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.

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

2016 ◽  
Vol 16 (9) ◽  
pp. 5481-5495 ◽  
Author(s):  
Elizabeth D. Keller ◽  
Jocelyn C. Turnbull ◽  
Margaret W. Norris
Keyword(s):  
Point Source ◽  
Co2 Emissions ◽  
Tree Ring ◽  
Power Plants ◽  
Model Simulation ◽  
Treatment Plant ◽  
Point Sources ◽  
Gas Treatment ◽  
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 2004–2005 and 2011–2012 from two trees growing near the Kapuni Gas Treatment 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 the 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 is reduced 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 sustained emissions changes on the order of 10 %, given suitable meteorology and observations.

scholarly journals Effects of point source emission heights in WRF–STILT: a step towards exploiting nocturnal observations in models

2021 ◽  
Author(s):  
Fabian Maier ◽  
Christoph Gerbig ◽  
Ingeborg Levin ◽  
Ingrid Super ◽  
Julia Marshall ◽  
...  
Keyword(s):  
Point Source ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Ground Level ◽  
Point Sources ◽  
Observation Site ◽  
Surface Source ◽  
Concentration Difference ◽  
Nearby Point

Abstract. An appropriate representation of point source emissions in atmospheric transport models is very challenging. In the Stochastic Time Inverted Lagrangian Transport model (STILT), all point source emissions are typically released from the surface, meaning that the actual emission stack height plus subsequent plume rise is not considered. This can lead to erroneous predictions of trace gas concentrations, especially during nighttime when vertical atmospheric mixing is minimal. In this study we use two WRF–STILT model approaches to simulate fossil fuel CO2 (ffCO2) concentrations: (1) the standard “surface source influence (SSI)” approach, and (2) an alternative “volume source influence (VSI)” approach, where nearby point sources release CO2 according to their effective emission height profiles. The comparison with 14C-based measured ffCO2 data from two-week integrated afternoon and nighttime samples collected at Heidelberg, 30 m above ground level, shows that the root-mean-square deviation (RMSD) between modelled and measured ffCO2 is indeed almost twice as high during night (RMSD = 6.3 ppm) compared to the afternoon (RMSD = 3.7 ppm) when using the standard SSI approach. In contrast, the VSI approach leads to a much better performance at nighttime (RMSD = 3.4 ppm), which is similar to its performance during afternoon (RMSD = 3.7 ppm). Representing nearby point source emissions with the VSI approach could, thus, be a first step towards exploiting nocturnal observations in STILT. To further investigate the differences between these two approaches, we conducted a model experiment in which we simulated the ffCO2 contributions from 12 artificial power plants with typical annual emissions of one million tons of CO2 and with distances between 5 and 200 km from the Heidelberg observation site. We find that such a power plant must be more than 50 km away from the observation site in order for the mean modelled ffCO2 concentration difference between the SSI and VSI approach to fall below 0.1 ppm.

Quantifying CO2 emissions of power plants with the CO2M mission

2021 ◽  
Author(s):  
Gerrit Kuhlmann ◽  
Stephan Henne ◽  
Yasjka Meijer ◽  
Lukas Emmenegger ◽  
Dominik Brunner
Keyword(s):  
Mass Balance ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Detection Algorithm ◽  
Point Sources ◽  
Satellite Mission ◽  
Temporal Sampling ◽  
Balance Approach ◽  
Mass Balance Approach

