Western wildfires have a major impact on air quality in the US. In the fall of 2016, 107 test fires were burned in the large-scale combustion facility at the US Forest Service Missoula Fire Sciences ...Laboratory as part of the Fire Influence on Regional and Global Environments Experiment (FIREX). Canopy, litter, duff, dead wood, and other fuel components were burned in combinations that represented realistic fuel complexes for several important western US coniferous and chaparral ecosystems including ponderosa pine, Douglas fir, Engelmann spruce, lodgepole pine, subalpine fir, chamise, and manzanita. In addition, dung, Indonesian peat, and individual coniferous ecosystem fuel components were burned alone to investigate the effects of individual components (e.g., “duff”) and fuel chemistry on emissions. The smoke emissions were characterized by a large suite of state-of-the-art instruments. In this study we report emission factor (EF, grams of compound emitted per kilogram of fuel burned) measurements in fresh smoke of a diverse suite of critically important trace gases measured using open-path Fourier transform infrared spectroscopy (OP-FTIR). We also report aerosol optical properties (absorption EF; single-scattering albedo, SSA; and Ångström absorption exponent, AAE) as well as black carbon (BC) EF measured by photoacoustic extinctiometers (PAXs) at 870 and 401 nm. The average trace gas emissions were similar across the coniferous ecosystems tested and most of the variability observed in emissions could be attributed to differences in the consumption of components such as duff and litter, rather than the dominant tree species. Chaparral fuels produced lower EFs than mixed coniferous fuels for most trace gases except for NOx and acetylene. A careful comparison with available field measurements of wildfires confirms that several methods can be used to extract data representative of real wildfires from the FIREX laboratory fire data. This is especially valuable for species rarely or not yet measured in the field. For instance, the OP-FTIR data alone show that ammonia (1.62 g kg−1), acetic acid (2.41 g kg−1), nitrous acid (HONO, 0.61 g kg−1), and other trace gases such as glycolaldehyde (0.90 g kg−1) and formic acid (0.36 g kg−1) are significant emissions that were poorly characterized or not characterized for US wildfires in previous work. The PAX measurements show that the ratio of brown carbon (BrC) absorption to BC absorption is strongly dependent on modified combustion efficiency (MCE) and that BrC absorption is most dominant for combustion of duff (AAE 7.13) and rotten wood (AAE 4.60): fuels that are consumed in greater amounts during wildfires than prescribed fires. Coupling our laboratory data with field data suggests that fresh wildfire smoke typically has an EF for BC near 0.2 g kg−1, an SSA of ∼ 0.91, and an AAE of ∼ 3.50, with the latter implying that about 86 % of the aerosol absorption at 401 nm is due to BrC.
Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This ...work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.
The isotopic composition of atmospheric trace gases such as CO2 and
CH4 provides a valuable tracer for the sources and sinks that contribute
to atmospheric trace gas budgets. In the past, isotopic ...composition has
typically been measured with high precision and accuracy by isotope ratio
mass spectrometry (IRMS) offline and separately from real-time or flask-based
measurements of concentrations or mole fractions. In recent years,
development of infrared optical spectroscopic techniques based on laser and
Fourier-transform infrared spectroscopy (FTIR) has provided high-precision
measurements of the concentrations of one or more individual isotopologues of
atmospheric trace gas species in continuous field and laboratory
measurements, thus providing both concentration and isotopic measurements
simultaneously. Several approaches have been taken to the calibration of
optical isotopologue-specific analysers to derive both total trace gas
amounts and isotopic ratios, converging into two different approaches:
calibration via the individual isotopologues as measured by the optical
device and calibration via isotope ratios, analogous to IRMS. This paper sets out a practical guide to the calculations required to
perform calibrations of isotopologue-specific optical analysers, applicable
to both laser and broadband FTIR spectroscopy. Equations to calculate the
relevant isotopic and total concentration quantities without approximation
are presented, together with worked numerical examples from actual
measurements. Potential systematic errors, which may occur when all required
isotopic information is not available, or is approximated, are assessed.
Fortunately, in most such realistic cases, these systematic errors incurred
are acceptably small and within the compatibility limits specified by the
World Meteorological Organisation – Global Atmosphere Watch.
Isotopologue-based and ratio-based calibration schemes are compared.
Calibration based on individual isotopologues is simpler because the
analysers fundamentally measure amounts of individual isotopologues, not
ratios. Isotopologue calibration does not require a range of isotopic ratios
in the reference standards used for the calibration, only a range of
concentrations or mole fractions covering the target range. Ratio-based
calibration leads to concentration dependence, which must also be
characterised.
