Pub Date : 2024-06-19DOI: 10.5194/acp-24-7041-2024
Tapio Schneider, L. Ruby Leung, Robert C. J. Wills
Abstract. Accelerated progress in climate modeling is urgently needed for proactive and effective climate change adaptation. The central challenge lies in accurately representing processes that are small in scale yet climatically important, such as turbulence and cloud formation. These processes will not be explicitly resolvable for the foreseeable future, necessitating the use of parameterizations. We propose a balanced approach that leverages the strengths of traditional process-based parameterizations and contemporary artificial intelligence (AI)-based methods to model subgrid-scale processes. This strategy employs AI to derive data-driven closure functions from both observational and simulated data, integrated within parameterizations that encode system knowledge and conservation laws. In addition, increasing the resolution to resolve a larger fraction of small-scale processes can aid progress toward improved and interpretable climate predictions outside the observed climate distribution. However, currently feasible horizontal resolutions are limited to O(10 km) because higher resolutions would impede the creation of the ensembles that are needed for model calibration and uncertainty quantification, for sampling atmospheric and oceanic internal variability, and for broadly exploring and quantifying climate risks. By synergizing decades of scientific development with advanced AI techniques, our approach aims to significantly boost the accuracy, interpretability, and trustworthiness of climate predictions.
{"title":"Opinion: Optimizing climate models with process knowledge, resolution, and artificial intelligence","authors":"Tapio Schneider, L. Ruby Leung, Robert C. J. Wills","doi":"10.5194/acp-24-7041-2024","DOIUrl":"https://doi.org/10.5194/acp-24-7041-2024","url":null,"abstract":"Abstract. Accelerated progress in climate modeling is urgently needed for proactive and effective climate change adaptation. The central challenge lies in accurately representing processes that are small in scale yet climatically important, such as turbulence and cloud formation. These processes will not be explicitly resolvable for the foreseeable future, necessitating the use of parameterizations. We propose a balanced approach that leverages the strengths of traditional process-based parameterizations and contemporary artificial intelligence (AI)-based methods to model subgrid-scale processes. This strategy employs AI to derive data-driven closure functions from both observational and simulated data, integrated within parameterizations that encode system knowledge and conservation laws. In addition, increasing the resolution to resolve a larger fraction of small-scale processes can aid progress toward improved and interpretable climate predictions outside the observed climate distribution. However, currently feasible horizontal resolutions are limited to O(10 km) because higher resolutions would impede the creation of the ensembles that are needed for model calibration and uncertainty quantification, for sampling atmospheric and oceanic internal variability, and for broadly exploring and quantifying climate risks. By synergizing decades of scientific development with advanced AI techniques, our approach aims to significantly boost the accuracy, interpretability, and trustworthiness of climate predictions.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"44 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-19DOI: 10.5194/egusphere-2024-1561
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, Ilse Aben
Abstract. We use satellite observations of carbon monoxide (CO) to estimate CO emissions from European integrated iron & steel plants, the continent’s highest emitting CO point sources. We perform analytical inversions to estimate emissions from 21 individual plants using observations from the Tropospheric Monitoring Instrument (TROPOMI) for 2019. As prior emissions, we use values reported by the facilities to the European Pollutant Release and Transfer Register (E-PRTR). These reported emissions vary in estimation methodology, including both measurements and calculations. With the Weather Research and Forecasting (WRF) model, we perform an ensemble of simulations with different transport settings to best replicate the observed emission plumes for each day and site. Comparing the inversion-based emission estimates to the E-PRTR reports, nine of the plants agree within uncertainties. For the remaining plants, we generally find lower emission rates than reported. Our posterior emission estimates are well-constrained by the satellite observations (90 % of the plants have averaging kernel sensitivities above 0.7) except for a few low-emitting or coastal sites. We find agreement between our inversion results and emissions we estimate using the Cross-Sectional Flux (CSF) method for the seven strongest-emitting plants, building further confidence in the inversion estimates. Finally, for four plants with large year-to-year variability in reported emission rates or large differences between the reported emission rate and our posterior estimate, we extend our analysis to 2020. We find no evidence in either the observed carbon monoxide concentrations or our inversion results for strong changes in emission rates. This demonstrates how satellites can be used to identify potential uncertainties in reported emissions.
