A spatial uncertainty metric for anthropogenic CO<sub>2</sub>emissions

Woodard, D.; Branham, Meredith; Buckingham, G.; Hogue, S.; Hutchins, M.; Gosky, Ross; Marland, Gregg; Marland, Eric

doi:10.1080/20430779.2014.1000793

Cited by 13 publications

(27 citation statements)

References 7 publications

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“…If this result can be verified elsewhere and if a robust large point source database can be developed at appropriate spatial and temporal scales, this may lead to better global maps of FFCO2 emissions. While current large point source databases have known spatial deficiencies (e.g., Oda and Maksyutov, 2011;Nassar et al, 2013;Woodard et al, 2015), these spatial deficiencies can be overcome with additional geolocation efforts. Current large point source databases are usually based on a certain point in time and offer little to no temporal information.…”

Section: Discussionmentioning

confidence: 99%

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

2016

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Abstract. Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4-190 %, with an average of 120 % (2σ ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

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Section: Discussionmentioning

confidence: 99%

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

2016

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“…PSUM can be treated similarly to a standard deviation and has the same units. Our measures of spatial uncertainty are thus the derived PSUM values as described in Woodard et al [] (see Figure ).…”

Section: Uncertainty For a Modified Gridded Cdiac Data Setmentioning

confidence: 99%

Uncertainty in gridded CO₂ emissions estimates

et al. 2016

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We are interested in the spatial distribution of fossil-fuel-related emissions of CO 2 for both geochemical and geopolitical reasons, but it is important to understand the uncertainty that exists in spatially explicit emissions estimates. Working from one of the widely used gridded data sets of CO 2 emissions, we examine the elements of uncertainty, focusing on gridded data for the United States at the scale of 1 ∘ latitude by 1 ∘ longitude. Uncertainty is introduced in the magnitude of total United States emissions, the magnitude and location of large point sources, the magnitude and distribution of non-point sources, and from the use of proxy data to characterize emissions. For the United States, we develop estimates of the contribution of each component of uncertainty. At 1 ∘ resolution, in most grid cells, the largest contribution to uncertainty comes from how well the distribution of the proxy (in this case population density) represents the distribution of emissions. In other grid cells, the magnitude and location of large point sources make the major contribution to uncertainty. Uncertainty in population density can be important where a large gradient in population density occurs near a grid cell boundary. Uncertainty is strongly scale-dependent with uncertainty increasing as grid size decreases. Uncertainty for our data set with 1 ∘ grid cells for the United States is typically on the order of ±150%, but this is perhaps not excessive in a data set where emissions per grid cell vary over 8 orders of magnitude.

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“…In the USA, the eGRID data set covers only 10 of the years in the 1996-2010 interval Woodard et al 2014 show also that even in the USA we have to deal with both locational and magnitude uncertainty. This analysis shows that at spatial resolutions of 1°or greater different analytical approaches yield highly correlated results, but at higher spatial resolution, estimates of emissions will carry high uncertainty until LPS can be well characterized.…”

Section: Discussionmentioning

confidence: 98%

A comparison of five high-resolution spatially-explicit, fossil-fuel, carbon dioxide emission inventories for the United States

Hutchins

Colby

Marland

et al. 2016

Mitig Adapt Strateg Glob Change

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The quantification of fossil-fuel-related emissions of carbon dioxide to the atmosphere is necessary in order to accurately represent carbon cycle fluxes and to understand and project the details of the global carbon cycle. In addition, the monitoring, reporting, and verification (MRV) of carbon dioxide emissions is necessary for the success of international agreements to reduce emissions. However, existing fossil-fuel carbon dioxide (FFCO 2 ) emissions inventories vary in terms of the data and methods used to estimate and distribute FFCO 2 . This paper compares how the approaches used to create spatially explicit FFCO 2 emissions inventories affect the spatial distribution of emissions estimates and the magnitude of emissions estimates in specific locales. Five spatially explicit FFCO 2 emission inventories were compared: Carbon Dioxide Information and Analysis Center (CDIAC), Emission Database for Global Atmospheric Research (EDGAR), Fossil Fuel Data Assimilation System (FFDAS), Opensource Data Inventory for Anthropogenic CO 2 (ODIAC), and Vulcan. The effects of using specific data and approaches in the creation of spatially explicit FFCO 2 emissions inventories, and the effect of resolution on data representation are analyzed using graphical, numerical, and cartographic approaches. We examined the effect of using top-down versus bottom-up Mitig Adapt Strateg Glob Change approaches, nightlights versus population proxies, and the inclusion of large point sources. The results indicate that the approach used to distribute emissions in space creates distinct patterns in the distribution of emissions estimates and hence in the estimates of emissions in specific locations. The different datasets serve different purposes but collectively show the key role of large point sources and urban centers and the strong relationship between scale and uncertainty.

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A spatial uncertainty metric for anthropogenic CO₂emissions

Cited by 13 publications

References 7 publications

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Uncertainty in gridded CO₂ emissions estimates

A comparison of five high-resolution spatially-explicit, fossil-fuel, carbon dioxide emission inventories for the United States

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A spatial uncertainty metric for anthropogenic CO2emissions

Cited by 13 publications

References 7 publications

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Uncertainty in gridded CO2 emissions estimates

A comparison of five high-resolution spatially-explicit, fossil-fuel, carbon dioxide emission inventories for the United States

Contact Info

Product

Resources

About

A spatial uncertainty metric for anthropogenic CO₂emissions

Uncertainty in gridded CO₂ emissions estimates