scholarly journals A remote sensing technique for global monitoring of power plant CO<sub>2</sub> emissions from space and related applications

2010 ◽  
Vol 3 (4) ◽  
pp. 781-811 ◽  
Author(s):  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
M. Reuter ◽  
T. Krings ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Wind Speed ◽  
Power Plant ◽  
Co2 Emissions ◽  
Kyoto Protocol ◽  
Inverse Modeling ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Independent Verification ◽  
Anthropogenic Co2

Abstract. Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas (GHG) causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times – primarily due to burning of fossil fuels – and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing satellite instruments such as SCIAMACHY/ENVISAT and TANSO/GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also constrain anthropogenic CO2 emissions. Here we present a promising satellite remote sensing concept based on spectroscopic measurements of reflected solar radiation and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the atmospheric CO2 column distribution at a spatial resolution of 2×2 km2 with a precision of 0.5% (2 ppm) or better. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with a swath width of 500 km, each power plant (PP) is overflown every 6 days or more frequent. Based on the MODIS cloud mask data product we conservatively estimate that typically 20 sufficiently cloud free overpasses per PP can be achieved every year. We found that for typical wind speeds in the range of 2–6 m/s the statistical uncertainty of the retrieved PP CO2 emission due to instrument noise is in the range 1.6–4.8 MtCO2/yr for single overpasses. This corresponds to 12–36% of the emission of a mid-size PP (13 MtCO2/yr). We have also determined the sensitivity to parameters which may result in systematic errors such as atmospheric transport and aerosol related parameters. We found that the emission error depends linearly on wind speed, i.e., a 10% wind speed error results in a 10% emission error, and that neglecting enhanced aerosol concentrations in the PP plume may result in errors in the range 0.2–2.5 MtCO2/yr, depending on PP aerosol emission. The discussed concept has the potential to contribute to an independent verification of reported anthropogenic CO2 emissions and therefore could be an important component of a future global anthropogenic GHG emission monitoring system. This is of relevance in the context of Kyoto protocol follow-on agreements but also allows detection and monitoring of a variety of other strong natural and anthropogenic CO2 and CH4 emitters. The investigated instrument is not limited to these applications as it has been specified to also deliver the data needed for global regional-scale CO2 and CH4 surface flux inverse modeling.

scholarly journals A remote sensing technique for global monitoring of power plant CO<sub>2</sub> emissions from space and related applications

2010 ◽  
Vol 3 (1) ◽  
pp. 55-110 ◽  
Author(s):  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
M. Reuter ◽  
T. Krings ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Power Plant ◽  
Greenhouse Gas ◽  
Co2 Emissions ◽  
Kyoto Protocol ◽  
Inverse Modeling ◽  
Co2 Emission ◽  
Power Plants ◽  
Independent Verification ◽  
Anthropogenic Co2

Abstract. Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times – primarily due to burning of fossil fuels – and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing greenhouse gas observing satellites such as SCIAMACHY and GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also measure anthropogenic CO2 emissions. Here we present a promising satellite remote sensing technology based on spectroscopic measurements of reflected solar radiation in the short-wave infrared (SWIR) and near-infrared (NIR) spectral regions and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the CO2 column distribution at a spatial resolution of 2×2 km2 or better with a precision of about 0.5% (2 ppm) or better of the background column. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with an across-track swath width of 500 km each power plant is overflown every 6 days or faster. Based on clear sky statistics we conservatively estimate that about one useful measurement per 1–2 months for a given power plant can typically be achieved. We found that the uncertainty of the retrieved power plant CO2 emission during a single satellite overpass is in the range 0.5–5 MtCO2/year – depending on observation conditions – which is about 2–20% of the CO2 emission of large power plants (25 Mt CO2/year). The investigated instrument aims at fulfilling all requirements for global regional-scale CO2 and CH4 surface flux inverse modeling. Using a significantly less demanding instrument concept based on a single SWIR channel we indicate that this also enables the monitoring of power plant CO2 emissions in addition to high-quality methane retrievals. The latter has already been demonstrated by SCIAMACHY. The discussed technology has the potential to significantly contribute to an independent verification of reported anthropogenic CO2 emissions and therefore could be an important component of a future global anthropogenic CO2 emission monitoring system. This is of relevance in the context of Kyoto protocol follow-on agreements but also allows to detect and monitor strong natural CO2 and CH4 emitters such as (mud) volcanoes.

