Environmental Engineering / Çevre Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4321
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Article Citation - WoS: 40Citation - Scopus: 38Investigating the Local-Scale Fluctuations of Groundwater Storage by Using Downscaled Grace/Grace-fo Jpl Mascon Product Based on Machine Learning (ml) Algorithm(Springer, 2023) Khorrami, Behnam; Ali, Shoaib; Gündüz, OrhanGroundwater storage is of grave significance for humanity by sustaining the required water for agricultural irrigation, industry, and domestic use. Notwithstanding the impressive contribution of the state-of-the-art Gravity Recovery and Climate Experiment (GRACE) to detecting the groundwater storage anomaly (GWSA), its feasibility for the characterization of GWSA variation hotspots over small scales is still a major challenge due to its coarse resolution. In this study, a spatial water balance approach is proposed to enhance the spatial depiction of groundwater storage and depletion changes that can detect the hotspots of GWSA variation. In this study, Random Forest Machine Learning (RFML) model was utilized to simulate fine-resolution (10 km) groundwater storage based on the coarse resolution (50 km) of GRACE observations. To this end, parameters including soil moisture, snow water, evapotranspiration, precipitation, surface runoff, surface elevation, and GRACE data were integrated into the RFML model. The results show that with a correlation of above 0.98, the RFML model is very successful in simulating the fine-resolution groundwater storage over the Western Anatolian Basin (WAB), Turkiye. The results indicate an estimated annual depletion rate of 0.14 km(3)/year for the groundwater storage of the WAB, which is equivalent to about 2.57 km(3) of total groundwater depletion from 2003 to 2020. The findings also suggest that the downscaled GWSA is in harmony with the original GWSA in terms of temporal variations. The validation of the results demonstrates that the correlation is increased from 0.56 (for the GRACE-derived GWSA) to 0.60 (for the downscaled GWSA) over the WAB.Article Citation - WoS: 5Citation - Scopus: 10Removal of Pesticide Residues From Apple and Tomato Cuticle(Springer, 2023) Tari, Vinaya; Yalçın, Melis; Turgut, Nalan; Gökbulut, Cengiz; Mermer, Serhan; Sofuoğlu, Sait Cemil; Turgut, CaferPesticide residues are always an unsolved problem in the world despite all kinds of prevention measures. The present research work is based on a scientific hypothesis, i.e., The removal of average pesticide residue is inversely proportional to the thickness of cuticle. The effects of boron-containing products and plant-based surfactants were tested for the removal of five pesticides (lambda-cyhalothrin, chlorpyrifos, diflubenzuron, metaflumizone, acetamiprid) on tomatoes and apples. Boron-containing products were able to remove the pesticide residues on average between 58.0 and 72.6% in tomatoes and 33.2-58.8% in an apple. While plant-based surfactants removed residues on average between 58.5 and 66.6% in tomatoes and 41.0-53.2% in an apple. The highest removal rate was 72% with etidot at 1%. The solution of 1% C8-C10 provided 66.6% average removal for tomatoes. Less removal was achieved in apples. For an apple, Log K-ow and molecular mass (independent variables) were significant with p < 0.01, and the coefficient of determination (R-2) was > 0.87. However, the multiple linear regression analysis for ground colemanite was significant with R-2 of 0.96. In tomatoes, neither Log K-ow nor molecular mass as significant. The correlation was found between the physical and chemical properties of pesticides, but it is estimated that the thickness of the cuticle is effective in removing pesticides.Article Citation - WoS: 11Citation - Scopus: 12Investigation of the Best Possible Methods for Wind Turbine Blade Waste Management by Using Gis and Fahp: Turkey Case(Springer, 2022) Öztürk, Samet; Karipoğlu, FatihThe aim of this study is to present the status and projections of wind turbine blade retirement in Turkey; to investigate the number of retiring WT blades in the regional, manufacturer, and material aspects; and to discuss the management methods for retired WT blades. To determine the best possible wind turbine blade waste management methods for Turkey, a combined application of Geographical Information Systems (GIS) and the Fuzzy Analytical Hierarchy Process (FAHP) is used in this study. It is found that around nine thousand WT blades will become waste between 2020 and 2039 in Turkey, corresponding to around 80,500 tons of waste. On average, 52,325 tons of glass/carbon and 28,175 tons of polymers will be accumulated between 2020 and 2039 from wind turbine blades. More than half of the WT blade waste will come from two WT manufacturers, namely, Enercon and Nordex. Aegean and Marmara regions will provide 74% of the blade waste, where 33% of them will be 2 MW and 2.5 MW sizes of WT blades. Furthermore, a case study is applied to Izmir city to demonstrate the results of FAHP for finding the best available method to dispose of WT blades. The results show that using blade waste as filling material is the best alternative, while waste-to-energy is the last favorable option for blade waste management. Finally, sensitivity analyses are applied to demonstrate the robustness of the results for the inclusion of new alternatives and the bias of experts’ judgments.