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Abdallah C, Lauvaux T, Lian J, Bréon FM, Ramonet M, Laurent O, Ciais P, Denier van der Gon HAC, Dellaert S, Perrussel O, Baudic A, Utard H, Gros V. A Gradient-Descent Optimization of CO 2-CO-NO x Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:302-314. [PMID: 38114451 DOI: 10.1021/acs.est.3c00566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.
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Affiliation(s)
- Charbel Abdallah
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Groupe de Spectrométrie Moléculaire et Atmosphérique GSMA, Université de Reims-Champagne Ardenne, UMR CNRS 7331, Moulin de la Housse, BP 1039, 51687 Reims 2, France
| | - Thomas Lauvaux
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Groupe de Spectrométrie Moléculaire et Atmosphérique GSMA, Université de Reims-Champagne Ardenne, UMR CNRS 7331, Moulin de la Housse, BP 1039, 51687 Reims 2, France
| | - Jinghui Lian
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Origins.earth, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense Cedex 6, France
| | - François-Marie Bréon
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Michel Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Olivier Laurent
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | | | - Stijn Dellaert
- Department of Climate, Air and Sustainability, TNO, P.O. Box 80015, 3508 TA Utrecht, The Netherlands
| | - Olivier Perrussel
- Association de Surveillance de la Qualité de l'Air en Île-de-France (AIRPARIF), 75004 Paris, France
| | - Alexia Baudic
- Association de Surveillance de la Qualité de l'Air en Île-de-France (AIRPARIF), 75004 Paris, France
| | - Hervé Utard
- Origins.earth, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense Cedex 6, France
| | - Valérie Gros
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
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Lian J, Lauvaux T, Utard H, Bréon FM, Broquet G, Ramonet M, Laurent O, Albarus I, Cucchi K, Ciais P. Assessing the Effectiveness of an Urban CO 2 Monitoring Network over the Paris Region through the COVID-19 Lockdown Natural Experiment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:2153-2162. [PMID: 35080881 DOI: 10.1021/acs.est.1c04973] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The Paris metropolitan area, the largest urban region in the European Union, has experienced two national COVID-19 confinements in 2020 with different levels of restrictions on mobility and economic activity, which caused reductions in CO2 emissions. To quantify the timing and magnitude of daily emission reductions during the two lockdowns, we used continuous atmospheric CO2 monitoring, a new high-resolution near-real-time emission inventory, and an atmospheric Bayesian inverse model. The atmospheric inversion estimated the changes in fossil fuel CO2 emissions over the Greater Paris region during the two lockdowns, in comparison with the same periods in 2018 and 2019. It shows decreases by 42-53% during the first lockdown with stringent measures and by only 20% during the second lockdown when traffic reduction was weaker. Both lockdown emission reductions are mainly due to decreases in traffic. These results are consistent with independent estimates based on activity data made by the city environmental agency. We also show that unusual persistent anticyclonic weather patterns with north-easterly winds that prevailed at the start of the first lockdown period contributed a substantial drop in measured CO2 concentration enhancements over Paris, superimposed on the reduction of urban CO2 emissions. We conclude that atmospheric CO2 monitoring makes it possible to identify significant emission changes (>20%) at subannual time scales over an urban region.
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Affiliation(s)
- Jinghui Lian
- Origins.S.A.S, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense, Cedex, France
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Thomas Lauvaux
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Hervé Utard
- Origins.S.A.S, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense, Cedex, France
| | - François-Marie Bréon
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Grégoire Broquet
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Michel Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Olivier Laurent
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Ivonne Albarus
- Origins.S.A.S, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense, Cedex, France
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
| | - Karina Cucchi
- Origins.S.A.S, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense, Cedex, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif sur Yvette, Cedex, France
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus
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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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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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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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Liu Y, Yue T, Zhang L, Zhao N, Zhao M, Liu Y. Simulation and analysis of XCO 2 in North China based on high accuracy surface modeling. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2018; 25:27378-27392. [PMID: 30033484 PMCID: PMC6132398 DOI: 10.1007/s11356-018-2683-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 06/29/2018] [Indexed: 06/08/2023]
Abstract
As an important cause of global warming, CO2 concentrations and their changes have aroused worldwide concern. Establishing explicit understanding of the spatial and temporal distributions of CO2 concentrations at regional scale is a crucial technical problem for climate change research. High accuracy surface modeling (HASM) is employed in this paper using the output of the CO2 concentrations from weather research and forecasting-chemistry (WRF-CHEM) as the driving fields, and the greenhouse gases observing satellite (GOSAT) retrieval XCO2 data as the accuracy control conditions to obtain high accuracy XCO2 fields. WRF-CHEM is an atmospheric chemical transport model designed for regional studies of CO2 concentrations. Verified by ground- and space-based observations, WRF-CHEM has a limited ability to simulate the conditions of CO2 concentrations. After conducting HASM, we obtain a higher accuracy distribution of the CO2 in North China than those calculated using the classical Kriging and inverse distance weighted (IDW) interpolation methods, which were often used in past studies. The cross-validation also shows that the averaging mean absolute error (MAE) of the results from HASM is 1.12 ppmv, and the averaging root mean square error (RMSE) is 1.41 ppmv, both of which are lower than those of the Kriging and IDW methods. This study also analyses the space-time distributions and variations of the XCO2 from the HASM results. This analysis shows that in February and March, there was the high value zone in the southern region of study area relating to heating in the winter and the dense population. The XCO2 concentration decreased by the end of the heating period and during the growing period of April and May, and only some relatively high value zones continued to exist.
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Affiliation(s)
- Yu Liu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Tianxiang Yue
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Lili Zhang
- Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101 China
| | - Na Zhao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Miaomiao Zhao
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Yi Liu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
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Liu Z, Bambha RP, Pinto JP, Zeng T, Boylan J, Huang M, Lei H, Zhao C, Liu S, Mao J, Schwalm CR, Shi X, Wei Y, Michelsen HA. Toward verifying fossil fuel CO2 emissions with the CMAQ model: motivation, model description and initial simulation. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2014; 64:419-435. [PMID: 24843913 DOI: 10.1080/10962247.2013.816642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
UNLABELLED Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2 spatiotemporal variability and verify CO2 fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2 simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere-atmosphere exchange, and meteorology in regulating the spatial distribution of CO2 near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2 concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver CO, the CMAQ model using hourly varying, high-resolution CO2 fossil-fuel emissions from the Vulcan inventory and Carbon Tracker optimized NEE reproduced the observed diurnal profile of CO2 reasonably well but with a low bias in the early morning. The spatial distribution of CO2 was found to correlate with NO(x), SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2 observations and understand CO2 variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2 source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2 spatiotemporal variability and various uncertainties in the future. IMPLICATIONS Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant.
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