Carbon Monoxide Total Column Research Articles

A Comparative Analysis of Satellite-Derived CO Retrievals During the 2020 Wildfires in North America.

In September 2020, the Western United States experienced anomalously severe wildfires that resulted in carbon monoxide (CO) emissions almost three times the 2001-2019 average. In this study, we investigate the influence of wildfires on atmospheric carbon monoxide (CO) variability through a comparative analysis of observations from the Measurements of Pollution in the Troposphere (MOPITT), the Infrared Atmospheric Sounding Interferometer (IASI), and the Tropospheric Monitoring Instrument (TROPOMI). Our focus is on the North American domain, aiming to understand the differences among these products. In general, all instruments show excellent agreement under typical atmospheric CO conditions. However, notable discrepancies were observed in the CO data from the three sensors, particularly in regions with elevated CO total column (TC) values. IASI and TROPOMI consistently showed higher CO values over the western U.S. compared to MOPITT. During the fire episodes, we found that the IASI retrievals suggested higher CO abundances near the surface than the MOPITT thermal infrared retrievals that are probably the result of the differences in the covariance matrices used in IASI and MOPITT retrievals. We also found that the high IASI and TROPOMI CO observations over the western U.S. coincided with high values of the TROPOMI aerosol index (AI), suggesting the presence of absorbing aerosols. The analysis exhibited better agreement between TROPOMI and MOPITT CO TC when the AI values were low. Our results suggest that appropriate quality filtering should be employed when analyzing pollution events with these data. In particular, utilizing the AI for quality filtering may be useful when analyzing extreme pollution events with these satellite products.

CO2 variability over a tropical coastal station in India: Synergy of observation and model

Carbon dioxide (CO2), being the prime greenhouse gas, has largest contribution in radiative forcing and global warming due to increased anthropogenic emissions leading to regional and global climate change. We performed CO2 measurements using a continuous monitoring instrument at a tropical coastal station at the southern tip of India (Thumba; 8.54° N, 76.86° E) during 2017–2021. Combining measurements with model simulations and satellite observations, present study aims to understand CO2 variabilities, contribution of various sources and role of dynamics. The observed trend of 2.19 ppm y−1 is well simulated (2.47 ppm y−1) by the chemistry-transport model (MIROC4-ACTM), which is contributed by trends in fossil fuel (4.59 ppm y−1), biosphere (−1.46 ppm y−1) and ocean (−0.66 ppm y−1) tracers of CO2 flux. Mean seasonal cycle with amplitude of about 8 ppm is observed, with a maximum during premonsoon (April) and minimum at the end of the monsoon season (September). The model reproduced the observed seasonal cycle well (r2 = 0.89) and showed that the seasonal peak is predominantly contributed by the land biospheric flux seasonality. Biospheric sink during postmonsoon is counterbalanced by emissions from fossil fuel burning. Biosphere and fossil fuel are major contributors in shaping the observed seasonal pattern with negligible seasonality in oceanic tracer due to its uniform flux patterns in the Indian Ocean. Mean diurnal pattern of CO2 exhibits lower values during daytime (cleaner marine airmass) and higher values during nighttime (continental airmass) with deeper diurnal amplitude in the winter (~50 ppm) than in the summer (~31 ppm). Seasonal pattern in total column CO2 from OCO-2 (Orbiting Carbon Observatory-2) is similar to the surface observations but shows nearly half of the observed seasonal amplitude. Long-term continuous measurements over distinct environments are desirable for further deepening the understanding of CO2 variability, estimation of regional carbon budget and for climate mitigation policies.

Tropospheric ozone precursors: global and regional distributions, trends, and variability

Abstract. Tropospheric ozone results from in situ chemical formation and stratosphere–troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

TROPOMI unravels transboundary transport pathways of atmospheric carbon monoxide in Tibetan Plateau

