Assessing the constraint of the CO2 monitoring mission on fossil fuel emissions from power plants and a city in a regional carbon cycle fossil fuel data assimilation system

2021 ◽  
Author(s):  
Thomas Kaminski ◽  
Marko Scholze ◽  
Peter Rayner ◽  
Sander Houweling ◽  
Michael Voßbeck ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Power Plants ◽  
Fossil Fuel ◽  
Spatial Scales ◽  
The Other ◽  
Model Parameters ◽  
Atmospheric Measurements ◽  
Co2 Monitoring ◽  
The Impact ◽  
Fossil Fuel Emissions

<p>The Paris Agreement foresees to establish a transparency framework that builds upon inventory-based national greenhouse gas emission reports, complemented by independent emission estimates derived from atmospheric measurements through inverse modelling. The capability of such a Monitoring and Verification Support (MVS) capacity to constrain fossil fuel emissions to a sufficient extent has not yet been assessed. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2), is expected to become a key component of an MVS capacity. </p><p>Here we present a CCFFDAS that operates at the resolution of the CO2M sensor, i.e. 2km by 2km, over a 200 km by 200 km region around Berlin. It combines models of sectorial fossil fuel CO2 emissions and biospheric fluxes with the Community Multiscale Air Quality model (coupled to a model of the plume rise from large power plants) as observation operator for XCO2 and tropospheric column NO2 measurements. Inflow from the domain boundaries is treated as extra unknown to be solved for by the CCFFDAS, which also includes prior information on the process model parameters. We discuss the sensitivities (Jacobian matrix) of simulated XCO2 and NO2 troposheric columns with respect to a) emissions from power plants, b) emissions from the surface and c) the lateral inflow and quantify the respective contributions to the observed signal. The Jacobian representation of the complete modelling chain allows us to evaluate data sets of simulated random and systematic CO2M errors in terms of posterior uncertainties in sectorial fossil fuel emissions. We provide assessments of XCO2 alone and in combination with NO2 on the posterior uncertainty in sectorial fossil fuel emissions for two 1-day study periods, one in winter and one in summer. We quantify the added value of the observations for emissions at a single point, at the 2km by 2km scale, at the scale of Berlin districts, and for  Berlin and further cities in our domain. This means the assessments include temporal and spatial scales typically not covered by inventories. Further, we quantify the effect of better information of atmospheric aerosol, provided by a multi-angular polarimeter (MAP) onboard CO2M, on the posterior uncertainties.</p><p>The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector”. We find that XCO2 measurements alone provide a powerful constraint on emissions from larger power plants and a constraint on emissions from the other sector that increases when aggregated to larger spatial scales. The MAP improves the impact of the CO2M measurements for all power plants and for the other sector on all spatial scales. Over our study domain, the impact of the MAP is particularly high in winter. NO2 measurements provide a powerful additional constraint on the emissions from power plants and from the other sector.</p>

scholarly journals Spatial distribution of Δ<sup>14</sup>CO<sub>2</sub> across Eurasia: measurements from the TROICA-8 expedition

2008 ◽  
Vol 8 (4) ◽  
pp. 15207-15238
Author(s):  
J. C. Turnbull ◽  
J. B. Miller ◽  
S. J. Lehman ◽  
D. Hurst ◽  
P. P. Tans ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Co2 Emissions ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Eastern Siberia ◽  
Sulphur Hexafluoride ◽  
Atmospheric Measurements ◽  
Northern Asia ◽  
Continental Scale ◽  
Fossil Fuel Emissions

Abstract. Because fossil fuel derived CO2 is the only source of atmospheric CO2 that is devoid of 14C, atmospheric measurements of Δ14CO2 can be used to constrain fossil fuel emissions at local and regional scales. However, at the continental scale, atmospheric transport and other sources of variability in Δ14CO2 may influence the fossil fuel detection capability. We present a set of Δ14CO2 observations from the train-based TROICA-8 expedition across Eurasia in March–April 2004. Local perturbations in Δ14CO2 are caused by easily identifiable sources from nuclear reactors and localized pollution events. The remaining data show an increase in Δ14CO2 from Western Russia (40° E) to Eastern Siberia (120° E), consistent with depletion in 14CO2 caused by fossil fuel CO2 emissions in heavily populated Europe, and gradual dispersion of the fossil fuel plume across Northern Asia. Other tracer gas species which may be correlated with fossil fuel CO2 emissions, including carbon monoxide, sulphur hexafluoride, and perchloroethylene, were also measured and the results compared with the Δ14CO2 measurements. The sulphur hexafluoride longitudinal gradient is not significant relative to the measurement uncertainty. Carbon monoxide and perchloroethylene show large-scale trends of enriched values in Western Russia and decreasing values in Eastern Siberia, consistent with fossil fuel emissions, but exhibit significant spatial variability, especially near their primary sources in Western Russia. The clean air Δ14CO2 observations are compared with simulated spatial gradients from the TM5 atmospheric transport model. We show that the change in Δ14CO2 across the TROICA transect is due almost entirely to emissions of fossil fuel CO2, but that the magnitude of this Δ14CO2 gradient is relatively insensitive to modest uncertainties in the fossil fuel flux. In contrast, the Δ14CO2 gradient is strongly sensitive to the modeled representation of vertical mixing, suggesting that Δ14CO2 may be a useful tracer for training mixing in atmospheric transport models.