{"title":"Comparing space-based to reported carbon monoxide emission estimates for Europe’s iron & steel plants","authors":"Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, Ilse Aben","doi":"10.5194/egusphere-2024-1561","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1561","url":null,"abstract":"<strong>Abstract.</strong> We use satellite observations of carbon monoxide (CO) to estimate CO emissions from European integrated iron & steel plants, the continent’s highest emitting CO point sources. We perform analytical inversions to estimate emissions from 21 individual plants using observations from the Tropospheric Monitoring Instrument (TROPOMI) for 2019. As prior emissions, we use values reported by the facilities to the European Pollutant Release and Transfer Register (E-PRTR). These reported emissions vary in estimation methodology, including both measurements and calculations. With the Weather Research and Forecasting (WRF) model, we perform an ensemble of simulations with different transport settings to best replicate the observed emission plumes for each day and site. Comparing the inversion-based emission estimates to the E-PRTR reports, nine of the plants agree within uncertainties. For the remaining plants, we generally find lower emission rates than reported. Our posterior emission estimates are well-constrained by the satellite observations (90 % of the plants have averaging kernel sensitivities above 0.7) except for a few low-emitting or coastal sites. We find agreement between our inversion results and emissions we estimate using the Cross-Sectional Flux (CSF) method for the seven strongest-emitting plants, building further confidence in the inversion estimates. Finally, for four plants with large year-to-year variability in reported emission rates or large differences between the reported emission rate and our posterior estimate, we extend our analysis to 2020. We find no evidence in either the observed carbon monoxide concentrations or our inversion results for strong changes in emission rates. This demonstrates how satellites can be used to identify potential uncertainties in reported emissions.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"25 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/acp-24-6987-2024
Wei Sun, Xiaodong Hu, Yuzhen Fu, Guohua Zhang, Yujiao Zhu, Xinfeng Wang, Caiqing Yan, Likun Xue, He Meng, Bin Jiang, Yuhong Liao, Xinming Wang, Ping'an Peng, Xinhui Bi
Abstract. While aqueous-phase processing is known to contribute to the formation of nitrogen-containing organic compounds (NOCs), the specific pathways involved remain poorly understood. In this study, we aimed to characterize the NOCs present in both pre-fog aerosols and fog water collected at a suburban site in northern China. Fourier-transform ion cyclotron resonance mass spectrometry was utilized to analyze the molecular composition of NOCs in both negative and positive modes of electrospray ionization (ESI− and ESI+). In both pre-fog aerosols and fog water samples, NOCs constituted a significant portion, accounting for over 60 % of all assigned formulas in ESI− and more than 80 % in ESI+. By comparing the molecular composition of NOCs originating from biomass burning, coal combustion, and vehicle emissions, we identified that 72.3 % of NOCs in pre-fog aerosols were attributed to primary anthropogenic sources (pNOCs), while the remaining NOCs were categorized as secondary NOCs formed within the aerosols (saNOCs). Unique NOCs found in fog water were classified as secondary NOCs formed within the fog water (sfNOCs). Through a comprehensive “precursor–product pair” screening involving 39 reaction pathways, we observed that the nitration reaction, the amine pathway, and the intramolecular N-heterocycle pathway of NH3 addition reactions contributed 43.6 %, 22.1 %, and 11.6 % of saNOCs, respectively. In contrast, these pathways contributed 26.8 %, 28.4 %, and 29.7 % of sfNOCs, respectively. This disparity in formation pathways is likely influenced by the diverse precursors, the aqueous acidity, and the gas-phase species partitioning. Correspondingly, saNOCs were found to contain a higher abundance of carbohydrate-like and highly oxygenated compounds with two nitrogen atoms compared to pNOCs. Conversely, sfNOCs exhibited a higher content of lipid-like compounds with fewer oxygen atoms. These results underscore the distinct secondary processes contributing to the diversity of NOCs in aerosols and fog water, which may lead to their different climate effects.