Numerous studies have reported in situ monitoring and source analysis in the Tibetan Plateau (TP), a region crucial for climate systems. However, a gap remains in understanding the comprehensive distribution of atmospheric pollutants in the TP and their transboundary pollution transport. Here, we analyzed the high-resolution satellite TROPOMI observations from 2018 to 2023 in Tibet and its surrounding areas. Our result reveals that, contrary to the results from in situ surface CO monitoring, Tibet exhibits a distinct seasonality in atmospheric carbon monoxide total column average mixing ratio (XCO), with higher levels in summer and lower levels in winter. This distinctive seasonal pattern may be related to the TP's ‘air pump’ effect and the Asia summer monsoon. Before 2022, the annual growth rate of XCO in Tibet was 1.63 %·year−1; however, it declined by 6.88 % in 2022. Source analysis and satellite observations suggest that CO from South Asia may enter Tibet either by crossing the Himalayas or through the Yarlung Zangbo Grand Canyon. We discovered that spring outbreaks of open biomass burning (OBB) in South and Southeast Asia led to an 11.57–27.98 % increase in XCO over Tibet. Favorable wind pattern and unique topography of the canyon promote the high concentrations CO transport to Tibet. Our greater concern is whether the TP will experience more severe transboundary pollution in the future.

Diurnal Carbon Monoxide Retrieval from FY-4B/GIIRS Using a Novel Machine Learning Method

Carbon monoxide (CO) is one of the primary reactive trace gases in the Earth’s atmosphere and plays an important role in atmospheric chemistry. The Geostationary Interferometric Infrared Sounder (GIIRS) onboard the FY-4 series satellites is currently the only geostationary hyperspectral thermal infrared sensor capable of monitoring the unprecedented hourly CO concentrations in East Asia during both daytime and nighttime. In this study, we presented a radiative transfer model-driven machine learning approach to quickly convert CO spectral features extracted from FY-4B/GIIRS into CO total columns. We built machine learning models for land and ocean regions separately from July 2022 to June 2023, and these models reproduced more than 97.77% (land) and 98.49% (ocean) of the CO column variance in the training set. We estimated the absolute uncertainty of the retrieved CO column based on error propagation theory and found that it is dominated by GIIRS measurement noise. We compared the machine learning retrieval results with optimal estimation and ground-based Fourier transform infrared measurements, and the results reveal the consistent spatial distribution and temporal variation across these different datasets. Our results confirm that the machine learning method has the potential to provide reliable CO products without the computationally intensive iterative process required by traditional retrieval methods. The diel cycle and monthly variation of CO over land and ocean demonstrate the value of GIIRS in monitoring the long-range transport of anthropogenic pollutants and biomass burning emissions.

JWST Reveals Widespread CO Ice and Gas Absorption in the Galactic Center Cloud G0.253+0.016

We report JWST NIRCam observations of G0.253+0.016, the molecular cloud in the Central Molecular Zone known as “The Brick,” with the F182M, F187N, F212N, F410M, F405N, and F466N filters. We catalog 56,146 stars detected in all six filters using the crowdsource package. Stars within and behind The Brick exhibit prodigious absorption in the F466N filter that is produced by a combination of CO ice and gas. In support of this conclusion, and as a general resource, we present models of CO gas and ice and CO2 ice in the F466N, F470N, and F410M filters. Both CO gas and ice contribute to the observed stellar colors. We show, however, that CO gas does not absorb the Pfβ and Huϵ lines in F466N, but that these lines show excess absorption, indicating that CO ice is present and contributes to observed F466N absorption. The most strongly absorbed stars in F466N are extincted by ∼2 mag, corresponding to >80% flux loss. This high observed absorption requires very high column densities of CO, and thus a total CO column that is in tension with standard CO abundance and/or gas-to-dust ratios. This result suggests the CO/H2 ratio and dust-to-gas ratio are greater in the Galactic Center than in the Galactic disk. Ice and/or gas absorption is observed even in the cloud outskirts, implying that additional caution is needed when interpreting stellar photometry in filters that overlap with ice bands throughout galactic centers.

