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The Total Carbon Column Observing Network (TCCON) is the baseline ground-based network of instruments that record solar absorption spectra from which accurate and precise column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4), CO (XCO), and other gases are retrieved. The TCCON data have been widely used for carbon cycle science and validation of satellites measuring greenhouse gas concentrations globally. The number of stations in the network (currently about 25) is limited and has a very uneven geographical coverage: the stations in the Northern Hemisphere are distributed mostly in North America, Europe, and Japan, and only 20 % of the stations are located in the Southern Hemisphere, leaving gaps in the global coverage. A denser distribution of ground-based solar absorption measurements is needed to improve the representativeness of the measurement data for various atmospheric conditions (humid, dry, polluted, presence of aerosol), various surface conditions such as high albedo (>0.4) and very low albedo, and a larger latitudinal distribution. More stations in the Southern Hemisphere are also needed, but a further expansion of the network is limited by its costs and logistical requirements. For this reason, several groups are investigating supplemental portable low-cost instruments. The European Space Agency (ESA) funded campaign Fiducial Reference Measurements for Ground-Based Infrared Greenhouse Gas Observations (FRM4GHG) at the Sodankylä TCCON site in northern Finland aims to characterise the assessment of several low-cost portable instruments for precise solar absorption measurements of XCO2, XCH4, and XCO. The test instruments under investigation are three Fourier transform spectrometers (FTSs): a Bruker EM27/SUN, a Bruker IRcube, and a Bruker Vertex70, as well as a laser heterodyne spectroradiometer (LHR) developed by the UK Rutherford Appleton Laboratory. All four remote sensing instruments performed measurements simultaneously next to the reference TCCON instrument, a Bruker IFS 125HR, for a full year in 2017. The TCCON FTS was operated in its normal high-resolution mode (TCCON data set) and in a special low-resolution mode (HR125LR data set), similar to the portable spectrometers. The remote sensing measurements are complemented by regular AirCore launches performed from the same site. They provide in situ vertical profiles of the target gas concentrations as auxiliary reference data for the column retrievals, which are traceable to the WMO SI standards. The reference measurements performed with the Bruker IFS 125HR were found to be affected by non-linearity of the indium gallium arsenide (InGaAs) detector. Therefore, a non-linearity correction of the 125HR data was performed for the whole campaign period and compared with the test instruments and AirCore. The non-linearity-corrected data (TCCONmod data set) show a better match with the test instruments and AirCore data compared to the non-corrected reference data. The time series, the bias relative to the reference instrument and its scatter, and the seasonal and the day-to-day variations of the target gases are shown and discussed. The comparisons with the HR125LR data set gave a useful analysis of the resolution-dependent effects on the target gas retrieval. The solar zenith angle dependence of the retrievals is shown and discussed. The intercomparison results show that the LHR data have a large scatter and biases with a strong diurnal variation relative to the TCCON and other FTS instruments. The LHR is a new instrument under development, and these biases are currently being investigated and addressed. The campaign helped to characterise and identify instrumental biases and possibly retrieval biases, which are currently under investigation. Further improvements of the instrument are ongoing. The EM27/SUN, the IRcube, the modified Vertex70, and the HR125LR provided stable and precise measurements of the target gases during the campaign with quantified small biases. The bias dependence on the humidity along the measurement line of sight has been investigated and no dependence was found. These three portable low-resolution FTS instruments are suitable to be used for campaign deployment or long-term measurements from any site and offer the ability to complement the TCCON and expand the global coverage of ground-based reference measurements of the target gases.

Carbonyl sulfide (OCS) is a non-hygroscopic trace species in the free troposphere and the primary sulfur reservoir maintained by direct oceanic, geologic, biogenic and anthropogenic emissions and t...

Australian fires are a primary driver of variability in Australian atmospheric composition and contribute significantly to regional and global carbon budgets. However, biomass burning emissions fro...

Column-averaged dry-air mole fraction of CO (XCO) measurements are obtained from two ground-based Fourier transform infrared (FTIR) spectrometer networks: the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). In this study, the differences between the TCCON and NDACC XCO measurements are investigated and discussed based on six NDACC–TCCON sites using data over the period 2007–2017. A direct comparison shows that the NDACC XCO measurements are about 5.5 % larger than the TCCON data at Ny-Ålesund, Bremen, and Izaña (Northern Hemisphere), and the absolute bias between the NDACC and TCCON data is within 2 % at Saint-Denis, Wollongong and Lauder (Southern Hemisphere). The hemispheric dependence of the bias is mainly attributed to their smoothing errors. The systematic smoothing error of the TCCON XCO data varies in the range between 0.2 % (Bremen) and 7.9 % (Lauder), and the random smoothing error varies in the range between 2.0 % and 3.6 %. The systematic smoothing error of NDACC data is between 0.1 % and 0.8 %, and the random smoothing error of NDACC data is about 0.3 %. For TCCON data, the smoothing error is significant because it is higher than the reported uncertainty, particularly at Southern Hemisphere sites. To reduce the influence from the a priori profiles and different vertical sensitivities, the scaled NDACC a priori profiles are used as the common a priori profiles for comparing TCCON and NDACC retrievals. As a result, the biases between TCCON and NDACC XCO measurements become more consistent (5.6 %–8.5 %) with a mean value of 6.8 % at these sites. To determine the sources of the remaining bias, regular AirCore measurements at Orléans and Sodankylä are compared to co-located TCCON measurements. It is found that TCCON XCO measurements are 6.1 ± 1.6 % and 8.0 ± 3.2 % smaller than the AirCore measurements at Orléans and Sodankylä, respectively, indicating that the scaling factor of TCCON XCO data should be around 1.0000 instead of 1.0672. Further investigations should be carried out in the TCCON community to determine the correct scaling factor to be applied to the TCCON XCO data. This paper also demonstrates that the smoothing error must be taken into account when comparing FTIR XCO data, and especially TCCON XCO data, with model or satellite data.

In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015–2016 to derive an XCO2 scaling factor of 0.9954 relative to TCCON. Although we found a slight drift of 0.13 % over 3 months in the calibration curve of the EM27/SUN vs. TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a 2-week campaign, keeping the retrieved Xair values, another measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to better understand the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at https://doi.org/10.4225/48/5b21f16ce69bc (Velazco et al., 2018).

In Australia, bushfires are a natural part of the country’s landscape and essential for the regeneration of plant species, however, the 2019–20 bushfires were unprecedented in their extent and intensity. This paper is focused on the 2019–20 Australian bushfires and the resulting surface and column atmospheric carbon monoxide (CO) anomalies around Wollongong. Column CO data from the ground-based Total Carbon Column Observing Network (TCCON) and Network for the Detection of Atmospheric Composition Change (NDACC) site in Wollongong are used together with surface in situ measurements. A systematic comparison was performed between the surface in situ and column measurements of CO to better understand whether column measurements can be used as an estimate of the surface concentrations. If so, satellite column measurements of CO could be used to estimate the exposure of humans to CO and other fire-related pollutants. We find that the enhancements in the column measurements are not always significantly evident in the corresponding surface measurements. Topographical features play a key role in determining the surface exposures from column abundance especially in a coastal city like Wollongong. The topography at Wollongong, combined with meteorological effects, potentially exacerbates differences in the column and surface. Hence, satellite column amounts are unlikely to provide an accurate reflection of exposure at the ground during major events like the 2019–2020 bushfires.