{"title":"Different formation pathways of nitrogen-containing organic compounds in aerosols and fog water in northern China","authors":"Wei Sun, Xiaodong Hu, Yuzhen Fu, Guohua Zhang, Yujiao Zhu, Xinfeng Wang, Caiqing Yan, Likun Xue, He Meng, Bin Jiang, Yuhong Liao, Xinming Wang, Ping'an Peng, Xinhui Bi","doi":"10.5194/acp-24-6987-2024","DOIUrl":"https://doi.org/10.5194/acp-24-6987-2024","url":null,"abstract":"Abstract. While aqueous-phase processing is known to contribute to the formation of nitrogen-containing organic compounds (NOCs), the specific pathways involved remain poorly understood. In this study, we aimed to characterize the NOCs present in both pre-fog aerosols and fog water collected at a suburban site in northern China. Fourier-transform ion cyclotron resonance mass spectrometry was utilized to analyze the molecular composition of NOCs in both negative and positive modes of electrospray ionization (ESI− and ESI+). In both pre-fog aerosols and fog water samples, NOCs constituted a significant portion, accounting for over 60 % of all assigned formulas in ESI− and more than 80 % in ESI+. By comparing the molecular composition of NOCs originating from biomass burning, coal combustion, and vehicle emissions, we identified that 72.3 % of NOCs in pre-fog aerosols were attributed to primary anthropogenic sources (pNOCs), while the remaining NOCs were categorized as secondary NOCs formed within the aerosols (saNOCs). Unique NOCs found in fog water were classified as secondary NOCs formed within the fog water (sfNOCs). Through a comprehensive “precursor–product pair” screening involving 39 reaction pathways, we observed that the nitration reaction, the amine pathway, and the intramolecular N-heterocycle pathway of NH3 addition reactions contributed 43.6 %, 22.1 %, and 11.6 % of saNOCs, respectively. In contrast, these pathways contributed 26.8 %, 28.4 %, and 29.7 % of sfNOCs, respectively. This disparity in formation pathways is likely influenced by the diverse precursors, the aqueous acidity, and the gas-phase species partitioning. Correspondingly, saNOCs were found to contain a higher abundance of carbohydrate-like and highly oxygenated compounds with two nitrogen atoms compared to pNOCs. Conversely, sfNOCs exhibited a higher content of lipid-like compounds with fewer oxygen atoms. These results underscore the distinct secondary processes contributing to the diversity of NOCs in aerosols and fog water, which may lead to their different climate effects.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"46 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/egusphere-2024-1671
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, Ye Wu
Abstract. The advancement of analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS), enables the efficient separation of complex organic matrix. Developing innovative methods for data processing and analysis is crucial to unlock the full potential of GC×GC-MS in understanding intricate chemical mixtures. In this study, we proposed an innovative method for the semi-automated identification and quantification of complex organic mixtures using GC×GC-MS. The method was formulated based on self-constructed mass spectrum patterns and the traversal algorithms and was applied to organic vapor and aerosol samples collected from tailpipe emissions of heavy-duty diesel vehicles and the ambient atmosphere. Thousands of compounds were filtered, speciated, and clustered into 26 categories, including aliphatic and cyclic hydrocarbons, aromatic hydrocarbons, aliphatic oxygenated species, phenols and alkyl-phenols, and heteroatom containing species. The identified species accounted for over 80 % of all the eluted chromatographic peaks at the molecular level. A comprehensive analysis of quantification uncertainty was undertaken. Using representative compounds, quantification uncertainties were found to be less than 37.67 %, 22.54 %, and 12.74 % for alkanes, polycyclic aromatic hydrocarbons (PAHs), and alkyl-substituted benzenes, respectively, across the GC×GC space, excluding the first and the last time intervals. From source apportionment perspective, adamantane was clearly isolated as a potential tracer for heavy-duty diesel vehicles (HDDVs) emission. The systematic distribution of N-containing compounds in oxidized and reduced valences was discussed and many of them served as critical tracers for secondary nitrate formation processes. The results highlighted the benefits of developing self-constructed model for the enhanced peak identification, automated cluster analysis, robust uncertainty estimation, and source apportionment and achieving the full potential of GC×GC-MS in atmospheric chemistry.
