scholarly journals Determination of the Emission Rates of CO<sub>2</sub> Point Sources with Airborne Lidar

2020 ◽  
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Power Plants ◽  
Point Sources ◽  
Airborne Lidar ◽  
Emission Rates ◽  
Flux Method ◽  
Cross Sectional ◽  
Spatial Coverage ◽  
International Climate Agreements ◽  
The Cross

Abstract. Anthropogenic point sources, such as coal-fired power plants, produce a major share of global CO2 emissions. International climate agreements demand their independent monitoring. Due to the high amount of point sources and their global spatial distribution, a mobile measurement approach with fast spatial coverage is needed. Active remote sensing measurements by airborne lidar show much promise in this respect. The integrated-path differential-absorption lidar CHARM–F is installed onboard an aircraft, in order to detect weighted vertical columns of CO2 mixing ratios, below the aircraft along its flight track. During the Carbon Dioxide and Methane mission (CoMet) in spring 2018, airborne greenhouse gas measurements were performed, focusing on the major European sources of anthropogenic CO2 emissions, i.e. large coal–fired power plants. The flights were designed to transect isolated exhaust plumes. From the resulting enhancement in the CO2 mixings ratios, emission rates can be derived in terms of the cross–sectional flux method. On average, we find our results roughly corresponding to reported annual emission rates, but observe significant variations between individual overflights ranging up to a factor of 2. We suppose that these variations are mostly driven by turbulence. This hypothesis is supported by a high–resolution large eddy simulation that enables us to give a qualitative assessment of the influence of plume inhomogeneity on the cross–sectional flux method. Our findings suggest avoiding periods of strong turbulence, e.g. midday and afternoon. More favorable measurement conditions prevail during nighttime and morning. Since lidars are intrinsically independent of sunlight, they have a significant advantage in this regard.

scholarly journals Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar

2021 ◽  
Vol 14 (4) ◽  
pp. 2717-2736
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Power Plants ◽  
Point Sources ◽  
Airborne Lidar ◽  
Observation System ◽  
Emission Rates ◽  
Flux Method ◽  
Cross Sectional ◽  
Mixing Ratios ◽  
The Cross

Abstract. Anthropogenic point sources, such as coal-fired power plants, produce a major share of global CO2 emissions. International climate agreements demand their independent monitoring. Due to the large number of point sources and their global spatial distribution, the implementation of a satellite-based observation system is convenient. Airborne active remote sensing measurements demonstrate that the deployment of lidar is promising in this respect. The integrated path differential absorption lidar CHARM-F is installed on board an aircraft in order to detect weighted column-integrated dry-air mixing ratios of CO2 below the aircraft along its flight track. During the Carbon Dioxide and Methane Mission (CoMet) in spring 2018, airborne greenhouse gas measurements were performed, focusing on the major European sources of anthropogenic CO2 emissions, i.e., large coal-fired power plants. The flights were designed to transect isolated exhaust plumes. From the resulting enhancement in the CO2 mixing ratios, emission rates can be derived via the cross-sectional flux method. On average, our results roughly correspond to reported annual emission rates, with wind speed uncertainties being the major source of error. We observe significant variations between individual overflights, ranging up to a factor of 2. We hypothesize that these variations are mostly driven by turbulence. This is confirmed by a high-resolution large eddy simulation that enables us to give a qualitative assessment of the influence of plume inhomogeneity on the cross-sectional flux method. Our findings suggest avoiding periods of strong turbulence, e.g., midday and afternoon. More favorable measurement conditions prevail during nighttime and morning. Since lidars are intrinsically independent of sunlight, they have a significant advantage in this regard.

scholarly journals Quantifying methane point sources from fine-scale (GHGSat) satellite observations of atmospheric methane plumes

2018 ◽  
Author(s):  
Daniel J. Varon ◽  
Daniel J. Jacob ◽  
Jason McKeever ◽  
Dylan Jervis ◽  
Berke O. A. Durak ◽  
...  
Keyword(s):  
Wind Speed ◽  
Methane Emissions ◽  
Point Sources ◽  
Small Scale ◽  
Atmospheric Methane ◽  
Flux Method ◽  
Pixel Resolution ◽  
Cross Sectional ◽  
Source Rate ◽  
The Cross

