Corrigendum to "Satellite observations and model simulations of tropospheric NO₂ columns over south-eastern Europe" published in Atmos. Chem. Phys., 9, 6119–6134, 2009

No abstract available

GOME-2 total ozone columns from MetOp-A/MetOp-B and assimilation in the MACC system

The two Global Ozone Monitoring Instrument (GOME-2) sensors operated in tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites, launched in October 2006 and September 2012 respectively. This paper presents the operational GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) total ozone products provided by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). These products are generated using the latest version of the GOME Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the application of Brion–Daumont–Malicet ozone absorption cross sections, are presented here. On a global scale, GOME-2B has the same high accuracy as the corresponding GOME-2A products. There is an excellent agreement between the ozone total columns from the two sensors, with GOME-2B values slightly lower with a mean difference of only 0.55±0.29%. First global validation results for 6 months of GOME-2B total ozone using ground-based measurements show that on average the GOME-2B total ozone data obtained with GDP 4.7 are slightly higher than, both, Dobson observations by about 2.0±1.0% and Brewer observations by about 1.0±0.8%. It is concluded that the total ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent and may be used simultaneously without introducing systematic effects, which has been illustrated for the Antarctic ozone hole on 18 October 2013. GOME-2A total ozone data have been used operationally in the Copernicus atmospheric service project MACC-II (Monitoring Atmospheric Composition and Climate – Interim Implementation) near-real-time (NRT) system since October 2013. The magnitude of the bias correction needed for assimilating GOME-2A ozone is reduced (to about −6 DU in the global mean) when the GOME-2 ozone retrieval algorithm changed to GDP 4.7

Evaluation of high resolution simulated and OMI retrieved tropospheric NO2 column densities over South-Eastern Europe

High resolution model estimates (10 × 10 km2) of tropospheric NO2 column amounts from the Comprehensive Air Quality Model (CAMx) for the Balkan Peninsula are compared with OMI/Aura measurements (13 × 24 km2 at nadir) for the year April 2009 to March 2010. The Balkan area contributes significantly to the NO2 burden in European air and so numerous urban, industrial and rural regions are studied aiming to investigate the consistency of both satellite retrievals and model predictions at high spatial resolution. It has already been shown that OMI can detect the tropospheric column of NO2 over polluted Balkan cities due to its fine horizontal resolution and instrument sensitivity (Zyrichidou et al., 2009). In this study the improved OMI DOMINO v2.0 satellite retrievals showed that over South-Eastern Europe the monthly mean NO2 tropospheric column density fluctuated between 2.0 and 5.7 ± 1.1 × 1015 molecules/cm2 over urban areas, 1.6–5.0 ± 0.7 × 1015 molecules/cm2 over large industrial complexes and 1.1–2.2 ± 0.4 × 1015 molecules/cm2 over rural areas for the year studied. The Comprehensive Air Quality Model with extensions (CAMx) version 4.40 is a publicly available open-source computer modeling system for the integrated assessment of gaseous and particulate air pollution. The anthropogenic emissions used in CAMx for the Greek domain being studied were compiled employing bottom-up approaches (road transport sector, off-road machinery, etc.) as well as other national registries and international databases. The rest of the Balkan domain has natural and anthropogenic emissions based on the TNO emission inventory of 2003. The high-resolution CAMx simulations reveal consistent spatial and temporal patterns with the OMI/Aura data. The annual spatial correlation coefficient between OMI and CAMx computed in this high spatial resolution analysis is of the order of 0.6, somewhat improved over those estimated in Zyrichidou et al. (2009) (R ˜ 0.5). However, in such a validation study it is important to take into account the averaging kernel (AK) information in order to achieve the creation of comparable data sets. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of limiting the effect of the a priori profile on the comparison is on average small. The main aim of the paper, which was to evaluate OMI retrieved and high resolution simulated tropospheric NO2 column densities over South-Eastern Europe and to assess the use of the averaging kernels, is achieved and the two data sources are being employed further in an inverse emission inventory creation study (Zyrichidou et al., in preparation)

Evaluation of high resolution simulated and OMI retrieved tropospheric NO2 column densities over South-Eastern Europe

