Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets

oai:publications.copernicus.org:essd109417Monitoring the atmospheric concentrations of greenhouse gases (GHGs) is crucial to improve our understanding of their climate impact. However, there are no long-term profile data sets of important GHGs that can be used to gain a better insight into the processes controlling their variations in the atmosphere. In this study, we apply corrections to chemical transport model (CTM) output based on profile measurements from two solar occultation instruments: the HALogen Occultation Experiment (HALOE) and the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS). The goal is to construct long-term (1991–2021), gap-free stratospheric profile data sets, hereafter referred to as TCOM, for two important GHGs. To estimate the corrections that need to be applied to the CTM profiles, we use the extreme gradient boosting (XGBoost) regression model. For methane (TCOM-CH4), we utilize both HALOE and ACE satellite profile measurements from 1992 to 2018 to train the XGBoost model, while profiles from 2019 to 2021 serve as an independent evaluation data set. As there are no nitrous oxide (N2O) profile measurements for earlier years, we derive XGBoost-derived correction terms to construct TCOM-N2O profiles using only ACE-FTS profiles from the 2004–2018 time period, with profiles from 2019–2021 used for the independent evaluation. Overall, both TCOM-CH4 and TCOM-N2O profiles exhibit excellent agreement with the available satellite-measurement-based data sets. We find that compared to evaluation profiles, biases in TCOM-CH4 and TCOM-N2O are generally less than 10 % and 50 %, respectively, throughout the stratosphere. The daily zonal mean profile data sets, covering altitude (15–60 km) and pressure (300–0.1 hPa) levels, are publicly available via the following links: https://doi.org/10.5281/zenodo.7293740 for TCOM-CH4 (Dhomse, 2022a) and https://doi.org/10.5281/zenodo.7386001 for TCOM-N2O (Dhomse, 2022b).</p

The increasing threat to stratospheric ozone from dichloromethane.

It is well established that anthropogenic chlorine-containing chemicals contribute to ozone layer depletion. The successful implementation of the Montreal Protocol has led to reductions in the atmospheric concentration of many ozone-depleting gases, such as chlorofluorocarbons. As a consequence, stratospheric chlorine levels are declining and ozone is projected to return to levels observed pre-1980 later this century. However, recent observations show the atmospheric concentration of dichloromethane-an ozone-depleting gas not controlled by the Montreal Protocol-is increasing rapidly. Using atmospheric model simulations, we show that although currently modest, the impact of dichloromethane on ozone has increased markedly in recent years and if these increases continue into the future, the return of Antarctic ozone to pre-1980 levels could be substantially delayed. Sustained growth in dichloromethane would therefore offset some of the gains achieved by the Montreal Protocol, further delaying recovery of Earth's ozone layer

Satellite Observations of Stratospheric Hydrogen Flouride and Comparisons with SLIMCAT Calculations

The vast majority of emissions of fluorine-containing molecules are anthropogenic in nature, e.g. chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), and hydrofluorocarbons (HFCs). Many of these fluorine-containing species deplete stratospheric ozone and are regulated by the Montreal Protocol. Once in the atmosphere they slowly degrade, ultimately leading to the formation of hydrogen fluoride (HF), the dominant reservoir of stratospheric fluorine due to its extreme stability. Monitoring the growth of stratospheric HF is therefore an important marker for the success of the Montreal Protocol. We report the comparison of global distributions and trends of HF measured in the Earth\u27s atmosphere by the satellite remote-sensing instruments ACE-FTS (Atmospheric Chemistry Experiment Fourier transform spectrometer), which has been recording atmospheric spectra since 2004, and HALOE (HALogen Occultation Experiment), which recorded atmospheric spectra between 1991 and 2005, with the output of SLIMCAT, a state-of-the-art three-dimensional chemical transport model. In general the agreement between observation and model is good, although the ACE-FTS measurements are biased high by  ∼  10 % relative to HALOE. The observed global HF trends reveal a substantial slowing down in the rate of increase of HF since the 1990s: 4.97 ± 0.12 % year−1 (1991–1997; HALOE), 1.12 ± 0.08 % year−1 (1998–2005; HALOE), and 0.52 ± 0.03 % year−1 (2004–2012; ACE-FTS). In comparison, SLIMCAT calculates trends of 4.01, 1.10, and 0.48 % year−1, respectively, for the same periods; the agreement is very good for all but the earlier of the two HALOE periods. Furthermore, the observations reveal variations in the HF trends with latitude and altitude; for example, between 2004 and 2012 HF actually decreased in the Southern Hemisphere below  ∼  35 km. An additional SLIMCAT simulation with repeating meteorology for the year 2000 produces much cleaner trends in HF with minimal variations with latitude and altitude. Therefore, the variations with latitude and altitude in the observed HF trends are due to variability in stratospheric dynamics on the timescale of a few years. Overall, the agreement between observation and model points towards the ongoing success of the Montreal Protocol and the usefulness of HF as a metric for stratospheric fluorine