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

scholarly journals Integrasi Teknologi Pengideraan Jauh dan Sistem Informasi Geografis untuk Estimasi Serapan dan Emisi CO2 di Kota Denpasar

2018 ◽  
Vol 12 (2) ◽  
pp. 240
Author(s):  
I Wayan Nuarsa ◽  
Abd. Rahman As-syakur ◽  
I Gusti Alit Gunadi ◽  
I Made Sukewijaya
Keyword(s):  
Remote Sensing ◽  
Co2 Emissions ◽  
Open Space ◽  
Point Sources ◽  
Co2 Uptake ◽  
Co2 Absorption ◽  
Remote Sensing Technology ◽  
Mobile Sources ◽  
Sensing Technology ◽  
Pollutant Sources

Integration of Remote Sensing Technology And Geographic Information Systems for Estimation of CO2 Updake and Emissions in Denpasar City Rapid economic growth in the Denpasar City has an impact on the rate of population growth. This will lead to increasing land requirements for settlements, infrastructure, and other supporting facilities. Meanwhile, the availability of land for green open space (RTH) will decrease. Several studies show that from year to year the area of ??vegetation cover decreases, and the air temperature in Denpasar City is increasing. Therefore, research to calculate CO2 uptake by urban plants and CO2 emissions from various activities in the city of Denpasar is needed to be done. Estimates of CO2 uptake by plants are carried out using remote sensing technology and GIS. Meanwhile, the calculation of CO2 emissions is carried out by an inventory of CO2 pollutant sources from point sources, areas sources, and mobile sources. The output of this study is a distribution map of CO2 absorption and emissions. From the map it can be seen whether the CO2 emissions of Denpasar City are higher than the ability of existing plants to absorb them. The results showed that the ability of plants in Denpasar as a green open space to absorb CO2 was 235,780.63 tCO2/year, while total emissions from pollutant sources were 862,955,856 tCO2/year. The sources of CO2 emissions include from point source 37,649 tons/year, from source area 95,310 tons/year, and from mobile sources at 862,955,856 tons/year. From the movable source the biggest contributor to CO2 emissions is light vehicles, which amounted to 540,355.88 tons/year (62.63%), then followed by motorcycles at 260,187.43 tons/year (30.16%). The amount of CO2 emissions in Denpasar City is 3.66 times greater than the ability of plants to absorb CO2 in 2015 and there is a tendency for this gap to be even greater in the future. To overcome this problem, regulations are needed such as reducing the number of motorized vehicles by increasing public transportation services. The use of vehicles using energy sources other than fuel such as electricity is another alternative to consider. Finally, the increase in the number and quality of green open spaces is a conventional method that needs to be done.

scholarly journals Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: quantification and attribution

2018 ◽  
Vol 11 (3) ◽  
pp. 1251-1272 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
ZhaoCheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Desert Grassland ◽  
Chemical Transport Model ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of the column-averaged dry air mole fraction of CO2 (XCO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a latitude band of 37–42° N segmented into 8 cells in a grid of 5° from west to east (80–120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7–1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0–1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO2 retrievals. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo.

scholarly journals Towards space-borne monitoring of localized CO<sub>2</sub> emissions: an instrument concept and first performance assessment

2020 ◽  
Author(s):  
Johan Strandgren ◽  
David Krutz ◽  
Jonas Wilzewski ◽  
Carsten Paproth ◽  
Ilse Sebastian ◽  
...  
Keyword(s):  
Power Plant ◽  
Performance Assessment ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Point Sources ◽  
Source Strength ◽  
Spectral Window ◽  
Instrument Noise ◽  
Noise Error

