O3 Column Research Articles

Impact of the eruption of Mt Pinatubo on the chemical composition of the stratosphere

Abstract. This article describes the volcanic effect of the Mt Pinatubo eruption in June 1991 on the ozone (O3) and methane (CH4) distribution in the stratosphere, as simulated with the chemistry–climate model EMAC (ECHAM/MESSy Atmospheric Chemistry: ECHAM5, version 5.3.02; MESSy, version 2.51). In this study, the effects of volcanic heating and heterogeneous chemistry on the chemical composition, caused by the volcanic aerosol, are separated. Global model simulations over the relevant period of the eruption from 1989 to 1997 with EMAC in T42L90MA resolution with specified dynamics and interactive chemistry were performed. The first simulation (VOL) contains the volcanic perturbation as an additional aerosol load and thus simulates the interaction of the aerosol with the chemistry and the radiation. The second simulation (NOVOL) neglects the eruption and represents the undisturbed atmosphere. In the third simulation (CVOL) the volcanic aerosol only interacts with the heterogeneous chemistry, such that volcanic heating is omitted. The differences between the simulation results VOL−NOVOL describe the total effect of the Mt Pinatubo eruption on the chemical composition, VOL−CVOL the stratospheric heating effect, and CVOL−NOVOL the chemical effect of the aerosol on the heterogeneous chemistry. The post-volcanic stratosphere shows a decrease in the O3 column in the tropics and an increase in the midlatitudes and polar regions, lasting roughly 1 year. This change in the ozone column is solely a result of the heating effect. The subsequent decrease in the ozone column is related to the chemical effect. The contribution of the catalytic loss cycles (NOx, HOx, ClOx, and BrOx) on the depletion of O3 is analysed in detail. In the tropics, CH4 increases in the upper stratosphere because of stronger vertical transport.

Ozone Trends during 1979–2019 over Tibetan Plateau Derived from Satellite Observations

Ozone (O3) is a very important atmospheric component related to many atmospheric processes. Tibetan Plateau (TP) has played an important role to weather and climate in South Asia and was found to modulate the variation of ozone amount, leading to the ozone low over the TP in both the summer and winter. To better understand the changing trend of ozone, a novel statistic method, i.e. the Ensemble Empirical Mode Decomposition (EEMD) method, is used to analyze the trends of total column O3 (TCO) and the ozone deficit after removing the corresponding zonal mean TCO over the TP. Data of TCO over TP is from satellite observations by OMI/Aura, and for comparison the long-term Merged Ozone Data from NASA is used to analyze the trend of TCO in three latitude zones near TP. In consistent with some other studies, slightly recovery of ozone at 1996-1997 is evident from the zonal mean in three latitude zones between 25oN to 40oN in northern hemisphere, however after 2013 only the north of TP shows an increase trend but the zonal mean between 30oN to 40oN show decrease trends. In contrast, TCO over the TP shows a consistent increase trend from 2004 to 2019, and the ozone deficit over the TP has a rapid increase trend after 2013, with a larger increase trend in the winter season than in the summer. Further analysis to the ozone low events in the winter and summer from 2004 to 2019 shows that the ozone low in May is much deeper and lasts longer than that in the winter. These results show the mechanism of ozone low and its trend in winter is more complex and worthy for more investigation.

Annular Solar Eclipse on 26 December 2019 and its Effect on Trace Pollutant Concentrations and Meteorological Parameters in Kannur, India: a Coastal City

