scholarly journals Estimation of fossil-fuel CO<sub>2</sub> emissions using satellite measurements of "proxy" species

2016 ◽  
Vol 16 (21) ◽  
pp. 13509-13540 ◽  
Author(s):  
Igor B. Konovalov ◽  
Evgeny V. Berezin ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
Ruslan V. Zhuravlev ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Fossil Fuel ◽  
Inventory Data ◽  
Satellite Measurements ◽  
Top Down ◽  
Bottom Up ◽  
Study Region ◽  
Emission Estimate

Abstract. Fossil-fuel (FF) burning releases carbon dioxide (CO2) together with many other chemical species, some of which, such as nitrogen dioxide (NO2) and carbon monoxide (CO), are routinely monitored from space. This study examines the feasibility of estimation of FF CO2 emissions from large industrial regions by using NO2 and CO column retrievals from satellite measurements in combination with simulations by a mesoscale chemistry transport model (CTM). To this end, an inverse modeling method is developed that allows estimating FF CO2 emissions from different sectors of the economy, as well as the total CO2 emissions, in a given region. The key steps of the method are (1) inferring "top-down" estimates of the regional budget of anthropogenic NOx and CO emissions from satellite measurements of proxy species (NO2 and CO in the case considered) without using formal a priori constraints on these budgets, (2) the application of emission factors (the NOx-to-CO2 and CO-to-CO2 emission ratios in each sector) that relate FF CO2 emissions to the proxy species emissions and are evaluated by using data of "bottom-up" emission inventories, and (3) cross-validation and optimal combination of the estimates of CO2 emission budgets derived from measurements of the different proxy species. Uncertainties in the top-down estimates of the NOx and CO emissions are evaluated and systematic differences between the measured and simulated data are taken into account by using original robust techniques validated with synthetic data. To examine the potential of the method, it was applied to the budget of emissions for a western European region including 12 countries by using NO2 and CO column amounts retrieved from, respectively, the OMI and IASI satellite measurements and simulated by the CHIMERE mesoscale CTM, along with the emission conversion factors based on the EDGAR v4.2 emission inventory. The analysis was focused on evaluation of the uncertainty levels for the top-down NOx and CO emission estimates and "hybrid" estimates (that is, those based on both atmospheric measurements of a given proxy species and respective bottom-up emission inventory data) of FF CO2 emissions, as well as on examining consistency between the FF NO2 emission estimates derived from measurements of the different proxy species. It is found that NO2 measurements can provide much stronger constraints to the total annual FF CO2 emissions in the study region than CO measurements, the accuracy of the NO2-measurement-based CO2 emission estimate being mostly limited by the uncertainty in the top-down NOx emission estimate. Nonetheless, CO measurements are also found to be useful as they provide additional constraints to CO2 emissions and enable evaluation of the hybrid FF CO2 emission estimates obtained from NO2 measurements. Our most reliable estimate for the total annual FF CO2 emissions in the study region in 2008 (2.71 ± 0.30 Pg CO2) is found to be about 11 and 5 % lower than the respective estimates based on the EDGAR v.4.2 (3.03 Pg CO2) and CDIAC (2.86 Pg CO2) emission inventories, with the difference between our estimate and the CDIAC inventory data not being statistically significant. In general, the results of this study indicate that the proposed method has the potential to become a useful tool for identification of possible biases and/or inconsistencies in the bottom-up emission inventory data regarding CO2, NOx, and CO emissions from fossil-fuel burning in different regions of the world.

scholarly journals Estimation of fossil-fuel CO<sub>2</sub> emissions using satellite measurements of "proxy" species

2016 ◽  
Author(s):  
Igor B. Konovalov ◽  
Evgeny V. Berezin ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
Ruslan B. Zhuravlev ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Fossil Fuel ◽  
Inventory Data ◽  
Satellite Measurements ◽  
Top Down ◽  
Bottom Up ◽  
Study Region ◽  
Emission Estimate

