Abstract
The air is polluted and the atmospheric pollution has becoming a great problem for human beings due to the high rate consumption of energy. Most of the scientists dealing with the air pollution state that the first reason of all environmental problems is the population increase. Depending on population, the high consumption of energy (including heating purposes, electricity production, transportation and industries) agricultural activities, waste disposal and the pressure for destroying forest areas create air pollution problem. The atmosphere is polluted and the concentrations of pollutants have increased tremendously. Karabuk Province is one of the famous provinces of heavy industries. There are 3 air quality measurement stations. In this study, the last 2 years hourly and daily air pollutants (PM10, SO2 , NO, NOx , NO2 , O3 and CO) were studied as a time series by using graphical and statistical approaches. The results were considered seasonally and annually. The meteorological condition is also very effective in atmospheric pollution. Moreover, the industrial production and consumption of energy are also high pressure on Karabuk province. The concentrations in each station are also showing different characteristics during two years’ period. The highest concentrations (such as PM10, SO2 , NO, NOx ) are, as usual, seen in winter season due to industrial usage of energy for production and household consumption of energy for heating. However, for O3 , the highest concentration is observed in summer season, because the atmospheric ozone trend is supposed to show an opposite trend compared with NO due to photochemical reaction with these gases. For CO, the maximum concentration is recorded as 4779 μg/m3 in august in 2015. The analyses of data have shown that, the atmosphere is polluted highly with PM10, SO2 , NO, NOx , NO2 , and CO during winter season. The households are very effective using high coal for heating purposes in Karabuk Province.
Highlights
INTRODUCTIONTime series are mainly used to estimate missing data or used to determine trend for future estimation [1]
The air pollution data are always evaluated as time series
The time series analyses have shown that the pollutant is fluctuating throughout the years
Summary
Time series are mainly used to estimate missing data or used to determine trend for future estimation [1]. The biggest problem in time series analyses is the missing data. The increases of missing data over 10% are always resulted in some assumptions in the analyses. The meteorology, geographical aspect, persistence in the air, climate and seasons have big effect in the air pollution [9, 12, 13]. In another words, the time series are the sequence of many segments and environment [4, 8]. The main difficulty is the missing data due to equipment failure for some days during the study years
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