&lt;p&gt;In this study, we analyse the capability of the Copernicus CO&lt;sub&gt;2&lt;/sub&gt; monitoring (CO2M) satellite mission to quantify the CO&lt;sub&gt;2&lt;/sub&gt; emissions of individual power plants, which is one of the prime goals of the mission. The study relies on synthetic CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;2&lt;/sub&gt; satellite observations over parts of the Czech Republic, Germany and Poland and quantifies the CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;x&lt;/sub&gt; emissions of the 15 largest power plants in that region using a data-driven mass-balance approach.&lt;/p&gt;&lt;p&gt;The synthetic observations were generated for six CO2M satellites based on high-resolution simulations of the atmospheric transport model COSMO-GHG. To identify the emission plumes, we developed a plume detection algorithm that identifies the location, orientation and extent of multiple plumes from CO2M's NO&lt;sub&gt;2&lt;/sub&gt; observations. Afterwards, a mass-balance approach was applied to individual plumes to estimate CO&lt;sub&gt;2&lt;/sub&gt; and NO&lt;sub&gt;x&lt;/sub&gt; emissions by fitting Gaussian curves to the across-plume signals. Annual emissions were obtained by interpolating the temporally sparse individual estimates applying a low-order spline fit.&lt;/p&gt;&lt;p&gt;Individual CO&lt;sub&gt;2&lt;/sub&gt; emissions were estimated with an accuracy &lt;65% for a source strength &gt;10 Mt CO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;-1&lt;/sup&gt;, while NO&lt;sub&gt;x&lt;/sub&gt; emissions &gt;10 kt NO&lt;sub&gt;2&lt;/sub&gt; yr&lt;sup&gt;-1 &lt;/sup&gt;were estimated with &lt;56% accuracy. NO&lt;sub&gt;2&lt;/sub&gt; observations were essential for detecting the plume and constraining the shape of the Gaussian curve. With three CO2M satellites, annual CO&lt;sub&gt;2&lt;/sub&gt; emissions were estimated with an uncertainty &lt;30% for source strengths larger than 10 Mt yr&lt;sup&gt;-1&lt;/sup&gt;, which includes an estimate of the uncertainty in the temporal variability of emissions. Annual NO&lt;sub&gt;x&lt;/sub&gt; emissions were estimated with an uncertainty &lt;21%. Since NO&lt;sub&gt;x&lt;/sub&gt; emissions can be determined with better accuracy, estimating CO&lt;sub&gt;2&lt;/sub&gt; emissions directly from the NO&lt;sub&gt;x&lt;/sub&gt; emissions by applying a representative CO&lt;sub&gt;2&lt;/sub&gt;:NO&lt;sub&gt;x&lt;/sub&gt; emission ratio &amp;#160;seems appealing but this approach was found to suffer significantly from the high uncertainty in the&amp;#160; CO&lt;sub&gt;2&lt;/sub&gt;:NO&lt;sub&gt;x&lt;/sub&gt; emission ratios determined from the same CO2M observations.&lt;/p&gt;&lt;p&gt;Our study shows that CO2M should be able to quantify the emissions of the 400 largest point sources globally with emissions larger than 10 Mt yr&lt;sup&gt;-1&lt;/sup&gt; that account for about 20 % of global anthropogenic CO&lt;sub&gt;2&lt;/sub&gt; emissions. However, the mass-balance approach used here has relatively high uncertainties that are dominated by the uncertainties in the estimated CO&lt;sub&gt;2&lt;/sub&gt; background and the wind speed in the plume, and uncertainties associated with the sparse temporal sampling of the varying emissions. Estimates could be significantly improved if these parameters can be better constrained, e.g., with atmospheric transport simulations and independent observations.&lt;/p&gt;

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 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 Modelling atmospheric transport of α-hexachlorocyclohexane in the Northern Hemispherewith a 3-D dynamical model: DEHM-POP

2004 ◽  
Vol 4 (4) ◽  
pp. 1125-1137 ◽  
Author(s):  
K. M. Hansen ◽  
J. H. Christensen ◽  
J. Brandt ◽  
L. M. Frohn ◽  
C. Geels
Keyword(s):  
Environmental Fate ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Model Development ◽  
Average Concentration ◽  
The Arctic ◽  
Atmospheric Concentration ◽  
Surface Exchange ◽  
Exchange Processes

Abstract. The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur into the Arctic. A new version of the model, DEHM-POP, developed to study the atmospheric transport and environmental fate of persistent organic pollutants (POPs) is presented. During environmental cycling, POPs can be deposited and re-emitted several times before reaching a final destination. A description of the exchange processes between the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The α-isomer of the pesticide hexachlorocyclohexane (α-HCH) is used as tracer in the model development. The structure of the model and processes included are described in detail. The results from a model simulation showing the atmospheric transport for the years 1991 to 1998 are presented and evaluated against measurements. The annual averaged atmospheric concentration of α-HCH for the 1990s is well described by the model; however, the shorter-term average concentration for most of the stations is not well captured. This indicates that the present simple surface description needs to be refined to get a better description of the air-surface exchange processes of POPs.

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