<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Software for Modelling the Air Pollution by Vehicles</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Vasyl Tymchyshyn</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Natalia Porplytsya</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Andriy Melnyk</string-name>
          <email>melnyk.andriy@gmail.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Bohdan Tymchyshyn</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>ІІ. METHODS FOR MEASURING THE</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Department of Computer Science, Ternopil National Economic University, UKRAINE</institution>
          ,
          <addr-line>Ternopil, 8 Chekhova str.</addr-line>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2018</year>
      </pub-date>
      <fpage>1</fpage>
      <lpage>3</lpage>
      <abstract>
        <p>In this work the issues of the ecological safety of motor transport, the impact of motor vehicles on the environment are highlighted. Directions and measures concerning the raised ecological safety of motor transport are determined.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>CONCENTRATIONS OF HARMFUL SUBSTANCES IN
THE NEAR-GROUND LAYER OF THE ATMOSPHERE
There are two main methods of measuring the harmful
substances in the air: chemical analysis and microbiological
analysis.</p>
      <p>The chemical analysis of air provides information on the
qualitative and quantitative composition on the basis of
which it is possible to predict the degree pollution and plan
the implementation of measures to control air quality. Detects
indicators such as dust, sulfur dioxide, nitrogen dioxide,
carbon monoxide, phenol, ammonia, hydrogen chloride,
formaldehyde, benzene, toluene, etc. This technique allows to
determine the presence in the air of volatile organic
compounds with a boiling point of 40 to 250 ° C, affecting
human health (phenols, phthalates, organic acids, aromatic
compounds, ethers, morphine and other compounds - up to
250).</p>
      <p>Microbiological analysis air allows us to establish the
presence of biological aerosols (bacteria and fungi). It is
necessary to conduct detection pathogenic microorganisms
according to such indicators as: total number of
microorganisms, gold staphylococci, mold and yeast. Gas
analysis of air is carried out using a device called a gas
analyzer. Gas analyzer is a measuring device for determining
the qualitative and quantitative composition of gas mixtures.</p>
      <p>Depending on the pressure in the reaction chamber, gas
analyzers of atmospheric and low pressure are distinguished.
Gas analyzers with built-in NO2 / NO converters produce
analytical signals for NO, NOx and NO2 simultaneously or
sequentially. Table 1 gives a comparative characteristics NO2
measuring devices.</p>
    </sec>
    <sec id="sec-2">
      <title>Name</title>
    </sec>
    <sec id="sec-3">
      <title>Dimensions</title>
    </sec>
    <sec id="sec-4">
      <title>Measurement</title>
      <p>error</p>
      <p>DGS-NO
968-037</p>
      <p>2
2100</p>
      <p>Nitrogen dioxide is a toxic substance, which is why the
important task is to control the release this compound.</p>
      <p>Many devices have been developed to measure nitrogen
dioxide, but one of the most effective uses is the use of the
DGS-NO2 968-037 sensor as it many advantages, such as
low price, high resolution etc.</p>
      <p>Fig. 1 shows the general view of the sensor DGS-NO2
968-037.</p>
      <p>Fig.1. General view of the sensor DGS-NO2 968-037</p>
      <p>To collect experimental data on the pollution of air by
harmful emissions of vehicles, the study was conducted at the
crossroads of the streets Za Rudkoyu str. and Chekhova srt.,
because precisely at this point one of the most intense
automobile streams of the "New World" micro district in
Ternopil.</p>
      <p>Experiment date: 27.10.17, time from 14.00 to 15.00, air
temperature 110С, air humidity 74%. For effective
measurement nitrogen dioxide concentration, the sensor
should be located at the point of the road as close as possible
to the asphalt surface, because in this point the concentration
of NO2 is maximal.</p>
      <p>Table 2 shows the averaged NO2 concentrations obtained
over an hour by measuring the concentration of the
DGSNO2 968-037 sensor. The format of the output is: Sensor
number [XXXXXXXXXXX], PPB (Part per billion) [0:
999999], Temperature (0С) [-99:99], RH [0:99], RawSensor
[ADCCount], TempDigital, RHDigital, Day [0:99], Hour
[0:23], Minute [0:59], Second [0:59].
