Seasonal variation of PCDD/Fs in the metropolis of Istanbul,Turkey

Atmospheric concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) compounds were investigated at three different regions of Istanbul which reflect urban, urban/industrial, and sub-urban characteristics. Air samples were collected simultaneously for both gaseous and particulate phases using high volume samplers on monthly time intervals from May 2011 to October 2012. The highest concentrations (3,056 fg/m³ and 156 fg I-TEQ/m³) were observed at the sampling site that reflects traffic, residential, and industrial emission source characteristics, while the lowest concentrations (829 fg/m³ and 38 fg I-TEQ/m³) were observed at the sampling point which is far away from centrum and reflects sub-urban characteristics. Concentrations of PCDD congeners were, in general, found to be higher than PCDF congeners, and OCDD, 1,2,3,4,6,7,8-HpCDD/F, and OCDF congeners were recorded to be the most abundant congeners. Winter season concentrations were also found to be higher especially in particulate phase. As a result, combustion processes such as motor vehicles and residential heating equipment were thought to be the principal sources of emissions of PCDD/F compounds when both congener profiles and seasonal variations are considered. Basic statistical evaluation of the data resembled high degree of inverse correlations between PCDD/F concentrations and UV and solar radiation.     

Invisible Face of Boron Pollution in Fluvial Ecosystem: The Level in the Tissues of Sentinel and Nectonic Organisms

Turkey is the largest producer of borate products in the world. Among four largest boron mines in Turkey two of them are located in basins of Orhaneli and Emet Streams. In this study, boron levels in abiotic (water–sediment) and some biotic elements (sentinel organisms; Asellus aquaticus, Gammarus pulex,Chironomus tentans, Limnodrilus hoffmeisteri and nektonic organism; Squalius cii) of Orhaneli and Emet Streams were investigated and their ranks among the food chain were demonstrated. Since Orhaneli and Emet Streams confluence to form Mustafakemalpaşa Brook which feeds Uluabat Lake which is one of the most important Ramsar fields of the world, Boron levels in those two streams have importance in terms of both continuances of aquatic systems. Present study results have shown that boron levels in water of both streams are much higher (vary between 8.64 and 16.73 mg L⁻¹) than not only Turkish Standard but also limits determined by WHO, US EPA, and NAS. Boron levels determined in sediments of two streams vary between 18.05 and 36.7 mg kg⁻¹. The highest boron level in the biotic elements was determined in liver of Squalius cii (34.64 mg kg⁻¹), it is followed by Limnodrilus hoffmeisteri (2.84 mg kg⁻¹), Chironomus tentans (2.11 mg kg⁻¹), and Gammarus pulex (1.98 mg kg⁻¹).     

A detailed investigation of ambient aerosol composition and size distribution in an urban atmosphere

This research was executed between March 2009 and March 2010 to monitor particulate matter size distribution and its composition in Istanbul. Particulate matter composition was determined using ion chromatography and inductively coupled plasma optical emission spectrometry. The sampling point is adjacent to a crowded road and the Bosporus Strait. Two prevailing particulate modes are found throughout PM₁₀ by sampling with a nine-stage low-volume cascade impactor. First mode in the fine mode is found to be between 0.43 and 0.65 μm, whereas the other peak was observed between 3.3 and 4.7 μm, referring to the coarse mode. The mean PM₁₀ concentration was determined as 41.2 μg/m³, with a standard deviation of 16.92 μg/m³. PM_0.43 had the highest mean concentration value of 10.67 μg/m³, making up nearly one fourth of the total PM₁₀ mass. For determining the effect of traffic on particulate matter (PM) composition and distribution, four different sampling cycles were applied: entire day, nighttime, rush hour, and rush hour at weekdays. SO ₄ ^?2 and organic carbon/elemental carbon proportions are found to be lower in night samples, representing a decrease in traffic. The long-range transports of dust storms were observed during the sampling periods. Their effects were determined analytically and their route models were run by the HYSPLIT model and validated through satellite photographs taken by the NASA Earth Observatory.     

