The city of Baghdad has witnessed an urban and industrial expansion with an increase in population, especially since 2003. Air pollution sources have multiplied by the increase in the number of vehicles and electricity generators, causing the emission of large quantities of hydrocarbon gases, including carbon dioxide, CO2. The discharge of such gases into the atmosphere and large amounts, will surely have a role in contributing to global warming. Therefore, it will have prominent adverse effects in influencing the rise in temperatures in the city. The research aimed to show the applied aspect of remote sensing and geographic information systems techniques in estimating the CO2 and its relationship to thermal balance for Baghdad city through fifteen stations distributed throughout the city. Remote sensing data adopted from US Geological and the European Centre, in addition to CO2 data for the Atmospheric Infrared sounder (AIRS) from Giovanni for the extended period (2003-2018), were used. Processing and statistical analysis were performed on data using GIS 10.6 and Origin 2018 software. The monthly rates of CO2 showed seasonal fluctuations between winter and summer, where the highest value of CO2 in July and the lowest value in February. Inverse Distance Weighting (IDW) technology was used to represent the spatial distribution of CO2 concentrations in the city. Residential and industrial regions experienced higher levels compared to agricultural areas. Pearson correlation coefficient was used to find out the relationship between carbon dioxide and temperatures. The correlation coefficient showed a high positive relationship between increased gas concentrations and high temperatures for all study stations over the entire study period. It can be concluded the concentration of carbon dioxide differs locally in regions of Baghdad, such as residential, commercial, traffic, industrial, and rural areas, as well as during the months of the year.
Investigating rapid deforestation and carbon dioxide release in Bangladesh using geospatial information from remote sensing data