{"title":"Automated compound speciation, cluster analysis, and quantification of organic vapours and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry","authors":"Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, Ye Wu","doi":"10.5194/egusphere-2024-1671","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1671","url":null,"abstract":"<strong>Abstract.</strong> The advancement of analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS), enables the efficient separation of complex organic matrix. Developing innovative methods for data processing and analysis is crucial to unlock the full potential of GC×GC-MS in understanding intricate chemical mixtures. In this study, we proposed an innovative method for the semi-automated identification and quantification of complex organic mixtures using GC×GC-MS. The method was formulated based on self-constructed mass spectrum patterns and the traversal algorithms and was applied to organic vapor and aerosol samples collected from tailpipe emissions of heavy-duty diesel vehicles and the ambient atmosphere. Thousands of compounds were filtered, speciated, and clustered into 26 categories, including aliphatic and cyclic hydrocarbons, aromatic hydrocarbons, aliphatic oxygenated species, phenols and alkyl-phenols, and heteroatom containing species. The identified species accounted for over 80 % of all the eluted chromatographic peaks at the molecular level. A comprehensive analysis of quantification uncertainty was undertaken. Using representative compounds, quantification uncertainties were found to be less than 37.67 %, 22.54 %, and 12.74 % for alkanes, polycyclic aromatic hydrocarbons (PAHs), and alkyl-substituted benzenes, respectively, across the GC×GC space, excluding the first and the last time intervals. From source apportionment perspective, adamantane was clearly isolated as a potential tracer for heavy-duty diesel vehicles (HDDVs) emission. The systematic distribution of N-containing compounds in oxidized and reduced valences was discussed and many of them served as critical tracers for secondary nitrate formation processes. The results highlighted the benefits of developing self-constructed model for the enhanced peak identification, automated cluster analysis, robust uncertainty estimation, and source apportionment and achieving the full potential of GC×GC-MS in atmospheric chemistry.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"2 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. The chemical composition of individual particles can be revealed by single-particle mass spectrometers (SPMSs). With higher accuracy in the ratio of mass to charge (m/z), more detailed chemical information could be obtained. In SPMSs, the conventional standard-based calibration methods (internal/external) are constrained by the inhomogeneity of ionization lasers and the finite focusing ability of the inlet system, etc.; therefore, the mass accuracy is restricted. In this study, we obtained the detailed and reliable chemical composition of single particles utilizing a standard-free mass calibration algorithm. In the algorithm, the characteristic distributions of hundreds of ions were concluded and collected in a database denoted as prototype. Each single-particle mass spectrum was initially calibrated by a function with specific coefficients. The range of coefficients was constrained by the magnitude of mass deviation to a finite vector space. To find the optimal coefficient vector, the conformity of each initially calibrated spectrum to the prototype dataset was assessed. The optimum calibrated spectrum was obtained with maximum conformity. For more than 98 % ambient particles, a 20-fold improvement in mass accuracy, from ∼ 10 000 ppm (integer) to ∼ 500 ppm (two decimal places), was achieved. The improved mass accuracy validated the determination of adjacent ions with a m/z difference ∼ 0.05 Th. Furthermore, atmospheric particulate trace elements that were poorly studied before are specified. The obtained detailed single-particle-level chemical information could help explain the source apportionment, reaction mechanism, and mixing state of atmospheric particles.
