Atmospheric Composition Change Research Articles

Intercomparison and evaluation of ground- and satellite-based stratospheric ozone and temperature profiles above Observatoire de Haute-Provence during the Lidar Validation NDACC Experiment (LAVANDE)

Abstract. A two-part intercomparison campaign was conducted at Observatoire de Haute-Provence (OHP) for the validation of lidar ozone and temperature profiles using the mobile NASA Stratospheric Ozone Lidar (NASA STROZ), satellite overpasses from the Microwave Limb Sounder (MLS), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), meteorological radiosondes launched from Nîmes, and locally launched ozonesondes. All the data were submitted and compared “blind”, before the group could see results from the other instruments. There was good agreement between all ozone measurements between 20 and 40 km, with differences of generally less than 5 % throughout this region. Below 20 km, SABER and MLS measured significantly more ozone than the lidars or ozonesondes. Temperatures for all lidars were in good agreement between 30 and 60 km, with differences on the order of ±1 to 3 K. Below 30 km, the OHP lidar operating at 532 nm has a significant cool bias due to contamination by aerosols. Systematic, altitude-varying bias up to ±5 K compared to the lidars was found for MLS at many altitudes. SABER temperature profiles are generally closer to the lidar profiles, with up 3 K negative bias near 50 km. Total uncertainty estimates for ozone and temperature appear to be realistic for nearly all systems. However, it does seem that the very low estimated uncertainties of lidars between 30 and 50 km, between 0.1 and 1 K, are not achieved during Lidar Validation Network for the Detection of Atmospheric Composition Change (NDACC) Experiment (LAVANDE). These estimates might have to be increased to 1 to 2 K.

Ground-based Fourier transform infrared (FTIR) O<sub>3</sub> retrievals from the 3040 cm<sup>−1</sup> spectral range at Xianghe, China

Abstract. In this study, we present O3 retrievals from ground-based Fourier transform infrared (FTIR) solar absorption measurements between June 2018 and December 2019 at Xianghe, China (39.75∘ N, 116.96∘ E). The FTIR spectrometer at Xianghe is operated with indium gallium arsenide (InGaAs) and indium antimonide (InSb) detectors, recording the spectra between 1800 and 11 000 cm−1. As the harmonized FTIR O3 retrieval strategy (Vigouroux et al., 2015) within the Network for the Detection of Atmospheric Composition Change (NDACC) uses the 1000 cm−1 spectral range, we apply the O3 retrieval in the 3040 cm−1 spectral range at Xianghe. The retrieved O3 profile is mainly sensitive to the vertical range between 10 and 40 km, and the degrees of freedom for signal is 2.4±0.3 (1σ), indicating that there are two individual pieces of information in partial columns between the surface and 20 km and between 20 and 40 km. According to the optimal estimation method, the systematic and random uncertainties of the FTIR O3 total columns are about 13.6 % and 1.4 %, respectively. The random uncertainty is consistent with the observed daily standard deviation of the FTIR retrievals. To validate the FTIR O3 total and partial columns, we apply the same O3 retrieval strategy at Maïdo, Réunion (a.k.a. Reunion Island; 21.08∘ N, 55.38∘ E). The FTIR O3 (3040 cm−1) measurements at Xianghe and Maïdo are then compared with the nearby ozonesondes at Beijing (39.81∘ N, 116.47∘ E) and at Gillot (20.89∘ S, 55.53∘ E), respectively, as well as with co-located TROPOspheric Monitoring Instrument (TROPOMI) satellite measurements at both sites. In addition at Maïdo, we compare the FTIR O3 (3040 cm−1) retrievals with the standard NDACC FTIR O3 measurements using the 1000 cm−1 spectral range. It was found that the total columns retrieved from the FTIR O3 3040 cm−1 measurements are underestimated by 5.5 %–9.0 %, which is mainly due to the systematic uncertainty in the partial column between 20 and 40 km (about −10.4 %). The systematic uncertainty in the partial column between surface and 20 km is relatively small (within 2.4 %). By comparison with other measurements, it was found that the FTIR O3 (3040 cm−1) retrievals capture the seasonal and synoptic variations of the O3 total and two partial columns very well. Therefore, the ongoing FTIR measurements at Xianghe can provide useful information on the O3 variations and (in the future) long-term trends.

