scholarly journals A local- to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions

2021 ◽  
Vol 14 (1) ◽  
pp. 403-433
Author(s):  
Diego Santaren ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Frédéric Chevallier ◽  
Denis Siméoni ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Plants ◽  
Western Europe ◽  
Transport Model ◽  
Strong Dependence ◽  
Point Sources ◽  
Anthropogenic Emissions ◽  
Modeling Framework ◽  
Wide Range ◽  
Regional Budgets

Abstract. This work presents a flux inversion system which assesses the potential of new satellite imagery measurements of atmospheric CO2 for monitoring anthropogenic emissions at scales ranging from local intense point sources to regional and national scales. Such imagery measurements will be provided by the future Copernicus Anthropogenic Carbon Dioxide Monitoring Mission (CO2M). While the modeling framework retains the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the CHIMERE regional transport model which covers most of western Europe with a 2 km resolution grid over northern France, western Germany and Benelux. For each day of March and May 2016, over the 6 h before a given satellite overpass, the inversion separately controls the hourly budgets of anthropogenic emissions in this area from ∼ 300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budget and spatial extent while accounting for the uncertainties associated with natural fluxes and the overlapping of plumes from different sources. The potential of satellite data for monitoring CO2 fluxes is quantified with posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. A first analysis focuses on the hourly to 6 h budgets of the emissions of the Paris urban area and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions of emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system's ability to separately monitor neighboring sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions on the emission budgets, on the wind speed and on whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. All of the tests are conducted considering clear-sky conditions, and the limitations from cloud cover are ignored. Furthermore, in these tests, the inversion system is perfectly informed about the statistical properties of the various sources of errors that are accounted for, and systematic errors in the XCO2 retrievals are ignored; thus, the scores of URs are assumed to be optimistic. For the emissions within the 6 h before a satellite overpass, URs of more than 50 % can only be achieved for power plants and cities whose annual emissions are more than ∼ 2 MtC yr−1. For regional budgets encompassing more diffuse emissions, this threshold increases up to ∼ 10 MtC yr−1. The results therefore suggest an imbalance in the monitoring capabilities of the satellite XCO2 spectro-imagery towards high and dense sources.

scholarly journals A local to national-scale inverse modeling system to assess the potential of spaceborne CO<sub>2</sub> measurements for the monitoring of anthropogenic emissions

2020 ◽  
Author(s):  
Diego Santaren ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Frédéric Chevallier ◽  
Denis Siméoni ◽  
...  
Keyword(s):  
Wind Speed ◽  
Power Plants ◽  
Western Europe ◽  
Transport Model ◽  
Strong Dependence ◽  
Point Sources ◽  
Anthropogenic Emissions ◽  
Modeling Framework ◽  
Wide Range ◽  
Regional Budgets

Abstract. This work presents a flux inversion system for assessing the potential of new satellite imagery measurements of atmospheric CO2 to monitor anthropogenic emissions at scales ranging from local intense point sources to regional and national scales. While the modeling framework keeps the complexity of previous studies focused on individual and large cities, this system encompasses a wide range of sources to extend the scope of the analysis. This atmospheric inversion system uses a zoomed configuration of the regional transport model CHIMERE which covers most of Western Europe with a 2-km resolution grid over Northern France, Western Germany and Benelux. For each day of March and May 2016, over the 6 hours before a given satellite overpass, the inversion controls separately the hourly budgets of anthropogenic emissions in this area from ~300 cities, power plants and regions. The inversion also controls hourly regional budgets of the natural fluxes. This enables the analysis of results at the local to regional scales for a wide range of sources in terms of emission budgets and spatial extent while accounting for the uncertainties associated with natural fluxes and the overlapping of plumes from different sources. The potential of satellite data to monitor CO2 fluxes is quantified by posterior uncertainties or uncertainty reductions (URs) from prior inventory-based statistical knowledge. A first analysis focuses on the hourly to 6-hour budgets of the emissions of the Paris urban area, and on the sensitivity of the results to different characteristics of the images of vertically integrated CO2 (XCO2) corresponding to the spaceborne instrument: the pixel spatial resolution, the precision of the XCO2 retrievals per pixel, and the swath width. This sensitivity analysis provides a correspondence between these parameters and thresholds on the targeted precisions on emission estimates. However, the results indicate a large sensitivity to the wind speed and to the prior flux uncertainties. The analysis is then extended to the large ensemble of point sources, cities and regions in the study domain, with a focus on the inversion system ability to monitor separately neighbor sources whose atmospheric signatures overlap and are also mixed with those produced by natural fluxes. Results highlight the strong dependence of uncertainty reductions to the emission budgets, to the wind speed and whether the focus is on point or area sources. With the system hypothesis that the atmospheric transport is perfectly known, the results indicate that the atmospheric signal overlap is not a critical issue. For the emissions within the 6-hours before a satellite overpass, UR of more than 50 % can only be achieved for power plants and cities whose annual emissions are more than ~2 MtC yr−1. For more regional budgets encompassing more diffuse emissions, this threshold increases up to ~10 MtC yr−1. The results suggest therefore an imbalance of the monitoring capabilities towards high and dense sources.