scholarly journals Toward consistency between bottom-up CO<sub>2</sub> emissions trends and top-down atmospheric measurements in the Los Angeles megacity

2015 ◽  
Vol 15 (20) ◽  
pp. 29591-29638 ◽  
Author(s):  
S. Newman ◽  
X. Xu ◽  
K. R. Gurney ◽  
Y.-K. Hsu ◽  
K.-F. Li ◽  
...  
Keyword(s):  
Los Angeles ◽  
Natural Gas ◽  
Co2 Emissions ◽  
Power Plants ◽  
Fossil Fuel ◽  
Fuel Combustion ◽  
Fossil Fuel Combustion ◽  
Atmospheric Measurements ◽  
Bottom Up ◽  
Gasoline Taxes

Abstract. Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO2 mole fractions and Δ14C and δ13C values of CO2 in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO2 contributions from fossil fuel combustion for both sites and broken those down into contributions from petroleum/gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena CO2 emissions from fossil fuel combustion during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO2 from our observations are used to infer seasonality of natural gas and petroleum combustion. For natural gas, inferred emissions are out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but are consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO2 emissions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare emissions from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO2 reflect seasonal variations in wind direction. The seasonality of the local CO2 excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in fall and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO2 signals are consistent with sampling the bottom-up Hestia-LA fossil CO2 emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

Urban fossil fuel CO2 emissions from space: lessons learned from the OCO missions

2020 ◽  
Author(s):  
Thomas Lauvaux ◽  
Sha Feng ◽  
Ruixue Lei ◽  
Tomohiro Oda ◽  
Alexandre Danjou ◽  
...  
Keyword(s):  
Los Angeles ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Power Plants ◽  
Fossil Fuel ◽  
Urban Environments ◽  
Lessons Learned ◽  
Atmospheric Measurements ◽  
Gas Emissions ◽  
Fossil Fuel Emissions

&lt;p&gt;Pledges from nations and cities to reduce their carbon footprints have reinforced the needs for accurate and transparent reporting of fossil fuel emissions at various scales, with the ultimate goal of the establishments of carbon stocktake as defined by the Paris Agreement. But the assessment of anthropogenic emissions results primarily in collecting socio-economic indicators and emission factors, hence difficult to evaluate, track, or compare without a more standardized and robust methodology. Atmospheric measurements of greenhouse gases are of particular interests by offering an independent and global source of information thanks to satellite platforms observing continuously the atmospheric content of the major gases responsible for human-induced climate change. &lt;br&gt;&lt;br&gt;Based on lessons learned from the NASA Orbiting Carbon Observatory (OCO)-2 mission, we present the potential of satellite-based approaches to monitor greenhouse gas emissions from large metropolitan areas across the world (Riyadh, Lahore, Los Angeles). After exploring the technical aspects and challenges of the approach, potential aerosol contamination (CALIPSO), and model requirements, we introduce the upcoming capabilities from the follow-up mission, OCO-3, dedicated in part to urban emissions with the Snapshot Area Mapping mode, the first imagery of atmospheric CO2 concentrations for hundreds of targeted cities and power plants. Early snapshots are examined with high-resolution simulations over a handful of cities. The ongoing development of assimilation systems to inform policy makers about current trends and inter-annual variations is presented and discussed. We finally examine the potential roles and objectives of satellite missions by exploring recent trends in fossil fuel emissions along with proxies of air quality (MODIS) as a unique opportunity to track not only greenhouse gas emissions but more generally the evolution of urban environments.&lt;/p&gt;

scholarly journals Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Kai Wu ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis ◽  
Aijun Deng ◽  
Israel Lopez Coto ◽  
...  
Keyword(s):  
High Resolution ◽  
Urban Environment ◽  
Co2 Emissions ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
System Simulation ◽  
Co2 Flux ◽  
Point Sources ◽  
Co2 Fluxes ◽  
The Impact

