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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Monitoring of NO2 emission at Russian cities scale using TROPOMI (Sentinel-5P) data</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Anna M. Konstantinova</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Alexei A. Bril</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Space Research Institute of the Russian Academy of Sciences (IKI RAS)</institution>
          ,
          <addr-line>Moscow</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <fpage>476</fpage>
      <lpage>483</lpage>
      <abstract>
        <p>The paper presents products on gas components, created in the archives of the Center for Collective Use “IKI-Monitoring” and available in information services, developed at the IKI RAS. The features of constructing composite images of diferent time duty cycle with average, minimum and maximum values of the products are described. Approaches to the analysis of nitrogen dioxide concentration in Russian cities based on the data of the TROPOMI Sentinel-5P device are presented, seasonal and interannual trends in concentration are revealed.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Remote sensing</kwd>
        <kwd>data processing</kwd>
        <kwd>satellite data</kwd>
        <kwd>environment</kwd>
        <kwd>gas components</kwd>
        <kwd>air pollution</kwd>
        <kwd>nitrogen dioxide</kwd>
        <kwd>“IKI-Monitoring” Center for Collective Use</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>natural processes such as forest fires, lightning, etc. In large cities, the main source of nitrogen
dioxide is combustion products from vehicles and thermal power plants, and nitrogen dioxide is
a good indicator for assessing the state of urban air quality. At the same time, the lifetime of
this gas is relatively short, on the order of several hours, which, in a first approximation, makes
it possible to use satellite data to obtain actual values of its concentrations in the tropospheric
column and to monitor air pollution without access to the territory, and to form an independent
global picture.</p>
      <p>
        With the help of the automated tool for monitoring the state of objects ObjectsSurveysSMIS [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ],
developed at the IKI RAS, and based on the created composite images, the average values of
the concentration of this gas within large cities of Russia were calculated, including within the
sectors of circles with a large radius of influence of these cities. The following chapters are
devoted to the peculiarities of the construction of information products on gas components
and the analysis of the obtained results of the analysis of nitrogen dioxide on the scale of large
cities.
      </p>
    </sec>
    <sec id="sec-2">
      <title>2. Available satellite data</title>
      <p>
        In April 2018, as part of the Copernicus program, the European space agency ESA launched the
Sentinel-5P satellite. The satellite is equipped with a TOPOMI instrument with a spatial
resolution of 3.5 by 7 km. (Tropospheric Monitoring Instrument), which measures the concentration
of gas components in the atmosphere. The purpose of the TROPOMI instrument is to provide
accurate and timely observations of the key elements of the atmospheric composition for
monitoring air quality, climate and ozone layer. TROPOMI data is provided by the ESA Copernicus
Open Access Hub [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]. In 2004, NASA launched the AURA research satellite, designed to study
the Earth’s atmosphere. The satellite has an OMI device with a spatial resolution of 13 by 24 km,
the main task of which is to control climate change on Earth, air pollution, and the state of the
Earth’s ozone layer. OMI data is provided by the NASA Level-1 and Atmosphere Archive and
Distribution System Distributed Active Archive Center (LAADS DAAC) [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
      <p>Figure 1 shows the data coverage area by TROPOMI and OMI for one day. To monitor and
analyze the dynamics of the state of the atmosphere based on the daily incoming data on the
a
b
concentration of gases in the atmosphere, composite images of various temporal resolutions are
automatically created: daily, weekly, monthly, annual and long-term. Users of the Vega-Science
IS have access to the averaged, maximum and minimum concentration data for each type of gas
available in the archives of the IKI-Monitoring Center for Collective Use. Figures 2 and 3 show
examples of calculated information products.</p>
    </sec>
    <sec id="sec-3">
      <title>3. Instrument</title>
      <p>At IKI RAS, an automated tool for monitoring the state of objects ObjectsSurveysSMIS was
developed, which allows calculating the averaged values of various indicators (thematic products,
spectral indices, channel data) along the contours of arbitrary polygons of the objects under
study based on the satellite data scenes available in the archives of the IKI-Monitoring Center
for Collective Use, historical and operational. With the help of this tool, integrated into the
Vega-Science information system, the concentrations of nitrogen dioxide over the territory
of large cities of Russia were calculated. Figure 4 shows a specialized section for working
with objects (cities) and indicators calculated for them in the Vega-Science IS, an example of
establishing a zone of influence of a pollution source (city) with an indication of the radius of
influence and subsequent division of the zone into sectors and moving away from the center of
the ring is given.</p>
      <p>After automated calculations, it is possible to visualize the values of indicators on the map,
including by sectors and rings. For greater contrast, you can “renormalize” the values of the
indicator within the area of influence, that is, apply the original palette of the thematic product
relative to the local minimum and maximum (Figure 4). To identify seasonal and interannual
trends in the values of indicators, as well as for the joint analysis of several objects (cities), a
module for analyzing the time series of objects and uploading the calculated values to tabular
interfaces is available.</p>
      <p>As a result of the study, 15 cities of Russia, located in diferent federal districts, were delineated.
