Search

Long-range transport (LRT) of air pollutants from a range of sources can substantially enhance background pollution levels, especially in urbanized regions, which can exacerbate high-pollution episodes. In the Aburrá Valley (AV), Colombia, and other cities in northern South America, biomass burning (BB), dust, and volcanic degassing have been identified as sources of long-range aerosol transport. However, the impact of these sources on air quality and the characterization of these sources have yet to be thoroughly studied. This work investigates the influence of these sources on the chemical composition of PM 2.5 during annual and intra-annual high-load aerosol events in the AV. We identified, tracked, and meteorologically characterized LRT events and evaluated their influence on PM 2.5 concentration and chemical composition. We found that the LRT of aerosols from BB, dust, and volcanic degassing influenced approximately 13 %, 8 %, and 13 % of days in the year, respectively. We applied the positive-matrix-factorization (PMF) statistical model to quantify PM 2.5 concentrations and chemical compositions for the different LRT event types (e.g., BB). For BB events, we identified large contributions from organic carbon (OC1 and OC2), F- , and secondary aerosol tracers (SO42- and NO3-). For dust LRT events, crustal mineral components, along with Ti and Ca, were the primary contributors to aerosol composition, while SO42- , Na, Al, and Ca were the primary contributors during volcanic events. The concentrations of some ions and toxic heavy metals (Cr, Mn, Cd, and Ni) were also elevated during BB and volcanic-degassing events. BB contributed the most to PM 2.5 levels during the LRT events (∼11 µgm-3), while contributions from aerosols arising from dust and volcanic events were also substantial (<7 µgm-3). Our study identifies the Orinoco and the Middle Magdalena Valley as sizable sources of BB aerosols and Nevado del Ruiz as a source of volcanic aerosols. Additionally, we found that African dust reached the Andean region via the Caribbean route. As a result, we identify the need for future chemical-transport modeling studies in the region and new support strategies to manage internal and external pollution sources that degrade air quality in the AV and the surrounding region. [ABSTRACT FROM AUTHOR]

Land surface changes can have substantial impacts on biosphere–atmosphere interactions. In South America, rainforests abundantly emit biogenic volatile organic compounds (BVOCs), which, when coupled with pyrogenic emissions from deforestation fires, can have substantial impacts on regional air quality. We use novel and long-term satellite records of five trace gases, namely isoprene (C 5 H 8), formaldehyde (HCHO), methanol (CH 3 OH), carbon monoxide (CO), and nitrogen dioxide (NO 2), in addition to aerosol optical depth (AOD), vegetation (land cover and leaf area index), and burned area. We characterise the impacts of biogenic and pyrogenic emissions on atmospheric composition for the period 2001 to 2019 in the southern Amazon, a region of substantial deforestation. The seasonal cycle for all of the atmospheric constituents peaks in the dry season (August–October), and the year-to-year variability in CO, HCHO, NO 2 , and AOD is strongly linked to the burned area. We find a robust relationship between the broadleaf forest cover and total column C 5 H 8 (R2 = 0.59), while the burned area exhibits an approximate fifth root power law relationship with tropospheric column NO 2 (R2 = 0.32) in the dry season. Vegetation and burned area together show a relationship with HCHO (R2 = 0.23). Wet-season AOD and CO follow the forest cover distribution. The land surface variables are very weakly correlated with CH 3 OH, suggesting that other factors drive its spatial distribution. Overall, we provide a detailed observational quantification of biospheric process influences on southern Amazon regional atmospheric composition, which in future studies can be used to help constrain the underpinning processes in Earth system models. [ABSTRACT FROM AUTHOR]

