FUZZY MODEL OF AIR QUALITY IN KYIV FOR PM2.5 AND PM10 - Наукові конференції
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FUZZY MODEL OF AIR QUALITY IN KYIV FOR PM2.5 AND PM10

13.11.2021 09:44

[3. Технічні науки]

Автор: Bozhko K.M., PhD, associate professor, Department of Information and Measuring Technologies, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”; Morozova I.V., postgraduate, Department of Information and Measuring Technologies, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”; Kirilenko E.A., student, Department of Information and Measuring Technologies, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”


Particulate matter (PM) is small airborne particles. Some particulate matter is natural and some is man- made. In general, the smaller the particle the deeper it can be inhaled into the lung. A type of gravimetric sampler used for measuring ambient concentrations of PM10 or PM2.5.

PM10. Particles which pass through a size-selective inlet with a 50 % efficiency cut-off at 10 micrometers aerodynamic diameter, as defined in ISO 7708:1995, Clause 6[1]. PM10 is ‘particles of less than 10 micrometers in diameter’.

PM2.5. Particles which pass through a size-selective inlet with a 50 % efficiency cut-off at 2.5 micrometers aerodynamic diameter, as defined in ISO 7708:1995, Clause 7.1 [1]. This size fraction described as the ‘high risk respirable convention’ in the above ISO standard. PM2.5 is ‘particles of less than 2.5 micrometers in diameter’ though this is not strictly correct. 

Modelling of dust emissions (PM10 and PM2,5) in Mediterranean region is executions in [2-3]. In Poland researched dust emission (PM2,5) in atmospheric air in urban agglomeration of Lublin [4]. 119 stations of air quality monitoring in Kyiv measure PM10 and PM2,5 in real time [5].

Based on the measurement results for the stations in Kyiv a fuzzy logic model were applied. The concentration range was divided into three parts (membership functions): green, yellow and orange.

For PM2.5 concentration as 0-12 microgram in cubic meter is green; 12-35,4 – yellow; 35,5-55,4 – orange.

For PM10 concentration as 0-54 microgram in cubic meter is green; 55-154 – yellow; 155-254 – orange.

The following parameters were set in the simulation:

- Model type – Mamdani;

- The number of inputs is two: for PM2.5 and PM10;

- The type of input membership functions is Gaussian;

- The type of output membership functions is triangular;

- The number of membership functions for inputs is three; 

- The number of membership functions for output is three.

The meteorological station is located at 13 Borshchahivska Street in Kyiv. The simulation results are in Figure 1. 



Figure 1 – Fuzzy model of air quality: PM2.5 concentration is 52,6 mcg per cubic meter; PM10 – 66,9 mcg; AQ is 6,04 (11.11.2021, 20-00)

Air quality 6,04 is in yellow part (Fig. 1).

Rules of modelling: 

1) if Green2.5 & Green10 then Green;

2) if Green2.5 & Yellow10 then Yellow;

3) if Green2.5 & Orange10 then Yellow;

4) if Yellow2.5 & Green10 then Yellow;

5) if Yellow2.5 & Yellow10 then Orange;

6) if Yellow2.5 & Orange10 then Orange;

7) if Orange2.5 & Green10 then Yellow;

8) if Orange2.5 & Yellow10 then Orange;

9) if Orange2.5 & Orange10 then Orange.

The simulation results as surface are in Figure 2. 



Figure 2 – Surface simulation of air quality 

References:  

1. ISO 7708:1995.  Air quality – Particle size fraction definitions for health-related sampling. – 1995. [Actual from 1995].

2. Flaounas, E.; Kotroni, V.; Lagouvardos, K.; Klose, M.; Flamant, C.; Giannaros, T. Sensitivity of the WRF-Chem (V3.6.1) model to different dust emission parametrisation: Assessment in the broader Mediterranean region. //Geoscientific Model Development, 2017, Issue10, Pages 2925–2945. 

3. Rizza, U.; Barnaba, F.; Miglietta, M.M.; Mangia, C.; Di Liberto, L.; Dionisi, D.; Costabile, F.; Grasso, F.; Gobbi, G.P. WRF-Chem model simulations of a dust outbreak over the central Mediterranean and comparison with multi-sensor desert dust observations. //Atmospheric Chemistry Physics, 2016, Issue 17, Pages 93–115. 



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