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Li J, Zhang X, Guo L, Zhong J, Wang D, Wu C, Li F, Li M. Invert global and China's terrestrial carbon fluxes over 2019-2021 based on assimilating richer atmospheric CO 2 observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 929:172320. [PMID: 38614352 DOI: 10.1016/j.scitotenv.2024.172320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 04/03/2024] [Accepted: 04/06/2024] [Indexed: 04/15/2024]
Abstract
With China's commitment to reach carbon peak by 2030 and achieve carbon neutrality by 2060, it is particularly important to obtain terrestrial ecosystem carbon fluxes with low uncertainty both globally and in China. The use of more observation data may help reduce the uncertainty of inverting carbon fluxes. This study uses the observation data from global stations, background stations and provincial stations in China, as well as the OCO-2 satellite, and uses the China Carbon Monitoring, Verification and Supporting System for Global (CCMVS-G) to estimate the carbon fluxes of global and Chinese terrestrial ecosystems from 2019 to 2021. The results revealed that the global terrestrial ecosystem carbon sink was approximately -3.40 Pg C/yr from 2019 to 2021. The carbon sinks in the Northern Hemisphere are large, especially in Asia, North America, and Europe. From 2019 to 2021, the carbon sink of China's terrestrial ecosystem was approximately -0.44 Pg C/yr. Carbon sinks exhibit significant seasonal and interannual variations in China. After assimilating the observation data, the uncertainty of the posterior flux is smaller than that of the prior flux, a more reasonable distribution of carbon sources and sinks can be obtained, and more accurate boundary conditions can be provided for the China Carbon Monitoring, Verification and Supporting System for Regional (CCMVS-R). In the future, it is important to establish a well-designed CO2 ground-based observation network.
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Affiliation(s)
- Jiaying Li
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Xiaoye Zhang
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Joint Laboratory of Climate Change Mitigation and Carbon Neutrality of Henan Univ. & CAMS, Henan 475001, China.
| | - Lifeng Guo
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Joint Laboratory of Climate Change Mitigation and Carbon Neutrality of Henan Univ. & CAMS, Henan 475001, China.
| | - Junting Zhong
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Joint Laboratory of Climate Change Mitigation and Carbon Neutrality of Henan Univ. & CAMS, Henan 475001, China.
| | - Deying Wang
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Joint Laboratory of Climate Change Mitigation and Carbon Neutrality of Henan Univ. & CAMS, Henan 475001, China.
| | - Chongyuan Wu
- Monitoring and Assessment Center for GHGs and Carbon Neutrality, State Key Laboratory of Severe Weather of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Fugang Li
- China Global Atmosphere Watch Baseline Observatory, Xining 810000, China.
| | - Ming Li
- China Global Atmosphere Watch Baseline Observatory, Xining 810000, China.
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2
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Hussain N, Gonsamo A, Wang S, Arain MA. Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data. ECOLOGICAL PROCESSES 2024; 13:37. [PMID: 38756370 PMCID: PMC11093731 DOI: 10.1186/s13717-024-00520-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 04/25/2024] [Indexed: 05/18/2024]
Abstract
Background Deciduous forests in eastern North America experienced a widespread and intense spongy moth (Lymantria dispar) infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon (C) cycle in forests across the Great Lakes region in Canada, utilizing high-resolution (10 × 10 m2) Sentinel-2 satellite remote sensing images and eddy covariance (EC) flux data. Study results showed a significant reduction in leaf area index (LAI) and gross primary productivity (GPP) values in deciduous and mixed forests in the region in 2021. Results Remote sensing derived, growing season mean LAI values of deciduous (mixed) forests were 3.66 (3.18), 2.74 (2.64), and 3.53 (2.94) m2 m-2 in 2020, 2021 and 2022, respectively, indicating about 24 (14)% reduction in LAI, as compared to pre- and post-infestation years. Similarly, growing season GPP values in deciduous (mixed) forests were 1338 (1208), 868 (932), and 1367 (1175) g C m-2, respectively in 2020, 2021 and 2022, showing about 35 (22)% reduction in GPP in 2021 as compared to pre- and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area (178,000 km2), resulted in 21.1 (21.4) Mt of C loss as compared to 2020 (2022), respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes region. Conclusions The methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions.
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Affiliation(s)
- Nur Hussain
- School of Earth, Environment and Society and McMaster Centre for Climate Change, McMaster University, Hamilton, ON L8S 4K1 Canada
| | - Alemu Gonsamo
- School of Earth, Environment and Society and McMaster Centre for Climate Change, McMaster University, Hamilton, ON L8S 4K1 Canada
| | - Shusen Wang
- Canada Centre for Remote Sensing, Natural Resources Canada, 1280 Main Street West, Ottawa, ON Canada
| | - M. Altaf Arain
- School of Earth, Environment and Society and McMaster Centre for Climate Change, McMaster University, Hamilton, ON L8S 4K1 Canada
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3
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Jiao K, Liu Z, Wang W, Yu K, Mcgrath MJ, Xu W. Carbon cycle responses to climate change across China's terrestrial ecosystem: Sensitivity and driving process. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170053. [PMID: 38224891 DOI: 10.1016/j.scitotenv.2024.170053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/19/2023] [Accepted: 01/08/2024] [Indexed: 01/17/2024]
Abstract
Investigations into the carbon cycle and how it responds to climate change at the national scale are important for a comprehensive understanding of terrestrial carbon cycle and global change issues. Contributions of carbon fluxes to the terrestrial sink and the effects on climate change are still not fully understood. In this study, we aimed to explore the relationship between ecosystem production (GPP/SIF/NDVI) and net ecosystem carbon exchange (NEE) and to investigate the sensitivity of carbon fluxes to climate change at different spatio-temporal scales. Furthermore, we sought to delve into the carbon cycle processes driven by climate stress in China since the beginning of the 21st century. To achieve these objectives, we employed correlation and sensitivity analysis techniques, utilizing a wide range of data sources including ground-based observations, remote sensing observations, atmospheric inversions, machine learning, and model simulations. Our findings indicate that NEE in most arid regions of China is primarily driven by ecosystem production. Climate variations have a greater influence on ecosystem production than respiration. Warming has negatively impacted ecosystem production in Northeast China, as well as in subtropical and tropical regions. Conversely, increased precipitation has strengthened the terrestrial carbon sink, particularly in the northern cool and dry areas. We also found that ecosystem respiration exhibits heightened sensitivity to warming in southern China. Moreover, our analysis revealed that the control of terrestrial carbon cycle by ecosystem production gradually weakens from cold/arid areas to warm/humid areas. We identified distinct temperature thresholds (ranging from 10.5 to 13.7 °C) and precipitation thresholds (approximately 1400 mm yr-1) for the transition from production-dominated to respiration-dominated processes. Our study provides valuable insights into the complex relationship between climate change and carbon cycle in China.
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Affiliation(s)
- Kewei Jiao
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China
| | - Zhihua Liu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China.
| | - Wenjuan Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
| | - Kailiang Yu
- High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Matthew Joseph Mcgrath
- Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Wenru Xu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, China; Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China
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4
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Zhang Z, Luo X, Friess DA, Wang S, Li Y, Li Y. Stronger increases but greater variability in global mangrove productivity compared to that of adjacent terrestrial forests. Nat Ecol Evol 2024; 8:239-250. [PMID: 38172286 DOI: 10.1038/s41559-023-02264-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 10/31/2023] [Indexed: 01/05/2024]
Abstract
Mangrove forests are a highly productive ecosystem with important potential to offset anthropogenic greenhouse gas emissions. Mangroves are expected to respond differently to climate change compared to terrestrial forests owing to their location in the tidal environment and unique ecophysiological characteristics, but the magnitude of difference remains uncertain at the global scale. Here we use satellite observations to examine mean trends and interannual variability in the productivity of global mangrove forests and nearby terrestrial evergreen broadleaf forests from 2001 to 2020. Although both types of ecosystem experienced significant recent increases in productivity, mangroves exhibited a stronger increasing trend and greater interannual variability in productivity than evergreen broadleaf forests on three-quarters of their co-occurring coasts. The difference in productivity trends is attributed to the stronger CO2 fertilization effect on mangrove photosynthesis, while the discrepancy in interannual variability is attributed to the higher sensitivities to variations in precipitation and sea level. Our results indicate that mangroves will have a faster increase in productivity than terrestrial forests in a CO2-rich future but may suffer more from deficits in water availability, highlighting a key difference between terrestrial and tidal ecosystems in their responses to climate change.
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Affiliation(s)
- Zhen Zhang
- State Key Laboratory of Marine Environmental Science, Key Laboratory of Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment and Ecology, Xiamen University, Xiamen, China
- Department of Geography, National University of Singapore, Singapore, Singapore
| | - Xiangzhong Luo
- Department of Geography, National University of Singapore, Singapore, Singapore.
- Center for Nature-Based Climate Solutions, National University of Singapore, Singapore, Singapore.
| | - Daniel A Friess
- Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA, USA
| | - Songhan Wang
- Jiangsu Collaborative Innovation Center for Modern Crop Production/Key Laboratory of Crop Physiology and Ecology in Southern China, Nanjing Agricultural University, Nanjing, China
| | - Yi Li
- State Key Laboratory of Marine Environmental Science, Key Laboratory of Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment and Ecology, Xiamen University, Xiamen, China
| | - Yangfan Li
- State Key Laboratory of Marine Environmental Science, Key Laboratory of Coastal and Wetland Ecosystems (Ministry of Education), College of the Environment and Ecology, Xiamen University, Xiamen, China.
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5
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Na R, Rong Z, Wang ZA, Liang S, Liu C, Ringham M, Liang H. Air-sea CO 2 fluxes and cross-shelf exchange of inorganic carbon in the East China Sea from a coupled physical-biogeochemical model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167572. [PMID: 37804969 DOI: 10.1016/j.scitotenv.2023.167572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 09/20/2023] [Accepted: 10/01/2023] [Indexed: 10/09/2023]
Abstract
The East China Sea (ECS) has been reported to be a significant sink of atmospheric CO2, but less is known about horizontal transport of dissolved inorganic carbon (DIC) across the shelf. A coupled physical-biogeochemical model has been implemented for the ECS to simulate the inorganic carbon system and estimate CO2 fluxes and cross-shelf DIC transport in the ECS. A 6-year model hindcast (2013-2018) was performed and assessed. Multiple existing datasets from in-situ observations are used to constrain and validate the model. The model reproduces the spatial and temporal patterns of nitrogen, chlorophyll and CO2 parameters in general agreement with observations. Modeling estimation reveals that the ECS takes up CO2 at an annual mean rate of about 8.20 ± 3.13 mmol m-2 d-1, and experiences substantial seasonal variability. The total annual CO2 uptake in the ECS is about 21.55 Tg C yr-1. Modeling estimation suggests that the biological processes contribute to about 15 % of the shelf CO2 uptake in the ECS, leaving ~80 % of the shelf uptake contributed by other physical-chemical processes, e.g., physical pump and/or solubility pump. The horizontal fluxes of DIC between the ECS and the adjacent ocean are more than two orders of magnitude larger than the air-sea CO2 flux on the ECS and result in a net DIC export of about ~33.8 ± 14.87 Tg C yr-1 from the shelf area. Modeling results suggest that this conveyance of DIC to the open ocean is equivalent to about 70 % of the inorganic carbon inflow from riverine and atmospheric pathways in the annual scale.
