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 Towards space-borne monitoring of localized CO2 emissions: an instrument concept and first performance assessment

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

&lt;p&gt;Independent verification of reported carbon dioxide (CO2) emissions is a corner stone for advancing towards emission accounting and reduction measures agreed upon in the Paris agreement. Here, we present the concept and first performance assessment of a compact space-borne imaging spectrometer that could support the task of &quot;monitoring, verification, reporting'' (MVR) of CO2 emissions worldwide. With a ground resolution of 50m x 50m, the goal is to estimate the CO2 emissions from localized sources down to a source strength of approx. 1 MtCO2/yr, hence complementing other planned CO2 monitoring missions, like the European Carbon Constellation (CO2M).&lt;/p&gt;&lt;p&gt;Such fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, a fleet of satellites, each carrying such an instrument is envisioned, requiring a relatively low-cost and simple design, e.g. by restricting the spectrometer to a single spectral window. To demonstrate that column-averaged dry-air mole-fractions of CO2 (XCO2) can be reliably retrieved with a single spectral window and at the required coarse spectral resolution, we use degraded GOSAT short-wave infrared spectra of the CO2 bands near 1.6 and 2.0 &amp;#181;m, respectively.&lt;/p&gt;&lt;p&gt;Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is further shown that an instrument noise error of 1.1 ppm (1sigma) can be achieved for the XCO2 retrieval. Despite the 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, with deviations of at most 4.0 ppm from the true abundance for 68 % of the scenes in the global trial ensemble.&lt;/p&gt;&lt;p&gt;Finally we simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban environment 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 can be resolved, i.e. well below the target source strength of 1 MtCO2/yr. Hence, some margin for additional error sources like scattering particles and complex meteorology exists.&lt;/p&gt;

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

2020 ◽  
Vol 13 (6) ◽  
pp. 2887-2904 ◽  
Author(s):  
Johan Strandgren ◽  
David Krutz ◽  
Jonas Wilzewski ◽  
Carsten Paproth ◽  
Ilse Sebastian ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Co2 Flux ◽  
Point Sources ◽  
Noise Model ◽  
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. The independent verification of these reported emissions is a cornerstone for advancing towards the 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 spaceborne imaging spectrometer with a spatial resolution of 50×50 m2 that could contribute to the “monitoring, verification and reporting” (MVR) of CO2 emissions worldwide. CO2 emissions from medium-sized power plants (1–10 Mt CO2 yr−1), currently not targeted by other spaceborne missions, represent a significant part of the global CO2 emission budget. In this paper we show that the proposed instrument concept is able to resolve emission plumes from such localized sources as a first step towards corresponding CO2 flux estimates. 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 a 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 two-thirds 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 Mt CO2 yr−1 can be resolved, i.e., well below the target source strength of 1 Mt CO2 yr−1. This leaves a significant margin for additional error sources, like scattering particles and complex meteorology, and shows the potential for subsequent CO2 flux estimates with the proposed instrument concept.

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 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 CO2 Emission Calculation and Emission Characteristics Analysis of Typical 600MW Coal-fired Thermal Power Unit

2020 ◽  
Vol 165 ◽  
pp. 01029 ◽  
Author(s):  
Yu Honghai ◽  
Wang Zhi ◽  
Chen Li ◽  
Wu Jianan
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Emission Intensity ◽  
Co2 Emission ◽  
Power Plants ◽  
Thermal Power ◽  
Emission Characteristics ◽  
The Past ◽  
Characteristics Analysis ◽  
Co2 Emission Intensity

In order to effectively reduce the total CO2 emissions of coal-fired power plants and reduce greenhouse gas emissions, the relevant data of a typical 600MW coal-fired power plant in the past five years was collected and investigated, and CO2 emissions and emission intensity were calculated. And the results were used to measure the CO2 emission level of coal-fired power plants. By comparing and analyzing the CO2 emission intensity and emission trend of 600MW coal-fired units with different unit types and different fuel types, the CO2 emission characteristics of typical 600MW coal-fired power plants are obtained.