Abstract. The UNFCCC (United Nations Framework Convention on Climate Change) requires the nations of the world to report their carbon dioxide (CO2) emissions. Independent verification of these reported emissions is a corner stone for advancing towards emission accounting and reduction measures agreed upon in the Paris agreement. In this paper, we present the concept and first performance assessment of a compact space-borne imaging spectrometer that could support the task of "monitoring, verification, reporting" (MVR) of CO2 emissions worldwide. With a single spectral window in the short-wave infrared spectral region and a spatial resolution of 50 x 50 m2, the goal is to reliably estimate the CO2 emissions from localized sources down to a source strength of approx. 1 MtCO2 yr-1, hence complementing other planned CO2 monitoring missions, like the planned European Carbon Constellation (CO2M). Resolving CO2 plumes also from medium-sized power plants (1–10 MtCO2 yr-1) is of key importance for independent quantification of CO2 emissions from the coal-fired power plant sector. Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is shown that an instrument noise error of 1.1 ppm (1σ) can be achieved for the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2). Despite limited amount of information from a single spectral window and a relatively coarse spectral resolution, scattering by atmospheric aerosol and cirrus can be partly accounted for in the XCO2 retrieval, with deviations of at most 4.0 ppm from the true abundance for 68 % of the scenes in the global trial ensemble. We further simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban area using high-resolution CO2 emission and surface albedo data for the city of Indianapolis. Given the preliminary instrument design and the corresponding instrument noise error, emission plumes from point sources with an emission rate down to the order of 0.3 MtCO2 yr-1 can be resolved, i.e. well below the target source strength of 1 MtCO2 yr-1. Hence, the proposed instrument concept could be able to resolve and quantify the CO2 plumes from localized point sources responsible for approx. 90 % of the power plant CO2 emission budget, assuming global coverage through a fleet of sensors and favorable conditions with respect to illumination and particle scattering.

scholarly journals Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: Quantification and attribution

2017 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
Zhaocheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Taklimakan Desert ◽  
Dust Aerosols ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of XCO2 (column-averaged dry air mole fraction of CO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a band of 37° N–42° N segmented into 8 cells in a grid of 5° from west to east (80° E–120° E) in China, where there are typical land surface types and geographic conditions. The former include the various land covers of desert, grassland and built-up areas mixed with cropland, and the latter include anthropogenic emissions that tend to be small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from five algorithms (ACOS, NIES, EMMA, OCFP, and SRFP) by intercomparison and particularly by comparing these with simulated XCO2 from the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem), the nested model in East Asia. We introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the five algorithms demonstrate smaller absolute biases between 0.9–1.5 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells with a high-brightness surface, 1.2–2.2 ppm from the pairwise comparison results of XCO2 retrievals. The inconsistency of XCO2 from the five algorithms tends to be high in the Taklimakan Desert in western cells, which is likely induced by high surface albedo in addition to dust aerosols in this region. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values of ACOS and SRFP better agree with GEOS-XCO2, while OCFP is the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS, SRFP and EMMA demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the five algorithms is the smallest in eastern cells in the investigated band where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the five algorithms presented in western deserts with a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols and albedo.

scholarly journals Dynamics of global atmospheric CO<sub>2</sub> concentration from 1850 to 2010: a linear approximation

2014 ◽  
Vol 11 (9) ◽  
pp. 13957-13983 ◽  
Author(s):  
W. Wang ◽  
R. Nemani
Keyword(s):  
Co2 Emissions ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Box Model ◽  
Modeling Framework ◽  
Elevated Atmospheric Co2 ◽  
Atmospheric Co2 Concentration ◽  
Co2 Concentrations ◽  
Anthropogenic Co2 ◽  
Atmospheric Co2 Concentrations

Abstract. The increase in anthropogenic CO2 emissions largely followed an exponential path between 1850 and 2010, and the corresponding increases in atmospheric CO2 concentration were almost constantly proportional to the emissions by the so-called "airborne fraction". These observations suggest that the dynamics of atmospheric CO2 concentration through this time period may be properly approximated as a linear system. We demonstrate this hypothesis by deriving a linear box-model to describe carbon exchanges between the atmosphere and the surface reservoirs under the influence of disturbances such as anthropogenic CO2 emissions and global temperature changes. We show that the box model accurately simulates the observed atmospheric CO2 concentrations and growth rates across interannual to multi-decadal time scales. The model also allows us to analytically examine the dynamics of such changes/variations, linking its characteristic disturbance-response functions to bio-geophysically meaningful parameters. In particular, our results suggest that the elevated atmospheric CO2 concentrations have significantly promoted the gross carbon uptake by the terrestrial biosphere. However, such "fertilization" effects are partially offset by enhanced carbon release from surface reservoirs promoted by warmer temperatures. The result of these interactions appears to be a decline in net efficiency in sequestering atmospheric CO2 by ∼30% since 1960s. We believe that the linear modeling framework outlined in this paper provides a convenient tool to diagnose the observed atmospheric CO2 dynamics and monitor their future changes.