A global database of plant production and carbon exchange from global change manipulative experiments

Numerous ecosystem manipulative experiments have been conducted since 1970/80 s to elucidate responses of terrestrial carbon cycling to the changing atmospheric composition (CO2 enrichment and nitrogen deposition) and climate (warming and changing precipitation regimes), which is crucial for model projection and mitigation of future global change effects. Here, we extract data from 2,242 publications that report global change manipulative experiments and build a comprehensive global database with 5,213 pairs of samples for plant production (productivity, biomass, and litter mass) and ecosystem carbon exchange (gross and net ecosystem productivity as well as ecosystem and soil respiration). Information on climate characteristics and vegetation types of experimental sites as well as experimental facilities and manipulation magnitudes subjected to manipulative experiments are also included in this database. This global database can facilitate the estimation of response and sensitivity of key terrestrial carbon-cycling variables under future global change scenarios, and improve the robust projection of global change‒terrestrial carbon feedbacks imposed by Earth System Models.

Changes in ambient air quality and atmospheric composition and reactivity in the South East of the UK as a result of the COVID-19 lockdown

The COVID-19 pandemic forced governments around the world to impose restrictions on daily life to prevent the spread of the virus. This resulted in unprecedented reductions in anthropogenic activity, and reduced emissions of certain air pollutants, namely oxides of nitrogen. The UK ‘lockdown’ was enforced on 23/03/2020, which led to restrictions on movement, social interaction, and ‘non-essential’ businesses and services. This study employed an ensemble of measurement and modelling techniques to investigate changes in air quality, atmospheric composition and boundary layer reactivity in the South East of the UK post-lockdown. The techniques employed included in-situ gas- and particle-phase monitoring within central and local authority air quality monitoring networks, remote sensing by long path Differential Optical Absorption Spectroscopy and Sentinel-5P's TROPOMI, and detailed 0-D chemical box modelling. Findings showed that de-trended NO2 concentrations decreased by an average of 14–38% when compared to the mean of the same period over the preceding 5-years. We found that de-trended particulate matter concentrations had been influenced by interregional pollution episodes, and de-trended ozone concentrations had increased across most sites, by up to 15%, such that total Ox levels were roughly preserved. 0-D chemical box model simulations showed the observed increases in ozone concentrations during lockdown under the hydrocarbon-limited ozone production regime, where total NOx decreased proportionally greater than total non-methane hydrocarbons, which led to an increase in total hydroxyl, peroxy and organic peroxy radicals. These findings suggest a more complex scenario in terms of changes in air quality owing to the COVID-19 lockdown than originally reported and provide a window into the future to illustrate potential outcomes of policy interventions seeking large-scale NOx emissions reductions without due consideration of other reactive trace species.

Heat stored in the Earth system: where does the energy go?

Abstract. Human-induced atmospheric composition changes cause a radiative imbalance at the top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of the Earth system – and particularly how much and where the heat is distributed – is fundamental to understanding how this affects warming ocean, atmosphere and land; rising surface temperature; sea level; and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory and presents an updated assessment of ocean warming estimates as well as new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960–2018. The study obtains a consistent long-term Earth system heat gain over the period 1971–2018, with a total heat gain of 358±37 ZJ, which is equivalent to a global heating rate of 0.47±0.1 W m−2. Over the period 1971–2018 (2010–2018), the majority of heat gain is reported for the global ocean with 89 % (90 %), with 52 % for both periods in the upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 % (5 %) over these periods, 4 % (3 %) is available for the melting of grounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Our results also show that EEI is not only continuing, but also increasing: the EEI amounts to 0.87±0.12 W m−2 during 2010–2018. Stabilization of climate, the goal of the universally agreed United Nations Framework Convention on Climate Change (UNFCCC) in 1992 and the Paris Agreement in 2015, requires that EEI be reduced to approximately zero to achieve Earth's system quasi-equilibrium. The amount of CO2 in the atmosphere would need to be reduced from 410 to 353 ppm to increase heat radiation to space by 0.87 W m−2, bringing Earth back towards energy balance. This simple number, EEI, is the most fundamental metric that the scientific community and public must be aware of as the measure of how well the world is doing in the task of bringing climate change under control, and we call for an implementation of the EEI into the global stocktake based on best available science. Continued quantification and reduced uncertainties in the Earth heat inventory can be best achieved through the maintenance of the current global climate observing system, its extension into areas of gaps in the sampling, and the establishment of an international framework for concerted multidisciplinary research of the Earth heat inventory as presented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOI https://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2 (von Schuckmann et al., 2020).