Abstract. Fossil fuel (FF) burning releases carbon dioxide (CO2) together with many other chemical species, some of which, such as, e.g., nitrogen dioxide (NO2) and carbon monoxide (CO), are routinely monitored from space. This study examines the feasibility of estimation of FF CO2 emissions from large industrial regions by using NO2 and CO column retrievals from satellite measurements in combination with simulations by a mesoscale chemistry transport model (CTM). To this end, an inverse modeling method is developed that allows estimating FF CO2 emissions from different sectors of the economy, as well as the total CO2 emissions, in a given region. The key steps of the method are (1) inferring "top-down" estimates of the regional budget of anthropogenic emissions of proxy species (that is, NOx and CO in the case considered) from satellite measurements without using formal a priori constraints on these budgets, (2) application of emission factors (the NOx-to-CO2 and CO-to-CO2 emission ratios in each sector) that relate FF CO2 emissions to the emissions of the proxy species and are evaluated by using data of "bottom-up" emission inventories, (3) cross-validation and optimal combination of the estimates of CO2 emission budgets derived from measurements of the different proxy species. Uncertainties in the top-down estimates of the emissions of the proxy species are evaluated and systematic differences between the measured and simulated data are taken into account by using original robust techniques validated with synthetic data. To examine the potential of the method, it was applied to the budget of emissions for a western European region including 12 countries by using NO2 and CO column amounts retrieved from, respectively, the OMI and IASI satellite measurements and simulated by the CHIMERE mesoscale CTM, along with the emission conversion factors based on the EDGAR v4.2 emission inventory. The analysis was focused on evaluation of the uncertainty levels for the "top-down" NOx and CO emission estimates and "hybrid" estimates (that is, those based on both atmospheric measurements of a given proxy species and respective "bottom-up" emission inventory data) of FF CO2 emissions, as well as on examining consistency between the FF СO2 emission estimates derived from measurements of the different proxy species. It is found that NO2 measurements can provide much stronger constraints to the total annual FF CO2 emissions in the study region than CO measurements, the accuracy of the NO2-measurement-based CO2 emission estimate being mostly limited by the uncertainty in the top-down NOx emission estimate. Nonetheless, CO measurements are also found to be useful as they provide additional constraints to CO2 emissions and enable evaluation of the hybrid FF CO2 emission estimates obtained from NO2 measurements. Our most reliable estimate for the total annual FF CO2 emissions in the study region in 2008 (2.71±0.30 Pg CO2) is found to be about 11 % and 5 % lower than the respective estimates based on the EDGAR v.4.2 (3.03 Pg CO2) and CDIAC (2.86 Pg CO2) emission inventories, with the difference between our estimate and the CDIAC inventory data being not statistically significant. In general, the results of this study indicate that the proposed method has a potential to become a useful tool for identification of possible biases and/or inconsistencies in the bottom-up emission inventory data regarding CO2, NOx and CO emissions from fossil fuel burning in different regions of the world.

scholarly journals Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

2013 ◽  
Vol 13 (1) ◽  
pp. 255-309 ◽  
Author(s):  
E. V. Berezin ◽  
I. B. Konovalov ◽  
P. Ciais ◽  
A. Richter ◽  
S. Tao ◽  
...  
Keyword(s):  
Time Series ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Satellite Measurements ◽  
Top Down ◽  
Bottom Up ◽  
Tropospheric No2 ◽  
Emission Changes

Abstract. Multi-annual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect annual top-down estimates of CO2 emissions are derived from the satellite NO2 columns measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry transport model and the CO2 to NOx emission ratios from the Emission Database for Global Atmospheric Research version 4.2 (EDGAR v4.2) global anthropogenic emission inventory. Exponential trends in the normalized time series of annual emission are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are estimated to be in the range from 3.7 to 8.0 and from 9.5 to 13.0 percent per year, respectively, taking into account both statistical and probable systematic uncertainties. Comparison of our top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by EDGAR v4.2 and Global Carbon Project (GCP) emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of the both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies which indicated probable large uncertainties in the energy production and other activity data from international energy statistics used as the input information in the emission inventories for China. For the period from 2001 to 2008, the different kinds of estimates agree within the uncertainty range. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources colocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

scholarly journals Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

2013 ◽  
Vol 13 (18) ◽  
pp. 9415-9438 ◽  
Author(s):  
E. V. Berezin ◽  
I. B. Konovalov ◽  
P. Ciais ◽  
A. Richter ◽  
S. Tao ◽  
...  
Keyword(s):  
Time Series ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Satellite Measurements ◽  
Top Down ◽  
Global Emission ◽  
Tropospheric No2 ◽  
Emission Changes ◽  
Emission Ratios