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000–2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one‐quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry‐climate model simulations, which assume emissions reductions similar to those caused by the COVID‐19 crisis. COVID‐19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020., Plain Language Summary: Worldwide actions to contain the COVID‐19 virus have closed factories, grounded airplanes, and have generally reduced travel and transportation. Less fuel was burnt, and less exhaust was emitted into the atmosphere. Due to these measures, the concentration of nitrogen oxides and volatile organic compounds (VOCs) decreased in the atmosphere. These substances are important for photochemical production and destruction of ozone in the atmosphere. In clean or mildly polluted air, reducing nitrogen oxides and/or VOCs will reduce the photochemical production of ozone and result in less ozone. In heavily polluted air, in contrast, reducing nitrogen oxides can increase ozone concentrations, because less nitrogen oxide is available to destroy ozone. In this study, we use data from three types of ozone instruments, but mostly from ozonesondes on weather balloons. The sondes fly from the ground up to 30 kilometers altitude. In the first 8 km, we find significantly reduced ozone concentrations in the northern extratropics during spring and summer of 2020, less than in any other year since at least 2000. We suggest that reduced emissions due to the COVID‐19 crisis have lowered photochemical ozone production and have caused the observed ozone reductions in the troposphere., Key Points: In spring and summer 2020, stations in the northern extratropics report on average 7% (4 nmol/mol) less tropospheric ozone than normal Such low tropospheric ozone, over several months, and at so many sites, has not been observed in any previous year since at least 2000 Most of the reduction in tropospheric ozone in 2020 is likely due to emissions reductions related to the COVID‐19 pandemic, NASA | Earth Sciences Division (NASA Earth Science Division) http://dx.doi.org/10.13039/100014573, Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (NSERC) http://dx.doi.org/10.13039/501100000038, Australian Research Council, Fonds De La Recherche Scientifique ‐ FNRS (FNRS) http://dx.doi.org/10.13039/501100002661, Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659, Bundesministerium für Wirtschaft und Energie (BMWi) http://dx.doi.org/10.13039/501100006360

2019 was both the hottest and driest year on record for Australia, leading to large forest fires in the southeast from November 2019 to January 2020. However, in early 2020, the fires and hot-dry c...

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (≈4 nmol/mol) below the 2000 to 2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere contributed less than one quarter of the observed tropospheric anomaly. The observed anomaly is consistent with recent chemistry-climate model simulations, which assume emissions reductions similar to those caused by the COVID-19 crisis. COVID-19 related emissions reductions appear to be the major cause for the observed reduced free tropospheric ozone in 2020.

The major air pollutant emissions have decreased and the overall air quality has substantially improved across China in recent years as a consequence of active clean air policies for mitigating severe air pollution problems. As key precursors of formaldehyde (HCHO) and ozone (O3), the volatile organic compounds (VOCs) in China are still increasing because current clean air policies lack mitigation measures for VOCs. In this study, we mapped the drivers of HCHO variability over eastern China using ground-based high-resolution Fourier transform infrared (FTIR) spectrometry and GEOS-Chem model simulation. Diurnal, seasonal, and interannual variability of HCHO over eastern China was investigated and hydroxyl (OH) radical production from HCHO was evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO were analysed by using ground level carbon monoxide (CO) and Ox (O3 + nitrogen oxide (NO2)) as tracers for emitted and photochemical HCHO, respectively. Contributions of various emission sectors and geographical transport to the observed HCHO summertime enhancements were determined by using a GEOS-Chem tagged-tracer simulation. The tropospheric HCHO volume mixing ratio (VMR) reached a maximum monthly mean value of (1.1 ± 0.27) ppbv in July and a minimum monthly mean value of (0.4 ± 0.11) ppbv in January. The tropospheric HCHO VMR time series from 2015–2019 shows a positive trend of (1.43 ± 0.14) % per yr. The photochemical HCHO is the dominant source of atmospheric HCHO over eastern China for most of the year (68.1 %). In the studied years, the HCHO photolysis was an important source of OH radical over eastern China during all sunlight hours of both summer and winter days. The anthropogenic emissions (fossil fuel + biofuel emissions) accounted for 31.96 % and the natural emissions (biomass burning + biogenic) accounted for 48.75 % of HCHO summertime enhancements. The observed HCHO summertime enhancements were largely attributed to the emissions within China (76.92 %), where eastern China dominated the contribution (46.24 %). The increased trend in HCHO in recent years was largely attributed to the increase in the HCHO precursors such as CH4 and nonmethane VOCs (NMVOCs). This study can provide an evaluation of recent VOC emissions and regional photochemical capacity in China. In addition, this study is also important for regulatory and control purposes and will help to improve urban air quality and contribute to the formation of new Chinese clean air policies in the future.

We retrieved lower stratospheric vertical profiles of O3, HNO3, and HCl from solar spectra taken with a ground-based Fourier-Transform infrared spectrometer (FTIR) installed at Syowa Station, Antarctica (69.0°S, 39.6°E) from March to December 2007 and September to November 2011. This was the first continuous measurements of chlorine species throughout the ozone hole period from the ground in Antarctica. We analyzed temporal variation of these species combined with ClO, HCl, and HNO3 data taken with the Aura/MLS (Microwave Limb Sounder) satellite sensor, and ClONO2 data taken with the Envisat/MIPAS (The Michelson Interferometer for Passive Atmospheric Sounding) satellite sensor at 18 and 22 km over Syowa Station. HCl and ClONO2 decrease occurred from the end of May at both 18 and 22 km, and eventually in early winter, both HCl and ClONO2 were almost depleted. When the sun returned to Antarctica in spring, enhancement of ClO and gradual O3 destruction were observed. During the ClO enhanced period, negative correlation between ClO and ClONO2 was observed in the time-series of the data at Syowa Station. This negative correlation was associated with the relative distance between Syowa Station and the edge of the polar vortex. We used MIROC3.2 Chemistry-Climate Model (CCM) results to investigate the behavior of whole chlorine and related species inside the polar vortex and the boundary region in more detail. From CCM model results, rapid conversion of chlorine reservoir species (HCl and ClONO2) into Cl2, gradual conversion of Cl2 into Cl2O2, increase of HOCl in winter period, increase of ClO when sunlight became available, and conversion of ClO into HCl, was successfully reproduced. HCl decrease in the winter polar vortex core continued to occur due to both transport of ClONO2 from the subpolar region to higher latitudes, providing a flux of ClONO2 from more sunlit latitudes into the polar vortex, and the heterogeneous reaction of HCl with HOCl. Temporal variation of chlorine species over Syowa Station was affected by both heterogeneous chemistries related to Polar Stratospheric Cloud (PSC) occurrence inside the polar vortex, and transport of a NOx-rich airmass from the polar vortex boundary region which can produce additional ClONO2 by reaction of ClO with NO2. The deactivation pathways from active chlorine into reservoir species (HCl and/or ClONO2) were confirmed to be highly dependent on the availability of ambient O3. At 18 km where most ozone was depleted, most ClO was converted to HCl. At 22km where some O3 was available, additional increase of ClONO2 from pre-winter value occurred, similar as in the Arctic.