60 3 0,003 0,00608
Note, that the measurements were made at a frequency of
10 seconds, so Figure 3 shows the averaging values of the
concentration of nitrogen dioxide in 10 minutes.</p>
      <sec id="sec-4-1">
        <title>EMISSIONS FROM VEHICLES</title>
        <p>
          Regular measurement of atmospheric pollution by harmful
emissions vehicles and establishment actual concentrations
pollution requires a huge amount resources, in particular gas
analyzers, special equipment for ecological monitoring
systems, which is unrealistic even for countries with high
economic levels and social development. An alternative to
this is the development monitoring systems with
mathematical models in their composition, which, based on a
limited sample data, make it possible to predict time changes
the concentrations harmful emissions. In this case, it is
expedient to use interval discrete dynamic models, and to
identify them based on the analysis of interval data, as shown
in such works [
          <xref ref-type="bibr" rid="ref2 ref3 ref4 ref5">2-5</xref>
          ].
        </p>
        <p>
          In order to construct the model, is necessary a set of
experimental data. Within the scope of work, a mobile
measurement unit, based on a personal computer and a digital
gas sensor type DGS-NO2 968-037, was used for their
obtaining. Measurement was carried out at the crossroads of
the streets Ruska str. - Zamkova str, in Ternopil city every
second. In order to compensate for a random measurement
error, which is normally distributed with zero mathematical
expectation, the measured instantaneous values were
averaged in a window with a duration of 20 minutes. The
fragment measured values of the concentration of nitrogen
dioxide, temperature, humidity and traffic intensity of cars, at
the crossroads of the streets Ruska-Zamkova, Ternopil, with
a discrete of 20 minutes, is given in Table 3.
23:00 0,04608 0,06235 2 77,4495 254
23:20 0,04486 0,06069 2 77,9879 219
23:40 0,04478 0,06059 2 78,3345 196
0:00 0,04419 0,05979 2 78,1432 172
Further, a well-known structural identification method,
built on the basis behavioral models of the bee colony [
          <xref ref-type="bibr" rid="ref6 ref7">6, 7</xref>
          ],
was used to construct a mathematical model for predicting
the concentrations harmful emissions [
          <xref ref-type="bibr" rid="ref8 ref9">8, 9</xref>
          ].
        </p>
        <p>
          The using of the method involves the transformation of
structures of interval discrete models by operators
P(Λ mcn , F ) , Pδ (Λ mcn , F ) , PN (F , I min , I max ) and through
holding selection procedures by operators D1( λ s ,λ s′ ), D2(
λ s , Λ′s ) in order to provide the reduction on each iteration of
the goal function values for optimization task of structural
identification the interval discrete dynamic model[
          <xref ref-type="bibr" rid="ref8">8</xref>
          ].
        </p>
        <p>As a result of using the structural identification method, an
adequate mathematical model for predicting the
concentrations of harmful emissions from vehicles was
obtained:</p>
        <p>vk = 0.0365 + 0.3541⋅ vk −1
+0.118 ⋅ vk −1 ⋅ vk −3 + 0.5059 ⋅ vk −1 ⋅ u3,k / u3,k −1 −
</p>
        <p>
−0.01544 ⋅ vk −2 ⋅ u3,k −1 / u3,k +1 ,
(1)
where k=4…72; vk – the predicted concentration nitrogen
dioxide value in k moment of time; u3 = (u3,0,...,u3,k +1 ) –
known input variables vector (the intensity of traffic flows).</p>
        <p>Note, the concentrations of measured values of harmful
emissions NO2 (at points k = 0 ... 3) should be set as initial
conditions in the interval ± 0,5%, for the modeling with using
linear discrete equation (1).</p>
        <p>As we see, the obtained mathematical model reflects the
dynamics concentrations of nitrogen dioxide, with a discrete
time value 20 minutes. To use it, it is sufficient to set initial
values of the measured concentrations, the temperature and
humidity forecast, which is not a problem at short time
intervals (for example, in the interval of one day). Note that
the finded model can be used to model the concentrations
harmful emissions in other city dots, provided that the
parameters of the model are clarified.</p>
        <p>V. DESIGNING OF THE MONITORING SYSTEM’S</p>
        <p>ARCHITECTURE</p>
        <p>
          Figure 4 shows the developed architecture of the software
system for automation monitoring and visualization pollution
the near-ground layer atmosphere by harmful emissions of
vehicles. As can be seen from the figure in this typical
architecture, there are three logical layers [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ]:
1) user interface (visualization layer);
2) data processing (business logic layer);
3) data access layer.
