Glyoxal (CHOCHO) and formaldehyde (HCHO) are
intermediate products in the tropospheric oxidation of the majority of
volatile organic compounds (VOCs). CHOCHO is also a precursor of secondary
organic ...aerosol (SOA) in the atmosphere. CHOCHO and HCHO are released from
biogenic, anthropogenic, and pyrogenic sources. CHOCHO and HCHO
tropospheric lifetimes are typically considered to be short during the
daytime at mid-latitudes (e.g. several hours), as they are rapidly removed
from the atmosphere by their photolysis, oxidation by OH, and uptake on
particles or deposition. At night and at high latitudes, tropospheric
lifetimes increase to many hours or even days. Previous studies demonstrated
that CHOCHO and HCHO vertical column densities (VCDs) are well retrieved
from space-borne observations using differential optical absorption
spectroscopy (DOAS). In this study, we present CHOCHO and HCHO VCDs
retrieved from measurements by TROPOMI (TROPOspheric Monitoring Instrument), launched on the
Sentinel-5 Precursor (S5P) platform in October 2017. We observe strongly
elevated amounts of CHOCHO and HCHO during the 2018 fire season in British
Columbia, Canada, where a large number of fires occurred in August. CHOCHO
and HCHO plumes from individual fire hot spots are observed in air masses
travelling over distances of up to 1500 km, i.e. much longer than expected
for the relatively short tropospheric lifetime expected for CHOCHO and
HCHO. Comparison with simulations by the particle dispersion model FLEXPART
(FLEXible PARTicle dispersion model)
indicates that effective lifetimes of 20 h and more are needed to
explain the observations of CHOCHO and HCHO if they decay in an effective
first-order process. FLEXPART used in the study calculates accurately the
transport. In addition an exponential decay, in our case assumed to be
photochemical, of a species along the trajectory is added. We have used this
simple approach to test our assumption that CHOCHO and HCHO are created
in the fires and then decay at a constant rate in the plume as it is
transported. This is clearly not the case and we infer that CHOCHO and HCHO
are either efficiently recycled during transport or continuously formed
from the oxidation of longer-lived precursors present in the plume, or
possibly a mixture of both. We consider the best explanation of the observed
CHOCHO and HCHO VCD in the plumes of the fire is that they are produced by
oxidation of longer-lived precursors, which were also released by the fire and present
in the plume.
Due to proceeding climate change, some regions such as California face rising weather extremes with dry periods becoming warmer and drier, entailing the risk that wildfires and associated air ...pollution episodes will continue to increase. November 2018 turned into one of the most severe wildfire episodes on record in California, with two particularly destructive wildfires spreading concurrently through the north and the south of the state. Both fires ignited at the wildland-urban interface, causing many civilian fatalities and forcing the total evacuation of several cities and communities.
Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH.sub.4) is the second most important greenhouse gas contributing to human-induced climate change. ...Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The growth rate of atmospheric carbon dioxide (CO2) reflects the net
effect of emissions and uptake resulting from anthropogenic and natural
carbon sources and sinks. Annual mean CO2 growth rates ...have been
determined from satellite retrievals of column-averaged dry-air mole fractions
of CO2, i.e. XCO2, for the years 2003 to 2016. The XCO2
growth rates agree with National Oceanic and Atmospheric Administration
(NOAA) growth rates from CO2 surface observations within the uncertainty
of the satellite-derived growth rates (mean difference ± standard
deviation: 0.0±0.3 ppm year−1; R: 0.82). This new and independent data
set confirms record-large growth rates of around 3 ppm year−1
in 2015 and 2016, which are attributed to the 2015–2016 El Niño. Based on a comparison of
the satellite-derived growth rates with human CO2 emissions from fossil
fuel combustion and with El Niño Southern Oscillation (ENSO) indices, we
estimate by how much the impact of ENSO dominates the impact of fossil-fuel-burning-related emissions in explaining the variance of the atmospheric
CO2 growth rate. Our analysis shows that the ENSO impact on CO2
growth rate variations dominates that of human emissions throughout the
period 2003–2016 but in particular during the period 2010–2016 due to strong
La Niña and El Niño events. Using the derived growth rates and their
uncertainties, we estimate the probability that the impact of ENSO on the
variability is larger than the impact of human emissions to be 63 % for the
time period 2003–2016. If the time period is restricted to 2010–2016, this
probability increases to 94 %.
Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high ...latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCH4) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH4 fluxes using the CarbonTracker Europe-CH4 (CTE-CH4) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research’s (SRON) operational and University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH4 emission maximum is later, when the SRON’s operational data are assimilated. The TROPOMI inversions show higher CH4 emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In the past decade, there has been a massive growth in the horizontal drilling and hydraulic fracturing of shale gas and tight oil reservoirs to exploit formerly inaccessible or unprofitable energy ...resources in rock formations with low permeability. In North America, these unconventional domestic sources of natural gas and oil provide an opportunity to achieve energy self‐sufficiency and to reduce greenhouse gas emissions when displacing coal as a source of energy in power plants. However, fugitive methane emissions in the production process may counter the benefit over coal with respect to climate change and therefore need to be well quantified. Here we demonstrate that positive methane anomalies associated with the oil and gas industries can be detected from space and that corresponding regional emissions can be constrained using satellite observations. On the basis of a mass‐balance approach, we estimate that methane emissions for two of the fastest growing production regions in the United States, the Bakken and Eagle Ford formations, have increased by 990 ± 650 ktCH4 yr−1 and 530 ± 330 ktCH4 yr−1 between the periods 2006–2008 and 2009–2011. Relative to the respective increases in oil and gas production, these emission estimates correspond to leakages of 10.1% ± 7.3% and 9.1% ± 6.2% in terms of energy content, calling immediate climate benefit into question and indicating that current inventories likely underestimate the fugitive emissions from Bakken and Eagle Ford.
Key Points
Emissions of oil and gas industries are constrained using satellite observations
Current inventories likely underestimate fugitive methane emissions
Climate benefit of transition to unconventional oil and gas is questionable
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Satellite retrievals of the atmospheric dry-air column-average mole fraction of CO 2 (XCO 2 ) based on hyperspectral measurements in appropriate near (NIR) and short wave infrared (SWIR) O 2 and CO 2 ...absorption bands can help to answer important questions about the carbon cycle but the precision and accuracy requirements for XCO 2 data products are demanding. Multiple scattering of light at aerosols and clouds can be a significant error source for XCO 2 retrievals. Therefore, so called full physics retrieval algorithms were developed aiming to minimize scattering related errors by explicitly fitting scattering related properties such as cloud water/ice content, aerosol optical thickness, cloud height, etc. However, the computational costs for multiple scattering radiative transfer (RT) calculations can be immense. Processing all data of the Orbiting Carbon Observatory-2 (OCO-2) can require up to thousands of CPU cores and the next generation of CO 2 monitoring satellites will produce at least an order of magnitude more data. For this reason, the Fast atmOspheric traCe gAs retrievaL FOCAL has been developed reducing the computational costs by orders of magnitude by approximating multiple scattering effects with an analytic solution of the RT problem of an isotropic scattering layer. Here we confront FOCAL for the first time with measured OCO-2 data and protocol the steps undertaken to transform the input data (most importantly, the OCO-2 radiances) into a validated XCO 2 data product. This includes preprocessing, adaptation of the noise model, zero level offset correction, post-filtering, bias correction, comparison with the CAMS (Copernicus Atmosphere Monitoring Service) greenhouse gas flux inversion model, comparison with NASA’s operational OCO-2 XCO 2 product, and validation with ground based Total Carbon Column Observing Network (TCCON) data. The systematic temporal and regional differences between FOCAL and the CAMS model have a standard deviation of 1.0 ppm. The standard deviation of the single sounding mismatches amounts to 1.1 ppm which agrees reasonably well with FOCAL’s average reported uncertainty of 1.2 ppm. The large scale XCO 2 patterns of FOCAL and NASA’s operational OCO-2 product are similar and the most prominent difference is that FOCAL has about three times less soundings due to the inherently poor throughput (11%) of the MODIS (moderate-resolution imaging spectroradiometer) based cloud screening used by FOCAL’s preprocessor. The standard deviation of the difference between both products is 1.1 ppm. The validation of one year (2015) of FOCAL XCO 2 data with co-located ground based TCCON observations results in a standard deviations of the site biases of 0.67 ppm (0.78 ppm without bias correction) and an average scatter relative to TCCON of 1.34 ppm (1.60 ppm without bias correction).
