Articles | Volume 18, issue 24
https://doi.org/10.5194/bg-18-6579-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-6579-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Extreme events driving year-to-year differences in gross primary productivity across the US
Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
Philipp Köhler
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91226, USA
Troy S. Magney
Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA
Christian Frankenberg
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91226, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Inez Fung
Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, CA 94720, USA
Ronald C. Cohen
Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, CA 94720, USA
College of Chemistry, University of California, Berkeley, Berkeley, CA 94720, USA
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Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yu Yan Cui, Dien Wu, Alex Turner, and Marc Fischer
Atmos. Chem. Phys., 25, 8475–8492, https://doi.org/10.5194/acp-25-8475-2025, https://doi.org/10.5194/acp-25-8475-2025, 2025
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Satellites, such as NASA's Orbiting Carbon Observatory-2 and -3 (OCO-2 and OCO-3, respectively), retrieve carbon dioxide (CO2) concentrations, which provide vital information for estimating surface CO2 emissions. Here, we investigate the ability of OCO-2/3 retrievals to constrain CO2 emissions for the state of California for the major emission sectors (i.e., fossil fuels, net ecosystem exchange, and wildfire).
Nikhil Dadheech and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3441, https://doi.org/10.5194/egusphere-2025-3441, 2025
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We developed a generalized emulator of atmospheric transport (FootNet v3) trained over the United States, enabling the emulation of both surface & column-averaged footprints at kilometer-scale resolution. We demonstrate that FootNet v3 generalizes to previously unseen regions and meteorological conditions, enabling accurate out-of-sample simulation of atmospheric transport. Flux inversion case studies show that FootNet matches or exceeds the performance of full-physics models in unseen regions.
Eric John Mei, Gregory J. Hakim, Max Taniguchi-King, Dominik Stiller, and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3258, https://doi.org/10.5194/egusphere-2025-3258, 2025
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Chemistry-climate models are used to investigate how physical climate influences the composition of the atmosphere but are slow and expensive to run. We train a linear inverse model that can replicate the behavior of chemistry-climate models at low computational cost. It captures how large-scale climate features like El Niño affect atmospheric composition and can make accurate forecasts up to a year ahead. This model enables fast hypothesis testing and estimates of past atmospheric composition.
Nikhil Dadheech, Tai-Long He, and Alexander J. Turner
Atmos. Chem. Phys., 25, 5159–5174, https://doi.org/10.5194/acp-25-5159-2025, https://doi.org/10.5194/acp-25-5159-2025, 2025
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We developed an efficient GHG (greenhouse gas) flux inversion framework using a machine-learning emulator (FootNet) as a surrogate for an atmospheric transport model, resulting in a 650 × speedup. Paradoxically, the flux inversion using the ML (machine-learning) model outperforms the full-physics model in our case study. We attribute this to the ML model mitigating transport errors in the GHG flux inversion.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Johannes Gensheimer, Alexander J. Turner, Philipp Köhler, Christian Frankenberg, and Jia Chen
Biogeosciences, 19, 1777–1793, https://doi.org/10.5194/bg-19-1777-2022, https://doi.org/10.5194/bg-19-1777-2022, 2022
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We develop a convolutional neural network, named SIFnet, that increases the spatial resolution of SIF from TROPOMI by a factor of 10 to a spatial resolution of 0.005°. SIFnet utilizes coarse SIF observations, together with a broad range of high-resolution auxiliary data. The insights gained from interpretable machine learning techniques allow us to make quantitative claims about the relationships between SIF and other common parameters related to photosynthesis.
Helen L. Fitzmaurice, Alexander J. Turner, Jinsol Kim, Katherine Chan, Erin R. Delaria, Catherine Newman, Paul Wooldridge, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 3891–3900, https://doi.org/10.5194/acp-22-3891-2022, https://doi.org/10.5194/acp-22-3891-2022, 2022
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On-road emissions are thought to vary widely from existing predictions, as the effects of the age of the vehicle fleet, the performance of emission control systems, and variations in speed are difficult to assess under ambient driving conditions. We present an observational approach to characterize on-road emissions and show that the method is consistent with other approaches to within ~ 3 %.