High resolution model estimates (10 × 10 km2) of tropospheric NO2 column amounts from the Comprehensive Air Quality Model (CAMx) for the Balkan Peninsula are compared with OMI/Aura measurements (13 × 24 km2 at nadir) for the year April 2009 to March 2010. The Balkan area contributes significantly to the NO2 burden in European air and so numerous urban, industrial and rural regions are studied aiming to investigate the consistency of both satellite retrievals and model predictions at high spatial resolution. It has already been shown that OMI can detect the tropospheric column of NO2 over polluted Balkan cities due to its fine horizontal resolution and instrument sensitivity (Zyrichidou et al., 2009). In this study the improved OMI DOMINO v2.0 satellite retrievals showed that over South-Eastern Europe the monthly mean NO2 tropospheric column density fluctuated between 2.0 and 5.7 ± 1.1 × 1015 molecules/cm2 over urban areas, 1.6–5.0 ± 0.7 × 1015 molecules/cm2 over large industrial complexes and 1.1–2.2 ± 0.4 × 1015 molecules/cm2 over rural areas for the year studied. The Comprehensive Air Quality Model with extensions (CAMx) version 4.40 is a publicly available open-source computer modeling system for the integrated assessment of gaseous and particulate air pollution. The anthropogenic emissions used in CAMx for the Greek domain being studied were compiled employing bottom-up approaches (road transport sector, off-road machinery, etc.) as well as other national registries and international databases. The rest of the Balkan domain has natural and anthropogenic emissions based on the TNO emission inventory of 2003. The high-resolution CAMx simulations reveal consistent spatial and temporal patterns with the OMI/Aura data. The annual spatial correlation coefficient between OMI and CAMx computed in this high spatial resolution analysis is of the order of 0.6, somewhat improved over those estimated in Zyrichidou et al. (2009) (R ˜ 0.5). However, in such a validation study it is important to take into account the averaging kernel (AK) information in order to achieve the creation of comparable data sets. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of limiting the effect of the a priori profile on the comparison is on average small. The main aim of the paper, which was to evaluate OMI retrieved and high resolution simulated tropospheric NO2 column densities over South-Eastern Europe and to assess the use of the averaging kernels, is achieved and the two data sources are being employed further in an inverse emission inventory creation study (Zyrichidou et al., in preparation)

Updated SO₂ emission estimates over China using OMI/Aura observations

The main aim of this paper is to update existing sulfur dioxide (SO2) emission inventories over China using modern inversion techniques, state-of-the-art chemistry transport modelling (CTM) and satellite observations of SO2. Within the framework of the EU Seventh Framework Programme (FP7) MarcoPolo (Monitoring and Assessment of Regional air quality in China using space Observations) project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, 10 years of Ozone Monitoring Instrument (OMI)/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied (15–55° N, 102–132° E) from 26.30 to 32.60 Tg annum−1, with positive updates which are stronger in winter ( ∼  36 % increase). New source areas were identified in the southwest (25–35° N, 100–110° E) as well as in the northeast (40–50° N, 120–130° E) of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the a posteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg annum−1 of SO2 emissions. When studying the entire OMI/Aura time period (2005 to 2015), it was shown that the SO2 emissions remain nearly constant before the year 2010, with a drift of −0.51 ± 0.38 Tg annum−1, and show a statistically significant decline after the year 2010 of −1.64 ± 0.37 Tg annum−1 for the entire domain. Similar findings were obtained when focusing on the greater Beijing area (30–40° N, 110–120° E) with pre-2010 drifts of −0.17 ± 0.14 and post-2010 drifts of −0.47 ± 0.12 Tg annum−1. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China, which also includes updated NOx, volatile organic compounds and particulate matter emissions

Evaluating a new homogeneous total ozone climate data record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality ozone data products generated from different satellite sensors. For total ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the total ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI total ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Système D′Analyse par Observations Zénithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 total ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI total ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 ± 1% level for all three sensors while the near-zero decadal stability of the total ozone columns (TOCs) provided by the three European instruments falls well within the 1–3% requirement of the European Space Agency's Ozone Climate Change Initiative project

Identification of surface NO<SUB>x</SUB> emission sources on a regional scale using OMI NO<SUB>2</SUB>