Atmospheric ammonia (NH3) plays an important role in the formation of fine particulate matter, leading to severe environmental degradation and human health issues. In this work, ground-based FTIR observations are used to obtain the total columns and vertical profiles of atmospheric NH3 at a measurement site in Hefei, China, from December 2016 to November 2018. The spatial distribution and temporal variation, seasonal trend, emission sources and potential sources of NH3 are analyzed. The time series of ammonia columns show that FTIR observations captured the seasonal cycle of NH3 over the two years of measurement, with a 22.14 % yr-1 annual increase rate over the Hefei site. We used IASI satellite data to compare with the FTIR data, and the correlation coefficients (R) between the two datasets are 0.86 and 0.78 for IASI-A and IASI-B, respectively. The results demonstrate the IASI data are in broad agreement with our FTIR data. To examine the contribution of traffic to NH3 columns, we analyze the relationship of NH3 columns with CO surface concentrations. NH3 columns show high correlation (R = 0.77) with CO concentrations in summer, indicating that the elevated NH3 columns are partly caused by urban emissions from vehicles. Further, high correlation of NH3 columns with air temperature is obvious from their diurnal variation during the observation period. In addition, the clear correlation between NH3 columns and air temperature in spring and autumn over Hefei, suggests that agriculture was indeed the main source of ammonia in spring and autumn. Furthermore, the back trajectories of air masses calculated by the HYSPLIT model confirmed that agriculture was the dominant source of ammonia in spring, autumn and winter, while urban anthropogenic emissions contributed to the high level of NH3 in summer over the Hefei site. The potential source areas influencing the NH3 columns were distributed in the local area of Hefei, the northern part of Anhui province, as well as Shangdong, Jiangsu and Henan provinces. This study helps to identify the emission sources and potential sources that contribute to NH3 columns over Hefei, a highly populated and polluted area. This is the first time that ground-based FTIR remote sensing of NH3 columns and comparison with satellite data are reported in China.

TROPOMI (the TROPOspheric Monitoring Instrument), on-board the Sentinel-5 Precursor satellite, has been monitoring the Earth's atmosphere since October 2017, with an unprecedented horizontal resolution (initially 7×3.5 km2, upgraded to 5.5×3.5 km2 since August 2019). Monitoring air quality is one of the main objectives of TROPOMI, with the measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products (version 1.1.[5-7]), using ground-based solar-absorption FTIR (Fourier Transform Infrared) measurements of HCHO from twenty-five stations around the world, including high, mid, and low latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns, using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). We observe that, at all sites, the TROPOMI accuracy is below the upper limit of the pre-launch requirements of 80 %, and below the lower limit of 40 % for 20 of the 25 stations. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations, except for the highest HCHO levels site where it is found to be underestimated. We find that, while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation (+26 ± 5 %) of TROPOMI is observed for very small HCHO levels ( 8.0 × 1015 molec/cm2). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias at the regions of emissions, and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI=+ 1.10 (± 0.05) × 1015+ 0.64 (± 0.03) × FTIR, in molec/cm2). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful to minimize a possible additional collocation error. The precision requirement of 1.2 × 1016 molec/cm2 for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be twice better (0.5–0.8 × 1015 molec/cm2 for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R = 0.88 for 3 hours-mean coincidences; R = 0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products which is well within the pre-launch requirements for both accuracy and precision. This paper advises for a refinement of the TROPOMI random uncertainty budget and of the TROPOMI quality assurance values for a better filtering of the remaining outliers.

Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50 % can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations.For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12 % and 27 % and between 1 and 11×1014 molec cm−2, respectively. The median values among all stations are 13 % and 2.9×1014 molec cm−2 for the total systematic and random uncertainties.This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013 molec cm−2) to highly polluted levels (7×1016 molec cm−2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions.

Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH3 retrieval (CFPR) column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 × 1016 molecules cm−2, i.e. ranging from moderate to polluted conditions, the relative difference is on average ∼ 0–5 % with a standard deviation of 25–50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (

Formic (HCOOH) and acetic acids (CH3COOH) are the most abundant carboxylic acids in the Earth's atmosphere and key compounds to aqueous-phase chemistry. Here we present the first distributions of CH3COOH retrieved from the 2007–2018 satellite observations of the nadir-looking infrared atmospheric sounding interferometer (IASI), using a neural network-based retrieval approach. A joint analysis with the IASI HCOOH product reveals that the two species exhibit similar distributions, seasonality, and atmospheric burden, pointing to major common sources. We show that their abundance is highly correlated to isoprene and monoterpenes emissions, as well as to biomass burning. Over Africa, evidence is provided that residual smoldering combustion might be a major driver of the HCOOH and CH3COOH seasonality. Earlier seasonal enhancement of HCOOH at Northern Hemisphere middle and high latitudes and late seasonal secondary peaks of CH3COOH in the tropics suggest that sources and production pathways specific to each species are also at play., SCOPUS: ar.j, info:eu-repo/semantics/published

TROPOMI (the TROPOspheric Monitoring Instrument), on board the Sentinel-5 Precursor (S5P) satellite, has been monitoring the Earth's atmosphere since October 2017 with an unprecedented horizontal resolution (initially 7 km2×3.5 km2, upgraded to 5.5 km2×3.5 km2 in August 2019). Monitoring air quality is one of the main objectives of TROPOMI; it obtains measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products versions 1.1.(5-7), using ground-based solar-absorption FTIR (Fourier-transform infrared) measurements of HCHO from 25 stations around the world, including high-, mid-, and low-latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions, from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). The pre-launch accuracy requirements of TROPOMI HCHO are 40 %–80 %. We observe that these requirements are well reached, with the BIAS found below 80 % at all the sites and below 40 % at 20 of the 25 sites. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations except for the highest-HCHO-level site, where it is found to be underestimated. We find that while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation (+26±5 %) of TROPOMI is observed for very low HCHO levels (<2.5×1015 molec. cm−2), while an underestimation (-30.8%±1.4 %) is found for high HCHO levels (>8.0×1015 molec. cm−2). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias in the regions of emissions and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI =+1.10±0.05 ×1015+0.64±0.03 × FTIR; in molecules per square centimetre). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful for minimizing a possible additional collocation error. The precision requirement of 1.2×1016 molec. cm−2 for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be 2 times better (0.5–0.8×1015 molec. cm−2 for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R=0.88 for 3 h mean coincidences; R=0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products, which is well within the pre-launch requirements for both accuracy and precision. This paper makes suggestions for the refinement of the TROPOMI random uncertainty budget and TROPOMI quality assurance values for a better filtering of the remaining outliers.

