, and aerosol surface area. This work emphasizes the importance of both NPF in remote marine regions like Bermuda and vertical heterogeneity that exists in its contribution to aerosol and cloud condensation nuclei number budgets.</p></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120831"},"PeriodicalIF":4.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271698","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}