This paper highlights the variations of surface ozone (O3), total column ozone (TCO), oxides of nitrogen (NO and NO2), carbon monoxide (CO), sulphur dioxide (SO2), ammonia (NH3), volatile organic compounds (Benzene, Tolune, Ethyle Benzene, Xylenes (collectively called BTEX)), particulate matters (PM10 and PM2.5), and meteorological parameters at the time of an annular solar eclipse on 26 December 2019 at Kannur town in Kerala, South India. The maximum solar obscuration has resulted a decrease in solar radiation by 93%, air temperature by 16.3%, wind speed by 36.1% and an increase in relative humidity by 27.1% at this coastal location. Along with the reduction in solar radiation, the concentration of surface O3 (61.5%) and total column O3 (11.8%) have been observed to decrease at the maximum phase of solar eclipse. CO and NO2 concentration were found to be increased by 28.9% and 42.2%, respectively, while NO exhibited its typical diurnal variation. Further, a decrease in concentrations of SO2 by 17.6%, PM10 by 18.5%, and PM2.5 by 11.3% were observed. NH3 and BTEX were found to be higher than 11.3% and 22.6% of the concentrations in control days. All of these deviated parameters could be seen returning to their normal state after completing the eclipse episode. The variation of photodissociation coefficient j(NO2) values were theoretically calculated from the observed data, which shows a good agreement with the model simulated j(NO2) reduction. This is an extensive second observation on the variation of trace pollutants on solar eclipse, after the partial solar eclipse observed on 15 January 2010 at Kannur.

Comparisons of upper air ozone at a coastal and urban site and the impacts of non-controllable ozone sources

Abstract This study quantified the impact of non-controllable and urban emission sources on the enhancement of ozone (O3) in the troposphere. These enhancements were investigated using data from simultaneous ozonesonde launches at Half Moon Bay (HMB), CA and San Jose (SJ), CA on eleven dates in July and August 2018. The urban O3 enhancement in the SJ vertical profile was derived by subtracting out HMB, which represents baseline O3, from the urban SJ profile. Within the planetary boundary layer (PBL), urban emissions had a large impact on SJ, as SJ O3 was 20–30 ppb higher than HMB for all dates. Above the PBL, most enhancement profiles remained close to zero, indicating little differences aloft between HMB and SJ. The two sites had strong correlation coefficients (CCs), highlighting the influence of baseline O3 on SJ. A major axis regression for all vertical levels between SJ and HMB revealed a slope of 1.00 SJ ppb/HMB ppb and intercept of 0.004 ppb. The percent contribution of mixing layer (ML) O3 to tropospheric O3 and tropospheric O3 to total column O3 demonstrates the predominant influence of baseline O3 on the O3 profile, even over a polluted urban region. The contribution of ML O3 was low for all dates, between 2 and 6%, whereas the tropospheric contribution was 11–18%. These findings emphasize the importance of baseline O3 in regions with reduced vertical mixing; polluted urban air near the surface has minimal impacts on O3 concentrations above the PBL.

The use of the 1.27 µm O<sub>2</sub> absorption band for greenhouse gas monitoring from space and application to MicroCarb

