Global Attention to Turkey Due to Desertification

Desertification has recognized as an environmental problem by many international organizations such as UN, NATO and FAO. Desertification in Turkey is generally caused by incorrect land use, excessive grazing, forest fires, urbanization, industry, genetic erosion, soil erosion, salinization, and uncontrolled wild type plants picking. Due to anthropogenic destruction of forest, steppe flora gradually became dominant in Anatolia. In terms of biodiversity, Turkey has a significant importance in Europe and Middle East. Nine thousands plant species naturally grown in Turkey, one third of them are endemic. Also, endemic species of vertebrates, thrive in the lakes and marshy areas. The studies of modelling simulation of vegetation on the effects of Mediterranean climate during the Roman Classical period by using vegetation history showed that, in 2000 years BP, Mediterranean countries were more humid than today. Turkey is a special place on the global concern in terms of desertification because of biodiversity, agricultural potential, high population, social and economical structure, topographical factors and strategic regional location. Communication among scientists, decision makers and international non-profit organizations must be improved.     

Migration of polycyclic aromatic hydrocarbons (PAHs) in urban treatment sludge to the air during PAH removal applications

In the present study, the amounts of polycylic aromatic hydrocarbons (PAHs) penetrating into air during PAH removal applications from the urban treatment sludge were investigated. The effects of the temperature, photocatalyst type, and dose on the PAH removal efficiencies and PAH evaporation were explained. The sludge samples were taken from an urban wastewater treatment plant located in the city of Bursa, with 585,000 equivalent population. The ultraviolet C (UV-C) light of 254 nm wavelength was used within the UV applications performed on a specially designed setup. Internal air of the setup was vacuumed through polyurethane foam (PUF) columns in order to collect the evaporated PAHs from the sludge during the PAH removal applications. All experiments were performed with three repetitions. The PAH concentrations were measured by gas chromatography–mass spectrometry (GC-MS). It was observed that the amounts of PAHs penetrating into the air were increased with increase of temperature, and more than 80% of PAHs migrated to the air consisted of 3-ring compounds during the UV and UV-diethylamine (DEA) experiments at 38 and 53 °C. It was determined that 40% decrease was ensured in Σ₁₂ (total of 12) PAH amounts with UV application and 13% of PAHs in sludge penetrated into the air. In the UV-TiO₂ applications, a maximum 80% of Σ₁₂ PAH removal was obtained by adding 0.5% TiO₂ of dry weight of sludge. The quantity of PAH penetrating into air did not exceed 15%. UV-TiO₂ applications ensured high levels of PAH removal in the sludge and also reduced the quantity of PAH penetrating into the air. Within the scope of the samples added with DEA, there was no increase in PAH removal efficiencies and the penetration of PAHs into air was not decreased. In light of these data, it was concluded that UV-TiO₂ application is the most suitable PAH removal alternative that restricts the convection of PAH pollution.

Implications: Polycyclic aromatic hydrocarbon (PAH) evaporation rates from sludge samples obtained from an urban wastewater treatment plant were investigated here for the first time by employing removal applications. TiO₂ and diethylamine were used as photocatalysts in this study. A special device was designed and successfully used in this study. Treatment sludge can be a significant source of PAHs for the atmosphere. The data highlight the need for removal of PAHs in treatment sludge via methods limiting their evaporation to the air. It was observed that UV-TiO₂ application was the most suitable PAH removal alternative that restricts the convection of PAH pollution.     

Scientific basis of dissolved organic carbon limitation for landfilling of municipal treatment sludge – Is it attainable and justifiable?

This study evaluated the scientific and technical basis of the dissolved organic carbon (DOC) limitation imposed on municipal sludge for landfilling, mainly for assessing the attainability of the implemented numerical level. For this purpose, related conceptual framework was analyzed, covering related sewage characteristics, soluble microbial products generation, and substrate solubilization and leakage due to hydrolysis. Soluble COD footprint was experimentally established for a selected treatment plant, including all the key steps in the sequence of wastewater treatment and sludge handling. Observed results were compared with reported DOCs in other treatment configurations. None of the leakage tests performed or considered in the study could even come close to the prescribed limitation. All observed results reflected 10–20 fold higher DOC levels than the numerical limit of 800 mg/kg (80 mg/L), providing conclusive evidence that the DOC limitation imposed on municipal treatment sludge for landfilling is not attainable, and therefore not justifiable on the basis of currently available technology.     

Quantifying the Effects of Forest Management Strategies on the Production of Forest Values: Timber,Carbon, Oxygen,Water, and Soil

Forest management practices alter forest structure quantified with ecosystem characteristics and values. In this paper, we utilized a forest management simulation model to assess the effects of three forest management strategies focusing on timber production, carbon sequestration, oxygen production, soil erosion, and water production of a forest management unit in Turkey. A forest simulation model “ETÇAPSimülasyon” was developed and used to project forest ecosystem development over 100 years under three forest management policies of timber-oriented forest management (TFM), multipurpose forest management (MFM), and no intervention (NI). The results showed that TFM strategy produced more timber and its net present value than MFM and NI strategies did. The amount of carbon sequestration and oxygen production potential was also found to be the highest with TFM strategy than with the MFM and NI strategies. Compared with the other strategies, however, NI strategy produced the highest amount of water production and soil losses over the planning horizon. The effects of a forest management strategy depend mainly on the initial forest structure, the rate of development and the level of forest management interventions. Therefore, forest dynamics under various management strategies should be explained before the final management decision. Understanding long-term effects of any management strategies on forest structure will provide the basis for better reaching the management objectives.     