Tea Thum, Javier Pacheco-Labrador, Mika Aurela, Alan Barr, Marika Honkanen, Bruce Johnson, Hannakaisa Lindqvist, Troy Magney, Mirco Migliavacca, Zoe Amie Pierrat, Tristan Quaife, Jochen Stutz, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2025-4432, https://doi.org/10.5194/egusphere-2025-4432, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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Solar-induced chlorophyll fluorescence (SIF) is an optical signal emitted by plants, connected to the biochemical status of the plants. Therefore it helps to unveil what happens inside plants and since it can be observed with remote sensing, it provides a global view of plant activity. We included SIF module in a terrestrial biosphere model and examined how to best describe movement of the SIF signal in the forest. Our work will help to model SIF in boreal coniferous forests.
Jiaqi Shen, Ronald C. Cohen, Glenn M. Wolfe, and Xiaomeng Jin
Atmos. Chem. Phys., 25, 8701–8718, https://doi.org/10.5194/acp-25-8701-2025, https://doi.org/10.5194/acp-25-8701-2025, 2025
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This study shows large chemical and radiative effects of smoke aerosols from fires on near-surface ozone production. Aerosol loading and NOx levels are identified as the primary factors influencing these effects. Furthermore, we show that the ratio of surface PM2.5 to NO2 tropospheric column can be used as an indicator for identifying aerosol-dominated regimes, facilitating the assessment of aerosol impacts on ozone formation through satellite observations.
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yu Yan Cui, Dien Wu, Alex Turner, and Marc Fischer
Atmos. Chem. Phys., 25, 8475–8492, https://doi.org/10.5194/acp-25-8475-2025, https://doi.org/10.5194/acp-25-8475-2025, 2025
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Satellites, such as NASA's Orbiting Carbon Observatory-2 and -3 (OCO-2 and OCO-3, respectively), retrieve carbon dioxide (CO2) concentrations, which provide vital information for estimating surface CO2 emissions. Here, we investigate the ability of OCO-2/3 retrievals to constrain CO2 emissions for the state of California for the major emission sectors (i.e., fossil fuels, net ecosystem exchange, and wildfire).
Nikhil Dadheech and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3441, https://doi.org/10.5194/egusphere-2025-3441, 2025
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We developed a generalized emulator of atmospheric transport (FootNet v3) trained over the United States, enabling the emulation of both surface & column-averaged footprints at kilometer-scale resolution. We demonstrate that FootNet v3 generalizes to previously unseen regions and meteorological conditions, enabling accurate out-of-sample simulation of atmospheric transport. Flux inversion case studies show that FootNet matches or exceeds the performance of full-physics models in unseen regions.
Eric John Mei, Gregory J. Hakim, Max Taniguchi-King, Dominik Stiller, and Alexander J. Turner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3258, https://doi.org/10.5194/egusphere-2025-3258, 2025
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Chemistry-climate models are used to investigate how physical climate influences the composition of the atmosphere but are slow and expensive to run. We train a linear inverse model that can replicate the behavior of chemistry-climate models at low computational cost. It captures how large-scale climate features like El Niño affect atmospheric composition and can make accurate forecasts up to a year ahead. This model enables fast hypothesis testing and estimates of past atmospheric composition.
Nikhil Dadheech, Tai-Long He, and Alexander J. Turner
Atmos. Chem. Phys., 25, 5159–5174, https://doi.org/10.5194/acp-25-5159-2025, https://doi.org/10.5194/acp-25-5159-2025, 2025
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We developed an efficient GHG (greenhouse gas) flux inversion framework using a machine-learning emulator (FootNet) as a surrogate for an atmospheric transport model, resulting in a 650 × speedup. Paradoxically, the flux inversion using the ML (machine-learning) model outperforms the full-physics model in our case study. We attribute this to the ML model mitigating transport errors in the GHG flux inversion.
