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.
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.
Substantial and prolonged enhancements in stratospheric water vapor (SWV) have occurred after large‐magnitude explosive tropical volcanic eruptions, with modified tropopause entry caused by ...aerosol‐absorptive heating. Here, we analyze the timing and longevity of heating‐driven post‐eruption SWV changes within CMIP6‐VolMIP short‐term climate‐response experiments with the UK Earth System Model (UKESM1). We find aerosol‐absorptive heating causes peak SWV increases of 17% (∼1 ppmv) and 10% (0.5 ppmv) at 100 and 50 hPa, at ∼18 and ∼23 months after a Pinatubo‐like eruption, respectively. We track the temperature response in the tropical lower stratosphere and identify the main SWV increase occurs only after the descending aerosol heating reaches the tropopause, suggesting a key role for aerosol microphysical processes (sedimentation rate). We explore how El Niño–Southern Oscillation variability modulates this effect. Post‐eruption SWV increases are ∼80% stronger for the La Nina phase compared to the ensemble mean. Tropical upwelling strongly mediates this effect.
Plain Language Summary
Strong volcanic eruptions, such as the 1991 eruption of Mt Pinatubo, inject a large amount of SO2 directly into the stratosphere, thereby enhancing the stratospheric aerosol layer and causing a short‐term climatic perturbation. Another substantial part of the climatic influence is the change in stratospheric water vapor (SWV), which affects the chemical processes and the radiative budget of the atmosphere. Along with near‐instantaneous injection of water vapor into the stratosphere, volcanic eruptions can indirectly enhance the entry of water vapor into the stratosphere through aerosol‐induced tropopause heating. This work analyses Earth system model experiments designed to explore how volcanic impacts combine with internal climate variability. We find that peak SWV entry mixing ratios occur only within the second post‐eruption year, consistent with the substantially lagged timing of SWV increase seen in post‐Pinatubo satellite measurements. This analysis provides a new perspective on the temporal evolution of the observed post‐Pinatubo SWV increase and an improved quantification of its impacts.
Key Points
Aerosol‐induced absorptive‐heating increases stratospheric water vapor (SWV) by up to 17% at 18 months post‐eruption in a Pinatubo‐like experiment
Analyzing simulations by El Niño–Southern Oscillation (ENSO) variability show an 80% larger peak SWV increase occurs if an eruption is followed by a La Niña phase
The timing of peak SWV increase occurs when volcanic‐aerosol‐induced heating reaches the tropopause, with ENSO modulation of tropical upwelling
We use a three‐dimensional chemical transport model and satellite observations to investigate Arctic ozone depletion in winter/spring 2019/20 and compare with earlier years. Persistently, low ...temperatures caused extensive chlorine activation through to March. March‐mean polar‐cap‐mean modeled chemical column ozone loss reached 78 DU (local maximum loss of ∼108 DU in the vortex), similar to that in 2011. However, weak dynamical replenishment of only 59 DU from December to March was key to producing very low (<220 DU) column ozone values. The only other winter to exhibit such weak transport in the past 20 years was 2010/11, so this process is fundamental to causing such low ozone values. A model simulation with peak observed stratospheric total chlorine and bromine loading (from the mid‐1990s) shows that gradual recovery of the ozone layer over the past 2 decades ameliorated the polar cap ozone depletion in March 2020 by ∼20 DU.
Plain Language Summary
Ozone depletion in the polar stratosphere is caused by chlorine and bromine species which are activated by low temperatures. Chlorine and bromine are transported to the stratosphere following the surface emission of ozone‐depleting substances (ODSs). While springtime ozone depletion in the Antarctic is almost always large, it is much more variable in the Arctic due to warmer temperatures and more disturbed stratospheric dynamics. Using a three‐dimensional atmospheric chemical transport model and satellite observations, we show that the very low ozone columns observed in March 2020 were a consequence of large chemical destruction and weaker‐than‐normal replenishment by transport. These very low ozone levels are, by some measures, record values despite 2 decades of decreasing stratospheric chlorine and bromine through controls of the Montreal Protocol. Had the meteorology of 2019/20 occurred 2 decades ago, the ozone loss would have been notably larger. The Arctic stratospheric dynamics for 2019/20 are extreme relative to the past 2 decades but fit a compact relationship that links column ozone variations over Arctic and Antarctic winters.
