Embed Size (px)
Citation preview
The 1st International Conference on
Air – Land – Sea Interaction
ICALSI2019
Conference Proceedings
The 1st International Conference on
Air – Land – Sea Interaction
4-5 April 2019, Baku, Azerbaijan
Organized by
Edited by: Orhan ŞEN, Istanbul Technical University, Turkey
Rovshan ABBASOV, Khazar University, Azerbaijan
Ceyhan KAHYA, Istanbul Technical University, Turkey
Zafer ASLAN, Istanbul Aydın University, Turkey
ISBN: 978-975-561-502-8
Abstracting and nonprofit use of the material is permitted with credit to the source. Instructors are
permitted to photocopy isolated articles for noncommercial use without fee. The authors have the right
to republish, in whole or in part, in any publication of which they are an author or editor, and to make
other personal use of the work. Any republication or personal use of the work must explicitly identify
prior publication in Proceedings of Abstracts and Papers (e-Proceedings) of the 1st International
Conference on Air – Land – Sea Interaction including the page numbers.
All rights reserved.
All papers in the proceedings have been peer reviewed by experts in the respective fields responsibility
for the contents of these papers rests upon the authors.
Copyright © 2019
Editors: Orhan SEN Rovshan ABBASOV
Ceyhan KAHYA
Zafer ASLAN
ISBN: 978-975-561-502-8
PREFACE
Air-sea-land interactions and the ocean-biosphere system have been causing changes in the
atmosphere-ocean-biosphere intersection for 100 years. At the end of the 1940s, we were
interested in the study of weather forecasting, and this led to research in atmospheric sciences. The
ocean absorbs most of the heat from the sun, re-distributes this heat around the world, and warms
the atmosphere from the bottom. The interactions among air – land – sea exert strong influences
on the variability of climate, terrain environment, and many aspects of our earth that are crucial
for our human beings. Efforts are underway to obtain longer-term reliable estimates and to increase
regional input parameters in short-term forecasts. Atmospheric Sciences nowadays are involved
in a multi-disciplinary and collaborative study.
The 1st International Conference on “Air-Land -Sea Interaction (ICALSI 2019)” was held on April
4-5, 2019 in Baku, Azerbaijan. The conference was jointly organized by Khazar University, the
UNESCO Chair on Eremology, Ghent University, Belgium, Istanbul Aydın University, Istanbul
Technical University, Chinese Academy of Sciences, and Eurasian Universities Union (EURAS).
We have organized ICALSI2019 to understand, simulate and eliminate limitations of researches
together with participants. The idea of performing this symposium emerged at the 8th Symposium
of Atmospheric Sciences (ATMOS 2017) organized at Istanbul Technical University, Turkey.
After the discussions, the idea of the conference on air-sea-land interactions was suggested by
Hon. Prof. Dr. Donald GABRIELS, UNESCO Chair on Eremology, Ghent University, Belgium.
One of the editorial board members, Prof. Dr. Zafer ASLAN is former fellow of these graduate
programs coordinated by Prof. Dr. Khristina KATSAROS in University of Washington in 1986.
The ICALSI 2019 and periodic conferences will provide an opportunity of interactions and co-
operations for scientists from different countries wit specialist researchers and young scientists in
this field. The conference intends to discuss and to present recent studies on interactions among
air-land-sea and environmental and climatic variability. It also covers new methodologies and
techniques on graduate programs in this field. In this conference, all aspects of air-land-sea
interaction are discussed in a large time and space scale. The main issues include but are not limited
to the land, ocean, air-sea interface, heat, momentum and flux, boundary layer structure, and wind
and solar energy. The conference consists of plenary, general, and joint sessions, as well as a
workshop on inter-institutional co-operations in research.
We sincerely would like to thank all participants for the high-level presentations, focused debates
and discussions, and for the exchange of information during the ICALSI 2019.
Editor in Chief: Orhan ŞEN
Editorial Board: Rovshan ABBASOV
Ceyhan KAHYA
Zafer ASLAN
April, 2019
http://www.icalsi.itu.edu.tr/icalsi2019
Chair
Zafer ASLAN, Istanbul Aydın University, Istanbul, Turkey
Co-Chairs
Rovshan ABBASOV, Khazar University, Baku, Azerbaijan
Orhan ŞEN, Istanbul Technical University, Istanbul, Turkey
Lin WANG, Chinese Academy of Sciences, Beijing, China
Honorary Board
Hamlet ISAXANLI, Founder, Khazar University, Baku, Azerbaijan
Mehmet KARACA, Rector, Istanbul Technical University, Istanbul, Turkey
Mustafa AYDIN, President, Istanbul Aydın University, Istanbul, Turkey
Yadigar IZMIRLI, Rector, Istanbul Aydın University, Istanbul, Turkey
Jiang ZHU, DirectorChinese Academy of Sciences, Beijing, China
Organizing Committee
Elshan ABDULLAYEV, Institute of Geography, AMEA, Baku, Azerbaijan
Zafer ASLAN, Istanbul Aydın University, Istanbul, Turkey
Hasan HEPERKAN, Istanbul Aydın University, Istanbul, Turkey
Donald GABRIELS, UNESCO Chair on Eremology, Ghent University, Belgium
Irada KHALILOVA, Khazar University, Baku, Azerbaijan
Orhan ŞEN, Istanbul Technical University, Istanbul, Turkey
Ahmet Duran ŞAHİN, Istanbul Technical University, Istanbul, Turkey
Lin WANG, Chinese Academy of Sciences, Beijing, China
Steering Committee Didem ODABASI CINGI, Istanbul Aydın University, Istanbul, Turkey
Zeki ÇELİKBAŞ, Istanbul Technical University, Istanbul, Turkey
RASHAD KHALİGOV, Khazar University, Azerbaijan
Yuyun LIU, Chinese Academy of Sciences, Beijing, China
Paul OKON, Associate ICTP, Italy
Evren ÖZGÜR, Istanbul Medeniyet University, Istanbul, Turkey
İlayda KURŞUN, İstanbul Technical University, Istanbul, Turkey
Mahammad SHARİFOV, Khazar University, Azerbaijan
Adil TEK, Boğaziçi University, Istanbul, Turkey
International Advisory Committee Donald GABRIELS, UNESCO Chair on Eremology, Ghent University, Belgium
Flippo GIORGI, ICTP, Head, Earth Systems Physics, Trieste, Italy
Wen CHEN, Chinese Academy of Sciences, Beijing, China
Erica COPOLLA, ICTP Earth Systems Physics, Trieste, Italy
Wim CORNELIS, UNESCO Co-Chair on Eremology, Ghent University, Belgium
Carmelo DAZZI, University of Palermo, President ESSC, Italy
Ricardo FARNETTI, ICTP Earth Systems Physics, Trieste, Italy
Enrico FEOLI, University of Trieste, Italy
Michael FULLEN, University of Wolverhampton, UK
İsmail GÜLTEPE, Toronto, Canada
Jorgen JENSEN, NCAR, Boulder, Colorado USA
In Sik KANG, APEC Climate Center (APCC)
Fred KUCHARSKI, ICTP Earth Systems Physics, Trieste, Italy
Pammy MANCHANDA, Guru Nanak Dev University, Amritsar, India
José Luis RUBIO, Univeristy of Valencia, Spain Luis M Sánchez RUIZ, University of Polytechnic, Valencia, Spain
Abul Hasan SIDDIQI, Sharda University, NCR, India
Scientific Committee
Rza MAHMUDOV, Ministry of Ecology and Natural Resources of Azerbaijan Republic
Elshan ABDULLAYEV, Institute of Geography, AMEA, Baku, Azerbaijan
Rovshan ABBASOV, Khazar University, Baku, Azerbaijan
Zelha ALTINKAYA, Yalova University, Yalova, Turkey
Zafer ASLAN, Istanbul Aydın University, Istanbul, Turkey
Duncan AXISA, NCAR, Boulder, USA
Robert BORNSTEIN, San Jose State University, USA
Zafer BOYBEYİ, George Mason University, USA
Roelof BRUINTJES, NCAR, Boulder, USA
Ivana Herceg BULIC, University of Zagreb, Croatia
Don COLLINS, Texas A&M University, USA
Deniz O. DEMİRCİ, Boğaziçi University, Istanbul, Turkey
Funda DÖKMEN, Kocaeli University, Izmit, Turkey
Gokhan ERDEMİR, Istanbul Zaim University, Istanbul, Turkey
Gunay Erpul, Ankara University, Turkey
Donald GABRIELS, UNESCO Chair on Eremology, Ghent University, Belgium
Ali GÜNEŞ, Istanbul Aydın University, Istanbul, Turkey
Mikdat KADIOGLU, Istanbul Technical University, Turkey
Ceyhan KAHYA, Istanbul Technical University, Turkey
Doğan KANTARCI, Istanbul University, Turkey
Kasım KOÇAK, Istanbul Technical University, Istanbul, Turkey
Deyanira LOBO, Central University of Venezuela
Sibel MENTEŞ, Istanbul Technical University, Turkey
Mehmet Talad ODMAN, Georgia Institute of Technology, USA
Gürcan ORALTAY, Marmara University, Turkey
Güven ÖZDEMİR, Istanbul Technical University, Istanbul, Turkey
Hasan Sabri ÖZTÜRK, Ankara University, Turkey
Ahmet Duran ŞAHİN, Istanbul Technical University, Istanbul, Turkey
Orhan ŞEN, Istanbul Technical University, Istanbul, Turkey
Ömer Lütfi ŞEN, Istanbul Technical University, Turkey
Elçin TAN, Istanbul Technical University, Turkey
Hasan TATLI, Çanakkale Onsekiz Mart University, Turkey
Ali TOKAY, University of Maryland-Baltimore, USA
Ahmet TOKGÖZLÜ, Süleyman Demirel University, Isparta, Turkey
Doğanay TOLUNAY, Istanbul University, Turkey
Sema TOPÇU, Istanbul Technical University, Turkey
Hüseyin TOROS, Istanbul Technical University, Turkey
Osman UÇAN, Altınbaş University, Istanbul, Turkey
Lin WANG, Chinese Academy of Sciences, Beijing, China
Yalçın YÜKSEL, Yıldız Technical University, Istanbul, Turkey
Contents LAND DEGRADATION AND DESERTIFICATION: AN INTERACTION OF LAND, WATER
AND WEATHER ...................................................................................................................................... 10
Donald Gabriels ....................................................................................................................................... 10
FLOATING SOLAR PHOTOVOLTAIC (FSPV) AND AN APPLICATION IN ISTANBUL,
TURKEY ................................................................................................................................................... 11
Ahmet Duran SAHIN, Mustafa Kemal KAYMAK ................................................................................ 11
PROSPECTS OF THE CONSUMPTION OF BIOFUELS IN AZERBAIJAN .................................. 13
Yusifova Mahluga, Sultanova Nigar ....................................................................................................... 13
THE INFLUENCE OF CONTEMPORARY CLIMATE CHANGES TO
HYDROMETEOROLOGICAL SECURITY OF TRACECA ............................................................. 19
Rza Mahmudov ....................................................................................................................................... 19
DEVELOPING PROTECTION AND SE SCENARIOS SCENARIOS FOR THE KHOJASAN
LAKE, AZERBAIJAN ............................................................................................................................. 20
Rovshan Abbasov .................................................................................................................................... 20
SEQUENCE ANALYSIS OF DREB GENE FROM WHEAT GENOTYPE 'BARAKATLİ 95' ..... 21
G. R. Abdullayeva, S. M. Rustamova, I. M. Huseynova ........................................................................ 21
STUDY OF SULFUR, NITROGEN-ORGANIC COMPOUNDS OBTAINED FROM
ECOLOGICALLY PURE GLYCEROL DERIVATIVES ................................................................... 22
V. Farzaliyev, G. Ismailova, B. Musayeva, N. Novotorjina ................................................................... 22
TRANSBOUNDARY POLLUTION IN THE KURA RIVER BASIN ................................................ 24
Rashail Ismayilov .................................................................................................................................... 24
DYNAMICS OF SOME CARBON AND NITROGEN METABOLISM ENZYMES DURING THE
DAY IN VARIOUS WHEAT GENOTYPES UNDER DROUGHT .................................................... 25
Ulduza Gurbanova, Shahniyar Bayramov, Irada Huseynova .................................................................. 25
OCCURRENCE AND DIVERSITY OF SINGLE AND DOUBLE VIRAL INFECTIONS OF
SOLANACEOUS CROPS IN AZERBAIJAN ....................................................................................... 26
N. F. Sultanova ........................................................................................................................................ 26
ASSESSMENT OF ENVIRONMENTAL POLLUTION ALONG THE COASTLINES OF THE
CASPIAN SEA .......................................................................................................................................... 27
Albert Tagiev, Imran Amirov, Alibaba Niftaliyev .................................................................................. 27
IDENTIFICATION OF VERTICILLIUM DAHLIAE RESISTANT COTTON GENOTYPES
USING CHROMOSOME SUBSTITUTION LINES ............................................................................ 28
Ruhangiz Mammadova, Afag Musayeva, Leyla Nagiyeva, Efsane Abdullayeva ................................... 28
AIR POLLUTION IN ROAD TRANSPORT OF AZERBAIJAN ....................................................... 29
Rovshan Karimov .................................................................................................................................... 29
DIURNAL TEMPERATURE-RELATED DYNAMICS OF GLUTATHIONE REDUCTASE
ACTIVITY IN WHEAT GENOTYPES UNDER DROUGHT ............................................................ 30
Lale Aydinli, Durna Aliyeva ................................................................................................................... 30
CONCEPTUAL APPROACH OF THE REGIONAL PROBLEM OF THE GLOBAL CLIMATE
CHANGE ................................................................................................................................................... 31
Rustam Rustamov ................................................................................................................................... 31
MICROSEISMIC ZONES OF THE CASPIAN SEA, FIRST IDENTIFIED ON THE BASIS OF
THE ABNORMALITIES IN THE YEAR-ROUND MONITORING OF THE UNDERGROUND
WATER’S REGIME IN AZERBAIJAN (1986-2014) ........................................................................... 32
Keramova Ramida Aga-Dadash .............................................................................................................. 32
CATALASE ACTIVITY DURING FLAG LEAF SENESCENCE OF WHEAT PLANTS UNDER
WATER DEFICIT .................................................................................................................................... 33
T. Y. Isgandarova, S. M. Rustamova ...................................................................................................... 33
AWARENESS OF UNIVERSITY STUDENTS ON RENEWABLE ENERGY ................................. 34
Zelha Altinkaya ....................................................................................................................................... 34
ENVIRONMENTAL PROBLEMS OF CLEANING WATER AND GROUND SURFACE FROM
PETROLEUM AND PETROLEUM PRODUCTS ............................................................................... 35
Jevahir Rajabli, Gulgez Nagiyeva ........................................................................................................... 35
THE ROLE OF THE KUR RIVER BASIN IN THE ECONOMY OF AZERBAIJAN .................... 37
Maksud Babaev, Gunay Hasanova .......................................................................................................... 37
CARBON EMISSIONS MARKET AND TRADING ............................................................................ 38
Korhan Hüseyin Sen, Fatih Anil and Orhan Sen ..................................................................................... 38
FLUCTUATION OF THE WINTERTIME ARCTIC OSCILLATION PATTERN ......................... 48
Lin Wang ................................................................................................................................................. 48
STUDY OF MEMBRANE STABILITY AND MEMBRANE DAMAGE RATE IN WHEAT
CULTIVARS UNDER HEAT STRESS .................................................................................................. 49
S. T. Zulfugarova, S. A . Omarova, S. M. Rustamova ............................................................................ 49
BIODIVERSITY ASSESSMENT OF DURUM WHEAT ACCESSION BASED ON MOLECULAR
MARKERS ................................................................................................................................................ 50
Gulnar Shikhseyidova, Samira Salayeva, Ellada Akhundova ................................................................. 50
MOLECULAR DIVERSITY OF STURGEONS (ACIPENSERIDAE) IN THE CASPIAN SEA
BASIN ........................................................................................................................................................ 51
Gulnara Guluzada, Javid Ojaghi ............................................................................................................. 51
MICROBIOLOGICAL PURIFICATION OF OIL POLLUTION IN CASPIAN SEA WATERS... 53
P.Mamedova, K.Kakhramanova, E.Babayev, T.Ibragimova .................................................................. 53
AIR POLLUTION AND INVERSION FEATURES IN ....................................................................... 56
ERZURUM, TURKEY ............................................................................................................................. 56
Orhan Şen, Esra Keşaf, Merve Yılmaz, Evren Özgür ............................................................................. 56
METEOROLOGICAL ANALYSIS OF WINTER SPORTS IN VARIOUS PLACES IN TURKEY
.................................................................................................................................................................... 68
Onur UYSAL, Elcin TAN, Zeynep F. UNAL, Orhan SEN .................................................................... 68
APPLICATION OF DEEP LEARNING METHOD FOR AIR POLLUTION FORECASTING ON
ANKARA ................................................................................................................................................... 79
Zeynep Feriha Unal, Umur Dinc, Huseyin Toros ................................................................................... 79
POSTERS .................................................................................................................................................. 87
CHANGE OF MICROFAUNIST RESIDUES BASED ON MINERALOGICAL AND
GEOCHEMICAL ANALYSIS (USING THE EXAMPLE OF THE KHARA-ZIRA AREA) .......... 88
Fatma Suleymanova ................................................................................................................................ 88
PREDICTABILITY AND FEEDBACK EFFECTS OF LAND SURFACE CLASSIFICATION
AND ATMOSPHERIC PARAMETERS ................................................................................................ 89
Buket ISLER, Zafer ASLAN .................................................................................................................. 89
RECONSTRUCTION OF QUANTITATIVE INDICATORS OF AZERBAIJAN'S CLIMATE IN
EARLY PLEISTOCENE BASED ON MINERALOGICAL INFORMATION ................................. 95
Muradly Eldar V. ..................................................................................................................................... 95
INVESTIGATION OF WIND STORMS and HEAVY RAIN AT NEWCASTLE WILLIAMTOWN
AIRPORT IN AUSTRALIA .................................................................................................................... 98
Emrah Tuncay Özdemir, Omer Yetemen, Zafer Aslan ........................................................................... 98
ABNORMAL CHANGES IN THE RADON FIELD IN THE UNDERGROUND WATER OF
AZERBAIJAN IN THE PREPARATION OF STRONG EARTHQUAKES (on the example of local
and remote earthquakes) ........................................................................................................................ 104
Keramova R. A., Yusifova Kh.Kh., Badalova M.G., Gurbanzadeh S.N. .............................................. 104
CLIMATE CHANGE IMPACTS ON WATER RESOURCES OF SHAKIZAGATALA REGION,
AZERBAIJAN......................................................................................................................................... 110
Gulnur Salmanova ................................................................................................................................. 110
CONTEMPORARY CHANGES IN HIGH MOUNTAIN LANDSCAPES IN SOUTHERN SLOPES
OF GREAT CAUCASUS, AZERBAIJAN ........................................................................................... 111
Sevinj Burzuyeva .................................................................................................................................. 111
LAND DEGRADATION AND DESERTIFICATION: AN INTERACTION
OF LAND, WATER AND WEATHER
Donald Gabriels
UNESCO Chair on Eremolgy, University of Ghent, Belgium
ABSTRACT Desertification is land degradation in drylands including the arid and semi-arid regions and the dry
subhumid areas.
Drylands are characterized by a ratio P/ PET with P the Precipation and PET the Potential
Evapotranspiration. A ratio between 0,15 and 0,65 means a deficit of water in the soil between 85 and 35%.
Weather, involving mainly temperature and rainfall, is part of the climate with the latter including also the
land and the land management systems, not to forget the oceans and ocean management.
The main topics to be discussed are the management of the land, the water stress as part of the soil water
balance and the weather conditions, all being factors in the climatological conditions of different regions in
the world. There is an interaction between the weather and the land and water. The interaction of land, water
and weather = climate.
Keywords: land degradation, desertification, water balance, drylands, Eremology, weather, climate
FLOATING SOLAR PHOTOVOLTAIC (FSPV) AND AN APPLICATION
IN ISTANBUL, TURKEY
Ahmet Duran SAHIN, Mustafa Kemal KAYMAK
Istanbul Technical University, Aeronautics and Astronautics Faculty, Meteorological Engineering Department,
Maslak 34469, İstanbul, Turkey
Abstract
The noticeable rise in the electricity demand, fast depletion of fossil fuels, along with environmental
concerns throughout the world has led to the requirement of commissioning Solar PV plants in large scale.
However, PV systems installation have the burden of intense land requirements which will always be a
premium commodity.
With the increasing importance of environmental issues, clean energy technology has gained importance.
Photovoltaic (PV) cells are becoming the most significant tool in the renewable energy technologies.
Because, the sun has an unlimited energy source and we have to gain the most favor of this resource.
Therefore, not only PV but also efficiency of solar energy systems should be increased. Another important
factor for considering PV electricity generation is environmental, in other words, atmospheric conditions
besides the matter of cell produced. When we consider the Istanbul perspective, we see Floating Solar
Photovoltaic (FSPV) Systems which are another form of solar energy applications. To conserve the valuable
land and water, installing FSPV systems on water bodies like oceans, lakes, lagoons, reservoir, irrigation
ponds, waste water treatment plants, wineries, fish farms, dams and canals can be an attractive option.
These systems have many benefits and these can be listed as follows
a. They reduce the evaporation of water,
b. They reduce algae formation in water,
c. Additional land use is eliminated,
d. In addition to cooling on water, they have higher efficiency due to their low shading factor.
One of the main objectives of these systems is to evaluate the land in a way that allows dual use. For this
purpose, environmental values and impacts are evaluated and investigated as a priority. Istanbul Water and
Sewerage Administration (ISKI) has started a research project for the implementation of FPVS since 2015.
The first proposal of the project was made by the R & D company of ITU Arı Teknokent, Meteo Energy
Ltd. Com. First of all, feasibility studies and were carried out and a system of 9 kWp was installed on the
water (Figure 1). In this system, a pontoon with applications in the world has been used but the upper carrier
system has been designed and implemented by our research group.
Figure 1. The first FSPV system installed on the water in Büyükçekmece dam, İstanbul, Turkey.
Based on the shortcomings seen in this application, it was concluded that a new pontoon design should be
made. Following the first application, a total of 210 kWp YGES application to the same region was decided
by İSKİ. Two different systems have been applied in this FSPV. One of the systems has an installed capacity
of 90 kWp (Figure 2). The buoyancy system has completely domestic design and production, and the first
application was made in Büyükçekmece FSPV. A scientific study and monitoring project covering the
efficiency and environmental impact of the 220 kWp FsPV system installed in Büyükçekmece was initiated
in order to continue these studies.
Figure 2. 90 kWp FSPV system that installed on the water İn Büyükçekmece, İstanbul.
PROSPECTS OF THE CONSUMPTION OF BIOFUELS IN AZERBAIJAN
Yusifova Mahluga1, Sultanova Nigar2
1Faculty of Ecology and Soil Science, Baku State University, Baku, Azerbaijan, AZ 1148, Z.Chalil. str.53.
2Baku Slavic University, Baku, Azerbaijan, S.Rustam street 33
Abstract
Azerbaijan has extensive reserves of renewable energy of all types: solar, wind, geothermal, hydropower
and biomass energy. In this article, based on statistical data, a brief analysis of the level of biofuel use in
the world market today is given, an analysis of the potential of the main sources of renewable energy in
Azerbaijan is given; studied the prospects for the development of the biofuel market in Azerbaijan and
identified the main problems in the development of bioenergy in Azerbaijan.
Keywords: biofuel, biogas, alternative energy sources, organic waste
INTRODUCTION
At the end of the twentieth century, mankind faced the urgent need to find new, alternative energy sources.
The reason for this was the impending fuel and energy crisis and the increase the level of environmental
pollution. In other words, it became necessary to find new sources of thermal energy that could replace oil
and gas. Agriculture and energy have always been closely interrelated, but the nature and strength of their
relationship changed over time. Agriculture has always been a source of energy, and energy is one of the
main factors of modern agricultural production. The recent emergence of crop-based liquid biofuels as fuel
for transport has restored the link between agricultural and energy markets. Thus, along with the
development of solar-wind, geothermal energy types also appeared no less perspective and more budget
direction- energy from biomass [2-4]. The issue of forming a sustainable industry for biofuel production
is becoming increasingly significant. The depletion of conventional energy sources, increasing demand and
cost of hydrocarbon energy resources cause concern among specialists all over the world. Since 2003, there
has been a growing trend throughout the world not only in the production of biofuels, but also in their
consumption [6-10]. This is facilitated by the rise in oil prices, as well as already been formed at the moment
the concept of energy security.
Liquid biofuels can significantly affect agricultural markets, but it still accounts for a relatively small part
of the total energy market. The total global demand for primary energy is about 11,400 million tonnes of
oil equivalent (Mtoe) in year; biomass, including agricultural and forestry products and organic waste and
residues, accounts for 10% of the total volume (Diagram 1) [11].
Diagram 1. World primary energy demand [11]
In some developing countries, almost 90% of total energy consumption comes from biomass. Solid biofuels,
for example, fuelwood, charcoal and dung, of course, are the largest segment of the bioenergy sector,
accounting for exactly 99% of all biofuels. For millennia, humankind has used biomass for heating and
cooking, so the developing countries of Africa and Asia are still largely dependent on such traditional uses
of biomass. Biomass and waste products currently account for 10% of the global primary energy demand.
For example, in the US, fuel ethanol is obtained from corn, which is mainly used instead of petrol [5]. In
Europe, biodiesel, which is obtained from various oils, is the most popular, and is subsequently used to
replace diesel fuel [1,11,12]. Attention has also increased to second-generation biofuels produced by
various methods of biomass pyrolysis [15,16]. The advantage is lower and sometimes even negative cost
of raw materials.
In order to establish global environmental and energy security, experts are taking initiatives to reduce the
dependence of the energy sector on fossil fuels [17,18]. As a result, one of the measures taken for the
formation of modern energy is the use of biofuels.
According to experts, the potential of renewable energy sources in Azerbaijan exceeds 8 GW, which is
more than the current installed capacity. However, the amount of electricity generated by gas-fired power
plants could be significantly reduced by unlocking the potential of renewable energy sources. In this case,
this would be a factor for a more sustainable and long-term growth of GDP, which is currently provided by
oil and gas exports. With respect the above, consideration of the problem of production and use of biofuels
in our republic has both scientific-theoretical and practical significance.