From lowland plains to the Altiplano: The impacts of regional transport of wildfire smoke on the air quality of Bolivian cities

Wildfires emerged as a global concern in recent decades, because they deteriorate the air quality in urban centres situated downwind, impact human health, ecosystems and regional climate. In this study, we assessed the air quality of Bolivia's three largest metropolitan areas during the period 2017–2019 by analysing in situ criteria air pollutant data (PM10, O3 and NOx) coupled with satellite (aerosol optical depth AOD and total CO column), fire foci data, and airmass backward trajectories. The Bolivian lowland plains were highly impacted by smoke transported from the Amazon and Cerrado biomes. Due to its proximity to the fire foci, Santa Cruz was the most affected city, where PM10, CO and AOD increased between 1.3- and 3.9-fold in September (maximum fire activity) compared to April (lowest fire activity). In Cochabamba and La Paz-El Alto, the impacts of wildfires on AOD and CO were lower (15–16% increase). A case study of regional smoke in September 2019 using Cochabamba as an example revealed that: i) airmass trajectories passed over regions with high fire radiative power density in southern Bolivia, Paraguay and northern Argentina; ii) the advection of wildfire smoke caused unusual episodes of enhanced nocturnal O3 concentrations (20–45 μg/m3) over a four-day pollution event. The results indicated that local sources (e.g., motorised traffic, brick kilns and dust resuspension) largely contributed to deteriorate the air quality, particularly in the dry months, surpassing the World Health Organization recommendations for PM10, in La Paz-El Alto and Cochabamba. We highlight the need of international cooperation among South American countries to combat fire practices in the region, given the transboundary nature of the biomass burning plumes. Moreover, it is crucial to implement local measures aimed at tackling local air pollution sources, especially in a changing climate in which drier conditions can favour the onset and propagation of wildfires and accumulation of air pollutants.

Validation of TROPOMI Orbital Observations of the CO Total Column by Ground-Based Measurements at the OIAP Stations in Moscow and Zvenigorod

Validation of TROPOMI Orbital Observations of the CO Total Column by Ground-Based Measurements at the OIAP Stations in Moscow and Zvenigorod

The CO(6−5) Protostellar Jet Driven by HH 212 as Imaged by ALMA-Band 9

During the earliest phases of the formation of a Sun-like star, jets play a key role in removing angular momentum from the accretion disk, allowing accretion onto the central star. Here we report, for the first time, the bipolar fast (∼150 km s−1) jet driven by the archetypical HH 212, as imaged on scales of ∼100 au by CO(6–5). Adopting Local Thermodynamic Equilibrium conditions, and optically thin emission, we derive the total CO column densities in the jet lobes: ∼1017 cm−2. Both jet lobes are 1200 au long. The observations have been performed using the ALMA Early Science operations, showing how the ALMA interferometer can be efficiently used in its Band 9 (>600 GHz) to investigate of protostellar jet.

Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B

Abstract. The Geostationary Interferometric Infrared Sounder (GIIRS) on board FengYun-4 series satellites is the world's first geostationary hyperspectral infrared sounder. With hyperspectral measurement collected from a geostationary orbit covering the carbon monoxide (CO) absorption window around 2150 cm−1, GIIRS provides a unique opportunity for monitoring the diurnal variabilities of atmospheric CO over eastern Asia. In this study, we develop the FengYun Geostationary satellite Atmospheric Infrared Retrieval (FY-GeoAIR) algorithm to retrieve the CO profiles using observations from GIIRS on board FY-4B, which was launched in June 2021, and provide CO maps at a spatial resolution of 12 km and a temporal resolution of 2 h. The performance of the algorithm is first evaluated by conducting retrieval experiments using simulated synthetic spectra. The result shows that the GIIRS data provide significant information for constraining CO profiles. The degree of freedom for signal (DOFS) and retrieval error are both highly correlated with thermal contrast (TC), the temperature difference between the surface and the lower atmosphere. Retrieval results from 1 month of GIIRS spectra in July 2022 show that the DOFS for the majority is between 0.8 and 1.5 for the CO total column and between 0 and 0.8 for the bottom three layers ranging from the surface to 3 km a.s.l. Consistent with CO retrievals from low-Earth-orbit (LEO) infrared sounders, the largest observation sensitivity, as quantified by the averaging kernel (AK), is in the free troposphere at around 3–6 km. The diurnal changes in DOFS and vertical sensitivity of observation are primarily driven by the diurnal TC variabilities. Finally, we compare the CO total columns between GIIRS and Infrared Atmospheric Sounding Interferometer (IASI) and find that the two datasets show good consistency in capturing the spatial and temporal variabilities. This study demonstrates that the GIIRS retrievals are able to reproduce the temporal variability of CO total columns over eastern Asia in the daytime in July. Nevertheless, the retrievals have low detectivity in the nighttime due to their weak sensitivity to the ground level CO changes limited by low information content. Model assimilation that takes into account the retrieved diurnal CO profiles and the associated vertical sensitivity will have potential in improving local and global air quality and climate research over eastern Asia.