Abstract. Monitoring CO2 from space is essential to characterize the spatiotemporal distribution of this major greenhouse gas and quantify its sources and sinks. The mixing ratio of CO2 to dry air can be derived from the CO2∕O2 column ratio. The O2 column is usually derived from its absorption signature on the solar reflected spectra over the O2 A band (e.g. Orbiting Carbon Observatory-2 (OCO-2), Thermal And Near infrared Sensor for carbon Observation (TANSO)/Greenhouse Gases Observing Satellite (GOSAT), TanSat). As a result of atmospheric scattering, the atmospheric path length varies with the aerosols' load, their vertical distribution, and their optical properties. The spectral distance between the O2 A band (0.76 µm) and the CO2 absorption band (1.6 µm) results in significant uncertainties due to the varying spectral properties of the aerosols over the globe. There is another O2 absorption band at 1.27 µm with weaker lines than in the A band. As the wavelength is much closer to the CO2 and CH4 bands, there is less uncertainty when using it as a proxy of the atmospheric path length to the CO2 and CH4 bands. This O2 band is used by the Total Carbon Column Observing Network (TCCON) implemented for the validation of space-based greenhouse gas (GHG) observations. However, this absorption band is contaminated by the spontaneous emission of the excited molecule O2*, which is produced by the photo-dissociation of O3 molecules in the stratosphere and mesosphere. From a satellite looking nadir, this emission has a similar shape to the absorption signal that is used. In the frame of the CNES (Centre National d'Études Spatiales – the French National Centre for Space Studies) MicroCarb project, scientific studies have been performed in 2016–2018 to explore the problems associated with this O2* airglow contamination and methods to correct it. A theoretical synthetic spectrum of the emission was derived from an approach based on A21 Einstein coefficient information contained in the line-by-line high-resolution transmission molecular absorption (HITRAN) 2016 database. The shape of our synthetic spectrum is validated when compared to O2* airglow spectra observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat in limb viewing. We have designed an inversion scheme of SCIAMACHY limb-viewing spectra, allowing to determine the vertical distribution of the volume emission rate (VER) of the O2* airglow. The VER profiles and corresponding integrated nadir intensities were both compared to a model of the emission based on the Reactive Processes Ruling the Ozone Budget in the Stratosphere (REPROBUS) chemical transport model. The airglow intensities depend mostly on the solar zenith angle (both in model and data), and the model underestimates the observed emission by ∼15 %. This is confirmed with SCIAMACHY nadir-viewing measurements over the oceans: in such conditions, we have disentangled and retrieved the nadir O2* emission in spite of the moderate spectral resolving power (∼860) and found that the nadir SCIAMACHY intensities are mostly dictated by solar zenith angle (SZA) and are larger than the model intensities by a factor of ∼1.13. At a fixed SZA, the model airglow intensities show very little horizontal structure, in spite of ozone variations. It is shown that with the MicroCarb spectral resolution power (25 000) and signal-to-noise ratio (SNR), the contribution of the O2* emission at 1.27 µm to the observed spectral radiance in nadir viewing may be disentangled from the lower atmosphere/ground absorption signature with a great accuracy. Indeed, simulations with 4ARCTIC radiative transfer inversion tool have shown that the CO2 mixing ratio may be retrieved with the accuracy required for quantifying the CO2 natural sources and sinks (pressure-level error ≤1 hPa; XCO2 accuracy better than 0.4 ppmv) with the O2 1.27 µm band only as the air proxy (without the A band). As a result of these studies (at an intermediate phase), it was decided to include this band (B4) in the MicroCarb design, while keeping the O2 A band for reference (B1). Our approach is consistent with the approach of Sun et al. (2018), who also analysed the potential of the O2 1.27 µm band and concluded favourably for GHG monitoring from space. We advocate for the inclusion of this O2 band on other GHG monitoring future space missions, such as GOSAT-3 and EU/European Space Agency (ESA) CO2-M missions, for a better GHG retrieval.

Constraining Ganymede's neutral and plasma environments through simulations of its ionosphere and Galileo observations

Ganymede's neutral and plasma environments are poorly constrained by observations. Carnielli et al. (2019) developed the first 3D ionospheric model aimed at understanding the dynamics of the present ion species and at quantifying the presence of each component in the moon's magnetosphere. The model outputs were compared with Galileo measurements of the ion energy flux, ion bulk velocity and electron number density made during the G2 flyby. A good agreement was found in terms of ion energy distribution and bulk velocity, but not in terms of electron number density.In this work, we present some improvements to our model (Carnielli et al., 2019) and quantitatively address the possible sources of the discrepancy found in the electron number density between the Galileo observations and our ionospheric model. We have improved the ion model by developing a collision scheme to simulate the charge-exchange interaction between the exosphere and the ionosphere. We have simulated the energetic component of the O2 population, which is missing in the exospheric model of Leblanc et al. (2017) and added it to the original distribution, hence improving its description at high altitudes. These improvements are found to be insufficient to explain the discrepancy in the electron number density. We provide arguments that the input O2 exosphere is underestimated and that the plasma production acts asymmetrically between the Jovian and anti-Jovian hemispheres. In particular, we estimate that the O2 column density should be greater than 1015 cm−2, i.e., higher than previously derived upper limits (and a factor 10 higher than the values from Leblanc et al. (2017)), and that the ionization frequency from electron impact must be higher in the anti-Jovian hemisphere for the G2 flyby conditions.