Abstract. Multiannual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect top-down annual estimates of CO2 emissions are derived from the satellite NO2 column measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry–transport model and the CO2-to-NOx emission ratios from the Emission Database for Global Atmospheric Research (EDGAR) global anthropogenic emission inventory and Regional Emission Inventory in Asia (REAS). Exponential trends in the normalized time series of annual emissions are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are best estimated to be in the range from 3.7 to 8.3 and from 11.0 to 13.2% per year, respectively, taking into account statistical uncertainties and differences between the CO2-to-NOx emission ratios from the EDGAR and REAS inventories. Comparison of our indirect top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by the EDGAR (version 4.2) and Global Carbon Project (GCP) glomal emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the global emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and indirect top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the global emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies that indicated probable large uncertainties in the energy production and other activity data for China from international energy statistics used as the input information in the global emission inventories. For the period from 2001 to 2008, some quantitative differences between the different kinds of estimates are found to be in the range of possible systematic uncertainties associated with our estimation method. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources collocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

scholarly journals Conflicting estimates of natural geologic methane emissions

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
B. F. Thornton ◽  
G. Etiope ◽  
S. Schwietzke ◽  
A. V. Milkov ◽  
R. W. Klusman ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Ice Cores ◽  
Methane Emissions ◽  
Ch4 Emission ◽  
Top Down ◽  
Bottom Up ◽  
Ch4 Emissions ◽  
Emission Estimate

Global bottom-up and top-down estimates of natural, geologic methane (CH4) emissions (average approximately 45 Tg yr–1) have recently been questioned by near-zero (approximately 1.6 Tg yr–1) estimates based on measurements of 14CH4 trapped in ice cores, which imply that current fossil fuel industries’ CH4 emissions are underestimated by 25%–40%. As we show here, such a global near-zero geologic CH4 emission estimate is incompatible with multiple independent, bottom-up emission estimates from individual natural geologic seepage areas, each of which is of the order of 0.1–3 Tg yr–1. Further research is urgently needed to resolve the conundrum before rejecting either method or associated emission estimates in global CH4 accounting.

scholarly journals Carbonaceous aerosols in China: top-down constraints on primary sources and estimation of secondary contribution

2011 ◽  
Vol 11 (10) ◽  
pp. 28219-28272 ◽  
Author(s):  
T.-M. Fu ◽  
J. J. Cao ◽  
X. Y. Zhang ◽  
S. C. Lee ◽  
Q. Zhang ◽  
...  
Keyword(s):  
Eastern China ◽  
Western China ◽  
Spatiotemporal Variability ◽  
Anthropogenic Source ◽  
Carbonaceous Aerosols ◽  
Top Down ◽  
Bottom Up ◽  
Secondary Sources ◽  
Secondary Formation ◽  
Emission Estimate

Abstract. We simulate elemental carbon (EC) and organic carbon (OC) aerosols in China and compare model results to surface measurements at Chinese rural and background sites, with the goal of deriving "top-down" emission estimates of EC and OC, as well as better quantifying the secondary sources of OC. We include in the model state-of-the-science Chinese "bottom-up" emission inventories for EC (1.92 Tg C yr−1) and OC (3.95 Tg C yr−1), as well as updated secondary OC formation pathways. The average simulated annual mean EC concentration at rural and background site is 1.1 μg C m−3, 56% lower than the observed 2.5 μg C m−3. The average simulated annual mean OC concentration at rural and background sites is 3.4 μg C m−3, 76% lower than the observed 14 μg C m−3. Multiple regression to fit surface monthly mean EC observations at rural and background sites yields best estimate of Chinese EC source of 3.05 ± 0.78 Tg C yr−1. Based on the top-down EC emission estimate and observed seasonal primary OC/EC ratios, we estimate Chinese OC total emissions to be 6.67 ± 1.30 Tg C yr−1. Using these top-down estimates, the simulated average annual mean EC concentration at rural and background sites significantly improved to 1.9 μg C m−3. However, the model still significantly underestimates observed OC in all seasons (simulated average annual mean OC at rural and background sites is 5.4 μg C m−3), with little skill in capturing the spatiotemporal variability. Secondary formation accounts for 21% of Chinese annual mean surface OC in the model, with isoprene being the most important precursor. In summer, as high as 62% of the observed surface OC may be due to secondary formation in eastern China. Our analysis points to three shortcomings in the current bottom-up inventories of Chinese carbonaceous aerosols: (1) the anthropogenic source is severely underestimated, particularly for OC; (2) there is a missing source in western China, likely associated with the use of biofuels or other low-quality fuels for heating; and (3) sources in fall are not well represented, either because the seasonal shifting of emissions and/or secondary formation are poorly captured or because specific fall emission events are missing. More regional measurements with better spatiotemporal coverage are needed to resolve these shortcomings.