Julien Lamour, Shawn P. Serbin, Alistair Rogers, Kelvin T. Acebron, Elizabeth Ainsworth, Loren P. Albert, Michael Alonzo, Jeremiah Anderson, Owen K. Atkin, Nicolas Barbier, Mallory L. Barnes, Carl J. Bernacchi, Ninon Besson, Angela C. Burnett, Joshua S. Caplan, Jérôme Chave, Alexander W. Cheesman, Ilona Clocher, Onoriode Coast, Sabrina Coste, Holly Croft, Boya Cui, Clément Dauvissat, Kenneth J. Davidson, Christopher Doughty, Kim S. Ely, Jean-Baptiste Féret, Iolanda Filella, Claire Fortunel, Peng Fu, Maquelle Garcia, Bruno O. Gimenez, Kaiyu Guan, Zhengfei Guo, David Heckmann, Patrick Heuret, Marney Isaac, Shan Kothari, Etsushi Kumagai, Thu Ya Kyaw, Liangyun Liu, Lingli Liu, Shuwen Liu, Joan Llusià, Troy Magney, Isabelle Maréchaux, Adam R. Martin, Katherine Meacham-Hensold, Christopher M. Montes, Romà Ogaya, Joy Ojo, Regison Oliveira, Alain Paquette, Josep Peñuelas, Antonia Debora Placido, Juan M. Posada, Xiaojin Qian, Heidi J. Renninger, Milagros Rodriguez-Caton, Andrés Rojas-González, Urte Schlüter, Giacomo Sellan, Courtney M. Siegert, Guangqin Song, Charles D. Southwick, Daisy C. Souza, Clément Stahl, Yanjun Su, Leeladarshini Sujeeun, To-Chia Ting, Vicente Vasquez, Amrutha Vijayakumar, Marcelo Vilas-Boas, Diane R. Wang, Sheng Wang, Han Wang, Jing Wang, Xin Wang, Andreas P. M. Weber, Christopher Y. S. Wong, Jin Wu, Fengqi Wu, Shengbiao Wu, Zhengbing Yan, Dedi Yang, and Yingyi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-213, https://doi.org/10.5194/essd-2025-213, 2025
Revised manuscript under review for ESSD
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We present the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. This repository provides a unique source of information for creating hyperspectral models for predicting photosynthetic traits and associated leaf traits in terrestrial plants.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Deepangsu Chatterjee, Randall V. Martin, Chi Li, Dandan Zhang, Haihui Zhu, Daven K. Henze, James H. Crawford, Ronald C. Cohen, Lok N. Lamsal, and Alexander M. Cede
Atmos. Chem. Phys., 24, 12687–12706, https://doi.org/10.5194/acp-24-12687-2024, https://doi.org/10.5194/acp-24-12687-2024, 2024
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We investigate the hourly variation of NO2 columns and surface concentrations by applying the GEOS-Chem model to interpret aircraft and ground-based measurements over the US and Pandora sun photometer measurements over the US, Europe, and Asia. Corrections to the Pandora columns and finer model resolution improve the modeled representation of the summertime hourly variation of total NO2 columns to explain the weaker hourly variation in NO2 columns than at the surface.
Benjamin A. Nault, Katherine R. Travis, James H. Crawford, Donald R. Blake, Pedro Campuzano-Jost, Ronald C. Cohen, Joshua P. DiGangi, Glenn S. Diskin, Samuel R. Hall, L. Gregory Huey, Jose L. Jimenez, Kyung-Eun Min, Young Ro Lee, Isobel J. Simpson, Kirk Ullmann, and Armin Wisthaler
Atmos. Chem. Phys., 24, 9573–9595, https://doi.org/10.5194/acp-24-9573-2024, https://doi.org/10.5194/acp-24-9573-2024, 2024
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Ozone (O3) is a pollutant formed from the reactions of gases emitted from various sources. In urban areas, the density of human activities can increase the O3 formation rate (P(O3)), thus impacting air quality and health. Observations collected over Seoul, South Korea, are used to constrain P(O3). A high local P(O3) was found; however, local P(O3) was partly reduced due to compounds typically ignored. These observations also provide constraints for unmeasured compounds that will impact P(O3).