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 Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: quantification and attribution

2018 ◽  
Vol 11 (3) ◽  
pp. 1251-1272 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
ZhaoCheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Desert Grassland ◽  
Chemical Transport Model ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of the column-averaged dry air mole fraction of CO2 (XCO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a latitude band of 37–42° N segmented into 8 cells in a grid of 5° from west to east (80–120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7–1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0–1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO2 retrievals. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo.

scholarly journals Future climatic drivers and their effect on PM<sub>10</sub> components in Europe and the Mediterranean Sea

2018 ◽  
Author(s):  
Arineh Cholakian ◽  
Augustin Colette ◽  
Giancarlo Ciarelli ◽  
Isabelle Coll ◽  
Matthias Beekmann
Keyword(s):  
Long Range ◽  
Transport Model ◽  
Regional Climate ◽  
Strong Dependence ◽  
Long Range Transport ◽  
Anthropogenic Emissions ◽  
Future Scenarios ◽  
Anthropogenic Emission ◽  
Impact Study ◽  
Range Transport

Abstract. Multiple CMIP5 future scenarios are compared to historic simulations in order to study different drivers governing air pollution: Regional climate, anthropogenic emissions and long-range transport. Climate impact study covers the period of 2031 to 2100 for future scenarios compared to 1976 to 2005 for historic simulations, and includes three RCPs (Representative concentration pathways, RCP2.6, RCP4.5 and RCP8.5). A detailed analysis of total PM10 concentrations, its changes and also that of its components is included. The individual effects of meteorological conditions on PM10 components are explored in these scenarios in an effort to pinpoint the meteorological parameter(s) governing each component. Anthropogenic emission impact study covers the period of 2046 and 2055 with CLE2050 (Current legislation emissions for 2050) anthropogenic emissions compared to CLE2010 in historic simulations covering the period of 1996 to 2005. Long-range transport is explored by changing the initial and boundary conditions in the chemistry-transport model, these scenarios cover the same period as the emission impact studies. Finally, a cumulative effects of these drivers is performed and the contribution of each driver on PM10 and its components is calculated. The results show that, regional climate causes a decrease in PM10 concentration in our scenarios, as a result of a decrease in nitrate, sulfate, ammonium and dust in most scenarios. Meanwhile, biogenic secondary organic aerosols (BSOA) shows an important increase in all scenarios. Nitrate and BSOA show a strong dependence to temperature, while sulfates are dependent to relative humidity. A cumulative look at all drivers shows that anthropogenic emission changes overshadow changes caused by climate and long-range transport for most components except for dust, for which long-range transport changes seem to be more influential.

scholarly journals PMIF v1.0: assessing the potential of satellite observations to constrain CO<sub>2</sub> emissions from large cities and point sources over the globe using synthetic data

2020 ◽  
Vol 13 (11) ◽  
pp. 5813-5831 ◽  
Author(s):  
Yilong Wang ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Franck Lespinas ◽  
Michael Buchwitz ◽  
...  
Keyword(s):  
Power Plants ◽  
Transport Model ◽  
Time Windows ◽  
Full Range ◽  
European Space Agency ◽  
Synthetic Data ◽  
Uncertainty Reduction ◽  
Horizontal Resolution ◽  
Point Sources ◽  
Large Cities