APPLICATION AND RESULTS
According to the BP report, renewable energy sources (RES) will develop progressively throughout the
period 2016 – 2035 years (growth will be 6.6% per year), thus, their market share will increase from 3%
today to 9% by 2035 [22,23]. In the next few decades, global demand for transport fuels is expected to
increase significantly - up to 55% by 2030 compared with 2004. This will accelerate the growth in demand
for biofuels, as they are expected to make a major contribution to meeting the energy needs of humanity
World Primary Energy Demand by source, 2010
2
10%
6%
21%
Oil
Coal
Gas
Biomass and Waste
25% Nuclear energy
Hydroenergy
[19]. In other words, there has been a rapid growth in the volume of liquid biofuel produced and its share
in the global demand for transport energy.
According to the results of the annual forecast of world energy by the oil and gas company BP-BP Energy
Outlook-2018, renewable sources of energy will be the fastest growing sector of the world energy market
by a large margin (Diagram 2). Prior to 2040, the share of renewable energy in global primary energy
consumption will increase by five times – up to 14% [22]
Diagram 2. Primary energy consumption of the fuel in 1970-2040 [22]
Azerbaijan has extensive reserves of renewable energy of all types: solar, wind, geothermal, hydropower
and biomass energy. A significant amount of agricultural activity in the country can provide agricultural
waste for biomass burning or gasification [13]. High annual average wind speeds provide the potential for
efficient use of wind energy, and in addition, the country has the potential to use solar energy because of
favorable natural conditions. The country is also rich in geothermal energy. The construction of small
hydropower plants (HPP) is the most perspective segment of the renewable energy sector (RES). Although
the country currently does not use all of the available types of RES, the development of renewable energy
is also one of the strategic priorities of the government [20].
Since 2004, the government of Azerbaijan has begun to pay more attention to the development of renewable
energy. This is also confirmed by the entry of Azerbaijan into the International Renewable Energy Agency
(IRENA) in June 2009, the creation of the State Agency for Alternative and Renewable Energy Sources
(SAARES) in July 2009, and the adoption of the State Program on the Use of Alternative and Renewable
Energy Sources for 2004 -2013 years [20].
Subsequently, the State Agency for Alternative and Renewable Energy Sources of the Republic of
Azerbaijan developed a National Strategy on the use of alternative and renewable energy sources for 2012-
2020. A budget of AZN 1 million was allocated for the project and a “Law on Renewable Energy Sources”
(2012) was prepared. The table presents data revealing the potential of renewable sources of our republic,
presented by the State Agency for Alternative and Renewable Energy Sources of Azerbaijan [20].
Table 1. Potential of renewable energy sources in Azerbaijan [20]
A source Realized potential, mW
small hydroelectric power plants >400
wind energy >800
solar energy >5000
bioenergy >1500
geothermal energy >800
Azerbaijan has set the following targets for the development of renewable energy by 2020:
• The share of renewable energy in electricity production - 20%;
• The share of RES in total energy consumption - 9.7%;
• Installed capacity of renewable energy - 2.000 MW.
In 2011, the share of renewable energy in the production of electricity was 10%, including 9.8% -
hydropower; the share of renewable energy in total energy consumption was only 2.3%. Achievement of
the goals for 2020 will require a strengthening of the regulatory - legal framework through the adoption and
enforcement of laws aimed at the promotion of renewable energy projects [21].
A budget of $ 60 million has been allocated for the development of renewable energy in Azerbaijan. The
first part of these funds are aimed at the development of hybrid plants based on renewable energy sources,
which ensure the simultaneous use of solar, wind and biomass energy, with a total installed capacity of 5.5
MW. The private sector is also involved in this activity [20].
The rapid development of industry, agriculture and social services in Azerbaijan opens up new opportunities
for the production of energy from biomass. The country has the following sources of biomass: combustible
industrial waste; forestry and waste from woodworking; agricultural products and organic waste; household
and municipal waste as well as waste from areas contaminated with oil and oil products. All these resources
can be used for energy production [14]. Azerbaijan produces 2 million tons of solid household and industrial
waste every year. Utilization of solid household waste and industrial waste would partially solve the
problem of heating public buildings in the capital and other large industrial cities [13].
Currently, more than 200 landfills for waste operate in Azerbaijan, the total area of which is 900 hectares.
Despite the fact that the biomass energy potential in the country is very high, only a small number of projects
using biomass are being implemented in Azerbaijan. According to estimates, the volume of methane
entering the atmosphere from landfills in large cities is:
• Baku - 30.4 thousand tons (42.8 million m3)
• Ganja - 5.1 thousand tons (7.2 million m3)
• Sumgait - 4.9 thousand tons (6.9 million m3)
• Mingachevir - 1.6 thousand tons (2.3 million m3)
• Nakhichevan - 1.2 thousand tons (l, 7 million m3)
• Shirvan - 1.2 thousand tons (1.7 million m3) [13].
On the basis of these landfills, small heat and power plants can be built to produce electricity.
As for the first biogas plant in Azerbaijan, it was installed in the Guba region. The volume of this installation
is 5 cubic meters, it allows producing 7-8 cubic meters of biological gas per day [20]. The experimental
Gobustan hybrid station was commissioned on September 13, 2011. The total capacity of the first hybrid
power plant is 5.5 MW. The energy is generated by three wind turbines with a capacity of 2.7 MW, solar
panels producing 1.8 MW, as well as a biogas power plant with a capacity of 1 MW. Today, the landfill is
fully supplied with electricity by the settlement of Gobustan [20].
Samukh Agroenergy Residential Complex consisting of a hybrid station that produces solar, wind,
geothermal energy and bioenergy through alternative and renewable energy sources, areas for the
collection, processing, sale of energy-supplied agricultural products, combines high technology and modern
management systems. It is also one of the components of the three-stage Energy Development Model
implemented in our country by the State Agency for Alternative and Renewable Energy Sources. The main
objective of the project is to meet the energy needs of the Samukh region entirely through alternative and
renewable energy sources, as well as to participate in meeting the energy and agricultural products needs
of our republic.
Until the end of 2010, the activities of 12 regional centers covering the entire territory of the country were
organized. The organizational stage for the creation of these centers and their activities is already at the
completion stage. In particular, regional centers have been established in the territory of Absheron, Guba,
Khachmaz, Gakh, Masalli, Kurdamir, Beylagan, Geranboy, Tovuz districts, the cities of Shirvan, and
Nakhchivan [14]. They will create favorable conditions for consumers in nearby areas.
To fulfill the tasks set, the State Agency works in the Surakhani, Pirallakh and Garadagh districts of Baku,
in the cities of Sumgait, Gobustan, Samukh, Absheron, Khizi, Siyazan, Sheki, Balakan, Oguz, Gadabay,
Aghjabedi, Neftchala, Jalilabad, and Nakhchivan regions. Projects are continuing to create new heat and
energy capacities at the expense of the State Agency for Alternative and Renewable Energy Sources, as
well as to obtain new energy products from organic substances and wastes [20].
Finally, two main barriers can be distinguished in the development of renewable energy in Azerbaijan:
• Insufficient incentives and inadequate current tariff calculation methods (tariffs for renewable energy are
too low);
• Insufficient regulatory framework and lack of network connectivity rules.
CONCLUSION
Based on the analysis of statistical data, it is determined that our country has a high biomass energy potential
for the production of biofuels. A significant amount of agricultural activity in the country can provide
agricultural waste for biomass burning or gasification. There are a number of factors hindering the growth
of the market, the main of which is the relative availability of fossil fuels for our country. It can be concluded
that the rate of introduction of biofuels in Azerbaijan will depend on government initiatives.
REFERENCES
1. "Biofuels - Second Generation Biofuels". biofuel.org.uk. Retrieved 2018-01-18.
2. "Biofuels Make a Comeback Despite Tough Economy". Worldwatch Institute. 2011-08-31. Retrieved
2011-08-31.
3. Biofuels Magazine (2011-04-11). "Energy Farming Methods Mature, Improve". Biofuels Magazine.
Archived from the original on 2013-07-27. Retrieved 2012-03-08.
4. Biogas Opportunities Roadmap / USDA, 2014
5. Biogas Potential in the United States / NREL, 2014
6. Biomass energy: the scale of the potential resource, Christopher B. Field, J. Elliott Campbell, David
B. Lobell // Trends in Ecology and Evolution. ‒ Volume 23, Issue 2, 2008. ‒ P. 65–72.
7. Drax to convert to biomass within five years / Process Engineering, 2012 [Electronic resource]. ‒
Access Mode: http://processengineering.co.uk/article/2013288/drax-to-convert-to-b
8. Ethanol Production Using Corn, Switchgrass, and Wood; Biodiesel Production Using Soybean and
Sunflower, David Pimentel and Tad W Patzek // Natural Resources Research. ‒ Volume 14, Issue
1, 2005. ‒ Р.65–76.
9. Eder, B., Schulz, H. Biogas plants. Practical guide. - Zorg Biogas, 2011., p. 181.
10. Global biofuels production up 17 % in 2010 to hit all-time high of 105 billion liters, August 2011.
[Electronic resource]. ‒ Access Mode: http://www.greencarcongress.com/2011/08/wwi-
20110831.html
11. International Energy Agency [Electronic resource]. ‒ Access Mode: http://www.iea.org/
12. "IEA bioenergy". IEA bioenergy. Archived from the original on 26 May 2010. Retrieved 2010-07-14.
13. In-depth Review of Energy Efficiency policy of Azerbaijan. Energy Charter Secretariat, Boulevard de
la Woluwe, 56. B-1200 Brussels, Belgium, 2013. ‒ 123 с. [Electronic resource]. ‒ Access Mode:
http://www.energycharter.org/fileadmin/ Documents Media/IDEER/IDEER-Azerbaijan_2013_ru.pdf
14. Nuralieva R.N. Economic-ecological problems of the development of the fuel-energy complex of
Azerbaijan. Monograph. Baku-Azerneshr-2010, 221 p.
15. National Renewable Energy Laboratory (2 March 2007). "Research Advantages: Cellulosic Ethanol"
(PDF). National Renewable Energy Laboratory. Archived from the original (PDF) on 25 January 2012.
Retrieved 2012-04-02.
16. “Power Systems of the Future” Edition of the National Renewable Energy Laboratory (National
Renewable Energy Laboratory), February 2015
17. The situation in the field of environmental management and agriculture. Biofuels: prospects, risks and
opportunities. Rome, 2008. - 159 p. [Electronic resource]. - Access Mode: http://www.fao.org/3/a-
i0100r.pdf
18. Wood Bioenergy: The Green Lie, 2010. ‒ 29 р. [Electronic resource]. ‒ Access Mode:
http://globalforestcoalition.org/wp-content/uploads/2010/10/briefing-paper-bioenergy_final_11.pdf
19. https://www.bp.com/content/dam/bp-country/ru_ru/Articles/NGV_6_2015_ВР_Final.pdf
20. http://www.area.gov.az
21. http://www.azerenerji.gov.az
22. http://renen.ru/bp-energy-outlook-2018-everything-will-grow-but-res-is-bigger-than-all/
23. https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-
energy/renewable-energy/biofuels-production.html
THE INFLUENCE OF CONTEMPORARY CLIMATE CHANGES TO
HYDROMETEOROLOGICAL SECURITY OF TRACECA
Rza Mahmudov
The Ministry of Ecology and Natural Resources for Azerbaijan Republic,
Hydrometeorological Scientific-Research Institute
Abstract Contemporary climate changes are the product of natural and anthropogenic factors. In the report along
with the known anthropogenic sides of climate changes there have been considered the role of natural
factors in the global form, and real regional impacts of climate changes in Azerbaijan. On researching of
the impact of natural factors to the climate changes there has been formed the model-scheme of climate
changes on the base of physical processes in the Sun, geophysical, astrophysical factors. On researching
the regional impacts of climate changes in the territory of Azerbaijan on the base of recommendations of
World Meteorological Organization (WMO) there have been analyzed climate changes in comparison with
the multiyear norm (1961 – 1990). Taking into account the situation of the territory of Azerbaijan between
-28 m and 4466 m heights on the base of multiyear observation data of more than 70 meteostations and 60
automatic meteostations there have been separately researched regional climate changes for both different
height intervals (lower than 0 m, 0 – 200, 201- 500, 501 – 1000, >1000 m) and 6 natural regions. Main
results:
• on the territory the increase of the average multiyear temperature consists of +0.920;
• most increase of the temperature consists of 1.30 C in 2010, 2012, 2014 years and +1.60 C in 2015 y. In
2011 there has been not observed the increase of the temperature;
• excepting of spring over the all of seasons there observes the increase of the temperature;
• most increase of the temperature is noted on the height more than > 1000 m (+1.20 C);
• the precipitation has been noted commonly, +70 mm, the maximal increase +124 mm in 2016 and the
minimal decrease in 2014 in comparison with the multiyear norm (462 mm);
• on the glacier mountain zones there continues territorial decrease.
The analysis of the multiyear trend of maximal (Qmax, m3/sec.), minimal (Qmin, m3/sec.), average annual
(Qannual, m3/sec.) water discharges in rivers shows over the republic on decreasing of the maximal,
minimal and annual water discharges in rivers with the high water and flood regime the minimal winter
flows are increased.
The research of the influence of contemporary climate changes to the hydrometeorological security of
TRCECA, which is one of the global projects nowadays, is very important.
The restoration of the historic silk route on a west-east axis from Europe across the Black Sea, through
Caucasus and Caspian Sea to Central Asia, requires the integrated development of the appropriate
infrastructure in countries involved. Hydrometeorological services for the safety of Haulage is an integral
part of this infrastructure. The TRACECA route goes through areas with a variety of landscapes, some of
which have complex and dangerous terrain and diverse meteorological and hydrological phenomena. These
may include mudflows, floods, avalanches, landslides, glazed frosts, thick for and dust storms. On the
maritime sections of the TRACECA route, phenomena such as gales, destructive waves and surges can
seriously threaten vessels and can lead to delays or temporary forbiddance of sailing. These phenomena can
have a disastrous effect on the transportation infrastructure, thus lead to considerable economic
losses.Researches on climate changes show that there are observed changes in the hydrometeorological
condition over the parts of Caspian Sea and Azerbaijan’s dry land territories, where passes TRACECA.
Keywords: Climate changes, water resources, surface waters, air temperature
DEVELOPING PROTECTION AND SE SCENARIOS SCENARIOS FOR
THE KHOJASAN LAKE, AZERBAIJAN
Rovshan Abbasov
Khazar University
Abstract
Khojasan lake, which is located in near to the largest city of Azerbaijan-Baku, is under extreme pressure
due to industrial and untreated municipal wastewater discharges. As a result of gradual land reclamation in
the basin, a large part of natural inflows were redirected to the main wastewater grid. Due to stormwater
mixed municipal and industrial wastewater discharges the environmental and ecological quality of the lake
has been drastically impaired, instigating potential hazards for human health, the ecosystem, and nuisance
to the close areas.
In 2017, the local water company started to develop a plan, according to which all the stormwater mixed
wastewater discharges to the lake will be stopped. This study confirms that this will make Khojasan a closed
lake and due to high evaporation from the surface will increase salinization in the lake.
It has been studied that stopping pollution and developing nature-based solutions for future management
may increase quality of ecosystem services and help local community and urban residents to have long-
term and sustained.
Results confirm that construction of water treatment sites with simultaneous construction of stormwater
system will improve ecological conditions in the lake and enable its sustained use.
Based on above aspects it is obvious that future water balance will be strongly affected by management
decisions and good governance regarding recreational use, fishing, and tourism. Respectively a functioning
institutional setup that can play a key role in future management is the main success reason for sustainable
management of Khojasan.
Keywords: pollution, nature-based solution, wastewater, industrial activity
SEQUENCE ANALYSIS OF DREB GENE FROM WHEAT GENOTYPE
'BARAKATLİ 95'
G. R. Abdullayeva, S. M. Rustamova, I. M. Huseynova
Institute of Molecular Biology & Biotechnologies, Azerbaijan National Academy of Sciences
Abstract
Drought tolerance is a complex trait controlled by many genes, including those encoding functional proteins
(e.g. late embryogenesis abundant (LEA) proteins, osmotin, molecular chaperones, and mRNA binding
proteins) or whose products are the transcription factors (TFs) such as basic leucine zipper (bZIP),
myelocytomatosis oncogene (MYC) and dehydration-responsive element-binding factor (DREB). The TFs
interact with specific cis-acting elements in the promoter regions of various stress-related genes to up-
regulate the expression of many downstream genes, thus imparting stress tolerance to environmental stress.
DREB is one of the largest families of TFs that plays a significant role in signaling network which
modulates many plant processes, such as abiotic stress tolerance. The main goal of the study was isolation
of DREB gene from the local durum wheat variety Barakatli 95, which is distinguished by high-
productivity, quality and tolerance to extreme factors and molecular characterization of this gene. DNA
was extracted using the modified CTAB method. To isolate DREB gene, two pairs of gene-specific primers
were used. PCR was performed in the "Applied Biosystems 2720 Thermal Cycler". The amplified products
were separated by electrophoresis in a 1.5% agarose gel with the addition of ethidium bromide and
documented using "Gel Documentation System UVITEK" and visualized with UV light. Dimensions of
amplified fragments were determined with respect to 1kb DNA marker. The PCR amplicons from agarose
gel were purified using ISOLATE II PCR & Gel Kit (BIOLINE) and sequenced using an ABI 3130xl DNA
analyzer (Applied Biosystems, USA).
DREB2 gene belonging to the superfamily of AP2/ERF plant transcription factors was amplified with the
gene-specific primer pair and electrophoretic analysis revealed two fragments of 300bp and 500 bp.
Amplicons were cut from agarose gel, purified with ISOLATE II PCR & Gel Kit and the nucleotide
sequence was read. According to the results of the BLASTn analysis the nucleotide sequence of the 500bp
fragment is 95% identical to Dreb2 gene of 2 Indian bread wheat varieties (PBW-175, HD-2932) placed in
GenBank and 94% identical to other 20 wheat genotypes. In the amino acid sequence corresponding to this
fragment, AP2 domain (valine in 14th (V14) and glutamine in 19th position (E19)) specific for proteins of
the DREB transcription signal and a nuclear localization signal (NLS) area were detected. Analysis using
the Softberry program suggests the existence of one gene consisting of two exons in the 500 bp fragment.
BLAST search of the respective amino acid sequences of the obtained exon areas revealed 70% identity
with T. dicoccoides and T. urartu, and ≤ 71% identity with 13 varieties of T. aestivum. BLASTn analysis
of the nucleotide sequence of 300bp fragment revealed 99% identity with certain areas of 3B chromosome
of the Chinese Spring variety of bread wheat.
Keywords: Wheat, transcription factors, DREB gene, FGENESH, BLAST
NaSCN(C2H
5)2
OS S
(C2H
5)2NCS - CH
2COCH
2
O OH
CH2OHClCH
2COCH
2 - CH CH
OH
CH2OH+
NaSCN(C2H
5)2(ClCH
2COCH
2)2 - CHOH + (C
2H
5)2NCS - CH
2COCH
2
CH - OH
OO S S
22
STUDY OF SULFUR, NITROGEN-ORGANIC COMPOUNDS OBTAINED
FROM ECOLOGICALLY PURE GLYCEROL DERIVATIVES
V. Farzaliyev, G. Ismailova, B. Musayeva, N. Novotorjina
Institute of Chemistry of Additives of NASA
Abstract The interaction of glycerol esters with sodium diethyldithitocarbamite synthesized derivatives of
diethyldtitocarbamic acid, which turned out to be effective anti-seize and anti-wear additives for lubricating
oils that do not cause ecological pollution of the earth.
Key words: glycerol, diethyldithitocarbamite, additive, ecology
INTRODUCTION The production of biodiesel from renewable energy sources of plants, algae in recent years has made
glycerin a cheap chemical raw material for producing various compounds used in the national economy.
Glycerin is used in the pharmaceutical, cosmetic food industry, in production of explosives, additives to
fuels, etc.
Most glycerol derivatives are easily destroyed by micro-organisms, turning into non-toxic or low-toxic
products, which play an important role in environmental protection.
One of the topical problems in petrochemistry is synthesis of organic compounds containing active elements
such as sulfur, nitrogen, phosphorus, boron, chlorine.
They are widely used as medications, herbicides, fungicides, flotation reagents, additives for lubricating
oils and so on .
Interest was in the synthesis of new effective sulfur-nitrogen containing compounds on the basis of glycerol
derivatives and their study as an anti-seize additive for lubricating oils.
By the interaction of glycerol with monochloroacetic acid glycerol esters - glycerides were obtained.There
were synthesized 2,3dihydroxy- propyl ether of chloroacetic acid(I) in the of ratio1:1 and 2-hydroxy-1,3
di(chloroacetoxy) propane (II) in the of ratio1:2 according to the following scheme:
I
II
By the interaction of both glycerol derivatives (I,II) with sodium diethyl dit hiocarbonate 2,3-dihydroxy
propyl ether of dithiocarbamine acid(III) and 2-hydroxy-1,3- di(thiocarbomoilthioacetoxy)propane (IV)
were obtained according to the following scheme:
III
IV
ClCH2COOH ClCH
2COCH
2CH - CH
2OH
OH
ClCH2COOH ClCH
2COCH
2CH - CH
2OCCH
2Cl
OH O
OH O
HOCH2CH - CH
2OH
OOH
HOCH2CH - CH
2OH
+
2+
The synthesized compounds were studied as an anti-wear and anti-seize additives for lubricating oils. 2-
Hydroxy-1,3- di(thiocarbomoilthioacetoxy)propane (IV) was showed the most high effective additive.
The effectiveness of sulfur-nitrogen containing compounds action that improves lubricating properties of
oils is determined by their structure.
The effectiveness of the above mentioned compound can be explained by the combination of carbonyl and
dithiocarbamine groups –SC. as the result of synergism.
DATA AND METHODS
The goal of this work was to study the synthesized sulfur-nitrogen containing organic compounds using
chemical raw materials that does not cause land environmental problems and negative air/environment
interaction. Synthesized S-N- containing compounds are used in car gearboxes, while the cars are driven,
exhaust gases are emitted, thus for their neutralization ecologically clean substances are needed.
Their anti-seize and anti-wear properties were studied on friction machine according to ГОСТ 9490-75.
Score indicators bully index И3, critical load Рk(N), welding load Pc (N) and wear spot diameter Du (mm).
APPLICATION AND RESULTS
The synthesized nitrogen- and sulfur-containing compounds were investigated as additives to oils. The
specified compound turned out to be quite effective anti-seize and anti-wear additives to lubricating oils
that do not cause environmental pollution of the earth.
CONCLUSIONS AND RECOMMENDATIONS
Syntesized surfur-nitrogen containing organic compounds by their effective anti-seize and anti-wear
properties are recommended in creating TM-3 type transmission oils.
REFERENCES
А.М.Кулиев, Г.Р.Гасанзаде, Б.И.Мусаева, Р.Г.Алиева Авт.свид.СССР №548982,5.10 1976
А.М.Кулиев «Химия и технология присадок к маслам и топливам» М.Изд-во «Химия» 1985 с.127-
128
А.С.Лядов, С.Н.Хаджиев Биоглицерин-альтернативное сырье для основного органического синтеза
ЖПХ, 2017,Т. 90.Вып.11,стр.1417
Б.Х,Кимсанов, И.Н.Бахиров, А.М. Закиров Перспективы развития химии глицерина. Материалы
республиканской конференции «Новейшие достижения в области химии» Душанбе,2001,стр.40.
Б.Х,Кимсанов, Д.Л.Рахманкулов, С.А.Расулов, Ю.К.Дмитриев Способы получения глицерина и
области его применения // Башкирский химический журнал, 2000-Т7,№6, с.39
TRANSBOUNDARY POLLUTION IN THE KURA RIVER BASIN
Rashail Ismayilov
Azerbaijan
Abstract
Overall, the concentrations of BOD5 and NH4+ indicate a limited impact of human activities on water
quality in the Kura river basin, as most measured concentrations did not exceed the established MAC limits.
Exemptions were observed for certain months during the low flow seasons. The above analysis also shows
the occurrence of certain transboundary issues in water quality, caused by the releases of organic pollutants
into the river from municipal and agricultural sources. Although the impact on chemical river water quality
appears to be still limited, there is an urgent need for the riparian countries to develop along-term integrated
regional environmental compliance action plan aiming at reducing the pollution loads from different
sources, with special focus on municipal waste water from main cities and villages located in the river
basin. Meanwhile there is a lack of information on the impact of pollution loads on the biological river
water quality.
Keywords: BOD, DO, PH, Transboundary Water management, water pollution
DYNAMICS OF SOME CARBON AND NITROGEN METABOLISM
ENZYMES DURING THE DAY IN VARIOUS WHEAT GENOTYPES
UNDER DROUGHT
Ulduza Gurbanova, Shahniyar Bayramov, Irada Huseynova
Institute of Molecular Biology and Biotechnologies, Azerbaijan
Abstract
PEPC plays a pivotal role in various metabolic processes in C3 plants such as providing intermediates for
Krebs cycle, maintaining intracellular pH and osmotic pressure, regulation of the movement of stomatal
guard cells, refixation of CO2 formed by respiration, forming carbon skeleton for the lipid synthesis during
the grain development period and nitrogen assimilation. Aspartate aminotransferase is essential in the
primary nitrogen assimilation, transportation of the reducing equivalents, exchange of carbon and nitrogen
resources among cellular subcompartments. Durum (Barakatli 95 and Garagylchyg 2) and bread wheat
genotypes (Gobustan and Tale 38) cultivated in the experimental field of the Research Institute of Crop
Husbandry were used as the study materials. The high activities of PEPC and NAD-MDH during the
morning hours and a positive correlation existing between them during the day suggest that functioning
mutually, these enzymes participate in the biosynthesis of malic acid.
