On the impact of granularity of space-based urban CO2 emissions in urban atmospheric inversions: A case study for Indianapolis, IN

Oda, Tomohiro; Lauvaux, Thomas; Lu, Dengsheng; Rao, Preeti; Miles, N. L.; Richardson, Scott J.; Gurney, K. R.

doi:10.1525/elementa.146

Cited by 42 publications

(43 citation statements)

References 34 publications

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“…The Open‐source Data Inventory for Atmospheric Carbon dioxide (ODIAC) Version 2015a (Oda et al, 2017; 2018; Oda & Maksyutov, 2011, 2015) is used in this paper for emissions from the cities of interest. The ODIAC emission product provides 1‐km × 1‐km gridded global and monthly ffCO 2 emissions.…”

Section: Methodsmentioning

confidence: 99%

Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Lauvaux

Kort

et al. 2020

JGR Atmospheres

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Satellite observations of the total column dry-air CO 2 (X CO2 ) are expected to support the quantification and monitoring of fossil fuel CO 2 (ffCO 2 ) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO-2) X CO2 retrievals to optimize whole-city emissions, using a Bayesian inversion system and high-resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: "plume city" located in relatively flat terrain, represented by Riyadh and Cairo; and "basin city" located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least numbers of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 8, 5, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffX CO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local X CO2 enhancements associated with local biospheric X CO2 variations are shown, which potentially lead to biased estimates of ffCO 2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO 2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.

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Section: Methodsmentioning

confidence: 99%

Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Lauvaux

Kort

et al. 2020

JGR Atmospheres

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“…Future studies on emission comparisons should address the impact of uncertainties in spatial structures or missing point sources in CO 2ff emission products, similar to (Oda et al, 2017a) gradients (Ware et al, 2016). Recent urban modeling studies (e.g.…”

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confidence: 99%

Constraining fossil fuel CO<sub>2</sub> emissions from urban area using OCO-2 observations of total column CO<sub>2</sub>

Lauvaux

Kort

et al. 2017

Preprint

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Abstract. Expanding urban populations and the significant contribution of cities to global fossil-fuel CO 2 (CO 2ff ) emissions emphasize the necessity of achieving independent and accurate quantifications of the emissions from urban area. In this paper, we assess the utility of total column dry air CO 2 mole fraction (X CO2 ) data retrieved from NASA's Orbiting Carbon Observatory 2 (OCO-2) observations to quantify CO 2ff emissions from cities. Observing System Simulation Experiments (OSSEs) are implemented by forward modeling of meteorological fields and column X CO2 . The impact of transport model 15 errors on the inverse emissions estimates is examined for two -plume cities‖ (Riyadh, Cairo) and a -basin city‖ (Los Angeles metropolitan region, LA). The pseudo data experiments indicate convergence of emission uncertainties related to transport model errors with increasing amount of observations. The 1-σ uncertainty of emission estimates is constrained to approximately 15%/5% with about 10 pseudo tracks for plume city/basin city. The systematic wind speed biases in simulated wind fields for LA lead to overestimations in total CO 2ff emission, which require data assimilation to improve high-resolution 20 atmospheric transport. The contribution of biogenic fluxes gradients in urban and rural area of Pearl River Delta metropolitan region in China are examined by simulations with biospheric fluxes imposed by the Net Ecosystem Exchange (NEE) from multiple terrestrial biosphere models, which show about 24±21% (1σ) and 19±15% (1σ) contributions to the total X CO2 enhancements for the two cases examined. The representations of transport model errors for the emission optimization are examined for Riyadh, Cairo and LA in real cases. The determination of background X CO2 is discussed for LA by using constant 25 and simulated background with biospheric fluxes included, demonstrating the need of careful consideration of the variations in background X CO2 for identifying concentration enhancements due to fossil fuel emissions.

