I. Zyrichidou

Attribution of the Arctic ozone column deficit in March 2011

Arctic column ozone reached record low values (∼310 DU) during March of 2011, exposing Arctic ecosystems to enhanced UV-B. We identify the cause of this anomaly using the Oslo CTM2 atmospheric chemistry model driven by ECMWF meteorology to simulate Arctic ozone from 1998 through 2011. CTM2 successfully reproduces the variability in column ozone, from week to week, and from year to year, correctly identifying 2011 as an extreme anomaly over the period. By comparing parallel model simulations, one with all Arctic ozone chemistry turned off on January 1, we find that chemical ozone loss in 2011 is enhanced relative to previous years, but it accounted for only 23% of the anomaly. Weakened transport of ozone from middle latitudes, concurrent with an anomalously strong polar vortex, was the primary cause of the low ozone When the zonal winds relaxed in mid-March 2011, Arctic column ozone quickly recovered.

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

The European Space Agencys 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)/Systeme D′Analyse par Observations Zenithales (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 Agencys Ozone Climate Change Initiative project.

Ozone and Spectroradiometric UV Changes in the Past 20 Years over High Latitudes

Abstract This study analyzes changes in solar ultraviolet (UV) irradiances at 305 and 325 nm at selected sites located at high latitudes of both hemispheres. Site selection was restricted to the availability of the most complete UV spectroradiometric datasets of the past twenty years (1990–2011). The results show that over northern high latitudes, between 55° and 70°N, UV irradiances at 305 nm decreased significantly by 3.9% per decade, whereas UV irradiance at 325 nm remained stable with no significant long-term change. Over southern high latitudes (55°–70°S), UV irradiances did not show any significant long-term changes at either 305 or 325 nm. Changes in solar UV irradiances are discussed in the context of long-term ozone and other atmospheric parameters affecting UV variability at ground level.

Phaethon: A System for the Validation of Satellite Derived Atmospheric Columns of Trace Gases

Phaethon is a system for the retrieval of column densities of various atmospheric gases from the ground by applying the technique of Differential Optical Absorption Spectroscopy on direct sun and sky radiance spectral measurements. The system comprises a spectrograph with a CCD detector operating in the wavelength range 300–650 nm, the entrance optics with a field of view of 1°, equipped with a filter wheel, a temperature stabilization unit, and a solar tracker. The Phaethon system was validated against a MAX-DOAS system during a campaign at the High Altitude Research Station Jungfraujoch. The comparison of differential slant column densities derived from off-axis measurements showed an average agreement of 5–10% (±5%) depending on the viewing angle for NO2, and 15–25% for O4 (±2% for viewing angles <8°). Following the validation of Phaethon, direct solar irradiance and sky radiance spectral measurements are regularly performed at Thessaloniki, Greece, to derive atmospheric columns of various trace gases. The retrieved atmospheric columns of total and tropospheric NO2 were compared to GOME-2 products revealing large discrepancies which are attributed to the large spatial variability of NO2 due to the localized air pollution sources over the area.

Top-Down SO 2 Emissions Over China; A Satellite Approach

With the rapid development of the Chinese economy since 2000, sulfur dioxide, SO2, emissions from China have been of increasing global concern. There have been indications that the emission growth rate slowed around 2005 and that emissions began to decrease after 2006, mainly due to the wide application of flue-gas desulfurization devices in power plants. However due to the differences in growth rate among the many Chinese Provinces, it remains to be seen whether this decreasing trend can be verified for the entire domain. In this study we use space-based observations of SO2 columns from the Ozone Monitoring Instrument on board the Aura satellite, OMI/Aura, to derive monthly top-down SO2 emissions over China via inverse modeling with the CHIMERE chemical transport model. The driving SO2 emissions have been provided by the Multi-resolution Emission Inventory for China (MEIC) model. In MEIC, the SO2 sources are further partitioned among industry, power and residential provenances. This study aims at providing updated SO2 emissions, based on satellite observations, which may later be used to update existing chemical transport model results.