Katherine R. Travis, Benjamin A. Nault, James H. Crawford, Kelvin H. Bates, Donald R. Blake, Ronald C. Cohen, Alan Fried, Samuel R. Hall, L. Gregory Huey, Young Ro Lee, Simone Meinardi, Kyung-Eun Min, Isobel J. Simpson, and Kirk Ullman
Atmos. Chem. Phys., 24, 9555–9572, https://doi.org/10.5194/acp-24-9555-2024, https://doi.org/10.5194/acp-24-9555-2024, 2024
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Human activities result in the emission of volatile organic compounds (VOCs) that contribute to air pollution. Detailed VOC measurements were taken during a field study in South Korea. When compared to VOC inventories, large discrepancies showed underestimates from chemical products, liquefied petroleum gas, and long-range transport. Improved emissions and chemistry of these VOCs better described urban pollution. The new chemical scheme is relevant to urban areas and other VOC sources.
Yitong Yao, Philippe Ciais, Emilie Joetzjer, Wei Li, Lei Zhu, Yujie Wang, Christian Frankenberg, and Nicolas Viovy
Earth Syst. Dynam., 15, 763–778, https://doi.org/10.5194/esd-15-763-2024, https://doi.org/10.5194/esd-15-763-2024, 2024
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Elevated CO2 concentration (eCO2) is critical for shaping the future path of forest carbon uptake, while uncertainties remain about concurrent carbon loss. Here, we found that eCO2 might amplify competition-induced carbon loss, while the extent of drought-induced carbon loss hinges on the balance between heightened biomass density and water-saving benefits. This is the first time that such carbon loss responses to ongoing climate change have been quantified separately over the Amazon rainforest.
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Qindan Zhu, Rebecca H. Schwantes, Matthew Coggon, Colin Harkins, Jordan Schnell, Jian He, Havala O. T. Pye, Meng Li, Barry Baker, Zachary Moon, Ravan Ahmadov, Eva Y. Pfannerstill, Bryan Place, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Carsten Warneke, Chelsea E. Stockwell, Lu Xu, Kristen Zuraski, Michael A. Robinson, J. Andrew Neuman, Patrick R. Veres, Jeff Peischl, Steven S. Brown, Allen H. Goldstein, Ronald C. Cohen, and Brian C. McDonald
Atmos. Chem. Phys., 24, 5265–5286, https://doi.org/10.5194/acp-24-5265-2024, https://doi.org/10.5194/acp-24-5265-2024, 2024
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Volatile organic compounds (VOCs) fuel the production of air pollutants like ozone and particulate matter. The representation of VOC chemistry remains challenging due to its complexity in speciation and reactions. Here, we develop a chemical mechanism, RACM2B-VCP, that better represents VOC chemistry in urban areas such as Los Angeles. We also discuss the contribution of VOCs emitted from volatile chemical products and other anthropogenic sources to total VOC reactivity and O3.
Russell Doughty, Yujie Wang, Jennifer Johnson, Nicholas Parazoo, Troy Magney, Zoe Pierrat, Xiangming Xiao, Luis Guanter, Philipp Köhler, Christian Frankenberg, Peter Somkuti, Shuang Ma, Yuanwei Qin, Sean Crowell, and Berrien Moore III
EGUsphere, https://doi.org/10.22541/essoar.168167172.20799710/v1, https://doi.org/10.22541/essoar.168167172.20799710/v1, 2024
Preprint archived
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Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation absorbed by chlorophyll. Potential uses of our model are to advance our understanding of the timing and magnitude of photosynthesis, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Milan Y. Patel, Pietro F. Vannucci, Jinsol Kim, William M. Berelson, and Ronald C. Cohen
Atmos. Meas. Tech., 17, 1051–1060, https://doi.org/10.5194/amt-17-1051-2024, https://doi.org/10.5194/amt-17-1051-2024, 2024
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Low-cost particulate matter (PM) sensors are becoming increasingly common in community monitoring and atmospheric research, but these sensors require proper calibration to provide accurate reporting. Here, we propose a hygroscopic growth calibration scheme that evolves in time to account for seasonal changes in hygroscopic growth. In San Francisco and Los Angeles, CA, applying a seasonal hygroscopic growth calibration can account for sensor biases driven by the seasonal cycles in PM composition.