We retrieved lower stratospheric vertical profiles of O3, HNO3, and HCl from solar spectra taken with a ground-based Fourier-Transform infrared spectrometer (FTIR) installed at Syowa Station, Antarctica (69.0° S, 39.6° E) from March to December 2007 and September to November 2011. This was the first continuous measurements of chlorine species throughout the ozone hole period from the ground in Antarctica. We analyzed temporal variation of these species combined with ClO, HCl, and HNO3 data taken with the Aura/MLS (Microwave Limb Sounder) satellite sensor, and ClONO2 data taken with the Envisat/MIPAS (The Michelson Interferometer for Passive Atmospheric Sounding) satellite sensor at 18 and 22 km over Syowa Station. HCl and ClONO2 decrease occurred at both 18 and 22 km, and soon ClONO2 was almost depleted in early winter. When the sun returned to Antarctica in spring, enhancement of ClO and gradual O3 destruction were observed. During the ClO enhanced period, negative correlation between ClO and ClONO2 was observed in the time-series of the data at Syowa Station. This negative correlation was associated with the distance between Syowa Station and the inner edge of the polar vortex. We used MIROC3.2 Chemistry-Climate Model (CCM) results to see the comprehensive behavior of chlorine and related species inside the polar vortex and the edge region in more detail. From CCM model results, rapid conversion of chlorine reservoir species (HCl and ClONO2) into Cl2, gradual conversion of Cl2 into Cl2O2, increase of ClO when sunlight became available, and conversion of ClO into HCl, was successfully reproduced. HCl decrease in the winter polar vortex core continued to occur due to the transport of ClONO2 from the subpolar region to higher latitudes, providing a flux of ClONO2 from more sunlit latitudes into the polar vortex. Temporal variation of chlorine species over Syowa Station was affected by both heterogeneous chemistry related to Polar Stratospheric Cloud (PSC) occurrence deep inside the polar vortex, and transport of an NOx-rich airmass from lower latitudinal polar vortex boundary region which can produce additional ClONO2 by reaction of ClO with NO2. The deactivation pathways from active chlorine into reservoir species (HCl and/or ClONO2) were found to be highly dependent on the availability of ambient O3. At an altitude where most ozone was depleted in Antarctica (18 km), most ClO was converted to HCl. However, at an altitude where there were some O3 available (22 km), additional increase of ClONO2 from initial value can occur, similar to the case in the Arctic.

High-resolution solar absorption spectra, observed by ground-based Fourier Transform Infrared spectroscopy (FTIR), are used to retrieve vertical profiles and partial or total column concentrations of many trace gases. In this study, we present the tropospheric CO2 columns retrieved by mid-infrared solar spectra over Hefei, China. To reduce the influence of stratospheric CO2 cross-dependencies on tropospheric CO2, an a posteriori optimization method based on a simple matrix multiplication is used to correct the tropospheric CO2 profiles and columns. The corrected tropospheric CO2 time series show an obvious annual increase and seasonal variation. The tropospheric CO2 annual increase rate is 2.71 ± 0.36 ppm yr-1, with the annual peak value in January, and CO2 decreases to a minimum in August. Further, the corrected tropospheric CO2 from GEOS-Chem simulations are in good agreement with the coincident FTIR data, with a correlation coefficient between GEOS-chem model and FTS of 0.89. The annual increase rate of XCO2 observed from near-infrared solar absorption spectra is in good agreement with the tropospheric CO2 but the annual seasonal amplitude of XCO2 is only about 1/3 of dry-air averaged mole fractions (DMF) of tropospheric CO2. This is mostly attributed to the seasonal variation of CO2 being mainly dominated by sources near the surface.

We report on the ground-based FTIR (Fourier transform infrared) tropospheric water vapour isotopologue remote sensing data that have been recently made available via the database of NDACC (Network for the Detection of Atmospheric Composition Change; ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA/) and via doi:10.5281/zenodo.48902. Currently, data are available for 12 globally distributed stations. They have been centrally retrieved and quality-filtered in the framework of the MUSICA project (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). We explain particularities of retrieving the water vapour isotopologue state (vertical distribution of H216O, H218O, and HD16O) and reveal the need for a new metadata template for archiving FTIR isotopologue data. We describe the format of different data components and give recommendations for correct data usage. Data are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies disregarding different isotopologues (comparison with radiosonde data, analyses of water vapour variability and trends, etc.). The second type is needed for analysing moisture pathways by means of H2O, δD-pair distributions.

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., SCOPUS: ar.j, info:eu-repo/semantics/published

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a mean relative difference of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (−50 to +100 %).

In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) from an EM27/SUN portable spectrometer, equipped with an automated clam shell cover, taken in a semi-arid region of Australia. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015–2016 to derive an XCO2 calibration factor of 0.9954 relative to TCCON. Although we found a slight drift of .0125 % per month in the calibration curve of the EM27/SUN vs TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a campaign, keeping the retrieved Xair values, a measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to improve the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at http://dx.doi.org/10.4225/48/5b21f16ce69bc (Velazco et al., 2018).

Nitrous oxide (N2O) is an important greenhouse gas and it can also generate nitric oxide, which depletes ozone in the stratosphere. It is a common target species of ground-based Fourier transform infrared (FTIR) near-infrared (TCCON) and mid-infrared (NDACC) measurements. Both TCCON and NDACC networks provide a long-term global distribution of atmospheric N2O mole fraction. In this study, the dry-air column-averaged mole fractions of N2O (XN2O) from the TCCON and NDACC measurements are compared against each other at seven sites around the world (Ny-Ålesund, Sodankylä, Bremen, Izaña, Réunion, Wollongong, Lauder) in the time period of 2007–2017. The mean differences in XN2O between TCCON and NDACC (NDACC–TCCON) at these sites are between −3.32 and 1.37 ppb (−1.1 %–0.5 %) with standard deviations between 1.69 and 5.01 ppb (0.5 %–1.6 %), which are within the uncertainties of the two datasets. The NDACC N2O retrieval has good sensitivity throughout the troposphere and stratosphere, while the TCCON retrieval underestimates a deviation from the a priori in the troposphere and overestimates it in the stratosphere. As a result, the TCCON XN2O measurement is strongly affected by its a priori profile. Trends and seasonal cycles of XN2O are derived from the TCCON and NDACC measurements and the nearby surface flask sample measurements and compared with the results from GEOS-Chem model a priori and a posteriori simulations. The trends and seasonal cycles from FTIR measurement at Ny-Ålesund and Sodankylä are strongly affected by the polar winter and the polar vortex. The a posteriori N2O fluxes in the model are optimized based on surface N2O measurements with a 4D-Var inversion method. The XN2O trends from the GEOS-Chem a posteriori simulation (0.97±0.02 (1σ) ppb yr−1) are close to those from the NDACC (0.93±0.04 ppb yr−1) and the surface flask sample measurements (0.93±0.02 ppb yr−1). The XN2O trend from the TCCON measurements is slightly lower (0.81±0.04 ppb yr−1) due to the underestimation of the trend in TCCON a priori simulation. The XN2O trends from the GEOS-Chem a priori simulation are about 1.25 ppb yr−1, and our study confirms that the N2O fluxes from the a priori inventories are overestimated. The seasonal cycles of XN2O from the FTIR measurements and the model simulations are close to each other in the Northern Hemisphere with a maximum in August–October and a minimum in February–April. However, in the Southern Hemisphere, the modeled XN2O values show a minimum in February–April while the FTIR XN2O retrievals show different patterns. By comparing the partial column-averaged N2O from the model and NDACC for three vertical ranges (surface–8, 8–17, 17–50 km), we find that the discrepancy in the XN2O seasonal cycle between the model simulations and the FTIR measurements in the Southern Hemisphere is mainly due to their stratospheric differences.