Uncertainty in parameterized convection remains a key obstacle for estimating surface fluxes of carbon dioxide

Abstract. The analysis of observed atmospheric trace-gas mole fractions to infer surface sources and sinks of chemical species relies heavily on simulated atmospheric transport. The chemical transport models (CTMs) used in flux-inversion models are commonly configured to reproduce the atmospheric transport of a general circulation model (GCM) as closely as possible. CTMs generally have the dual advantages of computational efficiency and improved tracer conservation compared to their parent GCMs, but they usually simplify the representations of important processes. This is especially the case for high-frequency vertical motions associated with diffusion and convection. Using common-flux experiments, we quantify the importance of parameterized vertical processes for explaining systematic differences in tracer transport between two commonly used CTMs. We find that differences in modeled column-average CO2 are strongly correlated with the differences in the models' convection. The parameterization of diffusion is more important near the surface due to its role in representing planetary-boundary-layer (PBL) mixing. Accordingly, simulated near-surface in situ measurements are more strongly impacted by this process than are simulated total-column averages. Both diffusive and convective vertical mixing tend to ventilate the lower atmosphere, so near-surface measurements may only constrain the net vertical mixing and not the balance between these two processes. Remote-sensing-based retrievals of total-column CO2, with their increased sensitivity to convection, may provide important new constraints on parameterized vertical motions.

Ground solar absorption observations of total column CO, CO2, CH4, and aerosol optical depth from California's Sequoia Lightning Complex Fire: emission factors and modified combustion efficiency at regional scales

Abstract. With global wildfires becoming more widespread and severe, tracking their emissions of greenhouse gases and air pollutants is becoming increasingly important. Wildfire emissions have primarily been characterized by in situ laboratory and field observations at fine scales. While this approach captures the mechanisms relating emissions to combustion phase and fuel properties, their evaluation on regional-scale plumes has been limited. In this study, we report remote observations of total column trace gases and aerosols during the 2020 wildfire season from smoke plumes in the Sierra Nevada of California with an EM27/SUN solar Fourier transform infrared (FTIR) spectrometer. We derive total column aerosol optical depth (AOD), emission factors (EFs) and modified combustion efficiency (MCE) for these fires and evaluate relationships between them, based on combustion phase at regional scales. We demonstrate that the EM27/SUN effectively detects changes in CO, CO2, and CH4 in the atmospheric column at ∼10 km horizontal scales that are attributed to wildfire emissions. These observations are used to derive total column EFCO of 120.5±12.2 and EFCH4 of 4.3±0.8 for a regional smoke plume event in mixed combustion phases. These values are consistent with in situ relationships measured in similar temperate coniferous forest wildfires. FTIR-derived AOD was compared to a nearby AERONET (AErosol RObotic NETwork) station and observed ratios of XCO to AOD were consistent with those previously observed from satellites. We also show that co-located XCO observations from the TROPOspheric Monitoring Instrument (TROPOMI) satellite-based instrument are 9.7±1.3 % higher than our EM27/SUN observations during the wildfire period. Finally, we put wildfire CH4 emissions in context of the California state CH4 budget and estimate that 213.7±49.8 Gg CH4 were emitted by large wildfires in California during 2020, about 13.7 % of the total state CH4 emissions in 2020. Our work demonstrates a novel application of the ground-based EM27/SUN solar spectrometers in wildfire monitoring by integrating regional-scale measurements of trace gases and aerosols from smoke plumes.