Clara M. Nussbaumer, Bryan K. Place, Qindan Zhu, Eva Y. Pfannerstill, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Ryan Ward, Anthony Bucholtz, John H. Seinfeld, Allen H. Goldstein, and Ronald C. Cohen
Atmos. Chem. Phys., 23, 13015–13028, https://doi.org/10.5194/acp-23-13015-2023, https://doi.org/10.5194/acp-23-13015-2023, 2023
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NOx is a precursor to hazardous tropospheric ozone and can be emitted from various anthropogenic sources. It is important to quantify NOx emissions in urban environments to improve the local air quality, which still remains a challenge, as sources are heterogeneous in space and time. In this study, we calculate NOx emissions over Los Angeles, based on aircraft measurements in June 2021, and compare them to a local emission inventory, which we find mostly overpredicts the measured values.
Eva Y. Pfannerstill, Caleb Arata, Qindan Zhu, Benjamin C. Schulze, Roy Woods, John H. Seinfeld, Anthony Bucholtz, Ronald C. Cohen, and Allen H. Goldstein
Atmos. Chem. Phys., 23, 12753–12780, https://doi.org/10.5194/acp-23-12753-2023, https://doi.org/10.5194/acp-23-12753-2023, 2023
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The San Joaquin Valley is an agricultural area with poor air quality. Organic gases drive the formation of hazardous air pollutants. Agricultural emissions of these gases are not well understood and have rarely been quantified at landscape scale. By combining aircraft-based emission measurements with land cover information, we found mis- or unrepresented emission sources. Our results help in understanding of pollution sources and in improving predictions of air quality in agricultural regions.
Qindan Zhu, Bryan Place, Eva Y. Pfannerstill, Sha Tong, Huanxin Zhang, Jun Wang, Clara M. Nussbaumer, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Allen H. Goldstein, and Ronald C. Cohen
Atmos. Chem. Phys., 23, 9669–9683, https://doi.org/10.5194/acp-23-9669-2023, https://doi.org/10.5194/acp-23-9669-2023, 2023
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Nitrogen oxide (NOx) is a hazardous air pollutant, and it is the precursor of short-lived climate forcers like tropospheric ozone and aerosol particles. While NOx emissions from transportation has been strictly regulated, soil NOx emissions are overlooked. We use the airborne flux measurements to observe NOx emissions from highways and urban and cultivated soil land cover types. We show non-negligible soil NOx emissions, which are significantly underestimated in current model simulations.
Vincent Humphrey and Christian Frankenberg
Biogeosciences, 20, 1789–1811, https://doi.org/10.5194/bg-20-1789-2023, https://doi.org/10.5194/bg-20-1789-2023, 2023
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Microwave satellites can be used to monitor how vegetation biomass changes over time or how droughts affect the world's forests. However, such satellite data are still difficult to validate and interpret because of a lack of comparable field observations. Here, we present a remote sensing technique that uses the Global Navigation Satellite System (GNSS) as a makeshift radar, making it possible to observe canopy transmissivity at any existing environmental research site in a cost-efficient way.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
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We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
Chi Li, Randall V. Martin, Ronald C. Cohen, Liam Bindle, Dandan Zhang, Deepangsu Chatterjee, Hongjian Weng, and Jintai Lin
Atmos. Chem. Phys., 23, 3031–3049, https://doi.org/10.5194/acp-23-3031-2023, https://doi.org/10.5194/acp-23-3031-2023, 2023
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Models are essential to diagnose the significant effects of nitrogen oxides (NOx) on air pollution. We use an air quality model to illustrate the variability of NOx resolution-dependent simulation biases; how these biases depend on specific chemical environments, driving mechanisms, and vertical variabilities; and how these biases affect the interpretation of satellite observations. High-resolution simulations are thus critical to accurately interpret NOx and its relevance to air quality.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
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We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Viral Shah, Daniel J. Jacob, Ruijun Dang, Lok N. Lamsal, Sarah A. Strode, Stephen D. Steenrod, K. Folkert Boersma, Sebastian D. Eastham, Thibaud M. Fritz, Chelsea Thompson, Jeff Peischl, Ilann Bourgeois, Ilana B. Pollack, Benjamin A. Nault, Ronald C. Cohen, Pedro Campuzano-Jost, Jose L. Jimenez, Simone T. Andersen, Lucy J. Carpenter, Tomás Sherwen, and Mat J. Evans
Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023, https://doi.org/10.5194/acp-23-1227-2023, 2023
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NOx in the free troposphere (above 2 km) affects global tropospheric chemistry and the retrieval and interpretation of satellite NO2 measurements. We evaluate free tropospheric NOx in global atmospheric chemistry models and find that recycling NOx from its reservoirs over the oceans is faster than that simulated in the models, resulting in increases in simulated tropospheric ozone and OH. Over the U.S., free tropospheric NO2 contributes the majority of the tropospheric NO2 column in summer.