Impacts of Chemical and Synoptic Processes on Summer Tropospheric Ozone Trend in North China

Compared with other regions in China, air pollution on the North China Plain (NCP) is serious. Fine particle pollution has been studied in-depth, but there is less research on long-term troposphere ozone (O3) variation. This study focuses on the summer interannual tropospheric O3 variation on the NCP and its influential factors. Our analysis relies on satellite observations (O3, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO), determined as vertical column density of the troposphere) and dynamical processes (El Niño-Southern Oscillation (ENSO), potential vorticity (PV), the quasibiennial oscillation (QBO), and East Asian summer monsoon index (EASMI)). Our results show the vertical column density of tropospheric O3 has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. The summer series of tropospheric O3 show two distinct phases: the first phase (2005–2011), with an average growth rate of 0.55 ± 0.20 DU/yr, and a second phase (2012–2016), with an average reduction rate of 0.16 ± 0.23 DU/yr. The tropospheric NO2 column in the NCP also has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. Tropospheric NO2 and CO column concentrations obtained from satellite observations indicate that emission reductions might be the main cause of the tropospheric O3 decrease. Particularly, the reduction of nitrogen oxides (NOx) is more significant, and NO2 decreased by (0.45 ± 0.11) × 1015 molec·cm−2 per year in summer since 2012. However, tropospheric column HCHO shows an increase of 0.05 × 1015 molec·cm−2 per year during the whole period of 2005 to 2016. An O3-NOx-VOC sensitivity experiment in the NCP showed that the O3 is still in a NOx-saturated state in some heavily polluted cities, although the NOx emissions are decreasing overall. In addition to the chemical reactions, atmospheric dynamic processes also have an effect on tropospheric O3. Finally, we built a model to analyze the contributions of chemical processes and dynamic processes to the tropospheric O3 column in the NCP. For the chemical process variables, 69.73% of the observed trend of tropospheric O3 could be explained by the NO2 tropospheric column. Therefore, the reduction of tropospheric O3 since 2012 is associated with the reduction of NOx. For the dynamical process variables, ENSO, PV, and EASMI can explain 60.64% of the observed trend of tropospheric O3. This result indicates that the atmospheric circulation of the western Pacific Ocean in summer has a significant impact on the interannual trends of tropospheric O3 in the NCP. It is also found that chemical processes had a more important impact on interannual tropospheric O3 than dynamic processes, although the dynamic processes cannot be neglected.

Satellite-based estimation of full-coverage ozone (O3) concentration and health effect assessment across Hainan Island

Abstract Ambient ozone (O3) poses great damage to human health, biodiversity, and climate change. Although the health risk due to O3 pollution has been widely evaluated, the spatiotemporal variation of O3 level and its potential health impact in a remote tropical island was less concerned. In the present study, we firstly employed an efficient machine learning model named random forest (RF) to fill the missing O3 column amount over Hainan Island of China based on the meteorological factors and other geographical covariates. The result suggested that the RF model achieved the best performance (R2 = 0.87, RMSE = 6.36 DU) among all of the filling methods. We further used an extreme gradient boosting (XGBoost) algorithm to estimate the surface O3 level around Hainan Island on the basis of the full-coverage O3 column amount and other predictors. The XGBoost method showed the better predictive performance (R2 = 0.59, RMSE = 24.14 μg/m3) compared with other estimation models. The predicted O3 concentration exhibited remarkably spatial difference with the highest value observed in Dongfang (77.61 ± 5.25 μg/m3), followed by that in Changjiang (72.51 ± 5.22 μg/m3), and the lowest one in Lingshui (64.16 ± 2.71 μg/m3). Based on the estimated O3 level, we found that the annually mean nonattainment days in Dongfang reached 29.26 ± 35.20 days and about one third of days in the winter fell into the severe O3 pollution over Hainan Island. Besides, the mean all-cause mortalities owing to severe O3 pollution over Hainan Island were calculated to be 391 (95%CI: (212–570)) cases each year, accounting for 0.004% of all the population in Hainan Island. The statistical simulation of O3 level at a remote island updated the traditional knowledge and aroused the public concern on island air pollution.