Abstract. Anthropogenic methane emissions originate from a large number of relatively small point sources. The planned GHGSat satellite fleet aims to quantify emissions from individual point sources by measuring methane column plumes over selected ~ 10 × 10 km2 domains with ≤ 50 × 50 m2 pixel resolution and 1–5 % measurement precision. Here we develop algorithms for retrieving point source rates from such measurements. We simulate a large ensemble of instantaneous methane column plumes at 50 × 50 m2 pixel resolution for a range of atmospheric conditions using the Weather Research and Forecasting model (WRF) in large eddy simulation (LES) mode and adding instrument noise. We show that standard methods to infer source rates by Gaussian plume inversion or source pixel mass balance are prone to large errors because the turbulence cannot be properly parameterized on the small scale of instantaneous methane plumes. The integrated mass enhancement (IME) method, which relates total plume mass to source rate, and the cross-sectional flux method, which infers source rate from fluxes across plume transects, are better adapted to the problem. We show that the IME method with local measurements of the 10-m wind speed can infer source rates with error of 0.07–0.17 t h−1 + 5–12 % depending on instrument precision (1–5 %). The cross-sectional flux method has slightly larger errors (0.07–0.26 t h−1 + 8–12 %) but a simpler physical basis. For comparison, point sources larger than 0.5 t h−1 contribute more than 75 % of methane emissions reported to the U.S. Greenhouse Gas Reporting Program. Additional error applies if local wind speed measurements are not available, and may dominate the overall error at low wind speeds. Low winds are beneficial for source detection but not for source quantification.

scholarly journals Quantification of CO2 Emission Rates from Large Coal-Fired Power Plants Using Airborne Lidar during CoMet 

2021 ◽  
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Fraction ◽  
Early Morning ◽  
Point Sources ◽  
Airborne Lidar ◽  
Emission Rates ◽  
Vertical Column ◽  
Mixing Ratios ◽  
Research Aircraft ◽  
Plant Emissions

&lt;p&gt;A large fraction of global anthropogenic greenhouse gas emissions originates from localized point sources. International climate treaties foresee their independent monitoring. Given the high number of point sources and their global spatial distribution, local monitoring is challenging, whereas a global satellite-based observing system is advantageous. In this perspective, a promising measurement approach is active remote sensing by airborne lidar, such as provided by the integrated-path differential-absorption lidar CHARM-F. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken at the largest European point sources of anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; emissions, i.e. coal-fired power plants and ventilation shafts of coal mines. The measurement flights aimed to transect isolated exhaust plumes, in order to derive the corresponding emission rates from the resulting enhancement in concentration, along the plume crossing. For the first time, multiple measurements of power plant emissions were made using airborne lidar. On average, we find that our measurements are consistent with reported numbers, but observe high discrepancies between successive plume crossings of up to 50 %. As an explanation for these high discrepancies, we assess the influence of inhomogeneity in the exhaust plume, caused by atmospheric turbulence. This assessment is based on the Weather Research and Forecasting Model (WRF). We find a pronounced diurnal cycle of plume inhomogeneity associated with local turbulence, predominately driven by midday solar irradiance. Our results reveal that periods of high turbulence, specifically during midday and afternoon, should be avoided whenever possible. Since lidar is intrinsically independent of sun light, measurements can be performed under conditions of weak turbulence, such as at night or in the early morning.&lt;/p&gt;

scholarly journals Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes

2018 ◽  
Vol 11 (10) ◽  
pp. 5673-5686 ◽  
Author(s):  
Daniel J. Varon ◽  
Daniel J. Jacob ◽  
Jason McKeever ◽  
Dylan Jervis ◽  
Berke O. A. Durak ◽  
...  
Keyword(s):  
Wind Speed ◽  
Methane Emissions ◽  
Point Sources ◽  
Small Scale ◽  
Atmospheric Methane ◽  
Flux Method ◽  
Pixel Resolution ◽  
Cross Sectional ◽  
Source Rate ◽  
The Cross