Helen L. Fitzmaurice and Ronald C. Cohen
Atmos. Chem. Phys., 22, 15403–15411, https://doi.org/10.5194/acp-22-15403-2022, https://doi.org/10.5194/acp-22-15403-2022, 2022
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We develop a novel method for finding heavy-duty vehicle (HDV) emission factors (g PM kg fuel) using regulatory sensor networks and publicly available traffic data. We find that particulate matter emission factors have decreased by a factor of ~ 9 in the past decade in the San Francisco Bay area. Because of the wide availability of similar data sets across the USA and globally, this method could be applied to other settings to understand long-term trends and regional differences in HDV emissions.
Yujie Wang and Christian Frankenberg
Biogeosciences, 19, 4705–4714, https://doi.org/10.5194/bg-19-4705-2022, https://doi.org/10.5194/bg-19-4705-2022, 2022
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Plant hydraulics is often misrepresented in topical research. We highlight the commonly seen ambiguities and/or mistakes, with equations and figures to help visualize the potential biases. We recommend careful thinking when using or modifying existing plant hydraulic terms, methods, and models.
Yujie Wang and Christian Frankenberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-172, https://doi.org/10.5194/bg-2022-172, 2022
Revised manuscript not accepted
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Leaf light absorption coefficient is often not measured along with leaf gas exchange, but assumed to be constant. This potentially causes biases in estimated photosynthetic capacity and modeled photosynthetic rates. We explored how leaf light absorption features and light source may impact the photosynthesis modeling, and found that the biases are dependent of model assumptions. Researchers need to be more cautious with these inaccurate assumptions in photosynthesis models.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Russell Doughty, Thomas P. Kurosu, Nicholas Parazoo, Philipp Köhler, Yujie Wang, Ying Sun, and Christian Frankenberg
Earth Syst. Sci. Data, 14, 1513–1529, https://doi.org/10.5194/essd-14-1513-2022, https://doi.org/10.5194/essd-14-1513-2022, 2022
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We describe and compare solar-induced chlorophyll fluorescence data produced by NASA from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 platforms.
Glenn M. Wolfe, Thomas F. Hanisco, Heather L. Arkinson, Donald R. Blake, Armin Wisthaler, Tomas Mikoviny, Thomas B. Ryerson, Ilana Pollack, Jeff Peischl, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Alex Teng, L. Gregory Huey, Xiaoxi Liu, Alan Fried, Petter Weibring, Dirk Richter, James Walega, Samuel R. Hall, Kirk Ullmann, Jose L. Jimenez, Pedro Campuzano-Jost, T. Paul Bui, Glenn Diskin, James R. Podolske, Glen Sachse, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 4253–4275, https://doi.org/10.5194/acp-22-4253-2022, https://doi.org/10.5194/acp-22-4253-2022, 2022
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Smoke plumes are chemically complex. This work combines airborne observations of smoke plume composition with a photochemical model to probe the production of ozone and the fate of reactive gases in the outflow of a large wildfire. Model–measurement comparisons illustrate how uncertain emissions and chemical processes propagate into simulated chemical evolution. Results provide insight into how this system responds to perturbations, which can help guide future observation and modeling efforts.