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies investigating long-term trends in the tropospheric column ozone (TCO 3) have shown large-scale spatio-temporal inconsistencies. Here, we investigate the long-term trends in lower-tropospheric column ozone (LTCO 3 , surface–450 hPa sub-column) by exploiting a synergy of satellite and ozonesonde data sets and an Earth system model (UK's Earth System Model, UKESM) over North America, Europe, and East Asia for the decade 2008–2017. Overall, we typically find small LTCO 3 linear trends with large uncertainty ranges using the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), while model simulations indicate a stable LTCO 3 tendency. The satellite a priori data sets show negligible trends, indicating that any year-to-year changes in the spatio-temporal sampling of these satellite data sets over the period concerned have not artificially influenced their LTCO 3 temporal evolution. The application of the satellite averaging kernels (AKs) to the UKESM simulated ozone profiles, accounting for the satellite vertical sensitivity and allowing for like-for-like comparisons, has a limited impact on the modelled LTCO 3 tendency in most cases. While, in relative terms, this is more substantial (e.g. on the order of 100 %), the absolute magnitudes of the model trends show negligible change. However, as the model has a near-zero tendency, artificial trends were imposed on the model time series (i.e. LTCO 3 values rearranged from smallest to largest) to test the influence of the AKs, but simulated LTCO 3 trends remained small. Therefore, the LTCO 3 tendencies between 2008 and 2017 in northern-hemispheric regions are likely to be small, with large uncertainties, and it is difficult to detect any small underlying linear trends due to interannual variability or other factors which require further investigation (e.g. the radiative transfer scheme (RTS) used and/or the inputs (e.g. meteorological fields) used in the RTS). [ABSTRACT FROM AUTHOR]

Assessing long-range transport (LRT) of pollutants recognizes that multiple sources of varying scale and location can impact air quality. In the Aburrá Valley, Colombia, and other cities in Northern South America, biomass burning (BB), dust, and volcanic degassing have been identified as sources of LRT of aerosols. However, the impact of these sources on air quality and their characterization have yet to be thoroughly studied. This work investigates the influence of these sources on the chemical composition of PM2.5 during annual and intra-annual high-load aerosol events. We identified, tracked, and meteorologically characterized LRT events and evaluated their influence on PM2.5 concentration and chemical composition. We ran a Positive Matrix Factorization (PMF) for each kind of event, identifying high contribution in organic carbon (OC1, OC2), F- and secondary aerosols trace SO2-4 and NO- for the BB events, crustal mineral along with Ti and Ca contribution for dust events and SO2-4, Na, Al and Ca for volcanic events. The increasing concentration of some ions and toxic heavy metals (Cr, Mn, Cd, and Ni) were also related to BB and volcanic degassing influence. During these LRT events, the BB fraction of PM2.5 dominates by frequency and amount, averaging 11.14 µg/m³ (38%). On average, dust and volcanic degassing contribute 6.77 µg/m³ (34%) and 6.46 µg/m³ (30%) of the concentrations. Of the three, dust events showed fewer affected days. The study highlighted hotspot zones such as the Orinoco and Middle Magdalena Valley for BB aerosols, the Caribbean for dust, and the Nevado del Ruíz volcano for volcanic aerosols. This study gives insights for future chemical transport modeling studies in the region and supports strategies to manage internal and external pollution sources and effects for the Aburrá Valley and the region. [ABSTRACT FROM AUTHOR]

Using state-of-the-art satellite ozone profile products, and a chemical transport model, we provide an updated estimate of the tropospheric ozone radiative effect (TO 3 RE) and observational constraint on its variability over the decade 2008–2017. Previous studies have shown the short-term (i.e. a few years) globally weighted average TO 3 RE to be 1.17 ± 0.03 W m -2. However, from our analysis, using decadal (2008–2017) ozone profile datasets from the Infrared Atmospheric Sounding Interferometer, average TO 3 RE ranges between 1.21 and 1.26 W m -2. Over this decade, the modelled and observational TO 3 RE linear trends show a negligible change (e.g. ± 0.1 % yr -1). Two model sensitivity experiments fixing emissions and meteorology to 1 year (i.e. start year – 2008) show that temporal changes in ozone precursor emissions (increasing contribution) and meteorological factors (decreasing contribution) have counteracting tendencies, leading to a negligible globally weighted average TO 3 RE trend. [ABSTRACT FROM AUTHOR]

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 (TCNO 2) 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 TCNO 2 trajectories come from the east and north-west of Delhi. TCNO 2 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 TCNO 2 trajectories are advected from Punjab and Haryana, where satellite TCNO 2 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 (>90 th 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. [ABSTRACT FROM AUTHOR]

Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies investigating long-term trends in tropospheric column ozone (TCO3) have shown large-scale spatiotemporal inconsistencies. Here, we investigate the long-term trends in lower tropospheric column ozone (LTCO3, surface-450 hPa sub-column) by exploiting a synergy of satellite and ozonesonde datasets and an Earth System Model (UKESM) over North America, Europe and East Asia for the decade 2008-2017. Overall, we typically find small LTCO3 linear trends with large uncertainty ranges from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), while model simulations indicate a stable LTCO3 tendency. Trends in the satellite a priori datasets show negligible trends indicating year-to-year sampling is not an issue. The application of the satellite averaging kernels AKs) to the UKESM ozone profiles, accounting for the satellite vertical sensitivity and allowing for like-for41 like comparisons, has a limited impact on the modelled LTCO3 tendency in most cases. While, in relative terms, this is more substantial (e.g. in the order of 100%), the absolute magnitudes of the model trends show negligible change. However, as the model has a near-zero tendency, artificial trends were imposed on the model time-series (i.e. LTCO3 values rearranged from smallest to largest) to test the influence of the AKs but simulated LTCO3 trends remained small. Therefore, the LTCO3 tendency between 2008 and 2017 in northern hemispheric regions are likely small, with large uncertainties, and it is difficult to detect any small underlying linear trends due to inter-annual variability or other factors which require further investigation. [ABSTRACT FROM AUTHOR]

In the summer of 2018, Europe experienced an intense heatwave which coincided with several persistent large-scale ozone (O3) pollution episodes. Novel satellite data of lower-tropospheric column O3 from the Global Ozone Monitoring Experiment-2 (GOME-2) and Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite showed substantial enhancements in 2018 relative to other years since 2012. Surface observations also showed ozone enhancements across large regions of continental Europe in summer 2018 compared to 2017. Enhancements to surface temperature and the O3 precursor gases carbon monoxide and methanol in 2018 were co-retrieved from MetOp observations by the same scheme. This analysis was supported by the TOMCAT chemistry transport model (CTM) to investigate processes driving the observed O3 enhancements. Through several targeted sensitivity experiments we show that meteorological processes, and emissions to a secondary order, were important for controlling the elevated O3 concentrations at the surface. However, mid-tropospheric (∼ 500 hPa) O3 enhancements were dominated by meteorological processes. We find that contributions from stratospheric O3 intrusions ranged between 15 %–40 %. Analysis of back trajectories indicates that the import of O3 -enriched air masses into Europe originated over the North Atlantic, substantially increasing O3 in the 500 hPa layer during summer 2018. [ABSTRACT FROM AUTHOR]

Using state-of-the-art satellite ozone profile products, and chemical transport model, we provide an updated estimate of the tropospheric ozone radiative effect (TO3RE) and observational constraint on its variability over the decade 2008–2017. Previous studies have shown the short-term (i.e. a few years) globally weighted average TO3RE to be 1.17±0.03 W/m², while our analysis suggests that the long-term (2008–2017) average TO3RE to be 1.21–1.28 W/m². Over this decade, the modelled/observational TO3RE linear trends show negligible change (i.e. ±0.1 %/year), so the tropospheric ozone radiative contribution to climate has remained stable with time. Two model sensitivity experiments fixing emissions and meteorology to one year (i.e. start year – 2008) show that ozone precursor emissions (meteorological factors) have had limited (substantial) impacts on the long-term tendency of globally weighted average TO3RE. Here, the meteorological variability in the tropical/sub-tropical upper troposphere is dampening any tendency in TO3RE from other factors (e.g. emissions, atmospheric chemistry). [ABSTRACT FROM AUTHOR]