Keywords: PEP-carboxylase, aspartate aminotransferase, NAD-malate dehydrogenase
OCCURRENCE AND DIVERSITY OF SINGLE AND DOUBLE VIRAL
INFECTIONS OF SOLANACEOUS CROPS IN AZERBAIJAN
N. F. Sultanova
Institute of Molecular Biology & Biotechnologies, Azerbaijan National Academy of Sciences, Azerbaijan
Abstract
Agriculture in Azerbaijan is one of the important sectors of the economy. Among the widely cultivated 32
species of vegetables, solanaceous crops such as tomato, pepper and eggplant are leading vegetables in our
country. Viruses always cause major losses in the quantity and quality of crops worldwide and they exhibit
one of the most significant limiting factors for growers. In order to identify viruses infecting these crops
and evaluate the prevalence of viral infections, surveys were conducted during June-July months of 2017-
2018 growing seasons in important vegetable growing areas of Azerbaijan including Jalilabad, Masalli and
Lankaran regions and Absheron peninsula. Total six fields were surveyed and 86 samples were collected
from symptomatic plants as well as from non-symptomatic and healthy plants. Also non-cultivated (weed
species) plants, showing virus like symptoms also were collected around fields surveyed. Collected samples
included fresh leaves and fruits of vegetables with various symptoms. Initially, rapid one-step assay
AgriStrip, which based on lateral flow immunochromatography and manufactured by Bioreba (Reinach,
Switzerland), was performed to confirm the presence of TMV, ToMV, CMV, TSWV in samples depending
on suspicious virus symptoms. Midrib and leaf petioles from symptomless plants as well as from samples
with virus-like symptoms were also tested for TMV, PMMoV, ToMV, CMV, TSWV, TRSV, AMV, BCTV
by TAS-ELSA and DAS-ELISA using the ELISA kits developed by Bioreba AG (Reinach, Switzerland)
and Agdia (USA) according to the manufacturer’s instructions. Six viruses, Alfalfa mosaic virus (AMV),
Pepper mild mottle virus (PMMoV), Cucumber mosaic virus (CMV), Tomato mosaic virus (ToMV),
Tobacco mosaic virus (TMV) and Tomato spotted wilt virus (TSWV) were detected as a single infection
in the tomato and pepper samples. Of 86 plants tested, 16 were doubly infected, and TMV+ PMMoV (9 out
of 16), ToMV +CMV (5 out of 16) were the most common double infection. Using serological methods
(rapid one-step assay AgriStrip, DAS/TAS-ELISA) 72 % samples out of total 86 tested samples, were found
positive against antisera of these viruses. To confirm the presence of single and double viral infections of
tomato and paper crops, leaf samples with a positive reaction in the serological assays were tested by PCR,
RT-PCR methods using universal primers and primer pairs designed for the specific detection of the virus.
Obtained results confirmed the presence of CMV, TMV, ToMV, TSWV and AMV in these samples. This
study reports the natural prevalence of solanaceous viruses in Azerbaijan, which can provide important
basic information useful for virus control strategies for vegetable growing in our country. Conducting
control over the vectors of insects, that spread viral diseases, should be of fundamental importance for the
prevention of these viruses.
Keywords: grapevine; grapevine leafroll disease; grapevine leafroll-associated virus 3; rapid one-step assay
AgriStrip; DAS-ELISA; RT-PCR
ASSESSMENT OF ENVIRONMENTAL POLLUTION ALONG THE
COASTLINES OF THE CASPIAN SEA
Albert Tagiev, Imran Amirov, Alibaba Niftaliyev
Sumgait State University, Azerbaijan
Abstract At present, the ecological situation of the Caspian Sea is extremely worsened. There are several dead zones
along the coastlines, which is highly polluted with a broad range of chemical contaminants.
The sources of contamination are quite diverse and may be grouped as follows: contaminants entered
through rivers flowing into the sea; industrial wastewaters from the chemical plants located along the sea,
offshore industrial activities, which include mainly oil and gas extraction, contamination from water sources
in coastal zones as a result of elevated levels in the Caspian Sea. In order to protect the Caspian Sea and
provide its future sustainable use, it is necessary to develop a special program that contain transboundary
approach to the management.
Keywords: Caspian Sea land degradation, coastal pollution, industrial wastewater
IDENTIFICATION OF VERTICILLIUM DAHLIAE RESISTANT
COTTON GENOTYPES USING CHROMOSOME SUBSTITUTION LINES
Ruhangiz Mammadova, Afag Musayeva, Leyla Nagiyeva, Efsane Abdullayeva
Baku State University, Azerbaijan
Abstract
The environment plays an important role in the evolutionary process and changes in environmental
conditions are predicted to alter diversity within populations. Climate is one of the most important drivers
of local adaptation in plant species, climate change has the potential to alter the genetic diversity of plant
populations with consequences for community dynamics and ecosystem processes. Genetic variation
among plant populations often occurs along different climatic gradients, such as changes in temperature
and precipitation.
Cotton (Gossypium sp.) is an extremely important source of both fiber and seed oil. The most economically
important disease of cotton is Verticillium wilt (VW) caused by a soil-borne fungus, Verticillium dahliae,
which has a wide host range encompassing 400 plant species. The pathogen is currently present in most
parts of the risk assessment area, where yield reductions up to 50 % or more have been reported on some
high value crops, including cotton (European Food Safety Authority.
Currently most commercial cotton cultivars are susceptible to Verticillium dahliae. Widespread infections
are especially dangerous because dead plant parts maintain a high level of fungus in the soil which cannot
be eliminated by fungicide treatment. As the diseased plant senesces, the fungus ramifies throughout
cortical tissue then produces microsclerotia, which are released into the soil. Once established in a field or
landscape, spread of the pathogen occurs primarily by soil cultivation and movement of soil by wind or
water. Inoculum densities and disease severity tend to increase from year to year when susceptible crops
are planted.
Creation of genetically resistant new cotton cultivars and donors of resistance for breeding programs is very
important to prevent cotton yield loss as well as wide dissemination of Vertcillium wilt pathogen by
planting resistant commertial cultivars of cotton. For this purpose 17 Cromosome substitution (CS), their
donor and recurrent parents, 5 nematode resistant mutant cotton lines were screened for Vertcillium wilt
resistance using conidia suspension inoculation method. Plants were inoculated after first true leafe stage.
Post inoculation phenotyping included physiological and biochemical markers as well as ranking based on
wilting symptoms.
Lines CS01, CS02, CS22Lo and mutant line REN with ranking score 0,6 were marked out as most resistant
genotypes to VD11 pathotype. We observed compliance of results for PYD V8 post inoculation ranking
results. CS01 with ranking score 0,4 and CS22Lo with ranking score 0,8 respectively were selected as most
resistant lines to both pathotypes. Each of the 18 CSB lines has a different chromosome or chromosome
arm from G. barbadense. Thus, we expect that the 18 CSB lines must be different in their resistance to
Verticillium wilt. This difference should identify to us which chromosomes are involved. We will then
sequence the individual CSB line and compare with TM-1 sequences. Differences will be related to the
particular chromosome in the CSB line. This will narrow the search to individual chromosome differences.
This is a way of searching for wilt resistance genes and markers one chromosome at a time by only
searching on those chromosomes that show resistance genes.
Keywords: genetic diversity, cotton, Verticillium wilt, chromosome substitution lines
AIR POLLUTION IN ROAD TRANSPORT OF AZERBAIJAN
Rovshan Karimov
Khazar University, Azerbaijan
Abstract
Motor transport is the leading subsector of transport of Azerbaijan with 83% of overall passenger
transportations in the country’s territory, and relevant environmental impact here is highest as well.
Transport sector is a major contributor of GHG in the country. Most of pollutant ingredients are emitted
from vehicles operating in big industrial cities of Azerbaijan.
Since volume of harmful emissions considerably depends on the number and structure of country’s
automobile park, vehicles in Azerbaijan are imported with strictly taking into account duration of their use
after the year of manufacturing. The application of Euro-4 standard in Azerbaijan made necessary the
prohibition of use of old vehicles and transition to ecologically safe cars. By 2017, the half of of all cars
used in Azerbaijan has been manufactured in Russia, and does not meet up-to-date requirements. However,
share of them declines. Meanwhile, the number of cars used more than 10 years has been increased from
50% in 2010 to 68% in 2017. Since the number of cars increases over years in the country, the amount of
ingredients emitted from them tends to grow. Total emission made up 981.9 thousand ton in 2016, or 32%
higher than in 2010.
This study deals with the analysis of data on emissions in Azerbaijan’s road transport and achieving
mitigation toward this emission. In road transport, the implementation of basic principles of sustainable
development is necessary, and decisions on regulating development of road transport sector must consider
economic efficiency, environmental concerns and security aspects, since all the three priorities are
important. Governmental agencies and also citizens are responsible for the decisions taken with respect to
road transport from ecological view, while the transition to environmentally safer vehicles must be
regulated efficiently.
Keywords: road transport, emission, air pollution
DIURNAL TEMPERATURE-RELATED DYNAMICS OF GLUTATHIONE
REDUCTASE ACTIVITY IN WHEAT GENOTYPES UNDER DROUGHT
Lale Aydinli1, Durna Aliyeva2
1Institute of Molecular Biology and Biotechnologies, Laboratory of Bioadaptation,
Azerbaijan National Academy of Sciences 2Institute of Molecular Biology and Biotechnologies, Laboratory of cell membrane systems,
Azerbaijan National Academy of Sciences
Abstract
The strategically important wheat plant is the most cultivated among cereals. Drought is one of the main
factors adversely affecting its productivity and grain quality. In plant cells exposed to stressors, the
antioxidant defense system implements the detoxification of reactive oxygen species (ROS). Components
of the ascorbate-glutathione cycle play an important role in this system. Diurnal dynamics of the
temperature-related glutathione reductase activity (GR), which is one of the main components of the
antioxidant defense system, was studied in durum (Barakatli 95, Garagylchyg 2) and bread (Gobustan, Tale
38) wheat genotypes with contrasting tolerance, exposed to sustained soil drought. Glutathione reductase
is highly sensitive to glutathione. This enzyme, performs detoxification of a strong oxidant - hydrogen
peroxide by reducing the oxidized form of glutathione in the presence of NADPH. Leaf samples were taken
at the end of the wax ripening phase in every 3 hours (800, 1100, 1400, 1700), frozen in liquid N2, and kept
at -800C. According to the results of the experiments, GR activity increased in stressed, tolerant (Barakatli
95, Gobustan) and decreased in stressed sensitive varieties (Garagylchyg 2, Tale 38) compared with watered
variants. In the samples taken at 1100, the enzyme activity increased in the all genotypes compared with
the control. However, in the Gobustan genotype the activity of the enzyme remained almost constant. At
the most intense temperatures (1400) GR activity decreased almost 2 times both in durum and bread wheat
varieties compared with the control. At 1700 GR activity increased in durum wheat genotypes and remained
at the low level in the bread wheat genotypes. Thus, durum wheat genotypes have a stronger defense system
against unfavorable environmental conditions compared with bread wheat genotypes.
Keywords: Triticum aestivum L, Triticum durum Desf., drought, ascorbate glutathione cycle, glutathione
reductase
CONCEPTUAL APPROACH OF THE REGIONAL PROBLEM OF THE
GLOBAL CLIMATE CHANGE
Rustam Rustamov
Research and Development Center of Khazar University, Azerbaijan
Abstract
Climate of the Earth system is the consequence of a complex interplay of external solar forcing andinternal
interactions among:
• atmosphere,
• the oceans,
• the land surface,
• biosphere and
• cryosphere.
Human activities as a potential factor influencing the change in the global system by altering the chemical
composition of the atmospheric concentrations of powerful greenhouse gases mainly such as CO2 and CH4
How and what needed to be undertaken for minimization of such impact?
• Space based technology to a point as able to accurately observe and sense globally the entire Earth system
and to understand Earth system processes Earth’s climate. From this point view it can be offered;
• document and understand an interrelations between Sun-Earth as an external forcing of the Earth’s climate
and also better understand the Earth’s intricately linked internal processes such as the global water, energy
and carbon cycles;
• Together with advances in computing and information systems technology, modern data assimilation
techniques, diagnostic and prediction models - provide a powerful combination of tools for understanding
of the Earth system and applying the knowledge and tools to the management of natural resources and the
mitigation of natural hazards; and
• Cooperation can be likely developed within the framework of existed programmers:
There is no doubt that the scale of climate change contribution is a global which makes necessary
engagement of countries and international institutions:
• Global Monitoring for Environment and Security (GMES) - joint initiative of the European Commission
(EC) and the European Space Agency (ESA), designed to establish a European capacity for the provision
and use of operational information for Global Monitoring of Environment and Security (GMES);
• The United Nations Platform for Space-based Information for Disaster Management and Emergency
Response – UN SPIDER capacity - a one the more opportunity for the enhancement of the foregoing
mentioned issue for the success of the international cooperative relationship establishment; and
• For instance, as per identified Global Monitoring for Environment and Security (GMES) is a joint
initiative of the European Commission (EC).
Keywords: atmosphere, the oceans, the land surface, biosphere and cryosphere
MICROSEISMIC ZONES OF THE CASPIAN SEA, FIRST IDENTIFIED
ON THE BASIS OF THE ABNORMALITIES IN THE YEAR-ROUND
MONITORING OF THE UNDERGROUND WATER’S REGIME IN
AZERBAIJAN (1986-2014)
Keramova Ramida Aga-Dadash
Azerbaijan National Academy of Sciences
Abstract
In the this abstract presents the results of a comprehensive interpretation of seismological data for the
Caspian sea and year-round seismogeodynamic (SFGD) monitoring of the fluids in Azerbaijan (1986-
2014). They are represented of the underground water, as well as - sea water of the Caspian coast (2001-
2014). The purpose of the researches is to identify “dangerous” focal zones of earthquakes (ml≥5.0) in the
Caspian sea for daily, remote, operational, seismic forecast.
In our researches (1998-2004), it was first established that SFGD anomalies appear only at the final stage
(1÷16 days) of earthquake preparation, and is specific for concrete seismic foci. Also, for the first time were
developed the SFGD “portraits” of the seismic foci.
From the published works it is known that in the middle and southern parts of the Caspian sea there are
three large seismogenic zones, and the Northern part is aseismic. On the basis SFGD “portraits” of the
hypocenters of the earthquakes in the Caspian sea we for the first time identified six microseismic zones.
As the results, in the Science of the Earth created a new direction–“Scan microseismic zones on the basis
of the seismogeodynamic’s (SFGD) fields within previously known seismogenic zones.”
Keywords: seismogeodynamic (SFGD) monitoring, microseismic zone
CATALASE ACTIVITY DURING FLAG LEAF SENESCENCE OF
WHEAT PLANTS UNDER WATER DEFICIT
T. Y. Isgandarova, S. M. Rustamova
Institute of Molecular Biology & Biotechnologies, Azerbaijan National Academy of Sciences
Abstract
Nowadays global warming is the crucial problem all over the world that cause deleterious consequences
such as drought. Drought is a stress that impacts negatively on plants and dramatically reduces its
productivity. Wheat is one of the main cereal crops in the world that used as the key sources of food and
contain all essential proteins. For wheat plants the uppermost three leaves, mainly the flag leaf have been
observed as the key sources of the photoassimilates accumulated in the grain. The flag leaf photosynthesis
in wheat provides about 30–50% of the assimilates for grain filling. The onset and rate of senescence are
important factors for defining yield productivity. Senescence is a genetically regulated process that includes
destroying cellular structure and penetration of the products of this degradation to other plant parts.
Senescence is related with an increased production of reactive oxygen species (ROS) such as hydrogen
peroxide (H2O2), superoxide and its more toxic derivative hydroxyl radical. One of the antioxidant
enzymes playing the main role in the plant protection system against oxidative stress is catalase (CAT).
The aim of this study was to determine dynamics of CAT activity in wheat cultivars during leaf senescence
under normal and drought conditions. Durum wheat genotype Tartar was used as a research object. The
enzyme extract was prepared by homogenizing leaf material (1 g fr wt) with a pestle in an ice-cold mortar
with 0.05 M Na2HPO4/NaH2PO4 buffer (pH 7.0). The activity of CAT was determined as a decrease in
absorbance at 240 nm for 1 min following the decomposition of H2O2. In 7-day-old flag leaves CAT
activity was 310±21mmol/mg.min under normal water supply. On the 14th day of the leaf development the
enzyme activity decreased approximately 2 times and increased on the 21th day reaching
269±13mmol/mg.min. To the end of ontogenesis CAT expressed maximum activity in 35-day-old flag
leaves. CAT activity of 7-day-old flag leaves of drought-exposed plants decreased 2 times compared with
the control variant (113±5mmol/mg.min). The enzyme activity increased slightly in 14-day-old flag leaves
of drought-exposed plants, and increased approximately 2 times in 21 day-old seedlings reaching the
maximum value (243±12 mmol/mg.min). CAT activity was found to decrease during the flag leaf
senescence. Contrary to the control variant, in stressed-variants the activity was minimum at the end of
ontogenesis (102±5 mmol/mg.min). The obtained results are being discussed.
Keywords: wheat, flag leaf senescence, CAT, drought
AWARENESS OF UNIVERSITY STUDENTS ON RENEWABLE ENERGY
Zelha Altinkaya
Yalova University, Turkey
Abstract
Many of the states in the World follow the renewable energy policies for the purpose of promoting the
security of energy supply, promoting technologial development, innovation, export providing opportunities
for raising employment, social cohesion and opportunities for the individuals and institution. Turkey also
follows similar policies and adopted series of regulations to support renewable energy sources to use in
green industrial production and for economic stability. In addition to technological need, Turkish economy
suffers large current account deficits due to import of fossil energy sources. Reducing current account
deficit is one of the primary target to keep economy stable. Turkey has green industrial production and
economic purposes. As a non-oil producing country, energy sources had been supplied by woods, in wood
rich land of Anatolia, in Turkey, in early years of Republic of Turkey. For a long time, coal and hydrojen
became the main source of energy. However, growing population growing economy needed more energy
than Turkey had. In adddition to oil sources, electricity have been imported from the mainly neighbour
countries where rich of oil or natural gas. However, in Turkey, 80 per cent of the energy sources have been
imported currently where Turkey suffers from the current account deficit in the economy for a long time.
Therefore, it was considered that knowledge and awareness of students at faculty of economics and
adminsitrative sciences on energy sources and security of renewable energy supply in Turkey are important
In this paper, the University students have been asked whether they are aware the use of Renewable energy
sources and they follow energy policies offered by the state. The first hypothesis is on whether students are
aware of states policies on renewable energy sources. Questionnaires have been given to 250 students where
they were the first year students at the Faculty of Economics and Administrative Sciences. Results show
that students are aware of the policies. The second hypothesis argue awareness and knowledge of
participants differ according to the gender differences. Both hypothesis have been accepted with 95 %
confidence level.
Keywords: Renewable energy, electricity production, current account, university students awareness
ENVIRONMENTAL PROBLEMS OF CLEANING WATER AND GROUND
SURFACE FROM PETROLEUM AND PETROLEUM PRODUCTS
Jevahir Rajabli, Gulgez Nagiyeva
Oil and Gas Institute of Azerbaijan National Academy of Sciences
[email protected], [email protected]
Abstract
Over the years there has been increased concerns over the environmental effects of the petroleum industry.
The environmental impacts of petroleum are mainly negative. This is due to the toxicity of petroleum which
contributes to air pollution, acid rain, and various illnesses in humans. Petroleum also fuels climate change,
due to the increased greenhouse gas emissions in its extraction, refinement, transport and consumption
phases. An oil spill is the release of a liquid petroleum hydrocarbon into the environment, especially marine
areas, due to human activity, and is a form of pollution. We can reduce the harmful effects of pollution with
different methods.
There are 4 main methods ofcleaning water and ground surfaces from petroleum and petroleum products:1.
Containment booms; 2. Chemical method; 3. The use of special sorbents; 4. Biological method
(microorganism - the use of destructors).
Oil is collected from the surface of the water depending on the thickness of the spill layer using threshold
and pump systems, mechanized skimmers and various sorbents. The main methods of localization and
liquidation of oil spills at the water surface divided into 4 groups:
1) Localization of containment booms that allow moving oil spills in the right direction and changing the
shape and area for ease of collection, as well as collecting oil with various adhesives, pumps, and other
technical means;
2) Chemical methods involving the dissolution of surface-active substances in water or oil, as a result of
which the ratio of the surface energies of the interphase boundaries in the oil-water system changes;
3) Biological methods (use of microorganisms - destructors);
4) Sorbent usage.
Mechanical methods of localization and liquidation are used to guard emergency vessels, to enter the port
of tankers, where it is necessary to prevent the spreading of oil and send in the required direction. As a
means of localizing oil spills on water, containment booms such as operational (film and panel) and
stationary have been used. Oil can be collected from the surface of the water by oil collectors or oil
collecting devices operating from standard tanker pumps and barges.
For fencing emergency ships, entering the port or harbor of tankers during cargo operations, to protect the
coast, where it is necessary to prevent oil from spreading or to direct it in the right direction, containment
booms are widely used - floating structures of about 100 constructive types.
Water jets from the fireboats can also be used to localize the oil spill, where the poured oil mass is brought
to the center for an appropriate collection.
Mechanical method - includes various fixed, transient, floating systems, floating equipment and devices.
The collection of oil and oil products from the water surface is carried out only with the help of tankers and
pumps operating on the staffing table on barges, as well as oil-collecting vessels supplied with oil devices.
Physicochemical booms also work on a collection basis. They can reduce and direct the contaminated area
(sealing spills) in the right direction.
After the localization of oil spills on the surface of the water using stationary or floating fences in the
necessary and possible cases can be produced burning oil directly on the water.
The main criteria that determine the effectiveness of polymeric sorbents for cleaning water and ground
surface from petroleum and petroleum products:
- high sorption capacity for oil and oil products;
- flotation;
- hydrophobicity;
- the ability to multiple regeneration and manufacturability of the process of spraying and collecting
polymeric sorbents from the water surface;
- environmental safety of their utilization.
For dipping oil to the bottom, sorbents are used, which, together with absorbed oil barriers, sink to the
bottom, causing significant damage to benthic organisms. This cleaning method cannot be considered
effective and environmentally friendly. Adsorbents began to be used to remove oil pollution from the water
surface before other physicochemical agents, which, as a result of adsorption (absorption), absorb oil. The
sorption mechanism is described in great detail in the special literature. The main property of the sorbent
material is the sorption capacity - the amount of petroleum product absorbed by a sorbent unit. The process
of sorption of oil from the water surface by sorbents obtained on the basis of the polymer mixture PA: PU,
with a ratio of components of 20:80.
The process of sorption of oil from the water surface by sorbents obtained on the basis of the polymer
mixture PA:
PU, with a ratio of components of 20:80.
a)the beginning of the process of sorption; b) sorption - after 15 minutes; c) sorption - after 40 minutes. It
should be noted that the sorption capacity of polymeric sorbents is 10-15 kg / kg (1 kg of sorbent absorbs
10-15 kg of oil). Due to its very low density and buoyancy, sorbents may remain in the water for a long
time. These sorbents are hydrophobic, and therefore the sorption process is selective, resulting in the
collection of oil from the water surface is 98-99%. It has been established that after the regeneration carried
out using a centrifuge, sorbents can be reused (at least 10 times). In this way, due to its high-performance
properties, these sorbents are real products ready for wide practical use. The development and research of
foam polymer sorbents is carried out at the Institute of Polymeric Materials under the guidance of Professor
Gahramanov Najaf Tofigoglu. Under natural conditions, after an oil spill on the surface of the water, as
well as on the soil, microbiodegradation of oil spills occurs with the participation of accompanying bacteria.
Usually, this process is slowed down due to the monotony of their nutrient medium; certain additives are
needed in order to stimulate it, which have become developed various types of drugs.
The greatest efficiency in water cleaning is achieved by the simultaneous use of sorbents and
microorganisms, sorption-microbiological method: strains of oil-degradable bacteria are immobilized on
the sorbent. The sorbent acts as a role of microorganisms and has a highly developed surface. The use of
this method makes it possible to significantly increase the degree and rate of degradation of the pollutant.
The process is accelerated by adding selected nutrients containing nitrogen and phosphorus.
Of great importance in the process of removing various pollutants from water are filter-organisms, with
bivalve mollusks playing the leading role. The work carried out since the beginning of the 90s of the 20th
century on the Black Sea has shown that some mollusks, in particular mussels, eat oil products. For use as
a water cleaner, they are placed on special metal frames and placed in water with oil spills on the surface.
Keywords: oil, petroleum, petroleum products, pollution, sea level, water surface, ground surface, cleaning,
environment, polymeric sorbents.
THE ROLE OF THE KUR RIVER BASIN IN THE ECONOMY OF
AZERBAIJAN
Maksud Babaev1, Gunay Hasanova2
1Baku State University, Azerbaijan 2Ministry of Ecology and Natural Resources, Azerbaijan
Abstract
The Kur River Basin is also of great importance for the economy of the Republic of Azerbaijan in terms of
agriculture.81.6% of total sown area, 77.8% of planting area of cereal and leguminous crops, 97.6% of total
planting area of technical plants, 95.9% of cotton planting area in the Republic of Azerbaijan which is
available in 2017 fall to the Kura basin region. It is also important to note that more than 99.8% of total
cultivated areas of the Kura basin located in the arid climate zone fall into irrigation agriculture. Currently,
165.6 thousand tons or 55.6% of meat production and 1.33 million tons or 73.3% of milk production in the
Azerbaijan Republic are concentrated in the Kura basin.
Keywords: Kura River, İntegrated Water Management, agricultural production, drinking water
CARBON EMISSIONS MARKET AND TRADING
Korhan Huseyin Sen*, Fatih Anil** and Orhan Sen***
*Yapi Kredi Bank IT Securtiy/Data Security Department, Cayirova, Kocaeli, Turkey
**Nisantasi University, School of Applied Sciences, Sariyer, Istanbul, Turkey
***Istanbul Technical University, Faculty of Aeronautics and Astronautics,
Department of Meteorological Engineering, Istanbul, Turkey.
Abstract
Human has to produce and consume to sustain human life. Production and consumption are the conditions
of existence of mankind. Life is a synthesis of these two factors. A person pollutes nature when he performs
production and consumption, which are essential for his life. The level of pollution is especially determined
by consumption. Consumption, which has turned into a passion, has led to the growth of industrial
production institutions, which are the most important sources of environmental pollution. Growing
industrial corporations have increased greenhouse gases in their wastes and the atmosphere. The most
common greenhouse gas in the atmosphere is CO2.
Mauna Loa records reveal the exponential increase of carbon dioxide with precise measurements made over
the past 25 years. The value of 407.18 ppm in March 2017 increased to 409, 46 ppm in March 2018.
Countries are looking for ways to reduce carbon emissions without shrinking growing economies. One such
is Emission Trading (ET). Initial views on the emission trading system (ETS) were raised at the Kyoto
Protocol. It has also been expressed in the Paris agreement, but it is still not fully implemented in the world.
The continuation of the increase in greenhouse gases will inevitably lead to emissions trading in the coming
years. For this reason, emissions trading will be one of the most important solutions in preventing global
warming and climate change, which is one of the top three issues in the world public opinion today.
When well designed, emissions trading can be a cost-effective means of reducing emissions by attracting
investment in the private sector and encouraging international co-operation. However, in order to increase
their efficiency, any Emission Trading System has to be designed in accordance with its own structure.