Dry-air column-averaged mole fractions of methane (XCH4) retrieved from ground-based solar Fourier transform infrared (FTIR) measurements provide valuable information for satellite validation, evaluation of chemical-transport models, and source-sink-inversions. In this context, Sussmann et al. (2013) have shown that midinfrared (MIR) soundings from the Network for the Detection of Atmospheric Composition Change (NDACC) can be combined with near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON) without the need to apply an overall intercalibration factor. However, in spite of efforts to reduce a priori impact, some residual seasonal biases were identified, and the reasons behind remained unclear. In extension to this previous work, which was based on multiannual quasi-coincident MIR and NIR measurements from the stations Garmisch (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong (34.41° S, 150.88° E, 30 m a.s.l.), we now investigate upgraded retrievals with longer temporal coverage and include three additional stations (Ny-Ålesund, 78.92° N, 11.93° E, 20 m a.s.l.; Karlsruhe, 49.08° N, 8.43° E, 110 m a.s.l.; Izaña, 28.31° N, 16.45° W, 2.370 m a.s.l.). Our intercomparison results (except for Ny-Ålesund) confirm that there is no overall bias between MIR and NIR XCH4 retrievals, and all MIR and NIR time series reveal a quasi-periodic seasonal bias for all stations, except for Izaña. We find that dynamical variability causes MIR–NIR differences of up to ~ 30 ppb (parts per billion) for Ny-Ålesund, ~ 20 ppb for Wollongong, ~ 18 ppb for Garmisch, and ~ 12 ppb for Karlsruhe. The mechanisms behind this variability are elaborated via two case studies, one dealing with stratospheric subsidence induced by the polar vortex at Ny-Ålesund and the other with a deep stratospheric intrusion event at Garmisch. Smoothing effects caused by the dynamical variability during these events are different for MIR and NIR retrievals depending on the altitude of the perturbation area. MIR retrievals appear to be more realistic in the case of stratospheric subsidence, while NIR retrievals are more accurate in the case of stratosphere–troposphere exchange (STE) in the upper troposphere/lower stratosphere (UTLS) region. About 35% of the FTIR measurement days at Garmisch are impacted by STE, and about 23% of the measurement days at Ny-Ålesund are influenced by polar vortex subsidence. The exclusion of data affected by these dynamical situations resulted in improved agreement of MIR and NIR seasonal cycles for Ny-Ålesund and Garmisch. We found that dynamical variability is a key factor in constraining the accuracy of MIR and NIR seasonal cycles. To mitigate this impact it is necessary to use more realistic a priori profiles that take these dynamical events into account (e.g., via improved models), and/or to improve the FTIR retrievals to achieve a more uniform sensitivity at all altitudes (possibly including profile retrievals for the TCCON data).

To understand and project future ozone recovery, understanding of mechanisms related to polar ozone destruction is crucial. For polar stratospheric ozone destruction, chlorine species play an important role, but detailed temporal evolution of chlorine species in the Antarctic winter is not well understood. We retrieved lower stratospheric vertical profiles of O3, HNO3, and HCl from solar spectra taken with a ground-based Fourier-Transform infrared spectrometer (FTIR) installed at Syowa Station, Antarctica (69.0º S, 39.6º E) from March to December 2007 and September to November 2011. We analyzed temporal variation of these species combined with ClO, HCl, and HNO3 data taken with the Aura/MLS (Microwave Limb Sounder) satellite sensor, and ClONO2 data taken with the Envisat/MIPAS (The Michelson Interferometer for Passive Atmospheric Sounding) satellite sensor at 18 and 22 km over Syowa Station. When the stratospheric temperature over Syowa Station fell below polar stratospheric cloud (PSC) saturation temperature in early winter, PSCs started to form and heterogeneous reaction on PSCs convert chlorine reservoirs into reactive chemical species. HCl and ClONO2 decrease occurred at both 18 and 22 km, and soon ClONO2 was almost depleted in early winter. When the sun returned to Antarctica in spring, enhancement of ClO and gradual O3 destruction were observed. During the ClO enhanced period, negative correlation between ClO and ClONO2 was observed in the time-series of the data at Syowa Station. This negative correlation was associated with the distance between Syowa Station and the inner edge of the polar vortex. Temporal variation of chlorine species over Syowa Station was affected by both heterogeneous chemistry related to PSC occurrence deep inside the polar vortex, and transport of an NONOx-rich airmass from lower latitudinal polar vortex boundary region which can produce additional ClONO2 by reaction between ClO and NO2. We used MIROC3.2 Chemistry-Climate Model (CCM) results to see the comprehensive behavior of chlorine and related species inside the polar vortex and the edge region in more detail. Rapid conversion of chlorine reservoir species (HCl and ClONO2) into Cl2, gradual conversion of Cl2 into Cl2O2, increase of ClO when sunlight became available, and conversion of ClO into HCl, was successfully reproduced by the CCM. HCl decrease in the winter polar vortex core continued to occur due to the transport of ClONO2 from the subpolar region (55–65º S) to higher latitudes (65–75º S), providing a flux of ClONO2 from more sunlit latitudes into the polar vortex. The deactivation pathways from active ClO into reservoir species (HCl and/or ClONO2) were found to be highly dependent on the availability of ambient O3 and NOx. At an altitude where most ozone was depleted in Antarctica, most ClO was converted to HCl. However, when there were some O3 and NOx available, super-recovery of ClONO2 can occur, similar to the case in the Arctic.

Toxic nitrogen oxides produced by high temperature combustion are prevalent in urban environments, contributing to a significant health burden. Nitrogen oxides such as NO2 and HONO in pollution are important for hydroxyl radical (OH) production and overall oxidative capacity in urban environments; however, current mechanisms cannot explain high daytime levels of HONO observed in many urban and rural locations around the world. Here we present HONO, NO2 and aerosol extinction vertical distributions retrieved from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in suburban Melbourne, which are the first MAX-DOAS results from the Australian continent. Using the optimal estimation algorithm HEIPRO we show that vertical profiles for NO2 and HONO can be calculated with a low dependence on the retrieval forward model and a priori parameters, despite a lack of independent co-located aerosol or trace gas measurements. Between December 2016 and April 2017 average peak NO2 values of 8±2 ppb indicated moderate traffic pollution levels, and high daytime peak values of HONO were frequently detected, averaging 220±30 ppt in the middle of the day. HONO levels measured in Melbourne were typically lower than those recorded in the morning in other places around the world, indicating minimal overnight accumulation, but peaked in the middle of the day to be commensurate with midday concentrations in locations with much higher NO2 pollution. Regular midday peaks in the diurnal cycle of HONO surface concentrations have only previously been reported in rural locations. The HONO measured implies a daytime source term 1 ppb h−1 above the predicted photostationary state (PSS) concentration and represents an OH radical source up to 4 times stronger than from ozone photolysis alone in the lowest 500 m of the troposphere. The dependence of the high midday HONO levels on soil moisture, combined with the observed diurnal and vertical profiles, provides evidence for a strong photoactivated and ground-based daytime HONO source.

Transport of carbonyl sulfide (OCS) from the troposphere to the stratosphere contributes sulfur to the stratospheric aerosol layer, which reflects incoming short-wave solar radiation, cooling the climate system. Previous analyses of OCS observations have shown no significant trend, suggesting that OCS is unlikely to be a major contributor to the reported increases in stratospheric aerosol loading and indicating a balanced OCS budget. Here we present analyses of ground-based Fourier transform spectrometer measurements of OCS at three Southern Hemisphere sites spanning 34.45°S to 77.80°S. At all three sites statistically significant positive trends are seen from 2001 to 2014 with an observed overall trend in total column OCS at Wollongong of 0.73 ± 0.03%/yr, at Lauder of 0.43 ± 0.02%/yr, and at Arrival Heights of 0.45 ± 0.05%/yr. These observed trends in OCS imply that the OCS budget is not balanced and could contribute to constraints on current estimates of sources and sinks.

