Sex ratio estimations of loggerhead sea turtle hatchlings by histological examination and nest temperatures at Fethiye beach, Turkey

Hatchling sex ratios in the loggerhead turtle (Caretta caretta) were estimated by placing electronic temperature recorders in 21 nests at Fethiye beach during 2000–2002. Over the seasons, the mean temperature in the middle third of the incubation period ranged from 26.7 to 32.1°C, and incubation periods ranged from 49 to 67 days. Based on the mean temperatures during the middle third of the incubation period, and on histologically sexed dead hatchlings, the sex ratios of hatchlings at Fethiye beach were roughly equal, i.e. 60–65% of the hatchlings were females. This contrasts with the highly female-skewed sex ratios in loggerhead turtles elsewhere; Fethiye has a relatively high proportion of male hatchlings. For endangered sea turtles, the knowledge of hatchling sex ratios at different beaches, coupled with appropriate conservation measures, can make an important contribution to their survival.     

Magnetic nanoparticles coated with aminated polymer brush as a novel material for effective removal of Pb(II) ions from aqueous environments

Environmental Science and Pollution Research - In the present study, a poly (vinylbenzyl chloride) grafted Fe3O4 nanoparticle (Fe3O4@PVBC) was prepared by surface-initiated reversible addition...     

Analysis of Heavy Metals in the Endometrial Tissue Using Electron Microscope

Objective This study was done to estimate whether heavy metals in the air may affect endometrial chemical composition. Materials and Methods A total of 30 albino Wistar rats were employed and randomly divided into three groups. The rats of Group 1 and 2 were acutely and sub-chronically exposed to the gas form of heavy metals, respectively. Group 3 was used as a control group. Endometrial tissue worth of heavy metals of the groups was measured in through using scanning electron microscope. Results A statistically no significant difference was found for endometrial chemical composition of all of the heavy metals (chrome, manganese, iron, cobalt, nickel, zinc and lead) between group 1 and 2 (p > 0.05). On the other hand, there was statistically significant difference for all of the heavy metals between group 1 and group 3 (p < 0.05), while there was statistically significant difference for chrome, manganese, iron, cobalt and nickel (p < 0.05), but zinc and lead (p > 0.05) between group 2 and 3. Conclusion Air pollutants of Pb and Zn resulting mostly from combustion of fossil fuels and certain special industrial process in Kirikkale may be a risk factor for the high pregnancy loses by changing endometrial homeostasis.     

Spatial distribution and source identification of trace elements in topsoil from heavily industrialized region,Aliaga, Turkey

Topsoil samples (n?=?40) were collected from a heavily industrialized region in Turkey. The region includes several scrap processing iron–steel plants with electric arc furnaces (EAFs), a petroleum refinery, a petrochemical complex, steel rolling mills, a natural gas-fired power plant, ship-breaking yards and very dense transportation activities. The region has undergone a rapid transition from an agricultural region to a heavily industrialized region in the last three decades. Collected soil samples were analyzed for 48 trace elements using inductively coupled plasma-mass spectrometry (ICP-MS). The elemental distribution pattern in the region indicated that Nemrut area with dense iron–steel production activities was a hotspot for elemental pollution. In addition to crustal elements, concentrations of anthropogenic trace elements (i.e., Fe, Zn, Pb, Mn, Cu, Cd, Cr and Mo) were very high in the area influencing many parts of the region. Elemental compositions of fugitive sources polluting the soil (i.e., paved and unpaved roads, slag piles, EAFs filter dust piles and coal piles) were also determined. The methods (enrichment factors [EFs] and the index of geoaccumulation [I _geo]) used for determination of pollution status of soil showed that Cr, Ag, Zn, As and Pb were the strongly contaminating elements for the region. Principal component analysis (PCA) clearly indicated that anthropogenic sources (steel production, refinery and petrochemical processes and traffic) were important sources in this region.     

Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks

Suspended sediment concentration (SSC) is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very costly and cannot be conducted for all river gauge stations. Therefore, correct estimation of suspended sediment amount carried by a river is very important in terms of water pollution, channel navigability, reservoir filling, fish habitat, river aesthetics and scientific interests. This study investigates the feasibility of using turbidity as a surrogate for SSC as in situ turbidity meters are being increasingly used to generate continuous records of SSC in rivers. For this reason, regression analysis (RA) and artificial neural networks (ANNs) were employed to estimate SSC based on in situ turbidity measurements. The SSC was firstly experimentally determined for the surface water samples collected from the six monitoring stations along the main branch of the stream Harsit, Eastern Black Sea Basin, Turkey. There were 144 data for each variable obtained on a fortnightly basis during March 2009 and February 2010. In the ANN method, the used data for training, testing and validation sets are 108, 24 and 12 of total 144 data, respectively. As the results of analyses, the smallest mean absolute error (MAE) and root mean square error (RMSE) values for validation set were obtained from the ANN method with 11.40 and 17.87, respectively. However these were 19.12 and 25.09 for RA. It was concluded that turbidity could be a surrogate for SSC in the streams, and the ANNs method used for the estimation of SSC provided acceptable results.     

Air Quality Management in Izmir Region of Turkey as Required by Clean Air Plans

Future (24 h later) daily ground level SO₂ concentration in Istanbul was modeled and predicted using a new and powerful technique, Artificial Neural Networks (ANN) in the case of meteorological parameters as input variables. Results show that the trend of SO₂ from higher values in winter to lower values in spring and summer, and again to higher values towards winter can be correctly represented by the neural networks. The model better predicted the lower SO₂ values in spring and summer seasons when compared to higher values in winter season because of the pattern distribution in training data sets. Beside the amount of the database, the more the variation of the values of the parameters in their own ranges, the more the network learns the database. As a result of this study, considerably successful results were obtained when considering the complex and nonlineer structure of the atmosphere, which is the source of the database.     

Influences of urban wastewaters on the stream water quality: a case study from Gumushane Province, Turkey

Urban wastewater in Turkey is primarily discharged without treatment to marine environments, streams and rivers, and natural and artificial lakes. Since it has been well established that untreated effluent in multi-use waters can have acute and chronic impacts to both the environment and human health, it is important to evaluate the consequences of organic enrichment relative to the structure and function of aquatic environment. We investigated the impacts of untreated municipal wastewater discharge from the city of Gumushane in the Eastern Black Sea Region of Turkey on the surface water quality of the stream Harsit. Several key water-quality indicators were measured: chemical oxygen demand (COD), ammonium nitrogen (NH ₄ ⁺ –N), nitrite nitrogen (NO ₂ ^? –N), nitrate nitrogen (NO ₃ ^? –N), total Kjeldahl nitrogen (TKN), total nitrogen (TN), orthophosphate phosphorus (PO ₄ ^3? –P), methylene blue active substances (MBAS), water temperature (t), pH, dissolved oxygen (DO), and electrical conductivity (EC). The monitoring and sampling studies were conducted every 15 days from March 2009 to February 2010 at three longitudinally distributed stations. While t, pH, DO, and EC demonstrated relatively little variability over the course of the study, other parameters showed substantial temporal and spatial variations. The most dramatic differences were noted in COD, NH ₄ ⁺ –N, NO ₂ ^? –N, TKN, TN, PO ₄ ^3— P, and MBAS immediately downstream of the wastewater discharge. Concentration increases of 309 and 418 % for COD, 5,635 and 2,162 % for NH ₄ ⁺ –N, 2,225 and 674 % for NO ₂ ^? –N, 283 and 478 % for TKN, 208 and 213 % for PO ₄ ^3? –P, and 535 and 1,260 % for MBAS were observed in the summer and autumn, respectively. These changes were associated with greatly diminished seasonal stream flows. Based on NO ₂ ^? –N, TKN, PO ₄ ^3— P, and MBAS concentrations, it was concluded that Harsit stream water was correctly classified as polluted. The most telling parameter, however, was NH ₄ ⁺ –N, which indicated highly polluted waters in both the summer and autumn. The elevated concentrations of both P and N in the downstream segment of the stream triggered aggressive growth of submerged algae. This eutrophication of river systems is highly representative of many urban corridors and is symptomatic of ongoing organic enrichment that must be addressed through improved water treatment facilities.     