Solar 11-Year Cycle Signal in Stratospheric Nitrogen Dioxide—Similarities and Discrepancies Between Model and NDACC Observations

NOx (NO2 and NO) plays an important role in controlling stratospheric ozone. Understanding the change in stratospheric NOx and its global pattern is important for predicting future changes in ozone and the corresponding implications on the climate. Stratospheric NOx is mainly produced by the reaction of N2O with the photochemically produced O(1D) and, therefore, it is expected to vary with changes in solar UV irradiance during the solar cycle. Previous studies on this topic, often limited by the relatively short continuous data, show puzzling results. The effect of the 1991 Pinatubo eruption might have caused interference in the data analysis. In this study, we examine the NO2 vertical column density (VCD) data from the Network for the Detection of Atmospheric Composition Change (NDACC). Data collected at 16 stations with continuous long-term observations covering the most recent Solar Cycles 23 and 24 were analyzed. We found positive correlations between changes in NO2 VCD and solar Lyman- $\alpha $ over nine stations (mostly in the Northern Hemisphere) and negative correlations over three stations (mostly in the Southern Hemisphere). The other four stations do not show significant NO2 solar-cycle signal. The varying NO2 responses from one location to another are likely due to different geo-locations (latitude and altitude). In particular, two high-altitude stations show the strongest positive NO2 solar-cycle signals. Our 1D chemical-transport model calculations help explain the altitude dependence of NO2 response to the solar cycle. NO2 solar-cycle variability is suggested to play an important role controlling O3 at an altitude range from $\approx20~\mbox{km}$ to near 60 km, while OH solar-cycle variability controls O3 at 40 – 90 km. While observations show both positive and negative NO2 responses to solar forcing, the 1D model predicts negative NO2 responses to solar UV changes throughout the middle atmosphere. 3D global model results suggest complex roles of dynamics in addition to photochemistry. The energetic particle-induced NO2 variabilities could also contribute significantly to the NO2 variability during solar cycles.

Observed Hemispheric Asymmetry in Stratospheric Transport Trends From 1994 to 2018

AbstractTotal columns of the trace gases nitric acid (HNO3) and hydrogen chloride (HCl) are sensitive to variations in the lower stratospheric age of air, a quantity that describes transport time scales in the stratosphere. Analyses of HNO3 and HCl columns from the Network for the Detection of Atmospheric Composition Change panning 77°S to 79°N have detected changes in the extratropical stratospheric transport circulation from 1994 to 2018. The HNO3 and HCl analyses combined with the age of air from a simulation using the MERRA2 reanalysis show that the Southern Hemisphere lower stratosphere has become 1 month/decade younger relative to the Northern Hemisphere, largely driven by the Southern Hemisphere transport circulation. The analyses reveal multiyear anomalies with a 5‐ to 7‐year period driven by interactions between the circulation and the quasi‐biennial oscillation in tropical winds. This hitherto unrecognized variability is large relative to hemispheric transport trends and may bias ozone trend regressions.

Future greening of the Earth may not be as large as previously predicted

Changes in global vegetation growth and its drivers during recent decades have been well studied with satellite data, ecosystem models and field experiments. However, a systematic understanding of how global vegetation will respond to projected changes in climate and atmospheric composition is still lacking. Here, we analyze changes in projected global leaf area index (LAI) from 16 Coupled Model Intercomparison Project phase 5 (CMIP5) and 17 phase 6 (CMIP6) Earth System Models (ESMs) during the 21st century under future scenarios RCP2.6, RCP4.5 and RCP8.5 and future scenarios SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5, respectively. In addition to the widely-used multi-model ensemble mean (MME) method, we employed the Reliability Ensemble Averaging (REA) strategy to integrate the modeled results. The REA integration weights were determined by combining the performance of the ESMs in simulating present-day LAI changes, which was based on a comparison with three long-term remote sensing LAI data sets, with their convergence of future predictions. The results suggest that global LAI will increase under all seven future scenarios with both integration methods. The magnitude of LAI growth is expected to increase with the forcing levels of the scenarios. The ESMs integrated with the REA weights predicted significantly smaller magnitudes and lower uncertainties in global LAI growth by the end of the 21st century than those integrated with the MME method. Both REA and MME results suggest that the growth in atmospheric CO2 concentration is the main positive driver of the projected increment of global LAI, which is partly offset by the negative effects of global warming. Our improved comprehensive prediction based on CMIP5 and CMIP6 ESMs using the REA integration strategy provides a more robust estimation of global vegetation change during the 21st century, and is expected to help better understand the state of the planet in the coming decades.