An Urban Scheme for the ECMWF Integrated Forecasting System: Global Forecasts and Residential CO2 Emissions

AbstractThe impact of urbanization on local weather patterns affects over half the global population. Global numerical weather prediction systems have reached a resolution at which urban conurbations can be spatially resolved, justifying their representation within land surface parameterizations with the aim of improving local predictions. Additionally, real‐time atmospheric monitoring of trace gas emissions can utilize weather variables relevant for urban areas. We investigated whether a simple single‐layer urban canopy scheme can be used within a global forecast model to jointly improve predictions of near‐surface weather variables and residential CO2 emissions. The scheme has been implemented in the Integrated Forecast System used operationally at the European Centre for Medium‐Range Weather Forecasts running at ∼9 km horizontal resolution. First, we selected a suitable urban land cover map (ECOCLIMAP‐SG) based on comparisons with regional data and land surface temperature MODIS retrievals. The urban scheme is verified by providing improved 2 m temperature (∼10%) and 10 m wind (∼17%) RMSE values for both summer and winter months around urban environments. The influence of the scheme was most noticeable at night. Additionally, we have implemented a simple temperature‐dependent residential emissions model to calculate real‐time CO2 heating emissions. These were validated against existing offline products, national reporting and by comparing atmospheric simulations with total column CO2 observations. The results show an improved temporal variability of emissions, which arise from synoptic scale temperature changes. Given the improved predictability from the urban scheme for both weather and emissions, it will be operationally implemented in an upcoming model cycle.

Biomass burning CO, PM and fuel consumption per unit burned area estimates derived across Africa using geostationary SEVIRI fire radiative power and Sentinel-5P CO data

Abstract. We present the first top-down CO fire emissions inventory for Africa based on the direct relation between geostationary satellite-based fire radiative power (FRP) observations and polar-orbiting satellite observations of total column carbon monoxide (TCCO). This work significantly extends the previous Fire Radiative Energy Emissions (FREM) approach that derived total particulate matter (TPM) emission coefficients from FRP and aerosol optical depth (AOD) observations. The use of satellite-based CO observations to derive biome-specific CO emission coefficients, ECCOb, addresses key uncertainties in the use of AOD observations to estimate fire-generated CO emissions including the requirement for a smoke mass extinction coefficient in the AOD to TPM conversion and the large variation in TPM emission factors – which are used to convert TPM emissions to CO emissions. We use the FREM-derived CO emission coefficients to produce a pan-African CO fire emission inventory spanning 2004 to 2019. Regional CO emissions are in close agreement with the most recent version of GFED(v4.1s), despite the two inventories using completely different satellite datasets and methodologies. Dry matter consumed (DMC) and DMC per unit burned area are generated from our CO emission inventory – the latter using the 20 m resolution Sentinel-2 FireCCISFD burnt area (BA) product for 2019. We carry out an evaluation of our FREM-based CO emissions by using them as input in the WRF-CMAQ chemical transport model and comparing simulated TCCO fields to independent Sentinel-5P TROPOMI TCCO observations. The results of this evaluation show FREM CO emissions to generally be in good agreement with these independent measures – particularly in the case of individual fire-generated CO plumes, where modelled in-plume CO was within 5 % of satellite observations with a coefficient of determination of 0.80. Modelled and observed total CO, aggregated over the full model domain, are within 4 % of each other, though localised regions show an overestimation of modelled CO by up to 50 %. When compared to other evaluations of current state-of-the-art fire emissions inventories, the FREM CO emission inventory derived in this work shows some of the best agreement with independent observations. Updates to previously published FREM TPM emissions coefficients based on this methodology are also provided, along with a similar evaluation as conducted for CO. The methodology described in this work is forming the basis of a forthcoming near-real-time fire emissions product from Meteosat to be issued by the EUMETSAT LSA SAF (https://landsaf.ipma.pt/en/, last access: 19 December 2022).

Validation of TROPOMI orbital observations of the CO total column by ground-based measurements at the OIAP stations in Moscow and Zvenigorod

Validation of TROPOMI orbital observations of the CO total column by ground-based measurements at the OIAP stations in Moscow and Zvenigorod

The system for near-real time air pollution monitoring over cities based on the Sentinel-5P satellite data

