Selçuk University

The cement industry is one of the most energy-intensive sectors and is responsible for a considerable share of industrial emissions. In cement production, the pre-calcination stage plays a critical role in fuel consumption and pollutant formation. Therefore, replacing coal with cleaner fuels such as liquefied natural gas (LNG) and optimizing combustion conditions are important for improving energy performance and reducing environmental impacts. This study investigates the effects of different LNG flow rates and excess air ratios on the energy efficiency, emission characteristics, environmental impact, and enviroeconomic performance of an LNG-fueled rotary burner used for cement pre-calcination. Experiments were conducted at LNG flow rates ranging from 5 to 30 L/min under different air excess ratio conditions. The results showed that increasing the LNG flow rate reduced both energy efficiency and environmental sustainability. The highest overall energy efficiency of 95.66% was achieved at λ = 1.15 with an LNG flow rate of 5 L/min, while the efficiency generally showed a decreasing trend at higher flow rates. Increasing lambda to 1.15 decreased CO, HC, and soot emissions by approximately 60%, 38%, and 60%, respectively. However, CO2 and NOx emissions increased by 6% and 29%, respectively. Due to the dominant contribution of CO2 and NOx, their combined share in the total environmental impact and enviroeconomic cost reached 99%. Overall, within the investigated operating range, the 5 L/min LNG condition provided the most favourable thermo-environmental performance due to its higher energy efficiency, lower heat-transfer losses, and lower absolute environmental and enviroeconomic burdens, whereas higher LNG flow rates increased the environmental and economic loads.

The impact of nanotechnology on contemporary agricultural practices is favorable as there is the use of fertilizers made up of nanoparticles, which are expected to deliver nutrients better than ever, improve crop yields, and cause minimal environmental impact. The review summarizes the existing developments in nanofertilizer preparations, their relationships with soil microbiota, nutrient bioavailability, and physiological pathways in plants. Evidence from controlled and field studies indicates that nano-formulations can increase NUE by 20–50

Today, sustainable water use has become a critical policy area, as dynamics such as increasing global water demand, water scarcity, and climate change directly affect agricultural production. In this study, the role of psychological and social factors in explaining water-saving behaviors in agricultural production was examined based on the Norm Activation Model (NAM); the model was extended with the environmental concern (EC) variable. Within the scope of the field study carried out in Konya province, data were collected from 270 farmers. Structural equation modeling results showed that personal norms exert a strong positive effect on water-saving behaviors (β = 0.430 in the original model; β = 0.341 in the extended model). The original NAM explained 19.5

Metaheuristic algorithms have been widely applied to complex optimization problems; however, many still suffer from premature convergence and entrapment in local optimal. The Tuna Swarm Optimization (TSO) algorithm, despite its effectiveness, also faces these limitations. To address this issue, two enhanced variants are proposed: Chebyshev Map-based TSO (TSO-CM) and Cuckoo Search (CS)–integrated TSO-CM (CSTSO-CM). TSO-CM improves population diversity through chaotic dynamics, while the integration of CS strengthens exploration capability, achieving a better balance between exploration and exploitation. The proposed algorithms were evaluated on 23 benchmark functions over 500 iterations with a population size of 30, and each experiment was repeated 30 times independently. Comparative results indicate that TSO-CM outperforms the standard TSO, while CSTSO-CM achieves the best or near-best solutions in the majority of the 23 test functions. Both the Wilcoxon signed-rank and Friedman tests confirm the statistically significant superiority of CSTSO-CM (p < 0.05). Furthermore, applications to gear train and welded beam design problems confirm the practical effectiveness of CSTSO-CM. These findings demonstrate that the proposed approaches successfully overcome the limitations of TSO and provide efficient solutions for challenging real-world optimization tasks.

Access to clean and safe freshwater is essential for human health and welfare in both developed and developing countries. Therefore, ecological monitoring of aquatic ecosystems is crucial for all living organisms dependent on these resources. Beyşehir Lake, largest freshwater lake in Türkiye, is a vital natural resource with ecological, economic importance and its sustainability is a national concern. This study investigates seasonally collected water, sediment, and fish (Carassius gibelio) from Beyşehir Lake to assess elemental distributions and potential risks to ecosystem and public health. Data for 21 parameters were compared with national and international regulations and findings from similar studies. Average concentrations showed that Be (2.67 µg L⁻1), Cr (2.77 µg L⁻1), Cu (3.25 µg L⁻1), and Pb (0.94 µg L⁻1) levels in water samples, and Cd (0.07 mg kg⁻1) and Sb (0.69 mg kg⁻1) in fish samples exceeded certain regulatory limits. In contrast, all elements in sediment samples were within acceptable limits. Bioconcentration factor (BCF) evaluation indicated that these elements have limited potential to accumulate in fish tissues. In the risk assessment for fish consumption, estimated daily intake (EDI) values for Cd, Fe and Ni exceeded tolerable daily intake (TDI) thresholds, indicating the need for monitoring. Despite these exceedances, the total target hazard quotient (TTHQ) value of 0.343 suggests that fish consumption does not pose a significant non-carcinogenic health risk. According to principal component analysis (PCA), lithogenic–anthropogenic rock weathering and natural mineralogical composition were identified as the main factors influencing the elemental content of water and sediment samples.