Impact of convection on the upper-tropospheric composition (water vapor and ozone) over a subtropical site (Réunion island; 21.1° S, 55.5° E) in the Indian Ocean

Abstract. Observations of ozonesonde measurements of the NDACC/SHADOZ (Network for the Detection of Atmospheric Composition Change and the Southern Hemisphere ADditional OZonesondes) program and humidity profiles from the daily Météo-France radiosondes at Réunion island (21.1∘ S, 55.5∘ E) from November 2013 to April 2016 were analyzed to identify the origin of wet upper-tropospheric air masses with low ozone mixing ratio observed above the island, located in the southwest Indian Ocean (SWIO). A seasonal variability in hydration events in the upper troposphere was found and linked to the convective activity within the SWIO basin. In the upper troposphere, ozone mixing ratios were lower (mean of 57 ppbv) in humid air masses (RH > 50 %) compared to the background mean ozone mixing ratio (73.8 ppbv). A convective signature was identified in the ozone profile dataset by studying the probability of occurrence of different ozone thresholds. It was found that ozone mixing ratios lower than 45 to 50 ppbv had a local maximum of occurrence between 10 and 13 km in altitude, indicative of the mean level of convective outflow. Combining FLEXPART Lagrangian back trajectories with METEOSAT-7 infrared brightness temperature products, we established the origin of convective influence on the upper troposphere above Réunion island. It has been found that the upper troposphere above Réunion island is impacted by convective outflows in austral summer. Most of the time, deep convection is not observed in the direct vicinity of the island, but it is observed more than 1000 km away from the island, in the tropics, either from tropical storms or the Intertropical Convection Zone (ITCZ). In November and December, the air masses above Réunion island originate, on average, from central Africa and the Mozambique Channel. During January and February the source region is the northeast of Mozambique and Madagascar. Those results improve our understanding of the impact of the ITCZ and tropical cyclones on the hydration of the upper troposphere in the subtropics in the SWIO.

TROPOMI–Sentinel-5 Precursor formaldehyde validation using an extensive network of ground-based Fourier-transform infrared stations

Abstract. 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.

Validation of Aura-OMI QA4ECV NO<sub>2</sub> climate data records with ground-based DOAS networks: the role of measurement and comparison uncertainties

Abstract. The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.

Continental records of organic carbon isotopic composition (δ13Corg), weathering, paleoclimate and wildfire linked to the End-Permian Mass Extinction

The late Permian was the acme of Pangea assembly, with collision and subduction of global plates accompanied by major changes in atmospheric composition, paleoclimates and paleoenvironments of the Earth's surface system. These events are extensively recorded in marine successions from the Tethys, but much less are known from continental successions that typically lack high-resolution stratigraphic control. In order to reveal these fluctuations in terrestrial strata and their relationship with the End-Permian Mass Extinction (EPME), we investigate continental δ13Corg, mercury and nickel concentrations, wildfire, and climate change proxies from the late Permian Changhsingian stage to Early Triassic Induan stage in the Yuzhou coalfield in the North China Plate (NCP). Results show two negative organic carbon isotope excursions (CIE) within the Changhsingian aged Sunjiagou Formation, the first (CIEI, 2.2‰) during mid-Changhsingian and a second, larger, excursion (CIE-II, 2.7‰) near the end of the Changhsingian that coincides with the peaks in the Chemical Index of Alteration (CIA) value and extinction of plant species. We infer CIE-II to be the global negative excursion of δ13Corg associated with the EPME. Arid climates prevailed in the study area from the Changhsingian to the early Induan inferred from the low kaolinite contents and weak continental weathering, except for two short-duration episodes with higher humidity that correspond with CIE-I and CIE-II. Extremely high fusinite content (x̄ = 63.1%) and its increasing abundance through the Changhsingian indicates that frequent wildfires may have been a direct cause for both the destruction of terrestrial vegetation ecosystems and the rapid decline of terrestrial biodiversity at the EPME. We consider that terrestrial ecosystems may have played an important role in the extinction of marine communities at the EPME. This represents the first time the EMPE has been demonstrated in the NCP based on combined evidence from negative carbon isotope excursion, concurrent weathering trends, Ni/Al ratio and biotic extinctions, representing an important step in accurately identifying and correlating the EPME in continental settings from the NCP.