Abstract. Anthropogenic methane emissions originate from a large number of relatively small point sources. The planned GHGSat satellite fleet aims to quantify emissions from individual point sources by measuring methane column plumes over selected ∼10×10 km2 domains with ≤50×50 m2 pixel resolution and 1 %–5 % measurement precision. Here we develop algorithms for retrieving point source rates from such measurements. We simulate a large ensemble of instantaneous methane column plumes at 50×50 m2 pixel resolution for a range of atmospheric conditions using the Weather Research and Forecasting model (WRF) in large eddy simulation (LES) mode and adding instrument noise. We show that standard methods to infer source rates by Gaussian plume inversion or source pixel mass balance are prone to large errors because the turbulence cannot be properly parameterized on the small scale of instantaneous methane plumes. The integrated mass enhancement (IME) method, which relates total plume mass to source rate, and the cross-sectional flux method, which infers source rate from fluxes across plume transects, are better adapted to the problem. We show that the IME method with local measurements of the 10 m wind speed can infer source rates with an error of 0.07–0.17 t h-1+5 %–12 % depending on instrument precision (1 %–5 %). The cross-sectional flux method has slightly larger errors (0.07–0.26 t h-1+8 %–12 %) but a simpler physical basis. For comparison, point sources larger than 0.3 t h−1 contribute more than 75 % of methane emissions reported to the US Greenhouse Gas Reporting Program. Additional error applies if local wind speed measurements are not available and may dominate the overall error at low wind speeds. Low winds are beneficial for source detection but detrimental for source quantification.

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.

Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling

2021 ◽  
Author(s):  
Sebastian Wolff ◽  
Friedemann Reum ◽  
Christoph Kiemle ◽  
Gerhard Ehret ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Remote Sensing ◽  
A Priori ◽  
Point Sources ◽  
Airborne Lidar ◽  
Inverse Modelling ◽  
Emission Rates ◽  
Coal Basin ◽  
Upper Silesian Coal Basin ◽  
The Individual ◽  
Modelling Approach

&lt;p&gt;Methane (CH&lt;sub&gt;4&lt;/sub&gt;) is the second most important anthropogenic greenhouse gas (GHG) with respect to radiative forcing. Since pre-industrial times, the globally averaged CH&lt;sub&gt;4&lt;/sub&gt; concentration in the atmosphere has risen by a factor of 2.5. A large fraction of global anthropogenic CH&lt;sub&gt;4&lt;/sub&gt; emissions originates from localized point sources, e.g. coal mine ventilation shafts. International treaties foresee GHG emission reductions, entailing independent monitoring and verification support capacities. Considering the spatially widespread distribution of point sources, remote sensing approaches are favourable, in order to enable rapid survey of larger areas. In this respect, active remote sensing by airborne lidar is promising, such as provided by the integrated-path differential-absorption lidar CHARM-F operated by DLR. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken in the Upper Silesian Coal Basin (USCB) in Poland. The USCB is considered to be a European hotspot of CH&lt;sub&gt;4&lt;/sub&gt; emissions, covering an area of approximately 50 km &amp;#215; 50 km. Due to the high number of coal mines and density of ventilation shafts in the USCB, individual CH&lt;sub&gt;4&lt;/sub&gt; exhaust plumes can overlap. This makes simple approaches to determine the emission rates of single shafts, i.e. the cross-sectional flux method, difficult. Therefore, we use an inverse modelling approach to obtain an estimate of the individual emission rates. Specifically, we employ the Weather Research and Forecast Model (WRF) coupled to the CarbonTracker Data Assimilation Shell (CTDAS), an Ensemble Kalman Filter. CTDAS-WRF propagates an ensemble realization of the a priori CH&lt;sub&gt;4&lt;/sub&gt; emissions forward in space and time, samples the simulated CH&lt;sub&gt;4&lt;/sub&gt; concentrations along the measurement&amp;#8217;s flight path, and scales the a priori emission rates to optimally fit the measured values, while remaining tied to the prior. Hereby, we obtain a regularized a posteriori best emission estimate for the individual ventilation shafts. Here, we report on the results of this inverse modelling approach, including individual and aggregated emission estimates, their uncertainties, and to which extent the data are able to constrain individual emitters independently.&lt;/p&gt;

scholarly journals Towards monitoring localized CO<sub>2</sub> emissions from space: co-located regional CO<sub>2</sub> and NO<sub>2</sub> enhancements observed by the OCO-2 and S5P satellites