        </p>
        <p>At the first layer, the modules with which the user works
and which are intended to visualize the results of the research
are presented. This level does not have a direct connection
with the database and the main business logic, in terms of
security.</p>
        <p>At the second layer, all data processing is carried out.
This level is represented by the following modules:
- data processing module;
- forecasting results module – the main system module,
which, implements the process of forecasting the
concentration harmful emissions vehicles in a specific
city point based on the model (1).</p>
        <p>At the data access level, modules are stored, through which
the business logic level interacts with the database using
CRUD operations.</p>
        <p>Figure 5 shows the system modules placement for
modeling atmosphere pollution by vehicle. As can be seen
from the figure, the modules are located on different
hardware.</p>
        <p>A mobile station measuring NO2 level is based on a
notebook with a Windows operating system and a sensor
called "SPEC Sensors DGS-NO2 968-037". The DGS-NO2
968-037 sensor is equipped with an UART-to-USB adapter,
which allows you to connect it to your computer through the
USB interface. For the correct sensor operation, it should be
installed CP210x USB to UART Bridge VCP driver and
terminal TeraTerm, on the laptop.</p>
        <p>The sensor connection is carried out similarly to the
previous case - via the USB interface. Measurement of
instant concentrations of NO2 is carried out every second.
Data is recorded in a log file and transmitted to the server
using a Wi-Fi connection.</p>
        <p>The monitoring station is the server where the NO2
measured concentrations are located, software for
constructing mathematical models to forecast the time
distribution of the indicated concentrations.</p>
        <p>Also, the monitoring station implemented a server part
webbased system to display the modeling results and archive data
on the level concentrations harmful emissions vehicles in the
atmosphere city Ternopil.</p>
        <p>On the user's side, deployed a client-side web-based
system that lets you monitor real-time emissions of nitrogen
dioxide into the air.</p>
        <p>To use the website, the user will need to access the Internet
from the computer that is used, and any web browser that
supports HTML5 and CSS3 standards is installed.</p>
        <p>Figure 6 shows the look of the home page of the website.</p>
        <p>As shown in Figure 6, in order to allow the user to view
the concentration data dioxide, he must select from the
dropdown list the control point (street crossings), after which
a concentration graph of the daily cycle of NO2 will be
displayed before it.</p>
      </sec>
      <sec id="sec-4-2">
        <title>VI. CONCLUSION</title>
        <p>The paper considers an approach for modeling a daily cycle
of changes in nitrogen dioxide concentrations within a road
single section. A method is developed for operative and
automated obtaining of experimental data. Designed and
developed software architecture for modeling the atmosphere
pollution by harmful emissions of vehicles. The proposed
method approbation for the receipt and processing
experimental data on NO2 concentrations, as well as software
developed on the example of modeling the distribution
harmful emissions in the city of Ternopil.</p>
      </sec>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <surname>Vasyukova</surname>
            <given-names>G.T.</given-names>
          </string-name>
          “
          <article-title>Ecology”: a textbook for students</article-title>
          ,
          <source>Kyiv: Condor</source>
          ,
          <year>2009</year>
          , 311 p.
          <article-title>(in Ukrainian)</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <surname>Dyvak</surname>
            <given-names>M. “</given-names>
          </string-name>
          <article-title>Tasks of mathematical modeling the static systems with interval”</article-title>
          . Ternopil, Ukraine: Ekonomichna dumka,
          <year>2011</year>
          , 216 p.