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Affiliation(s)
- Rong Na
- College of Oceanic and Atmospheric Sciences, Ocean University of China, 238 Songling Road, Qingdao, China
| | - Zengrui Rong
- College of Oceanic and Atmospheric Sciences, Ocean University of China, 238 Songling Road, Qingdao, China; Frontier Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, 238 Songling Road, Qingdao, China.
| | - Zhaohui Aleck Wang
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Shengkang Liang
- Frontier Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, 238 Songling Road, Qingdao, China; Key Laboratory of Marine Chemistry Theory and Technology, Ocean University of China, 238 Songling Road, Qingdao, China
| | - Chunying Liu
- Frontier Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, 238 Songling Road, Qingdao, China; Key Laboratory of Marine Chemistry Theory and Technology, Ocean University of China, 238 Songling Road, Qingdao, China
| | - Mallory Ringham
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA; Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Haorui Liang
- South China Sea Marine Survey and Technology Center, State Oceanic Administration, Guangzhou, China
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6
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Zhao S, Liu M, Tao M, Zhou W, Lu X, Xiong Y, Li F, Wang Q. The role of satellite remote sensing in mitigating and adapting to global climate change. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166820. [PMID: 37689189 DOI: 10.1016/j.scitotenv.2023.166820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/30/2023] [Accepted: 09/02/2023] [Indexed: 09/11/2023]
Abstract
Climate change has critical adverse impacts on human society and poses severe challenges to global sustainable development. Information on essential climate variables (ECVs) that reflects the substantial changes that have occurred on Earth is critical for assessing the influence of climate change. Satellite remote sensing (SRS) technology has led to a new era of observations and provides multiscale information on ECVs that is independent of in situ measurements and model simulations. This enhances our understanding of climate change from space and supports policy-making in combating climate change. However, it remains challenging to remotely retrieve ECVs due to the complexity of the climate system. We provide an update on the studies on the role of SRS in climate change research, specifically in monitoring and quantifying ECVs in the atmosphere (greenhouse gases, clouds and aerosols), ocean (sea surface temperature, sea ice melt and sea level rise, ocean currents and mesoscale eddies, phytoplankton and ocean productivity), and terrestrial ecosystems (land use and land cover change and carbon flux, water resource and hydrological hazards, solar-induced chlorophyll fluorescence and terrestrial gross primary production). The benefits and challenges of applying SRS in climate change studies are also examined and discussed. This work will help us apply SRS and recommend future SRS studies to mitigate and adapt to global climate change.
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Affiliation(s)
- Shaohua Zhao
- Satellite Environment Center, Ministry of Ecology and Environment/State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, China
| | - Min Liu
- College of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450000, China
| | - Minghui Tao
- School of Geography and Information Engineering, China University of Geosciences, Wuhan 430000, China
| | - Wei Zhou
- Satellite Environment Center, Ministry of Ecology and Environment/State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, China
| | - Xiaoyan Lu
- Guangxi Eco-Environmental Monitoring Centre, Nanning 530028, China
| | - Yujiu Xiong
- School of Civil Engineering, Sun Yat-Sen University, Zhuhai 519082, Guangdong, China; Center of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China.
| | - Feng Li
- School of Civil Engineering, Sun Yat-Sen University, Zhuhai 519082, Guangdong, China
| | - Qiao Wang
- Satellite Environment Center, Ministry of Ecology and Environment/State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, China; Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
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7
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Bansal S, Creed IF, Tangen BA, Bridgham SD, Desai AR, Krauss KW, Neubauer SC, Noe GB, Rosenberry DO, Trettin C, Wickland KP, Allen ST, Arias-Ortiz A, Armitage AR, Baldocchi D, Banerjee K, Bastviken D, Berg P, Bogard MJ, Chow AT, Conner WH, Craft C, Creamer C, DelSontro T, Duberstein JA, Eagle M, Fennessy MS, Finkelstein SA, Göckede M, Grunwald S, Halabisky M, Herbert E, Jahangir MMR, Johnson OF, Jones MC, Kelleway JJ, Knox S, Kroeger KD, Kuehn KA, Lobb D, Loder AL, Ma S, Maher DT, McNicol G, Meier J, Middleton BA, Mills C, Mistry P, Mitra A, Mobilian C, Nahlik AM, Newman S, O’Connell JL, Oikawa P, van der Burg MP, Schutte CA, Song C, Stagg CL, Turner J, Vargas R, Waldrop MP, Wallin MB, Wang ZA, Ward EJ, Willard DA, Yarwood S, Zhu X. Practical Guide to Measuring Wetland Carbon Pools and Fluxes. WETLANDS (WILMINGTON, N.C.) 2023; 43:105. [PMID: 38037553 PMCID: PMC10684704 DOI: 10.1007/s13157-023-01722-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 07/24/2023] [Indexed: 12/02/2023]
Abstract
Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions. Supplementary Information The online version contains supplementary material available at 10.1007/s13157-023-01722-2.
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Affiliation(s)
- Sheel Bansal
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Irena F. Creed
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON Canada
| | - Brian A. Tangen
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Scott D. Bridgham
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR USA
| | - Ankur R. Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI USA
| | - Ken W. Krauss
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Scott C. Neubauer
- Department of Biology, Virginia Commonwealth University, Richmond, VA USA
| | - Gregory B. Noe
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | | | - Carl Trettin
- U.S. Forest Service, Pacific Southwest Research Station, Davis, CA USA
| | - Kimberly P. Wickland
- U.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO USA
| | - Scott T. Allen
- Department of Natural Resources and Environmental Science, University of Nevada, Reno, Reno, NV USA
| | - Ariane Arias-Ortiz
- Ecosystem Science Division, Department of Environmental Science, Policy and Management, University of California, Berkeley, CA USA
| | - Anna R. Armitage
- Department of Marine Biology, Texas A&M University at Galveston, Galveston, TX USA
| | - Dennis Baldocchi
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA USA
| | - Kakoli Banerjee
- Department of Biodiversity and Conservation of Natural Resources, Central University of Odisha, Koraput, Odisha India
| | - David Bastviken
- Department of Thematic Studies – Environmental Change, Linköping University, Linköping, Sweden
| | - Peter Berg
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA USA
| | - Matthew J. Bogard
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB Canada
| | - Alex T. Chow
- Earth and Environmental Sciences Programme, The Chinese University of Hong Kong, Shatin, Hong Kong SAR China
| | - William H. Conner
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, SC USA
| | - Christopher Craft
- O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN USA
| | - Courtney Creamer
- U.S. Geological Survey, Geology, Minerals, Energy and Geophysics Science Center, Menlo Park, CA USA
| | - Tonya DelSontro
- Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON Canada
| | - Jamie A. Duberstein
- Baruch Institute of Coastal Ecology and Forest Science, Clemson University, Georgetown, SC USA
| | - Meagan Eagle
- U.S. Geological Survey, Woods Hole Coastal & Marine Science Center, Woods Hole, MA USA
| | | | | | - Mathias Göckede
- Department for Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Sabine Grunwald
- Soil, Water and Ecosystem Sciences Department, University of Florida, Gainesville, FL USA
| | - Meghan Halabisky
- School of Environmental and Forest Sciences, University of Washington, Seattle, WA USA
| | | | | | - Olivia F. Johnson
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
- Departments of Biology and Environmental Studies, Kent State University, Kent, OH USA
| | - Miriam C. Jones
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | - Jeffrey J. Kelleway
- School of Earth, Atmospheric and Life Sciences and Environmental Futures Research Centre, University of Wollongong, Wollongong, NSW Australia
| | - Sara Knox
- Department of Geography, McGill University, Montreal, Canada
| | - Kevin D. Kroeger
- U.S. Geological Survey, Woods Hole Coastal & Marine Science Center, Woods Hole, MA USA
| | - Kevin A. Kuehn
- School of Biological, Environmental, and Earth Sciences, University of Southern Mississippi, Hattiesburg, MS USA
| | - David Lobb
- Department of Soil Science, University of Manitoba, Winnipeg, MB Canada
| | - Amanda L. Loder
- Department of Geography, University of Toronto, Toronto, ON Canada
| | - Shizhou Ma
- School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK Canada
| | - Damien T. Maher
- Faculty of Science and Engineering, Southern Cross University, Lismore, NSW Australia
| | - Gavin McNicol
- Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL USA
| | - Jacob Meier
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Beth A. Middleton
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Christopher Mills
- U.S. Geological Survey, Geology, Geophysics, and Geochemistry Science Center, Denver, CO USA
| | - Purbasha Mistry
- School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK Canada
| | - Abhijit Mitra
- Department of Marine Science, University of Calcutta, Kolkata, West Bengal India
| | - Courtney Mobilian
- O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN USA
| | - Amanda M. Nahlik
- Office of Research and Development, Center for Public Health and Environmental Assessments, Pacific Ecological Systems Division, U.S. Environmental Protection Agency, Corvallis, OR USA
| | - Sue Newman
- South Florida Water Management District, Everglades Systems Assessment Section, West Palm Beach, FL USA
| | - Jessica L. O’Connell
- Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO USA
| | - Patty Oikawa
- Department of Earth and Environmental Sciences, California State University, East Bay, Hayward, CA USA
| | - Max Post van der Burg
- U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND USA
| | - Charles A. Schutte
- Department of Environmental Science, Rowan University, Glassboro, NJ USA
| | - Changchun Song
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Camille L. Stagg
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Jessica Turner
- Freshwater and Marine Science, University of Wisconsin-Madison, Madison, WI USA
| | - Rodrigo Vargas
- Department of Plant and Soil Sciences, University of Delaware, Newark, DE USA
| | - Mark P. Waldrop
- U.S. Geological Survey, Geology, Minerals, Energy and Geophysics Science Center, Menlo Park, CA USA
| | - Marcus B. Wallin
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Zhaohui Aleck Wang
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA USA
| | - Eric J. Ward
- U.S. Geological Survey, Wetland and Aquatic Research Center, Lafayette, LA USA
| | - Debra A. Willard
- U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA USA
| | - Stephanie Yarwood
- Environmental Science and Technology, University of Maryland, College Park, MD USA
| | - Xiaoyan Zhu
- Key Laboratory of Songliao Aquatic Environment, Ministry of Education, Jilin Jianzhu University, Changchun, China
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8
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Wang Y, Tian X, Duan M, Zhu D, Liu D, Zhang H, Zhou M, Zhao M, Jin Z, Ding J, Wang T, Piao S. Optimal design of surface CO 2 observation network to constrain China's land carbon sink. Sci Bull (Beijing) 2023; 68:1678-1686. [PMID: 37474444 DOI: 10.1016/j.scib.2023.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/02/2023] [Accepted: 05/04/2023] [Indexed: 07/22/2023]
Abstract
Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060. The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO2 fluxes that are optimally consistent with atmospheric CO2 measurements. But atmospheric inversion of China's land carbon sink has enormous uncertainties, with one major source arising from the poor coverage of CO2 observation stations. Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink. Compared with the large spread of inverted sink (∼1PgCa-1) from state-of-the-art inversions using existing CO2 observations, the uncertainty is constrained within 0.3PgCa-1 when a total of 30 stations were deployed, and is further reduced to approximately 0.2PgCa-1 when 60 stations were deployed. The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season, such as Southeast China, Northeast China, North China, and the Tibetan Plateau. Moreover, the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography. Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes.
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Affiliation(s)
- Yilong Wang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiangjun Tian
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy Sciences, Beijing 100049, China.
| | - Minzheng Duan
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Dan Zhu
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Dan Liu
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Hongqin Zhang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Minqiang Zhou
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Min Zhao
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhe Jin
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Jinzhi Ding
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Wang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Shilong Piao
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.
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9
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Raju A, Sijikumar S, Deb Burman PK, Valsala V, Tiwari YK, Mukherjee S, Lohani P, Kumar K. Very high-resolution Net Ecosystem Exchange over India using Vegetation Photosynthesis and Respiration Model (VPRM) simulations. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2023.110340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
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10
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Feldman AF, Zhang Z, Yoshida Y, Gentine P, Chatterjee A, Entekhabi D, Joiner J, Poulter B. A multi-satellite framework to rapidly evaluate extreme biosphere cascades: The Western US 2021 drought and heatwave. GLOBAL CHANGE BIOLOGY 2023; 29:3634-3651. [PMID: 37070967 DOI: 10.1111/gcb.16725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 04/04/2023] [Indexed: 06/06/2023]
Abstract
The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1-2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.