Long-term (1999–2019) variability of stratospheric aerosol over Mauna Loa, Hawaii, as seen by two co-located lidars and satellite measurements

Abstract. As part of the Network for the Detection of Atmospheric Composition Change (NDACC), ground-based measurements obtained from the Jet Propulsion Laboratory (JPL) stratospheric ozone lidar and the NOAA stratospheric aerosol lidar at Mauna Loa, Hawaii, over the past 2 decades were used to investigate the impact of volcanic eruptions and pyrocumulonimbus (PyroCb) smoke plumes on the stratospheric aerosol load above Hawaii since 1999. Measurements at 355 and 532 nm conducted by these two lidars revealed a color ratio of 0.5 for background aerosols and small volcanic plumes and 0.8 for a PyroCb plume recorded on September 2017. Measurements of the Nabro plume by the JPL lidar in 2011–2012 showed a lidar ratio of (64±12.7) sr at 355 nm around the center of the plume. The new Global Space-based Stratospheric Aerosol Climatology (GloSSAC), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Level 3 and Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III-ISS) stratospheric aerosol datasets were compared to the ground-based lidar datasets. The intercomparison revealed a generally good agreement, with vertical profiles of extinction coefficient within 50 % discrepancy between 17 and 23 km above sea level (a.s.l.) and 25 % above 23 km a.s.l. The stratospheric aerosol depth derived from all of these datasets shows good agreement, with the largest discrepancy (20 %) being observed between the new CALIOP Level 3 and the other datasets. All datasets consistently reveal a relatively quiescent period between 1999 and 2006, followed by an active period of multiple eruptions (e.g., Nabro) until early 2012. Another quiescent period, with slightly higher aerosol background, lasted until mid-2017, when a combination of extensive wildfires and multiple volcanic eruptions caused a significant increase in stratospheric aerosol loading. This loading maximized at the very end of the time period considered (fall 2019) as a result of the Raikoke eruption, the plume of which ascended to 26 km altitude in less than 3 months.

The Great Oxidation Event preceded a Paleoproterozoic “snowball Earth”

The inability to resolve the exact temporal relationship between two pivotal events in Earth history, the Paleoproterozoic Great Oxidation Event (GOE) and the first "snowball Earth" global glaciation, has precluded assessing causality between changing atmospheric composition and ancient climate change. Here we present temporally resolved quadruple sulfur isotope measurements (δ34S, ∆33S, and ∆36S) from the Paleoproterozoic Seidorechka and Polisarka Sedimentary Formations on the Fennoscandian Shield, northwest Russia, that address this issue. Sulfides in the former preserve evidence of mass-independent fractionation of sulfur isotopes (S-MIF) falling within uncertainty of the Archean reference array with a ∆36S/∆33S slope of -1.8 and have small negative ∆33S values, whereas in the latter mass-dependent fractionation of sulfur isotopes (S-MDF) is evident, with a ∆36S/∆33S slope of -8.8. These trends, combined with geochronological constraints, place the S-MIF/S-MDF transition, the key indicator of the GOE, between 2,501.5 ± 1.7 Ma and 2,434 ± 6.6 Ma. These are the tightest temporal and stratigraphic constraints yet for the S-MIF/S-MDF transition and show that its timing in Fennoscandia is consistent with the S-MIF/S-MDF transition in North America and South Africa. Further, the glacigenic part of the Polisarka Formation occurs 60 m above the sedimentary succession containing S-MDF signals. Hence, our findings confirm unambiguously that the S-MIF/S-MDF transition preceded the Paleoproterozoic snowball Earth. Resolution of this temporal relationship constrains cause-and-effect drivers of Earth's oxygenation, specifically ruling out conceptual models in which global glaciation precedes or causes the evolution of oxygenic photosynthesis.

