Assessment of NO2 Pollution Level during the COVID-19 Lockdown in a Romanian City.

This study investigates changes in pollution associated with the lockdown period caused by the COVID-19 pandemic in Galati (45.43° N, 28.03° E), a Romanian city located in the southeast of Romania. The study is focused on nitrogen dioxide (NO2), a trace gas which can be related to emissions from industrial activities, heating, and transportation. The investigation is based on in situ observations from local Air Quality Monitoring Stations (AQMS) and mobile remote sensing observations by Differential Optical Absorption Spectroscopy (DOAS) technique. We also show results of the NO2 vertical column measured by TROPOMI (TROPOspheric Monitoring Instrument), a space instrument onboard of satellite mission Sentinel-5P, to complement local ground-based measurements. For in situ observations, the lockdown interval (23 March 2020-15 May 2020) was separated from normal periods. The decrease in local NO2 concentration during lockdown, measured in situ, is rather small, of about 10-40% at the most, is observed only at some stations, and is better seen during workdays than during weekends. We conclude that the decrease in NO2 content over Galati city during lockdown is relatively small and may be attributed to the reduction in local traffic, a consequence of special measures and restrictions imposed during the COVID-19 lockdown by the Romanian authorities.

NILU-UV multi-filter radiometer total ozone columns: Comparison with satellite observations over Thessaloniki, Greece.

This study aims to construct and validate a neural network (NN) model for the production of high frequency (~1min) ground-based estimates of total ozone column (TOC) at a mid-latitude UV and ozone monitoring station in the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki (LAP/AUTh) for the years 2005-2014. In the first stage of model development, ~30,000 records of coincident solar UV spectral irradiance measurements from a Norsk Institutt for Luftforskning (NILU)-UV multi-filter radiometer and TOC measurements from a co-located Brewer spectroradiometer are used to train a NN to learn the nonlinear functional relation between the irradiances and TOC. The model is then subjected to sensitivity analysis and validation. Close agreement is obtained (R2=0.94, RMSE=8.21 DU and bias=-0.15 DU relative to the Brewer) for the training data in the correlation of NN estimates on Brewer derived TOC with 95% of the coincident data differing by less than 13 DU. In the second stage of development, a long time series (≥1 million records) of high frequency (~1min) NILU-UV ground-based measurements are presented as inputs to the NN model to generate high frequency TOC estimates. The advantage of the NN model is that it is not site dependent and is applicable to any NILU input data lying within the range of the training data. GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura and GOME2/MetOp-A TOC records are then used to perform a precise cross-validation analysis and comparison with the NILU TOC estimates over Thessaloniki. All 4 satellite TOC dataset are retrieved using the GOME Direct Fitting algorithm, version 3 (GODFIT_v3), for reasons of consistency. The NILU TOC estimates within ±30min of the overpass times agree well with the satellite TOC retrievals with coefficient of determination in the range 0.88≤R2≤0.90 for all sky conditions and 0.95≤R2≤0.96 for clear sky conditions. The mean fractional differences are found to be -0.67%±2.15%, -1.44%±2.25%, -2.09%±2.06% and -0.85%±2.19% for GOME, SCIAMACHY, OMI and GOME2 respectively for the clear sky cases. The near constant standard deviation (~±2.2%) across the array of sensors testifies directly to the stability of both the GODFIT_v3 algorithm and the NN model for providing coherent and robust TOC records. Furthermore, the high Pearson product moment correlation coefficients (0.94

Measurements of tropospheric NO2 in Romania using a zenith-sky mobile DOAS system and comparisons with satellite observations.

In this paper we present a new method for retrieving tropospheric NO2 Vertical Column Density (VCD) from zenith-sky Differential Optical Absorption Spectroscopy (DOAS) measurements using mobile observations. This method was used during three days in the summer of 2011 in Romania, being to our knowledge the first mobile DOAS measurements peformed in this country. The measurements were carried out over large and different areas using a mobile DOAS system installed in a car. We present here a step-by-step retrieval of tropospheric VCD using complementary observations from ground and space which take into account the stratospheric contribution, which is a step forward compared to other similar studies. The detailed error budget indicates that the typical uncertainty on the retrieved NO2tropospheric VCD is less than 25%. The resulting ground-based data set is compared to satellite measurements from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2). For instance, on 18 July 2011, in an industrial area located at 47.03°N, 22.45°E, GOME-2 observes a tropospheric VCD value of (3.4 ± 1.9) × 1015 molec./cm2, while average mobile measurements in the same area give a value of (3.4 ± 0.7) × 10(15) molec./cm2. On 22 August 2011, around Ploiesti city (44.99°N, 26.1°E), the tropospheric VCD observed by satellites is (3.3 ± 1.9) × 10(15) molec./cm2 (GOME-2) and (3.2 ± 3.2) × 10(15) molec./cm2 (OMI), while average mobile measurements give (3.8 ± 0.8) × 10(15) molec./cm2. Average ground measurements over "clean areas", on 18 July 2011, give (2.5 ± 0.6) × 10(15) molec./cm2 while the satellite observes a value of (1.8 ± 1.3) × 10(15) molec./cm2.

Modeling dynamic exchange of gaseous elemental mercury at polar sunrise.

At polar sunrise, gaseous elemental mercury (GEM) undergoes an exceptional dynamic exchange in the air and at the snow surface during which GEM can be rapidly removed from the atmosphere (the so-called atmospheric mercury depletion events (AMDEs)) as well as re-emitted from the snow within a few hours to days in the Polar Regions. Although high concentrations of total mercury in snow following AMDEs is well documented, there is very little data available on the redox transformation processes of mercury in the snow and the fluxes of mercury at the air/snow interface. Therefore, the net gain of mercury in the Polar Regions as a result of AMDEs is still an open question. We developed a new version of the global mercury model, GRAHM, which includes for the first time bidirectional surface exchange of GEM in Polar Regions in spring and summer by developing schemes for mercury halogen oxidation, deposition, and re-emission. Also for the first time, GOME satellite data-derived boundary layer concentrations of BrO have been used in a global mercury model for representation of halogen mercury chemistry. Comparison of model simulated and measured atmospheric concentrations of GEM at Alert, Canada, for 3 years (2002-2004) shows the model's capability in simulating the rapid cycling of mercury during and after AMDEs. Brooks et al. (1) measured mercury deposition, reemission, and net surface gain fluxes of mercury at Barrow, AK, during an intensive measurement campaign for a 2 week period in spring (March 25 to April 7, 2003). They reported 1.7, 1.0 +/- 0.2, and 0.7 +/- 0.2 microg m(-2) deposition, re-emission, and net surface gain, respectively. Using the optimal configuration of the model, we estimated 1.8 microg m(-2) deposition, 1.0 microg m(-2) re-emission, and 0.8 microg m(-2) net surface gain of mercury for the same time period at Barrow. The estimated net annual accumulation of mercury within the Arctic Circle north of 66.5 degrees is approximately 174 t with +/-7 t of interannual variability for 2002-2004 using the optimal configuration. We estimated the uncertainty of the model results to the Hg/Br reaction rate coefficient to be approximately 6%. Springtime is clearly demonstrated as the most active period of mercury exchanges and net surface gain (approximately 46% of annual accumulation) in the Arctic.

GOME level 1-to-2 data processor version 3.0: a major upgrade of the GOME/ERS-2 total ozone retrieval algorithm.

The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME data processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between -2% and +4% of ground-based values for moderate solar zenith angles lower than 70 degrees. A larger variability of about +5% and -8% is observed for higher solar zenith angles up to 90 degrees.