Masoud Derakhshandeh

Carbon dioxide absorption using amine based solvents is a well‐known approach for carbon dioxide removal. Especially with the increasing concerns about greenhouse gas emissions, there is a need for an optimization approach capable of multifactor calibration and prediction of interactions. Since conventional methods based on empirical relations are not efficiently applicable, this study investigates use of Response Surface Methodology as a strong optimization tool. A bubble column reactor was used and the effect of solvent concentration (10.0, 20.0 and 30.0 vol%), flow rate (4.0, 5.0 and 6.0 L min⁻¹), diffuser pore size (0.5, 1.0 and 1.5 mm) and temperature (20.0, 25.0 and 30.0°C) on the absorption capacity and also overall mass transfer coefficient was evaluated. The optimization results for maintaining maximum capacity and overall mass transfer coefficient revealed that different optimization targets led to different tuned operational factors. Overall mass transfer coefficient decreased to 34.7 min⁻¹ when the maximum capacity was the desired target. High reaction rate along with the highest absorption capacity was set as desirable two factor target in this application. As a result, a third scenario was designed to maximize both mass transfer coefficient and absorption capacity simultaneously. The optimized condition was achieved when a gas flow rate of 5.9 L min⁻¹, MEA solution of 29.6 vol%, diffuser pore size of 0.5 mm and temperature of 20.6°C was adjusted. At this condition, mass transfer coefficient reached a maximum of 38.4 min⁻¹, with a forecasted achievable absorption capacity of 120.5 g CO₂ per kg MEA.

Olası orman yangınlarının engellenmesi ve erken müdahalenin sağlanması için yangın öncesinde, yangın esnasında ve yangın sonrasında alınacak önlemler oldukça büyük önem taşımaktadır. Bu çalışma kapsamında, CBS ve UA teknolojileri destekli Frekans Oranı tekniğinden yararlanılarak orman yangını konusu irdelenmiştir. Çalışmada yangın riskini sınıflandırmak için üç yıl içinde (2017-2019) meydana gelen 107 orman yangını olayına ait bilgiler kullanılmıştır. Bu kapsamda Milas ilçesi orman alanları orman yangını riski açısından; çok düşük riskli, düşük riskli, orta riskli, yüksek riskli ve çok yüksek riskli olmak üzere beş risk grubunda sınıflandırılmıştır. Frekans oranı yöntemi sonucuna göre çalışma alanında en fazla dağılım gösteren risk sınıfının %55 oran ile orta riskli alanlar olduğu tespit edilmiştir. Elde edilen bulgular, Milas ilçesinde orman varlığının yangınlardan korunması için gerekli tedbirlerin acil olarak alınması gerektiğini ortaya koymuştur.

Forest fires are an important environmental problem, they negatively affect the entire ecosystem and human and animal life in it. In Turkey 192.734 hectares of forest area has been damaged in 46.669 forest fires in the last 20 years. Negligence-accident is the primary cause of these fires. For this reason, in order to minimize the frequency of forest fires and prevent damages, areas with fire risk should be determined and it is necessary to be prepared for the precautions to be taken before, during and after the fire. In this study, Logistic Regression (LR) and Geographic Information Systems (GIS) were used to model the forest fire risk for the Milas province in Muğla. Considering the topographic features, stand data and cultural data, the relationship of these factors with the occurrence of fires was investigated. Accuracy analyzes of fire risk estimation with LR and fire risks of areas with different properties were examined by Receiver Operating Characteristic (ROC) and Hosmer-Lemeshow test. In line with the findings obtained by the LR method, a forest fire risk map was created in the GIS environment. Here, forest fire risk is evaluated at five levels, with “1” very low risk and “5” very high risk. In the resulting forest fire risk map, it was concluded that 16% of the total forest areas in the study area are in high and very high risk classes.

In this study, the effect of adding microparticles of glass as a cell disruption enhancer to maximize the extracted lipid from wild-type microalgae Synechocystis and Chlorella sp. has been investigated. A general factorial design approach at different levels has been implemented to evaluate the effectiveness of size and quantity of glass particles for both species. The statistical analysis of variance for the obtained results revealed the significance of the method and defined factors. The recorded extraction efficiency of lipid without addition of particles was 45.02 and 23.19% for Synechocystis and Chlorella sp., respectively. With the addition of particles, the highest recorded value for Chlorella was 34.01% which stands for 46.60% enhancement of extraction efficiency. This was achieved when 40 µm particles in 2.25 mass proportion of particle to dried biomass were used. The addition of particle did not improve the lipid extraction efficiency for the Synechocystis sp. These findings also showed that the conventional gravimetric methods may underestimate the lipid content of microalgae species.