International audienceIn this study, an inverse modeling technique is applied to obtain, at a regional scale, top-down emission estimates for nitrogen oxides utilizing tropospheric nitrogen dioxide (NO2) columns retrieved by the OMI/Aura instrument and estimated by the Comprehensive Air Quality Model with extensions (CAMx). The main idea, applied previously using models with coarse spatial resolution, is to combine the a priori information from the bottom up emission inventory used in an air quality simulation that covers the Balkan peninsula in a high resolution grid (0.1° × 0.1°) with the tropospheric NO2 quantities estimated for one complete year by CAMx and the tropospheric NO2 columns retrieved by satellite observations in order to identify missing emissions sources on a regional scale. The results have identified biases between the a priori and a posteriori emission inventories due to the missing emission sources or over-estimation of the spread and quantity of certain emission sources. In such a fine resolution grid we have also analyzed and considered the horizontal transport on the a posteriori NOx emissions. The deduced a posteriori NOx emissions, dominated by the fossil fuel emissions, were found to be1.11 ± 0.30 Tg N/y, compared to 0.87 ± 0.43 Tg N/y found in the a priori Balkan emission inventory. Soil emissions over the extended Greek domain, omitted in the a priori inventory, were estimated to account for almost 20% of the total emitted amount, while for the year 2009 the biomass burning NOx emission flux was also estimated and the average rate accounted for 0.5 × 10-6 Tg N/km2

The operational Near-Real-Time Total Ozone Retrieval Algorithm for GOME-2 on MetOp-A & MetOp-B and perspectives for TROPOMI/S5P

The Montreal Protocol and its amendments were designed to reduce the production and consumption of ozone depleting substances and thereby introducing l a gradual recovery of the Earth´s fragile ozone layer. However, the exact timing of the expected ozone recovery and the inter-relationship between the ozone layer and on-going climate change are still under investigation. Therefore, long-term satellite total ozone datasets of high accuracy and stability are essential for monitoring the evolution of the stratospheric ozone layer. The TROPOMI (Tropospheric Monitoring Instrument) is the payload instrument for the Sentinel 5 Precursor (S5P) mission which will provide atmospheric composition products including ozone during the time frame from 2016 to 2022. It will consequently extend the data record initiated with GOME/ERS-2 and continued with the SCIAMACHY/ENVISAT, OMI/AURA and GOME-2/MetOp missions. Here we present the Near-Real-Time (NRT) TROPOMI/S5P total ozone retrieval algorithm which is based on the "DOAS-style" GOME Data Processor (GDP) algorithm Version 4.x. The DOAS technique for total ozone retrieval was deployed from the start of the GOME/ERS-2 mission in 1995 and is currently being used for the generation of the ESA SCIAMACHY and EUMETSAT O3M-SAF GOME-2 operational products. The enhancements in GDP 4.8 (the latest version of the GDP 4.x algorithm) are described first, and then we present the Global validation results for GOME-2/MetOp-A (GOME-2A) and GOME-2/MetOp-B (GOME-2B) total ozone measurements using Brewer and Dobson measurements as references. It is concluded that total ozone columns (TOCs) retrieved from GOME-2 using GDP 4.8 show very good agreement with ground-based measurements. TOCs from GOME-2A and GOME-2B are consistent with each other and may be used simultaneously without introducing trends or other systematic effects. One of the major challenges for the operational processing of TROPOMI/S5P measurements is the high data rate - two orders of magnitude more data than that from GOME-2. Here we discuss performance enhancements of the retrieval algorithms such as the development of an acceleration method for Radiative Transfer Model (RTM) simulations. GOME-2A and GOME-2B total ozone data have been used operationally in the Copernicus atmospheric service project MACC-II/III (Monitoring Atmospheric Composition and Climate - Interim Implementation) NRT system since October 2013 and May 2014 respectively. It is expected that the follow-on Copernicus Atmosphere Monitoring Service (CAMS) project will use NRT TROPOMI/S5P in addition to GOME-2 total ozone data

Comparisons of ground-based tropospheric NO₂ MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2

Investigating the GOME-2/Metop-A Total Sulphur Dioxide Load with the Aid of Chemical Transport Modelling over the Balkan Region

The current discerning capability of nadir viewing satellite instruments is mainly providing information on large volcanic events, such as the Kasatochi 2008 and the Eyjafjöll 2010 eruptions, and areas with high anthropogenic SO2 sources such as Peruvian smeltering regions. Consequently, there exists a constant need to improve the algorithms in order to provide satellite information on the megacities’ SO2 levels for air quality purposes. In the current study, we aim to assess the observational capability of the GOME2/MetopA instrument by analysing the total SO2 load estimated over the extended Balkan region with the use of the high spatial resolution Comprehensive Air Quality Model with extensions (CAMx) modelling results. Two years of satellite and modelling estimates have been analysed so as to pin-point locations of constantly high SO2 loading, locations with a marked seasonal variability as well as locations with high expected loading that might not be visible from the satellite orbit. Regions of specific interest will be chosen for further investigation and algorithm development based on updated modelling input parameters such as the SO2 loading profile