Undoubtedly, we will continue to look for solutions for how we can reduce carbon emissions without
slowing down the growing economy. We are looking for ways to increase the share of renewable resources
in acquiring energy. The aim of the research is to explain the air pollution system which is the cause of the
carbon accumulation in the atmosphere and therefore to manage the reduction properly. Another aim of the
thesis is to understand the Emission Trading System (ETS). The thesis also aims to reveal what the world
and Turkey should do about it.
Keywords: Emission Trading System (ETS), Greenhouse Gases
INTRODUCTION The first views on emissions trading were put forward in Kyoto Protocol. They were also mentioned in the
Paris agreement but still not fully implemented in the world. The continuation of the increase in greenhouse
gases will make emission trade inevitable in the following years. For this reason, ETS will be one of the
most important solutions to prevent global warming and climate change, which is one of the first 3 topics
discussed in the world public opinion today. The solutions to the question of how we can reduce carbon
emissions without slowing up the growing economy will continue. In other words, it is the price of carbon
to reduce emissions and achieve a more sustainable growth.
Carbon pricing is considered as the design and implementation of Emissions Trading Systems (ETS). Since
2016, ETSs have been operating in 35 countries, 13 states or provinces and seven cities around the world,
covering 40 percent of global gross domestic product (GDP) and developing additional systems. Recent
experience shows that, when well-designed, emissions trading can be a low-cost emission-reduction tool
that involves effective, reliable and transparent transparency by mobilizing private sector actors, attracting
investments and promoting international cooperation. However, in order to increase their efficiency, any
ETS should be designed in accordance with its own context. (Pamukcu, 2007).
Carbon pricing alone may not address all the complex factors of climate change; it is also necessary to take
some measures, standards, incentives, training programs and other measures. However, as part of an
integrated policy package, carbon pricing can help markets reduce emissions and help create the
perseverance needed to maintain a safer climate (Kossoy, et al. 2015).
Two types of market instruments can offer a clear price to carbon: emissions trading and carbon taxes. They
both have a lot in common. They change the behavior of Manufacturers, consumers and investors in a way
that will reduce the emissions, who will take action, who will take measures and provide flexibility on when
to take measures; Encourage innovation in technology and practice; Establishing environmental health,
economic and social benefits and, to reduce other taxes and to provide a government revenue to be used to
support public spending on climate or other areas.
The distinctive point here is that the carbon tax and the government determine the price and allow the
market to determine the amount of emissions. However, in emission trade, the government determines the
amount of emissions and allows the market to determine the price. Mixed systems that contain elements
from both approaches are available in different forms. An ETS with a Base and Emission Top Limit price
may be exemplary of taxation systems that accept emissions reductions to reduce tax liabilities. Carbon
pricing should be in line with the principles. The principle of polluter pays and the equitable distribution of
benefits and costs should be avoided and disproportionate burden on sensitive groups should be avoided. It
is necessary to use carbon pricing as one of a series of measures to facilitate competition and openness, to
provide equal opportunities for low-carbon alternatives and to interact with wider climate or non-climate
policies. Ensuring that design promotes economic efficiency reduces the cost of reducing emissions; and a
measurable reduction in environmentally harmful behavior.
Ellerman et al. (2003) emphasized that giving the emission sources the emission credits and the flexibility
to buy and sell the permits would reduce the costs of compliance in achieving the emission target.
Hansjürgens (2005) emphasizes that the analysis made because of the cost-effectiveness of the market-
based emission trading system suggests that the emissions trading system can provide cost savings of up to
90% compared to traditional public authority policies.
Benz and Trück (2009), Fehr and Hinz (2006), Paolella and Taschini (2006), Seifert et al. (2006) and Uhrig-
Homburg and Wagner (2007) studied the dynamic price behavior of emission certificates and spot price
movements of EU emission permits (EUA). Daskalakis, Psychoyios and Markellos (2006) were the first to
analyze the spot and futures prices of EUA contracts. In this study, an equilibrium pricing model based on
current spot prices is used for future prices for 2008-2010 period. Çikot (2009) and Kadi's (2010) 's
emissions markets, there is the functioning of the markets and traded in this market instruments with Turkey
to the Kyoto work on developments that may occur with the accession to the Protocol. While Peker and
Demirci (2008) emphasized the importance of emission trade by analyzing climate change from the
perspective of science and economics, Pamukçu (2007) evaluated whether the EU Emissions Trading
System (EU ETS) could be a model for a global emission trading system in the fight against climate change.
In this study, a method for calculating, collecting and distributing carbon tax is presented. This method is
applied to companies that produce electricity in Turkey as well. Turkey has also been used in the calculation
of the carbon tax emissions by 2016. The reason for using this year, the most recent year history of being
out of control emissions and the commitments given in the Turkey of 2016 is the Paris agreement. In carbon
tax calculation, the power generation with 80% share in greenhouse gas production in 2016 is considered.
For other emission sources, this method can be used in other studies.
DATA AND METHODS
The Kyoto Protocol has allowed flexibility in Annex 1 countries to purchase emissions reductions from
other countries to achieve their greenhouse gas emissions targets. This mechanism has been set for two
main reasons: Adhering to the Kyoto Protocol is very restrictive for some Annex 1 countries (especially for
countries that have already undergone minor emissions, such as Japan and the Netherlands, and respect
environmental standards). The Protocol thus allows these countries to obtain Carbon Credit instead of
reducing their greenhouse gas emissions; and in this way, countries not included in Annex I are encouraged
to reduce greenhouse gas emissions because they acquire resources for these projects by selling Carbon
Credit.
Emission trading system (ETS) is one of the leading projects. This system allows Annex 2 parties to sell
part of their release permits to Annex 1 on the part of Annex 2, which produces less greenhouse gas
emissions than specified amounts. However, although emissions trading allows emissions to be transferred
from one side to the other, total emissions may not be more than the previously agreed total release. In
addition, emissions trading can be performed in addition to local activities aimed at reducing or limiting
emissions. Countries that sell their rights are expected to make investments to reduce their emissions with
the money they will obtain. If the countries with emission rights to which they are able to sell now have an
increase in their discount obligations and energy demands in the later periods of obligations, the sale rights
to meet them are not bad results.
A properly functioning carbon market leads businesses to use clean technology by encouraging less
greenhouse gas emissions. It is possible to examine carbon markets under two categories as compulsory
and voluntary:
Compulsory Carbon Markets: The flexibility mechanisms defined in the Kyoto Protocol allow countries to
reduce emissions at low cost. The flexibility mechanisms described in the Protocol are Emission Trading
(ET), Joint Implementation (JI), and Clean Development Mechanism (CDM). According to the Kyoto
Protocol, Emissions Trading (ET) and Joint Implementation (JI) mechanisms can be made between Annex-
I countries, and the Clean Development Mechanism can be made between Annex-I and Annex-I countries
(CSB, 2012).
Carbon tax: The carbon tax applies to those designated by the regulatory authority. The tax relates to
greenhouse gas emissions that the entity is responsible for. The tax liability can be determined based on the
measured greenhouse gas emissions or converted to CO2 (equivalent) by energy (consumed, produced or
provided). In any case, emissions must be verified. Energy tax applied per fossil fuel energy unit consumed
by a pollutant is another type of tax that is very similar to carbon tax (Pamukcu, 2007). It provides incentives
to reduce emissions to pollutants by reducing carbon tax, fuel change, energy efficiency improvements,
transition to lower carbon density products, or reduced emissions to emissions generating activities. Carbon
tax is a method in which income is used again. Tax revenues can be re-used for future emission reduction
targets, or they can alleviate carbon distribution and economic burdens.
The UK has implemented an energy-based mortar that exemplifies how the carbon tax can be applied,
including re-use mechanisms of income (Kossoy, et al. 2015). The climate change fee is a type of tax that
is unique to the UK that applies to electricity and taxable fossil fuel commodities supplied to businesses
and public consumers. The climate change fee was introduced in 2001 and collected from the energy
suppliers by the government. It aims to change business behavior by providing a price signal to promote
energy efficiency and reduce emissions. Rates are expressed in terms of energy consumed, not in carbon
emissions (CSB,2012).
Carbon tax practice in Turkey, the distance to the domestic coal use and will create pressure to increase
dependence on imported natural gas, the energy security policy is in conflict considerably. In Turkey, the
field of application of environmental taxes can say literally and effectiveness in curbing the problems in
western countries is extremely limited. For example, already it does not have any carbon taxes on fossil
fuels in Turkey (Gundogan, 2015).
Revenue use: Carbon pricing policies, including policies aimed at energy efficiency and renewable energy,
can provide a (re-usable) income that can then be used to finance low-carbon activities or investments in
other activities. Re-use of revenue can help to stakeholder engagement by compensating those who are
directly or indirectly affected by increasing the resulting carbon reductions, meeting administrative costs,
or costs. According to the current regulation, the amount of expenditures for the environment; The amount
of goods, freight and insurance costs that are subject to the permissible control for importation of fuel and
wastes are collected from the sum of the cost of insurance (CIF), water and used water removal fees,
administrative fines imposed by the Environment Law, interest rates of credits and grants, donations and
sources of assistance. The amounts collected from the mentioned revenues are recorded as special income
in the general budget.
Emission Trading System: The transformation of global energy needs from an energy based fossil fuel to
an energy system based on renewable energy; more efficient use of energy across the economy and the use
of non-fossil fuels in electricity generation should be increased. Authorities are increasingly adopting
carbon pricing as a way of implementing the decarburization process. Carbon pricing includes the cost of
external greenhouse gas emissions into the economic system.
The introduction of a price on greenhouse gas emissions makes activities that do not cause greenhouse gas
emissions more profitable than those causing greenhouse gas emissions; it can help to direct investments
and innovations towards low-carbon development. There are two policies that set a net price for greenhouse
gas emissions. One of them is taxation on greenhouse gas emissions. In the carbon tax system, the
government determines the price to be paid for each ton of greenhouse gas emissions covered by the tax.
Finally, market dynamics will determine the amount of emissions corresponding to this tax level (CSB,
2017).
The other is the Emission Trading System (ETS), which imposes a limit (or upper limit of emissions) on
greenhouse gas emissions from facilities covered by the system. In this system, the facilities within the
scope of ETS must deliver the emission allocation covering the total greenhouse gas volume released. The
allocations corresponding to the upper limit of emissions are allocated at first, free of charge or through a
tender process. Appropriations can also be obtained through trade (trading) between facilities and other
third parties. Contracts and trade between facilities determine the market price for allocations. If the
emission limit is well established, the number of allocations is less than the need for allocations in a scenario
where there is no greenhouse gas reduction, and a demand in the market is created. Thus a price is set for
allocations and an incentive to reduce emissions (CSB, 2017)
The economic theory in which the emission trade is valid is to determine the emission limit of the lowest
cost options for emission reduction. The introduction of a price on greenhouse gas emissions makes the
activities that do not cause greenhouse gas emissions more profitable than those causing greenhouse gas
emissions. It can help to guide growth towards low carbon energy production in the economy.
International Carbon Action Partnership should keep in mind when designing the ETS in Turkey (ICAP)
must comply with the rules. It should determine which sectors and facilities to include in ETS. It is
necessary to determine the upper limit of emissions and clarify how allocations are distributed. ETS shall
determine whether to allow the use of emission reductions in projects outside the ETS scope to fulfill its
obligations. Emission reductions should be given to the participants when they are flexible. Price
estimation, cost protection, compliance with surveillance and compliance should be followed.
The scope of the ETS should be as broad as possible to optimize cost effectiveness. ETS needs to be
supported by other policies to ensure long-term reduction. Examples of these other policies include support
policies to reduce the costs of emission reduction technologies, policies to remove non-economic barriers
that often interfere with cost-effective energy efficiency policies and other policies.
In Turkey, the voluntary offset market is dominated by renewable energy projects having a direct impact
on emissions are likely covered by the ETS possible. It is recommended that new voluntary projects should
not be allowed to start in these sectors and a temporary solution should be found for existing projects that
continue to produce certificates.
APPLICATION AND RESULTS
Implementation of the Carbon Tax Policies in Turkey
Where can the carbon tax be used?
The use of carbon tax revenues to overcome macroeconomic problems, such as budget deficits, may lead
to deviations from the main objective. Ekins and Berker (2001) stated that income from carbon tax could
be used in four ways;
It can use it to subsidize energy efficiency measures to achieve the environmental objective.
It can be used for investments and technological developments by providing the efficiency of income
distribution from carbon tax. It can be used to reduce government debt to reduce future tax burden.
It can be used to reduce other inefficiencies in the economy. That is, the negative impact of tax practices
can be reduced by government spending financed by environmental tax revenues.
Carbon tax will lead to cost implications, Turkey's carbon tax must assess mechanisms together with the
re-use of revenue. Revenue-generating mechanisms often include the re-use of revenue to reduce cost
effects and to encourage additional reduction.
Table 1. According to the primary energy source for Turkey's installed capacity of 2016 MW (TEDKB, 2018).
Coal Liquid Fuels
Natural Gas
Renewable (Waste +
Waste Heat)
Multiple Fuels ( Solid + Liquid)
Multiple Fuels
(Liquid + Natural
Gas)
Hydraulic Power Plants
Geothermal Wind Solar Total
2016 17355.3 445.3 19563.6
496.4 582.7 5968.3 26681.1 820.9 5751.3 832.5 78497.4
% 22.11 0.57 24.92 0.63 8.35 33.99 1.05 7.33 1.06 100.00
Table 2. Distribution of Turkey in 2016 according to the primary energy source MW of installed power
Power Plants Hydraulic Power Plant Geothermal Wind Solar Total
2016 44411.6 26681.1 820.9 5751.3 832.5 78497.4
% 56.58 33.99 1.05 7.33 1.06 100.00
Table 3. sources of electricity generation as well as distribution calculations according to Turkey's installed
capacity in 2016 is given. The values of Table 1 and Table 2 from TEDBT were taken in these calculations.
In these calculations, Solid + Liquid and Fluid + Gas values in the tables are considered to be shared equally
between Coal - Liquid Fuel and Liquid Fuel - Natural gas. Table 3. The results of Turkey's electricity
installed capacity share of CO2 emissions in 2016, calculated the share of renewable and non-renewable
energy dispenser is given in Table 4.
Turkey's installed capacity of electricity generation in 2016 the largest share of 51.36% in energy coal to
non-renewable resources be used when the primary base is in the first place. In the second place, natural
gas comes with a share of 38.14%. The share of renewable energy used in the same year is 74,66%. Wind
energy (RES) is the second with 18.21% share.
Turkey 's clean energy sources should increase Solar and geothermal energy. Although hydraulic energy is also clean energy, rainfall amount decrease and rainfall severity increase in Turkey cause decrease in water resources due to climate change. Therefore, the energy to be produced from hydroelectric power
plants should be considered with suspicion. It should be encouraged to turn to clean energy sources. For
this reason, regulations that allow the trade of Carbon Tax or clean energy certificates to increase
investments in this sector should be done as soon as possible. In this system, a reasonable price should be
placed on carbon emissions for Users to pay. In this way, the use of fossil fuel will be reduced, thus reducing
CO2 emissions. The social cost of carbon in the world is estimated between $ 37 and> $ 400 / ton CO2e,
given the global warming and consequent damage to climate change.
Governments should determine the emission limit or reduction commitment in carbon pricing. In the carbon
tax or trade, pricing should be taken from the carbon exchange or the governments should determine.
Governments receive commitments from companies to spread emissions reduction targets over the years.
A maximum emission value per year is dictated
.
Figure 1. Example of carbon emission among companies
In Figure 1, A emits CO2 above the allowance. therefore he needs more trace. Company B emits less CO2
than allowed. Therefore, it has the right to spread more. Company B sells this right to A if it wishes.
What is the value of a carbon tax?
Company B Company A Company B
The quantity to be sold to Company A
Allowed CO2 Allowed CO2 Emitted CO2 = Allowed CO2 Emitted CO2 Emitted CO2
We know that greenhouse gas emissions cause damage. If we estimate how much carbon emissions are
actually at their expense (often referred to as the Social Cost of Carbon (SCC)), it will guide us to the kadar
right te price. However, these cost estimates are in a wide range. This value ranges from US $ 10 / tCO2e
to $ 400 / tCO2e.
According to FEMA (Federal Emergency Management Agency, USA) survey, sea level is estimated to
have increased by 1 meter to 2050. This will probably cause 40-60% more damage in storm fluctuations.
As hurricanes and storms become more intense, this damage will continue to increase. Estimates of
Hurricane Sandy cost $ 65 billion. These are just direct costs. Indirect costs such as health, product
uncertainties and others should be added. While the EPA calculated Social Cost Carbon (SCC) as $ 37 /
tCO2e, a Stanford study published in 2014 estimated the SCC to be $ 220 / tCO2e. The difference in the
Stanford study is that it includes environmental costs. This is the price to be placed on the loss of
biodiversity necessary for human health. In 2015, prices ranged from US $ 1 / tCO2e (Mexico) to US $ 168
/ tCO2e (Sweden). Most prices are well below the conservative estimates of carbon cost. On the other hand,
the European Union has a tonne of CO2 in the carbon market (as of 2017).
Turkey in the carbon tax has been taken into account greenhouse gas emissions in the power generation
installed capacity of eye, which makes up a share of 80%. Other emission sources can also participate in
calculations. Annual total energy and CO2 values are based on 2016 year. As the allowable limit CO2
emissions in Turkey's declaration given at the Paris agreement signed in 2016 was based. This declaration
includes an emission reduction of 21% on the basis of 2016 values. Therefore,% 79 part will be referred to
as allowed part. This value is 184.108.799.00 tons CO2 in 2016 values. This value will remain acceptable
until 2030. 21.9% of the tax is 48.940.313.7 tons of CO2. In the following years, the increase in the energy
need will increase the amount of tax. If this value is kept constant increase in energy needs if requested
Turkey must meet its renewable energy sources. Therefore, the income derived from carbon tax should be
shared among the companies that produce renewable energy.
Various countries' values have been investigated as carbon tax. In the calculations, the carbon exchange
value of the European Union, Euro 15 / TCO2, was taken. Table 3.3. For the year 2016, the total energy
obtained from non-renewable energy sources for 2016 is 202.736.15 MW. The amount of energy obtained
from renewable sources is 34,085,80 MW. In the same table, 233.049.113 Ton CO2 is produced from the
energy obtained from non-renewable energy sources. Turkey agreement in Paris, with 2030 declared that it
would reduce greenhouse gas emissions by up to 21 percent over the current situation. Turkey must make
the amount of carbon produced from non-renewable sources of energy up this reduction. Although the
production of CO2 from renewable energy sources may be seen in Table C, this is the emissions that occur
during the installation of the plants and they are only once. Therefore, a discount of 21% of this carbon
amount is irrational. For this reason, energy obtained from non-renewable energy source is discussed. This
includes the sum of coal, liquid fuel and natural gas.
Table 3. Breakdown of installed capacity, according to sources in Turkey's electricity production in 2016
(TEDKB, 2018). % Unit Amount Conversion
coef. for kg CO2
Produced
CO2 in one hour
(ton)
Produced
CO2 in a year (ton)
Coefficient
for conversion
to
renewable energy
Coefficient
for conversion
to non-
renewable energy
Renewable
energy (in-use)
Non-
renewable energy (in-
use)
Coal 23 kW
h
17646750 0.9 15882.08 1391270
21
0.035 3.978 0.7875 89.505
Liquid Fuels
5 kWh
3720800 0.7 2604.56 22815946
0.018 3.340 0.0846 15.698
Natural Gas 29 kW
h
22547600 0.36 8117.14 7110614
6
0.009 2.316 0.2583 66.4692
Nuclear Energy
0 kWh
0 0.02 0 0.012 4.060 0 0
Hydraulic
Energy
34 kW
h
26681100 0 0 1.127 0.029 38.318 0.986
Solar Energy
1 kWh
832500 0.05 41.62 364591 1.004 0.384 1.1044 0.4224
Wind
Energy
7 kW
h
5751300 0.01 57.51 503788 1.280 0.102 9.344 0.7446
Geothermal Energy
1 kWh
820900 0.03 24.63 215759 1.280 0.254 1.408 0.2794
Wood 0 kW
h
0 0 0 1.144 0.209 0 0
Others 1 kW
h
496400 0 0 0.031 0.254 0.0186 0.1524
Total 100 78497350 26727.54 2341332
51
51.3234 174.257
Average 0.3403 0.5132 1.7426
Note: 1 year is accepted as 8760 hour
Table 4. Turkey's Renewable Energy Potential and Use Case (Demir and Emeksiz, 2016)
Sources Available
Gross
Potential
(GWh/year)
Technically
Assessable
Potential
(GWh/year)
Economically
Assessable
Potential
(GWh/year)
Potential in-use
(GWh/year)
Use (%)
Hydraulics 430-450 215 100-130 35330 30
Solar 365 182* 91** 4.07 4.5
Biogas 1.58 0.79* 0.4** 0.067 16.8
Wind 400 124 98 61 62
Geothermal 16 8* 4** 0.89 22.5 *: 50% of Total Gross Potential is used
**: 50 % of Technically Assessable Potential is used
Table 5. Turkey’s renewable clean energy potential distribution in 2016.
Sources Potential in-use (%) Potential not in-use (%) Normalized (%)
Hydraulics 30 70 25
Solar 4.5 95.5 33
Wind 62 38 14
Geothermal 22.5 77.5 18
The taxable 21% value is 48.940.313.7 tons CO2. If the European Union is calculated using the value of
the carbon exchange, the total 1-year carbon tax income is 734.104.706,00 EURO. The distribution of this
tax by companies is given in the table below. This distribution is made according to the emissions of the
companies.
The use of carbon tax should be shared among renewable energy sources as described in the sections above.
When making this distribution, the share of renewable energy used as the installed power of companies
should be taken into consideration. Turkey has the highest rate in 2016 with 74.66% share of renewable
energy used in this sector hydropower (HPP) he said. This is followed by wind energy up to 18.21%. Solar
and geothermal energy exceeds 2% very little.
The distribution of the potential to be taken into account in this distribution and how much renewable energy
potential is available. Table 3. the potential for renewable energy in Turkey and used potential is given as
of 2016. The distribution of taxes by considering these factors is given in Table 5. These results were
obtained from the actual data of 2016 year. The government may make changes to the collected carbon tax
rates or make other deductions or breaks in distribution. In this study, calculations have been made
considering the current values. The calculations included non-CO2 emissions from renewable energy
sources. Biogas is therefore not included. The remaining four renewable energy sources (Hydraulics, Solar,
Wind, Geothermal) have been normalized among themselves. The obtained ratios were used in sharing.
These values are given in Table 5. According to these results, income from carbon tax was shared among
renewable clean energy source electricity generation companies (Table 6.).
Table 6. Turkey's electricity installed capacity share of CO2 emissions and renewable and non-renewable energy in
2016, their share in the dispenser. Source Non-renewable
energy (in-use)
Share in
produced CO2
Renewable
energy (in-use)
Encashed Carbon
Tax (Euro)
Distributed
Amount (Euro)
Coal 51.36 59.42 1.53 438275191.0
Liquid Fuels 9.01 9.74 0.16 71846827.0
Natural Gas 38.14 30.37 0.51 223982686.0
Hydraulic Energy 0.57 0 74.66 183256176.0
Solar Energy 0.24 0.16 2.15 242254553.0
Wind Energy 0.43 0.22 18.21 102774659.0
Geothermal
Energy
0.16 0.09 2.74 205549318.0
Others 0.09 0.00 0.04
Total 100.00 100.00 100.00
CONCLUSIONS AND RECOMMENDATIONS In this study, a method for calculating, collecting and distributing carbon tax is presented. This method is
applied to companies that produce electricity in Turkey as well. Turkey has also been used in the calculation
of the carbon tax emissions by 2016. The reason for using this year, the most recent year history of being
out of control emissions and the commitments given in the Turkey of 2016 is the Paris agreement. In the
carbon tax calculation, the installed power generation capacity of 80% of greenhouse gas production in
2016 is considered. For other emission sources, this method can be used in other studies. Turkey's electricity
production in 2016 is the first among the largest share of 51.36% to coal. Natural gas is the second with a
share of 38.14%. In 2016, the share of HEPP in renewable energy used is 74,66%. Wind energy (RES) is
the second with 18.21% share. The energy obtained from non-renewable energy sources for 2016 is
202.736.15 MW. The amount of energy obtained from renewable sources is 34,085,80 MW. 233.049.113
Ton CO2 is produced from the energy obtained from non-renewable energy sources.
As the allowable limit CO2 emissions in Turkey's declaration given at the Paris agreement signed in 2016
was based. This declaration includes an emission reduction of 21% on the basis of 2016 values. Therefore,%
79 part will be referred to as allowed part. This value is 184.108.799.00 tons CO2 in 2016 values. The
taxable 21% value is 48.940.313.7 tons CO2. In the calculations, the carbon exchange value of the European
Union, Euro 15 / T CO2 was taken. 2016 annual carbon tax revenue is 734.104.706,00 EUR. The
distribution method of this tax on the basis of companies is given in the findings section. Distribution of
renewable clean energy companies, Hydraulic Energy 25%, Solar Energy 33%, Wind Energy 14%, and
Geothermal Energy 28%.
In the following years, the increase in energy demand will increase the amount of tax. If this value is kept
constant increase in energy needs if requested Turkey must meet its renewable energy sources. Therefore,
the income derived from carbon tax should be shared among the companies that produce renewable energy.
The government may make changes to the collected carbon tax rates, make a deduction or other evaluation
of the distribution.
REFERENCES BENZ, E. ve TRÜCK, S. (2009). “Modelling the Price Dynamics of CO2 Emission Allowance”, Energy
Economics, 31, 1.
PAMUKÇU, K. (2007). “Küresel Emisyon Ticareti Sistemi İçin Bir Model: Avrupa Birliği Emisyon
Ticareti Programı”, İÜ Siyasal Bilgiler Fakültesi Dergisi, 37.
ÇŞB, 2012: Türkiye de Karbon Piyasası, T.C. Çevre ve Şehircilik Bakanlığı, Ankara
ÇŞB, 2017 a: Uygulamada Emisyon Ticareti. T.C. Çevre ve Şehircilik Bakanlığı, Ankara
ÇŞB, 2017 b : Karbon Piyasalarına Hazırlık Ortaklığı. T.C. Çevre ve Şehircilik Bakanlığı, Ankara
ÇİKOT, Ö. (2009). “Avrupa’da Karbon ve Enerji Borsaları”, Sermaye Piyasasında Gündem, 82.