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 µmol m–2 s–1 compared to the spatially averaged anthropogenic CO2 emissions of 5 µmol m–2 s–1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

scholarly journals The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis

2014 ◽  
Vol 26 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Chuan Ding ◽  
Chao Liu ◽  
Yaoyu Lin ◽  
Yaowu Wang
Keyword(s):  
Co2 Emissions ◽  
Mixed Method ◽  
Latent Variables ◽  
Choice Model ◽  
Mode Choice ◽  
Car Ownership ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Employer Attitudes ◽  
The Impact

Reducing car trips and promoting green commuting modes are generally considered important solutions to reduce the increase of energy consumption and transportation CO2 emissions. One potential solution for alleviating transportation CO2 emissions has been to identify a role for the employer through green commuter programs. This paper offers an approach to assess the effects of employer attitudes towards green commuting plans on commuter mode choice and the intermediary role car ownership plays in the mode choice decision process. A mixed method which extends the traditional discrete choice model by incorporating latent variables and mediating variables with a structure equation model was used to better understand the commuter mode choice behaviour. The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process. The results found in this paper provide helpful information for transportation and planning policymakers to test the transportation and planning policies effects and encourage green commuting reducing transportation CO2 emissions.

scholarly journals Effects of a Delayed Expansion of Interconnector Capacities in a High RES-E European Electricity System

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3098
Author(s):  
Ritter ◽  
Meyer ◽  
Koch ◽  
Haller ◽  
Bauknecht ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Electricity Market ◽  
Electricity Generation ◽  
Power Plants ◽  
Energy Transition ◽  
Market Model ◽  
Electricity Trading ◽  
Electricity System ◽  
System A ◽  
The Impact

In order to achieve a high renewable share in the electricity system, a significant expansion of cross-border exchange capacities is planned. Historically, the actual expansion of interconnector capacities has significantly lagged behind the planned expansion. This study examines the impact that such continued delays would have when compared to a strong interconnector expansion in an ambitious energy transition scenario. For this purpose, scenarios for the years 2030, 2040, and 2050 are examined using the electricity market model PowerFlex EU. The analysis reveals that both CO2 emissions and variable costs of electricity generation increase if interconnector expansion is delayed. This effect is most significant in the scenario year 2050, where lower connectivity leads roughly to a doubling of both CO2 emissions and variable costs of electricity generation. This increase results from a lower level of European electricity trading, a curtailment of electricity from a renewable energy source (RES-E), and a corresponding higher level of conventional electricity generation. Most notably, in Southern and Central Europe, less interconnection leads to higher use of natural gas power plants since less renewable electricity from Northern Europe can be integrated into the European grid.

scholarly journals Towards space based verification of CO<sub>2</sub> emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation

2011 ◽  
Vol 4 (4) ◽  
pp. 5147-5182
Author(s):  
V. A. Velazco ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
M. Reuter ◽  
O. Schneising ◽  
...  
Keyword(s):  
Power Plant ◽  
Systematic Error ◽  
Co2 Emissions ◽  
Power Plants ◽  
Fossil Fuel ◽  
Systematic Errors ◽  
Random Errors ◽  
Power Plant Emissions ◽  
Global Coverage ◽  
Plant Emissions

Abstract. Carbon dioxide (CO2) is the most important man-made greenhouse gas (GHG) that cause global warming. With electricity generation through fossil-fuel power plants now as the economic sector with the largest source of CO2, power plant emissions monitoring has become more important than ever in the fight against global warming. In a previous study done by Bovensmann et al. (2010), random and systematic errors of power plant CO2 emissions have been quantified using a single overpass from a proposed CarbonSat instrument. In this study, we quantify errors of power plant annual emission estimates from a hypothetical CarbonSat and constellations of several CarbonSats while taking into account that power plant CO2 emissions are time-dependent. Our focus is on estimating systematic errors arising from the sparse temporal sampling as well as random errors that are primarily dependent on wind speeds. We used hourly emissions data from the US Environmental Protection Agency (EPA) combined with assimilated and re-analyzed meteorological fields from the National Centers of Environmental Prediction (NCEP). CarbonSat orbits were simulated as a sun-synchronous low-earth orbiting satellite (LEO) with an 828-km orbit height, local time ascending node (LTAN) of 13:30 (01:30 p.m.) and achieves global coverage after 5 days. We show, that despite the variability of the power plant emissions and the limited satellite overpasses, one CarbonSat can verify reported US annual CO2 emissions from large power plants (≥5 Mt CO2 yr−1) with a systematic error of less than ~4.9 % for 50 % of all the power plants. For 90 % of all the power plants, the systematic error was less than ~12.4 %. We additionally investigated two different satellite configurations using a combination of 5 CarbonSats. One achieves global coverage everyday but only samples the targets at fixed local times. The other configuration samples the targets five times at two-hour intervals approximately every 6th day but only achieves global coverage after 5 days. From the statistical analyses, we found, as expected, that the random errors improve by approximately a factor of two if 5 satellites are used. On the other hand, more satellites do not result in a large reduction of the systematic error. The systematic error is somewhat smaller for the CarbonSat constellation configuration achieving global coverage everyday. Finally, we recommend the CarbonSat constellation configuration that achieves daily global coverage.