Introduction. Air pollution heterogeneity and rapid urbanization impose numerous constraints on available near-surface air quality monitoring. The solution for effective warning comes with the integration of different data, including remote sensing. Satellite data cannot answer whether dangerous pollution levels are observed; however, it provides a complete picture and may detect air pollution transportation towards or away from cities. The possibilities for effective near-real time (NRTI) monitoring have significantly improved with the launch of the Sentinel-5P satellite. The study aimed to describe the developed system for NRTI air pollution monitoring over Kharkiv, Kryvyi Rig, Kyiv, and Odesa based on NO2 and CO data derived from the Sentinel-5P satellite. Data and methodology. The NRTI System was developed for tropospheric NO2 and total CO column number densities based on the Sentinel-5P NRTI products. After satellite scanning of Ukrainian territory, the NRTI System goes live in 2-3 hours. It is fully automatic, and modules were written using Python, VB.NET, and batch-scripting. Results. The NRTI System includes four main phases: preparatory, source data downloading, processing and post-processing with visualization, archiving, and result distribution among users. Source data filtering with a quality assurance index and downscaling with linear kriging interpolation were developed. The output of the NRTI System is data in regular grids with a spatial resolution of 0.02o×0.02o. Based on the NRTI System work during October – December 2021, we conducted preliminary analyses to understand the possibilities of data usage. Higher NO2 content was observed in Kyiv and Kharkiv, where traffic emissions play a crucial role in air quality worsening. The use of daily time series allowed the detection of an increase in NO2 variance during the heating season, as well as plume distribution from cities to rural areas due to the prevailing wind. CO content is more homogeneous; however, higher values were observed in industrial Kryvyi Rig and Odesa. It is emphasized the huge impact of shipping CO emissions on air quality in Odesa. The temporal averaging of the NRTI System output allowed us to define the most polluted districts within the cities of interest. We intend to continue developing the presented NRTI System and develop the same algorithms for all cities with populations greater than 500 000 people in order to provide operational air pollution monitoring based on satellite data.

Assimilation of S5P/TROPOMI carbon monoxide data with the global CAMS near-real-time system

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel 5 Precursor (S5P) satellite, launched in October 2017, provides a wealth of atmospheric composition data, including total columns of carbon monoxide (TCCO) at high horizontal resolution (5.5 km × 7 km). Near-real-time TROPOMI TCCO data have been monitored in the global data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS) since November 2018 to assess the quality of the data. The CAMS system already routinely assimilates TCCO data from the Measurement of Pollution in the Troposphere (MOPITT) instrument and the Infrared Atmospheric Sounding Interferometer (IASI) outside the polar regions. The assimilation of TROPOMI TCCO data in the CAMS system was tested for the period 6 July to 31 December 2021, i.e. after the TROPOMI algorithm update to version 02.02.00 in July 2021. By assimilating TROPOMI TCCO observations, the CAMS CO columns increase by on average 8 %, resulting in an improved fit to independent observations (IAGOS aircraft profiles and NDACC Fourier transform infrared (FTIR) tropospheric and total-column CO data) compared to a version of the CAMS system where only TCCO from MOPITT and IASI is assimilated. The largest absolute and relative changes from the assimilation of TROPOMI CO are found in the lower and middle troposphere, i.e. that part of the atmosphere that is not already well constrained by the assimilated TIR MOPITT and IASI data. The largest impact near the surface comes from clear-sky TROPOMI data over land, and additional vertical information comes from the retrievals of measurements in cloudy conditions. July and August 2021 saw record numbers of boreal wildfires over North America and Russia, leading to large amounts of CO being released into the atmosphere. The paper assesses the impact of TROPOMI CO assimilation on selected CO plumes more closely. While the CO column can be well constrained by the assimilation of TROPOMI CO data, and the fit to individual IAGOS CO profiles in the lower and middle troposphere is considerably improved, the TROPOMI CO columns do not provide further constraints on individual plumes that are transported across continents and oceans at altitudes above 500 hPa.

Global spatiotemporal completion of daily high-resolution TCCO from TROPOMI over land using a swath-based local ensemble learning method