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Affiliation(s)
- Andrew F Feldman
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- NASA Postdoctoral Program, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Zhen Zhang
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
| | - Yasuko Yoshida
- Science Systems and Applications, Inc. (SSAI), Lanham, Maryland, USA
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, New York, USA
| | - Abhishek Chatterjee
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Dara Entekhabi
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Joanna Joiner
- Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Benjamin Poulter
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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11
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He C, Ji M, Grieneisen ML, Zhan Y. A review of datasets and methods for deriving spatiotemporal distributions of atmospheric CO 2. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 322:116101. [PMID: 36055102 DOI: 10.1016/j.jenvman.2022.116101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/04/2022] [Accepted: 08/23/2022] [Indexed: 06/15/2023]
Abstract
As the most abundant greenhouse gas, atmospheric carbon dioxide (CO2) is considered one of the main attributors to climate change. Atmospheric CO2 concentrations can be measured by ground-based monitoring networks, mobile monitoring campaigns, and carbon-observing satellites. However, the worldwide ground-based monitoring networks are composed of sparsely distributed sites and are inadequate to represent the spatiotemporal distributions of CO2. Satellite-based remote sensing features repeated, long-term, and large-scale measurements, so it plays a crucial role in monitoring the global distributions of atmospheric CO2. However, due to the presence of heavy clouds (or aerosols) and the limitation of satellite orbiting tracks, there exist large amounts of missing data in satellite retrievals. Various methods, including chemical transport models (CTMs), geostatistical methods, and regression-based models, have been employed to derive full-coverage spatiotemporal distributions of CO2 based on the limited CO2 measurements. This review summarizes the strengths and limitations of these methods. However, CTMs simulation results can have high uncertainty due to imperfect knowledge of the real world, and the interpolation accuracy of all geostatistical methods is limited by the large amount of data gaps in current satellite retrieved CO2 products. To overcome these limitations, regression-based methods (especially machine learning models) have the ability to predict CO2 with superior predictive performance, so this review also summarizes the framework of the machine learning approach. Leveraging the ongoing advancements of satellite instrumentation, the satellite-based CO2 products have been improving dramatically in recent decades, and this review will describe and critically assess the advantages and disadvantages of the currently used systems in detail. For future improvements, we recommend the fusion of data from multiple satellite retrievals and CTMs by using machine learning algorithms in order to obtain even longer-term, larger-scale, finer-resolution, and higher-accuracy CO2 datasets.
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Affiliation(s)
- Changpei He
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Mingrui Ji
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Michael L Grieneisen
- Department of Land, Air, and Water Resources, University of California, Davis, CA 95616, United States
| | - Yu Zhan
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China; School of Carbon Neutrality Future Technology, Sichuan University, Chengdu, Sichuan, 610065, China.
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12
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Liu Z, Kimball JS, Ballantyne AP, Parazoo NC, Wang WJ, Bastos A, Madani N, Natali SM, Watts JD, Rogers BM, Ciais P, Yu K, Virkkala AM, Chevallier F, Peters W, Patra PK, Chandra N. Respiratory loss during late-growing season determines the net carbon dioxide sink in northern permafrost regions. Nat Commun 2022; 13:5626. [PMID: 36163194 PMCID: PMC9512808 DOI: 10.1038/s41467-022-33293-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 09/12/2022] [Indexed: 11/20/2022] Open
Abstract
Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO2) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO2 uptake, and thus resulting in a slower rate of increasing annual net CO2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO2 uptake as high latitude ecosystems respond to warming climate conditions. The northern high latitude permafrost region has been an important contributor to the carbon sink since the 1980s. A new study finds that as tree cover increases, respiratory CO2 loss during late-growing season offsets photosynthetic CO2 uptake and leads to a slower rate of increasing annual net CO2 uptake.
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Affiliation(s)
- Zhihua Liu
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning, China.
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA. .,Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA.
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT, USA. .,Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France.
| | - Nicholas C Parazoo
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, Changchun, Jilin, China.
| | - Ana Bastos
- Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Kailiang Yu
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Wouter Peters
- Meteorology and Air Quality Group, Wageningen University and Research, Wageningen, the Netherlands.,University, Centre for Isotope Research, Groningen, the Netherlands
| | - Prabir K Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
| | - Naveen Chandra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
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13
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Yu Z, Ciais P, Piao S, Houghton RA, Lu C, Tian H, Agathokleous E, Kattel GR, Sitch S, Goll D, Yue X, Walker A, Friedlingstein P, Jain AK, Liu S, Zhou G. Forest expansion dominates China’s land carbon sink since 1980. Nat Commun 2022; 13:5374. [PMID: 36100606 PMCID: PMC9470586 DOI: 10.1038/s41467-022-32961-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/25/2022] [Indexed: 12/04/2022] Open
Abstract
Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China’s reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting. The impact of land-use and cover-change (LUCC) on ecosystem carbon stock in China is poorly known due to large biases in existing databases. Here the authors develop a new LUCC database with corrected false signals and reveal that forest expansion is the dominant driver of China’s recent carbon sink.
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14
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Walley S, Pal S, Campbell JF, Dobler J, Bell E, Weir B, Feng S, Lauvaux T, Baker D, Blume N, Erxleben W, Fan T, Lin B, McGregor D, Obland MD, O'Dell C, Davis KJ. Airborne Lidar Measurements of XCO 2 in Synoptically Active Environment and Associated Comparisons With Numerical Simulations. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2021JD035664. [PMID: 36582815 PMCID: PMC9786724 DOI: 10.1029/2021jd035664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 06/29/2022] [Accepted: 08/07/2022] [Indexed: 06/17/2023]
Abstract
Frontal boundaries have been shown to cause large changes in CO2 mole-fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO2 dry air mole-fraction (XCO2) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO2 frontal contrasts (ΔXCO2, i.e., warm minus cold sector average of XCO2). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO2 during four seasonal field campaigns of the Atmospheric Carbon and Transport-America (ACT-America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO2 in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO2 was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting--Chemistry (WRF-Chem) showed that (a) all products had a similar sign of ΔXCO2 though with different levels of agreement in ΔXCO2 magnitudes among seasons; (b) ΔXCO2 in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO2 frontal contrasts. A linear regression analyses between ΔXCO2 for MFLL versus GMAO, and MFLL versus WRF-Chem for summer-2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO2 variability among four seasons provide guidance to the spatial structures of XCO2 transport errors in models and satellite measurements of XCO2 in synoptically-active weather systems.
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Affiliation(s)
- Samantha Walley
- Department of GeosciencesAtmospheric Science DivisionTexas Tech UniversityLubbockTXUSA
| | - Sandip Pal
- Department of GeosciencesAtmospheric Science DivisionTexas Tech UniversityLubbockTXUSA
| | | | | | - Emily Bell
- Colorado State UniversityFort CollinsCOUSA
| | - Brad Weir
- Universities Space Research AssociationColumbiaMDUSA
- NASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Sha Feng
- Atmospheric Sciences and Global Change DivisionPacific Northwest National LaboratoryRichlandWAUSA
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Thomas Lauvaux
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
- LSCE ‐ IPSLCEA SaclaySaclayFrance
| | | | | | | | | | - Bing Lin
- NASA Langley Research Center (LaRC)HamptonVAUSA
| | | | | | | | - Kenneth J. Davis
- Atmospheric Sciences and Global Change DivisionPacific Northwest National LaboratoryRichlandWAUSA
- Earth and Environmental Systems InstituteThe Pennsylvania State UniversityUniversity ParkPAUSA
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15
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Feng S, Jiang F, Wang H, Shen Y, Zheng Y, Zhang L, Lou C, Ju W. Anthropogenic emissions estimated using surface observations and their impacts on PM 2.5 source apportionment over the Yangtze River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 828:154522. [PMID: 35288133 DOI: 10.1016/j.scitotenv.2022.154522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/11/2022] [Accepted: 03/08/2022] [Indexed: 06/14/2023]
Abstract
Source-tagged source apportionment (SA) has advantages for quantifying the contribution of various source regions and categories to PM2.5; however, it is highly affected by uncertainty in the emission inventory. In this study, we used a Regional multi-Air Pollutant Assimilation System (RAPAS) to optimize daily SO2, NOx and primary PM2.5 (PPM2.5) emissions in the Yangtze River Delta (YRD) in December 2016 by assimilating hourly in-situ measurements. The CMAQ-ISAM model was implemented with prior and posterior emissions respectively to investigate the impacts of optimizing emissions on PM2.5 SA in the YRD megalopolis (YRDM) and three megacities of Shanghai, Nanjing, and Hangzhou in the YRDM. The results showed that RAPAS significantly improved the simulations and reduced the emission uncertainties of the different pollutants. Compared with prior emissions, the posterior emissions in the YRD decreased by 13% and 11% for SO2 and NOx respectively, and increased by 24% for PPM2.5. Compared with SA using prior emissions, the contributions from Hangzhou, northern Zhejiang, and areas outside of the YRD to the YRDM increased. The local contributions from the YRDM, Nanjing and Shanghai decreased by 1.8%, 9.7%, and 2.3%, respectively, whereas that of Hangzhou increased by 5.6%. The changes in the daily local contributions caused by optimizing emissions ranged from -18.0% to 23.6%. Generally, under stable weather conditions, the local contribution changed the most, whereas under unstable weather conditions, the contribution from upwind areas changed significantly. Overall, with optimized emissions, we found in Nanjing, Shanghai, and Hangzhou, local emissions contributed 18.2%, 39.6% and 36.8% of their PM2.5 concentrations, respectively; long-range transport from outside the YRDM contributed 59.2%, 48.1%, and 48.2%, respectively. This study emphasizes the importance of improving emission estimations for source-tagged SA and provides more reliable SA results for the main cities in the YRD, which will contribute to pollution control in these regions.
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Affiliation(s)
- Shuzhuang Feng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Fei Jiang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China.
| | - Hengmao Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
| | - Yang Shen
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Yanhua Zheng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Lingyu Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Chenxi Lou
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Weimin Ju
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
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16
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Mitchell LE, Lin JC, Hutyra LR, Bowling DR, Cohen RC, Davis KJ, DiGangi E, Duren RM, Ehleringer JR, Fain C, Falk M, Guha A, Karion A, Keeling RF, Kim J, Miles NL, Miller CE, Newman S, Pataki DE, Prinzivalli S, Ren X, Rice A, Richardson SJ, Sargent M, Stephens BB, Turnbull JC, Verhulst KR, Vogel F, Weiss RF, Whetstone J, Wofsy SC. A multi-city urban atmospheric greenhouse gas measurement data synthesis. Sci Data 2022; 9:361. [PMID: 35750672 PMCID: PMC9232515 DOI: 10.1038/s41597-022-01467-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 06/09/2022] [Indexed: 11/28/2022] Open
Abstract
Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO2) and methane (CH4) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation. Measurement(s) | carbon dioxide • methane • carbon monoxide | Technology Type(s) | spectroscopy | Sample Characteristic - Environment | city | Sample Characteristic - Location | North America |
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Affiliation(s)
| | - John C Lin
- University of Utah, Salt Lake City, UT, USA
| | | | | | | | | | | | - Riley M Duren
- University of Arizona, Tucson, AZ, USA.,Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Abhinav Guha
- Bay Area Air Quality Management District, San Francisco, CA, USA
| | - Anna Karion
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Ralph F Keeling
- Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - Jooil Kim
- Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA, USA
| | | | - Charles E Miller
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Sally Newman
- Bay Area Air Quality Management District, San Francisco, CA, USA
| | | | | | - Xinrong Ren
- Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, USA
| | - Andrew Rice
- Portland State University, Portland, OR, USA
| | | | | | | | - Jocelyn C Turnbull
- GNS Science, Lower Hutt, New Zealand.,CIRES, University of Colorado at Boulder, Boulder, CO, USA
| | - Kristal R Verhulst
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Felix Vogel
- Environment and Climate Change Canada, Toronto, Canada
| | - Ray F Weiss
- Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - James Whetstone
- National Institute of Standards and Technology, Gaithersburg, MD, USA
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17
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Novick KA, Metzger S, Anderegg WRL, Barnes M, Cala DS, Guan K, Hemes KS, Hollinger DY, Kumar J, Litvak M, Lombardozzi D, Normile CP, Oikawa P, Runkle BRK, Torn M, Wiesner S. Informing Nature-based Climate Solutions for the United States with the best-available science. GLOBAL CHANGE BIOLOGY 2022; 28:3778-3794. [PMID: 35253952 DOI: 10.1111/gcb.16156] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/04/2022] [Indexed: 06/14/2023]
Abstract
Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point- and tree-scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.
