Estimation of rare and clustered population mean using stratified adaptive cluster sampling

For many clustered populations, the prior information on an initial stratification exists but the exact pattern of the population concentration may not be predicted. Under this situation, the stratified adaptive cluster sampling (SACS) may provide more efficient estimates than the other conventional sampling designs for the estimation of rare and clustered population parameters. For practical interest, we propose a generalized ratio estimator with the single auxiliary variable under the SACS design. The expressions of approximate bias and mean squared error (MSE) for the proposed estimator are derived. Numerical studies are carried out to compare the performances of the proposed generalized estimator over the usual mean and combined ratio estimators under the conventional stratified random sampling (StRS) using a real population of redwood trees in California and generating an artificial population by the Poisson cluster process. Simulation results show that the proposed class of estimators may provide more efficient results than the other estimators considered in this article for the estimation of highly clumped population.

     

Ecotoxicological risk assessment for sediments of Çavuşlu stream in Giresun,Turkey: association between garbage disposal facility and metallic accumulation

Environmental Science and Pollution Research - The objective of this paper was to stress the possible potential toxic element (PTE) accumulation in the surface sediments of the Çavu?lu...     

Basic processes in phytoremediation and some applications to air pollution control

In this short review, basic processes for phytoremediation and plant enzymes that are potentially useful in phytoremediation are briefly summarized. The remaining part describes the applications of the basic processes to decontaminate pollutants in the environments that have been done in our laboratory. Our work includes (1) analysis of the capability of various naturally occurring plants to decontaminate atmospheric nitrogen dioxide and selection of nitrogen-dioxide-philic plants that grow with nitrogen dioxide as the sole nitrogen source, (2) production of transgenic plants to improve plants' capability to decontaminate atmospheric nitrogen dioxide, and (3) analysis of the denitrification process in plants to innovate a gas--gas-converting plants that convert nitrogen dioxide to nitrogen gas.     

Transesterification of hazelnut oil by ultrasonic irradiation

Ultrasonic irradiation is considered an effective way to increase mass transfer between immiscible liquid–liquid phases in a heterogeneous system leading to faster transesterification and higher yield and saving excess methanol and catalyst. In this study, the transesteri?cation of hazelnut oil with methanol and ethanol was performed in the presence of potassium hydroxide or sodium methoxide as a catalyst using two types of ultrasonic irradiation with a probe (20 kHz, 200 W) and a bath (35 kHz, 400 W); a conventional production method was also used. The reaction time, alcohol:oil molar ratio, catalyst type (KOH or NaOCH₃), and catalyst amount (wt.% of oil) were studied as experimental parameters. The highest methyl ester conversion was obtained as 98.12% by using ultrasonic probe at a 5:1 methanol:oil molar ratio with KOH 1 wt.% of oil as catalyst in 20-min reaction time at autogenous temperature. The application of ultrasonic irradiation by using a probe decreased the level of energy consumption, showing that this method may be a promising alternative compared with the conventional production method.     

Land cover changes on the coastal zone of Candarli Bay, Turkey using remotely sensed data

Land cover of the Earth is changing dramatically because of human activities. Information about changes is useful for management of natural resources. Rapid land cover changes have taken place in many coastal areas of Turkey over the last two decades due to urbanization and land degradation. In this paper, land cover change dynamics were investigated by the combined use of satellite remote sensing and geographical information systems. The main objective of the study was to determine land-cover transition rates among land cover types in coastal areas of Turkey. A time series of Landsat TM and ASTER images were used to gather land cover change data of the coastal line of Candarli Bay, Izmir, Turkey. The images were classified using supervised classification and a post-classification comparison approach was used in change detection. The results show significant increase in urban areas but decrease in semi natural and agricultural areas.     

A review of plastic pollution in aquatic ecosystems of Turkey

Environmental Science and Pollution Research - Turkey is one of the major plastic pollution sources in the Mediterranean and the Black Sea. This review summarizes present information, data, and...     

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics

Bafa Lake Nature Park is one of Turkey’s most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural–natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.     

Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.