Johannes Gensheimer, Alexander J. Turner, Philipp Köhler, Christian Frankenberg, and Jia Chen
Biogeosciences, 19, 1777–1793, https://doi.org/10.5194/bg-19-1777-2022, https://doi.org/10.5194/bg-19-1777-2022, 2022
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We develop a convolutional neural network, named SIFnet, that increases the spatial resolution of SIF from TROPOMI by a factor of 10 to a spatial resolution of 0.005°. SIFnet utilizes coarse SIF observations, together with a broad range of high-resolution auxiliary data. The insights gained from interpretable machine learning techniques allow us to make quantitative claims about the relationships between SIF and other common parameters related to photosynthesis.
Helen L. Fitzmaurice, Alexander J. Turner, Jinsol Kim, Katherine Chan, Erin R. Delaria, Catherine Newman, Paul Wooldridge, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 3891–3900, https://doi.org/10.5194/acp-22-3891-2022, https://doi.org/10.5194/acp-22-3891-2022, 2022
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On-road emissions are thought to vary widely from existing predictions, as the effects of the age of the vehicle fleet, the performance of emission control systems, and variations in speed are difficult to assess under ambient driving conditions. We present an observational approach to characterize on-road emissions and show that the method is consistent with other approaches to within ~ 3 %.
Douglas A. Day, Pedro Campuzano-Jost, Benjamin A. Nault, Brett B. Palm, Weiwei Hu, Hongyu Guo, Paul J. Wooldridge, Ronald C. Cohen, Kenneth S. Docherty, J. Alex Huffman, Suzane S. de Sá, Scot T. Martin, and Jose L. Jimenez
Atmos. Meas. Tech., 15, 459–483, https://doi.org/10.5194/amt-15-459-2022, https://doi.org/10.5194/amt-15-459-2022, 2022
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Particle-phase nitrates are an important component of atmospheric aerosols and chemistry. In this paper, we systematically explore the application of aerosol mass spectrometry (AMS) to quantify the organic and inorganic nitrate fractions of aerosols in the atmosphere. While AMS has been used for a decade to quantify nitrates, methods are not standardized. We make recommendations for a more universal approach based on this analysis of a large range of field and laboratory observations.
Yujie Wang and Christian Frankenberg
Biogeosciences, 19, 29–45, https://doi.org/10.5194/bg-19-29-2022, https://doi.org/10.5194/bg-19-29-2022, 2022
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Modeling vegetation canopy is important in predicting whether the land remains a carbon sink to mitigate climate change in the near future. Vegetation canopy model complexity, however, impacts the model-predicted carbon and water fluxes as well as canopy fluorescence, even if the same suite of model inputs is used. Given the biases caused by canopy model complexity, we recommend not misusing parameters inverted using different models or assumptions.
Siraput Jongaramrungruang, Georgios Matheou, Andrew K. Thorpe, Zhao-Cheng Zeng, and Christian Frankenberg
Atmos. Meas. Tech., 14, 7999–8017, https://doi.org/10.5194/amt-14-7999-2021, https://doi.org/10.5194/amt-14-7999-2021, 2021
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This study shows how precision error and bias in column methane retrieval change with different instrument specifications and the impact of spectrally complex surface albedos on retrievals. We show how surface interferences can be mitigated with an optimal spectral resolution and a higher polynomial degree in a retrieval process. The findings can inform future satellite instrument designs to have robust observations capable of separating real CH4 plume enhancements from surface interferences.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
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Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Yujie Wang, Philipp Köhler, Liyin He, Russell Doughty, Renato K. Braghiere, Jeffrey D. Wood, and Christian Frankenberg
Geosci. Model Dev., 14, 6741–6763, https://doi.org/10.5194/gmd-14-6741-2021, https://doi.org/10.5194/gmd-14-6741-2021, 2021
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We present the first step in testing a new land model as part of a new Earth system model. Our model links plant hydraulics, stomatal optimization theory, and a comprehensive canopy radiation scheme. We compared model-predicted carbon and water fluxes to flux tower observations and model-predicted sun-induced chlorophyll fluorescence to satellite retrievals. Our model quantitatively predicted the carbon and water fluxes as well as the canopy fluorescence yield.