2019 ◽  
Author(s):  
Maximilian Reuter ◽  
Michael Buchwitz ◽  
Oliver Schneising ◽  
Sven Krautwurst ◽  
Christopher W. O'Dell ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Plants ◽  
Fossil Fuels ◽  
Open Data ◽  
Point Sources ◽  
Background Concentration ◽  
Multiple Sources ◽  
Cross Sectional ◽  
Fire Emissions ◽  
Dry Air

Abstract. Despite its key role for climate change, large uncertainties persist in our knowledge of the anthropogenic emissions of carbon dioxide (CO2) and no global observing system exists allowing to monitor emissions from localized CO2 sources with sufficient accuracy. The Orbiting Carbon Observatory-2 (OCO-2) satellite can retrieve the column-average dry-air mole fractions of CO2 (XCO2). However, regional column-average enhancements of individual point sources are usually small compared to the background concentration and its natural variability. This makes the unambiguous identification and quantification of anthropogenic emission plume signals challenging. NO2 is co-emitted with CO2 when fossil fuels are combusted at high temperatures. It has a short lifetime of the order of hours so that NO2 columns often exceed background levels by orders of magnitude near sources making it a suitable tracer of recently emitted CO2. Based on six case studies (Moscow, Russia; Lipetsk, Russia; Baghdad, Iraq; Medupi and Matimba power plants, South Africa; Australian wildfires; and Nanjing, China), we demonstrate the usefulness of simultaneous satellite observations of NO2 and the column-average dry-air mole fraction of CO2 (XCO2). For this purpose, we analyze co-located regional enhancements of XCO2 observed by OCO-2 and NO2 observed by the Sentinel-5 Precursor (S5P) satellite and estimate the CO2 plume's cross-sectional fluxes. We take advantage of the nearly simultaneous NO2 measurements with S5P's wide swath by identifying the source of the observed XCO2 enhancements, excluding interference with remote upwind sources, allowing to adjust the wind direction, and by constraining the shape of the CO2 plumes. We compare the inferred cross-sectional fluxes with the Emissions Database for Global Atmospheric Research (EDGAR), the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC), and, in the case of the Australian wildfires, with the Global Fire Emissions Database (GFED). The inferred cross-sectional fluxes range from 32 Mt CO2/a to 158 Mt CO2/a with uncertainties (1σ) between 23 % and 72 %. For the majority of analyzed emission sources, the estimated cross-sectional fluxes agree within their uncertainty with either EDGAR or ODIAC or lie in between them. We assess the contribution of multiple sources of uncertainty and find that the dominating contributions are related to the computation of the effective wind speed normal to the plume's cross-section. The planned European Copernicus anthropogenic CO2 monitoring mission (CO2M) will not only provide precise measurements with high spatial resolution but also imaging capabilities with a wider swath of simultaneous XCO2 and NO2 observations. Such a mission, in particular as a constellation of satellites, will deliver CO2 emission estimates from localized sources at an unprecedented frequency and level of accuracy.

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 Towards monitoring localized CO<sub>2</sub> emissions from space: co-located regional CO<sub>2</sub> and NO<sub>2</sub> enhancements observed by the OCO-2 and S5P satellites

2019 ◽  
Vol 19 (14) ◽  
pp. 9371-9383 ◽  
Author(s):  
Maximilian Reuter ◽  
Michael Buchwitz ◽  
Oliver Schneising ◽  
Sven Krautwurst ◽  
Christopher W. O'Dell ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Plants ◽  
Fossil Fuels ◽  
Open Data ◽  
Point Sources ◽  
Measurement Noise ◽  
Background Concentration ◽  
Multiple Sources ◽  
Cross Sectional ◽  
Fire Emissions

