Advances in quantifying power plant CO2 emissions with OCO-2

Nassar, Ray; Mastrogiacomo, Jon-Paul; Bateman-Hemphill, William; McCracken, Callum; MacDonald, Cameron G.; Hill, Tim; O’Dell, C.; Kiel, Matthäus; Crisp, David

doi:10.1016/j.rse.2021.112579

Cited by 79 publications

(70 citation statements)

References 23 publications

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“…Inverse systems designed to constrain fluxes on these scales typically incorporate a global chemical transport model that assimilates estimates of the atmospheric CO 2 dry air mole fraction with an optimization algorithm that derives estimates of the net surface CO 2 fluxes needed to match the observed CO 2 distribution to within its uncertainties in the presence of the imposed wind field (Baker, Doney, & Schimel, 2006; Bousquet et al., 2000; Enting, 2002; Enting et al., 1995; Peters et al., 2005). Studies of anthropogenic emissions from point sources or large urban areas typically employ simpler emission plume mass balance models (Nassar et al., 2017, 2021; Reuter et al., 2019; Varon et al., 2018) although some use more sophisticated inverse models with Eulerian (Lei et al., 2021; Ye et al., 2020) or Lagrangian transport schemes (Wu et al., 2018). Both types of systems are summarized here.…”

Section: The Atmospheric Carbon Cyclementioning

confidence: 99%

“…Space-based sensors do not yet have the coverage needed to track all local sources, but they do provide opportunities to assess the precision that could be delivered by future space-based instruments. For example, Nassar et al (2017Nassar et al ( , 2021 used OCO-2 XCO 2 estimates to quantify emissions from individual coal-fired power plants (Figure 4). They combine these estimates with wind speed and direction from ERA-5 (Hersbach et al, 2020) and MERRA-2 (Molod et al, 2015) in a simple Gaussian plume model to estimate the fluxes.…”

Section: Constraining Atmospheric Co 2 Emissions From Local Sourcesmentioning

confidence: 99%

“…These new measurement capabilities are also driving the development of atmospheric inverse systems, spawning a new series of multi-model intercomparison experiments that use only ground-based and airborne in situ observations, space-based measurements, or both (Chevallier et al, 2019;Ciais et al, 2022;Ciais, Yao, et al, 2020; Nassar et al [2021]). Crowell et al, 2019;Houweling et al, 2015;Kondo et al, 2020;Peiro et al, 2022).…”

Section: Constraining Atmospheric Co 2 Emissions From Local Sourcesmentioning

confidence: 99%

“…For example, Nassar et al. (2017, 2021) used OCO‐2 XCO 2 estimates to quantify emissions from individual coal‐fired power plants (Figure 4). They combine these estimates with wind speed and direction from ERA‐5 (Hersbach et al., 2020) and MERRA‐2 (Molod et al., 2015) in a simple Gaussian plume model to estimate the fluxes.…”

Section: The Atmospheric Carbon Cyclementioning

confidence: 99%

“…Bottom‐up methods use empirical or process‐based models to estimate fluxes, or to upscale in situ measurements of the time change of stocks or of direct flux observations of the oceans (e.g., Carroll et al., 2020; Doney et al., 2004; Gregor et al., 2019; Gruber, Clement, et al., 2019; Hauck et al., 2020; Landschützer et al., 2013; Long et al., 2013; Rödenbeck et al., 2014, 2015; Sabine et al., 2004; Watson et al., 2020) or land biosphere (Hubau et al., 2020; Jung et al., 2020; Pan et al., 2011; Piao, Wang, Wang, et al., 2020; Sitch et al., 2015). “Top‐down” models use inverse methods to estimate the surface CO 2 fluxes from the land or ocean needed to match the observed atmospheric or ocean CO 2 concentrations, within their uncertainties, in the presence of the prevailing winds and ocean circulation (e.g., Chevallier et al., 2010, 2019; Crowell et al., 2019; DeVries, 2014; Enting et al., 1995; Jacobson et al., 2007; Khatiwala et al., 2009; Mikaloff Fletcher et al., 2006; Nassar et al., 2021; Wu et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

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How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle?