Carbonyl sulfide (OCS) has emerged as a valuable proxy for photosynthetic uptake of carbon dioxide (CO 2) and is known to be important in the formation of aerosols in the stratosphere. However, uncertainties in the global OCS budget remain large. This is mainly due to the following three flux terms: vegetation uptake, soil uptake and oceanic emissions. Bottom-up estimates do not yield a closed budget, which is thought to be due to tropical emissions of OCS that are not accounted for. Here we present a simulation of atmospheric OCS over the period 2004–2018 using the TOMCAT 3-D chemical transport model that is aimed at better constraining some terms in the OCS budget. Vegetative uptake of OCS is estimated by scaling gross primary productivity (GPP) output from the Joint UK Land Environment Simulator (JULES) using the leaf relative uptake (LRU) approach. The remaining surface budget terms are taken from available literature flux inventories and adequately scaled to bring the budget into balance. The model is compared with limb-sounding satellite observations made by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) and surface flask measurements from 14 National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ESRL) sites worldwide. We find that calculating vegetative uptake using the LRU underestimates the surface seasonal cycle amplitude (SCA) in the Northern Hemisphere (NH) mid-latitudes and high latitudes by approximately 37 ppt (35 %). The inclusion of a large tropical source is able to balance the global budget, but further improvement to the SCA and phasing would likely require a flux inversion scheme. Compared to co-located ACE-FTS OCS profiles between 5 and 30 km, TOMCAT remains within 25 ppt (approximately 5 % of mean tropospheric concentration) of the measurements throughout the majority of this region and lies within the standard deviation of these measurements. This provides confidence in the representation of atmospheric loss and surface fluxes of OCS in the model. Atmospheric sinks account for 154 Gg S of the annual budget, which is 10 %–50 % larger than previous studies. Comparing the surface monthly anomalies from the NOAA-ESRL flask data to the model simulations shows a root-mean-square error range of 3.3–25.8 ppt. We estimate the total biosphere uptake to be 951 Gg S, which is in the range of recent inversion studies (893–1053 Gg S), but our terrestrial vegetation flux accounts for 629 Gg S of the annual budget, which is lower than other recent studies (657–756 Gg S). However, to close the budget, we compensate for this with a large annual oceanic emission term of 689 Gg S focused over the tropics, which is much larger than bottom-up estimates (285 Gg S). Hence, we agree with recent findings that missing OCS sources likely originate from the tropical region. This work shows that satellite OCS profiles offer a good constraint on atmospheric sinks of OCS through the troposphere and stratosphere and are therefore useful for helping to improve surface budget terms. This work also shows that the LRU approach is an adequate representation of the OCS vegetative uptake, but this method could be improved by various means, such as using a higher-resolution GPP product or plant-functional-type-dependent LRU. Future work will utilise TOMCAT in a formal inversion scheme to better quantify the OCS budget. [ABSTRACT FROM AUTHOR]

Hydrogen cyanide (HCN) is an important tracer of biomass burning, but there are significant uncertainties in its atmospheric budget, especially its photochemical and ocean sinks. Here we use a tracer version of the TOMCAT global 3-D chemical transport model to investigate the physical and chemical processes driving the abundance of HCN in the troposphere and stratosphere over the period 2004–2016. The modelled HCN distribution is compared with version 4.1 of the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) HCN satellite data, which provide profiles up to around 42 km, and with ground-based column measurements from the Network for the Detection of Atmospheric Composition Change (NDACC). The long-term ACE-FTS measurements reveal the strong enhancements in upper-tropospheric HCN due to large wildfire events in Indonesia in 2006 and 2015. Our 3-D model simulations confirm previous lower-altitude balloon comparisons that the currently recommended NASA Jet Propulsion Laboratory (JPL) reaction rate coefficient of HCN with OH greatly overestimates the HCN loss. The use of the rate coefficient proposed by in combination with the HCN oxidation by O(1 D) gives good agreement between ACE-FTS observations and the model. Furthermore, the model photochemical loss terms show that the reduction in the HCN mixing ratio with height in the middle stratosphere is mainly driven by the O(1 D) sink with only a small contribution from a reaction with OH. From comparisons of the model tracers with ground-based HCN observations we test the magnitude of the ocean sink in two different published schemes. We find that in our 3-D model the two schemes produce HCN abundances which are very different to the NDACC observations but in different directions. A model HCN tracer using the scheme overestimates the HCN concentration by almost a factor of 2, while a HCN tracer using the scheme underestimates the observations by about one-third. To obtain good agreement between the model and observations, we need to scale the magnitudes of the global ocean sinks by factors of 0.25 and 2 for the schemes of and , respectively. This work shows that the atmospheric photochemical sinks of HCN now appear well constrained but improvements are needed in parameterizing the major ocean uptake sink. [ABSTRACT FROM AUTHOR]

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 months, the prevailing northwesterly 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), a hazardous primary air pollutant for health, which can lead to the formation of secondary aerosols and ozone. We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P on-board 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 emission 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- (February - March) and post- (October - January) monsoon periods. During the premonsoon period, the residential and transport sectors together account for more than 50% of the total accumulated emissions, which are dominated by local sources (90%) under easterly winds and by non35 local sources (>70%) under 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 period). During the post-monsoon period non-local (60%) transport emissions are the largest contributor to the total accumulated emissions as high emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary-layer aid the build-up of emissions along the trajectory path. Analysis of surface daily NO2 observations indicates that high pollution episodes (> 90th percentile) occur predominantly in the post-monsoon and more than 75% of high pollution events are primarily caused by non-local sources. Overall, we find that in the post-monsoon period, there is a substantial import of NOx pollution into Delhi with a large contribution from the transport sector. This work indicates that the advection of highly polluted air originating from outside Delhi is of concern for the population and 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 sector, particularly during post-monsoon months. [ABSTRACT FROM AUTHOR]