At present, the daily global Total Column carbon monoxide (CO) (TCCO) product from TROPOMI is performed at the highest spatial resolution, which has been broadly adopted in atmospheric CO-related researches. Unfortunately, missing data emerges in the TROPOMI TCCO and the studies for the recovery of its missing pixels on a globe-scale are scarce. To address this issue, we develop a novel framework to recover missing data in global TROPOMI TCCO product over land from Jun. 01, 2018 to May. 31, 2021 by fusing multisource data. A finely devised Swath-based Local Ensemble Learning (SLEL) method is proposed due to the spatiotemporal discrepancy of missing pixels. In our study, three validation schemes are employed, including a Cross-Validation technique for each swath, in-situ validation against NDACC and TCCON, and transverse comparison with MOPITT and CAMS TCCO products. Validation results show that the developed framework presents an expected accuracy for recovering missing data in each swath, with daily average R and MB fluctuating around 0.9 and 0 mol/m2, respectively. Meanwhile, the accuracy of recovered results is satisfactory and close to that of TROPOMI, with the R of 0.885 against NDACC and 0.918 against TCCON. Furthermore, the recovered results achieve a small (distinctly) better performance than those of MOPITT (CAMS). The spatial pattern of the recovered TCCO is consistent with that of the MOPITT TCCO and can specify much finer spatial details by comparison with CAMS. As for daily examples, the SLEL method well recovers the missing pixels in global TROPOMI TCCO with rich spatial details, even for some critical missing cases. Seasonal variations of global CO spatial patterns are also clearly captured in our results. The daily full-coverage high-resolution (0.07°) TCCO can help obtain spatiotemporally continuous global changes of CO and support related researches, which is accessible on https://doi.org/10.5281/zenodo.7213104.

Interactions of Biosphere and Atmosphere within Longleaf Pine Restoration Areas

Longleaf pine forests are economically and culturally valued ecosystems in the southeastern United States. Efforts to restore the longleaf pine ecosystem have risen dramatically over the past three decades. Longleaf pine restoration generally involves varying degrees of forest harvesting and frequent applications of prescribed fire. Thus, it is important to understand their interactions with the atmosphere on a large scale. In this study, we analyzed 14 parameters of aerosols, gasses, and energy from three areas with longleaf pine restoration (named Bladen in eastern NC, Escambia in southern AL and northern FL, and Kisatchie in central LA, USA) from 2000 to 2021 using multiple satellites. Averaged across the areas, the monthly aerosol optical depth at 483.5 nm was about 0.022, and the monthly aerosol single scattering albedo was 0.97. Black carbon column mass density averaged 7.46 × 10−7 kg cm−2 across these areas, but Kisatchie had a higher monthly dust column mass density (2.35 × 10−4 kg cm−2) than Bladen or Escambia. The monthly total column ozone and CO concentration averaged about 285 DU and 135 ppbv across the three areas. Monthly SO2 column mass density was significantly higher in Bladen (4.42 × 10−6 kg cm−2) than in Escambia and Kisatchie. The monthly surface albedo in Escambia (0.116) was significantly lower than in the other areas. The monthly total cloud area fraction averaged about 0.456 across the three areas. Sensible and latent heat net flux and Bowen ratios significantly differed among the three areas. Bowen ratio and total cloud area fraction were not significantly correlated. Net shortwave of the forest surface averaged about 182.62 W m−2 across the three areas. The monthly net longwave was much lower in Bladen (−90.46 W m−2) than in Escambia and Kisatchie. These results provide the baseline information on the spatial and temporal patterns of interactions between longleaf pine forests under restoration and the atmosphere and can be incorporated into models of climate change.

Observations of atmospheric CO2 and CO based on in-situ and ground-based remote sensing measurements at Hefei site, China

The characteristics of long time series of CO2 and CO surface concentrations, tropospheric and total column dry-air mole fractions (DMF) from May 2015 to December 2019 were investigated. Both CO2 and CO show different seasonality for the three datasets. The annual increasing trend of CO2 is similar for all three datasets. However, the annual decreasing trend of CO for surface concentration is high compared to the other two measurements, mainly due to the improved combustion efficiency from power generation in recent years. The correlation between the tropospheric and total atmospheric CO2 and CO is higher than that between the surface concentration and tropospheric CO2 and CO. This is because the tropospheric and total atmospheric results both have common vertical profiles for CO2 and CO respective mole fractions that were observed in troposphere. Furthermore, the enhancement ratios of CO2 to CO derived from the three datasets during the period from 2016 to 2019 were compared. The ratio of ∆CO2 to ∆CO has an obvious increase with altitude each year, which means that the combustion efficiencies obtained from the three datasets are different. All ratios for the three datasets showed a slight increasing trend in recent years, which is attributed to increased combustion efficiency due to governmental measures for energy savings and emission reductions.