Study of Bulk and Sub-Event Wet Deposition in Gebze,Turkey

This study presents the chemical composition of bulk deposition during the period of February 1996–May 1997 and the chemical composition of sub-event wet deposition on 13 August 1997 in Gebze. Samples were analyzed for SO₄ ^2-, NO₃ ^-, Cl^-,Ca²⁺, Mg²⁺, K⁺, Na⁺, and NH₄ ⁺ in addition to pH. The source of some ionic components in the bulk deposition such as K⁺ and Ca²⁺ were found to be the terrestrial regions, as expected. The (non-sea Cl^-)/Cl^- ratio of 0.05 suggests that the very large portion of Cl^- in the bulkdeposition was of marine origin. The ratio of (non-sea SO₄ ^2-)/SO₄ ^2- varied between 0.86 and 0.99,indicating that the main source of sulfate was not the sea. It is found that the sulfate and calcium concentrations were highest in summer and lowest in fall. The analysis of bulk deposition also indicated that nearly 24% of the events were acidic (pH < 5.6). During sub-event wet deposition collectedon the same site pH decreased continually, and during the passageof cold front concentrations of Cl^-, SO₄ ^2- and NO₃ ^- increased.     

Characterization of Environmentally Friendly Polymers by Inverse Gas Chromatography: I Amylopectin

Amylopectin, as a potato starch based polymer, with a molecular weight of six million gram/mol was characterized using the Inverse Gas Chromatography Method (IGC). DSC method was also used to measure the glass and melting temperatures. Both DSC and IGC agreed well on a T_g of 105°C and T_m of 160–166°C. Nineteen solutes (solvents) were injected onto a chromatographic column containing amylopectin. These solutes revealed the interaction of alkanes with AP, and the wettability and water intake of AP. Alkanes showed exothermic values of interaction parameters which were increased as the temperature increased and as the number of carbons in the alkane series decreased. Retention diagrams of these solutes in a temperature range of 80–200°C revealed two zones, crystalline and amorphous. T_g and T_m were measured using these zones which complimented the DSC values. The two zones were used to calculate the degree of crystallinity below the melting temperature which ranged from 85% at 104°C to 0% at 161°C. The dispersive component of the surface energy of amylopectin was measured using alkanes which ranged from 25.35 mJ/m² at 80°C to 8.47 mJ/m² at 200°C. This is attributed to the weak crystalline surface of AP at 80°C and when the surface melted at 160°C the surface energy decreased due to the thermal expansion of the surface.     

An online air pollution forecasting system using neural networks

In this work, an online air pollution forecasting system for Greater Istanbul Area is developed. The system predicts three air pollution indicator (SO(2), PM(10) and CO) levels for the next three days (+1, +2, and +3 days) using neural networks. AirPolTool, a user-friendly website (http://airpol.fatih.edu.tr), publishes +1, +2, and +3 days predictions of air pollutants updated twice a day. Experiments presented in this paper show that quite accurate predictions of air pollutant indicator levels are possible with a simple neural network. It is shown that further optimizations of the model can be achieved using different input parameters and different experimental setups. Firstly, +1, +2, and +3 days' pollution levels are predicted independently using same training data, then +2 and +3 days are predicted cumulatively using previously days predicted values. Better prediction results are obtained in the cumulative method. Secondly, the size of training data base used in the model is optimized. The best modeling performance with minimum error rate is achieved using 3-15 past days in the training data set. Finally, the effect of the day of week as an input parameter is investigated. Better forecasts with higher accuracy are observed using the day of week as an input parameter.     

Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 microm; PM10) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a "Very Clear Air Zone" to a "Polluted Air Zone". Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM10 pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM10 levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.     

Classification of dimension stone wastes

Purpose

For countries in which the stone industry is well developed, opposition to quarry and plant waste is gradually increasing. The primary step for waste control and environmental management is to define the problem of concern. In this study, natural building stone wastes were classified for the first time in the literature.

Methods

Following on-site physical observations and research at more than 50 quarries and 20 plants, stone wastes were classified as (1) solid, (2) dust and (3) semi-slurry, slurry and cake.

Conclusions

As a result of this study, the characteristics of wastes, their main environmental threats and the industries in which wastes could be used were defined for each group.     

Experimental investigation of dust pollutants and the impact of environmental parameters on PV performance: an experimental study

The accumulation of dust pollution on the photovoltaic (PV) module can have a significant effect on the productivity and efficiency of PV systems in different locations in the world. Dust which accumulated over time on the PV module and is based on weather conditions led to the reduction in the effectiveness of solar cells. The aim of this research was to experimentally investigate the effect of the natural dust and the effects of environmental parameters on PV performance. The experiments were conducted to propose a model for the current, voltage, power and efficiency and to simulate the effect of environmental parameters on PV performance. The natural dust investigated consisted of different compounds: SiO₂ (45.53 %), CaO (24.62 %), Al₂O₃ (10.83 %), Fe₂O₃ (10.46 %), MgO (6.33 %), K₂O (0.87 %), TiO₂ (0.45 %), SO₃ (0.24 %), MnO₂ (0.21), Cr₂O₃ (0.23 %), SrO (0.13 %) and NiO (0.09 %). It was found that the most accurate correlation is a polynomial from seventh degree for current, voltage, power and efficiency, fourth degree for solar radiation and temperature, cubic degree for humidity and wind velocity. The coefficients of general model are 0.6343, 0.0110, 0.0 and 0.0001 for PV module, respectively, with 0.0011 fitting factor. The proposed model has been validated using models in the literature.