Evaluation of anthropogenic air pollutant emission inventories for South America at national and city scale

The changing composition of the atmosphere, driven by anthropogenic emissions, is the cause of anthropogenic climate change as well as deteriorating air quality. Emission inventories are essential to understand the contribution of various human activities, model and predict the changing atmospheric composition, and design cost-effective mitigation measures. At present, national emission inventories in South America (SA) focus on Greenhouse Gases (GHG) as part of their obligation to the United Nations Framework Convention for Climate Change (UNFCC) within the framework of their national communications. Emission inventories other than GHG in SA focus mainly on growing urban areas and megacities. Therefore, studies examining air quality at national, regional or continental scales in SA depend on (down-scaled) global emission inventories. This paper examines the emission estimates of air pollutants from various global inventories for five SA countries, namely Argentina, Brazil, Chile, Colombia and Peru. A more detailed analysis is conducted for the EDGAR and ECLIPSE emission inventories, in particular comparing local city-scale inventories of a major city in each country. Although total emissions between down-scaled global inventories and local city inventories are often comparable, large discrepancies exist between the sectoral contributions. This is critical, as the mitigation of poor air quality will depend on addressing the right sources. Potential sources of discrepancies between global and local inventories include the spatial distribution proxies, difference in emission factors used and/or the use of generic statistical country data when estimating emissions. This highlights the importance of using local information when generating national emission inventories, especially for air quality modeling and development of effective mitigation measures. This study represents the first step towards an increased understanding of the strengths and weaknesses of emissions information in SA.

Systems approach to the study of microbial methanogenesis in West-Siberian wetlands

This work is a lecture adapted to the format of a journal article on the course "Modern Topics in Biology", delivered by one of the authors in Yugra State University.
 The modern stage of the development of science and biology, in particular, is characterized by a systematic approach to the evaluation of various phenomena. In the concept of hierarchical holism, which dominates the systems approach, various biological systems form a hierarchical structure in which an element of one system is an independent system of a lower level. In any individual system, the key points are the interaction of its components and the structure that determines the stability of the system. The microbial systems of wetlands in West Siberia play a crucial ecological role in the context of the problem of greenhouse gases and changes in climate and atmospheric composition. The greenhouse gas methane entering the atmosphere is formed by the methanogenic microbial community, which is a complex biological system containing microbial groups which are closely related to each other by trophic interactions. The result of the work and the efficiency of the methanogenic microbial community is also determined by various physicochemical parameters of the environment. The main microbial agents responsible for the production of CH4 are methanogenic archaea, which are divided into three main trophic groups. The application of a systematic approach to the study of the methane cycle in wetlands of West Siberia allows us to comprehensively evaluate the vertical and horizontal system relationships, identify key elements and conduct a complex analysis of the problem under study.

Deriving Temporal and Vertical Distributions of Methane in Xianghe Using Ground-based Fourier Transform Infrared and Gas-analyzer Measurements

Methane (CH4) is one of the most important greenhouse gases in the atmosphere, making it worthwhile to study its temporal and vertical distributions in source areas, e.g., North China. For this purpose, a ground-based high-resolution Fourier transform infrared spectrometer (FTIR), the Bruker IFS 125HR, along with an in-situ instrument, the Picarro G2301, were deployed in Xianghe County (39.8°N,117.0°E), Hebei Province, China. Data have been recorded since June 2018. For the FTIR measurements, we used two observation modes to retrieve the mole fraction of CH4: the Total Carbon Column Observing Network (TCCON) method (retrieval algorithm: GGG2014), and the Network for the Detection of Atmospheric Composition Change (NDACC) method (retrieval algorithm: SFIT4). Combining FTIR with in-situ measurements, we found the temporal and vertical distributions of atmospheric CH4 within three vertical layers (near the ground, in the troposphere, and in the stratosphere), and throughout the whole atmosphere. Regarding the diurnal variation of CH4 near the ground, the concentration at night was higher than during the daytime. Regarding the seasonal variation, CH4 was low in spring and high in summer, for all three vertical layers. In addition, there was a peak of CH4 in winter near the ground, both in the troposphere and the whole atmosphere. We found that variation of CH4 in the tropospheric column was close to that of the in-situ measurements near the ground. Furthermore, the variations of CH4 in the stratospheric column could be influenced by vertical motions, since it was higher in summer and lower in winter.