Design, calibration, and application of an airborne gamma spectrometer system in Switzerland

Geophysics ◽  
1997 ◽  
Vol 62 (5) ◽  
pp. 1369-1378 ◽  
Author(s):  
Georg F. Schwarz ◽  
Ladislaus Rybach ◽  
Emile E. Klingelé
Keyword(s):  
Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Gamma Ray ◽  
Point Sources ◽  
Swiss Alps ◽  
Artificial Radioactivity ◽  
Radiation Level ◽  
Satellite Navigation System ◽  
Emergency Situations

Airborne radiometric surveys are finding increasingly wider applications in environmental mapping and monitoring. They are the most efficient tool to delimit surface contamination and to locate lost radioactive sources. To secure radiometric capability in survey and emergency situations, a new sensitive airborne system has been built that includes an airborne spectrometer with 256 channels and a sodium iodide detector with a total volume of 16.8 liters. A rack mounted PC with memory cards is used for data acquisition, with a GPS satellite navigation system for positioning. The system was calibrated with point sources using a mathematical correction to take into account the effects of gamma‐ray scattering in the ground and in the atmosphere. The calibration was complemented by high precision ground gamma spectrometry and laboratory measurements on rock samples. In Switzerland, two major research programs make use of the capabilities of airborne radiometric measurements. The first one concerns nuclear power plant monitoring. The five Swiss nuclear installations (four power plants and one research facility) and the surrounding regions of each site are surveyed annually. The project goal is to monitor the dose‐rate distribution and to provide a documented baseline database. The measurements show that all sites (with the exception of the Gösgen power plant) can be identified clearly on the maps. No artificial radioactivity that could not be explained by the Chernobyl release or earlier nuclear weapons tests was detected outside of the fenced sites of the nuclear installations. The second program aims at a better evaluation of the natural radiation level in Switzerland. The survey focused on the crystalline rocks of the Central Massifs of the Swiss Alps because of their relatively high natural radioactivity and lithological variability.

scholarly journals Comparative Environmental, Economic, and Jobs Impacts in the USA of Renewable Energy Compared to Carbon Capture, Utilization, and Storage

2021 ◽  
pp. 1-7
Author(s):  
Roger H Bezdek ◽  
Keyword(s):  
Renewable Energy ◽  
Environmental Economic ◽  
Power Plant ◽  
Co2 Emissions ◽  
Carbon Capture ◽  
Power Plants ◽  
Economic Benefits ◽  
The Usa ◽  
Coal Power ◽  
And Storage

This paper assesses the relative economic and jobs benefits of retrofitting an 847 MW USA coal power plant with carbon capture, utilization, and storage (CCUS) technology compared to replacing the plant with renewable (RE) energy and battery storage. The research had two major objectives: 1) Estimate the relative environmental, economic, and jobs impacts of CCUS retrofit of the coal plant compared to its replacement by the RE scenario; 2) develop metrics that can be used to compare the jobs impacts of coal fueled power plants to those of renewable energy. The hypotheses tested are: 1) The RE option will reduce CO2 emissions more than the CCUS option. We reject this hypothesis: We found that the CCUS option will reduce CO2 emissions more than the RE option. 2) The RE option will generate greater economic benefits than the CCUS option. We reject this hypothesis: We found that the CCUS option will create greater economic and jobs benefits than the RE option. 3) The RE option will create more jobs per MW than the CCUS option. We reject this hypothesis: We found that the CCUS option will create more jobs per MW more than the RE option. We discuss the implications of these findings.

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.

scholarly journals What would dense atmospheric observation networks bring to the quantification of city CO<sub>2</sub> emissions?

2016 ◽  
Vol 16 (12) ◽  
pp. 7743-7771 ◽  
Author(s):  
Lin Wu ◽  
Grégoire Broquet ◽  
Philippe Ciais ◽  
Valentin Bellassen ◽  
Felix Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Metropolitan Area ◽  
Land Surface ◽  
Co2 Emission ◽  
Power Plants ◽  
Lower Cost ◽  
Residential Buildings ◽  
Inversion Method ◽  
Monitoring Tool ◽  
Model Framework

Abstract. Cities currently covering only a very small portion ( <  3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO2, but they are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. This monitoring tool is configured for the quantification of the total and sectoral CO2 emissions in the Paris metropolitan area (∼  12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO2 concentrations at research stations are expensive (typically ∼  EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO2 emission during 1 month is significantly reduced by the inversion by ∼  42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation–model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.

Sign in / Sign up

Export Citation Format

Share Document