scholarly journals A global map of emission clumps for future monitoring of fossil fuel CO<sub>2</sub> emissions from space

2019 ◽  
Vol 11 (2) ◽  
pp. 687-703 ◽  
Author(s):  
Yilong Wang ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Tomohiro Oda ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Urban Areas ◽  
Power Plants ◽  
Fossil Fuel ◽  
Large Fraction ◽  
Point Sources ◽  
Bottom Up ◽  
Large Power ◽  
Data Product

Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of <1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

scholarly journals Improvement of the satellite-derived NO<sub><i>x</i></sub> emissions on air quality modeling and its effect on ozone and secondary inorganic aerosol formation in the Yangtze River Delta, China

2021 ◽  
Vol 21 (2) ◽  
pp. 1191-1209
Author(s):  
Yang Yang ◽  
Yu Zhao ◽  
Lei Zhang ◽  
Jie Zhang ◽  
Xin Huang ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Model Performance ◽  
Yangtze River Delta ◽  
Nox Emissions ◽  
Top Down ◽  
Bottom Up ◽  
Emission Estimation ◽  
Reduced Rate ◽  
The Yrd

Abstract. We developed a top-down methodology combining the inversed chemistry transport modeling and satellite-derived tropospheric vertical column of NO2 and estimated the NOx emissions of the Yangtze River Delta (YRD) region at a horizontal resolution of 9 km for January, April, July, and October 2016. The effect of the top-down emission estimation on air quality modeling and the response of ambient ozone (O3) and inorganic aerosols (SO42-, NO3-, and NH4+, SNA) to the changed precursor emissions were evaluated with the Community Multi-scale Air Quality (CMAQ) system. The top-down estimates of NOx emissions were smaller than those (i.e., the bottom-up estimates) in a national emission inventory, Multi-resolution Emission Inventory for China (MEIC), for all the 4 months, and the monthly mean was calculated to be 260.0 Gg/month, 24 % less than the bottom-up one. The NO2 concentrations simulated with the bottom-up estimate of NOx emissions were clearly higher than the ground observations, indicating the possible overestimation in the current emission inventory, attributed to its insufficient consideration of recent emission control in the region. The model performance based on top-down estimate was much better, and the biggest change was found for July, with the normalized mean bias (NMB) and normalized mean error (NME) reduced from 111 % to −0.4 % and from 111 % to 33 %, respectively. The results demonstrate the improvement of NOx emission estimation with the nonlinear inversed modeling and satellite observation constraint. With the smaller NOx emissions in the top-down estimate than the bottom-up one, the elevated concentrations of ambient O3 were simulated for most of the YRD, and they were closer to observations except for July, implying the VOC (volatile organic compound)-limited regime of O3 formation. With available ground observations of SNA in the YRD, moreover, better model performance of NO3- and NH4+ was achieved for most seasons, implying the effectiveness of precursor emission estimation on the simulation of secondary inorganic aerosols. Through the sensitivity analysis of O3 formation for April 2016, the decreased O3 concentrations were found for most of the YRD region when only VOC emissions were reduced or the reduced rate of VOC emissions was 2 times of that of NOx, implying the crucial role of VOC control in O3 pollution abatement. The SNA level for January 2016 was simulated to decline 12 % when 30 % of NH3 emissions were reduced, while the change was much smaller with the same reduced rate for SO2 or NOx. The result suggests that reducing NH3 emissions was the most effective way to alleviate SNA pollution of the YRD in winter.