DASKALAKIS, G., PSYCHOYIOS, D. ve MARKELLOS, R.N. (2006). “Modelling CO2 Emission
Allowance Prices and Derivatives: Evidence from the EEX”, Athens University of Economics and
Business.
ELLERMAN, A.D., JOSKOW, P.L. ve HARRİSON, D.Jr., (2003). Emissions Trading in the U.S.,
Experience, Lessons, and Considerations for Greenhouse Gases, US: Pew Center on Global Climate
Change.
FEHR, M. ve HINZ, J. (2006). “A Quantitative Approach to Carbon Price Risk Modeling”, Institute for
Operations Research, ETH Zurich
Gündoğan, A. C., 2015. Climate action tracker (CAT) assessment of Turkey’s INDC [online], Ankara,
http://www.cemgundogan.com/2015/10/22/climate- action-tracker-cat-assessment-of-turkeys-indc/.
KADILAR, R. (2010). Karbon Fırsat mı, Tehdit mi? İstanbul: Destek Yayınları
Kossoy, A., Grzegorz Peszko, Klaus Oppermann, Nicolai Prytz, Noémie Klein,Kornelis Blok, Long Lam,
Lindee Wong, Bram Borkent . 2015. State and Trends of Carbon Pricing 2015 (Eylül), by World Bank,
Washington, DC.
PEKER, O. ve DEMİRCİ, M. (2008). “İklim Değişikliğinin Bilim ve Ekonomi Perspektifinden Analizi”,
SDÜ İİBF, 13, 1.
PAOLELLA, M.S. ve TASCHINI, L. (2006). “An Econometric Analysis of Emission Trading
Allowances”, Research Paper Series 06–26, Swiss Finance Ins Petform, Kyoto protokolü bilgi notu, Kyoto
protokolünün Türkiye enerji sektörüne muhtemel etkileri, 2009. http://www.petform.org.tr.
SEIFERT, J., UHRIG-HOMBURG, M. ve WAGNER, M. (2006). “Dynamic Behaviour of CO2 Spot Prices
- Theory and Empirical Evidence”, Working Paper, Chair of Financial Engineering and Derivatives,
University of Karlsruhe.
UHRİG-HOMBURG, M. ve WAGNER, M. (2007). “Futures Price Dynamics of CO2 Emission Certificates
- An Emprical Analysis”, Working Paper, Chair of Financial Engineering and Derivatives, University of
Karlsruhe
TETKB, Türkiye Enerji ve Tabii Kaynaklar Bakanlığı 2018: www.enerji.gov.tr
FLUCTUATION OF THE WINTERTIME ARCTIC OSCILLATION
PATTERN
Lin Wang
Institute of Atmospheric Physics, Chinese Academy of Sciences, China
Abstract
The Arctic Oscillation (AO) is the leading mode of climate variability in the Northern Hemisphere winter.
It is generally regarded as a zonally-symmetric pattern with one center over Pacific and two centers over
the North Atlantic and North Pacific. Based on observational and reanalysis datasets with long records, the
multidecadal fluctuations in the patterns and teleconnections of the winter mean AO are investigated.
Results show that the Atlantic center of the AO pattern remains unchanged throughout the period 1920–
2010, whereas the Pacific center of the AO is strong during 1920–59 and 1986–2010 and weak during
1960–85. Consequently, the link between the AO and the surface air temperature over western North
America is strong during 1920–59 and 1986–2010 and weak during 1960–85. The time-varying Pacific
center of the AO motivates a revisit to the nature of the AO from the perspective of decadal change. It
reveals that the North Pacific mode (NPM) and North Atlantic Oscillation (NAO) are the inherent regional
atmospheric modes over the North Pacific and North Atlantic, respectively. Their patterns over the North
Pacific and North Atlantic remain stable and change little with time during 1920–2010. The Atlantic center
of the AO always resembles the NAO over the North Atlantic, but the Pacific center of the AO only
resembles the NPM over the North Pacific when the NPM–NAO coupling is strong. These results suggest
that the AO seems to be fundamentally rooted in the variability over the North Atlantic and that the annular
structure of the AO very likely arises from the coupling of the atmospheric modes between the North Pacific
and North Atlantic. Analysis of model outputs from the Coupled Model Intercomparison Project (CMIP)
phase 5 (CMIP5) also reveals fluctuations in the Pacific center of the AO, and the possible mechanism is
discussed.
Keywords: AO, teleconnection, decadal variation, CMIP
STUDY OF MEMBRANE STABILITY AND MEMBRANE DAMAGE
RATE IN WHEAT CULTIVARS UNDER HEAT STRESS
S. T. Zulfugarova, S. A. Omarova, S. M. Rustamova
Institute of Molecular Biology & Biotechnologies, Azerbaijan National Academy of Sciences
Abstract
Crops grown all over the world are critical for food supply. Changes in temperature and intensity of extreme
weather could have significant impacts on crop yields. Among crop plants wheat, widely cultivated for its
seeds,has a special place. Membrane stability, which is one of the main physiological indicators correlating
with plant productivity under stress conditions, is considered as an important parameter of stress resistance
in breeding programs. The main aim of present study is to identify gene locus Xbarc108-7A that is
associated with membrane stability as well as to measure the membrane damage rate in different wheat
genotypes during heat stress. Twelve wheat genotypes (Farandole, Tale38, Tartar2, Nurlu99, Murov2,
Gyzylbugda, Giymatly2/17, Layagatli80, Vugar, Shiraslan23, Gobustan, Gyrmyzygul 1), differing in stress
tolerance, productivity and other physiological parameters collected in the Gene Pool of the Research
Institute of Crop Husbandry (Baku, Azerbaijan) were used as the research objects. Plants were grown on
wet filter paper in petri dishes at 18-200C. DNA extraction from 7 day old seedlings was performed using
CTAB method with some modifications. After diluting DNA was quantified by taking the optical density
(OD) at λ = 260 with a spectrophotometer ULTROSPEC 3300 PRO (“AMERSHAM”, USA). The purity
of genomic DNA was determined by the A260/A280 absorbance ratio. The quality was also examined by
running the extracted DNA samples on 0.8 % agarose gel stained with 10 mg/ml ethidium bromide in
1×TBE (Tris base, Boric acid, EDTA) buffer. To assess the membrane stability in wheat genotypes, specific
barc108F/barc108R SSR marker (5'GCGGGTCGTTTTTTTGGAAATTCATCTAA3'/5'
GCGAAATGATTGGCGTTACCTGTTGG 3') was used for the PCR analysis. PCR was performed in the
“Applied Biosystems 2720 Thermal Cycler” thermocycler under the following conditions: After incubation
at 94 °C for 5 min, 5 cycles were performed with 94 °C for 1 min, 35 °C for 1 min, and 72 °C for 1 min 30
s. Further, the similar 35 cycles were performed with exception for the annealing temperature at 56 °C and
a final extension at 72 °C for 15 min. The reaction products were separated by electrophoresis in a 2%
agarose gel in the HR-2025-High Resolution («IBI SCIENTIFIC» U.S.) horizontal electrophoresis machine
with addition of ethidium bromide and documented using «Gel Documentation System UVITEK». Then
reaction products were separated by electrophoresis in 2% agaroza gel. Expected 156 bp fragment was
revealed in all studied genotypes. Xbarc108-7A locus that makes association with membrane stability is
located in 7A chromosomes of the studied genotypes. At the same time membrane thermal stability (MTS)
was measured during heat stress. To this end 7-day-old seedlings were subjected to heat stress within 5
minutes. In order to set the total electrolyte leakage from the leaf tissues, plants were kept in a boiling water
bath for 30 minutes. Then the total electrolyte leakage was recorded by conductivity meter (Horiba
Scientific). Highest membrane damage rate (MDR) was found in cultivar Shiraslan23 (39.53) and the
lowest in Giymatli2/17, (0.31). It is suggested that MDR value directly indicates membrane damage
rate.The existence of QTL for membrane stability in abiotic stress sensitive genotypes, such as
Giymatli2/17 and Gyrmyzygul 1, shows that these wheat genotypes also have genetic potential for
resistance, but the reason for their susceptibility should be studied at the level of gene expression.
Keywords: wheat, abiotic stress, QTL, SSR-marker, membrane damage rate
BIODIVERSITY ASSESSMENT OF DURUM WHEAT ACCESSION
BASED ON MOLECULAR MARKERS
Gulnar Shikhseyidova, Samira Salayeva, Ellada Akhundova
Department of Genetics and Theory of Evolution, Baku State University, Baku, Azerbaijan,
Abstract
Climate change refers to significant and long-term changes to a region’s climate. These changes can occur
over a few decades, or millions of years. Climate change alters entire ecosystems along with all of the plants
and animals that live there. As cli-mate has changed throughout Earth’s history, all living creatures have
had to adapt, move, or die out. When these changes happen gradually, ecosystems and species are able to
evolve together. A gradual change also gives species the opportunity to adapt to new conditions. But, when
the change happens very quickly, like it is today, the ability of species to adapt quickly enough or relocate—
assuming a suitable location exists—is a big concern.
Grain production needs to be doubled to feed an increasing world population which is estimated to reach
approximately 9 billion by 2050. The existing trends in wheat yield increase are inadequate to meet this
projected demand. Wheat is one of the most important crops providing one-fifth of the total calories for the
world’s population. Breeding gains rely on access to useful genetic variations from crops’ gene pools. Gene
banks are the repositories of beneficial gene(s)/alleles from crop’s primary, secondary or tertiary gene pools
which should be harnessed for present and future wheat genetic improvement programs. Genetics Marker
play an essential role today in the study of variability and diversity, in the construction of linkage maps,
and in the diagnosis of individuals or lines carrying certain linked genes. Within this context, the limitations
of morphological markers became quickly apparent. Recent advances in molecular biology have provided
us with novel tools to establish evolutionary and genetic relationships among plants of research interest,
which was a cumbersome job earlier. Genetic diversity analysis can be done by observing variations in
DNA sequence using molecular markers with high accuracy and throughput which is often not visible at
the phenotypic level. Genetic diversity studied via molecular markers can be efficiently used to identify the
taxonomic and phylogenetic relationships among cultivars for pedigree analysis and linkage mapping.
In this research the genetic relationship among 41 durum wheat accessions, collected from different
countries (Morocco, Ethiopia, Turkey, Lebanon, Kazakhstan, China, and Mongolia), was evaluated by
using 15 inter simple sequence repeats of genetic marker. Cluster analysis based on ISSR binary data was
used to group the wheat accessions using the complete linkage method. The obtained data from cluster
analysis showed high genetic diversity between studied durum wheat genotypes. Considering these
evidences, one might be inclined to conclude that East Asian areas can not be considered as important
centers for the diversity of durum wheat. Instead, as the results of this study show, areas in west Asia (Fertile
Crescent) and north and east of Africa are considered to be the main diversity centers for this plant.
Moreover, the results of present study also showed that ISSR analysis is quick and reliable. The marker
system provided sufficient polymorphism and reproducible fingerprinting profiles for evaluating genetic
diversity of durum wheat genotypes. Molecular variation assessed in this study in combination with
agronomic and morphological characters of wheat can be exploited in breeding programmes.
Keywords: genetic diversity, Fertile Crescent, molecular markers, durum wheat
MOLECULAR DIVERSITY OF STURGEONS (ACIPENSERIDAE) IN THE
CASPIAN SEA BASIN
Gulnara Guluzada1,2, Javid Ojaghi1
1Department of Life Sciences, Khazar University, Baku, Azerbaijan, [email protected] 2Department of Bioengineering, Azerbaijan Food Safety Institute, Baku, Azerbaijan, [email protected]
Abstract
The Caspian Sea was known the biggest lake in the world with 371,000 square kilometers surface area.
This renowned and intercontinental sea does not exist direct entrance to the ocean. Bordering by 5 countries
Russia, Kazakhstan, Azerbaijan, Turkmenistan, and Iran, the Caspian Sea are abundance with variety of
fish species such as sturgeon, roach, carp, pike perch, grey mullet, kutum, anchovy, bream, pike, and perch.
The main resource of sturgeon fishes approximately up to 90 percent belongs to Caspian Sea. Based on
fishing rights, leader of mentioned countries extended prohibition on catching sturgeon for coming another
year by taking into account endangered status. Nowadays, sturgeon and paddlefish species are edge of
extinction, mainly in the Ponto Caspian (including the Mediterranean, Aegean, Black, Azov, Caspian &
Aral Seas) region that is hotspot of sturgeon biodiversity globally.
Unfortunately, last three decades associated with dramatic decrease of sturgeon population by 99 percent
poaching and illegal catching that leads catastrophic population disappearing. Additionally, due to long life
cycle of sturgeons and late maturity make difficulties for the species to rescue from the proceed enforcement
of overexploitation, losing habitat and alteration. Since the Middle Ages, the sturgeon meat and especially
caviar have gained the most valuable products over the world commercially and culturally. Moreover,
habitat destruction and constructions of irrigation channels and barriers as well as dams are the main reason
acceleration of extreme drop.
Evolutionary, ecologically and commercially valuable sturgeon fishes belong to order Acipenseriformes
(two families Acipenseridae and Polyodontidae), superorder Chondrostei distribute northern hemisphere
that consist 27 species. These ancient groups of fishes are recognized from the Jurassic period that is
identified by cartilaginous skeleton, a spiral valve in the gut, a heterocercal tail, and an advanced rostrum
with mouth inferior.
In compare to another fish species sturgeons possess a very long life cycle (maximum lifetime up to over
150 years, depending on species). They differentiated by the late-maturation, and most of them grow to
very large sizes (up to 6–7 m long). Plenty of the sturgeon species are anadromous. As well as encountered
potamodromous (landlocked) species and forms, spending their entire life cycle in freshwater.
The knowledge of the genetic structure of populations is important for maintaining genetic diversity of the
Sturgeons (Acipenseridae) while it is reared. The most reliable method for studying gene diversity is
application of molecular marker technologies like microsatellite DNA analysis. The use of microsatellite
DNA as high polymorphic DNA markers has gained in importance for a number fish species over the past
decade owing to the fact that it is an easy and powerful method.
The major aim of this study is devoted to use of microsatellite DNA for estimation of genetic diversity in
Sturgeons (Acipenseridae) farmed at Azerbaijan fish farm. In this research fourteen microsatellite loci like
LS-19, LS-22, LS-23, LS-34, LS-39, LS-54, LS-57, LS-58, LS-62, LS-68, LS-69, AoxD234, AnacE4 and
AnacC11 will be analyzed and the genotypic data would be used to calculate the estimated heterozigosity
(HE), observed heterozigosity (HO) and null allele. This study will provide baseline data for the
development of scientifically sound management of the farmed Sturgeons (Acipenseridae) in Azerbaijan.
Keywords: sturgeon, genetic diversity, Caspian Sea, microsatellite markers
MICROBIOLOGICAL PURIFICATION OF OIL POLLUTION IN
CASPIAN SEA WATERS
P.Mamedova, K.Kakhramanova, E.Babayev, T.Ibragimova
Institute of Chemistry of Additives of NASA
Abstract
Application of technologies that contribute to the destruction of various organic compounds by use of
biological products obtained on the basis of active strains of microorganisms-oil destructors is a promising
way to eliminate technogenic pollution. The search for new strains of hydrocarbon-oxidizing
microorganisms is topical that allow us to solve specific problems of restoring natural oil-polluted objects,
including sea water. The hydrocarbon-oxidizing microorganisms - oil destructors were separated from
samples of oil-contaminated sea water. The process of oil biodegradation was investigated and the
destructive activity of microbial cultures isolated from seawater was determined. The obtained experimental
data allow us to recommend selected active cultures for further introducing them into the composition of
the developed microbial biopreparation.
Keywords: bioremediation, hydrocarbon oxidizing microorganisms, biological products.
INTRODUCTION Pollution of sea water by products of oil production and oil refining is one of the most important
environmental problems of the present time. The influence of oil and oil products leads to a deterioration
in the physical properties of water: change in color, taste, smell. The oil film prevents the penetration of
oxygen into the water. There are many aspects of environmental risk associated with the negative effects
of the oil itself, as well as with the possibility of its destruction and transformation processes contributing
to secondary water pollution by toxic substances. Intermediate products of the destruction of petroleum
hydrocarbons are also formed as a result of processes occurring in the water column, in particular bottom
sediments and in the water-atmosphere contact zone. Large amounts of harmful substances leads to the
death of fish, molluscs and seaweed [6].
It is known that during the remediation of oil-contaminated soils and sea waters, biological products both
including monocultures and based on associations of microorganisms are used. Activity of microorganisms
is one of the main factors contributing to the natural cleaning of the soil and water bodies. Although ability
of microorganisms to degrade various pollutants, including hydrocarbons - the main components of oil has
been known for a long time, currently it is being intensively studied. The processes of biological
remediation of natural ecosystems have received great attention. Bioremediation provides cost-effective,
highly specific and environmentally friendly cleaning, which leads to a decrease in the concentration of
petroleum products. However, as a rule, certain types of microorganisms capable of decomposing many
components of oil are rarely found. To increase the efficiency of cleaning oil-contaminated a constant study
of the properties of oil destructive microorganisms is carried out [1–4].
DATA AND METHODS The purpose of this work was searching for active strains of microorganisms - oil destructors capable of
intensifying the processes of cleaning sea water from oil pollution, as well as studying their hydrocarbon-
oxidizing ability.
The research objects were samples of sea water from the Baku Bay coastal zone, in particular near the Bibi-
Eybat field. The total number of microorganisms in sea water was determined by the limiting dilutions
method with seeding on agar media. The quantitative analysis of microorganisms was carried out: bacteria
(54.105 cells /ml), mold fungi (52.102 cells / ml) and yeast (38.102 cells / ml)
The selection of microorganisms began with obtaining accumulating or accumulated cultures in which there
was overwhelming quantity of the forms of interest. Pure cultures were obtained by successive re-sowing
accumulating cultures from Mills mineral medium (MMC) with addition of oil on agar nutrient mediums
(meat peptone agar (MPA), Mills and Chapek) with oil and oil products [5].
APPLICATION AND RESULTS The oil-degrading activity of the studied microorganisms was evaluated by the total indicator of the loss of
oil in a liquid medium determined in according to the gravimetric method. Selective screening of individual
hydrocarbon-oxidizing microorganisms was realized (the degree of oil destruction is 60-80%).
Table 1. Determination of hydrocarbon activity of the selected crops
Number of
microbial
cultures
pH of the medium Quantity of
biomass
(mg)
Quantity of
residual oil
(mg)
Oil destruction
percentage (%) Before the
experiment
After the
experiment
1К 7,0 7,2 413 19 81
2К 7,0 7,2 252 22 78
3К 7,0 6,5 170 32 68
4К 7,0 7,0 370 20 80
5К 7,0 6.0 130 43 57
6К 7,0 6,0 144 47 53
7К 7,0 7,8 320 27 73
8К 7,0 7,0 110 49 51
9К 7,0 6,0 127 64 36
10К 7,0 6,0 130 67 33
The optimal compositions of nutrient mediums for maximum activation of selected microorganisms were
developed.
CONCLUSIONS AND RECOMMENDATIONS Thus the obtained experimental data allow us to recommend the selected active cultures for further
introducing them into the composition of the developed microbial biopreparation.
REFERENCES Вельков В. В. Биоремедиация: принципы, проблемы, подходы // Биотехнология. 1995. №3. C. 20–
27.
Гольдберг В. М., Зверев В. П., Арбузов А. И. Техногенное загрязнение природных вод
углеводородами.
Колесниченко А. В. Марченко А. И., Побежимова Т. П., Зыкова В. В. Процессы биодеградации в
нефтезагрязненных почвах. Москва, Промэкобезопасность, 2004. 194 с.
Коронелли Т. В. Принципы и методы интенсификации биологического разрушения углеводородов
в окружающей среде (обзор) // Прикладная биохимия и микробиология. 1996. Т. 32. №6. C. 579–585.
Куликова И. Ю., Дзержинская И. С. Использование микробиологического метода для очистки
нефтезагрязненной морской воды // Вестник АГТУ 2007. № 4 (39),с.128
Мамедова П.Ш.. Бабаев Э.Р., Султанова С.А., Кахраманова К.З., Ибрагимова Т.М., Насибова Г.Р.
Биоочистка нефтяного загрязнения в морских водах. Материалы конференции «Институт химии
присадок-50» ,с.110
AIR POLLUTION AND INVERSION FEATURES IN
ERZURUM, TURKEY
Orhan Sen1, Esra Kesaf2, Merve Yilmaz2, Evren Ozgur2,3
1 Istanbul Technical University, Faculty of Aeronautics and Astronautics,
Department of Meteorological Engineering, Maslak, Istanbul, Turkey, [email protected] 2 Istanbul Technical University, Graduate School of Science Engineering and Technology, Maslak, Istanbul, Turkey.
3Istanbul Medeniyet University, Faculty of Engineering and Natural Sciences, Department of Civil Engineering,
Usküdar, Istanbul, Turkey, [email protected]
Abstract
Erzurum is located in a plateau that is surrounded by mountains from the eastern, southern and northern
parts. The height of this plateau is around 2000 m above sea level. This topographic structure and low
temperature cause an almost constant inversion layer over the city in winter. The altitude of Erzurum is
1950 m asl and the city is one of the coldest settlement centers of Turkey. Erzurum city is found among the
most affected cities from an air pollution point of view whether climate properties or settlement style.
Particularly in winter, an intense air pollution is noticed in the city because topographical properties of the
city. This study is conducted to determine the variation of PM10 and NOX concentrations in three towns of
Erzurum in the period of April 2016 – March 2018. One of these two towns is Taşhan that is a town in the
city and directly exposed to vehicle and domestic heating pollution. The other town is Palandöken that is
also one of the most important ski resorts in Turkey. Palandöken Mountain is a 3.271 m high tectonic
mountain in Erzurum Province, Turkey. The summit of the mountain is only 10 km away from Erzurum
city center. Aziziye is one of the biggest towns in Erzurum as its 300 000 km2 area. In this town, there are
geothermal sources which are important for winter tourism. Aziziye is on Erzurum plain and 14 km distance
from the city center. Average pollutant concentrations for all three towns are considered in this study. The
concentration of pollutants is determined in a seasonal period. Pollutant concentrations and inversion case
and noninversion case are observed. The intensity of inversion is also determined. A parameter is obtained
for all inversion intense conditions. It is used to determine the relationship between pollutant concentrations
and inversion intense in the observation period for two towns. Therefore, the comparison of pollutant
concentrations is obtained for three towns either there is inversion or not.
Keywords: Inversion, PM10, NOx, Erzurum, Turkey
INTRODUCTION
There is huge opinion and consensus in the world that the local concentration of air pollutants is effective
while the formation of the city. Erzurum, where is one of the highest and the coldest city of Turkey, has a
severe continental climate. Climate conditions usually last as freezing cold and snowy in winters and hot
and dry in summers. For this reason, air pollution originated from heating reaches high values during
the winter months in Erzurum by the effects of city topography with bowl-shaped, irregular urbanization
and meteorological factors (Torun, F. E. and Bingül, Z., 2015).
The topographical structure and the geological position of Erzurum cause the formation of a dry climate
around the region (Figure1). With the lowest average annual temperature in Turkey, Erzurum has long and
severe winters. On the other hand, summers of the city are short and dry. The winter period in the city is
usually longer than six months. In 1950-2016 period, average yearly temperature was 5.6°C in the city. The
maximum and minimum temperatures was measured as 35.6 °C and -37.2 °C, respectively. Yearly total
precipitation was 403.3 mm and average relative humidity was 66.29%. Maximum precipitation occurs in
May, seasonally first days in spring and summer and last days in fall. Snow in land may be seen from
October to May (Toy and Eymirli, 2018). These parameters show that the city is in the class of Dfc
according to Köppen. Precipitation type is generally snow in winters, in the first days of spring and in the
last days of fall (Toy et al., 2016).
Erzurum Airport is based on the minimum elevation of Erzurum Plateau. The plateau has been opened to
orographic heating and cooling with mountain sides in the near environment in winter and summer. After
this heating and cooling especially heavy and cold air parcels collapse as being cold air cone (Toy and
Eymirli, 2018) (Figure 2). Temperatures start falling in October and rise again in April. The average annual
rainfall of 460.5 mm in the province of Basra and the cyclone is usually under the influence of the Siberian
anticyclone. Snowfall starts by October and continues until May.
Erzurum is come up against significant air pollution problem especially in winters. The severity of the
problem increases during winter season due to heating activities. The other factors that are efficient in
pollution are the topographic structure of the city, unplanned urbanization and meteorological factors.
(Turan T. and Çelik, B.Y.). Aziziye and Palandöken towns are two metropole urbanizations in Erzurum.
Aziziye town is 1750 m and Palandöken town is 2100 m height. From eastern to western sides, elevation
values are generally decrease such as from Palandöken to Aziziye.
One of the most important air pollution sources in Erzurum is fossil fuels that are used in winter. Even
natural gas is started to use, topographical effects dominate air quality in the city. Thus, inversion features
affect Erzurum air quality especially in winter period. Some industrial plants are located near to Aziziye
and they are very efficient in air pollution in the town (Altaş, N.T., 2013).
Figure 1. Erzurum Topography
airport
TASHAN
Mountain
PALANDÖKEN
Figure 2. Collapsing effect in the area in winter (Toy and Eymirli, 2018)
Erzurum is in a vast plain and there are lots of mountains around the city. The colder air that collapsed in
that case makes a heavy fog layer by evaporating on the open surface of Karasu River or from the watery
areas (Toy and Eymirli, 2018). A map of Erzurum and Karasu River can be seen in Figure 3 given below.
Figure 3. Karasu River and Erzurum (Polat, Güney, 2018.)
DATA AND METHODOLOGY
The data used in this study is collected by the website of T.C. Ministry of Environment and Urbanization
which has the name of “Monitoring of Air Quality”. PM10, NOX values for Palandöken, Taşhan and Aziziye
stations are used. The data that the days which have inversion or not was obtained from Turkish State of
Meteorological Service (MGM).
For inversion intense, a criteria is maintained to calculate the pollutant amount in a formula such as
inversion end point temperature – inversion start point temperature over inversion thickness. From the day
of April the 1st of 2016 to March the 31th of 2018, all four seasons are observed. Average concentration of
pollutants is plotted for the days of inversion days and noninversion. In this study, inversion times are
observed for daily and nightly. The aim of the study is to understand the relationship between pollutant
concentrations and inversion.
