Istanbul Technical University

About: Istanbul Technical University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Fuzzy logic & Large Hadron Collider. The organization has 12889 authors who have published 25081 publications receiving 518242 citations. The organization is also known as: İstanbul Teknik Üniversitesi & Technical University of Istanbul.

Production of Sophorolipids from Candida bombicola ATCC 22214 Using Turkish Corn Oil and Honey

Abstract: The ability of Candida bombicola ATCC 22214 to produce sophorolipids using Turkish corn oil and honey was investigated. Shake flask experiments were carried out both with and without the addition of glucose as the second carbon source. The organism could produce sophorolipids under both conditions but higher production was obtained when corn oil was combined with glucose. The 3 L bioreactor was first operated in batch mode, using both corn oil and glucose. When all the glucose was consumed, 1/4th of the broth was pumped out and was replaced by freshly prepared medium containing 10 % [w/v] of cheap market honey as the sole carbon source. Feed was comprised of corn oil. High concentrations of sophorolipids (&n62; 400 g/L) were produced. The crude products obtained from the batch cultivation could be solidified as very light brown solids when unused oil was removed by hexane, while the products of the two-stage cultivation remained as viscous, honey-like liquids after identical treatments.

A multi-model evaluation of aerosols over South Asia: common problems and possible causes

Abstract: . Atmospheric pollution over South Asia attracts special attention due to its effects on regional climate, water cycle and human health. These effects are potentially growing owing to rising trends of anthropogenic aerosol emissions. In this study, the spatio-temporal aerosol distributions over South Asia from seven global aerosol models are evaluated against aerosol retrievals from NASA satellite sensors and ground-based measurements for the period of 2000–2007. Overall, substantial underestimations of aerosol loading over South Asia are found systematically in most model simulations. Averaged over the entire South Asia, the annual mean aerosol optical depth (AOD) is underestimated by a range 15 to 44% across models compared to MISR (Multi-angle Imaging SpectroRadiometer), which is the lowest bound among various satellite AOD retrievals (from MISR, SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra). In particular during the post-monsoon and wintertime periods (i.e., October–January), when agricultural waste burning and anthropogenic emissions dominate, models fail to capture AOD and aerosol absorption optical depth (AAOD) over the Indo–Gangetic Plain (IGP) compared to ground-based Aerosol Robotic Network (AERONET) sunphotometer measurements. The underestimations of aerosol loading in models generally occur in the lower troposphere (below 2 km) based on the comparisons of aerosol extinction profiles calculated by the models with those from Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Furthermore, surface concentrations of all aerosol components (sulfate, nitrate, organic aerosol (OA) and black carbon (BC)) from the models are found much lower than in situ measurements in winter. Several possible causes for these common problems of underestimating aerosols in models during the post-monsoon and wintertime periods are identified: the aerosol hygroscopic growth and formation of secondary inorganic aerosol are suppressed in the models because relative humidity (RH) is biased far too low in the boundary layer and thus foggy conditions are poorly represented in current models, the nitrate aerosol is either missing or inadequately accounted for, and emissions from agricultural waste burning and biofuel usage are too low in the emission inventories. These common problems and possible causes found in multiple models point out directions for future model improvements in this important region.