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“…Based on the high-resolution energy-related CO 2 emissions data, the Indianapolis Flux Experiment (INFLUX) project was conducted by integrating the data of the high-resolution CO 2 emissions inventory, tower monitoring, and aircraft monitoring to explore ways to reduce uncertainties and establish the Measurement, Reporting, and Verifying (MRV) system. The results indicate that high-resolution energy-related CO 2 inventory data based on the bottom-up method, combined with the atmospheric inversion method, can be used to more accurately predict regional CO 2 emissions trends [22,23].…”

Section: Introductionmentioning

confidence: 97%

Analyzing Temporal and Spatial Characteristics and Determinant Factors of Energy-Related CO2 Emissions of Shanghai in China Using High-Resolution Gridded Data

et al. 2019

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In this study, we create a high-resolution (1 km x 1 km) carbon emission spatially gridded dataset in Shanghai for 2010 to 2015 to help researchers understand the spatial pattern of urban CO 2 emissions and facilitate exploration of their driving forces. First, we conclude that high spatial agglomeration, CO 2 emissions centralized along the river and coastline, and a structure with three circular layers are the three notable temporal-spatial characteristics of Shanghai fossil fuel CO 2 emissions. Second, we find that large point sources are the leading factors that shaped the temporal-spatial characteristics of Shanghai CO 2 emission distributions. The changes of CO 2 emissions in each grid during 2010-2015 indicate that the energy-controlling policies of large point emission sources have had positive effects on CO 2 reduction since 2012. The changes suggest that targeted policies can have a disproportionate impact on urban emissions. Third, area sources bring more uncertainties to the forecasting of carbon emissions. We use the Geographical Detector method to identify these leading factors that influence CO 2 emissions emitted from area sources. We find that Shanghai's circular layer structure, population density, and population activity intensity are the leading factors. This result implied that urban planning has a large impact on the distribution of urban CO 2 emissions. At last, we find that unbalanced development within the city will lead to different leading impact factors for each circular layer. Factors such as urban development intensity, traffic land, and industrial land have stronger power to determine CO 2 emissions in the areas outside the Outer Ring, while factors such as population density and population activity intensity have stronger impacts in the other two inner areas. This research demonstrates the potential utility of high-resolution carbon emission data to advance the integration of urban planning for the reduction of urban CO 2 emissions and provide information for policymakers to make targeted policies across different areas within the city.

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On the impact of granularity of space-based urban CO2 emissions in urban atmospheric inversions: A case study for Indianapolis, IN

Abstract: Oda et al: On the impact of granularity of space-based urban CO 2 emissions in urban atmospheric inversions Art. 28, page 2 of 12

Cited by 42 publications

References 34 publications

Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Constraining fossil fuel CO<sub>2</sub> emissions from urban area using OCO-2 observations of total column CO<sub>2</sub>

Analyzing Temporal and Spatial Characteristics and Determinant Factors of Energy-Related CO2 Emissions of Shanghai in China Using High-Resolution Gridded Data

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On the impact of granularity of space-based urban CO2 emissions in urban atmospheric inversions: A case study for Indianapolis, IN

Abstract: Oda et al: On the impact of granularity of space-based urban CO 2 emissions in urban atmospheric inversions Art. 28, page 2 of 12

Cited by 42 publications

References 34 publications

Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2

Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2

Constraining fossil fuel CO&lt;sub&gt;2&lt;/sub&gt; emissions from urban area using OCO-2 observations of total column CO&lt;sub&gt;2&lt;/sub&gt;

Analyzing Temporal and Spatial Characteristics and Determinant Factors of Energy-Related CO2 Emissions of Shanghai in China Using High-Resolution Gridded Data

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Product

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Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Constraining Fossil Fuel CO₂ Emissions From Urban Area Using OCO‐2 Observations of Total Column CO₂

Constraining fossil fuel CO<sub>2</sub> emissions from urban area using OCO-2 observations of total column CO<sub>2</sub>