{"title":"Technical note: Determining chemical composition of atmospheric single particles by a standard-free mass calibration algorithm","authors":"Shao Shi, Jinghao Zhai, Xin Yang, Yechun Ruan, Yuanlong Huang, Xujian Chen, Antai Zhang, Jianhuai Ye, Guomao Zheng, Baohua Cai, Yaling Zeng, Yixiang Wang, Chunbo Xing, Yujie Zhang, Tzung-May Fu, Lei Zhu, Huizhong Shen, Chen Wang","doi":"10.5194/acp-24-7001-2024","DOIUrl":"https://doi.org/10.5194/acp-24-7001-2024","url":null,"abstract":"Abstract. The chemical composition of individual particles can be revealed by single-particle mass spectrometers (SPMSs). With higher accuracy in the ratio of mass to charge (m/z), more detailed chemical information could be obtained. In SPMSs, the conventional standard-based calibration methods (internal/external) are constrained by the inhomogeneity of ionization lasers and the finite focusing ability of the inlet system, etc.; therefore, the mass accuracy is restricted. In this study, we obtained the detailed and reliable chemical composition of single particles utilizing a standard-free mass calibration algorithm. In the algorithm, the characteristic distributions of hundreds of ions were concluded and collected in a database denoted as prototype. Each single-particle mass spectrum was initially calibrated by a function with specific coefficients. The range of coefficients was constrained by the magnitude of mass deviation to a finite vector space. To find the optimal coefficient vector, the conformity of each initially calibrated spectrum to the prototype dataset was assessed. The optimum calibrated spectrum was obtained with maximum conformity. For more than 98 % ambient particles, a 20-fold improvement in mass accuracy, from ∼ 10 000 ppm (integer) to ∼ 500 ppm (two decimal places), was achieved. The improved mass accuracy validated the determination of adjacent ions with a m/z difference ∼ 0.05 Th. Furthermore, atmospheric particulate trace elements that were poorly studied before are specified. The obtained detailed single-particle-level chemical information could help explain the source apportionment, reaction mechanism, and mixing state of atmospheric particles.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"13 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/acp-24-7013-2024
Yuehan Luo, Tianliang Zhao, Kai Meng, Jun Hu, Qingjian Yang, Yongqing Bai, Kai Yang, Weikang Fu, Chenghao Tan, Yifan Zhang, Yanzhe Zhang, Zhikuan Li
Abstract. Stratosphere-to-troposphere transport results in the stratospheric intrusion (SI) of O3 into the free troposphere through the folding of the tropopause. However, the mechanism of SI that influences the atmospheric environment through the cross-layer transport of O3 from the stratosphere and free troposphere to the atmospheric boundary layer has not been elucidated thoroughly. In this study, an SI event over the North China Plain (NCP; 33–40° N, 114–121° E) during 19–20 May 2019 was chosen to investigate the mechanism of the cross-layer transport of stratospheric O3 and its impact on the near-surface O3 based on multi-source reanalysis, observation data, and air quality modeling. The results revealed a mechanism of stratospheric O3 intrusion into the atmospheric environment induced by an extratropical cyclone system. The SI with downward transport of stratospheric O3 to the near-surface layer was driven by the extratropical cyclone system, with vertical coupling of the upper westerly trough, the middle of the northeast cold vortex (NECV), and the lower extratropical cyclone, in the troposphere. The deep trough in the westerly jet aroused the tropopause folding, and the lower-stratospheric O3 penetrated the folded tropopause into the upper and middle troposphere; the westerly trough was cut off to form a typical cold vortex in the upper and middle troposphere. The compensating downdrafts of the NECV further pushed the downward transport of stratospheric O3 in the free troposphere; the NECV activated an extratropical cyclone in the lower troposphere; and the vertical cyclonic circulation governed the stratospheric O3 from the free troposphere across the boundary layer top, invading the near-surface atmosphere. In this SI event, the average contribution of stratospheric O3 to near-surface O3 was accounted for at 26.77 %. The proposed meteorological mechanism of the vertical transport of stratospheric O3 into the near-surface atmosphere, driven by an extratropical cyclone system, could improve the understanding of the influence of stratospheric O3 on the atmospheric environment, with implications for the coordinated control of atmospheric pollution.