Comparison of Ground-Based Tropospheric NO 2 Columns with OMI/Aura Products in the Greater Area of Thessaloniki by Means of an Air Quality Modeling Tool

Phaethon is a ground-based MAX-DOAS system, easily deployed at different locations to address specific air quality problems and support satellite validation studies. Three Phaethon systems have been deployed at different sites in the greater area of Thessaloniki, characterized by diverse local pollution levels representing urban, suburban and rural conditions, aiming at linking tropospheric trace-gas modeling with satellite products. Tropospheric NO2 columns derived at these sites located within an area of about 15 by 30 km, comparable to the size of OMI/Aura pixel, are compared with the satellite retrievals. The OMI/Aura products underestimate the NO2 in the city centre, representing the average pollution levels in the sub-satellite pixel area which, in the case of Thessaloniki, corresponds mostly to rural conditions. In order to minimize the collocation differences in spatial distribution between satellite and ground-based measurements, the former are adjusted by factors that are calculated by means of a high resolution air quality modeling tool, consisting of WRF meteorological model and CAMx air quality model. This approach shows significant improvement in the comparisons between ground-based and satellite-derived observations.

Investigating the Impact of the Economic Recession Over Mediterranean Urban Regions on Satellite-Based Formaldehyde Columns; Comparison with Chemistry Transport Model Results

Formaldehyde (CH2O) is an important indicator of tropospheric hydrocarbon emissions and photochemical activity. CH2O is a high-yield intermediate product from the oxidation of Non-Methane Volatile Organic Compounds (NMVOCs) emitted by anthropogenic, biogenic, and biomass burning activities. For the past 30 years CH2O can be measured from space in the near-UV by solar backscatter instruments. An increased trend in CH2O over big cities around the Mediterranean has been observed from space since the beginning of the financial crisis. This fact could be associated with the enhanced use of wood and pellets for domestic/central heating during cold days, diesel being over-taxed and hence too expensive. This change on the fuel type, apart from more frequent PM10 episodes, is also reflected in CH2O emissions. We use satellite measurements to study the temporal variability of the winter-months CH2O column in order to ascertain the increased biomass burning emissions in urban areas which contribute to elevated levels of smog. We also validate the satellite retrievals using a chemistry transport model and test the ability of observations to reproduce geographical and seasonal variability in CH2O emissions over the Southern Europe.

MAX-DOAS NO 2 observations over Guangzhou, China; ground-based and satellite comparisons

In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOpA, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF≤ 0.3 and CF≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity (∼ 0.98) and the mean satellite underestimation is reduced to about half (from ∼ 7 to ∼ 3.5× 1015 molecules cm−2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤ 50 km) to 0.953 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km).

Compilation of a NOx Emission Inventory for the Balkan Region Using Satellite Tropospheric NO2 Columns

The important improvements in the quality of space-born tropospheric trace gas estimates have permitted their use, in combination with inverse atmospheric modelling, to obtain evolved top-down pollutant emission estimates. In this study, inverse modeling is applied to the case of tropospheric nitrogen dioxide (NO2) columns as seen by the OMI/Aura instrument and estimated by the Comprehensive Air Quality Model with extensions (CAMx). The main idea is to use the a priori information from the bottom up emission inventory used in the CAMx model, the tropospheric NO2 quantities estimated by the CAMx runs and the tropospheric NO2 columns deduced by the satellite observations to create an a posteriori NOx emission inventory. This new inventory, constrained in the top-down manner by the satellite estimates, can be used anew in the CAMx model to produce a new modeled NOx product. This work has identified biases in the original emission inventory for instance due to missing emission sources or over-estimation of the spread of emission sources and has proved an improved bottom-up emissions inventory.

Investigating the GOME2/MetopA 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 Eyjafjoll 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.