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Affiliation(s)
- Kimberly A Novick
- O'Neill School of Public and Environmental Affairs, Indiana University-Bloomington, Bloomington, Indiana, USA
| | - Stefan Metzger
- Battelle, National Ecological Observatory Network, Boulder, Colorado, USA
| | | | - Mallory Barnes
- O'Neill School of Public and Environmental Affairs, Indiana University-Bloomington, Bloomington, Indiana, USA
| | - Daniela S Cala
- O'Neill School of Public and Environmental Affairs, Indiana University-Bloomington, Bloomington, Indiana, USA
| | - Kaiyu Guan
- College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Kyle S Hemes
- Woods Institute for the Environment, Stanford University, Stanford, California, USA
| | - David Y Hollinger
- USDA Forest Service, Northern Research Station, Durham, New Hampshire, USA
| | - Jitendra Kumar
- Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Marcy Litvak
- Department of Biology, University of New Mexico, Albuquerque, New Mexico, USA
| | | | | | - Patty Oikawa
- Department of Earth & Environmental Science, California State University-East Bay, Hayward, California, USA
| | - Benjamin R K Runkle
- Department of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, Arkansas, USA
| | - Margaret Torn
- Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Susanne Wiesner
- Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
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18
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Jiang F, He W, Ju W, Wang H, Wu M, Wang J, Feng S, Zhang L, Chen JM. The status of carbon neutrality of the world's top 5 CO 2 emitters as seen by carbon satellites. FUNDAMENTAL RESEARCH 2022; 2:357-366. [PMID: 38933397 PMCID: PMC11197612 DOI: 10.1016/j.fmre.2022.02.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 12/24/2021] [Accepted: 02/06/2022] [Indexed: 11/23/2022] Open
Abstract
China, the Unite States (US), the European Union (EU), India, and Russia are the world's top 5 fossil fuel and cement CO2 (FFC) emitting countries or regions (CRs). It is very important to understand their status of carbon neutrality, and to monitor their future changes of net carbon fluxes (NCFs). In this study, we implemented a well-established global carbon assimilation system (GCAS, Version 2) to infer global surface carbon fluxes from May 2009 to December 2019 using both GOSAT and OCO-2 XCO2 retrievals. The reductions of flux uncertainty and XCO2 bias, and the evaluation of posterior flux show that GCAS has comparable and good performance in the 5 CRs. The results suggest that Russia has achieved carbon neutrality, but the other 4 are still far from being carbon neutral, especially China. The mean annual NCFs in China, the US, the EU, India, and Russia are 2.33 ± 0.29, 0.82 ± 0.20, 0.42 ± 0.16, 0.50 ± 0.12, and -0.33 ± 0.23 PgC yr-1, respectively. From 2010 to 2019, the NCFs showed an increasing trend in the US and India, a slight downward trend after 2013 in China, and were stable in the EU. The changes of land sinks in China and the US might be the main reason for their trends. India's trend was mainly due to the increase of FFC emission. The relative contributions of NCFs to the global land net carbon emission of China and the EU have decreased, while those of the US and India have increased, implying the US and India must take more active measures to control carbon emissions or increase their sinks. This study indicates that satellite XCO2 could be successfully used to monitor the changes of regional NCFs, which is of great significance for major countries to achieve greenhouse gas control goals.
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Affiliation(s)
- Fei Jiang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing 210023, China
| | - Wei He
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Weimin Ju
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
| | - Hengmao Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Mousong Wu
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Jun Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Shuzhuang Feng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Lingyu Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Jing M. Chen
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
- Department of Geography, University of Toronto, Toronto, Ontario M5S3G3, Canada
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19
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Hu C, Liu C, Hu N, Hong J, Ai X. Government environmental control measures on CO 2 emission during the 2014 Youth Olympic Games in Nanjing: Perspectives from a top-down approach. J Environ Sci (China) 2022; 113:165-178. [PMID: 34963526 DOI: 10.1016/j.jes.2021.04.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 04/16/2021] [Accepted: 04/16/2021] [Indexed: 06/14/2023]
Abstract
Strict air pollution control measures were conducted during the Youth Olympic Games (YOG) period at Nanjing city and surrounding areas in August 2014. This event provides a unique chance to evaluate the effect of government control measures on regional atmospheric pollution and greenhouse gas emissions. Many previous studies have observed significant reductions of atmospheric pollution species and improvement in air quality, while no study has quantified its synergism on anthropogenic CO2 emissions, which can be co-reduced with air pollutants. To better understand to what extent these pollution control measures have reduced anthropogenic CO2 emissions, we conducted atmospheric CO2 measurements at the suburban site in Nanjing city from 1st July to 30th September 2014 and 1st August to 31st August 2015, obvious decrease in atmospheric CO2 was observed between YOG and the rest period. By coupling the a priori emission inventory with atmospheric transport model, we applied the scale factor Bayesian inversion approach to derive the posteriori CO2 emissions in YOG period and regular period. Results indicate CO2 emissions from power industry decreased by 45%, and other categories also decreased by 16% for manufacturing combusting, and 37% for non-metallic mineral production. Monthly total anthropogenic CO2 emissions were 9.8 (±3.6) × 109 kg/month CO2 for regular period and decreased to 6.2 (±1.9) × 109 kg/month during the YOG period in Nanjing city, with a 36.7% reduction. When scaling up to whole Jiangsu Province, anthropogenic CO2 emissions were 7.1 (±2.4) × 1010 kg/month CO2 for regular period and decreased to 4.4 (±1.2) × 1010 kg/month CO2 during the YOG period, yielding a 38.0% reduction.
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Affiliation(s)
- Cheng Hu
- College of Biology and the Environment, Joint Center for sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information, Science & Technology, Nanjing 210044, China.
| | - Cheng Liu
- Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution/School of Water Resources and Environmental Engineering, East China University of Technology, Nanchang 330013, China.
| | - Ning Hu
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information, Science & Technology, Nanjing 210044, China
| | - Jun Hong
- National Key Laboratory on Electromagnetic Environmental Effects and Electro-Optical Engineering, Army Engineering University, Nanjing 210022, China
| | - Xinyue Ai
- College of Biology and the Environment, Joint Center for sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
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20
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Effect of assimilating CO2 observations in the Korean Peninsula on the inverse modeling to estimate surface CO2 flux over Asia. PLoS One 2022; 17:e0263925. [PMID: 35180259 PMCID: PMC8856549 DOI: 10.1371/journal.pone.0263925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/30/2022] [Indexed: 11/19/2022] Open
Abstract
To investigate the impact of two CO2 observation datasets obtained from the Korean Peninsula on the surface CO2 flux estimation over Asia, the two datasets are assimilated into the CarbonTracker (CT) inverse modeling system and the estimated surface CO2 fluxes are analyzed. Anmyeon-do (AMY) and Gosan (GSN) sites in the Korean Peninsula have observed surface CO2 mole fraction since the late 1990s. To investigate the effect of assimilating the additional Korean observations on the surface CO2 flux estimation over Asia, two experiments are conducted. The reference experiment (CNTL) only assimilates observations provided by National Oceanic and Atmospheric Administration (NOAA), while the other experiment (EXP1) assimilates both NOAA observations and two Korean observation datasets. The results are analyzed for 9 years from 2003 to 2011 in Asia region because both AMY and GSN datasets exist almost completely for this period. The annual average of estimated biosphere CO2 flux of EXP1 shows more flux absorption in summer and less flux emission from fall to spring compared to CNTL, mainly on Eurasia Temperate and Eurasia Boreal regions. When comparing model results to independent CO2 concentration data from surface stations and aircraft, the root mean square error is smaller for EXP1 than CNTL. The EXP1 yields more reduction on uncertainty of estimated biosphere CO2 flux over Asia, and the observation impact of AMY, GSN sites on flux estimation is approximately 11%, which is greater than other observation sites around the world. Therefore, the two CO2 observation sets in the Korean Peninsula are useful in reducing uncertainties for regional as well as global scale CO2 flux estimation.
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21
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Spatiotemporal Geostatistical Analysis and Global Mapping of CH4 Columns from GOSAT Observations. REMOTE SENSING 2022. [DOI: 10.3390/rs14030654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Methane (CH4) is one of the most important greenhouse gases causing the global warming effect. The mapping data of atmospheric CH4 concentrations in space and time can help us better to understand the characteristics and driving factors of CH4 variation as to support the actions of CH4 emission reduction for preventing the continuous increase of atmospheric CH4 concentrations. In this study, we applied a spatiotemporal geostatistical analysis and prediction to develop an approach to generate the mapping CH4 dataset (Mapping-XCH4) in 1° grid and three days globally using column averaged dry air mole fraction of CH4 (XCH4) data derived from observations of the Greenhouse Gases Observing Satellite (GOSAT) from April 2009 to April 2020. Cross-validation for the spatiotemporal geostatistical predictions showed better correlation coefficient of 0.97 and a mean absolute prediction error of 7.66 ppb. The standard deviation is 11.42 ppb when comparing the Mapping-XCH4 data with the ground measurements from the total carbon column observing network (TCCON). Moreover, we assessed the performance of this Mapping-XCH4 dataset by comparing with the XCH4 simulations from the CarbonTracker model and primarily investigating the variations of XCH4 from April 2009 to April 2020. The results showed that the mean annual increase in XCH4 was 7.5 ppb/yr derived from Mapping-XCH4, which was slightly greater than 7.3 ppb/yr from the ground observational network during the past 10 years from 2010. XCH4 is larger in South Asia and eastern China than in the other regions, which agrees with the XCH4 simulations. The Mapping-XCH4 shows a significant linear relationship and a correlation coefficient of determination (R2) of 0.66, with EDGAR emission inventories over Monsoon Asia. Moreover, we found that Mapping-XCH4 could detect the reduction of XCH4 in the period of lockdown from January to April 2020 in China, likely due to the COVID-19 pandemic. In conclusion, we can apply GOSAT observations over a long period from 2009 to 2020 to generate a spatiotemporally continuous dataset globally using geostatistical analysis. This long-term Mpping-XCH4 dataset has great potential for understanding the spatiotemporal variations of CH4 concentrations induced by natural processes and anthropogenic emissions at a global and regional scale.
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22
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Botía S, Komiya S, Marshall J, Koch T, Gałkowski M, Lavric J, Gomes-Alves E, Walter D, Fisch G, Pinho DM, Nelson BW, Martins G, Luijkx IT, Koren G, Florentie L, Carioca de Araújo A, Sá M, Andreae MO, Heimann M, Peters W, Gerbig C. The CO 2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales. GLOBAL CHANGE BIOLOGY 2022; 28:588-611. [PMID: 34562049 DOI: 10.1111/gcb.15905] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 09/16/2021] [Indexed: 06/13/2023]
Abstract
High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2 . In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal ( ΔCO2obs ) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between ΔCO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of ΔCO2obs . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of ΔCO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.