We use the TOMCAT 3-D chemical transport model with a balanced flux inventory to simulate the global distribution of atmospheric carbonyl sulfide (OCS). This is compared with limb-sounding satellite observations made by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) and surface flask measurements made worldwide at 14 National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ESRL) sites. By scaling gross primary productivity (GPP) output from the Joint UK Land Environment Simulator (JULES), we provide a new estimation of global OCS vegetative uptake. This is calculated by scaling GPP according to a leaf relative uptake (LRU) term, yielding a global yearly atmospheric uptake of approximately 629 Gg S, which is toward the lower estimates from recent studies. To compensate for this larger vegetative sink, we scale oceanic emissions of OCS up to an annual mean of 689 Gg S, focused over the tropical ocean region. We combine our OCS fluxes to derive a new inventory which was used in a TOMCAT simulation from 2004–2018 to allow and investigate the annual distribution and seasonality of OCS as well as long term comparisons with available measurements. The simulation matches satellite and surface observations to within their uncertainties in most instances. When compared to co-located ACE-FTS OCS profiles between 5 km and 30 km, the simulation remains within 5 % of the measurements throughout the majority of this region and lies within the standard deviation of these measurements. At the surface, the model captures background concentrations at most of the surface sites to within the maximum and minimum of the seasonal measurements. Compared to a control TOMCAT simulation using the existing Kettle et al. (2002) benchmark flux inventory, errors in the surface comparisons are reduced by as much as 57 %. Our new inventory reduces the average difference in the modelled seasonal amplitude compared to the surface measurements from ±40 % to ±34 %. Other key improvements include better representation of OCS seasonality at North Hemisphere continental sites, as well as a better match in background concentration at tropical Hawaiin sites. [ABSTRACT FROM AUTHOR]

We present a novel approach to derive indirect global information on the hydroxyl radical (OH), one of the most important atmospheric oxidants, using state-of-art satellite trace gas observations (key sinks and sources of OH) and a steady-state approximation (SSA). This is a timely study as OH observations are predominantly from spatially sparse field and infrequent aircraft campaigns, so there is a requirement for further approaches to infer spatial and temporal information on OH and its interactions with important climate (e.g. methane, CH4) and air quality (e.g. nitrogen dioxide, NO2) trace gases. Due to the short lifetime of OH (~1.0 s), SSAs of varying complexities can be used to model its concentration and offer a tool to examine the OH budget in different regions of the atmosphere. Here, we use the well-evaluated TOMCAT three-dimensional chemistry transport model to identify atmospheric regions where different complexities of the SSAs are representative of OH. In the case of a simplified SSA (S-SSA), where we have observations of ozone (O3), carbon moNO[sub x]ide (CO), CH4and water vapour (H2O) from the Infrared Atmospheric Sounding Interferometer (IASI) on-board ESA's MetOp-A satellite, it is most representative of OH between 600 and 700 hPa (though suitable between 400-800 hPa) within ~20 % of TOMCAT modelled OH. The same S-SSA is applied to aircraft measurements from the Atmospheric Tomography Mission (ATom) and compares well with the observed OH concentrations within ~30 % yielding a correlation of 0.78. We apply the S-SSA to IASI data spanning 2008-2017 to explore the global long-term inter-annual variability of OH. Relative to the 10-year mean, we find that global annual mean OH anomalies ranged from -3.1 % to +4.4 %, with the largest spread in the tropics between -7.0 % and +7.7 %. Investigation of the individual terms in the S-SSA over this time period suggests that O3and CO were the key drivers of variability in the production and loss of OH. For example, large enhancement in the OH sink during the positive 2015/2016 ENSO event was due to large scale CO emissions from drought induced wildfires in South East Asia). The methodology described here could be further developed as a constraint on the tropospheric OH distribution as further satellite data becomes available in the future. [ABSTRACT FROM AUTHOR]