Abstract. Despite its key role in climate change, large uncertainties persist in our knowledge of the anthropogenic emissions of carbon dioxide (CO2) and no global observing system exists that allows us to monitor emissions from localized CO2 sources with sufficient accuracy. The Orbiting Carbon Observatory-2 (OCO-2) satellite allows retrievals of the column-average dry-air mole fractions of CO2 (XCO2). However, regional column-average enhancements of individual point sources are usually small, compared to the background concentration and its natural variability, and often not much larger than the satellite's measurement noise. This makes the unambiguous identification and quantification of anthropogenic emission plume signals challenging. NO2 is co-emitted with CO2 when fossil fuels are combusted at high temperatures. It has a short lifetime on the order of hours so that NO2 columns often greatly exceed background and noise levels of modern satellite sensors near sources, which makes it a suitable tracer of recently emitted CO2. Based on six case studies (Moscow, Russia; Lipetsk, Russia; Baghdad, Iraq; Medupi and Matimba power plants, South Africa; Australian wildfires; and Nanjing, China), we demonstrate the usefulness of simultaneous satellite observations of NO2 and XCO2. For this purpose, we analyze co-located regional enhancements of XCO2 observed by OCO-2 and NO2 from the Sentinel-5 Precursor (S5P) satellite and estimate the CO2 plume's cross-sectional fluxes. We take advantage of the nearly simultaneous NO2 measurements with S5P's wide swath and small measurement noise by identifying the source of the observed XCO2 enhancements, excluding interference with remote upwind sources, allowing us to adjust the wind direction, and by constraining the shape of the CO2 plumes. We compare the inferred cross-sectional fluxes with the Emissions Database for Global Atmospheric Research (EDGAR), the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC), and, in the case of the Australian wildfires, with the Global Fire Emissions Database (GFED). The inferred cross-sectional fluxes range from 31 MtCO2 a−1 to 153 MtCO2 a−1 with uncertainties (1σ) between 23 % and 72 %. For the majority of analyzed emission sources, the estimated cross-sectional fluxes agree, within their uncertainty, with either EDGAR or ODIAC or lie somewhere between them. We assess the contribution of multiple sources of uncertainty and find that the dominating contributions are related to the computation of the effective wind speed normal to the plume's cross section. The flux uncertainties are expected to be reduced by the planned European Copernicus anthropogenic CO2 monitoring mission (CO2M), which will provide not only precise measurements with high spatial resolution but also imaging capabilities with a wider swath of simultaneous XCO2 and NO2 observations. Such a mission, particularly if performed by a constellation of satellites, will deliver CO2 emission estimates from localized sources at an unprecedented frequency and level of accuracy.

scholarly journals Detecting long-term changes in point source fossil CO<sub>2</sub> emissions with tree ring archives

2016 ◽  
Author(s):  
E. D. Keller ◽  
J. C. Turnbull ◽  
M. W. Norris
Keyword(s):  
Point Source ◽  
Co2 Emissions ◽  
Tree Ring ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Point Sources ◽  
Long Term Changes

Abstract. We examine the utility of tree ring 14C archives for detecting long term changes in fossil CO2 emissions from a point source. Trees assimilate carbon from the atmosphere during photosynthesis, in the process faithfully recording the average atmospheric 14C content in each new annual tree ring. Using 14C as a proxy for fossil CO2, we examine interannual variability over six years of fossil CO2 observations between 2004-05 and 2011-12 from two trees growing near the Kapuni Natural Gas Plant in rural Taranaki, New Zealand. We quantify the amount of variability that can be attributed to transport and meteorology by simulating constant point source fossil CO2 emissions over the observation period with the atmospheric transport model WindTrax. We compare model simulation results to observations and calculate the amount of change in emissions that we can detect with new observations over annual or multi-year time periods given both measurement uncertainty of 1ppm and the modelled variation in transport. In particular, we ask, what is the minimum amount of change in emissions that we can detect using this method, given a reference period of six years? We find that changes of 42% or more could be detected in a new sample from one year at the same observation location, or 22% in the case of four years of new samples. This threshold lowers and the method becomes more practical the more the size of the signal increases. For point sources 10 times larger than the Kapuni plant (a more typical size for power plants worldwide), it would be possible to detect sustaine d emissions changes on the order of 10% given suitable meteorology and observations.

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