scholarly journals Differences between trends in atmospheric CO2 and the reported trends in anthropogenic CO2 emissions

Tellus B ◽  
2010 ◽  
Vol 62 (5) ◽  
pp. 316-328 ◽  
Author(s):  
R.J. Francey ◽  
C.M. Trudinger ◽  
Van Der Schoot ◽  
P.B. Krummel ◽  
L.P. Steele ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Atmospheric Co2 ◽  
Anthropogenic Co2

scholarly journals Past and present of sediment and carbon biogeochemical cycling models

2004 ◽  
Vol 1 (1) ◽  
pp. 11-32 ◽  
Author(s):  
F. T. Mackenzie ◽  
A. Lerman ◽  
A. J. Andersson
Keyword(s):  
Carbon Cycle ◽  
Co2 Emissions ◽  
Coastal Zone ◽  
Inorganic Carbon ◽  
Atmospheric Co2 ◽  
Time Model ◽  
Gross Photosynthesis ◽  
Geological Processes ◽  
Anthropogenic Co2 ◽  
Global Carbon

Abstract. The global carbon cycle is part of the much more extensive sedimentary cycle that involves large masses of carbon in the Earth's inner and outer spheres. Studies of the carbon cycle generally followed a progression in knowledge of the natural biological, then chemical, and finally geological processes involved, culminating in a more or less integrated picture of the biogeochemical carbon cycle by the 1920s. However, knowledge of the ocean's carbon cycle behavior has only within the last few decades progressed to a stage where meaningful discussion of carbon processes on an annual to millennial time scale can take place. In geologically older and pre-industrial time, the ocean was generally a net source of CO2 emissions to the atmosphere owing to the mineralization of land-derived organic matter in addition to that produced in situ and to the process of CaCO3 precipitation. Due to rising atmospheric CO2 concentrations because of fossil fuel combustion and land use changes, the direction of the air-sea CO2 flux has reversed, leading to the ocean as a whole being a net sink of anthropogenic CO2. The present thickness of the surface ocean layer, where part of the anthropogenic CO2 emissions are stored, is estimated as of the order of a few hundred meters. The oceanic coastal zone net air-sea CO2 exchange flux has also probably changed during industrial time. Model projections indicate that in pre-industrial times, the coastal zone may have been net heterotrophic, releasing CO2 to the atmosphere from the imbalance between gross photosynthesis and total respiration. This, coupled with extensive CaCO3 precipitation in coastal zone environments, led to a net flux of CO2 out of the system. During industrial time the coastal zone ocean has tended to reverse its trophic status toward a non-steady state situation of net autotrophy, resulting in net uptake of anthropogenic CO2 and storage of carbon in the coastal ocean, despite the significant calcification that still occurs in this region. Furthermore, evidence from the inorganic carbon cycle indicates that deposition and net storage of CaCO3 in sediments exceed inflow of inorganic carbon from land and produce CO2 emissions to the atmosphere. In the shallow-water coastal zone, increase in atmospheric CO2 during the last 300 years of industrial time may have reduced the rate of calcification, and continuation of this trend is an issue of serious environmental concern in the global carbon balance.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to regridding of global fossil fuel CO<sub>2</sub> emissions

2014 ◽  
Vol 7 (6) ◽  
pp. 2867-2874 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady
Keyword(s):  
Co2 Emissions ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Grid Cells ◽  
Atmospheric Co2 Concentration ◽  
Dynamical Consistency

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO2 emissions (FFCO2) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell−1 yr−1 (−3.39 kgC m−2 yr−1) to +30.0 TgC grid cell−1 yr−1 (+2.6 kgC m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

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