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Fatma Kunt

Bio: Fatma Kunt is an academic researcher from Selçuk University. The author has contributed to research in topics: Air pollution & Environmental science. The author has an hindex of 4, co-authored 12 publications receiving 37 citations.

Papers
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Journal ArticleDOI
TL;DR: Artificial neural network and an adaptive neuro-fuzzy logic method developed to approximate the impact of certain environmental conditions on air quality and sulphur dioxide pollution level are used and used with this study in Konya city centre.
Abstract: Increasing industrial developments increased the environmental pollution problems in many cities of the world. Air quality modelling and indexes are used to introduce the information on local air quality indicators in polluted regions. Estimation and monitoring of air quality in the city centres are important due to environmental health and comfort of human-related topics. Air quality approximation is a complicate subject that artificial intelligent techniques are successfully used for modelling the complicated and nonlinear approximation problems. In present study, artificial neural network and an adaptive neuro-fuzzy logic method developed to approximate the impact of certain environmental conditions on air quality and sulphur dioxide pollution level and used with this study in Konya city centre. Data of sulphur dioxide concentrations were collected from 15 selected points of Konya city for prediction of air quality. Using air quality standards, air quality was discussed by considering the sulphur dioxide concentration as independent variables with meteorological parameters. Different meteorological parameters were used for investigation of pollution relation. One of the important modelling tools, adaptive network-based fuzzy inference system model, was used to assess performance by a number of checking data collected from different sampling stations in Konya. The outcomes of adaptive network-based fuzzy inference system model was evaluated by fuzzy quality charts and compared to the results obtained from Turkey and Environmental Protection Agency air quality standards. From the present results, fuzzy rule-based adaptive network-based fuzzy inference system model is a valuable tool prediction and assessment of air quality and tends to propagate accurate results.

20 citations

02 Jan 2018
TL;DR: In this article, metal industry wastewaters were analyzed in order to determine plant species whether they are sensitive or tolerant to heavy metals, and phytotoxicity tests were conducted with different plant species.
Abstract: Metal industry wastewaters include different types of heavy metals with respect to the metal production processes and products. There are several methods used for metal production industry such as refining and smelting operations. Both may produce air emissions like SO2 and particulate matter, wastewater originating from floatation and leachate, and other wastes like sludge and slag. Heavy metals of metal industry wastewaters are nickel, brass, chrome, gold, cadmium, copper, brass, and silver. Most of them may give severe damage to human and environment. For example, chrome ion leads to lung cancer, stomach ulcer, kidney and liver function disorders and death on human. Thus, heavy metal containing wastewaters could be very dangerous. Besides, plant species which have capability of accumulate heavy metals can be an option to bioaccumulate metal industry wastewaters while plant species which are sensitive to heavy metals can be used as a plant for phytotoxicity tests. In this study metal industry wastewaters were analysed in order to determine plant species whether they are sensitive or tolerant to heavy metals. During analysis phytotoxicity tests were conducted with different plant species.

4 citations

01 Jan 2008
TL;DR: In this study, noise maps of five different hospitals with excessive patients in Konya have been given with the help of GIS and recommendations were given in order to take measures fort the problematic places.
Abstract: Noise is an important environmental problem today and can be defined as undesirable voices which affect people's auditory health and perception negatively, damage physical and psychological balance, bring negative effects on people. Noise pollution has become an important problem in metropolitan cities, because of the increasing population, industry and traffic load. Usage area of GIS has increased as a result of speedy development in information technology. Geografic Information System applications on health and environment gained currency in our country as well as in many country and have found application area in health centers, recently. Detecting noise level by preparing noise maps with using GIS has become very important fort in the hospital management and patients in taking measures for annoying voices to provide patients who come to hospital leave peacefully. In this study, noise maps of five different hospitals with excessive patients in Konya have been given with the help of GIS and recommendations were given in order to take measures fort the problematic places.

4 citations

31 Dec 2013
TL;DR: In this article, aylarinda bazi gunlerde hava kirliligi haftayi bulacak sekilde meydana gelen yogun sis ve inversiyon tabakasiyla sehir merkezinde insanlarin rahatsizlik duyacagi boyuta ulasmasina sebep olmaktadir.
Abstract: Calismada bir tarim ve sanayi kenti olan Konya ilinin hava kalitesine meteorolojik, topografik ve mekânsal etkileri incelenmistir. Kentinin yerlesim alaninin onemli bir kismi verimli tarim arazileri uzerindedir. Sanayi ve yerlesim alanlarindan kaynaklan hava kirleticileri kuzey, Kuzey-dogu ve Kuzey-bati kesimlerde bulunan yukseltileri kis aylarinda cogunlukla asamadan il merkezi uzerinde yogunlasmaktadir. Diger taraftan, Konya hava kirliligi bakimindan Turkiye’de onde gelen illerden biridir. Kis aylarinda bazi gunlerde hava kirliligi haftayi bulacak sekilde meydana gelen yogun sis ve inversiyon tabakasiyla sehir merkezinde insanlarin rahatsizlik duyacagi boyuta ulasmasina sebep olmaktadir. Benzer olay maalesef Turkiye’de hava kirliligi yasanan bircok ilde de gorulen onemli ve care bulunmasi gereken bir durum olarak karsimiza cikmaktadir.

4 citations


Cited by
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Journal ArticleDOI
TL;DR: A protocol by Maier et al. (2010) for ANN model development is presented and applied to assess journal papers dealing with air pollution forecasting using ANN models, highlighting the need for developing systematic protocols for developing powerful ANN models.
Abstract: Research activity in the field of air pollution forecasting using artificial neural networks (ANNs) has increased dramatically in recent years. However, the development of ANN models entails levels of uncertainty given the black-box nature of ANNs. In this paper, a protocol by Maier et al. (2010) for ANN model development is presented and applied to assess journal papers dealing with air pollution forecasting using ANN models. The majority of the reviewed works are aimed at the long-term forecasting of outdoor PM10, PM2.5, and oxides of nitrogen, and ozone. The vast majority of the identified works utilised meteorological and source emissions predictors almost exclusively. Furthermore, ad-hoc approaches are found to be predominantly used for determining optimal model predictors, appropriate data subsets and the optimal model structure. Multilayer perceptron and ensemble-type models are predominantly implemented. Overall, the findings highlight the need for developing systematic protocols for developing powerful ANN models.

217 citations

Journal ArticleDOI
TL;DR: It is concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease.

89 citations

Journal ArticleDOI
TL;DR: In this article , a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus.
Abstract: In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM2.5 and PM10 as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.

81 citations

Journal ArticleDOI
TL;DR: In this paper, a systematic review of current knowledge gained by 73 published papers on experimental determination of SARS-CoV-2 RNA in air comparing different environments: outdoors, indoor hospitals and healthcare settings, and public community indoors.

47 citations