APPLICATION AND RESULTS
Figure 4 and 5 shows PM10 and NOX concentrations for three towns for 00.00 and 12.00Z in both case of
inversion and no inversion in the period of 2016-2018.
airport
Inversion layer
Figure 4. PM10 and NOX Concentrations at 00:00 in four seasons between 2016-2018
Figure 5. PM10 and NOX Concentrations at 12:00 in four seasons between 2016-2018
Especially in winter season, air pollution is increasing by using fuels. The tables and graphs are obtained
to observe the relationship between PM10 and NOx concentrations (µg/m3) and inversion parameter in
three towns.
This parameter is obtained such as:
𝑖𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑖𝑛𝑡𝑒𝑛𝑠𝑒 𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟
𝑖𝑖𝑝 = 𝑖𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑐𝑒𝑖𝑙 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒−𝑖𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑏𝑎𝑠𝑒 𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒
𝑖𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑐𝑒𝑖𝑙 ℎ𝑒𝑖𝑔ℎ𝑡−𝑖𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝑏𝑎𝑠𝑒 ℎ𝑒𝑖𝑔ℎ𝑡∗ 1000 in (K/m)
It is also observed the days of inversion intense such as between 0-49 and over 50. The graphs are also
obtained to see the relationship of inversion between air pollution and seasons. Average pollutant
concentrations are obtained such as spring, summer, fall and winter months in 2016-2018 for three towns.
Table 1 shows the average pollutant concentrations in 2016-2018 period for three towns.
Table 1a. Average Pollutant Concentrations in 2016-2018
TAŞHAN
0.00 12.00
INVERSION NO INVERSION INVERSION NO INVERSION
PM10 NOX PM10 NOX PM10 NOX PM10 NOX
SPRING 48.27 71.13 57.91 68.48 60.75 97.45 71.23 102.40
SUMMER 47.46 57.88 46.78 60.35 47.30 82.19 51.76 84.29
AUTUMN 69.89 108.80 55.08 83.82 75.56 128.88 86.90 146.25
WINTER 132.94 223.21 92.08 159.21 174.25 250.27 124.32 212.17
PALANDÖKEN
SPRING 14.52 12.41 26.06 14.13 22.06 11.81 23.90 13.54
SUMMER 22.65 10.33 28.69 9.43 23.61 10.81 36.13 9.24
AUTUMN 21.31 11.96 21.21 10.65 25.19 13.36 32.50 15.15
WINTER 16.91 27.32 18.14 26.88 34.83 54.86 24.46 32.68
AZİZİYE
SPRING 38.58 31.91 47.28 30.51 61.85 42.11 67.04 39.39
SUMMER 31.69 24.79 33.15 23.17 52.72 33.14 46.82 31.66
AUTUMN 77.52 52.49 59.84 39.37 88.19 60.45 102.49 65.34
WINTER 115.99 126.68 75.76 84.06 129.69 120.17 90.91 94.64
Table 1b. Average Pollutant Concentrations in 2016-2018
PM10 PM10 PM10 NOX NOX NOX
SPRING 48.27 14.52 38.58 71.13 12.41 31.91
SUMMER 47.46 22.65 31.69 57.88 10.33 24.79 INV_00
FALL 69.89 21.31 77.52 108.80 11.96 52.49
WINTER 132.94 16.91 115.99 223.21 27.32 126.68
T P A T P A
PM10 PM10 PM10 NOX NOX NOX
SPRING 57.91 26.06 47.28 68.48 14.13 30.51
SUMMER 46.78 28.69 33.15 60.35 9.43 23.17 0.00
FALL 55.08 21.21 59.84 83.82 10.65 39.37
WINTER 92.08 18.14 75.76 159.21 26.88 84.06
T P A T P A
PM10 PM10 PM10 NOX NOX NOX
SPRING 60.75 22.06 61.85 97.45 11.81 42.11
SUMMER 47.30 23.61 52.72 82.19 10.81 33.14 INV_12
FALL 75.56 25.19 88.19 128.88 13.36 60.45
WINTER 174.25 34.83 129.69 250.27 54.86 120.17
T P A T P A
PM10 PM10 PM10 NOX NOX NOX
SPRING 71.23 23.90 67.04 102.40 13.54 39.39
SUMMER 51.76 36.13 46.82 84.29 9.24 31.66 12.00
FALL 86.90 32.50 102.49 146.25 15.15 65.34
WINTER 124.32 24.46 90.91 212.17 32.68 94.64
T P A T P A
(T=Taşhan, P=Palandöken, A=Aziziye; inversion and no inversion at 00:00 and 12:00)
Figure 6 shows the average PM10 and NOX concentrations in seasonal basis at 00.00 and 12.00. It can be
seen in the figure that Taşhan NOX values are the biggest concentration values for all seasons for both
00.00Z and 12.00Z.
Figure 6. Average PM10 and NOX Concentrations in 2016-2018
Figure 7-10 show the PM10 and NOX concentrations with inversion intense for each season. It is clearly
said that Taşhan concentration values are the biggest values except fall season. On the other hand,
Palandöken concentration values are the smallest values for all period and time basis.
Figure 7. PM10 and NOX Concentrations in Spring in 2016-2018 with Inversion Intense
Figure 8. PM10 and NOX Concentrations in Summer in 2016-2018 with Inversion Intense
Figure 9. PM10 and NOX Concentrations in Fall in 2016-2018 with Inversion Intense
Figure 10. PM10 and NOX Concentrations in Winter in 2016-2018 with Inversion Intense
Table 2 shows the values of pollutant concentrations in a simple table. It can be easily said the same findings
as figure above.
Table 2. Average Pollutant Concentrations in four seasons in 2016-2018 with Inversion Intense
PM10_00.00
SPRING SUMMER FALL WINTER
0-49 54.05 51.59 70.37 130.43 TASHAN
0-49 13.56 26.16 19.37 14.31 PALANDOKEN
0-49 43.41 32.75 76.46 113.78 AZIZIYE
50- 42.60 41.33 61.33 82.67 TASHAN
50- 12.10 17.00 11.00 3.00 PALANDOKEN
50- 33.15 35.58 57.83 88.00 AZIZIYE
PM10_12.00
SPRING SUMMER FALL WINTER
0-49 64.04 47.42 73.56 165.07 TASHAN
0-49 19.67 25.46 24.38 32.36 PALANDOKEN
0-49 62.34 49.78 83.75 121.95 AZIZIYE
50- 71.00 58.50 82.04 35.00 TASHAN
50- 17.50 25.50 20.33 - PALANDOKEN
50- 34.50 - 99.00 33.00 AZIZIYE
NOX_00.00
SPRING SUMMER FALL WINTER
0-49 79.19 65.35 108.55 221.15 TASHAN
0-49 8.87 9.99 12.03 23.28 PALANDOKEN
0-49 35.39 28.16 53.75 121.63 AZIZIYE
50- 65.81 45.25 90.44 156.00 TASHAN
50- 15.50 5.06 7.17 16.00 PALANDOKEN
50- 29.83 42.53 47.11 124.50 AZIZIYE
NOX_12.00
SPRING SUMMER FALL WINTER
0-49 100.63 85.82 132.88 239.05 TASHAN
0-49 12.29 10.69 12.08 46.63 PALANDOKEN
0-49 47.18 30.68 64.39 108.71 AZIZIYE
50- 100.00 61.50 129.50 57.00 TASHAN
50- 9.00 8.50 20.00 - PALANDOKEN
50- 34.00 50.50 62.71 18.00 AZIZIYE
Figure 11 shows PM10 and NOX concentrations for three towns in the same figure. Both concentrations
have the highest values in winter season for all three towns. There are not critical differences of
concentration values between 00.00Z and 12.00Z.
Figure 11. PM10 and NOX Concentrations in 2016-2018 with Inversion Intense
CONCLUSION
The amount of pollution in terms of PM10 and NOx in Tashan is 4-5 times higher than in Palandöken and
Aziziye in winter. In the summer months, the difference is 1.5 to 2 times smaller. This is due to the pollutant
source in the winter heating of the accommodation. The lack of complete combustion due to oxygen
deficiency increases the number of contaminants. The height and intensity of the Inversion are effective in
the difference of pollutant concentrations between day and night. The inversion in Taşhan and Aziziye and
lack of inversion in Palandöken due to altitude prevent the transport of pollutants from the city.
REFERENCES
1. Altaş, N. T., 2015. Coğrafi Çevre Unsurlarıyla Şehirleşme Etkileşimi Bakımından Erzurum Şehri.
Atatürk Üniversitesi Bilimsel Araştırma Projeleri, No:2013/164. (in Turkish)
2. Dursun. D., Yavas, M., 2015. Air Quality in the City of Erzurum: Strategies for Climate Sensitive
Urban Design. ICUC9 - 9th International Conference on Urban Climate jointly with 12th Symposium
on the Urban Environment, Toulouse, France.
3. Karaca. A., Şenol. A., Denizli. F., Çiçek. M., Derman, Y., 2013. Erzurum Hava Kalitesi
Değerlendirme Raporu. Erzurum, Turkey. (in Turkish)
4. Kopar İ., Zengin M., 2009. Determination of Temporal and Spatial Distribution of Air Quality in
Erzurum City Depending on Geographic Factors. Türk Coğrafya Dergisi, 53, 51-68. (in Turkish)
5. Öz, Sezen I., Yilmaz, S., 2006. The Situation of Air Pollution in Erzurum City-Centre Between the
Years 1994-2004, Journal of the Faculty of Agriculture, 37(2), 217-224. (in Turkish)
67
6. Polat, S., Güney, Y., 2018. Salty-Brackish Water Spring and Salt Pans in Upper Basin of the Karasu
River (Western Euphrates), Gaziantep University Journal of Social Sciences, 17 (3), 774-795. (in
Turkish)
7. Sağol, S., Bingül, Z. Demircioğlu, N., 2008. Erzurum İli Hava Kirleticilerinin 1996-2008 Yıllarındaki
Değişimlerinin İncelenmesi. National Symposium of Air Pollution and Control, Hatay, Turkey. (in
Turkish)
8. Topçu, N., Keskinler, B., Bayramoğlu, M. Akçay, M., 1993. Air Pollution Modelling in Erzurum City,
Environmental Pollution, 79(1), 9-13.
9. Torun, F. E., Bingül, Z., 2015. Air pollution problem in Erzurum city during 2014-2015. 2nd
International Conference on Sustainable Agriculture and Environment, Konya, Turkey.
10. Toy, S., Eymirli, E. B., 2018. Evaluation of the Effects of Meteorological Events on Flights, Example
of Erzurum, International Airport. International Geography Symposium on the 30th Anniversary of
TUCAUM, Ankara, Turkey.
11. Turan, T. Yalçın Çelik B., 2012. The Change of Air Pollution in Erzurum City, Research Journal of
Biological Sciences, 5(1), 65-68. (in Turkish)
12. Turkish State Meteorological Service, Ulusal Hava Kalitesi İzleme Web Sitesi
13. http://www.mynet.com/haber/guncel/erzurum-tasit-sayisinda-yuzde-45lik-artis-3681922-1
68
METEOROLOGICAL ANALYSIS OF WINTER SPORTS IN VARIOUS
PLACES IN TURKEY
Onur UYSAL, Elcin TAN, Zeynep F. UNAL, Orhan SEN
Istanbul Technical University, Faculty of Aeronoutics and Astronaoutics, Department of Meteorological Engineering,
Istanbul, Turkey.
Abstract
The purpose of this project is analyzation of four different cities of Turkey for winter sports eligibility by
Physiologically Equivalent Temperature, Modified Physiologically Equivalent Temperature, Perceived
Temperature with RAYMAN 2017 software. To obtain RAYMAN outputs, some meteorological characteristics
of each regions data were used such as wind speed, air temperature, cloudiness, relative humidity and altitude as
well. The first phase of the project involves familiarization of each region by geographic and topographic
characteristics. After that phase, there are calculations, meteorological approaches, and presentation of each region
values also included. The final phase involves the results and comparison. By analyzing of cities for winter sports,
the most comfortable skiing area is found with the Physiologically Equivalent Temperature (PET), Perceived
Temperature (PT), and modified Physiologically Equivalent Temperature mPET scales. For analyzing, sample
human conditions are rearranged and used.
Keywords: PET, Winter Sport
INTRODUCTION
Winter sports events are always desired by many nations to host because this events may brought many benefits
to their nations such as inreasing their popularity on world-wide or contributing financially to their government
and particular regions as well. Therefore, one of the most concerns about this event is comfort of visitors and
participators that join the events for many reasons like proffesional sports, tourism or occupation. Even though the
largest international sport events have long been organized in summer months, some of them must be performed
in winter such as Winter Olympics or Winter Games. Because of that situation, ambient air and climate of Winter
Sports’ areas must be comfortable for each type of visitors. The significant weather events are always the most
important issue of these events. In the past significant weather events have affected nearly all of winter sports.
Unfortunately, several of this weather events have affected those events adversely by negative outdoor conditions
such as inadequate snow or severe weather events as heavy snowfall, strong winds or low visibility. This issue can
affect health, transportation, accommodation etc. with many reasons. When all these conditions are taken into
consideration, meteorological effects on visitors must be analyzed during and before games. Turkey is a country
which is candidate for hosting for winter sports such as Winter Olympics and Winter Games before and some
international winter sports events has been organized in the meantime. Although, north eastern region of Turkey
has hosted winter events, further areas are suitable for winter events such as Sarıkamış, Ilgaz, Kartalkaya or Erciyes
in account of psychological aspect of meteorology and they may be made eligible for International winter sports
standards. To achieve, obtaining of psychological effects of meteorological events on winter sports visitors, once
Physiologically Equivalent Temperature (PET) and Perceived Temperature (PT) must be analyzed for each area.
In this project, PET, mPET (modified Physiologically Equivalent Temperature) and PT values are analyzed for
Sarıkamış, Ilgaz, Kartalkaya and Erciyes separately and compared all of them with each other by winter sports
comfort. The analyze areas, wind speed, air temperature, relative humidity and cloudiness indexes are obtained
from National Meteorology Office (MGM) and used for each areas.
STATEMENT OF CHOSEN AREAS
KARS The city of Kars is located in the eastern Anatolia geographical region of Turkey (40°37′N 43°6′E) and at an
elevation of 1,768 m (5,801 ft). The city harbors a worldwide – famous ski center Sarıkamış – Cıbıltepe.
Population of the city center is about 114.694 while that of the whole province is 287.654 according to Turkish
State Statistics Institution in 2017 (Figure 1).
69
Figure 1. City of Kars filled with red in Turkey map
SARIKAMIŞ Sarıkamış is a town and a district of Kars Province in the Eastern Anatolia region of Turkey. Its population was
17,860 in 2010. The town sits in a valley and is surrounded by mountains, many of which are covered with pine
forests. It has a subalpine climate, with average of 7–8 ft/2.1m-2.4m of snowfall; it has very long winters and
short, dry summers. In recent years Sarıkamış has developed as a winter skiing resort, with one of the world's
longest tracks (Figure 2).
Sarıkamış district occupies an area of 1732 km2. Its average altitude is 1500-2200m and other important mountains
in Kars are Süphan, Balıklı (2835m), Kösedağı (2599 m), Çıplakdağ (2634 m) and Soğanlı (2849 m). Bayraktepe
(Cıbıltepe) skiing center is located at a 2 km distance from the Sarıkamış district of Kars province. Main
accommodation facilities and central mechanical facilities of the skiing center built in Bayraktepe, altitude of
which is 2634 m, are located at an altitude of 2150 m. Covered with pure Scotch pine vegetation, the center has 7
ski-slopes for alpine skiing activities and 1 ski-slopes for cross-country skiing activities, with various gradients.
As an appropriate spot for numerous winter tourism activities, the weather conditions at the center are in a suitable
condition to perform such activities during approximately four-month period between the months of December
and March of the year. There are no natural risks like avalanche and landslide due to the climatic and
morphological conditions of the center. Accommodation facilities with a wide range of means are available at the
center, which draws more and more attention day by day thanks to tourism and sports activities.
Figure 2. Sarıkamış ski plan http://www.deretepe.net/faydali-bilgiler/turkiye-kayak-merkezleri-ve-pist-
haritalari/
KAYSERİ The city of Kayseri is located in the middle of Anatolia geographical region of Turkey (38°43′N 35°28′E) and at
an elevation 1,057 m (3,467 ft) (http://www.mta.gov.tr/). The city harbors a famous ski center as well as Sarıkamış,
70
it is referred to by the same name with the Mountain Erciyes (Figure 3). Population of the city center is about
562,598 while that of the whole province is 1,376,722 according to Turkish State Statistics Institution (2017).
Figure 3. City of Kayseri filled with red in Turkey map
ERCİYES Erciyes (38°35′N 35°27′E) is a mountain and a district of Kayseri province. The elevation of Erciyes is 3,917
meters at the highest summit and named The Grand Erciyes. It is also an extinct volcano. The second highest
summit is named Safrakaya Summit which has elevation of 2700 meters. The northern slope of Erciyes Mountain
there are several volcanic summits that ranging from 2200 meters to 2700 meters height. Erciyes is the third highest
mountain of Turkey. In Erciyes, there is an International Winter Sports Center with extremely favorable runways
for skiing and mountaineering. Meanwhile, roads are always kept available for transportation as well as 24-hour
facility. Ali Mountain (1841m.) and Yılanlı Mountain (1640m.) are also volcanic mountains where the southern
side of Erciyes.
Figure 4. Erciyes skii area plan http://sarikamisdagas.org/index.php/pistlerimiz/
BOLU The city of Bolu is located in the middle of Anatolia geographical region of Turkey (40°73’N 31°60′E) and at an
elevation 726 m (2,381 ft). The city harbors a famous ski center named Kartalkaya. Population of the city center
is about 177,855 while that of the whole province is 303,184 in 8,341 km2 area according to Turkish State Statistics
Institution (2017) (http://www.mta.gov.tr/).
71
Figure 5. City of Bolu filled with red in Turkey map
KARTALKAYA
Kartalkaya (40°73′N 31°61′E) is a famous ski center and a district of Bolu Province. Kartalkaya is located in the
eastern side of The Köroğlu Mountain. The highest elevation of Köroğlu Mountain is 2499m and the summit of
Kartalkaya is 2200m and the whole mountain is surrounded by pine trees. Ski season of Kartalkaya is mostly
between December and April months and population of Kartalkaya can reach 880.000 during these seasons.
Figure 6. Kartalkaya skii plan http://www.tkf.org.tr/tr/kayak-merkezleri/kartalkaya
Köroğlu Mountain is actually a mountain chain. The distance between of east side to west side is around 400 km.
and Kartalkaya is the nearst place to the highest summit of this mountain chain. Özbek, Yıldırım, Işık and Semen
Mountains are the other summits of Köroğlu Mountain Chain.
KASTAMONU The city of Kastamonu is located in the middle of Black Sea geographical region of Turkey (41°22’N 36°46′E)
and at an elevation 784 m (2,572 ft). The city harbors a famous ski center, it is referred to by the same name with
the Mountain as well as Erciyes, named Ilgaz. Population of the city center is about 10,368 while that of the whole
72
province is 128,357 in 13,064 km2 area according to Turkish State Statistics Institution (2017). Ilgaz Mountain is
the famous geographical place of Kastamonu.
Figure 7. City of Kastamonu filled with red in Turkey map
ILGAZ Ilgaz Mountain is the highest chain mountain of Black Sea Region. The highest summit of Ilgaz is Büyükhacet
(2587m.) and the second one is Küçükhacet (2546m.). The upper elevation limit of forrest is 2200m which mostly
includes blackpines. The Winter Sports Facility of Ilgaz is located in Ilgaz National Park where the southern side
of Ilgaz Mountain. (41°07′N 33°72′E)
Figure 8. Ilgaz skii plan http://www.deretepe.net/faydali-bilgiler/turkiye-kayak-merkezleri-ve-pist-
haritalari/
METHODOLOGY AND DATA In order to calculate human thermal comfort conditions in the study, among the most widely employed indices,
Physiologically Equivalent Temperature (PET), Modified Physiologically Equivalent Temperature (mPET) and
Perceived Temperature (PT) indexes were used, which are based on the idea of balancing indoor and outdoor air
temperature considering an energy balance of human body at the same core and skin temperatures (Höppe 1999;
Mayer and Höppe 1987; Matzarakis et al. 1999) and the mean radiant temperature (Tmrt). Calculated temperatures
are in Celsius unit. RayMan software (Matzarakis et al., 2007, 2010) was used to calculate PET, mPET and PT
values considering monthly mean data – air temperature (Ta; in degrees Celsius), relative humidity (RH; %),
cloudiness (CA; in octas), wind speed (WS; in meters per second) measured at those skiing areas.
PET values are obtained through the model as single temperature values in Celsius according to standardized
European man (gender), who is 1.75 m (height), 75 kg (weight), at 35 years old, in work suit (clothing 1.0 clo) and
working in office (activity 80 w) and position standing (Höppe 1999; Mayer and Höppe 1987) and categorized
according to Pet & mPET and PT Index Tables (Table 1-2).
73
Table 1. Thermal sensation classes for human beings, modified after Matzarakis and Mayer (1996).
Table 2. The thermo-physiological meaning of PT results for central Europe as defined by VDI (2008),
Staiger et al. (2012)
Physiologically Equivalent Temperature Physiologically Equivalent Temperature (PET) is the most commonly used index for analyze human thermal
comfort in indoor environments and based on "Munich Energy Balance Model for Individuals" (MEMI, Höppe
1984). Therefore, calculation of this index does less affected by wind speed and solar radiation than mPET and
PT (Mayer and Höppe 1987, Höppe 1999, Matzarakis et al. 1999). In this case, PET values are actually used for
indoor winter activities for sample human.
Modified Physiologically Equivalent Temperature The difference between PET and mPET is, mPET is more sensitive to wind speed, solar radiation values and clo
setting. Skin temperature, clothing temperature and evaporative heat transfer can be added in mPET results. In this
case, mPET results are actually more accurate than PET, because clo setting is much valuable for on this case in
order to analyze the comfort of professional sportsmen and tourists (Chen, Matzarakis 2014).
Perceived Temperature The basic definition Perceived Temperature (PT) is actual sensible air temperature in environment that based on
"Klima-Michel-Model" (Jendritzky et al. 1990), calculated for people actually living outside. In this case, PT
values gives us the sensible outside temperature for winter sportsmen and winter touristes in particular. Besides,
PT values are more accurate for standing (walking speed < 4km/h) at outside 1.0 clo sample human.
DATA For this case, analyzation of skiing areas is calculated with measured datasets which are taken from National
Meteorological Office (MGM). Especially, monthly mean temperature in Celcius (Ta; Co), monthly mean relative
humidity (RH; %), monthly mean cloudiness (CA; in octas), monthly mean wind speed (WS; in meters per second)
are used. Data interval was between 2009 and 2017.