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Affiliation(s)
- Santiago Botía
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Shujiro Komiya
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Julia Marshall
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
| | - Thomas Koch
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Michał Gałkowski
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland
| | - Jost Lavric
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Eliane Gomes-Alves
- Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - David Walter
- Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Gilberto Fisch
- Departamento de Ciência e Tecnologia Aeroespacial (DCTA), Instituto de Aeronautica e Espaço (IAE), São José dos Campos, Brazil
| | - Davieliton M Pinho
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Bruce W Nelson
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Giordane Martins
- Environmental Dynamics Department, Brazil's National Institute for Amazon Research - INPA, Manaus, Brazil
| | - Ingrid T Luijkx
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Gerbrand Koren
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Liesbeth Florentie
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
| | | | - Marta Sá
- Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, Brazil
| | - Meinrat O Andreae
- Biogeochemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Martin Heimann
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
- Institute for Atmospheric and Earth System Research (INAR) / Physics, University of Helsinki, Helsinki, Finland
| | - Wouter Peters
- Meteorology and Air Quality Department, Wageningen University and Research Center, Wageningen, The Netherlands
- Groningen University, Energy and Sustainability Research Institute Groningen, Groningen, The Netherlands
| | - Christoph Gerbig
- Biogeochemical Signals Department, Max Planck Institute for Biogeochemistry, Jena, Germany
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23
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Long MC, Stephens BB, McKain K, Sweeney C, Keeling RF, Kort EA, Morgan EJ, Bent JD, Chandra N, Chevallier F, Commane R, Daube BC, Krummel PB, Loh Z, Luijkx IT, Munro D, Patra P, Peters W, Ramonet M, Rödenbeck C, Stavert A, Tans P, Wofsy SC. Strong Southern Ocean carbon uptake evident in airborne observations. Science 2021; 374:1275-1280. [PMID: 34855495 DOI: 10.1126/science.abi4355] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Matthew C Long
- National Center for Atmospheric Research, Boulder, CO, USA
| | | | - Kathryn McKain
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA.,Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Colm Sweeney
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Ralph F Keeling
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Eric A Kort
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Eric J Morgan
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Jonathan D Bent
- National Center for Atmospheric Research, Boulder, CO, USA.,Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Naveen Chandra
- National Institute of Environmental Studies, Tsukuba, Japan
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212 91191, France
| | - Róisín Commane
- Department of Earth and Environmental Sciences, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA
| | - Bruce C Daube
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Paul B Krummel
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Zoë Loh
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Ingrid T Luijkx
- Department of Meteorology and Air Quality, Environmental Sciences Group, Wageningen University, Netherlands
| | - David Munro
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA.,Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Prabir Patra
- Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan
| | - Wouter Peters
- Department of Meteorology and Air Quality, Environmental Sciences Group, Wageningen University, Netherlands.,Centre for Isotope Research, University of Groningen, Groningen, Netherlands
| | - Michel Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212 91191, France
| | | | - Ann Stavert
- Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Pieter Tans
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Steven C Wofsy
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA.,Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
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24
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Chen B, Zhang H, Wang T, Zhang X. An atmospheric perspective on the carbon budgets of terrestrial ecosystems in China: progress and challenges. Sci Bull (Beijing) 2021; 66:1713-1718. [PMID: 36654376 DOI: 10.1016/j.scib.2021.05.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Baozhang Chen
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Monitoring & Assessment Center for GHGs (Greenhouse Gases) & Carbon Neutrality, Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Huifang Zhang
- State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Tao Wang
- Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China
| | - Xiaoye Zhang
- Monitoring & Assessment Center for GHGs (Greenhouse Gases) & Carbon Neutrality, Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
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25
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Detecting the Responses of CO2 Column Abundances to Anthropogenic Emissions from Satellite Observations of GOSAT and OCO-2. REMOTE SENSING 2021. [DOI: 10.3390/rs13173524] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The continuing increase in atmospheric CO2 concentration caused by anthropogenic CO2 emissions significantly contributes to climate change driven by global warming. Satellite measurements of long-term CO2 data with global coverage improve our understanding of global carbon cycles. However, the sensitivity of the space-borne measurements to anthropogenic emissions on a regional scale is less explored because of data sparsity in space and time caused by impacts from geophysical factors such as aerosols and clouds. Here, we used global land mapping column averaged dry-air mole fractions of CO2 (XCO2) data (Mapping-XCO2), generated from a spatio-temporal geostatistical method using GOSAT and OCO-2 observations from April 2009 to December 2020, to investigate the responses of XCO2 to anthropogenic emissions at both global and regional scales. Our results show that the long-term trend of global XCO2 growth rate from Mapping-XCO2, which is consistent with that from ground observations, shows interannual variations caused by the El Niño Southern Oscillation (ENSO). The spatial distributions of XCO2 anomalies, derived from removing background from the Mapping-XCO2 data, reveal XCO2 enhancements of about 1.5–3.5 ppm due to anthropogenic emissions and seasonal biomass burning in the wintertime. Furthermore, a clustering analysis applied to seasonal XCO2 clearly reveals the spatial patterns of atmospheric transport and terrestrial biosphere CO2 fluxes, which help better understand and analyze regional XCO2 changes that are associated with atmospheric transport. To quantify regional anomalies of CO2 emissions, we selected three representative urban agglomerations as our study areas, including the Beijing-Tian-Hebei region (BTH), the Yangtze River Delta urban agglomerations (YRD), and the high-density urban areas in the eastern USA (EUSA). The results show that the XCO2 anomalies in winter well capture the several-ppm enhancement due to anthropogenic CO2 emissions. For BTH, YRD, and EUSA, regional positive anomalies of 2.47 ± 0.37 ppm, 2.20 ± 0.36 ppm, and 1.38 ± 0.33 ppm, respectively, can be detected during winter months from 2009 to 2020. These anomalies are slightly higher than model simulations from CarbonTracker-CO2. In addition, we compared the variations in regional XCO2 anomalies and NO2 columns during the lockdown of the COVID-19 pandemic from January to March 2020. Interestingly, the results demonstrate that the variations of XCO2 anomalies have a positive correlation with the decline of NO2 columns during this period. These correlations, moreover, are associated with the features of emitting sources. These results suggest that we can use simultaneously observed NO2, because of its high detectivity and co-emission with CO2, to assist the analysis and verification of CO2 emissions in future studies.
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26
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CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals. REMOTE SENSING 2021. [DOI: 10.3390/rs13152996] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.
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27
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Yun J, Jeong S. Contributions of economic growth, terrestrial sinks, and atmospheric transport to the increasing atmospheric CO 2 concentrations over the Korean Peninsula. CARBON BALANCE AND MANAGEMENT 2021; 16:22. [PMID: 34283298 PMCID: PMC8290544 DOI: 10.1186/s13021-021-00186-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/12/2021] [Indexed: 05/15/2023]
Abstract
BACKGROUND Understanding a carbon budget from a national perspective is essential for establishing effective plans to reduce atmospheric CO2 growth. The national characteristics of carbon budgets are reflected in atmospheric CO2 variations; however, separating regional influences on atmospheric signals is challenging owing to atmospheric CO2 transport. Therefore, in this study, we examined the characteristics of atmospheric CO2 variations over South and North Korea during 2000-2016 and unveiled the causes of their regional differences in the increasing rate of atmospheric CO2 concentrations by utilizing atmospheric transport modeling. RESULTS The atmospheric CO2 concentration in South Korea is rising by 2.32 ppm year- 1, which is more than the globally-averaged increase rate of 2.05 ppm year- 1. Atmospheric transport modeling indicates that the increase in domestic fossil energy supply to support manufacturing export-led economic growth leads to an increase of 0.12 ppm year- 1 in atmospheric CO2 in South Korea. Although enhancements of terrestrial carbon uptake estimated from both inverse modeling and process-based models have decreased atmospheric CO2 by up to 0.02 ppm year- 1, this decrease is insufficient to offset anthropogenic CO2 increases. Meanwhile, atmospheric CO2 in North Korea is also increasing by 2.23 ppm year- 1, despite a decrease in national CO2 emissions close to carbon neutrality. The great increases estimated in both South Korea and North Korea are associated with changes in atmospheric transport, including increasing emitted and transported CO2 from China, which have increased the national atmospheric CO2 concentrations by 2.23 ppm year- 1 and 2.27 ppm year- 1, respectively. CONCLUSIONS This study discovered that economic activity is the determinant of regional differences in increasing atmospheric CO2 in the Korea Peninsula. However, from a global perspective, changes in transported CO2 are a major driver of rising atmospheric CO2 over this region, yielding an increase rate higher than the global mean value. Our findings suggest that accurately separating the contributions of atmospheric transport and regional sources to the increasing atmospheric CO2 concentrations is important for developing effective strategies to achieve carbon neutrality at the national level.
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Affiliation(s)
- Jeongmin Yun
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, Republic of Korea
| | - Sujong Jeong
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, Republic of Korea.
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Wei Y, Shrestha R, Pal S, Gerken T, Feng S, McNelis J, Singh D, Thornton MM, Boyer AG, Shook MA, Chen G, Baier BC, Barkley ZR, Barrick JD, Bennett JR, Browell EV, Campbell JF, Campbell LJ, Choi Y, Collins J, Dobler J, Eckl M, Fiehn A, Fried A, Digangi JP, Barton‐Grimley R, Halliday H, Klausner T, Kooi S, Kostinek J, Lauvaux T, Lin B, McGill MJ, Meadows B, Miles NL, Nehrir AR, Nowak JB, Obland M, O’Dell C, Fao RMP, Richardson SJ, Richter D, Roiger A, Sweeney C, Walega J, Weibring P, Williams CA, Yang MM, Zhou Y, Davis KJ. Atmospheric Carbon and Transport - America (ACT-America) Data Sets: Description, Management, and Delivery. EARTH AND SPACE SCIENCE (HOBOKEN, N.J.) 2021; 8:e2020EA001634. [PMID: 34435081 PMCID: PMC8365738 DOI: 10.1029/2020ea001634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/19/2021] [Accepted: 05/09/2021] [Indexed: 06/13/2023]
Abstract
The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. We conducted 121 research flights during five campaigns in four seasons during 2016-2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 h of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT-America data sets.
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29
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Sub-Daily Natural CO2 Flux Simulation Based on Satellite Data: Diurnal and Seasonal Pattern Comparisons to Anthropogenic CO2 Emissions in the Greater Tokyo Area. REMOTE SENSING 2021. [DOI: 10.3390/rs13112037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
During the last decade, advances in the remote sensing of greenhouse gas (GHG) concentrations by the Greenhouse Gases Observing SATellite-1 (GOSAT-1), GOSAT-2, and Orbiting Carbon Observatory-2 (OCO-2) have produced finer-resolution atmospheric carbon dioxide (CO2) datasets. These data are applicable for a top-down approach towards the verification of anthropogenic CO2 emissions from megacities and updating of the inventory. However, great uncertainties regarding natural CO2 flux estimates remain when back-casting CO2 emissions from concentration data, making accurate disaggregation of urban CO2 sources difficult. For this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) land products, meso-scale meteorological data, SoilGrids250 m soil profile data, and sub-daily soil moisture datasets to calculate hourly photosynthetic CO2 uptake and biogenic CO2 emissions with 500 m resolution for the Kantō Plain, Japan, at the center of which is the Tokyo metropolis. Our hourly integrated modeling results obtained for the period 2010–2018 suggest that, collectively, the vegetated land within the Greater Tokyo Area served as a daytime carbon sink year-round, where the hourly integrated net atmospheric CO2 removal was up to 14.15 ± 4.24% of hourly integrated anthropogenic emissions in winter and up to 55.42 ± 10.39% in summer. At night, plants and soil in the Greater Tokyo Area were natural carbon sources, with hourly integrated biogenic CO2 emissions equivalent to 2.27 ± 0.11%–4.97 ± 1.17% of the anthropogenic emissions in winter and 13.71 ± 2.44%–23.62 ± 3.13% in summer. Between January and July, the hourly integrated biogenic CO2 emissions of the Greater Tokyo Area increased sixfold, whereas the amplitude of the midday hourly integrated photosynthetic CO2 uptake was enhanced by nearly five times and could offset up to 79.04 ± 12.31% of the hourly integrated anthropogenic CO2 emissions in summer. The gridded hourly photosynthetic CO2 uptake and biogenic respiration estimates not only provide reference data for the estimation of total natural CO2 removal in our study area, but also supply prior input values for the disaggregation of anthropogenic CO2 emissions and biogenic CO2 fluxes when applying top-down approaches to update the megacity’s CO2 emissions inventory. The latter contribution allows unprecedented amounts of GOSAT and ground measurement data regarding CO2 concentration to be analyzed in inverse modeling of anthropogenic CO2 emissions from Tokyo and the Kantō Plain.
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Quadri P, Silva LCR, Zavaleta ES. Climate-induced reversal of tree growth patterns at a tropical treeline. SCIENCE ADVANCES 2021; 7:7/22/eabb7572. [PMID: 34039595 PMCID: PMC8153731 DOI: 10.1126/sciadv.abb7572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 04/08/2021] [Indexed: 06/12/2023]
Abstract
Globally, cold-limited trees and forests are expected to experience growth acceleration as a direct response to warming temperatures. However, thresholds of temperature limitation may vary substantially with local environmental conditions, leading to heterogeneous responses in tree ecophysiology. We used dendroecological and isotopic methods to quantify shifting tree growth and resource use over the past 143 years across topographic aspects in a high-elevation forest of central Mexico. Trees on south-facing slopes (SFS) grew faster than those on north-facing slopes (NFS) until the mid-20th century, when this pattern reversed notably with marked growth rate declines on SFS and increases on NFS. Stable isotopes of carbon, oxygen, and carbon-to-nitrogen ratios suggest that this reversal is linked to interactions between CO2 stimulation of photosynthesis and water or nitrogen limitation. Our findings highlight the importance of incorporating landscape processes and habitat heterogeneity in predictions of tree growth responses to global environmental change.
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Affiliation(s)
- Paulo Quadri
- Sky Island Alliance, Tucson, AZ 85719, USA.