{"title":"A mechanism of stratospheric O3 intrusion into the atmospheric environment: a case study of the North China Plain","authors":"Yuehan Luo, Tianliang Zhao, Kai Meng, Jun Hu, Qingjian Yang, Yongqing Bai, Kai Yang, Weikang Fu, Chenghao Tan, Yifan Zhang, Yanzhe Zhang, Zhikuan Li","doi":"10.5194/acp-24-7013-2024","DOIUrl":"https://doi.org/10.5194/acp-24-7013-2024","url":null,"abstract":"Abstract. Stratosphere-to-troposphere transport results in the stratospheric intrusion (SI) of O3 into the free troposphere through the folding of the tropopause. However, the mechanism of SI that influences the atmospheric environment through the cross-layer transport of O3 from the stratosphere and free troposphere to the atmospheric boundary layer has not been elucidated thoroughly. In this study, an SI event over the North China Plain (NCP; 33–40° N, 114–121° E) during 19–20 May 2019 was chosen to investigate the mechanism of the cross-layer transport of stratospheric O3 and its impact on the near-surface O3 based on multi-source reanalysis, observation data, and air quality modeling. The results revealed a mechanism of stratospheric O3 intrusion into the atmospheric environment induced by an extratropical cyclone system. The SI with downward transport of stratospheric O3 to the near-surface layer was driven by the extratropical cyclone system, with vertical coupling of the upper westerly trough, the middle of the northeast cold vortex (NECV), and the lower extratropical cyclone, in the troposphere. The deep trough in the westerly jet aroused the tropopause folding, and the lower-stratospheric O3 penetrated the folded tropopause into the upper and middle troposphere; the westerly trough was cut off to form a typical cold vortex in the upper and middle troposphere. The compensating downdrafts of the NECV further pushed the downward transport of stratospheric O3 in the free troposphere; the NECV activated an extratropical cyclone in the lower troposphere; and the vertical cyclonic circulation governed the stratospheric O3 from the free troposphere across the boundary layer top, invading the near-surface atmosphere. In this SI event, the average contribution of stratospheric O3 to near-surface O3 was accounted for at 26.77 %. The proposed meteorological mechanism of the vertical transport of stratospheric O3 into the near-surface atmosphere, driven by an extratropical cyclone system, could improve the understanding of the influence of stratospheric O3 on the atmospheric environment, with implications for the coordinated control of atmospheric pollution.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"43 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.22541/essoar.170231679.99186200/v1
Michael Sicard, Alexandre Baron, Marion Ranaivombola, Dominique Gantois, Tristan Millet, Pasquale Sellitto, Nelson Bègue, Hassan Bencherif, Guillaume Payen, Nicolas Marquestaut, Valentin Duflot
Abstract. This study attempts to quantify the radiative impact over Reunion Island (21° S, 55° E) in the southern tropical Indian Ocean of the aerosols and water vapor injected in the stratosphere by the eruption on 15 January 2022 of the Hunga Tonga-Hunga Ha'apai underwater volcano in the South Pacific. Ground-based lidar and satellite passive instruments are used to parametrize a state-of-the-art radiative transfer model for the first thirteen months after the volcano eruption. The descending rate of the aerosol volcanic plume is -0.008 km day-1. At this rate, aerosols are expected to be present in the stratosphere until the first half of 2025. The overall aerosol and water vapor impact on the Earth’s radiation budget for the whole period is negative (cooling, -0.54 ± 0.29 W m-2) and dominated by the aerosol impact (~93 %; the remaining ~7 % are due to WV). At the Earth’s surface, aerosols are the main driver and produce a negative (cooling, -1.19 ± 0.40 W m-2) radiative impact. Between the short- (month 2 to 4 after the eruption) and mid-term (month 5 to 14 after the eruption) periods, the aerosol and water vapor radiative effect at both the surface and TOA reduces 22 to 25 %. Heating/cooling rate profiles during the mid-term period show a clear vertical difference in the stratosphere between the aerosol warming impact (17 to 25 km) and the water vapor cooling one (25 to 40 km).