This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical ...distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere. The CO seasonal variability obtained from the total columns and free tropospheric partial columns shows a maximum around March–April and a minimum around September–October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by the IASI–MetOp (Infrared Atmospheric Sounding Interferometer) and MOPITT (Measurements Of Pollution In The Troposphere) instruments confirm this seasonality. Ground-based FTIR (Fourier transform infrared) measurements provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios at the Paris and Jungfraujoch sites reveal a time lag of the near-surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem (Goddard Earth Observing System chemical transport model) is employed to interpret our observations. GEOS-Chem sensitivity runs identify the emission sources influencing the seasonal variation of CO. At both Paris and Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. At Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface measurements and total column data.
The Total Carbon Column Observing Network Wunch, Debra; Toon, Geoffrey C.; Blavier, Jean-François L. ...
Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences,
05/2011, Letnik:
369, Številka:
1943
Journal Article
Recenzirano
Odprti dostop
A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO 2 , CO, CH 4 , N 2 O and other molecules that absorb in the ...near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remote-sensing observations (better than 0.25% for CO 2 ). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.
We report new short‐wave infrared (SWIR) column retrievals of atmospheric methane (XCH4) from the Japanese Greenhouse Gases Observing SATellite (GOSAT) and compare observed spatial and temporal ...variations with correlative ground‐based measurements from the Total Carbon Column Observing Network (TCCON) and with the global 3‐D GEOS‐Chem chemistry transport model. GOSAT XCH4 retrievals are compared with daily TCCON observations at six sites between April 2009 and July 2010 (Bialystok, Park Falls, Lamont, Orleans, Darwin and Wollongong). GOSAT reproduces the site‐dependent seasonal cycles as observed by TCCON with correlations typically between 0.5 and 0.7 with an estimated single‐sounding precision between 0.4–0.8%. We find a latitudinal‐dependent difference between the XCH4 retrievals from GOSAT and TCCON which ranges from 17.9 ppb at the most northerly site (Bialystok) to −14.6 ppb at the site with the lowest latitude (Darwin). We estimate that the mean smoothing error difference included in the GOSAT to TCCON comparisons can account for 15.7 to 17.4 ppb for the northerly sites and for 1.1 ppb at the lowest latitude site. The GOSAT XCH4 retrievals agree well with the GEOS‐Chem model on annual (August 2009 – July 2010) and monthly timescales, capturing over 80% of the zonal variability. Differences between model and observed XCH4 are found over key source regions such as Southeast Asia and central Africa which will be further investigated using a formal inverse model analysis.
Key Points
CH4 is now successfully being retrieved from GOSAT satellite
Validation against ground‐based data shows good agreement
Excellent agreement to model simulations as a first step towards inversions
In 2019–2020, Australia experienced its largest wildfire season on
record. Smoke covered hundreds of square kilometers across the southeastern
coast and reached the site of the COALA-2020 ...(Characterizing Organics and
Aerosol Loading over Australia) field campaign in New South Wales. Using a
subset of nighttime observations made by a proton-transfer-reaction
time-of-flight mass spectrometer (PTR-ToF-MS), we calculate emission ratios
(ERs) and factors (EFs) for 15 volatile organic compounds (VOCs). We
restrict our analysis to VOCs with sufficiently long lifetimes to be
minimally impacted by oxidation over the ∼ 8 h between when
the smoke was emitted and when it arrived at the field site. We use oxidized
VOC to VOC ratios to assess the total amount of radical oxidation: maleic
anhydride / furan to assess OH oxidation, and (cis-2-butenediol + furanone) / furan to assess NO3 oxidation. We examine time series of
O3 and NO2 given their closely linked chemistry with wildfire
plumes and observe their trends during the smoke event. Then we compare ERs
calculated from the freshest portion of the plume to ERs calculated using
the entire nighttime period. Finding good agreement between the two, we are
able to extend our analysis to VOCs measured in more chemically aged
portions of the plume. Our analysis provides ERs and EFs for six compounds not
previously reported for temperate forests in Australia: acrolein (a compound
with significant health impacts), methyl propanoate, methyl methacrylate,
maleic anhydride, benzaldehyde, and creosol. We compare our results with two
studies in similar Australian biomes, and two studies focused on US
temperate forests. We find over half of our EFs are within a factor of 2.5
relative to those presented in Australian biome studies, with nearly all
within a factor of 5, indicating reasonable agreement. For US-focused
studies, we find similar results with over half our EFs within a factor of
2.5, and nearly all within a factor of 5, again indicating reasonably good agreement.
This suggests that comprehensive field measurements of biomass burning VOC
emissions in other regions may be applicable to Australian temperate
forests. Finally, we quantify the magnitude attributable to the primary
compounds contributing to OH reactivity from this plume, finding results
comparable to several US-based wildfire and laboratory studies.
Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and
methane (CH4) 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. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which
was successfully launched in October 2017, is a spaceborne nadir-viewing imaging spectrometer
measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath
on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the
shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These
characteristics enable the determination of both gases with an unprecedented level of detail on a
global scale, introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4
are simultaneously retrieved from TROPOMI's radiance measurements in the 2.3 µm
spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm
Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). This algorithm
is intended to be used with the operational algorithms for mutual verification and to provide new
geophysical insights. We introduce the algorithm in detail, including expected error characteristics
based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration
procedure applied in the post-processing of the XCH4 data. The quality of the results based
on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer
(FTS) measurements providing realistic error estimates of the satellite data: the XCO data
set is characterised by a random error of 5.1 ppb (5.8 %) and a systematic error of
1.9 ppb (2.1 %); the XCH4 data set exhibits a random error of 14.0 ppb
(0.8 %) and a systematic error of 4.3 ppb (0.2 %). The natural XCO and
XCH4 variations are well-captured by the satellite retrievals, which is demonstrated by a
high correlation with the validation data (R=0.97 for XCO and R=0.91 for XCH4 based
on daily averages). We also present selected results from the mission start until the end of 2018, including a first comparison
to the operational products and examples of the detection of emission sources in a single satellite
overpass, such as CO emissions from the steel industry and CH4 emissions from the
energy sector, which potentially allows for the advance of emission monitoring and air quality assessments
to an entirely new level.
Vegetation commonly managed by prescribed burning was collected from five southeastern and southwestern US military bases and burned under controlled conditions at the US Forest Service Fire Sciences ...Laboratory in Missoula, Montana. The smoke emissions were measured with a large suite of state-of-the-art instrumentation including an open-path Fourier transform infrared (OP-FTIR) spectrometer for measurement of gas-phase species. The OP-FTIR detected and quantified 19 gas-phase species in these fires: CO2, CO, CH4, C2H2, C2H4, C3H6, HCHO, HCOOH, CH3OH, CH3COOH, furan, H2O, NO, NO2, HONO, NH3, HCN, HCl, and SO2. Emission factors for these species are presented for each vegetation type burned. Gas-phase nitrous acid (HONO), an important OH precursor, was detected in the smoke from all fires. The HONO emission factors ranged from 0.15 to 0.60 g kg−1 and were higher for the southeastern fuels. The fire-integrated molar emission ratios of HONO (relative to NOx) ranged from approximately 0.03 to 0.20, with higher values also observed for the southeastern fuels. The majority of non-methane organic compound (NMOC) emissions detected by OP-FTIR were oxygenated volatile organic compounds (OVOCs) with the total identified OVOC emissions constituting 61 ± 12% of the total measured NMOC on a molar basis. These OVOC may undergo photolysis or further oxidation contributing to ozone formation. Elevated amounts of gas-phase HCl and SO2 were also detected during flaming combustion, with the amounts varying greatly depending on location and vegetation type. The fuels with the highest HCl emission factors were all located in the coastal regions, although HCl was also observed from fuels farther inland. Emission factors for HCl were generally higher for the southwestern fuels, particularly those found in the chaparral biome in the coastal regions of California.
In this study, we employ a regional inverse modelling approach to estimate monthly carbon fluxes over the Australian continent for 2015–2019 using the assimilation of the total column-averaged mole ...fractions of carbon dioxide from the Orbiting Carbon Observatory-2 (OCO-2, version 9) satellite. Subsequently, we study the carbon cycle variations and relate their fluctuations to anomalies in vegetation productivity and climate drivers. Our 5-year regional carbon flux inversion suggests that Australia was a carbon sink averaging −0.46 ± 0.08 PgC yr−1 (excluding fossil fuel emissions), largely influenced by a strong carbon uptake (−1.04 PgC yr−1) recorded in 2016. Australia's semi-arid ecosystems, such as sparsely vegetated regions (in central Australia) and savanna (in northern Australia), were the main contributors to the carbon uptake in 2016. These regions showed relatively high vegetation productivity, high rainfall, and low temperature in 2016. In contrast to the large carbon sink found in 2016, the large carbon outgassing recorded in 2019 coincides with an unprecedented rainfall deficit and higher-than-average temperatures across Australia. Comparison of the posterior column-averaged CO2 concentration with Total Carbon Column Observing Network (TCCON) stations and in situ measurements offers limited insight into the fluxes assimilated with OCO-2. However, the lack of these monitoring stations across Australia, mainly over ecosystems such as savanna and areas with sparse vegetation, impedes us from providing strong conclusions. To a certain extent, we found that the flux anomalies across Australia are consistent with the ensemble means of the OCO-2 Model Intercomparison Project (OCO-2 MIP) and FLUXCOM (2015–2018), which estimate an anomalous carbon sink for Australia in 2016 of −1.09 and −0.42 PgC yr−1 respectively. More accurate estimates of OCO-2 retrievals, with the addition of ocean glint data into our system, and a better understanding of the error in the atmospheric transport modelling will yield further insights into the difference in the magnitude of our carbon flux estimates.
PDF
