Browsing by Author "Kunt, Fatma"

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The Classification Local Area Based Climatic Data Used
(2019) Mankolli, Hysen; Dursun, Şükrü; Symochko, Lyudmyla; Cekani, Mirela Lika; Zucchetti, Massimo; Merko, Flora Ndroqi; Sapuric, Zoran; Kongoli, Cezar; Kunt, Fatma
Bio climate concept is a wide concept and from ecologic angle it shows content elements combination that predominate or determinate the planted and animal life. The bio climate of one zone is considered as a combination between vegetation zone and climatic elements. The bio clime study on Korça - eco zone and the bioclimatic indexes give a view about the conception and using values of bio climate classification indexes. This study based on Emberger and FAO Model of learned Frenchman, which is the most quoted on studies with bioclimatic character on Mediterranean eco-zone for period 30 years. The Emberger Classification is known and applied, because it gives a detailed using about studied zone. The Emberger Classification is based on pluviometric index Q and vegetation index and gives a more detailed classification than others. After mathematic data processing and comparison of bioclimatic indexes according to respective classes is concluded that according to Emberger Korça – eco zone is classificated on three respective bio climates: Micro zone with semiarid bio climate with coefficient 60
Cost Analysis of Waste Collection and Transport
(2019) Kunt, Fatma; Dursun, Şükrü; Merko, Flora
Garbage is an end of product that is inevitable to emerge as a result of our vital activities. The ways of collecting, transporting and disposing of thes products also affect the environmental health and the country's economy, significantly. In the solid waste management system, the collection and transport of waste is the part that has the highest financial value, so the garbage collection and transportation systems must be designed in the best and economical way. It is of great importance to collect and transport the garbage by the authorities, which is formed as a result of human and human activities in the use areas such as home, school, workplace, park, industry. In this study, the methods and cost of waste collection and transportation of the waste to the disposal which were investigated. At the same time, garbage collection and transportation costs were analyzed in Selcuklu district of Konya province.
Indoor Formaldehyde Emission in Air and Health Impacts
(Sage Publication, 2019) Kunt, Fatma; Ayturan, Zeynep Cansu; Dursun, Şükrü; Mankolli, Hysen
In this review, formaldehyde emission sources in indoor air and its effects on human health are examined. The most important sources of formaldehyde compound, which has several different varieties, have many different usage areas such as kitchen materials, binders in wooden materials and chemical materials. Nowadays, people spend most of their time in a closed environment. There are 3 kinds of formaldehyde according to usage area. Formaldehyde is polymerized to produce urea formaldehyde, melamine formaldehyde and phenol formaldehyde. These substances are volatile and have harmful effects on indoor air.
Citation - WoS: 6
Citation - Scopus: 7
Measurement and Evaluation of Particulate Matter and Atmospheric Heavy Metal Pollution in Konya Province, Turkey
(SPRINGER, 2021) Kunt, Fatma; Ayturan, Zeynep Cansu; Yümün, Feray; Karagönen, İlknur; Semerci, Mümin; Akgün, Mehmet
Air pollution has negative effects on human health, visibility, materials, plants, and animal health. Particulate matters are one of the most important air pollutants that may create a risk for human health. Especially particulate matters, which are composed of heavy metals and cancer-causing chemicals such as PAH, dioxin, furan, can cause serious reactions in the respiratory tract. Heavy metals are so important because of their capability of accumulation in human tissues. Almost 0.01-3% of heavy metal content may be found in particulate matter. Coarse particulate matters (PM10) which have smaller diameters than 10 microns may enter from the respiratory system and reach the lungs. In this study, PM10 concentrations and heavy metal content (Lead, Nickel, Arsenic, Cadmium) of the samples were measured and evaluated concerning present regulations and limit values for different points in Konya Province, Turkey. The samples were taken at different seasons such as winter, summer, and spring for 16 days. According to the results of this study, in the winter season, PM10 concentration of the measurement point (Directorate Building) located at the settlement area was found the highest. In the summer season, PM10 concentration of the measurement point (Sille Junction) located at crossroads was found the highest. In spring season, maximum PM10 concentration was detected on the measurement point (KOS base station) located in the industrial area. Moreover, daily average nickel (Ni) concentration measured at KOS base station was found the highest and some other station located close to the industrial area and settlement areas were detected higher than average annual limit values in the winter period. Daily average lead (Pb) value was found at least 67% and maximum 98% higher at Sille and Besyol Junctions, but below the annual average limits. Daily average cadmium (Cd) value was mostly calculated in the Directorate Building winter measurement, but it did not exceed the limit value during the measurement periods. Daily average arsenic (As) values at Directorate Building and Karkent measurement points in the winter period were found higher than the annual average limit values. Only daily average nickel concentrations were detected higher than the annual average limits for the summer and spring period at the KOS base station measurement point.