We have estimated the spatial changes in NO2 levels over different regions of India during the COVID-19 lockdown (25th March-3rd 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 enhancement of 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, and some parts of 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. [ABSTRACT FROM AUTHOR]

Volcanic eruptions can cause significant disruption to society and numerical models are crucial for forecasting the dispersion of erupted material. Here we assess the skill and limitations of the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) in simulating the dispersion of the sulfur dioxide (SO2) cloud from the 21-22 June 2019 eruption of the Raikoke volcano (48.3° N, 153.2° E). The eruption emitted around 1.5 ± 0.2 Tg of SO2, which represents the largest volcanic emission of SO2 into the stratosphere since the 2011 Nabro eruption. We simulate the temporal evolution of the volcanic SO2 cloud across the Northern Hemisphere (NH) and compare our model simulations to high-resolution SO2 measurements from the Tropospheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) satellite SO2 products. We show that NAME accurately simulates the observed location and horizontal extent of the SO2 cloud during the first 2-3 weeks after the eruption, but is unable, in its standard configuration, to capture the extent and precise location of very high-concentration regions within the volcanic cloud. Using the Fractional Skill Score as metric for model skill, NAME shows skill in simulating the horizontal extent of the cloud for 12-17 days after the eruption where vertical column densities (VCD) of SO2 (in Dobson Units, DU) are above 1 DU. For SO2 VCDs above 20 DU, which are predominantly observed as small-scale features within the SO2 cloud, the model shows skill on the order of 2-4 days only. The lower skill for these high-concentration regions is partly explained by the model-simulated SO2 cloud in NAME being too diffuse compared to TROPOMI retrievals. Reducing the standard diffusion parameters used in NAME by a factor of four results in a slightly increased model skill during the first five days of the simulation, but on longer timescales the simulated SO2 cloud remains too diffuse when compared to TROPOMI measurements. We find that the temporal evolution of the NH-mean SO2 mass burden simulated by NAME strongly depends on the fraction of SO2 mass emitted into the lower stratosphere, which is uncertain for the 2019 Raikoke eruption. When emitting 0.9-1.1 Tg of SO2 into the lower stratosphere (11-18 km) and 0.4-0.7 Tg into the upper troposphere (8-11 km), both NAME and TROPOMI show a similar peak in SO2 mass burden (1.4-1.6 Tg of SO2) with an average SO2 e-folding time of 14-15 days in the NH. Our work demonstrates the large potential of using high-resolution satellite retrievals to identify and rectify limitations in dispersion models like NAME, which will ultimately help to improve dispersion modelling efforts of volcanic SO2 clouds. [ABSTRACT FROM AUTHOR]

Various observation-based datasets have confirmed positive zonal mean column ozone trends at midlatitudes as a result of the successful implementation of the Montreal Protocol. However, there is still uncertainty about the longitudinal variation of these trends and the direction and magnitude of ozone changes at low latitudes. Here, we use the extended Copernicus Climate Change Service (C3S) dataset (1979–2017) to investigate the long-term variations in total column ozone (TCO) over the Tibetan Plateau (TP) for different seasons. We use piecewise linear trend (PWLT) and equivalent effective stratospheric chlorine loading (EESC)-based multivariate regression models with various proxies to attribute the influence of dynamical and chemical processes on the TCO variability. We also compare the seasonal behaviour of the relative total ozone low (TOL) over the TP with the zonal mean at the same latitude. Both regression models show that the TP column ozone trends change from negative trends from 1979 to 1996 to small positive trends from 1997 to 2017, although the later positive trend based on PWLT is not statistically significant. The wintertime positive trend starting from 1997 is larger than that in summer, but both seasonal TP recovery rates are smaller than the zonal means over the same latitude band. For TP column ozone, both regression models suggest that the geopotential height at 150 hPa (GH150) is a more suitable and realistic dynamical proxy compared to a surface temperature proxy used in some previous studies. Our analysis also shows that the wintertime GH150 plays an important role in determining summertime TCO over the TP through persistence of the ozone signal. For the zonal mean column ozone at this latitude, the quasi-biennial oscillation (QBO) is nonetheless the dominant dynamical proxy. We also use a 3-D chemical transport model to diagnose the contributions of different proxies for the TP region. The role of GH150 variability is illustrated by using two sensitivity experiments with repeating dynamics of 2004 and 2008. The simulated ozone profiles clearly show that wintertime TP ozone concentrations are largely controlled by tropics to midlatitude pathways, whereas in summer variations associated with tropical processes play an important role. These model results confirm that the long-term trends of TCO over the TP are dominated by different processes in winter and summer. The different TP recovery rates relative to the zonal means at the same latitude band are largely determined by wintertime dynamical processes. [ABSTRACT FROM AUTHOR]