- University of California, Santa Cruz, Santa Cruz, CA 95064, USA
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31
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Zeng ZC, Byrne B, Gong FY, He Z, Lei L. Correlation between paddy rice growth and satellite-observed methane column abundance does not imply causation. Nat Commun 2021; 12:1163. [PMID: 33608516 PMCID: PMC7895942 DOI: 10.1038/s41467-021-21434-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 01/19/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Zhao-Cheng Zeng
- Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, Los Angeles, CA, USA. .,Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.
| | - Brendan Byrne
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
| | - Fang-Ying Gong
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
| | | | - Liping Lei
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
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32
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Honeycutt WT, Kim T, Ley MT, Materer NF. Sensor array for wireless remote monitoring of carbon dioxide and methane near carbon sequestration and oil recovery sites. RSC Adv 2021; 11:6972-6984. [PMID: 35423189 PMCID: PMC8694925 DOI: 10.1039/d0ra08593f] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 02/02/2021] [Indexed: 12/02/2022] Open
Abstract
Carbon sequestration and enhanced oil recovery are two important geochemical applications currently deployed using carbon dioxide (CO2), a prevalent greenhouse gas. Despite the push to find ways to use and store excess CO2, the development of a large-area monitoring system is lacking. For these applications, there is little literature reporting the development and testing of sensor systems capable of operating in remote areas without maintenance and having significantly low cost to allow their deployment across a large land area. This paper presents the design and validation of a low-cost solar-power distributed sensing architecture using a wireless mesh network integrated, at selective nodes, into a cellular network. This combination allows an “internet of things” approach in remote locations and the integration of a large number of sensor units to monitor CO2 and methane (CH4). This system will allow efficient large area monitoring of both rare catastrophic leaks along with the common micro-seepage of greenhouse gas near carbon sequestration and oil recovery sites. The deployment and testing of the sensor system was performed in an open field at Oklahoma State University. The two-tear network functionality and robustness were determined from a multi-year field study. The reliability of the system was benchmarked by correlating the measured temperature, pressure, and humidity measurement by the network of devices to existing weather data. The CO2 and CH4 gas concentration tracked their expected daily and seasonal cycles. This multi-year field study established that this system can operate in remote areas with minimal human interactions. Demonstration of a solar-powered sensor array for remote carbon sequestration and enhanced oil recovery monitoring. An unattended sensor array can collect real-time gas concentrations, allow leak detection, and measure daily concentration cycles.![]()
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Affiliation(s)
- Wesley T Honeycutt
- Oklahoma Biological Survey, University of Oklahoma 111 Chesapeake St. Norman OK 73019 USA
| | - Taehwan Kim
- Centre for Infrastructure and Engineering and Safety, School of Civil and Environmental Engineering, The University of New South Wales Sydney NSW 2052 Australia
| | - M Tyler Ley
- College of Engineering, Architecture and Technology, Oklahoma State University 201 ATRC Stillwater OK 74078 USA
| | - Nicholas F Materer
- Department of Chemistry, Oklahoma State University 107 Physical Sciences Stillwater OK 74078 USA +1-405-744-5920
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33
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Ballantyne AP, Liu Z, Anderegg WRL, Yu Z, Stoy P, Poulter B, Vanderwall J, Watts J, Kelsey K, Neff J. Reconciling carbon-cycle processes from ecosystem to global scales. FRONTIERS IN ECOLOGY AND THE ENVIRONMENT 2021; 19:57-65. [PMID: 35874182 PMCID: PMC9292898 DOI: 10.1002/fee.2296] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Understanding carbon (C) dynamics from ecosystem to global scales remains a challenge. Although expansion of global carbon dioxide (CO2) observatories makes it possible to estimate C-cycle processes from ecosystem to global scales, these estimates do not necessarily agree. At the continental US scale, only 5% of C fixed through photosynthesis remains as net ecosystem exchange (NEE), but ecosystem measurements indicate that only 2% of fixed C remains in grasslands, whereas as much as 30% remains in needleleaf forests. The wet and warm Southeast has the highest gross primary productivity and the relatively wet and cool Midwest has the highest NEE, indicating important spatial mismatches. Newly available satellite and atmospheric data can be combined in innovative ways to identify potential C loss pathways to reconcile these spatial mismatches. Independent datasets compiled from terrestrial and aquatic environments can now be combined to advance C-cycle science across the land-water interface.
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Affiliation(s)
- Ashley P Ballantyne
- Department of Ecosystem and Conservation SciencesUniversity of MontanaMissoulaMT
- Laboratoire des Sciences du Climat et de l’EnvironnementGif-Sur-YvetteFrance
| | - Zhihua Liu
- CAS Key Laboratory of Forest Ecology and ManagementInstitute of Applied EcologyChinese Academy of SciencesShenyangChina
| | | | - Zicheng Yu
- Department of Earth and Environmental SciencesLehigh UniversityBethlehemPA
- Institute for Peat and Mire ResearchSchool of Geographical SciencesNortheast Normal UniversityChangchunChina
| | - Paul Stoy
- Department of Biological Systems EngineeringUniversity of Wisconsin–MadisonMadisonWI
| | - Ben Poulter
- National Aeronautics and Space AdministrationGoddard Space Flight CenterBiospheric Sciences LaboratoryGreenbeltMD
| | - Joseph Vanderwall
- Department of Ecosystem and Conservation SciencesUniversity of MontanaMissoulaMT
| | | | - Kathy Kelsey
- Geography and Environmental ScienceUniversity of Colorado DenverDenverCO
| | - Jason Neff
- Sustainability Innovation Laboratory and Environmental StudiesUniversity of ColoradoBoulderCO
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Miles NL, Davis KJ, Richardson SJ, Lauvaux T, Martins DK, Deng AJ, Balashov N, Gurney KR, Liang J, Roest G, Wang JA, Turnbull JC. The influence of near-field fluxes on seasonal carbon dioxide enhancements: results from the Indianapolis Flux Experiment (INFLUX). CARBON BALANCE AND MANAGEMENT 2021; 16:4. [PMID: 33515367 PMCID: PMC7847578 DOI: 10.1186/s13021-020-00166-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 12/18/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Networks of tower-based CO2 mole fraction sensors have been deployed by various groups in and around cities across the world to quantify anthropogenic CO2 emissions from metropolitan areas. A critical aspect in these approaches is the separation of atmospheric signatures from distant sources and sinks (i.e., the background) from local emissions and biogenic fluxes. We examined CO2 enhancements compared to forested and agricultural background towers in Indianapolis, Indiana, USA, as a function of season and compared them to modeled results, as a part of the Indianapolis Flux (INFLUX) project. RESULTS At the INFLUX urban tower sites, daytime growing season enhancement on a monthly timescale was up to 4.3-6.5 ppm, 2.6 times as large as those in the dormant season, on average. The enhancement differed significantly depending on choice of background and time of year, being 2.8 ppm higher in June and 1.8 ppm lower in August using a forested background tower compared to an agricultural background tower. A prediction based on land cover and observed CO2 fluxes showed that differences in phenology and drawdown intensities drove measured differences in enhancements. Forward modelled CO2 enhancements using fossil fuel and biogenic fluxes indicated growing season model-data mismatch of 1.1 ± 1.7 ppm for the agricultural background and 2.1 ± 0.5 ppm for the forested background, corresponding to 25-29% of the modelled CO2 enhancements. The model-data total CO2 mismatch during the dormant season was low, - 0.1 ± 0.5 ppm. CONCLUSIONS Because growing season biogenic fluxes at the background towers are large, the urban enhancements must be disentangled from the biogenic signal, and growing season increases in CO2 enhancement could be misinterpreted as increased anthropogenic fluxes if the background ecosystem CO2 drawdown is not considered. The magnitude and timing of enhancements depend on the land cover type and net fluxes surrounding each background tower, so a simple box model is not appropriate for interpretation of these data. Quantification of the seasonality and magnitude of the biological fluxes in the study region using high-resolution and detailed biogenic models is necessary for the interpretation of tower-based urban CO2 networks for cities with significant vegetation.
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Affiliation(s)
- Natasha L Miles
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Kenneth J Davis
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Scott J Richardson
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Thomas Lauvaux
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), 91190, Saint-Aubin, France
| | - Douglas K Martins
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
- FLIR Systems, Inc, West Lafayette, IN, 47906, USA
| | - A J Deng
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
- Utopus Insights, Inc, Valhalla, NY, 10595, USA
| | - Nikolay Balashov
- Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, 16802, USA
- NASA Goddard Space Flight Center/Universities Space Research Association, Greenbelt, MD, 20771, USA
| | | | - Jianming Liang
- Northern Arizona University, Flagstaff, AZ, 86011, USA
- Environmental Systems Research Institute, Redlands, CA, 92373, USA
| | - Geoff Roest
- Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - Jonathan A Wang
- Boston University, Boston, MA, 02215, USA
- University of California, Irvine, CA, 92697, USA
| | - Jocelyn C Turnbull
- GNS Science, Lower Hutt, 5040, New Zealand
- CIRES, University of Colorado at Boulder, Boulder, CO, USA
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35
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Pan G, Xu Y, Ma J. The potential of CO 2 satellite monitoring for climate governance: A review. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 277:111423. [PMID: 33031999 DOI: 10.1016/j.jenvman.2020.111423] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 08/21/2020] [Accepted: 09/19/2020] [Indexed: 06/11/2023]
Abstract
Good-quality CO2 emission data are fundamental for effective climate policy and governance. Data manipulation should be deterred, while developing countries are generally weaker than developed countries in compiling bottom-up CO2 emission inventories due to less adequate data collection capacity. This paper assesses the capabilities of CO2 satellites as objective, independent, potentially low-cost and external data sources for monitoring energy-related anthropogenic CO2 emissions at regional/national, megacity and point-source geographical scales. After overviewing all major CO2 satellites, SCIAMACHY, GOSAT and OCO-2 are focused on due to their wider research applications and higher CO2 sensitivity in total column measurements that include near surface emissions. Nighttime light satellite data for proxy CO2 monitoring are also brought into comparison to distinguish the importance of direct CO2 satellite monitoring. Studies are reviewed from the perspectives of spatial and temporal capability and accuracy to comprehend the current statuses of applications, assess the strengths and weaknesses of research methods, investigate major challenges and propose suggestions for future progress. We conclude that CO2 satellite monitoring can strengthen the data foundation for implementing international climate treaties and domestic climate policies.
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Affiliation(s)
- Guanna Pan
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China.
| | - Yuan Xu
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China.
| | - Jieqi Ma
- School of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen 518172, China.
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Karion A, Lopez-Coto I, Gourdji SM, Mueller K, Ghosh S, Callahan W, Stock M, DiGangi E, Prinzivalli S, Whetstone J. Background conditions for an urban greenhouse gas network in the Washington, D.C. and Baltimore metropolitan region. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:10.5194/acp-21-6257-2021. [PMID: 36873665 PMCID: PMC9982866 DOI: 10.5194/acp-21-6257-2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
As city governments take steps towards establishing emissions reduction targets, the atmospheric research community is increasingly able to assist in tracking emissions reductions. Researchers have established systems for observing atmospheric greenhouse gases in urban areas with the aim of attributing greenhouse gas concentration enhancements (and thus, emissions) to the region in question. However, to attribute enhancements to a particular region, one must isolate the component of the observed concentration attributable to fluxes inside the region by removing the background, which is the component due to fluxes outside. In this study, we demonstrate methods to construct several versions of a background for our carbon dioxide and methane observing network in the Washington, DC and Baltimore, MD metropolitan region. Some of these versions rely on transport and flux models, while others are based on observations upwind of the domain. First, we evaluate the backgrounds in a synthetic data framework, then we evaluate against real observations from our urban network. We find that backgrounds based on upwind observations capture the variability better than model-based backgrounds, although care must be taken to avoid bias from biospheric carbon dioxide fluxes near background stations in summer. Model-based backgrounds also perform well when upwind fluxes can be modeled accurately. Our study evaluates different background methods and provides guidance determining background methodology that can impact the design of urban monitoring networks.
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Affiliation(s)
- Anna Karion
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Israel Lopez-Coto
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794, USA
| | - Sharon M. Gourdji
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Kimberly Mueller
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Subhomoy Ghosh
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
- Center for Research Computing, University of Notre Dame, South Bend, IN, 46556, USA
| | | | | | | | | | - James Whetstone
- Special Programs Office, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
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Byrne B, Liu J, Bloom AA, Bowman KW, Butterfield Z, Joiner J, Keenan TF, Keppel‐Aleks G, Parazoo NC, Yin Y. Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America. GLOBAL BIOGEOCHEMICAL CYCLES 2020; 34:e2020GB006598. [PMID: 33281280 PMCID: PMC7685151 DOI: 10.1029/2020gb006598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 08/20/2020] [Accepted: 10/11/2020] [Indexed: 05/19/2023]
Abstract
Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.