scholarly journals Toward an Operational Anthropogenic CO2 Emissions Monitoring and Verification Support Capacity

2020 ◽  
Vol 101 (8) ◽  
pp. E1439-E1451 ◽  
Author(s):  
G. Janssens-Maenhout ◽  
B. Pinty ◽  
M. Dowell ◽  
H. Zunker ◽  
E. Andersson ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
European Space Agency ◽  
Green Light ◽  
Atmospheric Measurements ◽  
Top Down ◽  
Bottom Up ◽  
Holistic View ◽  
Support Tool ◽  
Anthropogenic Co2 ◽  
Operational Capacity

Abstract Under the Paris Agreement (PA), progress of emission reduction efforts is tracked on the basis of regular updates to national greenhouse gas (GHG) inventories, referred to as bottom-up estimates. However, only top-down atmospheric measurements can provide observation-based evidence of emission trends. Today, there is no internationally agreed, operational capacity to monitor anthropogenic GHG emission trends using atmospheric measurements to complement national bottom-up inventories. The European Commission (EC), the European Space Agency, the European Centre for Medium-Range Weather Forecasts, the European Organisation for the Exploitation of Meteorological Satellites, and international experts are joining forces to develop such an operational capacity for monitoring anthropogenic CO2 emissions as a new CO2 service under the EC’s Copernicus program. Design studies have been used to translate identified needs into defined requirements and functionalities of this anthropogenic CO2 emissions Monitoring and Verification Support (CO2MVS) capacity. It adopts a holistic view and includes components such as atmospheric spaceborne and in situ measurements, bottom-up CO2 emission maps, improved modeling of the carbon cycle, an operational data-assimilation system integrating top-down and bottom-up information, and a policy-relevant decision support tool. The CO2MVS capacity with operational capabilities by 2026 is expected to visualize regular updates of global CO2 emissions, likely at 0.05° x 0.05°. This will complement the PA’s enhanced transparency framework, providing actionable information on anthropogenic CO2 emissions that are the main driver of climate change. This information will be available to all stakeholders, including governments and citizens, allowing them to reflect on trends and effectiveness of reduction measures. The new EC gave the green light to pass the CO2MVS from exploratory to implementing phase.

scholarly journals A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide

2020 ◽  
Vol 20 (1) ◽  
pp. 99-116 ◽  
Author(s):  
Fei Liu ◽  
Bryan N. Duncan ◽  
Nickolay A. Krotkov ◽  
Lok N. Lamsal ◽  
Steffen Beirle ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Operating Conditions ◽  
Satellite Observations ◽  
Nox Emissions ◽  
Bottom Up ◽  
Monitoring Instrument ◽  
The Us

Abstract. We present a method to infer CO2 emissions from individual power plants based on satellite observations of co-emitted nitrogen dioxide (NO2), which could serve as complementary verification of bottom-up inventories or be used to supplement these inventories. We demonstrate its utility on eight large and isolated US power plants, where accurate stack emission estimates of both gases are available for comparison. In the first step of our methodology, we infer nitrogen oxides (NOx) emissions from US power plants using Ozone Monitoring Instrument (OMI) NO2 tropospheric vertical column densities (VCDs) averaged over the ozone season (May–September) and a “top-down” approach that we previously developed. Second, we determine the relationship between NOx and CO2 emissions based on the direct stack emissions measurements reported by continuous emissions monitoring system (CEMS) programs, accounting for coal quality, boiler firing technology, NOx emission control device type, and any change in operating conditions. Third, we estimate CO2 emissions for power plants using the OMI-estimated NOx emissions and the CEMS NOx∕CO2 emission ratio. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the US CEMS measurements, with a relative difference of 8 %±41 % (mean ± standard deviation). The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting. We explore the feasibility by comparing the derived NOx∕CO2 emission ratios for the US with those from a bottom-up emission inventory for other countries and applying our methodology to a power plant in South Africa, where the satellite-based emission estimates show reasonable consistency with other independent estimates. Though our analysis is limited to a few power plants, we expect to be able to apply our method to more US (and world) power plants when multi-year data records become available from new OMI-like sensors with improved capabilities, such as the TROPOspheric Monitoring Instrument (TROPOMI), and upcoming geostationary satellites, such as the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument.

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