We present global distributions of C2H2 and hydrogen cyanide (HCN) total columns derived from the Infrared Atmospheric Sounding Interferometer (IASI) for the years 2008–2010. These distributions are obtained with a fast method allowing to retrieve C2H2 abundance globally with a 5 % precision and HCN abundance in the tropical (subtropical) belt with a 10 % (25 %) precision. IASI data are compared for validation purposes with ground-based Fourier transform infrared (FTIR) spectrometer measurements at four selected stations. We show that there is an overall agreement between the ground-based and space measurements with correlation coefficients for daily mean measurements ranging from 0.28 to 0.81, depending on the site. Global C2H2 and subtropical HCN abundances retrieved from IASI spectra show the expected seasonality linked to variations in the anthropogenic emissions and seasonal biomass burning activity, as well as exceptional events, and are in good agreement with previous spaceborne studies. Total columns simulated by the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) are compared to the ground-based FTIR measurements at the four selected stations. The model is able to capture the seasonality in the two species in most of the cases, with correlation coefficients for daily mean measurements ranging from 0.50 to 0.86, depending on the site. IASI measurements are also compared to the distributions from MOZART-4. Seasonal cycles observed from satellite data are reasonably well reproduced by the model with correlation coefficients ranging from −0.31 to 0.93 for C2H2 daily means, and from 0.09 to 0.86 for HCN daily means, depending on the considered region. However, the anthropogenic (biomass burning) emissions used in the model seem to be overestimated (underestimated), and a negative global mean bias of 1 % (16 %) of the model relative to the satellite observations was found for C2H2 (HCN).

Trends in the vertical distribution of ozone are reported and compared for a number of new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere (as measured by equivalent effective stratospheric chlorine – EESC) was maximised in the second half of the 1990s. We examine the periods before and after the peak to see if any change in trend is discernible in the ozone record that might be attributable to a change in the EESC trend, though no attribution is attempted. Prior to 1998, trends in the upper stratosphere (~ 45 km, 4 hPa) are found to be −5 to −10 % per decade at mid-latitudes and closer to −5 % per decade in the tropics. No trends are found in the mid-stratosphere (28 km, 30 hPa). Negative trends are seen in the lower stratosphere at mid-latitudes in both hemispheres and in the deep tropics. However, it is hard to be categorical about the trends in the lower stratosphere for three reasons: (i) there are fewer measurements, (ii) the data quality is poorer, and (iii) the measurements in the 1990s are perturbed by aerosols from the Mt Pinatubo eruption in 1991. These findings are similar to those reported previously even though the measurements for the main satellite and ground-based records have been revised. There is no sign of a continued negative trend in the upper stratosphere since 1998: instead there is a hint of an average positive trend of ~ 2 % per decade in mid-latitudes and ~ 3 % per decade in the tropics. The significance of these upward trends is investigated using different assumptions of the independence of the trend estimates found from different data sets. The averaged upward trends are significant if the trends derived from various data sets are assumed to be independent (as in Pawson et al., 2014) but are generally not significant if the trends are not independent. This occurs because many of the underlying measurement records are used in more than one merged data set. At this point it is not possible to say which assumption is best. Including an estimate of the drift of the overall ozone observing system decreases the significance of the trends. The significance will become clearer as (i) more years are added to the observational record, (ii) further improvements are made to the historic ozone record (e.g. through algorithm development), and (iii) the data merging techniques are refined, particularly through a more rigorous treatment of uncertainties.

We investigate the impact of biogenic emissions on carbon monoxide (CO) and formaldehyde (HCHO) in the Southern Hemisphere (SH), with simulations using two different biogenic emission inventories for isoprene and monoterpenes. Results from four atmospheric chemistry models are compared to continuous long-term ground-based CO and HCHO column measurements at the SH Network for the Detection of Atmospheric Composition Change (NDACC) sites, the satellite measurement of tropospheric CO columns from the Measurement of Pollution in the Troposphere (MOPITT), and in situ surface CO measurements from across the SH, representing a subset of the National Oceanic and Atmospheric Administration's Global Monitoring Division (NOAA GMD) network. Simulated mean model CO using the Model of Emissions of Gases and Aerosols from Nature (v2.1) computed in the frame work of the Land Community Model (CLM-MEGANv2.1) inventory is in better agreement with both column and surface observations than simulations adopting the emission inventory generated from the LPJ-GUESS dynamical vegetation model framework, which markedly underestimate measured column and surface CO at most sites. Differences in biogenic emissions cause large differences in CO in the source regions which propagate to the remote SH. Significant inter-model differences exist in modelled column and surface CO, and secondary production of CO dominates these inter-model differences, due mainly to differences in the models' oxidation schemes for volatile organic compounds, predominantly isoprene oxidation. While biogenic emissions are a significant factor in modelling SH CO, inter-model differences pose an additional challenge to constrain these emissions. Corresponding comparisons of HCHO columns at two SH mid-latitude sites reveal that all models significantly underestimate the observed values by approximately a factor of 2. There is a much smaller impact on HCHO of the significantly different biogenic emissions in remote regions, compared to the source regions. Decreased biogenic emissions cause decreased CO export to remote regions, which leads to increased OH; this in turn results in increased HCHO production through methane oxidation. In agreement with earlier studies, we corroborate that significant HCHO sources are likely missing in the models in the remote SH.

Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-transform infrared) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these NDACC data records. Our XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this suggested NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons, and the bias is 25‰). Our XCO2 model is a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (multi-platform remote sensing of isotopologues for investigating the cycle of atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3‰.

Ground-based Fourier transform infrared (FTIR) measurements of solar absorption spectra can provide ozone total columns with a precision of 2% but also independent partial column amounts in about four vertical layers, one in the troposphere and three in the stratosphere up to about 45km, with a precision of 5–6%. We use eight of the Network for the Detection of Atmospheric Composition Change (NDACC) stations having a long-term time series of FTIR ozone measurements to study the total and vertical ozone trends and variability, namely, Ny-Ålesund (79° N), Thule (77° N), Kiruna (68° N), Harestua (60° N), Jungfraujoch (47° N), Izaña (28° N), Wollongong (34° S) and Lauder (45° S). The length of the FTIR time series varies by station but is typically from about 1995 to present. We applied to the monthly means of the ozone total and four partial columns a stepwise multiple regression model including the following proxies: solar cycle, quasi-biennial oscillation (QBO), El Niño–Southern Oscillation (ENSO), Arctic and Antarctic Oscillation (AO/AAO), tropopause pressure (TP), equivalent latitude (EL), Eliassen–Palm flux (EPF), and volume of polar stratospheric clouds (VPSC). At the Arctic stations, the trends are found mostly negative in the troposphere and lower stratosphere, very mixed in the middle stratosphere, positive in the upper stratosphere due to a large increase in the 1995–2003 period, and non-significant when considering the total columns. The trends for mid-latitude and subtropical stations are all non-significant, except at Lauder in the troposphere and upper stratosphere and at Wollongong for the total columns and the lower and middle stratospheric columns where they are found positive. At Jungfraujoch, the upper stratospheric trend is close to significance (+0.9 ± 1.0% decade−1). Therefore, some signs of the onset of ozone mid-latitude recovery are observed only in the Southern Hemisphere, while a few more years seem to be needed to observe it at the northern mid-latitude station.