Xiaomeng Jin, Qindan Zhu, and Ronald C. Cohen
Atmos. Chem. Phys., 21, 15569–15587, https://doi.org/10.5194/acp-21-15569-2021, https://doi.org/10.5194/acp-21-15569-2021, 2021
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We describe direct estimates of NOx emissions and lifetimes for biomass burning plumes using daily TROPOMI retrievals of NO2. Satellite-derived NOx emission factors are consistent with those from in situ measurements. We observe decreasing NOx lifetime with fire intensity, which is due to the increase in NOx abundance and radical production. Our findings suggest promise for applying space-based observations to track the emissions and chemical evolution of reactive nitrogen from wildfires.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Erin R. Delaria, Jinsol Kim, Helen L. Fitzmaurice, Catherine Newman, Paul J. Wooldridge, Kevin Worthington, and Ronald C. Cohen
Atmos. Meas. Tech., 14, 5487–5500, https://doi.org/10.5194/amt-14-5487-2021, https://doi.org/10.5194/amt-14-5487-2021, 2021
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The use of a dense network of low-cost CO2 sensors is an attractive option for measuring CO2 emissions in cities. However, these low-cost sensors are also subject to uncertainties. Here, we describe a novel method of field calibration for correcting temperature-related errors in the CO2 sensors deployed in the BEACO2N network. We show that with this temperature correction, we can achieve a sufficiently low network error to allow for the evaluation of CO2 emissions at a neighborhood scale.
Xueling Liu, Arthur P. Mizzi, Jeffrey L. Anderson, Inez Fung, and Ronald C. Cohen
Atmos. Chem. Phys., 21, 9573–9583, https://doi.org/10.5194/acp-21-9573-2021, https://doi.org/10.5194/acp-21-9573-2021, 2021
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Observations of winds in the planetary boundary layer remain sparse, making it challenging to simulate and predict the atmospheric conditions that are most important for describing and predicting urban air quality. Here we investigate the application of data assimilation of NO2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.
Jakob Borchardt, Konstantin Gerilowski, Sven Krautwurst, Heinrich Bovensmann, Andrew K. Thorpe, David R. Thompson, Christian Frankenberg, Charles E. Miller, Riley M. Duren, and John Philip Burrows
Atmos. Meas. Tech., 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, https://doi.org/10.5194/amt-14-1267-2021, 2021
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The AVIRIS-NG hyperspectral imager has been used successfully to identify and quantify anthropogenic methane sources utilizing different retrieval and inversion methods. Here, we examine the adaption and application of the WFM-DOAS algorithm to AVIRIS-NG measurements to retrieve local methane column enhancements, compare the results with other retrievals, and quantify the uncertainties resulting from the retrieval method. Additionally, we estimate emissions from five detected methane plumes.
Erin R. Delaria, Bryan K. Place, Amy X. Liu, and Ronald C. Cohen
Atmos. Chem. Phys., 20, 14023–14041, https://doi.org/10.5194/acp-20-14023-2020, https://doi.org/10.5194/acp-20-14023-2020, 2020
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Observations of NO2 deposition to vegetation have been widely reported, but the magnitude and mechanism remain uncertain. We use laboratory measurements to study NO2 deposition to leaves of 10 native California tree species. We report important differences in the uptake rates between species and find that this process is primarily diffusion-regulated. We suggest that processes within leaves at a cellular level represent a negligible limitation to NO2 deposition at the canopy level.
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Short summary
This work builds a high-resolution estimate (500 m) of gross primary productivity (GPP) over the US using satellite measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) between 2018 and 2020. We identify ecosystem-specific scaling factors for estimating gross primary productivity (GPP) from TROPOMI SIF. Extreme precipitation events drive four regional GPP anomalies that account for 28 % of year-to-year GPP differences across the US.
This work builds a high-resolution estimate (500 m) of gross primary productivity (GPP) over the...
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