Spaceborne monitoring of CO2 emissions from large cities and the impact of aerosols

2020 ◽  
Author(s):  
Sander Houweling ◽  
Jochen Landgraf ◽  
Friedemann Reum ◽  
Hein van Heck ◽  
Wei Tao ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
European Space Agency ◽  
Monitoring Network ◽  
Atmospheric Measurements ◽  
Large Cities ◽  
Anthropogenic Co2 ◽  
Space Agency ◽  
Spatial Coverage ◽  
Spaceborne Monitoring ◽  
The Impact

&lt;p&gt;International agreements to reduce CO2 emissions call for an independent mechanism for evaluating the compliance with emission reduction targets. Atmospheric measurements can provide important information in support of this goal. However, to do this globally requires a drastic expansion of the existing monitoring network, using a combination of surface measurements and satellites. CO2 sensing satellites can deliver the required spatial coverage, filling in the gaps that are difficult to cover on ground. However, to reach the accuracy that is required for monitoring CO2 from space is a challenge, and even more so for anthropogenic CO2.&lt;/p&gt;&lt;p&gt;The European space agency is preparing for the launch of a constellation of satellites for monitoring anthropogenic CO2 within the Copernicus program, starting in 2025. Scientific support studies have been carried out to define this mission in terms of payload and observational requirements. We report on the AeroCarb study, which investigated the impact retrieval errors due to aerosols in CO2 plumes downwind of large cities, and the potential benefit of an onboard aerosol sensor to help mitigate such errors. In this study, CO2 and aerosol plumes have been simulated at high-resolution for the cities of Berlin and Beijing. The impact of aerosol scattering on spaceborne CO2 measurements has been assessed using a combined CO2-aerosol retrieval scheme, with and without the use of an onboard multi-angular spectropolarimeter (MAP) for measuring aerosols. The results have been used to quantify the accuracy at which the CO2 emissions of Berlin and Beijing can be quantified using inverse modelling and the impact of aerosols depending on the chosen satellite payload.&amp;#160;&lt;/p&gt;&lt;p&gt;In this presentation we summarize the outcome of this study, and discuss the implications for the space borne monitoring of anthropogenic CO2 emissions from large cities.&lt;/p&gt;

Impact of using various prior flux models on the posterior NEE derived from the Jena Carboscope regional inversion system

2020 ◽  
Author(s):  
Saqr Munassar ◽  
Christoph Gerbig ◽  
Frank-Thomas Koch ◽  
Christian Rödenbeck
Keyword(s):  
Fossil Fuel ◽  
A Priori ◽  
Net Ecosystem Exchange ◽  
Observation System ◽  
Mixing Ratio ◽  
British Petroleum ◽  
Respiration Model ◽  
Atmospheric Data ◽  
The Impact ◽  
Fossil Fuel Emissions

&lt;p&gt;Regional flux estimates over Europe have been calculated using the two-step inverse system of the Jena CarboScope Regional inversion (CSR) to estimate the annual CO&lt;sub&gt;2&lt;/sub&gt; budgets for recent years, in cooperation with the research project VERIFY. The CSR system assimilates observational datasets of CO&lt;sub&gt;2&lt;/sub&gt; mixing ratio provided by the Integrated Carbon Observation System (ICOS) across the European domain to optimize Net Ecosystem Exchange (NEE) fluxes computed from biosphere models at a spatial resolution of 0.25 degree. Ocean fluxes are assumed to be constant over time. Fossil fuel emissions are obtained from EDGAR_v4.3 and updated based on British Petroleum (BP) statistics. Therefore, only biosphere-atmosphere exchange fluxes are considered to be optimized against the atmospheric data.&lt;/p&gt;&lt;p&gt;In this study we focus on the impact of using a-priori fluxes from different biosphere and ocean models on the annual CO&lt;sub&gt;2&lt;/sub&gt; budget of posterior fluxes. Results calculated using the Vegetation and Photosynthesis Respiration Model (VPRM) and Simple Biosphere/Carnegie-Ames Stanford Approach (SiBCASA) models show a consistent posterior interannual variability, largely independent of which prior fluxes are used, even though those prior fluxes show considerable differences on annual scales.&lt;/p&gt;

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