Tropospheric ozone over the Indian subcontinent from 2000 to 2015: Data set and simulation using GEOS-Chem chemical transport model

The Indian subcontinent (IS) is a region of increasing economic growth, urbanization, and consequently, anthropogenic emissions, altering tropospheric ozone (O3) over the region with impacts on the lives and health of 1.3 billion people. We have developed a comprehensive data set of the tropospheric O3 for 16 years (2000–2015) for the region between 50-115°E and 0–45°N, focusing on the IS. The data set included available balloon-borne, aircraft, and satellite-based measurements. We used a global three-dimensional chemical transport model, GEOS-Chem, at a 2° × 2.5° resolution to calculate daily tropospheric O3 over the region. The simulated O3 abundances in the boundary layer and lower, mid, and upper troposphere were compared with ozonesonde, aircraft, and satellite observations. The statistical analyses indicate that the model simulated boundary layer and lower, mid, and upper tropospheric O3 column abundances reasonably well with a mean bias ~1–3 DU in comparison to observations, but within the uncertainties of the observations. The model reproduced the vertical profiles of O3 and CO with a bias of less than 20% over different regions in the IS. The simulated tropospheric column NO2 was higher by a factor of ~1.5 compared to satellite observations. The model reproduced the regional difference in seasonal variations of tropospheric column O3 as observed by the Ozone Monitoring Instrument. We conclude that the CO emissions from the IS are underestimated while those of NOx are overestimated, both by around 20–30%.

Dynamical nature of tropospheric ozone over a tropical location in Peninsular India: Role of transport and water vapour

This paper deals with the temporal changes in the altitude distribution of tropospheric ozone (O3) based on the measurements by balloon-borne O3-sondes during 2011–2014, conducted at the tropical, coastal site Thiruvananthapuram on the south west coast of India. This is the first study from this region addressing the highly dynamic nature of tropospheric O3 profiles (in terms of their vertical structure and short-term changes) and attempting to categorise them based on 121 in-situ measured O3 profiles. The tropospheric O3 profiles could be categorised into four major groups namely (i) those with steady O3 mixing ratio (ii) with increasing mixing ratio, (iii) with mid-tropospheric enhancement and (iv) with multiple layers/laminar nature. The causative mechanisms of these different categories were examined. The observed differences in the tropospheric O3 distribution are attributed to meteorological conditions in particular the synoptic scale systems, long range transport, intrusion from stratosphere and photochemistry, most importantly, the effect of water vapour content. Water vapour and O3 showed complex dependence with positive and negative association depending on the precursor levels and availability of water vapour. The altitudinal changes in O3 also exhibited close association with those of potential temperature and equivalent potential temperature. An analysis of the seasonal characteristics of vertical distribution of tropospheric O3 also carried out along with the altitude-dependent seasonal behaviour. In general, the total column O3 estimated by the integration of O3-sonde retrieved profiles differed by about ±10% with those retrieved by satellite-based measurements. The TCO contributes to about 16% (34 DU) of the total column O3, with minimum of 9% in October and maximum of 27% on March. In general, the OMI retrievals under-estimates the O3-sonde derived TCO by 5–10 DU in all the seasons.

Ozone profile climatology for remote sensing retrieval algorithms

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of monthly mean O3 profiles and the corresponding covariances dependent on the local solar time, longitude (15∘), and latitude (10∘), which are parameterized by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of the O3 profile with total column O3 usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better captures the diurnal, seasonal, and spatial variations and dynamical changes in O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain the first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covariance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

WITHDRAWN: Climatology of the ozone vertical distribution on Mars from SPICAM/MEX UV occultations

Abstract The SPICAM/MEX ultraviolet spectrometer probed the Martian atmosphere with the occultation method from 2004 until 2014. SPICAM/MEX performed both stellar and solar occultations during in total four Martian Years with a good spatial and seasonal coverages. We have analyzed these occultations and compiled a climatology of the vertical distribution of Martian ozone, a key chemical species. The stellar occultations mostly probe the nightside atmosphere, whereas the solar occultations are acquired at the terminator (sunrise or sunset), allowing the study of the day-night transition of this photochemically active species. Comparison of the observations with a global climate model show a good overall qualitative agreement. However, quantitative differences are found in certain regions, possibly related to difficulties in correct modeling of the water cycle. In particular, at low latitudes SPICAM is detecting ozone practically throughout the Martian Year, whereas it is only predicted around aphelion in the models. The occultations probe the southern polar winter vortex, its mid-altitude ozone layer (peaking at 50 km), and the ozone layer in the lower atmosphere that shows much larger O3 column concentrations than predicted by modeling. The low- and midlatitude ozone layer forming in northern spring is mapped throughout both hemispheres and details of its structure are revealed. During the northern polar spring, SPICAM observes the lower atmosphere ozone layer, reaching from the surface up to 30 km, showing higher O3 concentrations than expected from modeling.