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Satellite retrievals of the atmospheric dry-air column-average mole fraction of CO 2 (XCO 2 ) based on hyperspectral measurements in appropriate near (NIR) and short wave infrared (SWIR) O 2 and CO 2 ...absorption bands can help to answer important questions about the carbon cycle but the precision and accuracy requirements for XCO 2 data products are demanding. Multiple scattering of light at aerosols and clouds can be a significant error source for XCO 2 retrievals. Therefore, so called full physics retrieval algorithms were developed aiming to minimize scattering related errors by explicitly fitting scattering related properties such as cloud water/ice content, aerosol optical thickness, cloud height, etc. However, the computational costs for multiple scattering radiative transfer (RT) calculations can be immense. Processing all data of the Orbiting Carbon Observatory-2 (OCO-2) can require up to thousands of CPU cores and the next generation of CO 2 monitoring satellites will produce at least an order of magnitude more data. Here we introduce the Fast atmOspheric traCe gAs retrievaL FOCAL including a scalar RT model which approximates multiple scattering effects with an analytic solution of the RT problem of an isotropic scattering layer and a Lambertian surface. The computational performance is similar to an absorption only model and currently determined by the convolution of the simulated spectra with the instrumental line shape function (ILS). We assess FOCAL’s quality by confronting it with accurate multiple scattering vector RT simulations using SCIATRAN. The simulated scenarios do not cover all possible geophysical conditions but represent, among others, some typical cloud and aerosol scattering scenarios with optical thicknesses of up to 0.7 which have the potential to survive the pre-processing of a XCO 2 algorithm for real OCO-2 measurements. Systematic errors of XCO 2 range from −2.5 ppm (−6.3‰) to 3.0 ppm (7.6‰) and are usually smaller than ±0.3 ppm (0.8‰). The stochastic uncertainty of XCO 2 is typically about 1.0 ppm (2.5‰). FOCAL simultaneously retrieves the dry-air column-average mole fraction of H 2 O (XH 2 O) and the solar induced chlorophyll fluorescence at 760 nm (SIF). Systematic and stochastic errors of XH 2 O are most times smaller than ±6 ppm and 9 ppm, respectively. The systematic SIF errors are always below 0.02 mW/m 2 /sr/nm, i.e., it can be expected that instrumental or forward model effects causing an in-filling of the used Fraunhofer lines will dominate the systematic errors when analyzing actually measured data. The stochastic uncertainty of SIF is usually below 0.3 mW/m 2 /sr/nm. Without understating the importance of analyzing synthetic measurements as presented here, the actual retrieval performance can only be assessed by analyzing measured data which is subject to part 2 of this publication.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The switch from the use of coal to natural gas or oil for energy generation potentially reduces greenhouse gas emissions and thus the impact on global warming and climate change because of the higher ...energy creation per CO.sub.2 molecule emitted. However, the climate benefit over coal is offset by methane (CH.sub.4) leakage from natural gas and petroleum systems, which reverses the climate impact mitigation if the rate of fugitive emissions exceeds the compensation point at which the global warming resulting from the leakage and the benefit from the reduction of coal combustion coincide. Consequently, an accurate quantification of CH.sub.4 emissions from the oil and gas industry is essential to evaluate the suitability of natural gas and petroleum as bridging fuels on the way to a carbon-neutral future.
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.
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