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Affiliation(s)
- B. Byrne
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - J. Liu
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
| | - A. A. Bloom
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - K. W. Bowman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
- Joint Institute for Regional Earth System Science and EngineeringUniversity of CaliforniaLos AngelesUSA
| | - Z. Butterfield
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - J. Joiner
- Laboratory of Atmospheric Chemistry and DynamicsNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - T. F. Keenan
- Earth and Environmental Sciences AreaLawrence Berkeley National LaboratoryBerkeleyCAUSA
- Department of Environmental Science, Policy and ManagementUniversity of CaliforniaBerkeleyCAUSA
| | - G. Keppel‐Aleks
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - N. C. Parazoo
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Y. Yin
- Division of Geological and Planetary SciencesCalifornia Institute of TechnologyPasadenaCAUSA
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Determination of Region of Influence Obtained by Aircraft Vertical Profiles Using the Density of Trajectories from the HYSPLIT Model. ATMOSPHERE 2020. [DOI: 10.3390/atmos11101073] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Aircraft atmospheric profiling is a valuable technique for determining greenhouse gas fluxes at regional scales (104–106 km2). Here, we describe a new, simple method for estimating the surface influence of air samples that uses backward trajectories based on the Lagrangian model Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). We determined “regions of influence” on a quarterly basis between 2010 and 2018 for four aircraft vertical profile sites: SAN and ALF in the eastern Amazon, and RBA and TAB or TEF in the western Amazon. We evaluated regions of influence in terms of their relative sensitivity to areas inside and outside the Amazon and their total area inside the Amazon. Regions of influence varied by quarter and less so by year. In the first and fourth quarters, the contribution of the region of influence inside the Amazon was 83–93% for all sites, while in the second and third quarters, it was 57–75%. The interquarter differences are more evident in the eastern than in the western Amazon. Our analysis indicates that atmospheric profiles from the western sites are sensitive to 42–52.2% of the Amazon. In contrast, eastern Amazon sites are sensitive to only 10.9–25.3%. These results may help to spatially resolve the response of greenhouse gas emissions to climate variability over Amazon.
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Lin X, Rogers BM, Sweeney C, Chevallier F, Arshinov M, Dlugokencky E, Machida T, Sasakawa M, Tans P, Keppel-Aleks G. Siberian and temperate ecosystems shape Northern Hemisphere atmospheric CO 2 seasonal amplification. Proc Natl Acad Sci U S A 2020; 117:21079-21087. [PMID: 32817563 PMCID: PMC7474631 DOI: 10.1073/pnas.1914135117] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
The amplitude of the atmospheric CO2 seasonal cycle has increased by 30 to 50% in the Northern Hemisphere (NH) since the 1960s, suggesting widespread ecological changes in the northern extratropics. However, substantial uncertainty remains in the continental and regional drivers of this prominent amplitude increase. Here we present a quantitative regional attribution of CO2 seasonal amplification over the past 4 decades, using a tagged atmospheric transport model prescribed with observationally constrained fluxes. We find that seasonal flux changes in Siberian and temperate ecosystems together shape the observed amplitude increases in the NH. At the surface of northern high latitudes, enhanced seasonal carbon exchange in Siberia is the dominant contributor (followed by temperate ecosystems). Arctic-boreal North America shows much smaller changes in flux seasonality and has only localized impacts. These continental contrasts, based on an atmospheric approach, corroborate heterogeneous vegetation greening and browning trends from field and remote-sensing observations, providing independent evidence for regionally divergent ecological responses and carbon dynamics to global change drivers. Over surface midlatitudes and throughout the midtroposphere, increased seasonal carbon exchange in temperate ecosystems is the dominant contributor to CO2 amplification, albeit with considerable contributions from Siberia. Representing the mechanisms that control the high-latitude asymmetry in flux amplification found in this study should be an important goal for mechanistic land surface models moving forward.
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Affiliation(s)
- Xin Lin
- Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109;
| | | | - Colm Sweeney
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace, Commissariat à l'Énergie Atomique et aux Énergies Alternatives-CNRS-Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Mikhail Arshinov
- Vladimir Evseevich Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, Tomsk 634055, Russia
| | - Edward Dlugokencky
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305
| | - Toshinobu Machida
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
| | - Motoki Sasakawa
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan
| | - Pieter Tans
- Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305
| | - Gretchen Keppel-Aleks
- Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109;
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40
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Multi-Year Comparison of CO2 Concentration from NOAA Carbon Tracker Reanalysis Model with Data from GOSAT and OCO-2 over Asia. REMOTE SENSING 2020. [DOI: 10.3390/rs12152498] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Accurate knowledge of the carbon budget on global and regional scales is critically important to design mitigation strategies aimed at stabilizing the atmospheric carbon dioxide (CO2) emissions. For a better understanding of CO2 variation trends over Asia, in this study, the column-averaged CO2 dry air mole fraction (XCO2) derived from the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker (CT) was compared with that of Greenhouse Gases Observing Satellite (GOSAT) from September 2009 to August 2019 and with Orbiting Carbon Observatory 2 (OCO-2) from September 2014 until August 2019. Moreover, monthly averaged time-series and seasonal climatology comparisons were also performed separately over the five regions of Asia; i.e., Central Asia, East Asia, South Asia, Southeast Asia, and Western Asia. The results show that XCO2 from GOSAT is higher than the XCO2 simulated by CT by an amount of 0.61 ppm, whereas, OCO-2 XCO2 is lower than CT by 0.31 ppm on average, over Asia. The mean spatial correlations of 0.93 and 0.89 and average Root Mean Square Deviations (RMSDs) of 2.61 and 2.16 ppm were found between the CT and GOSAT, and CT and OCO-2, respectively, implying the existence of a good agreement between the CT and the other two satellites datasets. The spatial distribution of the datasets shows that the larger uncertainties exist over the southwest part of China. Over Asia, NOAA CT shows a good agreement with GOSAT and OCO-2 in terms of spatial distribution, monthly averaged time series, and seasonal climatology with small biases. These results suggest that CO2 can be used from either of the datasets to understand its role in the carbon budget, climate change, and air quality at regional to global scales.
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41
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Atmospheric Simulations of Total Column CO2 Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework. ATMOSPHERE 2020. [DOI: 10.3390/atmos11080787] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Quantifying the uncertainty of inversion-derived CO2 surface fluxes and attributing the uncertainty to errors in either flux or atmospheric transport simulations continue to be challenges in the characterization of surface sources and sinks of carbon dioxide (CO2). Despite recent studies inferring fluxes while using higher-resolution modeling systems, the utility of regional-scale models remains unclear when compared to existing coarse-resolution global systems. Here, we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic CO2 fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of CO2 introduced into WRF, effectively nesting our regional domain covering most of North America (except the northern half of Canada) within the CMS global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions (XCO2) over North America for 2010. We find mean model-model differences in summer of ∼0.12 ppm, significantly lower than the original coupling scheme (from 0.5 to 1.5 ppm, depending on the boundary). While 85% of the XCO2 values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850 hPa. Satellite data from GOSAT and tower and aircraft data are used to show that vertical transport above the Planetary Boundary Layer is responsible for significant model-model differences in the horizontal distribution of column XCO2 across North America.
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42
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Carbon Dioxide Retrieval from TanSat Observations and Validation with TCCON Measurements. REMOTE SENSING 2020. [DOI: 10.3390/rs12142204] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In this study we present the retrieval of the column-averaged dry air mole fraction of carbon dioxide (XCO2) from the TanSat observations using the ACOS (Atmospheric CO2 Observations from Space) algorithm. The XCO2 product has been validated with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON) for 2 years of TanSat data from 2017 to 2018. Based on the correlation of the XCO2 error over land with goodness of fit in three spectral bands at 0.76, 1.61 and 2.06 μm, we applied an a posteriori bias correction to TanSat retrievals. For overpass averaged results, XCO2 retrievals show a standard deviation (SD) of ~2.45 ppm and a positive bias of ~0.27 ppm compared to collocated TCCON sites. The validation also shows a relatively higher positive bias and variance against TCCON over high-latitude regions. Three cases to evaluate TanSat target mode retrievals are investigated, including one field campaign at Dunhuang with measurements by a greenhouse gas analyzer deployed on an unmanned aerial vehicle and two cases with measurements by a ground-based Fourier-transform spectrometer in Beijing. The results show the retrievals of all footprints, except footprint-6, have relatively low bias (within ~2 ppm). In addition, the orbital XCO2 distributions over Australia and Northeast China between TanSat and the second Orbiting Carbon Observatory (OCO-2) on 20 April 2017 are compared. It shows that the mean XCO2 from TanSat is slightly lower than that of OCO-2 with an average difference of ~0.85 ppm. A reasonable agreement in XCO2 distribution is found over Australia and Northeast China between TanSat and OCO-2.
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43
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Basu S, Lehman SJ, Miller JB, Andrews AE, Sweeney C, Gurney KR, Xu X, Southon J, Tans PP. Estimating US fossil fuel CO 2 emissions from measurements of 14C in atmospheric CO 2. Proc Natl Acad Sci U S A 2020; 117:13300-13307. [PMID: 32482875 PMCID: PMC7306993 DOI: 10.1073/pnas.1919032117] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
We report national scale estimates of CO2 emissions from fossil-fuel combustion and cement production in the United States based directly on atmospheric observations, using a dual-tracer inverse modeling framework and CO2 and [Formula: see text] measurements obtained primarily from the North American portion of the National Oceanic and Atmospheric Administration's Global Greenhouse Gas Reference Network. The derived US national total for 2010 is 1,653 ± 30 TgC yr-1 with an uncertainty ([Formula: see text]) that takes into account random errors associated with atmospheric transport, atmospheric measurements, and specified prior CO2 and 14C fluxes. The atmosphere-derived estimate is significantly larger ([Formula: see text]) than US national emissions for 2010 from three global inventories widely used for CO2 accounting, even after adjustments for emissions that might be sensed by the atmospheric network, but which are not included in inventory totals. It is also larger ([Formula: see text]) than a similarly adjusted total from the US Environmental Protection Agency (EPA), but overlaps EPA's reported upper 95% confidence limit. In contrast, the atmosphere-derived estimate is within [Formula: see text] of the adjusted 2010 annual total and nine of 12 adjusted monthly totals aggregated from the latest version of the high-resolution, US-specific "Vulcan" emission data product. Derived emissions appear to be robust to a range of assumed prior emissions and other parameters of the inversion framework. While we cannot rule out a possible bias from assumed prior Net Ecosystem Exchange over North America, we show that this can be overcome with additional [Formula: see text] measurements. These results indicate the strong potential for quantification of US emissions and their multiyear trends from atmospheric observations.
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Affiliation(s)
- Sourish Basu
- Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO 80305;
- Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309
| | - Scott J Lehman
- Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder CO 80309
| | - John B Miller
- Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO 80305
| | - Arlyn E Andrews
- Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO 80305
| | - Colm Sweeney
- Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO 80305
| | - Kevin R Gurney
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011
| | - Xiaomei Xu
- Keck Carbon Cycle AMS Facility, University of California, Irvine, CA 92697
| | - John Southon
- Keck Carbon Cycle AMS Facility, University of California, Irvine, CA 92697
| | - Pieter P Tans
- Global Monitoring Laboratory, National Oceanographic and Atmospheric Administration, Boulder, CO 80305
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44
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Yun J, Jeong S, Ho CH, Park H, Liu J, Lee H, Sitch S, Friedlingstein P, Lienert S, Lombardozzi D, Haverd V, Jain A, Zaehle S, Kato E, Tian H, Vuichard N, Wiltshire A, Zeng N. Enhanced regional terrestrial carbon uptake over Korea revealed by atmospheric CO 2 measurements from 1999 to 2017. GLOBAL CHANGE BIOLOGY 2020; 26:3368-3383. [PMID: 32125754 DOI: 10.1111/gcb.15061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 01/14/2020] [Accepted: 02/05/2020] [Indexed: 06/10/2023]
Abstract
Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long-term atmospheric CO2 concentration measurements at the Anmyeondo Station (36.53°N, 126.32°E) located in the western coast. The influence of terrestrial carbon flux on atmospheric CO2 concentrations (ΔCO2 ) is estimated from the difference of CO2 concentrations that were influenced by the land sector (through easterly winds) and the Yellow Sea sector (through westerly winds). We find a significant trend in ΔCO2 of -4.75 ppm per decade (p < .05) during the vegetation growing season (May through October), suggesting that the regional terrestrial carbon uptake has increased relative to the surrounding ocean areas. Combined analysis with satellite measured normalized difference vegetation index and gross primary production shows that the enhanced carbon uptake is associated with significant nationwide increases in vegetation and its production. Process-based terrestrial model and inverse model simulations estimate that regional terrestrial carbon uptake increases by up to 18.9 and 8.0 Tg C for the study period, accounting for 13.4% and 5.7% of the average annual domestic carbon emissions, respectively. Atmospheric chemical transport model simulations indicate that the enhanced terrestrial carbon sink is the primary reason for the observed ΔCO2 trend rather than anthropogenic emissions and atmospheric circulation changes. Our results highlight the fact that atmospheric CO2 measurements could open up the possibility of detecting regional changes in the terrestrial carbon cycle even where anthropogenic emissions are not negligible.