Why Do Antarctic Ozone Recovery Trends Vary?

We use satellite ozone records and Global Modeling Initiative chemistry transport model simulations integrated with Modern Era Retrospective for Research and Analysis 2 meteorology to identify a metric that accurately captures the trend in Antarctic ozone attributable to the decline in ozone depleting substances (ODSs). The GMI CTM Baseline simulation with realistically varying ODS levels closely matches observed interannual to decadal scale variations in Antarctic September ozone over the past four decades. The expected increase or recovery trend is obtained from the differences between the Baseline simulation and one with identical meteorology and fixed 1995 ODS levels. The differences show that vortex-averaged column O3 has the greatest sensitivity to ODS change from 1 to 20 September. The observed vortex-averaged column O3 during this period produces a trend consistent with the expected recovery attributable to ODS decline. Trends from dates after 20 September have smaller sensitivity to ODS decline and are more uncertain due to transport variability. Simulations show that the greatest decrease in O3 loss (i.e., recovery) occurs inside the vortex near the edge. The polar cap metrics have vortex size-dependent bias and do not consistently sample this region. Because the 60-90°S 220 Dobson unit O3 mass deficit metric does not sample the edge region, its trend is lower than the expected trend; this is improved by area weighting. The 250-Dobson unit O3 mass deficit metric samples more of the edge region, which increases its trend. Approximately 25% of the September Antarctic O3 increase is due to higher O3 levels in June prior to winter depletion.

Comparison between the assimilation of IASI Level 2 ozone retrievals and Level 1 radiances in a chemical transport model

Abstract. The prior information used for Level 2 (L2) retrievals in the thermal infrared can influence the quality of the retrievals themselves and, therefore, their further assimilation in atmospheric composition models. In this study we evaluate the differences between assimilating L2 ozone profiles and Level 1 (L1) radiances from the Infrared Atmospheric Sounding Interferometer (IASI). We minimized potential differences between the two approaches by employing the same radiative transfer code (Radiative Transfer for TOVS, RTTOV) and a very similar setup for both the L2 retrievals (1D-Var) and the L1 assimilation (3D-Var). We computed hourly 3D-Var analyses assimilating L1 and L2 data in the chemical transport model MOCAGE and compared the resulting O3 fields among each other and against ozonesondes. We also evaluated the joint assimilation of limb measurements from the Microwave Limb Sounder (MLS) in combination with IASI to assess the impact of stratospheric O3 on tropospheric analyses. Results indicate that significant differences can arise between L2 and L1 assimilation, especially in regions where the L2 prior information is strongly biased (at low latitudes in this study). In these regions the L1 assimilation provides a better variability of the free-troposphere ozone column. L1 and L2 assimilation instead give very similar results at high latitudes, especially when MLS measurements are used to constrain the stratospheric O3 column. A critical analysis of the potential benefits and drawbacks of L1 assimilation is given in the conclusions. We also list remaining issues that are common to both the L1 and L2 approaches and that deserve further research.

Source attribution of carbon monoxide and ozone over the Indian subcontinent using MOZART-4 chemistry transport model