Citation - WoS: 6
Citation - Scopus: 8
Modeling and Assessment of Pm10 and Atmospheric Metal Pollution in Kayseri Province, Turkey
(MDPI, 2023) Kunt, Fatma; Ayturan, Zeynep Cansu; Yumun, Feray; Karagönen, Ilknur; Semerci, Mumin; Akgün, Mehmet
Air pollution has numerous detrimental consequences for human health, visibility, climate, materials, plant health, and animal health. A portion of air pollution consists of metals, which are emitted into the environment via the combustion of fossil fuels, industrial activities, and the incineration of metal-containing products. In this work, the particulate matter and particle-related metal pollution from various sources, in the Turkish province of Kayseri, were determined. AERMOD modeling was also used to examine the distribution of PM10 around the Kayseri Organized Industrial Zone (OIZ). Particulate matter (PM10) samples were collected using MCZ dust collecting devices at six monitoring locations mainly affected by residential heating (Hurriyet, Talas, and Kocasinan), industry (OIZ), and traffic (Tramway and Cumhuriyet) during the autumn/winter months and at three monitoring locations mainly affected by residential heating (Kocasinan), industry (OIZ), and traffic (Tramvay) during the spring months. ICP-MS analysis was used to assess the concentrations of the heavy metals (Pb, As, Cd, and Ni) in samples collected over 6 different time periods of 16 days each. During the autumn/winter months, the concentrations of Pb near roadways were found to exceed the Air Quality Assessment and Management Regulation of Turkey (AQAMR) limit value. During all the sampling periods, the Ni and Cd concentrations were below the AQAMR limit values. At the points associated with winter heating, the concentrations exceeded the AQAMR limit value, which may result from coal combustion.
Citation - Scopus: 1
A Review Investigation of the Usage Artificial Neural Networks on Air Pollution Modeling
(Hysen MANKOLLI, 2023) Kunt, Fatma; Kopuklu, Buse Nur; Cansu Ayturan, Zeynep; Dursun, Şükrü
Air pollution is one of the most important problems that negatively impacts human health and disrupts the ecological balance by changing the atmosphere because of the pollutants formed as a result of natural events and human activities. This problem is growing because of the increase in population, the development of industrialization and urbanization. Pollutants that cause air pollution reaching the atmosphere directly without changing their form are sulfur dioxide (SO2), hydrogen sulfide (H2S), nitrogen monoxide (NO), nitrogen dioxide (NO2), and carbon monoxide (CO), carbon dioxide (CO2) and particulate matter. Secondary pollutants are formed by reacting with other substances in the atmosphere after leaving the source are sulfur trioxide (SO3), sulfuric acid (H2SO4), ozone(O3), aldehydes, peroxyacetyl nitrate (PAN), and heavy metals. Besides, air pollution causes acid rain, increases acidity in lakes, destroys forests, damages agricultural and animal products, and significantly disrupts the ecological balance, especially in industrial countries Therefore, this issue should be evaluated in many ways such as modelling to predict future episode, monitoring to assess present air pollution levels efficiently and taking preventive precautions with respect to these evaluations. Artificial neural networks are one of the mostly used artificial intelligence prediction techniques for prediction of air pollutant future concentrations. It uses multilayer perceptron technique which consists of at least three layers of nodes: an input layer, a hidden layer, and an output layer for estimating recent atmospheric events and air quality. This study aims to examine the studies on the use of artificial neural network models to predict air pollution concentrations accurately and swiftly. It has been proven that the application of this method for air pollution prediction allows the improving of prediction accuracy. © 2023, Hysen MANKOLLI. All rights reserved.
STATISTICAL ANALYSIS AND EVALUATION OF PM CONCENTRATIONS DURING THE DUST STORMS AT MAY 2020 FOR SELÇUKLU DISTRICT OF KONYA CITY, TURKEY
(Uludağ Üniversitesi, 2021) Kunt, Fatma; Dursun, Şükrü; Ayturan, Zeynep Cansu
Dust storms are widespread events that occur several times a year and spread over many countries of the world relating the wind direction and speed. Especially particulate matter (PM) is the main pollutant spread over by these storms. Because of the dust storms, PM concentrations increase rapidly in the areas found on the way of dust storm passes In this study, statistical evaluation was made accordingly the PM data measured with personal measurement device in Selçuklu District of Konya and the meteorological and the air pollution data provided from air quality monitoring station, which is affiliated by the Ministry of Environment and Urbanization, located nearby. Pearson correlation test has been applied to both data sets and a significant relationship has been detected between the measured and provided data. Moreover, multiple linear regression was applied to the data for $PM_{2.5}$ and $PM_{10}$ separately. Adjusted $R^2$ of the analysis has been found as 0.573 and 0.559 respectively for $PM_{2.5}$ and $PM_{10}$ which explains almost half of the relationship between PM and meteorological variables. The highest positive effect on PM pollution was determined as air temperature. Finally, principal component analysis (PCA) was applied to both data and 4 different principal components were detected. Measured $PM_{2.5}$ and $PM_{10}$, air temperature, and relative humidity were clustered at the same component group.