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Affiliation(s)
- Jeongmin Yun
- School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
| | - Sujong Jeong
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, Republic of Korea
| | - Chang-Hoi Ho
- School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
| | - Hoonyoung Park
- Department of Environmental Planning, Graduate School of Environmental Studies, Seoul National University, Seoul, Republic of Korea
| | - Junjie Liu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Haeyoung Lee
- Environmental Meteorology Research Division, National Institute of Meteorological Sciences, Jeju, Republic of Korea
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Sebastian Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Danica Lombardozzi
- Climate and Global Dynamics, Terrestrial Sciences Section, National Center for Atmospheric Research, Boulder, CO, USA
| | | | - Atual Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - Sönke Zaehle
- Biogeochemical Integration Department, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Etsushi Kato
- Research & Development Division, Institute of Applied Energy (IAE), Tokyo, Japan
| | - Hanqin Tian
- School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA
| | - Nicolas Vuichard
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre-Simon Laplace, CEA-CNRS-UVSQ, CE Orme des Merisiers, Gif-sur-Yvette CEDEX, France
| | | | - Ning Zeng
- Department of Atmospheric and Oceanic Science and Earth System Science, Interdisciplinary Center, University of Maryland, College Park, MD, USA
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Kondo M, Patra PK, Sitch S, Friedlingstein P, Poulter B, Chevallier F, Ciais P, Canadell JG, Bastos A, Lauerwald R, Calle L, Ichii K, Anthoni P, Arneth A, Haverd V, Jain AK, Kato E, Kautz M, Law RM, Lienert S, Lombardozzi D, Maki T, Nakamura T, Peylin P, Rödenbeck C, Zhuravlev R, Saeki T, Tian H, Zhu D, Ziehn T. State of the science in reconciling top-down and bottom-up approaches for terrestrial CO 2 budget. GLOBAL CHANGE BIOLOGY 2020; 26:1068-1084. [PMID: 31828914 DOI: 10.1111/gcb.14917] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 11/07/2019] [Accepted: 11/07/2019] [Indexed: 06/10/2023]
Abstract
Robust estimates of CO2 budget, CO2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: "top-down" atmospheric inversions and "bottom-up" biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere-biosphere CO2 exchange. Here, we conducted a thorough comparison of CO2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s. Regionally, improved agreement in CO2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink-source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO2 budgets.
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Affiliation(s)
- Masayuki Kondo
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
| | - Prabir K Patra
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
- Department of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
| | - Benjamin Poulter
- Biospheric Science Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD, USA
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Josep G Canadell
- Global Carbon Project, Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Canberra, ACT, Australia
| | - Ana Bastos
- Department of Geography, Ludwig-Maximilian University of Munich, Munich, Germany
| | | | - Leonardo Calle
- W.A. Franke College of Forestry & Conservation, University of Montana, Missoula, MT, USA
| | - Kazuhito Ichii
- Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - Peter Anthoni
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Almut Arneth
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Vanessa Haverd
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Canberra, ACT, Australia
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | - Markus Kautz
- Institute of Meteorology and Climate Research/Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Department of Forest Health, Forest Research Institute Baden-Württemberg, Freiburg, Germany
| | - Rachel M Law
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Aspendale, Vic., Australia
| | - Sebastian Lienert
- Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Danica Lombardozzi
- Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO, USA
| | - Takashi Maki
- Meteorological Research Institute, Tsukuba, Japan
| | | | - Philippe Peylin
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | | | - Ruslan Zhuravlev
- Central Aerological Observatory of Russian Hydromet Service, Moscow, Russia
| | - Tazu Saeki
- Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
| | - Hanqin Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA
| | - Dan Zhu
- Laboratoire des Sciences du Climat et de l'Environnement, Institut Pierre Simon Laplace, Gif-sur-Yvette, France
| | - Tilo Ziehn
- Commonwealth Scientific and Industrial Research Organisation-Oceans and Atmosphere, Aspendale, Vic., Australia
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46
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Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China. REMOTE SENSING 2020. [DOI: 10.3390/rs12040718] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO2 concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO2 dry air mole fraction (XCO2) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO2 changes during growing season for 13 years. We derived a relationship between XCO2 and surface net CO2 fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO2 flux enhancement based on satellite observed XCO2 changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO2 emissions, we estimated an enhanced XCO2 drawdown during the GP of −0.070 to −0.084 ppm yr−1. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO2 to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.
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Wu J, Wu H, Ding Y, Qin J, Li H, Liu S, Zeng D. Interannual and seasonal variations in carbon exchanges over an alpine meadow in the northeastern edge of the Qinghai-Tibet Plateau, China. PLoS One 2020; 15:e0228470. [PMID: 32045420 PMCID: PMC7012402 DOI: 10.1371/journal.pone.0228470] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 01/15/2020] [Indexed: 11/18/2022] Open
Abstract
The alpine meadow is highly sensitive to global climate change due to its high elevation and cold environment. To understand the dynamics of ecosystem carbon cycling, CO2 fluxes were measured over the Suli alpine meadow, which is located at the upper reach of the Shule River basin at the northeastern edge of the Qinghai-Tibet Plateau (QTP), China. The measurements were taken from October 2008 to September 2012 using the eddy covariance technique. Obvious seasonal and inter-annual variations were observed in the CO2 flux. The annual net carbon exchange ranged from -195.28 g·CO2·m-2 to -118.49 g·CO2·m-2, indicating that the alpine meadow ecosystem in this area played a role as a carbon sink. The inter-annual variability in the net carbon exchange was significantly related to the length of the growing season for the alpine meadow. The results showed that the months of June, July and August were the strongest CO2 absorption periods, while April, May and October were the strongest CO2 release periods. The annual net exchanges of CO2 in the four years were -118.49 g·CO2·m-2, -130.75 g·CO2·m-2, -195.83 g·CO2·m-2 and -160.65 g·CO2·m-2, and the average value was -151.43 g·CO2·m-2. On a seasonal scale, the monthly CO2 fluxes were largely controlled by temperature. At the annual scale, there was no dominant factor that influenced the interannual variations in the CO2 flux.
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Affiliation(s)
- Jinkui Wu
- Key Laboratory of Ecological Hydrology and Basin Sciences in Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China
| | - Hao Wu
- College of hydraulic science and engineering, Yangzhou University, Yangzhou, China
- * E-mail:
| | - Yongjian Ding
- Key Laboratory of Ecological Hydrology and Basin Sciences in Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China
| | - Jia Qin
- Key Laboratory of Ecological Hydrology and Basin Sciences in Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Hongyuan Li
- Key Laboratory of Ecological Hydrology and Basin Sciences in Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Shiwei Liu
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China
| | - Di Zeng
- Key Laboratory of Ecological Hydrology and Basin Sciences in Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
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48
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Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method. REMOTE SENSING 2020. [DOI: 10.3390/rs12030576] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Column-averaged dry air mole fraction of atmospheric CO2 (XCO2), obtained by multiple satellite observations since 2003 such as ENVISAT/SCIAMACHY, GOSAT, and OCO-2 satellite, is valuable for understanding the spatio-temporal variations of atmospheric CO2 concentrations which are related to carbon uptake and emissions. In order to construct long-term spatio-temporal continuous XCO2 from multiple satellites with different temporal and spatial periods of observations, we developed a precision-weighted spatio-temporal kriging method for integrating and mapping multi-satellite observed XCO2. The approach integrated XCO2 from different sensors considering differences in vertical sensitivity, overpass time, the field of view, repeat cycle and measurement precision. We produced globally mapped XCO2 (GM-XCO2) with spatial/temporal resolution of 1 × 1 degree every eight days from 2003 to 2016 with corresponding data precision and interpolation uncertainty in each grid. The predicted GM-XCO2 precision improved in most grids compared with conventional spatio-temporal kriging results, especially during the satellites overlapping period (0.3–0.5 ppm). The method showed good reliability with R2 of 0.97 from cross-validation. GM-XCO2 showed good accuracy with a standard deviation of bias from total carbon column observing network (TCCON) measurements of 1.05 ppm. This method has potential applications for integrating and mapping XCO2 or other similar datasets observed from multiple satellite sensors. The resulting GM-XCO2 product may be also used in different carbon cycle research applications with different precision requirements.
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Liu Z, Kimball JS, Parazoo NC, Ballantyne AP, Wang WJ, Madani N, Pan CG, Watts JD, Reichle RH, Sonnentag O, Marsh P, Hurkuck M, Helbig M, Quinton WL, Zona D, Ueyama M, Kobayashi H, Euskirchen ES. Increased high-latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition. GLOBAL CHANGE BIOLOGY 2020; 26:682-696. [PMID: 31596019 DOI: 10.1111/gcb.14863] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 07/21/2019] [Indexed: 06/10/2023]
Abstract
Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.
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Affiliation(s)
- Zhihua Liu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - John S Kimball
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - Nicholas C Parazoo
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | - Wen J Wang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Nima Madani
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Caleb G Pan
- Numerical Terradynamic Simulation Group, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT, USA
| | | | | | - Oliver Sonnentag
- Département de géographie and Centre d'études nordiques, Université de Montréal, Montreal, QC, Canada
| | - Philip Marsh
- Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, ON, Canada
| | - Miriam Hurkuck
- Département de géographie and Centre d'études nordiques, Université de Montréal, Montreal, QC, Canada
| | - Manuel Helbig
- School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada
| | - William L Quinton
- Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, ON, Canada
| | - Donatella Zona
- Global Change Research Group, Department of Biology, San Diego State University, San Diego, CA, USA
| | - Masahito Ueyama
- Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Sakai, Japan
| | - Hideki Kobayashi
- Institute of Arctic Climate and Environment Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
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Park C, Park SY, Gurney KR, Gerbig C, DiGangi JP, Choi Y, Lee HW. Numerical simulation of atmospheric CO2 concentration and flux over the Korean Peninsula using WRF-VPRM model during Korus-AQ 2016 campaign. PLoS One 2020; 15:e0228106. [PMID: 31978112 PMCID: PMC6980530 DOI: 10.1371/journal.pone.0228106] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 01/07/2020] [Indexed: 11/18/2022] Open
Abstract
We conducted regional scale CO2 simulations using the Weather Research and Forecasting model (WRF) coupled with the Vegetation Photosynthesis and Respiration Model (VPRM). We contrasted simulated concentrations with column, ground and aircraft observations during the Korea-United States Air Quality (KORUS-AQ) 2016 field campaign. Overall, WRF-VPRM slightly underestimates CO2 concentrations at ground and column monitoring sites, but it significantly underestimates at an inland tower measurement site, especially within the stable (nocturnal) boundary layer in nighttime. The model successfully captures the airborne vertical profiles but showed a large offset within the planetary boundary layer (PBL) in the areas surrounding Seoul and around the Taeahn point source emissions in the west coastal area of the Korean Peninsula. A case study flight intended to capture Chinese influence observed no clear signals of long-range transport of CO2, due mainly to the much larger magnitude of background CO2 concentrations. The calculated Net Ecosystem Exchange (NEE) with flux measurements at a tower site in the South Korean Peninsula has also been evaluated comparing with CO2 flux measurements at a flux tower site, resulting in the underestimation by less than a factor of 1.
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Affiliation(s)
- Changhyoun Park
- Institute of Environmental Studies, Pusan National University, Busan, South Korea
- * E-mail:
| | - Soon-Young Park
- Department of Atmospheric Environmental Sciences, Pusan National University, Busan, South Korea
| | - Kevin R. Gurney
- School of Life Sciences, Arizona State University, Arizona, United States of America
| | - Christoph Gerbig
- Department Biogeochemical Systems, Max Plank Institute for Biogeochemistry, Jena, Germany
| | - Joshua P. DiGangi
- National Aeronautics and Space Langley Research Center, Hampton, Virginia, United States of America
| | - Yonghoon Choi
- National Aeronautics and Space Langley Research Center, Hampton, Virginia, United States of America
| | - Hwa Woon Lee
- Department of Atmospheric Environmental Sciences, Pusan National University, Busan, South Korea
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