The Net Effect of Cloud Cover on Carbon Dioxide Concentrations over Baghdad City

الملخص

The Green House Effect nowadays forms one of the major problems and is one of the side effects of technology. This effect is related to the mechanism of exchange of energy of earth with its environment. The CO₂ molecules have energy levels in the range of frequencies of the radiation from the earth this will prevent such frequencies from leaving earth, and as a result, affecting a temperature rise. The aim of this research was to analyze the hourly, daily, and monthly behavior of the CO₂ concentration, the cloud cover (total, high, medium and low) and find the relationship between the monthly averages of the CO₂ concentrations with the total cloud cover, based on the data of the European Centre for Medium-Range Weather Forecasts (ECMWF) for the cloud cover, and the data of the Ministry of the Environment of Iraq for CO₂ concentrations, for three different times (08:00 am, 12:00 pm and 04:00 pm) for the days (15 and 30) of rainy months for the year 2012 of the Wazireya industrial area in Baghdad city. And the use of some statistics such as Simple Linear Regression (SLR) and finding P-values, and using Pearson’s correlation test to find the strength of the relationship between CO₂ concentrations with total cloud cover. It was found that the highest concentration of CO₂ was at 08:00 am, the lowest concentration of CO₂ was at 04:00 pm, the highest daily of CO₂ concentrations was 549 PPM in (30/December), the lowest daily of CO₂ concentrations was 252 PPM in (13/September), the highest monthly of CO₂ concentrations was in the months (October and December), and the lowest monthly of CO₂ concentrations was in January. The lowest low and total cloud cover was found in a month (August and September), and there was a low positive relationship between the monthly of CO₂ concentrations and the total cloud cover of the months (January, April, October, November, and December) where the highest correlation in October was +0.36. It was also found that there was a weak inverse relationship in the months (February, March, and May), where the correlation coefficient (-0.08, -0.03, and -0.08) respectively.  

DOI=10.24897/acn.64.68.129