Quantifying effects of long-range transport of NO2 over Delhi using back trajectories and satellite data

© 2024 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Exposure to air pollution is a leading public health risk factor in India, especially over densely populated Delhi and the surrounding Indo-Gangetic Plain. During the post-monsoon seasons, the prevailing north-westerly winds are known to influence aerosol pollution events in Delhi by advecting pollutants from agricultural fires as well as from local sources. Here we investigate the year-round impact of meteorology on gaseous nitrogen oxides (NOxCombining double low lineNO+NO2). We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P aboard TROPOMI, alongside a back-trajectory model (ROTRAJ) to investigate the balance of local and external sources influencing air pollution changes in Delhi, with a focus on different emissions sectors. Our analysis shows that accumulated emissions (i.e. integrated along the trajectory path, allowing for chemical loss) are highest under westerly, north-westerly and northerly flow during pre-monsoon (February-May) and post-monsoon (October-February) seasons. According to this analysis, during the pre-monsoon season, the highest accumulated satellite TCNO2 trajectories come from the east and north-west of Delhi. TCNO2 is elevated within Delhi and the Indo-Gangetic Plain (IGP) to the east of city. The accumulated NOx emission trajectories indicate that the transport and industry sectors together account for more than 80% of the total accumulated emissions, which are dominated by local sources (>70%) under easterly winds and north-westerly winds. The high accumulated emissions estimated during the pre-monsoon season under north-westerly wind directions are likely to be driven by high NOx emissions locally and in nearby regions (since NOx lifetime is reduced and the boundary layer is relatively deeper in this season). During the post-monsoon season the highest accumulated satellite TCNO2 trajectories are advected from Punjab and Haryana, where satellite TCNO2 is elevated, indicating the potential for the long-range transport of agricultural burning emissions to Delhi. However, accumulated NOx emissions indicate local (70%) emissions from the transport sector are the largest contributor to the total accumulated emissions. High local emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary layer, aid the build-up of emissions locally and along the trajectory path. This indicates the possibility that fire emissions datasets may not capture emissions from agricultural waste burning in the north-west sufficiently to accurately quantify their influence on Delhi air quality (AQ). Analysis of daily ground-based NO2 observations indicates that high-pollution episodes (>90th percentile) occur predominantly in the post-monsoon season, and more than 75% of high-pollution events are primarily caused by local sources. But there is also a considerable influence from non-local (30%) emissions from the transport sector during the post-monsoon season. Overall, we find that in the post-monsoon season, there is substantial accumulation of high local NOx emissions from the transport sector (70% of total emissions, 70% local), alongside the import of NOx pollution into Delhi (30% non-local). This work indicates that both high local NOx emissions from the transport sector and the advection of highly polluted air originating from outside Delhi are of concern for the population. As a result, air quality mitigation strategies need to be adopted not only in Delhi but in the surrounding regions to successfully control this issue. In addition, our analysis suggests that the largest benefits to Delhi NOx air quality would be seen with targeted reductions in emissions from the transport and agricultural waste burning sectors, particularly during the post-monsoon season.Peer reviewe

Recent Trends in Stratospheric Chlorine From Very Short‐Lived Substances

Very short‐lived substances (VSLS), including dichloromethane (CH2Cl2), chloroform (CHCl3), perchloroethylene (C2Cl4), and 1,2‐dichloroethane (C2H4Cl2), are a stratospheric chlorine source and therefore contribute to ozone depletion. We quantify stratospheric chlorine trends from these VSLS (VSLCltot) using a chemical transport model and atmospheric measurements, including novel high‐altitude aircraft data from the NASA VIRGAS (2015) and POSIDON (2016) missions. We estimate VSLCltot increased from 69 (±14) parts per trillion (ppt) Cl in 2000 to 111 (±22) ppt Cl in 2017, with \u3e80% delivered to the stratosphere through source gas injection, and the remainder from product gases. The modeled evolution of chlorine source gas injection agrees well with historical aircraft data, which corroborate reported surface CH2Cl2 increases since the mid‐2000s. The relative contribution of VSLS to total stratospheric chlorine increased from ~2% in 2000 to ~3.4% in 2017, reflecting both VSLS growth and decreases in long‐lived halocarbons. We derive a mean VSLCltot growth rate of 3.8 (±0.3) ppt Cl/year between 2004 and 2017, though year‐to‐year growth rates are variable and were small or negative in the period 2015–2017. Whether this is a transient effect, or longer‐term stabilization, requires monitoring. In the upper stratosphere, the modeled rate of HCl decline (2004–2017) is −5.2% per decade with VSLS included, in good agreement to ACE satellite data (−4.8% per decade), and 15% slower than a model simulation without VSLS. Thus, VSLS have offset a portion of stratospheric chlorine reductions since the mid‐2000s

