Abstract
Long-term nitrogen dioxide (NO2) slant column density measurements using the MAX-DOAS (multi-axis differential optical absorption spectroscopy) technique were analyzed in order to demonstrate the temporal and horizontal variability of the trace gas in Athens for the period October 2012–July 2017. The synergy with in situ measurements and model simulations was exploited for verifying the MAX-DOAS technique and its ability to assess the spatiotemporal characteristics of NO2 pollution in the city. Tropospheric NO2 columns derived from ground-based MAX-DOAS observations in two horizontal and five vertical viewing directions were compared with in situ chemiluminescence measurements representative of urban, urban background and suburban conditions; a satisfactory correlation was found for the urban (r ≈ 0.55) and remote areas (r ≈ 0.40). Mean tropospheric slant columns retrieved from measurements at the lowest elevation over the urban area ranged from 0.1 to 32 × 1016 molec cm−2. The interannual variability showed a rate of increase of 0.3 × 1016 molec cm−2 per year since 2012 in the urban area, leading to a total increase of 20%. The retrieved annual cycles captured the seasonal variability with lower NO2 levels in summer, highly correlated (r ≈ 0.85) with the urban background and suburban in situ observations. The NO2 diurnal variation for different seasons exhibited varied patterns, indicating the different role of photochemistry and anthropogenic activities in the different seasons. Compared to in situ observations, the MAX-DOAS NO2 morning peak occurred with a one-hour delay and decayed less steeply in winter. Measurements at different elevation angles are shown as a primary indicator of the vertical distribution of NO2 at the urban environment; the vertical convection of the polluted air masses and the enhanced NO2 near-surface concentrations are demonstrated by this analysis. The inhomogeneity of the NO2 spatial distribution was shown using a relevant inhomogeneity index; greater variability was found during the summer period. Comparisons with city-scale model simulations demonstrated that the horizontal light path length of MAX-DOAS covered a distance of 15 km. An estimation of urban sources’ contribution was also made by applying two simple methodologies on the MAX-DOAS measurements. The results were compared to NO2 predictions from the high resolution air quality model to infer the importance of vehicle emissions for the urban NO2 levels; 20–35% of the urban NO2 was found to be associated with road transport.
Highlights
Nitrogen dioxide (NO2) constitutes an important tropospheric gaseous pollutant present in abundance in urban environments and affecting human health
For the evaluation of the MAX-DOAS measurements, the retrieved data sets were compared to in situ observation data acquired from three in situ monitoring stations located in an urban, urban background and suburban sites (Figure 1)
Tropospheric slant column densities of NO2 from MAX-DOAS measurements for the period October 2012 to July 2017 over Athens, Greece, were retrieved in order to be compared to near-surface NO2 measurements from chemiluminescence monitors
Summary
Nitrogen dioxide (NO2) constitutes an important tropospheric gaseous pollutant present in abundance in urban environments and affecting human health. The city of Athens ranks as the third worst among 25 European cities in terms of air pollution [4] and exceedances in NO2 are recorded regularly [5]. Athens ranks 16th out of 858 European cities in terms of mortality linked to NO2 pollution [6]. The main air pollution sources in Athens are road transport, domestic heating, the industrial area on the southwest side of the city and the port located on the south of the city center [7,8]. Road transport has been found to contribute to over 50% of NOx emissions in the urban environment of Athens [9]. As NO2 is an important parameter of urban air quality, several studies based on in situ NO2 measurements have been carried out in Athens since 1980, e.g., [10,11,12], and recent studies have used ground-based remote sensing techniques, such as lidar and active long path DOAS, e.g., [13,14]
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