We present the first intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR XCH4 time series for Garmisch shows a quasi-periodic seasonal bias leading to a standard deviation (stdv) of the difference time series (NIR–MIR) of 7.2 ppb. After reducing time-dependent a priori impact by using realistic site- and time-dependent ACTM-simulated profiles as a common prior, the seasonal bias is reduced (stdv = 5.2 ppb). A linear fit to the MIR/NIR scatter plot of monthly means based on same-day coincidences does not show a y-intercept that is statistically different from zero, and the MIR/NIR intercalibration factor is found to be close to ideal within 2-σ uncertainty, i.e. 0.9996(8). The difference time series (NIR–MIR) do not show a significant trend. The same basic findings hold for Wollongong. In particular an overall MIR/NIR intercalibration factor close to the ideal 1 is found within 2-σ uncertainty. At Wollongong the seasonal cycle of methane is less pronounced and corresponding smoothing errors are not as significant, enabling standard MIR and NIR retrievals to be used directly, without correction to a common a priori. Our results suggest that it is possible to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

We present lower/middle tropospheric column-averaged CH4 mole fraction time series measured by nine globally distributed ground-based FTIR (Fourier transform infrared) remote sensing experiments of the Network for the Detection of Atmospheric Composition Change (NDACC). We show that these data are well representative of the tropospheric regional-scale CH4 signal, largely independent of the local surface small-scale signals, and only weakly dependent on upper tropospheric/lower stratospheric (UTLS) CH4 variations. In order to achieve the weak dependency on the UTLS, we use an a posteriori correction method. We estimate a typical precision for daily mean values of about 0.5% and a systematic error of about 2.5%. The theoretical assessments are complemented by an extensive empirical study. For this purpose, we use surface in situ CH4 measurements made within the Global Atmosphere Watch (GAW) network and compare them to the remote sensing data. We briefly discuss different filter methods for removing the local small-scale signals from the surface in situ data sets in order to obtain the in situ regional-scale signals. We find good agreement between the filtered in situ and the remote sensing data. The agreement is consistent for a variety of timescales that are interesting for CH4 source/sink research: day-to-day, monthly, and inter-annual. The comparison study confirms our theoretical estimations and proves that the NDACC FTIR measurements can provide valuable data for investigating the cycle of CH4.

The abundance of chlorine in the Earth's atmosphere increased considerably during the 1970s to 1990s, following large emissions of anthropogenic long-lived chlorine-containing source gases, notably the chlorofluorocarbons. The chemical inertness of chlorofluorocarbons allows their transport and mixing throughout the troposphere on a global scale, before they reach the stratosphere where they release chlorine atoms that cause ozone depletion. The large ozone loss over Antarctica was the key observation that stimulated the definition and signing in 1987 of the Montreal Protocol, an international treaty establishing a schedule to reduce the production of the major chlorine- and bromine-containing halocarbons. Owing to its implementation, the near-surface total chlorine concentration showed a maximum in 1993, followed by a decrease of half a per cent to one per cent per year, in line with expectations. Remote-sensing data have revealed a peak in stratospheric chlorine after 1996, then a decrease of close to one per cent per year, in agreement with the surface observations of the chlorine source gases and model calculations. Here we present ground-based and satellite data that show a recent and significant increase, at the 2σ level, in hydrogen chloride (HCl), the main stratospheric chlorine reservoir, starting around 2007 in the lower stratosphere of the Northern Hemisphere, in contrast with the ongoing monotonic decrease of near-surface source gases. Using model simulations, we attribute this trend anomaly to a slowdown in the Northern Hemisphere atmospheric circulation, occurring over several consecutive years, transporting more aged air to the lower stratosphere, and characterized by a larger relative conversion of source gases to HCl. This short-term dynamical variability will also affect other stratospheric tracers and needs to be accounted for when studying the evolution of the stratospheric ozone layer.

The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument provides the longest continuous dataset of carbon monoxide (CO) from space. We perform the first validation of MOPITT version 6 retrievals using total column CO measurements from ground-based remote-sensing Fourier transform infrared spectrometers (FTSs). Validation uses data recorded at 14 stations, that span a wide range of latitudes (80° N to 78° S), in the Network for the Detection of Atmospheric Composition Change (NDACC). MOPITT measurements are spatially co-located with each station, and different vertical sensitivities between instruments are accounted for by using MOPITT averaging kernels (AKs). All three MOPITT retrieval types are analyzed: thermal infrared (TIR-only), joint thermal and near infrared (TIR–NIR), and near infrared (NIR-only). Generally, MOPITT measurements overestimate CO relative to FTS measurements, but the bias is typically less than 10 %. Mean bias is 2.4 % for TIR-only, 5.1 % for TIR–NIR, and 6.5 % for NIR-only. The TIR–NIR and NIR-only products consistently produce a larger bias and lower correlation than the TIR-only. Validation performance of MOPITT for TIR-only and TIR–NIR retrievals over land or water scenes is equivalent. The four MOPITT detector element pixels are validated separately to account for their different uncertainty characteristics. Pixel 1 produces the highest standard deviation and lowest correlation for all three MOPITT products. However, for TIR-only and TIR–NIR, the error-weighted average that includes all four pixels often provides the best correlation, indicating compensating pixel biases and well-captured error characteristics. We find that MOPITT bias does not depend on latitude but rather is influenced by the proximity to rapidly changing atmospheric CO. MOPITT bias drift has been bound geographically to within ±0.5 % yr−1 or lower at almost all locations.

Changes of atmospheric methane (CH4) since 2005 have been evaluated using Fourier Transform Infrared (FTIR) solar observations performed at ten ground-based sites, all members of the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns that amounts to 0.31 ± 0.03 % year−1 (2-sigma level of uncertainty) for the 2005–2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem Chemical Transport Model tagged simulation that accounts for the contribution of each emission source and one sink in the total methane, simulated over the 2005–2012 time period and based on emissions inventories and transport. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane of 0.35 ± 0.03 % year−1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04 % year−1, averaged over ten stations). Analysis of the GEOS-Chem tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the inter-annual variability of methane. However, anthropogenic emissions such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Based on the GEOS-Chem tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained.

The practical usefulness of a desktop optical spectrum analyzer (OSA) for measuring atmospheric CO2 and CH4 column densities at surface sites was examined in two separate measurement campaigns. The first comparison involved operating the OSA in parallel with a high resolution Fourier transform spectroscopy (FTS) situated at the University of Wollongong in Australia. Scale factors for the OSA were assigned for the column average volume mixing ratios of xCO2 and xCH4 by comparing with the well-studied FTS. The second method is a calibration against aircraft CO2 profiles in situ over Tsukuba in Japan obtained during a GOSAT validation campaign carried out from 28 January to 7 February 2011. The xCO2 values in the campaign, deduced by use of a derived OSA scale factor, were in excellent agreement with the integrated aircraft profiles.