74
CALCULATIONS
Figure 9. RAYMAN 2017 UI & Location Section
Table 3. RAYMAN 2017 output values for Erciyes
Table 4. RAYMAN 2017 output values for Kartalkaya
Table 5. RAYMAN 2017 output values for Ilgaz
Enum. Latit. Long. Altit. A Ta RH v C height weight age sex cloth. activ. PET PT mPET
/tag °N °E m W/m² °C % m/s octas m kg a clo W °C °C °C
1 38.35 35.27 3000 207.1 -4.9 69.3 8.8 3.4 1.8 80 35 m 1 80 -12.6 -15.6 -11.2
2 38.35 35.27 3000 215.7 -3.1 68.6 7.6 3.4 1.8 80 35 m 1 80 -10.7 -13.1 -8.8
3 38.35 35.27 3000 225.5 -1.4 68.1 8.3 3.5 1.8 80 35 m 1 80 -9.1 -11 -7.4
4 38.35 35.27 3000 250.3 3.4 63.8 7.8 3.4 1.8 80 35 m 1 80 -4.4 -4.6 -2.4
5 38.35 35.27 3000 274.9 7.9 65.3 7 2.9 1.8 80 35 m 1 80 0 1.4 1.1
6 38.35 35.27 3000 291.8 11.3 64.1 6.4 2 1.8 80 35 m 1 80 3.3 4.6 4.5
7 38.35 35.27 3000 303.7 14.6 50.5 6.5 1.3 1.8 80 35 m 1 80 6.5 7.2 7
8 38.35 35.27 3000 311.9 16 50.1 5.4 1.2 1.8 80 35 m 1 80 7.9 8.4 8.2
9 38.35 35.27 3000 289 12 51.1 5.5 1.7 1.8 80 35 m 1 80 4.1 5 5.3
10 38.35 35.27 3000 260.6 5.8 62.2 5.9 2.7 1.8 80 35 m 1 80 -1.8 -1.2 0.8
11 38.35 35.27 3000 237.4 1.5 66 5.7 2.6 1.8 80 35 m 1 80 -5.8 -6.7 -3.2
12 38.35 35.27 3000 214 -3.2 65.2 6.8 3.3 1.8 80 35 m 1 80 -10.6 -13 -8.4
Enum. Latit. Long. Altit. A Ta RH v C height weight age sex cloth. activ. PET PT mPET
/tag °N °E m W/m² °C % m/s octas m kg a clo W °C °C °C
1 40.73 31.62 3100 221.8 -5.2 86 4.4 5.3 1.8 80 35 m 1 80 -11.7 -14.5 -8.4
2 40.73 31.62 3100 231.8 -2.5 80.1 4.7 5 1.8 80 35 m 1 80 -9.4 -11.4 -6.2
3 40.73 31.62 3100 237.6 -1.1 76.4 4.7 4.8 1.8 80 35 m 1 80 -8 -9.6 -4.9
4 40.73 31.62 3100 250.9 2.3 71.4 4.2 4.1 1.8 80 35 m 1 80 -4.7 -5.2 -1.4
5 40.73 31.62 3100 277.1 6.4 76 3.9 4.1 1.8 80 35 m 1 80 -0.8 0.2 2.5
6 40.73 31.62 3100 297.4 10.4 78.6 3.1 3.4 1.8 80 35 m 1 80 3 4.4 5.4
7 40.73 31.62 3100 312.6 14.3 70.4 2.9 2.4 1.8 80 35 m 1 80 6.5 7.4 8.3
8 40.73 31.62 3100 313.5 14.3 73.8 2.8 2.3 1.8 80 35 m 1 80 6.6 7.5 8.4
9 40.73 31.62 3100 292.7 10.7 64.9 3.2 3.1 1.8 80 35 m 1 80 3.3 4.4 5.4
10 40.73 31.62 3100 270.2 5.6 72.6 3.6 4.1 1.8 80 35 m 1 80 -1.5 -0.9 1.9
11 40.73 31.62 3100 246.5 1.8 72.4 4.5 3.8 1.8 80 35 m 1 80 -5.2 -5.9 -2.1
12 40.73 31.62 3100 225.9 -2.9 75.8 4.2 4.6 1.8 80 35 m 1 80 -9.5 -11.6 -6.2
Enum. Latit. Long. Altit. A Ta RH v C height weight age sex cloth. activ. PET PT mPET
/tag °N °E m W/m² °C % m/s octas m kg a clo W °C °C °C
1 41.07 33.72 2010 232.8 -0.9 83 1.4 3.3 1.8 80 35 m 1 80 -5.6 -6.8 -1
2 41.07 33.72 2010 246.7 2.1 75.6 1.6 3.2 1.8 80 35 m 1 80 -3.4 -3.8 0.9
3 41.07 33.72 2010 259.2 5 68.2 1.8 2.9 1.8 80 35 m 1 80 -1.1 -0.8 2.9
4 41.07 33.72 2010 287.5 9.9 62.9 1.9 3.2 1.8 80 35 m 1 80 3 4.4 5.6
5 41.07 33.72 2010 314.9 14.3 67.2 1.6 3.2 1.8 80 35 m 1 80 6.8 7.5 8.8
6 41.07 33.72 2010 333.5 18.1 66.4 1.6 2.5 1.8 80 35 m 1 80 10 10.5 11.1
7 41.07 33.72 2010 348.9 21.8 56.4 1.7 1.8 1.8 80 35 m 1 80 12.9 13 13.5
8 41.07 33.72 2010 348.5 21.7 54.7 1.7 1.9 1.8 80 35 m 1 80 12.8 12.9 13.4
9 41.07 33.72 2010 327.8 17.6 57.2 1.5 2.5 1.8 80 35 m 1 80 9.5 9.9 10.5
10 41.07 33.72 2010 296.3 11.3 69.4 1.5 2.8 1.8 80 35 m 1 80 4.4 5.2 7
11 41.07 33.72 2010 262.2 5.4 73.6 1.3 2.4 1.8 80 35 m 1 80 -0.4 0.2 3.8
12 41.07 33.72 2010 243.6 1.2 82.1 1.4 3.1 1.8 80 35 m 1 80 -3.8 -4.4 0.7
Figure 10. RAYMAN 2017 modified “locations.txt” file
75
Table 6. RAYMAN 2017 output values for Sarıkamış
Table 7. RAYMAN 2017 PET, PT and mPET monthly distributed values for Erciyes
Table 8. RAYMAN 2017 PET, PT and mPET monthly distributed values for Kartalkaya
Table 9. RAYMAN 2017 PET, PT and mPET monthly distributed values for Ilgaz
Enum. Latit. Long. Altit. A Ta RH v C height weight age sex cloth. activ. PET PT mPET
/tag °N °E m W/m² °C % m/s octas m kg a clo W °C °C °C
1 40.32 42.62 2138 197.4 -7.1 75.2 1.5 3.2 1.8 80 35 m 1 80 -11 -14 -6.1
2 40.32 42.62 2138 204.8 -5.8 75.6 1.5 3.4 1.8 80 35 m 1 80 -9.9 -12.5 -5.1
3 40.32 42.62 2138 224.7 -1.7 70.7 1.8 3.6 1.8 80 35 m 1 80 -6.8 -8.5 -2.4
4 40.32 42.62 2138 257 4 67.9 1.7 3.7 1.8 80 35 m 1 80 -1.8 -1.8 2.2
5 40.32 42.62 2138 282.9 8.4 68.8 1.6 3.6 1.8 80 35 m 1 80 1.9 3.3 4.8
6 40.32 42.62 2138 304.7 13.1 64 1.5 2.7 1.8 80 35 m 1 80 5.8 6.5 8.1
7 40.32 42.62 2138 319.1 16 58.5 2.7 2.6 1.8 80 35 m 1 80 8 8.6 9.1
8 40.32 42.62 2138 323.1 16.6 57.6 1.3 2.7 1.8 80 35 m 1 80 8.7 9.2 10
9 40.32 42.62 2138 296.7 12.4 58.1 1.1 2.3 1.8 80 35 m 1 80 5.4 6 7.9
10 40.32 42.62 2138 268.1 6.2 70.2 1.2 3.1 1.8 80 35 m 1 80 0.4 1.1 4.5
11 40.32 42.62 2138 230.9 -0.1 71.2 1.3 2.7 1.8 80 35 m 1 80 -4.7 -5.8 -0.2
12 40.32 42.62 2138 206.1 -5.4 76.1 1.3 3.1 1.8 80 35 m 1 80 -9.2 -11.7 -4.3
76
Table 10. RAYMAN 2017 PET, PT and mPET monthly distributed values for Sarıkamış
RESULTS As be seen in monthly PT, PET and mPET tables for four areas (Table 7-10), although there are temperature
difference between three value categories, motnthly distributions are showed similar behaviour. By it means,
thermal comfort of sample human directly relative with microclimate. If each result is analized more detailed, all
can be seen that for the same peak period, which is between July and August. On the other hand, mPET values are
very sensitive to wind index, greater than 5 m/s average speed value in particular.
ERCİYES As seen in the boxplot (Table 11), PT values are the widest section of plot. This means, environmental changes
of temperature is more than effectivenes on winter sportsmen. Bussiness clo. and wind speed value effects are
more effective on mPET plot. Thus, temperature change is too much, though not at a level that adversely affect
the winter sports. Especially in Erciyes, because of the average wind speed is greater than 5 m/s, maximum
temperature level of each plot is smaller than the other three analized areas.
Table 11. Boxplot of PET, PT and mPET distributions for Erciyes (Average Wind Speed: 6.80 m/s)
KARTALKAYA As seen in the boxplot (Table 12), PT values are the widest section of plot such as Erciyes. This also means,
environmental changes of temperature is more than effectivenes on winter sportsmen. Bussiness clo. and wind
speed value effects are more effective on mPET plot as well (Mayer and Höppe 1987, Höppe 1999, Matzarakis et
al. 1999). Thus, temperature change is too much, though not at a level that adversely affect the winter sports.
Especially in Kartalkaya, because of the average wind speed is beteween 3-5 m/s, maximum temperature level of
each plot is smaller than Ilgaz and Sarıkamış.
77
Table 12. Boxplot of PET, PT and mPET distributions for Kartalkaya (Average Wind Speed: 3.80 m/s)
ILGAZ As seen in the boxplot (Table 13), PT values are similar with PET values. Meaning of this situation, wind speed
is less effective than other three areas because, average wind speed is smaller than 3 m/s and air temperature values
are higher than other three areas. Yet, bussiness clo. and wind speed value effects are more effective on mPET
plot as well (Mayer and Höppe 1987, Höppe 1999, Matzarakis et al. 1999). Especially in Ilgaz, whereas other
taking into account all of four areas and their indexes, Ilgaz is the most comfortable area for winter sports and
winter tourism as well.
Table 13. Boxplot of PET, PT and mPET distributions for Ilgaz (Average Wind Speed: 1.58 m/s)
SARIKAMIŞ As seen in the boxplot (Table 14), PT values are the widest section of plot such as Erciyes and Kartalkaya. This
also means, environmental changes of temperature is more than effectivenes on winter sportsmen. Bussiness clo.
and wind speed value effects are more effective on mPET plot as well as Kartalkaya. Behaviour of PT, PET and
mPET values are very similar with Ilgaz, however, temperature changes are higher and maximum temperature
values are smaller than Ilgaz. This information is given the less comfortable situoation then Ilgaz for winter sports
and winter tourism indeed.
Table 14. Boxplot of PET, PT and mPET distributions for Sarıkamış (Average Wind Speed: 1.54 m/s)
After those calculations are analized, according to PT and PET&mPET comfort scale (Table 1,2) for sample human
that standardized European man (gender), who is 1.75 m (height), 75 kg (weight), at 35 years old, in work suit
(clothing 1.0 clo) and working in office (activity 80 w) and position standing, table of comfortability for each area
is obtained. As shown in tables (Table 15-18) all of four areas are comfortable for winter sports and winter tourism
according to psychological aspects of meteorology. Besides, Ilgaz is the most comfortable area and second is
Sarıkamış, third is Kartalkaya and Erciyes is the fourth one.
78
As Table 15 shown that value distribution indicates, Ilgaz is the most comfortable are for winter sports and
Olympics, according to indexes (Matzarakis Amelung, 2008).
Table 15. Rayman 2017 Output PT, PET and mPET distribution index for Ilgaz
Because of the number of comfortable days are lesser than Ilgaz and PT (Table 16) values are cooler than Ilgaz,
Sarıkamış is the second best option for winter sports and Olympics, according to indexes (Matzarakis Amelung,
2008).
Table 16. Sarıkamış Rayman 2017 Output PT, PET and mPET distribution index for Sarıkamış
Kartalkaya (Table 17) and Erciyes (Table 18) are quite similar in account of indexes (Matzarakis Amelung, 2008)
yet, wind speed is also determinant for winter sports and Olympics, mean wind speed of Erciyes is geater than 5
m/s and mean wind speed of Kartalkaya of course (Table 3). This situation means Kartalkaya is the third best
option and Erciyes is fourth for winter sports and Olympics (Matzarakis Amelung, 2008).
Table 17. Sarıkamış Rayman 2017 Output PT, PET and mPET distribution index for Kartalkaya
Table 18. Sarıkamış Rayman 2017 Output PT, PET and mPET distribution index for Erciyes
REFERENCES
Chen, Y. C., & Matzarakis, A. (2014). Modification of physiologically equivalent temperature. Journal of Heat
Island Institute International , 9-2.
General Directorate of Mineral Research and Exploration. Date retrieved 22.05.2018, adress:
http://www.mta.gov.tr/v3.0/arastirmalar/cografi-bilgi-sistemleri
Matzarakis, A. Rayman 2017. Rayman 2017 Manual. Date retrieved 02.05.2018, adress:
http://www.urbanclimate.net/rayman/introraymanpro.htm
Matzarakis, A., & Toy, S. (2017). Quantification of Biıoclimate Conditions For Winter Sports Events-Cancidate
City Erzurum For Winter Olympic Games 2026. : 8th Atmospheric Sciences Symposium. Istanbul.
Mayer, H., Matzarakis, A., & Iziomon, M. G. (1999). Applications of a universal thermal index: Physiological
equivalent temperature. Int J Biometeorol , 76-84.
National Department of Statistics. Date retrieved 02.05.2018, adress: http://www.tuik.gov.tr
National Meteorological Office. Date retrieved 02.05.2018, adress: https://www.mgm.gov.tr
World Meteorological Organisation. (1999). Climate and human health. World Climate News, 3-5
Months 1 2 3 4 5 6 7 8 9 10 11 12
PT -6.8 -3.8 -0.8 4.4 7.5 10.5 13 12.9 9.9 5.2 0.2 -4.4
PET -5.6 -3.4 -1.1 3 6.8 10 12.9 12.8 9.5 4.4 -0.4 -3.8
mPET -1 0.9 2.9 5.6 8.8 11.1 13.5 13.4 10.5 7 3.8 0.7
Months 1 2 3 4 5 6 7 8 9 10 11 12
PT -14 -12.5 -8.5 -1.8 3.3 6.5 8.6 9.2 6 1.1 -5.8 -11.7
PET -11 -9.9 -6.8 -1.8 1.9 5.8 8 8.7 5.4 0.4 -4.7 -9.2
mPET -6.1 -5.1 -2.4 2.2 4.8 8.1 9.1 10 7.9 4.5 -0.2 -4.3
Months 1 2 3 4 5 6 7 8 9 10 11 12
PT -14.5 -11.4 -9.6 -5.2 0.2 4.4 7.4 7.5 4.4 -0.9 -5.9 -11.6
PET -11.7 -9.4 -8 -4.7 -0.8 3 6.5 6.6 3.3 -1.5 -5.2 -9.5
mPET -8.4 -6.2 -4.9 -1.4 2.5 5.4 8.3 8.4 5.4 1.9 -2.1 -6.2
Months 1 2 3 4 5 6 7 8 9 10 11 12
PT -15.6 -13.1 -11 -4.6 1.4 4.6 7.2 8.4 5 -1.2 -6.7 -13
PET -12.6 -10.7 -9.1 -4.4 0 3.3 6.5 7.9 4.1 -1.8 -5.8 -10.6
mPET -11.2 -8.8 -7.4 -2.4 1.1 4.5 7 8.2 5.3 0.8 -3.2 -8.4
79
APPLICATION OF DEEP LEARNING METHOD FOR AIR POLLUTION
FORECASTING ON ANKARA
Zeynep Feriha Unal, Umur Dinc, Huseyin Toros
1 Istanbul Technical University, Faculty of Aeronautics and Astronautics, Department of Meteorological
Engineering, Istanbul, Turkey
Abstract Air pollution is one of the significant problems for human life because average healthy person inhales about 15
m3 of air every day and in fact the air pollutant content of this air directly causes respiratory issues in human body.
Forecasting air pollution for near future can help people who are sensitive for this air quality affect and also help
taking precautions from extreme meteorological events like dust storms, acid rains. Deep learning method is new
and outstanding forecasting method among many air pollution forecasting methods. This study is mainly focused
on Turkey’s second biggest city and also capital city Ankara at five observation points. In this study, PM 10
measurement data from Ministry of Environment and Urbanization and meteorological data from and Turkish
State Meteorological Service are used for training deep learning model. Additionally, NOAA’s GFS data to run
WRF-model to predict for the future by using our trained deep learning model. The final step for this study, we
changed wind direction range to reduce deep learning model’s prediction error.
Keywords: Air pollution, Air pollution forecasting, Deep learning, PM2.5, PM10
INTRODUCTION
Air pollution is one of the challenging environmental issues among the other environmental issues like climate
change and increasing Greenhouse gas event. In addition to that, air pollution is one of the reasons for most of the
environmental issues in the world. Although there are many reasons for air pollution, it is possible to examine in
two main groups as natural reasons and reasons that created by human activities. As natural reasons, volcanic
eruptions and forest fires and also dust storms are countable. The main reasons of human activities for air pollution
are industrialization and urbanization (Toros et al., 2014; Sümer, 2014). One of the main concerns about this
challenging issue is the impact on human health due to inhaling 15.3 m3 of air. The pollutant content of air effects
%91 of the population around the world and also air pollution is the reason of 6 million pre-mature baby death in
2016 (WHO, 2016). Most of metropolitan cities are experiencing elevated concentrations of ground-level air
pollutants. Predict and evaluate the concentration of air pollutants are an important issue due to environmental or
health agencies (Zhang and Ding, 2017). Another big concern is the scale of air pollution parameters such as PM10,
SO2, NO2 and O3. Air pollution parameters’ concentration are analyzed for Turkey’s 16 big cities and it is found
that daily PM10 distribution frequency is between 20-60 µgm3 which approximately equals %59, daily SO2
concentration is 20 µgm3 which is under %84. At the same time, the study shows that at level of 45 µgm3, NO2
concentration is %44; at the level of 30 µgm3, O3 is under %59 (Toros et al., 2013). Behind these dangerous levels,
there are two main arguments: urbanization and industrialization. As it is clearly seen above, air pollution levels
in Turkey are not normal and if people cannot control these levels of air pollution today, tomorrow the hazards
and deaths will widen. At that point, air pollution forecasting technique is one of the air pollution control
mechanisms preventing from extreme air pollution events such as dust storms, acid rains. In addition to that, there
are various forecasting methods for air pollution that authorities can know possible episode events to take
precaution for society. Unfortunately, air pollution studies are not considered to be important in developing
countries. In particular, there is lack of understanding and evaluation of air pollution in ways of meteorological
conditions and meteorological events. This study mainly focused on forecasting air pollution in a with deep
learning model “H2O” which is one of the trendy and successful methods. This study differs from the other studies
in this field due to our deep learning model configuration and using WRF output to train this model. Our aim for
this study is to help people who are interested in this field. This study is integrated to Turkey's capital and second
largest city, Ankara. The results we got from this study will be our guide to reduce predicting error and the
improved model configuration will be obtained for other cities in Turkey.
80
STUDY AREA AND DATA Considering air pollution, Ankara is one of the most polluted cities in Turkey due to having industrial facilities,
coal usage in buildings and also crowded traffic issue. Ankara’s climate classification resembles with mid-latitude
steppe climate which has hot-summer and quite cold, snowy winter. The rainfall occurs during the spring and
autumn. Air pollution increases during winter season due to increasing coal usage in building and also inversion
layer occurrence. For topographical point of view, Ankara is the deepest point in the valley surrounded by
mountains. Because of the temperature inversion in this area, decreasing boundary layer depth and also
anthropogenic heat cause to have intense urban heat island effect on Ankara in winter season (Çiçek & Doğan,
2006). Advection and radiation fogs are likely to be seen on this area as temperature inversion occurs frequently
in winter season. Another important point for air pollution, the population over Ankara is 5.503.985 people as
much as 1/3 of Istanbul. Crowded population in big cities are likely to have low air quality, thus it also means that
so many people including risk groups are affected by air pollution in Ankara.
Figure 1. Location of Ankara in Turkey filled with red color
In this study, we used temperature, wind speed and direction meteorological parameters for 2 years from Turkish
State Meteorological Service and also measured PM10 and SO2 parameters for 2 years from Ministry of
Urbanization and Environment for our H2O model input. Couple of reasons why we select PM10 and SO2
parameters are there are no observation for PM2.5 and also other parameters’ data set aren’t available for using,
only selected parameters have suitable data group on the website of Ministry of Urbanization and Environment.
Later on, we used GFS data which has 0.25 degree resolution (~25 km in latitudes of Turkey) from NOAA
(National Oceanic and Atmospheric Administration) for WRF model input and for final step, the model output is
used for Deep Learning Model called as H2O.
Figure 2. PM10 Measurement Points of Ankara shown as green, orange and yellow areas
81
METHOD AND MODEL SETUP
The Weather Research and Forecasting (WRF) is an open-source mesoscale numerical weather prediction model
is developed by NCAR, it is mainly used for atmospheric research and operational forecasting applications. In this
study, we used WRF 4.0.2 with one domain that has 9x9km resolution is showed in Figure 3.1.
Figure 3. Our domain used for our study
Table 1: Physics options used in this experiment
Physics Options
Microphysics New Thompson
Cumulus
Parameterization
Tiedtke
Longwave Radiation RRTMG
Shortwave Radiation RRTMG
Planetary Boundary
layer
MYJ
Surface Layer Eta
Land Surface NOAH
There are many machining learning approaches which are widely used by big communities such as TensorFlow,
Pytorch. We choose H2O for our study The reason why we selected as our study model, H2O has an easy user
interface to perform great predictional applications. H2O is an open-source machine learning platform which is
one of the most common used machine learning platforms.
In this study, firstly we used meteorological data such as temperature, wind speed and wind direction of
Meteorological Service and locational measurements of PM10 and SO2 data from Ministry of Urbanization and
Environment to train our Deep Learning Model which is developed by H2O to forecast future PM10 and SO2 values.
Since we can’t measure the future atmospheric variables, we used dynamic atmospheric models to get future
predicted atmospheric variable that we used from Meteorological Service to train our deep learning model.
Therefore, we used WRF model that is developed by NCAR with input NOAA’s GFS data which has 0.25 degree
82
resolution. After that we try to make predictions of PM10 and SO2 with our trained deep learning model by using
the atmospheric variable that we predicted from WRF model.
RESULTS
Our outcomes for predicting air pollution parameters don’t have high compatibility with observations, there are
many reasons behind these low compatibility between them. First reason is no usage of wide meteorological
parameters including boundary layer height, mixing ratio, pressure, humidity etc. from Meteorological Service to
train our deep learning model wisely. Thus, our historical data set for air pollution doesn’t include all of main
parameters such as PM2.5, NO, NO2,CO and CO2 and also there are many unavailable and bad measurement data
in data set from Ministry of Urbanization and Environment. However, in future studies, we strongly believe that
we will add this features and we will decrease our error percentage.
Bahçelievler
The RMSE (Root Mean Square Error) is 16.6, MAE (Mean Absolute Error) is 13.6 of PM10, RMSE is 4.64, MAE
is 3.49 of SO2 in Bahçelievler. As it can be seen, these values are high according to RMSE and MAE calculation.
Figure 4. Comparing Model Results and Observation Values of PM10 for Bahçelievler, Ankara
Figure 5. Comparing Model Results and Observation Values of SO2 for Bahçelievler, Ankara
Demetevler
The RMSE (Root Mean Square Error) is 28.9, MAE (Mean Absolute Error) is 21.2 of PM10, in Demetevler. As it
can be seen, these values are high according to RMSE and MAE calculation.
0
20
40
60
80
PM10
Prediction Observation
05
10152025
SO2
Prediction Observation
83
Figure 6. Comparing Model Results and Observation Values of PM10 for Demetevler, Ankara
Kayaş
The RMSE (Root Mean Square Error) is 21.1, MAE (Mean Absolute Error) is 16.4 of PM10, RMSE is 3.5, MAE
is 2.43 of SO2 in Kayaş. As it can be seen, these values are high according to RMSE and MAE calculation.
Figure 7. Comparing Model Results and Observation Values of PM10 for Kayaş, Ankara
Figure 8. Comparing Model Results and Observation Values of SO2 for Kayaş, Ankara
Sıhhiye
The RMSE (Root Mean Square Error) is 19.8, MAE (Mean Absolute Error) is 16.7 of PM10, RMSE is 3.53, MAE
is 2.61 of SO2 in Sıhhiye. As it can be seen, these values are high according to RMSE and MAE calculation.
0
50
100
150
PM10
Prediction Observation
020406080
100120
2.0
1.2
01
9
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
29
.01
.20
19
30
.01
.20
19
31
.01
.20
19
PM10
Prediction Observation
0
10
20
30
40
2.0
1.2
01
9
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
29
.01
.20
19
30
.01
.20
19
31
.01
.20
19
SO2
Prediction Observation
84
Figure 9. Comparing Model Results and Observation Values of PM10 for Sıhhiye, Ankara
Figure 10. Comparing Model Results and Observation Values of SO2 for Sıhhiye , Ankara
Sincan
The RMSE (Root Mean Square Error) is 71.4, MAE (Mean Absolute Error) is 58 of PM10, RMSE is 9.3, MAE is
8.08 of SO2 in Sincan. As it can be seen, these values are high according to RMSE and MAE calculation.
01020304050607080
2.0
1.2
01
9
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
PM10
Predicted Observed
02468
1012141618
2.0
1.2
01
9
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
SO2
Predicted Observed
85
Figure 11. Comparing Model Results and Observation Values of PM10 for Sincan, Ankara
Figure 12. Comparing Model Results and Observation Values of SO2 for Sincan , Ankara
CONCLUSION
As it is known air pollution is quite dangerous for humanity and their living habitat, therefore its forecast is
necessary to take precautions for dangerous air episodes’. Because Ankara is Capital city and second most
populous city in Turkey, air pollution forecast of Ankara is so essential. In this study, we proposed the prediction
of the concentration of air pollutants based on a machine learning method. It was shown that H2O as a machine
learning method performs not well performance because of data quality both meteorological and air pollution. The
quality of data will be improved and different method will be train for improve the result of forecasting.
Acknowledgments:
The authors are grateful to Turkish State Meteorological Service (MGM) and Ministry of Environment and
Urbanization (ÇŞB) for both meteorological and air pollution data.
REFERENCES
Çiçek İ., Doğan U., 2006. Detection of Urban Heat Island in Ankara, Turkey, Il Nuovo Cimento, 29(4), 309-409.
doi: 10.1393/ i2005-10028-2
Toros H, Erdun H., Çapraz Ö., Özer B., Daylan E.B., Öztürk A.İ., 2013. Air Pollution and Quality Levels in
Metropolitans of Turkey for Sustainable life, European Journal of Science and Technology (EJOSAT), 1(1),
12-18.
0
50
100
150
200
2502
.01
.20
19
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
PM10
Predicted Observed
05
10152025303540
2.0
1.2
01
9
3.0
1.2
01
9
4.0
1.2
01
9
5.0
1.2
01
9
6.0
1.2
01
9
7.0
1.2
01
9
8.0
1.2
01
9
9.0
1.2
01
9
10
.01
.20
19
11
.01
.20
19
12
.01
.20
19
13
.01
.20
19
14
.01
.20
19
15
.01
.20
19
16
.01
.20
19
17
.01
.20
19
18
.01
.20
19
19
.01
.20
19
20
.01
.20
19
21
.01
.20
19
22
.01
.20
19
23
.01
.20
19
24
.01
.20
19
25
.01
.20
19
26
.01
.20
19
27
.01
.20
19
28
.01
.20
19
SO2
Predicted Observed
86
Toros H, Geertsema G, Cats G, 2014. Evaluation of the HIRLAM and HARMONIE numerical weather
prediction models during an air pollution episode over Greater İstanbul Area. CLEAN - Soil, Air, Water,
42(7), 863-870.
Sümer, G., 2014. Hava Kirliği Kontrolü: Türkiye’de Hava Kirliliğini Önlemeye Yönelik Yasal Düzenlemelerin
Ve Örgütlenmelerin İncelenmesi [Air Pollution Control: Examining the Legal And Regulatory Organization
of Prevention of Air Pollution in Turkey], International Journal of Economic and Administrative Studies,
13, 37-56.
Zhang J., Ding W., 2017. Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine:
The Case of Hong Kong. International journal of environmental research and public health, 14(2), 114.
WHO,http://breathelife2030.org/news/infographic-library/
87
POSTERS
88
CHANGE OF MICROFAUNIST RESIDUES BASED ON MINERALOGICAL
AND GEOCHEMICAL ANALYSIS (USING THE EXAMPLE OF THE KHARA-
ZIRA AREA)
Fatma Suleymanova
ANAS Institute of Geology and Geophysics, Azerbaijan
Abstract
As is known, the Quaternary period was characterized by frequent and sharp fluctuations. Climate, the level of
oceans and seas, a significant change in relief, fauna, flora and other components of the earth system. As a result
of large-scale structural and exploratory drilling, many well cuts were obtained at the Khara-Zira area, in which
Ostracod, foraminiferal, mollusk and other fauna were studied in detail, stratigraphy and lithofacial features of the
Quaternary sediments of the area.
Keywords: quaternary sediments, stratigraphy, relief, ostracod fauna, lithofacies, sandstones, shallow water.
89
PREDICTABILITY AND FEEDBACK EFFECTS OF LAND SURFACE
CLASSIFICATION AND ATMOSPHERIC PARAMETERS
Buket ISLER, Zafer ASLAN
Faculty of Engineering, Istanbul Aydın University, 34295 Florya, Istanbul, Turkey
[email protected], [email protected]
Abstract
Developing technological tools and software, to make comprehensive data analysis, to make predictions for the
future are gradually reached up to promising points. The continuation of vitality, perhaps the most important
problem of humanity, is one that has been researched by scientific circles for years. The deterioration of natural
resources, damage on vegetation, urbanization, increasing population density, changing climate with human
impact, signals the future of humanity. Although it is a neglected issue, studies with satellite data and artificial
intelligence technologies reveal the urgency of the situation.
