Measument, modeling and evaluation of some air pollutant in Gaziantep province

In this study, the air quality and the effect of climate change in Gaziantep province were analyzed and the precautions to be taken were discussed. For this purpose, between 2015 and 2020, 5 measurement periods for NO2 and SO2 were carried out at 30 points, especially in winter periods. SPSS 17 program was used in the statistical analysis of passive sampling data, and it was determined that there was a significant statistical relationship between the data. The mentioned data were analyzed with the SigmaPlot version 11.0 program and the correlation coefficients (R2) for the NO2 and SO2 parameters were calculated as 0.9999 and 0.9762, respectively. Passive sampling data were evaluated according to linear artificial neural network (ANN) and nonlinear artificial neural network (NARX-ANN) regression algorithms, and the Bayesian Regularization Algorithm of the nonlinear NARX-ANN structure of the best-fit model (R2=0.8785 for NO2, R2 = 0.9021 for SO2). As a result of the modeling studies, the R2 value of the results obtained in the modeling with SigmaPlot is close to 1, which shows that more reliable results can be obtained with this developed model. As a result of the greenhouse gas calculation studies carried out in Gaziantep, a total of 10.05 million tons of CO2e greenhouse gas emissions were calculated and it was determined that 35% of the total greenhouse gas emission in the city was formed by the industrial sector. In order to control air quality and climate change, adaptation and mitigation action plans should be prepared at local and national scales, and price/performance-oriented methods and technologies for the determined reduction actions should be determined and implemented.