Daily simulations of tropospheric carbon monoxide (CO) and ozone (O3) have been made using MOZART-4 (Model for OZone And Related chemical Tracers version 4) during 2007–08. The model simulated CO and O3 are evaluated against MOZAIC (Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft) airborne observations over Hyderabad and IASI (Infrared Atmospheric Sounding Interferometer) retrievals over five most populous cities of India i.e. Mumbai, Delhi, Bangalore, Hyderabad, and Ahmedabad. The MOZAIC tropospheric column showed winter maxima and summer minima for CO whereas spring maxima and summer minima for O3. These seasonal features are reproduced well by model over Hyderabad. Model lower and middle tropospheric CO (O3) columns are positively biased by about 14 (8) ppbv as compared to MOZAIC observations. Model underestimated (overestimated) IASI CO columns during pre-monsoon (post-monsoon) while it overestimated IASI O3 columns throughout the year. Model simulated column of CO and O3 are positively biased by 4–13% and 23–33% respectively as compared to the IASI retrievals over five most populous cities. Tagged and sensitivity simulations of MOZART-4 have been used to quantify the contribution of different sources to the tropospheric CO and O3 distribution over the Indian landmass region. At surface, anthropogenic contribution varies from 55% to 81% during different seasons with an annual average contribution of 67%. This contribution decreases with increasing altitude up to 35% at 300 hPa. The contribution of photochemically produced CO is found to be 9–33% at surface. Unlike ANT-CO, the photochemically produced CO increases with altitude as it reaches up to 48% at 300 hPa. Surface BB-CO contributes upto 30% over parts of North East India during pre-monsoon season. Contribution of NAT-CO is found to be negligible (Approximately 6%) near surface as well as at the higher altitudes. Sensitivity simulations are used to decompose the total ozone (TO) into contributions from enhancement of ozone from Indian anthropogenic emissions, referred as Indian pollution ozone (IPO) and from the total background ozone (TBO). Annual total ozone is found to be 30 to 70 ppbv at surface and 77 to 85 ppbv at 300 hPa over the Indian landmass region. IPO and TBO contribute annually 58% and 42% at surface while 45% and 55% at 300 hPa respectively. The IPO contributes strongly at surface, with maximum (68%) impact during pre-monsoon season.

Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models during Recent Field Campaigns in Australia, Part II: Comparison of WRF/Chem and WRF/Chem-ROMS and Impacts of Air-Sea Interactions and Boundary Conditions

Air-sea interactions play an important role in atmospheric circulation and boundary layer conditions through changing convection processes and surface heat fluxes, particularly in coastal areas. These changes can affect the concentrations, distributions, and lifetimes of atmospheric pollutants. In this Part II paper, the performance of the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are intercompared for their applications over quadruple-nested domains in Australia during the three following field campaigns: The Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2) and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). The results are used to evaluate the impact of air-sea interaction representation in WRF/Chem-ROMS on model predictions. At 3, 9, and 27 km resolutions, compared to WRF/Chem, the explicit air-sea interactions in WRF/Chem-ROMS lead to substantial improvements in simulated sea-surface temperature (SST), latent heat fluxes (LHF), and sensible heat fluxes (SHF) over the ocean, in terms of statistics and spatial distributions, during all three field campaigns. The use of finer grid resolutions (3 or 9 km) effectively reduces the biases in these variables during SPS1 and SPS2 by WRF/Chem-ROMS, whereas it further increases these biases for WRF/Chem during all field campaigns. The large differences in SST, LHF, and SHF between the two models lead to different radiative, cloud, meteorological, and chemical predictions. WRF/Chem-ROMS generally performs better in terms of statistics and temporal variations for temperature and relative humidity at 2 m, wind speed and direction at 10 m, and precipitation. The percentage differences in simulated surface concentrations between the two models are mostly in the range of ±10% for CO, OH, and O3, ±25% for HCHO, ±30% for NO2, ±35% for H2O2, ±50% for SO2, ±60% for isoprene and terpenes, ±15% for PM2.5, and ±12% for PM10. WRF/Chem-ROMS at 3 km resolution slightly improves the statistical performance of many surface and column concentrations. WRF/Chem simulations with satellite-constrained boundary conditions (BCONs) improve the spatial distributions and magnitudes of column CO for all field campaigns and slightly improve those of the column NO2 for SPS1 and SPS2, column HCHO for SPS1 and MUMBA, and column O3 for SPS2 at 3 km over the Greater Sydney area. The satellite-constrained chemical BCONs reduce the model biases of surface CO, NO, and O3 predictions at 3 km for all field campaigns, surface PM2.5 predictions at 3 km for SPS1 and MUMBA, and surface PM10 predictions at all grid resolutions for all field campaigns. A more important role of chemical BCONs in the Southern Hemisphere, compared to that in the Northern Hemisphere reported in this work, indicates a crucial need in developing more realistic chemical BCONs for O3 in the relatively clean SH.