{"title":"Radiative impact of the Hunga Tonga-Hunga Ha'apai stratospheric volcanic plume: role of aerosols and water vapor in the southern tropical Indian Ocean","authors":"Michael Sicard, Alexandre Baron, Marion Ranaivombola, Dominique Gantois, Tristan Millet, Pasquale Sellitto, Nelson Bègue, Hassan Bencherif, Guillaume Payen, Nicolas Marquestaut, Valentin Duflot","doi":"10.22541/essoar.170231679.99186200/v1","DOIUrl":"https://doi.org/10.22541/essoar.170231679.99186200/v1","url":null,"abstract":"<strong>Abstract.</strong> This study attempts to quantify the radiative impact over Reunion Island (21° S, 55° E) in the southern tropical Indian Ocean of the aerosols and water vapor injected in the stratosphere by the eruption on 15 January 2022 of the Hunga Tonga-Hunga Ha'apai underwater volcano in the South Pacific. Ground-based lidar and satellite passive instruments are used to parametrize a state-of-the-art radiative transfer model for the first thirteen months after the volcano eruption. The descending rate of the aerosol volcanic plume is -0.008 km day<sup>-1</sup>. At this rate, aerosols are expected to be present in the stratosphere until the first half of 2025. The overall aerosol and water vapor impact on the Earth’s radiation budget for the whole period is negative (cooling, -0.54 ± 0.29 W m<sup>-2</sup>) and dominated by the aerosol impact (~93 %; the remaining ~7 % are due to WV). At the Earth’s surface, aerosols are the main driver and produce a negative (cooling, -1.19 ± 0.40 W m<sup>-2</sup>) radiative impact. Between the short- (month 2 to 4 after the eruption) and mid-term (month 5 to 14 after the eruption) periods, the aerosol and water vapor radiative effect at both the surface and TOA reduces 22 to 25 %. Heating/cooling rate profiles during the mid-term period show a clear vertical difference in the stratosphere between the aerosol warming impact (17 to 25 km) and the water vapor cooling one (25 to 40 km).","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"13 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/acp-24-7027-2024
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, Hong Liao
Abstract. Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx, but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO2 reflects a dynamic balance between emission and chemical loss.
{"title":"Interpreting Geostationary Environment Monitoring Spectrometer (GEMS) geostationary satellite observations of the diurnal variation in nitrogen dioxide (NO2) over East Asia","authors":"Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, Hong Liao","doi":"10.5194/acp-24-7027-2024","DOIUrl":"https://doi.org/10.5194/acp-24-7027-2024","url":null,"abstract":"Abstract. Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx, but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO2 reflects a dynamic balance between emission and chemical loss.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"24 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/egusphere-2024-1454
Mingxu Liu, Hitoshi Matsui, Douglas Hamilton, Sagar Rathod, Kara Lamb, Natalie Mahowald
Abstract. Atmospheric aerosol deposition acts as a major source of soluble (bioavailable) iron in open ocean regions where it limits phytoplankton growth and primary production. The aerosol size distribution of emitted iron particles, along with particle growth from mixing with other atmospheric components, is an important modulator of its long-range transport potential. There currently exists a large uncertainty in the particle size distribution of iron aerosol, and the role of aerosol size in shaping global soluble iron deposition is thus unclear. In this study, we couple a sophisticated microphysical, size-resolved aerosol model with an iron-speciated and -processing module to disentangle the impact of iron emission size distributions on soluble iron input to the ocean, with a focus on anthropogenic combustion and metal smelting sources. We first evaluate our model results against a global-scale flight measurement dataset for anthropogenic iron concentration and find that the different representations of iron size distribution at emission, as adopted in previous studies, introduces a variability in modeled iron concentrations over remote oceans of a factor of 10. Shifting the iron aerosol size distribution toward finer particle sizes (<1 μm) enables longer atmospheric lifetime (a doubling), promoting atmospheric processing that enhances the soluble iron deposition to ocean basins by up to 50 % on an annual basis. Importantly, the monthly enhancements reach 110 % and 80 % over the Southern Ocean and North Pacific Ocean, respectively. Compared with emission flux uncertainties, we find that iron emission size distribution plays an equally important role in regulating soluble iron deposition, especially to the remote oceans. Our findings provide implications for understanding the effects of atmospheric nutrients input on marine biogeochemistry, including but not limited to iron, phosphorus, and others.