Variation of total organic carbon content along the stream Harsit, Eastern Black Sea Basin, Turkey

The TOC in surface waters and wastewater is an important analytical parameter describing the total content of all organic substances containing carbon. In practice, the TOC originated from natural and anthropogenic sources, and even if it is not directly responsible for dangers on human health, its determination is important for any kind of water that is used by public. The aim of this study was to determine variation of total organic carbon (TOC) and total carbon (TC) content in the stream Harsit, which courses in Eastern Black Sea Region, Turkey. Sampling was fortnightly conducted in each of the four seasons between March 2009 and February 2010. A total of 230 water samples were collected from ten sampling stations along the main branch of the stream Harsit with 143 km of length. Obtained TOC values were evaluated and used to classify the water quality of stream Harsit, according to the Turkish Water Pollution Control Regulation (TWPCR). The annual average TOC content values for the stations were found between 2.33 and 6.97 mg/L. It was seen that the TOC content have increased along the streamcourse of Harsit until the fourth station, where reaches its maximum value. The TOC content, then, has decreased and the minimum value was observed in the eighth station. The results showed that, except in winter season, maximum TOC content observed in many of the water samples were above Class I water standard indicated in TWPCR, which classifies the water resources according to the different area of uses. It was also found that TOC has a small contribution to TC and the highest TOC content in stream waters were measured in Gumushane station where direct discharge of city wastewaters and solid waste dumping to the stream were observed.     

Air Quality Management in Izmir Region of Turkey as Required by Clean Air Plans

As a first step to work out an abatement plan against air pollution, a local emission inventory with 1 hr temporal and 1 km spatial resolution in the city of Izmir and its surroundings was prepared. The study area consisted of a 200 × 170 km² rectangle having the city of Izmir at the centre. The studied pollutants were total particulate matter (PM), sulfur oxides (SO_x), nitrogen oxides (NO_x), volatile organic compounds (VOC) and carbon monoxide (CO). Emissions of these pollutants were determined by estimation methods making use of suitable emission factors. Emission sources were evaluated in three categories; point, area and line sources. For year 2000 total emissions in the study area on an average day were estimated as 173 tons PM, 299 tons SOx, 136 tons NOx, 68 tons VOC and 320 tons CO. At the second part of the study, calculated emissions were transformed into air quality predictions in the area by using the Industrial Source Complex – Short Term (ISCST3) dispersion model. Model results were tested with monitoring data from urban air quality stations obtained during the year 2000. Results of the past, present and future air quality estimates in the region were discussed. In order to do so, future scenarios including various control technology applications were formulated and tested to see their effect on the future air quality.     

Determining the level and cost of sickness presenteeism among hospital staff in Turkey

Objective. This study aimed to determine the associations between sickness presenteeism and socio-demographic factors, perceived health status and health complaints among hospital staff and to calculate the cost burdens and productivity losses attributed to presenteeism. Methods. A cross-sectional study was conducted using 951 hospital staff, including physicians, nurses, midwives, other health personnel and administrative staff working in two hospitals located in K?r?kkale province in Turkey. The health and work performance questionnaire developed by Kessler et al. was revised to measure sickness presenteeism. Results. After performing Student’s t test and a one-way analysis of variance, presenteeism was mostly observed in women, nurse-midwives, young employees, university health staff and health workers with low health status. Average productivity loss and cost of lost productivity per staff member were calculated as 19.92?h/TRY 315.57 for 2 weeks and 478.08?h/TRY 7573.68 for 1 year. Conclusions. The problem of sickness presenteeism is mostly observed in women and nurses. It causes both financial burdens and productivity losses for hospitals. These survey results are thus expected to provide critically important information on presenteeism for decision-makers and healthcare managers.