COVID-19 lockdown induced changes in NO2 levels across India observed by multi-satellite and surface observations

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.We have estimated the spatial changes in NO 2levels over different regions of India during the COVID-19 lockdown (25 March-3 May 2020) using the satellite-based tropospheric column NO 2observed by the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), as well as surface NO 2concentrations obtained from the Central Pollution Control Board (CPCB) monitoring network. A substantial reduction in NO 2levels was observed across India during the lockdown compared to the same period during previous business-as-usual years, except for some regions that were influenced by anomalous fires in 2020. The reduction (negative change) over the urban agglomerations was substantial (~20 %-40 %) and directly proportional to the urban size and population density. Rural regions across India also experienced lower NO 2values by ~15 %-25 %. Localised enhancements in NO 2associated with isolated emission increase scattered across India were also detected. Observed percentage changes in satellite and surface observations were consistent across most regions and cities, but the surface observations were subject to larger variability depending on their proximity to the local emission sources. Observations also indicate NO 2enhancements of up to~25%during the lockdown associated with fire emissions over the north-east of India and some parts of the central regions. In addition, the cities located near the large fire emission sources show much smaller NO 2reduction than other urban areas as the decrease at the surface was masked by enhancement in NO 2due to the transport of the fire emissions.Peer reviewedFinal Published versio

Effects of stratosphere-troposphere chemistry coupling on tropospheric ozone

A new, computationally efficient coupled stratosphere-troposphere chemistry-climate model (S/T-CCM) has been developed based on three well-documented components: a 64-level general circulation model from the UK Met Office Unified Model, the tropospheric chemistry transport model (STOCHEM), and the UMSLIMCAT stratospheric chemistry module. This newly developed S/T-CCM has been evaluated with various observations, and it shows good performance in simulating important chemical species and their interdependence in both the troposphere and stratosphere. The modeled total column ozone agrees well with Total Ozone Mapping Spectrometer observations. Modeled ozone profiles in the upper troposphere and lower stratosphere are significantly improved compared to runs with the stratospheric chemistry and tropospheric chemistry models alone, and they are in good agreement with Michelson Interferometer for Passive Atmospheric Sounding satellite ozone profiles. The observed CO tape recorder is also successfully captured by the new CCM, and ozone-CO correlations are in accordance with Atmospheric Chemistry Experiment observations. However, because of limitations in vertical resolution, intrusion of CO-rich air in the stratosphere from the mesosphere could not be simulated in the current version of S/T-CCM. Additionally, the simulated stratosphere-to-troposphere ozone flux, which controls upper tropospheric OH and O3 concentrations, is found to be more realistic in the new coupled model compared to STOCHEM. © 2010 by the American Geophysical Union

Dynamically controlled ozone decline in the tropical mid-stratosphere observed by SCIAMACHY

Despite the recently reported beginning of a recovery in global stratospheric ozone (O3), an unexpected O3 decline in the tropical mid-stratosphere (around 30–35 km altitude) was observed in satellite measurements during the first decade of the 21st century. We use SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) measurements for the period 2004–2012 to confirm the significant O3 decline. The SCIAMACHY observations show that the decrease in O3 is accompanied by an increase in NO2. To reveal the causes of these observed O3 and NO2 changes, we performed simulations with the TOMCAT 3-D chemistry-transport model (CTM) using different chemical and dynamical forcings. For the 2004–2012 time period, the TOMCAT simulations reproduce the SCIAMACHY-observed O3 decrease and NO2 increase in the tropical mid-stratosphere. The simulations suggest that the positive changes in NO2 (around 7 % decade−1) are due to similar positive changes in reactive odd nitrogen (NOy), which are a result of a longer residence time of the source gas N2O and increased production via N2O + O(1D). The model simulations show a negative change of 10 % decade−1 in N2O that is most likely due to variations in the deep branch of the Brewer–Dobson Circulation (BDC). Interestingly, modelled annual mean “age of air” (AoA) does not show any significant changes in transport in the tropical mid-stratosphere during 2004–2012. However, further analysis of model results demonstrates significant seasonal variations. During the autumn months (September–October) there are positive AoA changes that imply transport slowdown and a longer residence time of N2O allowing for more conversion to NOy, which enhances O3 loss. During winter months (January–February) there are negative AoA changes, indicating faster N2O transport and less NOy production. Although the variations in AoA over a year result in a statistically insignificant linear change, non-linearities in the chemistry–transport interactions lead to a statistically significant negative N2O change