{"title":"Representation of iron aerosol size distributions is critical in evaluating atmospheric soluble iron input to the ocean","authors":"Mingxu Liu, Hitoshi Matsui, Douglas Hamilton, Sagar Rathod, Kara Lamb, Natalie Mahowald","doi":"10.5194/egusphere-2024-1454","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1454","url":null,"abstract":"<strong>Abstract.</strong> Atmospheric aerosol deposition acts as a major source of soluble (bioavailable) iron in open ocean regions where it limits phytoplankton growth and primary production. The aerosol size distribution of emitted iron particles, along with particle growth from mixing with other atmospheric components, is an important modulator of its long-range transport potential. There currently exists a large uncertainty in the particle size distribution of iron aerosol, and the role of aerosol size in shaping global soluble iron deposition is thus unclear. In this study, we couple a sophisticated microphysical, size-resolved aerosol model with an iron-speciated and -processing module to disentangle the impact of iron emission size distributions on soluble iron input to the ocean, with a focus on anthropogenic combustion and metal smelting sources. We first evaluate our model results against a global-scale flight measurement dataset for anthropogenic iron concentration and find that the different representations of iron size distribution at emission, as adopted in previous studies, introduces a variability in modeled iron concentrations over remote oceans of a factor of 10. Shifting the iron aerosol size distribution toward finer particle sizes (<1 μm) enables longer atmospheric lifetime (a doubling), promoting atmospheric processing that enhances the soluble iron deposition to ocean basins by up to 50 % on an annual basis. Importantly, the monthly enhancements reach 110 % and 80 % over the Southern Ocean and North Pacific Ocean, respectively. Compared with emission flux uncertainties, we find that iron emission size distribution plays an equally important role in regulating soluble iron deposition, especially to the remote oceans. Our findings provide implications for understanding the effects of atmospheric nutrients input on marine biogeochemistry, including but not limited to iron, phosphorus, and others.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"1 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.5194/egusphere-2024-1715
Namrata Shanmukh Panji, Deborah F. McGlynn, Laura E. R. Barry, Todd M. Scanlon, Manuel T. Lerdau, Sally E. Pusede, Gabriel Isaacman-VanWertz
Abstract. Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated BVOC measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA for the 2020 year with emissions estimated by MEGANv3.2. The emissions were subjected to oxidation in a 0-D box-model (F0AM v4.3) to generate timeseries of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability of regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using LDF=0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions-chemistry model constrained by regional concentrations of NOx and O3.
{"title":"Constraining Light Dependency in Modeled Emissions Through Comparison to Observed BVOC Concentrations in a Southeastern US Forest","authors":"Namrata Shanmukh Panji, Deborah F. McGlynn, Laura E. R. Barry, Todd M. Scanlon, Manuel T. Lerdau, Sally E. Pusede, Gabriel Isaacman-VanWertz","doi":"10.5194/egusphere-2024-1715","DOIUrl":"https://doi.org/10.5194/egusphere-2024-1715","url":null,"abstract":"<strong>Abstract.</strong> Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated BVOC measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA for the 2020 year with emissions estimated by MEGANv3.2. The emissions were subjected to oxidation in a 0-D box-model (F0AM v4.3) to generate timeseries of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability of regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDF<sub>α-pinene</sub>=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using LDF=0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions-chemistry model constrained by regional concentrations of NO<sub>x</sub> and O<sub>3</sub>.","PeriodicalId":8611,"journal":{"name":"Atmospheric Chemistry and Physics","volume":"23 1","pages":""},"PeriodicalIF":6.3,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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