Key Points
Large mean Arctic (>63°N) chemical ozone destruction in 2019/20 of 78 DU, similar to other extreme cold winters in the past 2 decades
Anomalously weak wintertime dynamical replenishment of only ∼60 DU contributed strongly to the very low observed ozone column in March
Ozone recovery caused 20 DU less mean Arctic ozone loss in March 2020 than would have occurred with stratospheric halogens at 1995 levels
We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range ...weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, we use the Copernicus Climate Change Service (C3S) data (1979-2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set (1984-2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases ( 15 DU, Dobson units) during winter-spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show that, compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the Southern Hemisphere (SH) mid latitudes, while for A_ERAI in the NH mid latitudes, simulated ozone trends remain negative. Similarly, in the lower stratosphere, B_ERA5 shows positive ozone recovery trends for both NH and SH mid latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid latitudes.
The January 2022 eruption of Hunga Tonga‐Hunga Ha'apai (HTHH) injected a huge amount (∼150 Tg) of water vapor (H2O) into the stratosphere, along with small amount of SO2. An off‐line 3‐D chemical ...transport model (CTM) successfully reproduces the spread of the injected H2O through October 2023 as observed by the Microwave Limb Sounder. Dehydration in the 2023 Antarctic polar vortex caused the first substantial (∼20 Tg) removal of HTHH H2O from the stratosphere. The CTM indicates that this process will dominate removal of HTHH H2O for the coming years, giving an overall e‐folding timescale of 4 years; around 25 Tg of the injected H2O is predicted to still remain in the stratosphere by 2030. Following relatively low Antarctic column ozone in midwinter 2023 due to transport effects, additional springtime depletion due to H2O‐related chemistry was small and maximized at the vortex edge (10 DU in column).
Plain Language Summary
Around 150 Tg (150 million tons) of water vapor was injected into the stratosphere during the eruption of Hunga Tonga‐Hunga Ha'apai. Water vapor is a greenhouse gas and this increase is expected to have a warming effect in the troposphere, as well causing perturbations in stratospheric chemistry and aerosols. We use an atmospheric model to study the residence time of this excess water vapor and its impact on the recent Antarctic ozone hole. The model performance is evaluated by comparison with satellite measurements. Wintertime dehydration in the Antarctic stratosphere in 2023 is found to be an important mechanism for removal of the volcanic water from the stratosphere. However, the overall removal rate is predicted to be slow; around 25 Tg (17%) is still present in 2030. The direct impact of the excess water vapor on ozone via chemical processes in the Antarctic ozone hole in 2023 is small.
Key Points
Antarctic dehydration is a major removal pathway of stratospheric H2O injected from Hunga Tonga‐Hunga Ha'apai (HTHH) eruption
HTHH H2O caused small (up to 10 DU) additional chemical ozone depletion in 2023 Antarctic spring
Model indicates e‐folding timescale of 4 years for removal of HTHH H2O from stratosphere
Accurate quantification of long-term trends in stratospheric ozone can be challenging due to their sensitivity to natural variability, the quality of the observational datasets, and non-linear ...changes in forcing processes as well as the statistical methodologies. Multivariate linear regression (MLR) is the most commonly used tool for ozone trend analysis; however, the complex coupling in many atmospheric processes can make it prone to the issue of over-fitting when using the conventional ordinary-least-squares (OLS) approach. To overcome this issue, here we adopt a regularized (ridge) regression method to estimate ozone trends and quantify the influence of individual processes. We use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) merged dataset (v2.7) to derive stratospheric ozone profile trends for the period 1984-2020. Besides SWOOSH, we also analyse a machine-learning-based satellite-corrected gap-free global stratospheric ozone profile dataset from a chemical transport model (ML-TOMCAT) and output from a chemical transport model (TOMCAT) simulation forced with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis.
We have estimated the spatial changes in NO2 levels over different regions of India during the COVID-19 lockdown (25 March–3 May 2020) using the satellite-based tropospheric column NO2 observed by ...the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), as well as surface NO2 concentrations obtained from the Central Pollution Control Board (CPCB) monitoring network. A substantial reduction in NO2 levels 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 NO2 values by ∼ 15 %–25 %. Localised enhancements in NO2 associated 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 NO2 enhancements 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 NO2 reduction than other urban areas as the decrease at the surface was masked by enhancement in NO2 due to the transport of the fire emissions.
As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive ...stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.
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 (NOx=NO+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.
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