Application of multivariate statistical techniques in the assessment of groundwater quality in seawater intrusion area in Bafra Plain, Turkey

Multivariate statistical techniques such as cluster analysis and principal component analysis were performed on 28 groundwater wells in Bafra Plain. Cluster analysis results show that the groundwater in the study area is classified into three groups (A, B, and C), and factor analysis indicates that groundwater is composed of 89.64 % of total variance of 12 variables and is mainly affected by three factors. Factor 1 (seawater salinization) includes concentrations of electrical conductivity, TDS, Cl^?, Na⁺, and sodium adsorption ratio, factor 2 (mixing water) includes δ¹⁸O, δD, and T, and factor 3 (fresh) includes Ca²⁺. For determination of the source of water, Ca/Cl, Cl/HCO₃, Mg/Cl, and Ca/Na as initials and Mg/Ca and SO₄/Cl as molar rates which were identified, the rates had been found to be very useful. Cluster analysis was made by using these rates and the waters were classified in two groups (group 1 and group 2). First group waters were affected by seawater, and the second group were very less affected by freshwater or seawater. According to the comparison of two different parameters, group 1 comprised group A and group B-2, -3, and -4 from the same wells, and group 2 comprised group B-1 and group C from the same well. As a result of this study, it could be said that multivariate statistical methods gave very useful results for the determination of the source.     

Impacts of seawater intrusion on soil salinity and alkalinity in Bafra Plain, Turkey

This study was carried out to investigate possible seawater intrusion into groundwater along the coastal lines of the Bafra Plain and salinity–alkalinity problems over land areas irrigated with water exposed to seawater intrusion were evaluated. For this purpose, 32 groundwater wells were selected over the plain, water samples were taken from these wells between October 2007 and September 2008, and chemical analyses were performed over these samples. Soil samples were taken from the fields irrigated with this water at 32 different locations at the end of the irrigation season in September 2008 from 0–30, 30–60, 60–90, and 90–120 cm soil depths and textures. EC, pH, Na, Ca, Mg, and K analyses were performed over these samples. Excessive seawater intrusion was observed in some parts of the plain and impacts of seawater intrusion decreased with the distance from the coastal line. It was determined that groundwater quality was significantly affected from seawater intrusion. Salinity and especially alkalinity problems were observed in land areas irrigated with this water and alkalinity increased with the rate of intrusion.     

Application of multivariate statistical techniques in the assessment of surface water quality in Uluabat Lake, Turkey

The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, [Formula: see text], NH(4)-N, NO(2)-N, NO(3)-N, [Formula: see text], BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.     

In vitro effects of erythromycin and florfenicol on primary cell lines of Unio crassus and Cyprinus carpio

Environmental Science and Pollution Research - The ubiquitous use of antibiotics leads exposure of these chemicals on non-target aquatic species, while the toxicity assays for these chemicals are...     

Does digitalization matter in green preferences in nexus of output volatility and environmental quality?

Environmental Science and Pollution Research - The fact is that output volatility and carbon dioxide (CO2) emissions move together over the period. This empirical study examines the dynamic effect...     

Identification of hotspots using different statistical methods in a region of manufacturing plants

Incident electromagnetic radiation hitting the Earth’s surface shows three phenomena as absorptivity, reflectivity and transmissivity where sum of the three is equal to one. The transmissivity is zero when the surface is opaque. There is a strong relationship between absorptivity and emissivity that is explained by Kirchhoff’s Law. Emissivity is managed by the thermal radiation on the Earth’s surface. Thermal radiation related with the heat transfer of the electromagnetic radiation is controlled by passing energy of atoms and molecules. There are different sources of energy other than the Sun such as geothermal activities, volcanoes and manufacturing plants that contributes to the emissivity of the surface. The thermal radiation produced by manufacturing plants contributes to the Earth’s surface temperature as well.In this study, land surface temperatures were estimated by using inverse Planck function from five Advanced Spaceborne Thermal Emission and Reflection Radiometer remote-sensing satellite sensor thermal infrared bands. It is aimed to highlight hotspots related to manufacturing plants in the region of Kocaeli, Turkey. The hotspots are examined statistically with the minimum noise fraction, the independent component analysis, the local Moran’s I index and the Getis-Ord G_i index methods by using land surface temperatures.     

The Importance of the Chosen Technique to Estimate Diffuse Solar Radiation by Means of Regression

The Ordinary Least Squares (OLS) is one of the widely used methods which is used for estimating the diffuse solar radiation. However, in order to use the OLS method in the estimation, the dataset must provide certain assumptions. In this study, alternative robust methods have been described and they were compared with the OLS method, which is used for estimating diffuse radiation frequently in an application. At the end of the analysis, the R² value obtained by the OLS method is less than the values obtained by M regression models. In other words, the explanation of the dependent value is weak when the OLS method is used. Finally, it can be said that the most appropriate method is Andrews for estimating the diffuse solar radiation.