This study addresses the odor problem at a waste and residue treatment incineration and utilization plant located within the borders the Alikahya district of the Kocaeli province in Turkey. In the first stage of the study, odor measurements were made at designated sampling points, while in the second stage, odor concentrations were determined at the receptor points through dispersion modelling using a USEPA (United States Environmental Protection Agency) certified long-range (>50 km) CALPUFF lagrangian puff model. In the final stage, an analysis of the predicted and observed values was carried out using such statistical methods as geometric mean bias (MG), geometric variance (VG) and fractions of predictions within a factor of two observations (FAC2). During the modelling study, the highest one-hour concentration level was found to be 1868.10 OU (Odor Units), and the 24-hour concentration level was found to be 1316 OU, representing a decrease of approximately 30 percent. According to the measurement made, the maximum concentration value was 2455 OU. Odor measurements were carried out at 13 points within the area in order to assess the prediction results. When the results were assessed using the MG, VG and FAC2 statistical methods, it was observed that an acceptable model performance was not achieved for the whole sampling point. When the reason for this was investigated, it was concluded that the observed values were lower than the predicted values due to the fact on the measurement days, the odor was dispersed by wind. It was further concluded that the observed values were higher than the predicted values as a result of odors emitted by other plants in the area. When the measurements in residential areas were examined to identify the effect of the odors, it was determined that although the primary density of settlement is to the southwest of the plant, it was not this area that was affected most, but rather the area to the northeast, where there is a lower settlement density.

Air quality modellings are highly useful systems used to investigate the possible impact of emissions diffusing into the atmosphere in any area they might have on that area. There are many modelling methods whose capacities are limited by their advantages and disadvantages or the equipment they use. In this study, therefore, both steady-state models (AERMOD and ISCST-3) and the Lagrangian model (CALPUFF) are used. This study has two purposes: one is to specify performance of the models. Performances were determined with various statistical methods such as fractional bias (FB), mean squared error (MSE), and geometric mean bias (MG). The other purpose of this study is to evaluate temporal and spatial variations of point (P), area (A), and line (L) - sourced CO and NO_x emissions in the research area by using the modelling methods. The district of Körfez, which is one of the districts of the province of Kocaeli, was chosen as the study area. When the results obtained with modelling all P and A sources by three programs are analyzed, the highest annual concentration AERMOD, ISCST-3, and CALPUFF were found as 128.82, 86.96, and 201.30 μg/m³ for CO, and 7.56, 26.31, and 6.10 μg/m³ for NO_x, respectively. On the other hand, when the results obtained with modelling all P and A and L sources by two programs are investigated, the highest annual concentration AERMOD and ISCST-3 were found to be 155.12, 92.46 μg/m³ for CO, and 166.93 and 89.98 μg/m³ for NO_x, respectively. When contributions of the pollutant sources on pollution are evaluated, it was observed that area sources and line sources are more predominant than other sources for CO and NO_x emissions. It was observed by analyzing the diffusion maps that residential areas in the district are more concentrated. Therefore, in the study the predicted and observed values were also compared with national and international limit values and determined to meet these limit values. According to the results obtained by evaluation of performances of the models with FB, MS, and MG statistical methods, performance sorting for NO_x emissions was found to be ISCST-3 > CALPUFF > AERMOD, while for CO emissions it is given as CALPUFF > AERMOD > ISCST-3. However, since it is not correct to distinguish between performance of a model for an application and that of another model accurately, performances of the models were interpreted according to the results of this study and literature review

As road traffic in Turkey is a significant source of emissions due to the increasing number of vehicles on the road, the goal of this study is to calculate greenhouse gas emissions from Turkey’s roads between 2010 and 2020, create an inventory, and estimate possible emissions until 2050. In the study, both greenhouse gases (carbon dioxide (CO₂) and nitrous oxide (N₂O) and co-emitting air pollutants that indirectly contribute to climate change (ammonia—NH₃, nitrogen oxide—NO_X, sulfur dioxide—SO₂, carbon monoxide—CO, non-methane volatile organic compounds—NMVOC, and particulate matter—PM) were investigated. The study revealed that the total number of vehicles using state roads in Turkey increased by 60% between 2010 and 2020. As a result, emissions of CO₂, N₂O, NH₃, NO_X, SO₂, CO, NMVOC, and PM increased by 29.6%, 24.2%, 0.5%, 19.9%, 9.9%, 18.2%, 21.5%, and 39.7%, respectively. When emissions were analyzed on a provincial basis, particular attention was drawn to provinces with high levels of urbanization. Based on forecast studies, the total number of vehicles registered for traffic will increase by 105% by 2050. Due to this increase, CO₂, N₂O, NH₃, NO_X, SO₂, CO, NMVOC, and PM emissions are estimated to increase by 149.17%, 151.78%, 154.39%, 138.95%, 150.97%, 153.09%, 152.09%, and 151.47%, respectively.