Abstract. 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-the-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 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 monoxide (CO), CH4 and 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 %–30 % 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 ∼26 %, 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 +4.7 %, with the largest spread in the tropics between −6.9 % and +7.7 %. Investigation of the individual terms in the S-SSA over this time period suggests that O3 and 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 El Niño–Southern Oscillation (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 additional satellite data become available in the future.

Transforming waste materials into added-value products is critical for a sustainable and circular economy. Here, Mg/Fe layered double hydroxide (LDH) materials, with a Mg2+:Fe3+ ratio of 2, were successfully synthesized via the co-precipitation method from a dissolved acid mine drainage precipitate waste “ochre”, which is normally put to landfill. The prepared LDH materials were tested as a heterogeneous base catalyst to promote the production of the ketone, 12-tricosanone, from lauric acid, a component of plant oils, through a ketonic decarboxylation reaction, giving a circular economy route to catalysts for sustainable ketone production. The highest yield of the ketone observed was 80%.

Abstract. 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 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), 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 pre-monsoon 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 non-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.

Vegetation fires occur regularly in Australia between the months of August and December (Giglio et al., 2013;van der Werf et al., 2017). Burning activity predominantly occurs in northern Australia, but is widespread across the continent (Andela et al., 2017). Giglio et al. (2013) suggested that the majority of vegetation fires take place on savanna and shrubland, but in south-eastern Australia forest fires are most prevalent (Bradstock et al., 2012; van der Werf et al., 2010). Over recent decades, there have been largescale decreases in Australian fire activity (Andela et al., 2017;Rabin et al., 2015). However, with present and future climate and land-use change, conditions in Australia are predicted to yield more frequent largescale fire events (Clarke et al., 2011;Di Virgilio et al., 2019;Pitman et al., 2007). According to the Australian Bureau of Meteorology (2020), the 2019 summer was the warmest (1.52°C above the national average, and driest (rainfall 40% lower than average) season on record. This provided suitable conditions for wildfires to ignite and spread.The Australian wildfires of the 2019/2020 fire season, colloquially known as the "black summer," represented some of the largest events in recent decades. The fires burned over 110,000 km 2 of bush, forest and parks (BBC, 2020). The majority of the fire activity occurred in south-eastern Australia (New South Wales and Victoria), which is predominantly eucalyptus forest and woodland (SOTE, 2016). The fires caused 33 deaths (BBC, 2020) and killed over approximately 1 billion animals (UoS, 2020). In comparison, the Black

The Australian wildfires of the 2019/2020 fire season, colloquially known as the "black summer," represented some of the largest events in recent decades. The fires burned over 110,000 km 2 of bush, forest and parks (BBC, 2020). The majority of the fire activity occurred in south-eastern Australia (New South Wales and Victoria), which is predominantly eucalyptus forest and woodland (SOTE, 2016). The fires caused 33 deaths (BBC, 2020) and killed over approximately 1 billion animals (UoS, 2020). In comparison, the Black

Abstract. Ozone is a potent air pollutant in the lower troposphere and an important short-lived climate forcer (SLCF) in the upper troposphere. Studies using satellite data to investigate spatiotemporal variability of troposphere ozone (TO3) have predominantly focussed on the tropospheric column metric. This is the first study to investigate long-term spatiotemporal variability in lower tropospheric column ozone (LTCO3, surface-450 hPa sub-column) by merging multiple European Space Agency – Climate Change Initiative (ESA-CCI) products produced by the Rutherford Appleton Laboratory (RAL) Space. We find that in the LTCO3, the degrees of freedom of signal (DOFS) from these products varies with latitude range and season and is up to 0.65, indicating that the retrievals contain useful information on lower TO3. The spatial and seasonal variation of the RAL Space products are in good agreement with each other but there are systematic offsets of up to 3.0–5.0 DU between them. Comparison with ozonesondes shows that the Global Ozone Monitoring Experiment (GOME-1, 1996–2003), the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY, 2003–2010) and the Ozone Monitoring Instrument (OMI, 2005–2017) have stable LTCO3 records over their respective periods, which can be merged together. While GOME-2 (2008–2018) shows substantial drift in its bias with respect to ozonesondes. We have therefore constructed a robust merged dataset of LTCO3 from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing the LTCO3 differences between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases (3.0–5.0 DU) in the tropics/sub-tropics, while in the northern mid-latitudes, we find small scale differences in LTCO3. Therefore, we conclude that there has been a substantial increase in tropical/sub-tropical LTCO3 during the satellite-era.

<div> <p>The hydroxyl radical (OH) is one of the most important species in atmospheric chemistry. It plays a dominant role in the oxidation of many other species in the troposphere, such as anthropogenic pollutants. Direct in-situ and satellite measurements of OH are scarce due to its short lifetime (around 1 second) and low abundance. Other indirect methods of inferring global mean OH have been established, such as using methyl chloroform as a tracer. However because of its recent phase out there is a demand for another method of calculating the global OH abundance. It is therefore useful to explore indirect methods for calculating OH. In particular, global satellite data can provide a means for estimating mean OH within large atmospheric regions. An improved understanding of the global distribution of OH will allow a better understanding of atmospheric chemistry, especially the distributions of anthropogenic pollutants.  </p> </div><div> <p>Due to the short lifetime of OH, a steady-state approximation can be used to model its concentration. This allows the OH distribution to be calculated using a simple equation and the accuracy of the estimate depends on the number of source/sink terms which can be included in the equation. In this work, a steady state approximation has been applied to the global OH budget as defined in the TOMCAT 3-D model. The full steady-state equation (based on all reactions in the model) has been simplified in various ways to include only the major sources and sinks of OH that can be observed directly by satellite, such as carbon monoxide (CO), methane (CH4), water vapour (H2O) and ozone (O3). </p> </div><div> <p>Recent satellite observations of these species is then applied to the steady-state approximation to derive an estimate of the global OH distribution. We use the 3-D model to determine where the simplified steady-state approximation is likely to be most valid. The overall potential of this method to calculate an accurate OH distribution, bearing in mind satellite observation errors, is discussed. </p> </div>

Supplemental InformationSection S1. Comparison of partially sampled (spatial and temporal) and fully sampled satellite data