We use a regional chemistry transport model (WRF-Chem) in conjunction with surface observations of tropospheric ozone and Ozone Monitoring Instrument (OMI) satellite retrievals of tropospheric column NO2 to evaluate processes controlling the regional distribution of tropospheric ozone over Western Siberia for late-spring and summer in 2011. This region hosts a range of anthropogenic and natural ozone precursor sources, and serves as a gateway for near-surface transport of Eurasian pollution to the Arctic. However, there is a severe lack of in-situ observations to constrain tropospheric ozone sources and sinks in the region. We show widespread negative bias in WRF-Chem tropospheric column NO2 when compared to OMI satellite observations from May - August, which is reduced when using ECLIPSE v5a emissions (FMB= -0.82 to -0.73) compared with the EDGAR-HTAP-2 emissions data (FMB= -0.80 to -0.70). Despite the large negative bias, the spatial correlations between model and observed NO2 columns suggest that the spatial pattern of NOx sources in the region is well represented. Based on ECLIPSE v5a emissions, we assess the influence of the two dominant anthropogenic emission sectors (transport and energy) and vegetation fires on surface NOx and ozone over Siberia and the Russian Arctic. Our results suggest regional ozone is more sensitive to anthropogenic emissions, particularly from the transport sector, and the contribution from fire emissions maximises in June and is largely confined to latitudes south of 60° N. Large contributions to surface ozone from energy emissions are simulated in April north of 60° N, due to emissions associated with oil and gas extraction. Ozone dry deposition fluxes from the model simulations show that the dominant ozone dry deposition sink in the region is to forest, averaging 6.0 Tg of ozone per month, peaking at 9.1 Tg of ozone deposition during June. The impact of fires on ozone dry deposition within the domain is small compared to anthropogenic emissions, and is negligible north of 60° N. Overall, our results suggest that surface ozone in the region is controlled by an interplay between seasonality in atmospheric transport patterns, vegetation dry deposition, and a dominance of transport and energy sector emissions. [ABSTRACT FROM AUTHOR]

We use the ozone dataset from the Copernicus Climate Change Service (C3S) during 1979-2017 to investigate the long-term variations of the total column ozone (TCO) and the relative total ozone low (TOL) over the Tibetan Plateau (TP) during different seasons. Based on various regression models, the wintertime TCO over the TP decreases overall during 1979-2017 with ongoing decreases since 1997. We perform multivariate regression analysis to quantify the influence of dynamical and chemical processes responsible for the long-term TCO variability over the TP. We use both piecewise linear trend (PWLT) and equivalent effective stratospheric chlorine loading (EESC)-based regression models that include explanatory variables such as the 11-year solar cycle, quasi-biennial oscillation (QBO) at 30 hPa and 10 hPa and the geopotential height (GH) at 150 hPa. The 150 hPa GH is found to be a major dynamical contributor to the total ozone variability (8 %) over the TP in wintertime. We also find strong correlation between TCO in DJF and the following JJA, indicating that negative/positive anomalies in the wintertime build up persist into summer. We also use the TOMCAT/SLIMCAT 3-D chemical transport model to investigate the contributions of different factors to the ozone variations over the TP. Using identical regression model on simulated TCO time series, we obtain consistent results with C3S-based data. We perform two sensitivity experiments with repeating dynamics of 2004 and 2008 to further study the role that the GH at 150 hPa plays in the ozone variations over the TP. The GH differences between the two years show an obvious, negative centre near 150 hPa over the TP in DJF. Composite analysis show that GH fluctuations associated with Inter Tropical Convergence Zone, ENSO events or Walker circulation play a key role in controlling TCO variability in the lower stratosphere. [ABSTRACT FROM AUTHOR]

Here we present a description of the UKCA StratTrop chemical mechanism which is used in the UKESM1 Earth System Model for CMIP6. The StratTrop chemical mechanism is a merger of previously well evaluated tropospheric and stratospheric mechanisms and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address. [ABSTRACT FROM AUTHOR]