The cities were selected visually from the constructed annual composite image with the average
concentration of nitrogen dioxide of the TROPOMI device (Sentinel-5P). Within the framework
of this experiment, cities with the maximum average annual emissions of nitrogen dioxide
were taken. To assess the air quality, a polygon was set up directly above the city’s territory,
corresponding to the city’s territory according to MSI high-resolution data (Sentinel-2A, B).
To analyze the distribution of gas around cities and identify the most polluted areas, zones
of influence with a radius of 100 km were set up, the concentration of nitrogen dioxide was
calculated for a fixed number of sectors (45 degrees each).</p>
    </sec>
    <sec id="sec-4">
      <title>4. Examples</title>
      <p>This section provides examples of approaches to monitoring nitrogen dioxide in selected cities
of Russia. First of all, on the basis of the created composite images, the average annual
concentrations of nitrogen dioxide over the territories of cities were calculated since the launch of
TROPOMI (Sentinel-5P) to the present. Table 1 presents the calculation results, cities are sorted
in descending order of nitrogen dioxide emissions, taking into account the entire observation
period.</p>
      <p>The table clearly shows that the same trends are observed for some cities. For large cities
located in the European part of Russia, there is a predominantly decrease in the concentration
of nitrogen dioxide from 2018 to 2020, while almost all cities located in Siberia are growing. The
study of the reasons for the obtained trends requires a more detailed analysis and research with
the connection of climatic indicators and is not considered in this work.</p>
      <p>Since the cities in the Siberian part of Russia have a similar distribution of nitrogen dioxide
concentration, they were combined into a group for analyzing the concentration on a monthly
basis. The graphs in Figure 5 show the intra-annual course of nitrogen dioxide concentration for
2019 and 2020. In almost all cities, a seasonal change in concentration is observed: a decline in
the summer months and an increase in the autumn-winter period, which is presumably related
to the heating season and also requires a separate study. To confirm this assumption, small
areas of sparsely populated and unpopulated areas were delineated.</p>
      <p>In Figure 6 shows a comparison of monthly concentrations of nitrogen dioxide for 2020 over
the territories of Moscow and Novokuznetsk with the concentrations of sparsely populated
areas near these cities. It is clearly seen from the graphs that the gas concentration outside
urban areas remains practically unchanged throughout the year.
Average NO2, micromol/m2
2018 2019 2020
136.34
103.52
92.57
81.83
66.82
72.25
68.40
64.84
54.22
52.15
57.45
45.33
46.23
41.65
44.40</p>
      <p>To analyze the distribution of emissions from large cities, the concentrations of nitrogen
dioxide were calculated by sectors within the 100-kilometer zone. Figure 7 shows the average
monthly concentration of dioxide for the 2019 season by sector around Moscow. From the
presented graph it can be seen that in the summer months in all directions from the city center,
the concentrations are approximately equal, while in winter, in some directions, there is a
decrease in concentration (mainly in the West and South-West), and in some — an increase in
concentrations (East and Northeast), which also indicates the presence of a seasonal trend and
significant wind drift of nitrogen dioxide emissions.</p>
      <p>Also, based on monthly data, studies were conducted on how restrictive measures on
movement and anthropogenic activities during the spread of Covid-19 afected nitrogen dioxide
emissions in large cities. In some cities, there is a significant drop in nitrogen dioxide
concentration in April-May 2020, apparently related to the restrictive measures for Covid-19. For
example, in Moscow, the oficial lockdown lasted from March 30, and on June 9, digital passes
were canceled. Figure 8 shows graphs of nitrogen dioxide emissions for several representative
cities for 2019 and 2020.</p>
    </sec>
    <sec id="sec-5">
      <title>5. Conclusions</title>
      <p>Thus, we can say that the presence in the archives of the IKI-Monitoring Center for Collective
Use of data on the concentration of the main gases in various layers of the atmosphere using
the TROPOMI (Sentinel-5P) and OMI (AURA) instruments allows solving quite a variety of
tasks related to monitoring the state of the atmosphere.</p>
      <p>Using nitrogen dioxide as an example, we see that the created TROPOMI data information
products (Sentinel-5P) and a set of tools for observing objects in a first approximation can become
the basis for monitoring atmospheric pollution with this gas within large cities. The results
obtained clearly show seasonal trends and a decrease in nitrogen dioxide emissions during the
period of restrictive measures is observed. For a more detailed analysis, it is necessary to take
into account the meteorological conditions, the relief, the wind rose in the entire tropospheric
column, and the presence of local sources of nitrogen dioxide emissions.</p>
    </sec>
    <sec id="sec-6">
      <title>Acknowledgments</title>
      <p>
        The reported study was funded by RFBR, project No. 19-37-90114 using resources of the
“IKIMonitoring” Center for Collective Use [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
      </p>
    </sec>
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