Fourier transform infrared time series of tropospheric HCN in eastern China: seasonality, interannual variability, and source attribution

Abstract. We analyzed seasonality and interannual variability of tropospheric hydrogen cyanide (HCN) columns in densely populated eastern China for the first time. The results were derived from solar absorption spectra recorded with a ground-based high-spectral-resolution Fourier transform infrared (FTIR) spectrometer in Hefei (31∘54′ N, 117∘10′ E) between 2015 and 2018. The tropospheric HCN columns over Hefei, China, showed significant seasonal variations with three monthly mean peaks throughout the year. The magnitude of the tropospheric HCN column peaked in May, September, and December. The tropospheric HCN column reached a maximum monthly mean of (9.8±0.78)×1015 molecules cm−2 in May and a minimum monthly mean of (7.16±0.75)×1015 molecules cm−2 in November. In most cases, the tropospheric HCN columns in Hefei (32∘ N) are higher than the FTIR observations in Ny-Ålesund (79∘ N), Kiruna (68∘ N), Bremen (53∘ N), Jungfraujoch (47∘ N), Toronto (44∘ N), Rikubetsu (43∘ N), Izana (28∘ N), Mauna Loa (20∘ N), La Reunion Maido (21∘ S), Lauder (45∘ S), and Arrival Heights (78∘ S) that are affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Enhancements of tropospheric HCN column were observed between September 2015 and July 2016 compared to the same period of measurements in other years. The magnitude of the enhancement ranges from 5 % to 46 % with an average of 22 %. Enhancement of tropospheric HCN (ΔHCN) is correlated with the concurrent enhancement of tropospheric CO (ΔCO), indicating that enhancements of tropospheric CO and HCN were due to the same sources. The GEOS-Chem tagged CO simulation, the global fire maps, and the potential source contribution function (PSCF) values calculated using back trajectories revealed that the seasonal maxima in May are largely due to the influence of biomass burning in Southeast Asia (SEAS) (41±13.1 %), Europe and boreal Asia (EUBA) (21±9.3 %), and Africa (AF) (22±4.7 %). The seasonal maxima in September are largely due to the influence of biomass burnings in EUBA (38±11.3 %), AF (26±6.7 %), SEAS (14±3.3 %), and North America (NA) (13.8±8.4 %). For the seasonal maxima in December, dominant contributions are from AF (36±7.1 %), EUBA (21±5.2 %), and NA (18.7±5.2 %). The tropospheric HCN enhancement between September 2015 and July 2016 at Hefei (32∘ N) was attributed to an elevated influence of biomass burnings in SEAS, EUBA, and Oceania (OCE) in this period. In particular, an elevated number of fires in OCE in the second half of 2015 dominated the tropospheric HCN enhancement between September and December 2015. An elevated number of fires in SEAS in the first half of 2016 dominated the tropospheric HCN enhancement between January and July 2016.

Intercomparison of NO<sub>2</sub>, O<sub>4</sub>, O<sub>3</sub> and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Abstract. In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Global sensitivity analysis of chemistry–climate model budgets of tropospheric ozone and OH: exploring model diversity

Abstract. Projections of future atmospheric composition change and its impacts on air quality and climate depend heavily on chemistry–climate models that allow us to investigate the effects of changing emissions and meteorology. These models are imperfect as they rely on our understanding of the chemical, physical and dynamical processes governing atmospheric composition, on the approximations needed to represent these numerically, and on the limitations of the observations required to constrain them. Model intercomparison studies show substantial diversity in results that reflect underlying uncertainties, but little progress has been made in explaining the causes of this or in identifying the weaknesses in process understanding or representation that could lead to improved models and to better scientific understanding. Global sensitivity analysis provides a valuable method of identifying and quantifying the main causes of diversity in current models. For the first time, we apply Gaussian process emulation with three independent global chemistry-transport models to quantify the sensitivity of ozone and hydroxyl radicals (OH) to important climate-relevant variables, poorly characterised processes and uncertain emissions. We show a clear sensitivity of tropospheric ozone to atmospheric humidity and precursor emissions which is similar for the models, but find large differences between models for methane lifetime, highlighting substantial differences in the sensitivity of OH to primary and secondary production. This approach allows us to identify key areas where model improvements are required while providing valuable new insight into the processes driving tropospheric composition change.