We analyse the carbon monoxide (CO), ethane (C2H6) and hydrogen cyanide (HCN) partial columns (from the ground to 12 km) derived from measurements by ground-based solar Fourier Transform Spectroscopy at Lauder, New Zealand (45° S, 170° E), and at Arrival Heights, Antarctica (78° S, 167° E), from 1997 to 2009. Significant negative trends are calculated for all species at both locations, based on the daily-mean observed time series, namely CO (−0.94 ± 0.47% yr−1), C2H6 (−2.37 ± 1.18% yr−1) and HCN (−0.93 ± 0.47% yr−1) at Lauder and CO (−0.92 ± 0.46% yr−1), C2H6 (−2.82 ± 1.37% yr−1) and HCN (−1.41 ± 0.71% yr−1) at Arrival Heights. The uncertainties reflect the 95% confidence limits. However, the magnitudes of the trends are influenced by the anomaly associated with the 1997–1998 El Niño Southern Oscillation event at the beginning of the time series reported. We calculate trends for each month from 1997 to 2009 and find negative trends for all months. The largest monthly trends of CO and C2H6 at Lauder, and to a lesser degree at Arrival Heights, occur during austral spring during the Southern Hemisphere tropical and subtropical biomass burning period. For HCN, the largest monthly trends occur in July and August at Lauder and around November at Arrival Heights. The correlations between CO and C2H6 and between CO and HCN at Lauder in September to November, when the biomass burning maximizes, are significantly larger that those in other seasons. A tropospheric chemistry-climate model is used to simulate CO, C2H6, and HCN partial columns for the period of 1997–2009, using interannually varying biomass burning emissions from GFED3 and annually periodic but seasonally varying emissions from both biogenic and anthropogenic sources. The model-simulated partial columns of these species compare well with the measured partial columns and the model accurately reproduces seasonal cycles of all three species at both locations. However, while the model satisfactorily captures both the seasonality and trends in HCN, it is not able to reproduce the negative trends in either C2H6 or CO. A further simulation assuming a 35% decline of C2H6 and a 26% decline of CO emissions from the industrial sources from 1997 to 2009 largely captures the observed trends of C2H6 and CO partial columns at both locations. Here we attribute trends in HCN exclusively to changes in biomass burning and thereby isolate the influence of anthropogenic emissions as responsible for the long-term decline in CO and C2H6. This analysis shows that biomass burning emissions are the main factors in controlling the interannual and seasonal variations of these species. We also demonstrate contributions of biomass burning emission from different southern tropical and sub-tropical regions to seasonal and interannual variations of CO at Lauder; it shows that long-range transport of biomass burning emissions from southern Africa and South America have consistently larger year-to-year contributions to the background seasonality of CO at Lauder than those from other regions (e.g. Australia and South-East Asia). However, large interannual anomalies are triggered by variations in biomass burning emissions associated with large-scale El Niño Southern Oscillation and prolonged biomass burning events, e.g. the Australian bush fires.

Time series of total column abundances of hydrogen chloride (HCl), chlorine nitrate (ClONO2), and hydrogen fluoride (HF) were determined from ground-based Fourier transform infrared (FTIR) spectra recorded at 17 sites belonging to the Network for the Detection of Atmospheric Composition Change (NDACC) and located between 80.05° N and 77.82° S. By providing such a near-global overview on ground-based measurements of the two major stratospheric chlorine reservoir species, HCl and ClONO2, the present study is able to confirm the decrease of the atmospheric inorganic chlorine abundance during the last few years. This decrease is expected following the 1987 Montreal Protocol and its amendments and adjustments, where restrictions and a subsequent phase-out of the prominent anthropogenic chlorine source gases (solvents, chlorofluorocarbons) were agreed upon to enable a stabilisation and recovery of the stratospheric ozone layer. The atmospheric fluorine content is expected to be influenced by the Montreal Protocol, too, because most of the banned anthropogenic gases also represent important fluorine sources. But many of the substitutes to the banned gases also contain fluorine so that the HF total column abundance is expected to have continued to increase during the last few years. The measurements are compared with calculations from five different models: the two-dimensional Bremen model, the two chemistry-transport models KASIMA and SLIMCAT, and the two chemistry-climate models EMAC and SOCOL. Thereby, the ability of the models to reproduce the absolute total column amounts, the seasonal cycles, and the temporal evolution found in the FTIR measurements is investigated and inter-compared. This is especially interesting because the models have different architectures. The overall agreement between the measurements and models for the total column abundances and the seasonal cycles is good. Linear trends of HCl, ClONO2, and HF are calculated from both measurement and model time series data, with a focus on the time range 2000–2009. This period is chosen because from most of the measurement sites taking part in this study, data are available during these years. The precision of the trends is estimated with the bootstrap resampling method. The sensitivity of the trend results with respect to the fitting function, the time of year chosen and time series length is investigated, as well as a bias due to the irregular sampling of the measurements. The measurements and model results investigated here agree qualitatively on a decrease of the chlorine species by around 1% yr−1. The models simulate an increase of HF of around 1% yr−1. This also agrees well with most of the measurements, but some of the FTIR series in the Northern Hemisphere show a stabilisation or even a decrease in the last few years. In general, for all three gases, the measured trends vary more strongly with latitude and hemisphere than the modelled trends. Relative to the FTIR measurements, the models tend to underestimate the decreasing chlorine trends and to overestimate the fluorine increase in the Northern Hemisphere. At most sites, the models simulate a stronger decrease of ClONO2 than of HCl. In the FTIR measurements, this difference between the trends of HCl and ClONO2 depends strongly on latitude, especially in the Northern Hemisphere.

This paper presents extensive validation analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. The ACE satellite instruments operate in the mid-infrared and ultraviolet-visible-near-infrared spectral regions using the solar occultation technique. In order to continue the long-standing record of solar occultation measurements from space, a detailed quality assessment is required to evaluate the ACE data and validate their use for scientific purposes. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the mean differences range generally between 0 and +10% with a slight but systematic positive bias (typically +5%). At higher altitudes (45-60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments by up to ~40% (typically +20%). For the ACE-MAESTRO version 1.2 ozone data product, agreement within ±10% (generally better than ±5%) is found between 18 and 40 km for the sunrise and sunset measurements. At higher altitudes (45-55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (by as much as -10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS and indicate a large positive bias (+10 to +30%) in this altitude range. In contrast, there is no significant difference in bias found for the ACE-FTS sunrise and sunset measurements. These systematic effects in the ozone profiles retrieved from the measurements of ACE-FTS and ACE-MAESTRO are being investigated. This work shows that the ACE instruments provide reliable, high quality measurements from the tropopause to the upper stratosphere and can be used with confidence in this vertical domain

The authors report the results of an intercomparison of vertical column amounts of hydrogen chloride (HCl), hydrogen fluoride (HF), nitrous oxide (N2O), nitric acid (HNO3), methane (CH4), ozone (O3), carbon dioxide (CO2), and nitrogen (N2) derived from the spectra recorded by two ground-based Fourier transform infrared (FTIR) spectrometers operated side-by-side using the sun as a source. The procedure used to record spectra and derive vertical column amounts follows the format of previous instrument intercomparisons organized by the Network for the Detection of Atmospheric Composition Change (NDACC), formerly known as the Network for Detection of Stratospheric Change (NDSC). For most gases the differences were typically around 3%, and in about half of the results the error bars given by the standard deviation of the measurements from each instrument did not overlap. The worst level of agreement was for HF where differences of over 5% were typical. The level of agreement achieved during this intercomparison is a little worse than that achieved in previous intercomparisons between ground-based FTIR spectrometers.