Ground-based Measurements of Atmospheric Trace Gases in Beijing during the Olympic Games

A portable Fourier Transform Spectrometer (B3M-IR) is built and used to measure atmospheric trace gases in the city of Beijing during Olympic Games in 2008. A short description of the instrument is first provided in this paper. A detailed spectral analysis is then presented. The total columns of ozone (O3), carbon monoxide (CO), methane (CH4) and nitrous oxide (N2O) are retrieved from the ground-based solar absorption spectra recorded by the B3M-IR during the Olympic Games. Lacking validation data, only the retrieved total column of O3 is compared with that retrieved by MAX-DOAS, which is deployed at the same station. The mean difference between the two methods of measurement is 6.5%, demonstrating the performance and reliability of B3M-IR.

Ground-based Measurements of Atmospheric Trace Gases in Beijing during the Olympic Games

A portable Fourier Transform Spectrometer (B3M-IR) is built and used to measure atmospheric trace gases in the city of Beijing during Olympic Games in 2008. A short description of the instrument is first provided in this paper. A detailed spectral analysis is then presented. The total columns of ozone (O3), carbon monoxide (CO), methane (CH4) and nitrous oxide (N2O) are retrieved from the ground-based solar absorption spectra recorded by the B3M-IR during the Olympic Games. Lacking validation data, only the retrieved total column of O3 is compared with that retrieved by MAX-DOAS, which is deployed at the same station. The mean difference between the two methods of measurement is 6.5%, demonstrating the performance and reliability of B3M-IR.

The Influence of Instrumental Line Shape Degradation on the Partial Columns of O3, CO, CH4 and N2O Derived from High-Resolution FTIR Spectrometry

High resolution Fourier transform infrared (FTIR) measurement of direct sunlight does not only provide information of trace gas total columns, but also vertical distribution. Measured O3, CO, CH4, and N2O can be separated into multiple partial columns using the optimal estimation method (OEM). The retrieval of trace gas profiles is sensitive to the instrument line shape (ILS) of the FTIR spectrometer. In this paper, we present an investigation of the influence of ILS degradation on the partial column retrieval of O3, CO, CH4, and N2O. Sensitivities of the partial column, error, and degrees of freedom (DOFs) of each layer to different levels of ILS degradation for O3, CO, CH4, and N2O are estimated. We then evaluate the impact of ILS degradation on the long-term measurements. In addition, we derive the range of ILS degradation corresponding to the acceptable uncertainties of O3, CO, CH4, and N2O results. The results show that the uncertainties induced by the ILS degradation on the absolute value, error, and the DOFs of the partial column are altitude and gas species dependent. The uncertainties of the partial columns of O3 and CO are larger than those on CH4 and N2O. The stratospheric partial columns are more sensitive to the ILS degradation compared to the tropospheric part. Our result improves the understanding of the ILS degradation on the FTIR measurements, which is important for the quantification of the measurement uncertainties and minimizes the bias of the inter-comparison between different measurement platforms. This is especially useful for the validation of satellite observations, the data assimilation of chemical model simulations, and the quantification of the source/sink/trend from the FTIR measurements.

Ground-based Measurements of Atmospheric Trace Gases in Beijing during the Olympic Games

A portable Fourier Transform Spectrometer (B3M-IR) is built and used to measure atmospheric trace gases in the city of Beijing during Olympic Games in 2008. A short description of the instrument is first provided in this paper. A detailed spectral analysis is then presented. The total columns of ozone (O3), carbon monoxide (CO), methane (CH4) and nitrous oxide (N2O) are retrieved from the ground-based solar absorption spectra recorded by the B3M-IR during the Olympic Games. Lacking validation data, only the retrieved total column of O3 is compared with that retrieved by MAX-DOAS, which is deployed at the same station. The mean difference between the two methods of measurement is 6.5%, demonstrating the performance and reliability of B3M-IR.