Abstract. This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during 1 year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 08:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 00:00–08:30 and 11:30–00:00) for each clump and for the 366 d of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e., the relative difference between the prior and posterior uncertainties). Beyond the one city or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC yr−1 can potentially have their emissions between 08:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within 1 year (ignoring the potential to cross or extrapolate information between 08:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 08:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need for systematic assessment of the sources of uncertainty in the spatiotemporally resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty in constraining the total budget of CO2 emissions from all the cities and power plants within a country or over the globe with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.

scholarly journals Regional uncertainty of GOSAT XCO<sub>2</sub> retrievals in China: Quantification and attribution

2017 ◽  
Author(s):  
Nian Bie ◽  
Liping Lei ◽  
Zhaocheng Zeng ◽  
Bofeng Cai ◽  
Shaoyuan Yang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Transport Model ◽  
Point Sources ◽  
Western Desert ◽  
Anthropogenic Emissions ◽  
Taklimakan Desert ◽  
Dust Aerosols ◽  
Anthropogenic Co2 ◽  
Comparison Results

Abstract. The regional uncertainty of XCO2 (column-averaged dry air mole fraction of CO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a band of 37° N–42° N segmented into 8 cells in a grid of 5° from west to east (80° E–120° E) in China, where there are typical land surface types and geographic conditions. The former include the various land covers of desert, grassland and built-up areas mixed with cropland, and the latter include anthropogenic emissions that tend to be small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from five algorithms (ACOS, NIES, EMMA, OCFP, and SRFP) by intercomparison and particularly by comparing these with simulated XCO2 from the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem), the nested model in East Asia. We introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the five algorithms demonstrate smaller absolute biases between 0.9–1.5 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells with a high-brightness surface, 1.2–2.2 ppm from the pairwise comparison results of XCO2 retrievals. The inconsistency of XCO2 from the five algorithms tends to be high in the Taklimakan Desert in western cells, which is likely induced by high surface albedo in addition to dust aerosols in this region. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values of ACOS and SRFP better agree with GEOS-XCO2, while OCFP is the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS, SRFP and EMMA demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the five algorithms is the smallest in eastern cells in the investigated band where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the five algorithms presented in western deserts with a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols and albedo.

scholarly journals Instrumentation and measurement strategy for the NOAA SENEX aircraft campaign as part of the Southeast Atmosphere Study 2013

2016 ◽  
Vol 9 (7) ◽  
pp. 3063-3093 ◽  
Author(s):  
Carsten Warneke ◽  
Michael Trainer ◽  
Joost A. de Gouw ◽  
David D. Parrish ◽  
David W. Fahey ◽  
...  
Keyword(s):  
Power Plants ◽  
Point Sources ◽  
Anthropogenic Emissions ◽  
Paper Mills ◽  
Southeastern Us ◽  
Early Results ◽  
Secondary Pollutants ◽  
Natural Emissions ◽  
Nearby Point ◽  
The City

Abstract. Natural emissions of ozone-and-aerosol-precursor gases such as isoprene and monoterpenes are high in the southeastern US. In addition, anthropogenic emissions are significant in the southeastern US and summertime photochemistry is rapid. The NOAA-led SENEX (Southeast Nexus) aircraft campaign was one of the major components of the Southeast Atmosphere Study (SAS) and was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants. During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. Here we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign. The aircraft, its capabilities and standard measurements are described. The instrument payload is summarized including detection limits, accuracy, precision and time resolutions for all gas-and-aerosol phase instruments. The inter-comparisons of compounds measured with multiple instruments on the NOAA WP-3D are presented and were all within the stated uncertainties, except two of the three NO2 measurements. The SENEX flights included day- and nighttime flights in the southeastern US as well as flights over areas with intense shale gas extraction (Marcellus, Fayetteville and Haynesville shale). We present one example flight on 16 June 2013, which was a daytime flight over the Atlanta region, where several crosswind transects of plumes from the city and nearby point sources, such as power plants, paper mills and landfills, were flown. The area around Atlanta has large biogenic isoprene emissions, which provided an excellent case for studying the interactions between biogenic and anthropogenic emissions. In this example flight, chemistry in and outside the Atlanta plumes was observed for several hours after emission. The analysis of this flight showcases the strategies implemented to answer some of the main SENEX science questions.

scholarly journals The DACCIWA Project: Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa

2015 ◽  
Vol 96 (9) ◽  
pp. 1451-1460 ◽  
Author(s):  
Peter Knippertz ◽  
Hugh Coe ◽  
J. Christine Chiu ◽  
Mat J. Evans ◽  
Andreas H. Fink ◽  
...  
Keyword(s):  
West Africa ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Strong Dependence ◽  
West African Monsoon ◽  
Atmospheric Composition ◽  
Anthropogenic Emissions ◽  
Aerosol Chemistry ◽  
Wide Range

Abstract Massive economic and population growth, and urbanization are expected to lead to a tripling of anthropogenic emissions in southern West Africa (SWA) between 2000 and 2030. However, the impacts of this on human health, ecosystems, food security, and the regional climate are largely unknown. An integrated assessment is challenging due to (a) a superposition of regional effects with global climate change; (b) a strong dependence on the variable West African monsoon; (c) incomplete scientific understanding of interactions between emissions, clouds, radiation, precipitation, and regional circulations; and (d) a lack of observations. This article provides an overview of the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) project. DACCIWA will conduct extensive fieldwork in SWA to collect high-quality observations, spanning the entire process chain from surface-based natural and anthropogenic emissions to impacts on health, ecosystems, and climate. Combining the resulting benchmark dataset with a wide range of modeling activities will allow (a) assessment of relevant physical, chemical, and biological processes; (b) improvement of the monitoring of climate and atmospheric composition from space; and (c) development of the next generation of weather and climate models capable of representing coupled cloud–aerosol interactions. The latter will ultimately contribute to reduce uncertainties in climate predictions. DACCIWA collaborates closely with operational centers, international programs, policymakers, and users to actively guide sustainable future planning for West Africa. It is hoped that some of DACCIWA’s scientific findings and technical developments will be applicable to other monsoon regions.

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 Microplastic Fiber Emissions From Wastewater Effluents: Abundance, Transport Behavior and Exposure Risk for Biota in an Arctic Fjord

2021 ◽  
Vol 9 ◽  
Author(s):  
Dorte Herzke ◽  
Peygham Ghaffari ◽  
Jan Henry Sundet ◽  
Caroline Aas Tranang ◽  
Claudia Halsband
Keyword(s):  
Benthic Fauna ◽  
Global Scale ◽  
Point Sources ◽  
Mitigation Strategies ◽  
The Arctic ◽  
Modeling Framework ◽  
Svalbard Archipelago ◽  
Untreated Wastewater ◽  
Wide Range ◽  
Wastewater Effluents

Microfibers (MF) are one of the major classes of microplastic found in the marine environment on a global scale. Very little is known about how they move and distribute from point sources such as wastewater effluents into the ocean. We chose Adventfjorden near the settlement of Longyearbyen on the Arctic Svalbard archipelago as a case study to investigate how microfibers emitted with untreated wastewater will distribute in the fjord, both on a spatial and temporal scale. Fiber abundance in the effluent was estimated from wastewater samples taken during two one-week periods in June and September 2017. Large emissions of MFs were detected, similar in scale to a modern WWTP serving 1.3 million people and providing evidence of the importance of untreated wastewater from small settlements as major local sources for MF emissions in the Arctic. Fiber movement and distribution in the fjord mapped using an online-coupled hydrodynamic-drift model (FVCOM-FABM). For parameterizing a wider spectrum of fibers from synthetic to wool, four different density classes of MFs, i.e., buoyant, neutral, sinking, and fast sinking fibers are introduced to the modeling framework. The results clearly show that fiber class has a large impact on the fiber distributions. Light fibers remained in the surface layers and left the fjord quickly with outgoing currents, while heavy fibers mostly sank to the bottom and deposited in the inner parts of the fjord and along the northern shore. A number of accumulation sites were identified within the fjord. The southern shore, in contrast, was much less affected, with low fiber concentrations throughout the modeling period. Fiber distributions were then compared with published pelagic and benthic fauna distributions in different seasons at selected stations around the fjord. The ratios of fibers to organisms showed a very wide range, indicating hot spots of encounter risk for pelagic and benthic biota. This approach, in combination with in-situ ground-truthing, can be instrumental in understanding microplastic pathways and fate in fjord systems and coastal areas and help authorities develop monitoring and mitigation strategies for microfiber and microplastic pollution in their local waters.

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