          <article-title>(in Ukrainian)</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <surname>Ivakhnenko</surname>
            <given-names>A.G.</given-names>
          </string-name>
          ,
          <article-title>“Long-term forecasting and management of complex systems”</article-title>
          . Kyiv, Ukraine: Tekhnika,
          <year>1975</year>
          , 311 p.
          <article-title>(in Russian)</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <given-names>T.</given-names>
            <surname>Dyvak</surname>
          </string-name>
          ,
          <article-title>"Parametric identification of interval difference operator on the example of micromodel for distribution of humidity in the drywall sheets in the process of drying", Information Technologies</article-title>
          and Computer Engineering: international
          <source>Scientific Journal</source>
          , vol.
          <volume>3</volume>
          , pp.
          <fpage>79</fpage>
          -
          <lpage>85</lpage>
          ,
          <year>2012</year>
          . (in Ukrainian)
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [5]
          <string-name>
            <given-names>N.</given-names>
            <surname>Porplytsya</surname>
          </string-name>
          , M. Dyvak, “
          <article-title>Interval difference operator for the task of identification recurrent laryngeal nerve”</article-title>
          ,
          <source>Computational Problems of Electrical Engineering: Proceedings of the 16th International Conference (CPEE)</source>
          , pp.
          <fpage>156</fpage>
          -
          <lpage>158</lpage>
          ,
          <year>2015</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <given-names>D.</given-names>
            <surname>Karaboga</surname>
          </string-name>
          and
          <string-name>
            <given-names>B.</given-names>
            <surname>Basturk</surname>
          </string-name>
          , “
          <article-title>A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm”</article-title>
          ,
          <source>Journal of Global Optimization</source>
          , vol.
          <volume>39</volume>
          , pp.
          <fpage>459</fpage>
          -
          <lpage>471</lpage>
          ,
          <year>2007</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <surname>Karaboga</surname>
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gorkemli</surname>
            <given-names>B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ozturk</surname>
            <given-names>C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Karaboga</surname>
            <given-names>N. “</given-names>
          </string-name>
          <article-title>A comprehensive survey: artificial bee colony (ABC) algorithm</article-title>
          and applications”,
          <source>Artificial Intelligence Review</source>
          ,
          <volume>42</volume>
          (
          <issue>1</issue>
          ), pp.
          <fpage>21</fpage>
          -
          <lpage>57</lpage>
          ,
          <year>2014</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <given-names>N.</given-names>
            <surname>Porplytsya</surname>
          </string-name>
          and
          <string-name>
            <given-names>M.</given-names>
            <surname>Dyvak</surname>
          </string-name>
          , “
          <article-title>Synthesis of structure of interval difference operator using artifitional bee colony algorithm”, Inductive modeling of complex systems</article-title>
          , vol.
          <volume>5</volume>
          , pp.
          <fpage>256</fpage>
          -
          <lpage>269</lpage>
          , Kyiv, Ukraine,
          <year>2013</year>
          . (in Ukrainian)
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <given-names>M.</given-names>
            <surname>Dyvak</surname>
          </string-name>
          ,
          <string-name>
            <given-names>N.</given-names>
            <surname>Porplytsya</surname>
          </string-name>
          , I. Borivets,
          <string-name>
            <surname>M.</surname>
          </string-name>
          <article-title>Shynkaryk "Improving the computational implementation of the parametric identification method for interval discrete dynamic models"</article-title>
          ,
          <source>12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)</source>
          , pp.
          <fpage>533</fpage>
          -
          <lpage>536</lpage>
          ,
          <year>2017</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <given-names>W.</given-names>
            <surname>Eckerson</surname>
          </string-name>
          ,
          <article-title>"Three Tier Client/Server Architecture Achieving Scalability, Performance, and Efficiency in Client Server Applications."</article-title>
          <source>Open Information Systems</source>
          vol,
          <volume>87</volume>
          , no.
          <issue>3</issue>
          , pp.
          <fpage>330</fpage>
          -
          <lpage>333</lpage>
          ,
          <year>2007</year>
          .
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>