Impacts of Meteorological Factors on Particulate Pollution: Design of Optimization Procedure

In this study, Taguchi L 8 orthogonal array design was applied to determine the most polluted meteorological conditions in Kocaeli. Meteorological factors were decided as temperature, relative humidity and rainfall in two different levels. Larger is better function was applied for calculation of signal-to-noise ratios. The impact ratios of meteorological factors were also determined by using Taguchi model. PM 10 concentrations were predicted by the model. Results of the model showed that predicted and obtained concentrations were closer to each other. These calculations and results show the success of Taguchi model in this study.


Introduction
Particulate matter (PM) is one of the major air pollutants in urbanization region [1]. Effects of PM pollution on human and environmental systems have been discussed by many of scientists. Particulates with aerodynamic diameters <10μm (PM 10 ) and <2.5μm (PM 2.5 ) causes lung cancer, asthma, morbidity and mortality [2,3]. So, air pollution control and monitoring are very important for saving ecological system.

Relationship
between aerosol concentration and meteorological variables should be investigated for better control and monitoring applications. Aerosol concentrations are controlled by atmospheric mixing, chemical transformation, emission etc. [4]. Although this presence of concentrationmeteorology system is real, the understanding of the connection between meteorological factors (relative humidity, temperature, wind, rainfall etc.) with particulate matter is not clear [5]. Because in lots of countries, researchers have limited number of studies about different aerosol fractions for a long time to characterization of relationship between meteorological factors and air pollution [4][5][6].
In last decades, some statistical and optimization tools such as multiple linear regression analyses [7], artifi cial neural networks [7,8], Box-Behnken designs [9], Taguchi orthogonal arrays [10][11][12] etc. are used for investigation of pollution in different environments. Taguchi bases on statistical design systems and successfully applied in lots of scientifi c disciplines. Compared to other statistical methods, Taguchi model is simple, effective and innovator for investigation of environmental risks [13,14]. Harmful effects of multiple factors on environment can be investigated by this model. On the other hand, the infl uence of individual factors is more important for success of this model [10].

Study area
Kocaeli is one of the important and crowded cities in Turkey. Lots of heavy industrial plants have been located here.
On the other hand, it has quite an intense traffi c network. So, air pollution is the major environmental problem in this city. In this study, PM 10 and meteorological data sets obtained from the station of Ministry of Environment and Urban Planning. The study area is located between latitude of 40° 46' North and 29° 31' East ( Figure 1).

Taguchi procedure
Selection of the control factors is the most important step in Taguchi applications. Temperature, relative humidity and rainfall with two levels were selected as control factors in this model study (Table 1).
In Taguchi model studies, the variability of factors expressed by signal-to-noise ratios ( S N ). One of the S N functions must be chosen as "smaller is better", "nominal is better" and "larger is better" [15]. Larger is better characteristics was chosen for this work. Because this study was designed to investigate the meteorological factors which cause maximum PM 10 concentration in Kocaeli. The S N ratio for the larger is better function was calculated as: (1) where i y is the observed PM 10 concentrations and n is the number of repetitions. L 8 orthogonal array was chosen for this study. Table 2 shows L 8 orthogonal array of meteorological factors onto PM 10. All calculations and applications of this study were hosted in Minitab 16 software package and Microsoft Excel 2007.

Results and Discussions
In this study, the general goal was to determine the impacts of some meteorological factors such as temperature, relative humidity and rainfall onto PM 10 pollution in an industrial area of Kocaeli. Taguchi method was designed as L 8 orthogonal array for this work.
In Taguchi applications, calculating of S N ratios are the most important stage for evaluate the meteorological and PM 10 data sets clearly. S N ratios show the consistency between control factors (temperature, relative humidity and rainfall) and response data (PM 10 ). Larger is better type of S N ratios were calculated according to Eq. (1) and the results were given in Table 3.
As seen from Table 3 The impact ratio of temperature was calculated as 69.40%.
Whereas impacts of temperature were higher, relative humidity was the less effective factor in this model study. Impact ratios of the meteorological factors were presented in Table 4.