Crisp

Dolman

Tanhua

et al. 2022

Reviews of Geophysics

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Fossil fuel combustion, land use change and other human activities have increased the atmospheric carbon dioxide (CO2) abundance by about 50% since the beginning of the industrial age. The atmospheric CO2 growth rates would have been much larger if natural sinks in the land biosphere and ocean had not removed over half of this anthropogenic CO2. As these CO2 emissions grew, uptake by the ocean increased in response to increases in atmospheric CO2 partial pressure (pCO2). On land, gross primary production also increased, but the dynamics of other key aspects of the land carbon cycle varied regionally. Over the past three decades, CO2 uptake by intact tropical humid forests declined, but these changes are offset by increased uptake across mid‐ and high‐latitudes. While there have been substantial improvements in our ability to study the carbon cycle, measurement and modeling gaps still limit our understanding of the processes driving its evolution. Continued ship‐based observations combined with expanded deployments of autonomous platforms are needed to quantify ocean‐atmosphere fluxes and interior ocean carbon storage on policy‐relevant spatial and temporal scales. There is also an urgent need for more comprehensive measurements of stocks, fluxes and atmospheric CO2 in humid tropical forests and across the Arctic and boreal regions, which are experiencing rapid change. Here, we review our understanding of the atmosphere, ocean, and land carbon cycles and their interactions, identify emerging measurement and modeling capabilities and gaps and the need for a sustainable, operational framework to ensure a scientific basis for carbon management.

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Section: The Atmospheric Carbon Cyclementioning

confidence: 99%

Section: Constraining Atmospheric Co 2 Emissions From Local Sourcesmentioning

confidence: 99%

Section: Constraining Atmospheric Co 2 Emissions From Local Sourcesmentioning

confidence: 99%

Section: The Atmospheric Carbon Cyclementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle?

Crisp

Dolman

Tanhua

et al. 2022

Reviews of Geophysics

Self Cite

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How Well Do We Understand the Land-Ocean-Atmosphere Carbon Cycle?

Crisp

Dolman

Tanhua

et al. 2021

Preprint

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Since the beginning of the industrial age, human activities have increased the atmospheric concentrations of carbon dioxide (CO 2 ) and other greenhouse gases (GHGs) to levels never before seen in human history. These large increases are driving climate change because CO 2 is an efficient greenhouse gas with atmospheric residence times spanning years to millennia (see Box 6.1 of Ciais et al. [2013]). Bottom-up statistical inventories indicate that fossil fuel combustion, industry, agriculture, forestry, and other human activities are now adding more than 11.5 Pg of carbon (Pg C) to the atmosphere each year (Friedlingstein et al., 2019(Friedlingstein et al., , 2020(Friedlingstein et al., , 2021. Direct measurements of CO 2 in the atmosphere and in air bubbles in ice cores (Etheridge et al., 1996) indicate that human activities have increased the globally averaged atmospheric CO 2 dry air mole fraction from less than 277 parts

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Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network (LUCCN): First Integrated Campaign in China

Yang,

Zhao,

Yao

et al. 2023

Adv. Atmos. Sci.

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In this study, we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network (LUCCN) prototype. The LUCCN primarily consists of two categories of instruments, including ground-based and UAV-based in-situ measurement. We use the GMP343, a low-cost non-dispersive infrared sensor, in both ground-based and UAV-based instruments. The first integrated measurement campaign took place in Shenzhen, China, 4 May 2023. During the campaign, we found that LUCCN's UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources, which was especially obvious at a gas power plant in Shenzhen. The emission flux was calculated by a crosssectional flux (CSF) method, the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC). The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross section. The LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information, especially in scenarios involving the detection of smaller-scale, rapidly varying sources and sinks.

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Advances in quantifying power plant CO2 emissions with OCO-2

Cited by 79 publications

References 23 publications

How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle?

How Well Do We Understand the Land‐Ocean‐Atmosphere Carbon Cycle?

How Well Do We Understand the Land-Ocean-Atmosphere Carbon Cycle?

Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network (LUCCN): First Integrated Campaign in China

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