NDVI (Normalized Vegetation Index) and Leaf Area Index (LAI) is a measurement method that takes into account
the total leaf area per unit of a surface area. The determination of NDVI and LAI allows researchers to have
knowledge about atmosphere, vegetation growth, incoming solar radiation, energy transfer, precipitation and gas
exchange. The leaf area is determined by two measurement methods: direct and indirect. With direct measurement,
the leaves of the deciduous tree are collected after falling from a tree on a large tarp. An imaging scanner can also
be used (Url-4). This is a challenging and difficult task. In this paper, satellite data will be used to determine
NDVI and LAI. It is aimed to investigate and predict the effects of regional urbanization and climate change on
vegetation by using artificial intelligence methods. In vegetation analysis, the multi-time index (NDVI, EVI, LAI
etc.) values obtained from TERRA-MODIS have been analysed. The study area in different geographical regions
of Turkey as Istanbul and Ankara were considered. The results of the analysis, is to bring a comprehensive and
new perspective on interpretation of the effects of urbanization. Two examples of application of NDVI and LAI
are given by a data set describing plant community types (vegetated and urbanized parts of Istanbul and Ankara).
ANN and Wavelet methodologies help to understand predictively of indexes and some atmospheric parameters
(solar radiation, insolation, precipitation and air temperature) and their feedback.
Keywords: ANN, Wavelet, Land Surface Classification, NDVI, LAI, Forecasting.
INTRODUCTION
Migration from rural areas to urban areas leads to a rapid urbanization process in Turkey. Industrialization and
rapid urbanization have a negative impact on many environmental values such as regional climate changes, basic
ecosystem and global diversity. Even without taking account of climate changes, the loss of agricultural land in
the world finds 24 billion tons. Precipitation enters the universal soil loss equation (USLE) as a component of a
factor called the water erosivity (Land use 2018; Aslan et al. 2009; Dragan et al. 2003; Jha et al. 2015; Moncada
et al. 2014; Moyano et al. 2015; Michiels and Gabriels 1996). Aslan et al. (2009) and Okcu et al. (2013) reported
the combined effects of water and wind erosivity risks close to lakes in western and southern parts of Turkey.
Because of the importance of the subject for human and living health, researches on the effects of urbanization on
land vegetation are increasing and gaining importance.
MATERIAL and METHODS
Study Area
North-western part of Turkey (Istanbul, latitude: 40.993999, longtitude: 29.237539) and Central Anatolia (Ankara,
latitude: 40.021062, longtitude: 32.831015, provinces and surrounding was selected as the study area.
Data
The data sets to be used in the study will be obtained from the data centre archive of the ORNL DAAC (Oak Ridge
National Laboratory Distributed Active Archive Centre) in the United States. In vegetation analysis, the multi-
90
time index (NDVI, LAI) values obtained from TERRA-MODIS will be used. In the application section of the
thesis, it is planned to use the data for the period of 2013-2018.
Methods
The data processing steps to be followed in the paper are listed below:
• Formulating the problem, data collection, data cleaning, pre-processing, transformation, mining task,
method selection and evaluation of results, visualization tools to achieve meaningful results,
• Data Cleaning, Data Reduction, Data Transformation
• To create appropriate modelling techniques according to the researched data set(ANN and Wavelet
methodologies)
• Forecast 2023
• Method Performance tests and graphics interpretation
Artificial Neural Network
As known; there are nerve cells on the basis of behaviour such as generating new information, creating new
information, remembering and discovering by means of learning which are features of human brain. There are an
estimated 1011 nerve cells in the human brain, and there is an inter-nerve bond called synaptic junction between
these nerve cells. Therefore, it is difficult or impossible to perform this complex structure of the human brain with
traditional programming methods. (http://edergi.atauni.edu.tr/index.php/SBED/article/viewFile/453/446) The
essence of ANN is shown in Figure-1. (https://medium.com/@ivanliljeqvist/the-essence-of-artificial-neural-
networks-5de300c995d6)
No specific method is followed step by step when performing ANN calculations. Since the neural network has a
distributed structure, it produces the internal rules that make the association and arranges these rules by comparing
the results of these with the previous examples. Learns how to do network work through trial and error.
Artificial neural networks, such as people, benefit from past experiences, aim to make a future forecast and are
created for a specific purpose. The ability to learn artificial neural networks and to process a different information
can change its structure and weight. These features indicate the ability of ANN to solve complex problems.
Figure-1 Essence of ANN Han, J. and Kamber, (2016)
91
Wavelet Techniques
The discrete wavelet transform (DWT) is a linear signal processing technique that, when applied to a data vector
X, transforms it to a numerically different vector, of wavelet coefficients.
The DWT is closely related to the discrete Fourier transform (DFT), a signal processing technique involving
sine’s and cosines. In general, however, the DWT achieves better compression.
This study is based on wavelet techniques and their applications to cloud cover data. In this section we give the
basic definitions about the wavelet transform. Wavelets are families of small waves generated from a single
function f(t) which is called the mother wavelet. A sufficient condition for f(t) to qualify as a mother wavelet is
given as below:
dttf 2|)(| (1a)
The Fourier transform F of f(t) is defined as
dtetfwF iwt)()( (1b)
A function (t) satisfying the following condition is called a continuous wavelet:
1|)(| 2 dtt (2a)
It may be observed that the scalogram can be represented either as three-dimensional plot or as a two-dimensional
grey scale image.6 As mentioned above, parameters a and b represent, respectively, the scaling factor and the
location in time.7 In the following sections, f(t) will be considered as monthly values of NDVI over selected areas
in Turkey.
Table 1 presents our definitions of climate variability and the related time scale values in months or in years. In
this paper, by applying wavelet techniques, climate variability of cloud cover and its time scale will been defined.
ANALYSES This part of the paper is related with ANN outputs on NDVI forecasting. Results in training, test data are presented
in figures 2 and 3.
Analyses of ANN model applications in Ankara NDVI observations
Figure 2. ANN applications to Ankara, training, and error histogram
92
Figure 3. ANN applications to Ankara, for training, validation and test forecasting
Comparison of model shows some over and lover estimations. The last part of the prediction closely follows
observation data.
Analyses of ANN model applications in Istanbul NDVI observations
Figure 3. ANN applications to Istanbul NDVI data, training, and error histogram
Figure 3 shows histogram of NDVI values for training, validation and test period.
93
Figure 4. ANN applications to Istanbul, for training, validation and test forecasting
Deviations between model and observations are more at higher and lover values and observations (Fig. 4).
Wavelet applications
1D wavelet packets an 1D continuous wavelet analyses show the role of small, meso and large scale influences on
NDVI variations in two study areas and period. Results of these analyses are important to decrease the model
errors. By using hybrid models (ANN-wavelet combined applications on data ) reliability of forecasting will
increase.
Clustering
(a) (b)
Figure 5a – 5b. K-means clustering of NDVI in Istanbul. Scheme: weka.clusterers.SimpleKMeans -init 0 -max-
candidates 100 -periodic-pruning 10000 -min-density 2.0 -t1 -1.25 -t2 -1.0 -N 2 -A
"weka.core.EuclideanDistance -R first-last" -I 500 -num-slots 1 -S 10; b) K-means clustering of NDVI in
Ankara. Scheme: weka.clusterers.SimpleKMeans -init 0 -max-candidates 100 -periodic-pruning 10000 -min-
density 2.0 -t1 -1.25 -t2 -1.0 -N 2 -A "weka.core.EuclideanDistance -R first-last" -I 500 -num-slots 1 -S 10
Figure 5a shows K-means clustering of NDVI in Istanbul, Model and evaluation on training set. Data is clustered
as; 0; ( 139; 97%) and 1; (4; 3%). Figure 5b shows K-means clustering of NDVI in Ankara, Model and evaluation
on training set. Data is clustered as; 0; (142; 99%) and 1; (1; 1%)
94
RESULTS
This paper covers some case studies on applications of ANN, wavelet and clustering techniques in two studies in
Turkey (Istanbul and Ankara). After NDVI analyses, indeed there are two clusters, but Ankara shows more
homogeneous structure than Istanbul.
Acknowledgements
Author(s) thank Assist. Mustafa TAKAOĞLU, IAU, for his kind helps on data handling.
REFERENCES
Han, J. And Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco,
Second Edition, 2006.
Aslan, Z., Gabriels, D., Ayday, C., Erpul, G., Gürer, K., Yeniçeri, N.,et al. (2009) Actual erosivity analysis based
on ground measurements and remote sensing data, TUJJB-TUMAHAP-01-06.
Dragan, M., Feoli, E., Fernetti, M., & Zerihun, W. (2003). Application of a spatial decision support system
(SDSS) to reduce soil erosion in northern Ethiopia. Environmental Modelling and Software, 18, 861–868.
Jha, S. K., Zhao, H., Woldemeskel, F. M., & Sivakumar, B. (2015). Network theory and spatial rainfall
connections: An interpretation. Journal of Hydrology, 527, 13–19.
Moncada, M. P., Ball, B. C., Gabriels, D., Lobo, D., & Cornelius, W. M. (2014). Evaluation of soil physical
quality index S for some tropical and temperate medium textured soils. Soil Science Society of America Journal.
https://doi.org/10.2136/sssaj2014. 06.0259.
Moyano, M. C., Tornos, L., & Juana, L. (2015). Water balance and flow rate discharge on a receiving water
body: Application to the B-XII irrigation district in Spain. Journal of Hydrology, 527, 38–49.
Okcu, D., Aslan, Z., Maktav, D., Söğüt, A. S., Oğuzhan, B., Çağlar, Z. N., et al. (2013). Flood analysis,
Bosphorus University, Metallurgical Laboratory, Research Foundation, BU, BAP-ProjectNo: 5572.
Michiels, P., & Gabriels, D. (1996). Rain variability indices for the assessment of rainfall erosivity in the
Mediterranean region. In L. Rubio & A. Calvo (Eds.), Soil degration and desertification in Mediterranean
environments (pp. 49–70). Logrono, Espana: Geoforma Ediciones.
95
RECONSTRUCTION OF QUANTITATIVE INDICATORS OF AZERBAIJAN'S
CLIMATE IN EARLY PLEISTOCENE BASED ON MINERALOGICAL
INFORMATION
Muradly Eldar V.
Geography of Institute named after Academic H.A.Aliyev of Azerbaijan NAS,
Jalilabad branch of Azerbaijan State Pedagogical University
Abstract
The degradation of the relief ensures rapid transport of wearing products, thereby accelerating their change. In
acutely degraded relief, even in the conditions favourable for chemical abrasions, sedimentary rocks are formed
from only modified rock fragments. Summarizing all the above mentioned facts, it is possible to show the
qualitative characteristics of climate change in the early Pleistocene according to the mineralogical elements.
Keywords: Pleistocene, Baku age, Baku semi-horizon, Early Pleistocene,
Introduction
The elemental composition of sediments is closely associated to climate conditions that existed during their
formation. Climate change affects the intensity and nature of weathering, the weathering environment, the
accumulation of weathering products, and the elemental composition of sediments. The nature of weathering is
one of the indicators showing the past weather conditions. The higher the average annual temperature and the
greater the humidity on the surface, the more active chemical degradation will be, or vice versa.
However, it should be taken into account that besides climate, the relief also has impact on the weathering process.
The degradation of the relief ensures rapid transport of wearing products, thereby accelerating their change. In
acutely degraded relief, even in the conditions favourable for chemical abrasions, sedimentary rocks are formed
from only modified rock fragments. We believe that the main characteristics of Azerbaijan's relief have been
shaped before the Pleistocene. No wonder, the high, middle, low mountainous valleys and plains had emerged,
and a hydrographic network had been formed then as it is now. Therefore, differences in the continental
lithogenesis are characterized by major climate changes.
Materials
In the early Pleistocene (780-460 thousand years ago), the thickest cuttings of the Pleistocene's stratigraphic
sections, which were absolutely age-abiding, full-scale, with the greatest possible scope, were involved in the
research in order to study the qualitative characteristics of Azerbaijan's climate. Particular attention was paid to
the study of the elemental composition of the cuttings of Baku horizon (Figure 1)., Azykh, Kichik Harami,
Mishovdag and Hasanriz. 17 cuttings have been involved in the analysis.
Figure 1. Mineralogy scheme of the mountains of Baku
96
We investigated the Turkan horizon, regarding the geomorphological, paleontological, archaeological, and
paleomagnetic studies [1; 2; 4; 6].The lower (Turkan) horizon, Lower Pleistocene horizon is followed in the
cuttings of Baku horizon, Kichik Harami, Mishovdag and Ushtal.
The mineralogical composition of the lower part of the lower Baku horizon is characterized by the advantage of
the minerals formed in cold conditions (augite, hornblende and others).
The cutting of Kichik Harami should be especially emphasized here, because the composition of dolomite reaches
50%. Muscovite, limonite, magnetite-ilmenite, as well as zirconium and epidote, which are not found in
resistant minerals groups, are observed in this cutting [1; 2, 5, 7].
Among the light-weighted minerals, feldspars, modified feldspars and clay aggregates prevail. The coefficients of
the mineral spectra of sediments are 2-3. The mineralogical spectra of the lower part of the early Baku semi-
horizon indicate their formation in the extreme cold climate.
The upper part of the lower Baku semi-horizon is characterized by the growth of the sand fraction according
to the granulometric analysis (apart from the Kichik Harami cutting, where it is 30-35%). Carbon dioxide
substantially increases. Muscovite (54.9%), ilmenite-magnetite (24%) and limonite (18.5%) are the dominant
minerals on the surface of the lower Baku semi-horizon [3;4;6].
The upper part of the lower Baku semi-horizon in the Caspian region is characterized by the weakening of mineral
associations, where mostly muscovite is observed among the variable minerals. The main fibrous minerals of the
light fraction of depicted sediments consist of feldspars, their remains and clay aggregates.
Comparative analysis of the mineralogical composition of sediments in the upper part of the lower Baku semi-
horizon, sharp decrease in the composition of non-durable minerals, and, respectively, the advantage of durable
minerals indicate significant warming and humidity in the territory of Azerbaijan.
Palynological researches of the respective sediments (Soltanli, Chartaz Fuzuli, Kalva and others), as well as the
collection of the lower Baku horizon sediments in the upper part show the warming and humidity of the climate.
The sediments of all studied sections of the lower part of the middle Baku semi-horizon are characterized by their
low carbonation (apart from the Baku horizon and Garaja cuttings) [1; 2; 3].
Slightly durable and non-durable minerals prevail in the mineralogical composition of the cross sections of this
period. Along with durable minerals in the Absheron peninsula (muscovite, limonite and others), non-durable
minerals also prevail (medium plagioclases, pyroxenes, and others). The same rule is observed in Gobustan, where
augite, biotite, hornblende prevail. Among durable minerals - magnesium, magnetite, muscovite and limonite
prevail.
Quantitative and qualitative analysis of mineralogical composition of sediments in the lower part of the middle
Baku semi-horizon (increase in non-durable minerals, absence of derivative minerals, etc.) shows that sediments
have occurred in cold and relatively dry climatic conditions.
The upper part of the Middle Baku semi-horizon is not sharply different due to its the granulometric composition,
and the proportion of soft and rough fractions is equally divided. The clay faction prevails in the foothills of the
south-eastern part of the Lesser Caucasus. The warm and humid climate at that period is also proved by carbonate
clays in the cuttings of Nuran, Chartaz and Fuzuli.
The Caspian region is characterized by durable minerals. Among this group of minerals, limonite (60%),
muscovite (20-25%) and magnetite-ilmenite (9%), and zircon (4%) in small quantities are found. The light fraction
is abundant in the sediments of clay aggregates and feldspars.
97
Durable minerals (muscovite, magnetite-ilmenite, and limonite) dominate in the south-east foothills of the Greater
Caucasus (the Nuran and Ushtal cuttings). Light-fractional composition is superior to feldspars and clay aggregates.
One of durable minerals of the light fraction, quartz is observed in the Nuran cutting.
The clay fraction in the granulometric composition prevails in the Garaja and Duzdag cuttings, and carbon dioxide
is 10-15%. The composition of the heavy fraction is characterized by significant storage of muscovite, limonite,
magnetite-ilmenite, zircon and epidote. Light- fractional composition includes rock sediments with feldspars, clay
aggregates, silicium.
Conclusion.
Summarizing all the above mentioned facts, it is possible to show the qualitative characteristics of climate change
in the early Pleistocene according to the mineralogical elements as follows (Figure 2).
Figure 2. Coefficient line of Early Pleistocene
References
1. Velichko, A.A., Antonova, T.V., Zelikson, E.M. and others. Paleogeography of the Azykh site — the most ancient
settlement of primitive man on the territory of the USSR. Press Academy of Sciences of the USSR, a series of geographical.
1980, No. 3, p. 20-35.1980.
2. Logvinenko N.V. Petrography of sedimentary rocks. Ed. "Higher School" Moscow-1967. 416 S.
3. Mamedov A.V., Aleskerov B.D. Pleistocene of Azerbaijan. Baku: Nafta-Press. 2002, 190 p.
4. Mamedov A.V., Tagiyev E.N. The evolution of the landscape and climate of the Caucasus in the Pliocene. / Fund In-that
Geography of the Academy of Sciences of Azerbaijan. 1993
5. Mamedov A.V., Aleskerov B.D. New data on stratigraphy, chronology and paleogeography of the Pleistocene of Azerbaijan
and the Caspian region. // Izv. AN Az.SSR. Senr Earth Sciences. 1985. No. 3. p. 46-54 .;
6. M. Suleymanov Habitat of primitive man in the south-east of the Lesser Caucasus (according to the Paleolithic caves
Azykh and Taglar). Author.diss ... Cand. geogr. sciences. Moscow, 1982, 23 p.
7. Suleymanov M.V. The dynamics of the development of the natural environment of the southeastern part of the Lesser
Caucasus in the Late Eo-Pleistocene and Pleistocene. Press AN Azerbaijani SSR, a series of Earth sciences, № 3, 1986
98
INVESTIGATION OF WIND STORMS and HEAVY RAIN AT NEWCASTLE
WILLIAMTOWN AIRPORT IN AUSTRALIA
Emrah Tuncay Özdemir1,2, Omer Yetemen2, Zafer Aslan3
1 Turkish State Meteorological Service, Atatürk International Airport Meteorology Office, 34149,
Yeşilköy, Istanbul, Turkey. [email protected], [email protected] 2 Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan, 2308,
Australia. [email protected] 3 Istanbul Aydın University, Faculty of Engineering, Computer Engineering Department, 34392,
Florya, Istanbul, Turkey. [email protected]
Abstract
Wind storms and heavy rain are important meteorological parameters that negatively affect aviation. In this study,
we investigated high-wind and heavy-rain event days based on a 20-year record of daily maximum gust and total
precipitation measurements for 1997-2017 at Williamtown Airport, Newcastle, NSW, Australia. Gust speeds equal
or faster than 50 knots and daily total precipitation is greater than 76 mm are accepted as threshold values of high-
wind and heavy rain event day, respectively. We evaluated 30 high-wind events and three heavy-rain events during
the study period. The maximum wind gust was measured as 66 knots on 23 June 1998 with no precipitation.
However, in another austral winter day, on 9 June 2007, 53-knot of gust occurred with 147 mm of daily
precipitation. This heavy-rain event estimated as 20-year return period event, which caused flooding in and near
vicinity of Newcastle, and named as the Pasha Bulker Storm after a ship ran aground on the Newcastle coast after
a strong wind. The paper covers the case studies and evaluation of severe weather conditions.
Keywords: Wind storms, heavy rain, Williamtown Airport, wind gust, aviation meteorology
INTRODUCTION
A storm is a disturbed state of the atmosphere particularly moving its surface, and powerfully implying severe
weather. It should be marked by vital disruptions to traditional conditions like sturdy wind, tornadoes, hail,
thunder, and lightning, serious precipitation, serious temperature reduction rain, sturdy winds, or wind transporting
some substance through the atmosphere as in an exceedingly sandstorm, blizzard, sandstorm, etc [1].
Storms have the potential to hurt lives and property via storm surge, severe rain or snow inflicting flooding or road
impassibility, lightning, wildfires, and vertical wind shear. Systems with important downfall and length facilitate
alleviate drought in places they move through [1].
Storms are created once a middle of air mass develops with the system of high close it. This mixture of opposing
forces will produce winds and lead to the formation of cloud like storm clouds [1].
There are many studies on the formation, development, and effects of storms in scientific literature (Ertüre,1974-
1977; Saaroni et al., 1998; Grumm, 2010; Grumm and Lambert, 2010; Dreveton et al., 1998; Jungo et al., 2002;
Alpaslan et al., 2003; Engin 2004; Knox et al., 2008; Ashley and Black, 2008; Gastineau and Soden, 2009; Toros
et al., 2010; Donat et al., 2010; Knox et al., 2011; Deniz et al., 2013; Özdemir and Deniz, 2014; Özdemir and
Deniz, 2016; Sirdas et al., 2017; Özdemir et al., 2018; Özdemir and Aslan, 2018; Özdemir 2018).
In this study, we investigated high-wind and heavy-rain event days based on a 20-year record of daily maximum
gust and total precipitation measurements for 1997-2017 at Williamtown Airport, Newcastle, New South Wales
(NSW), Australia.
MATERIAL AND METHOD
Royal Australian Air Force (RAAF) Base Williamtown (ICAO: YWLM) is the RAAF military base settled fifteen
kilometers north of the coastal town of Newcastle (27 kilometers by road) within the authorities space of Port
99
Stephens, in New South Wales, Australia (Figure 1). The bottom is the headquarters to each the Air Combat cluster
and also the police work and Response cluster of the RAAF. The military base shares its runway facilities with
Newcastle flying field. The closest cities are Raymond Terrace, settled eight kilometers west of the bottom and
Medowie, 6.8 kilometers, north of the bottom, where is home to several of the base's workers [2].
Figure 1: Location of RAAF Base Williamtown Airport (BOM, 2019).
Table 1 shows the geographic information for Williamtown RAAF Airport Meteorology Station.
Table 1: Information of Williamtown RAAF Airport Meteorology Station (BOM, 2019).
Station name: Williamtown RAAF Station
number: 061078 Commenced time: 1942
Latitude: 32.79°S Longitude:151.84°E Elevation: 7 m Operational
status: Open
High wind event is described by the National Weather Service (NWS) as, the threshold speed of wind may create
a hazard or become life-threatening. The factors for this definition may vary from state to state in the United States.
For example, in the state of Michigan, the factors are sustained non-convective (not associated with thunderstorms)
winds faster than or equal to thirty five knots lasting for one hour or longer, or winds faster than or equal to fifty
knots for any period (Knox et al., 2008; Knox et al., 2011; Sirdas et al., 2017; Özdemir et al., 2018; Özdemir and
Aslan, 2018; Özdemir 2018; NWS, 2019).
In this study, meteorological data obtained from the Bureau of Meteorology (BOM) are used. The study period is
between 1997 and 2017.
ANALYSIS AND RESULTS
Gust speed equal or faster than 50 knots and daily total precipitation greater than 76 mm are accepted as threshold
values of high-wind and heavy rain event day, respectively. We evaluated 30 high-wind events and three heavy-
rain events during the study period (Table 2).
100
Table 2: Convective and non-convective stormy days & severe rain between 1997 and 2017.
The maximum wind gust was measured as 66 knots on 23 June 1998 with no precipitation. However, in another
austral winter day, on 9 June 2007, 53-knot of gust occurred with 147 mm of daily precipitation (Figures 2 and 3).
This heavy-rain event is estimated as 20-year return period event, which caused flooding in the vicinity of
Newcastle, and named as the Pasha Bulker Storm after a ship ran aground on the Newcastle coast after strong wind
(Figure 2).
101
Figure 2: The MV Pasha Bulker aground on the reef at Nobbys Beach, Newcastle, [3].
Figure 3: Flooding at the corner of King and Steel Streets, Newcastle, on 8 June 200, [3].
On 08 June 2007 at 00:00 UTC, a low pressure center of 1004 hPa was centered on NSW (Figure 4). According
to the same map, there is a sharp trough extending to the north. The synoptic chart has a steep pressure gradient.
The 850 hPa map has a steep temperature gradient (map not shown). On the same day, at 18:00 UTC, the
pressure center was deepen to 998 hPa (Figure 5). In the 850 hPa map, the steep temperature gradient continued
(map not shown). The presence of pressure and temperature gradient intensified the wind strength and caused
the wind to blow in the form of a storm. As a result of the deepening of the low pressure center and the
continuation of its activity, it caused an excessive moisture transport over the large ocean, and the region was
exposed to extreme rainfall.
102
Figure 4: The synoptic chart 08, Jun 2007, 00:00 UTC (BOM, 2019).
Figure 5: The synoptic chart 08, Jun 2007, 18:00 UTC (BOM, 2019).
ACKNOWLEDGEMENT
The authors would like to thank BOM for the acquisition of meteorological data. In addition, Dr. Özdemir thanks
to the Scientific and Technological Research Council of Turkey (TUBITAK) for support.
REFERENCES
Alpaslan, M., Tekinay, A. A , Sağlam, M. (2003). Çanakkale Boğazı’na ait bazı meteorolojik parametreler ve
bunların yöre balıkçılığı üzerine etkileri. E.U. Journal of Fisheries and Aquatic Sciences, 20: 185-192. (in
Turkish)
Ashley, W. S, Black, A. W. (2008). Fatalities associated with non-convective high-wind events in the United
States. J. Appl. Meteor. Climatol., 47, 717–725.
BOM (2019). Bureau of Meteorology, http://www.bom.gov.au/, received date: Mar, 25, 2019.
Deniz, A., Özdemir, E. T., Sezen, İ., Coşkun, M. (2013). Investigations of storms in the region of Marmara in
Turkey. Theor. Appl. Climatol., 112: 61-71.
Dreveton, C., Benech B, Jourdain, S. (1998). Classification of windstorms over France. Int. J. Climatol., 18,
1325-1343.
103
Donat, M.G., Leckebusch, G. C., Pinto, J. G., Ulbrich, U. (2010). Examination of wind storms over Central
Europe with respect to circulation weather types and NAO phases. Int. J. Climatol., 30: 1289-1300.
Engin, İ. (2004). Trabzon'da fırtınalar. Doğu Coğrafya Dergisi, 12: 119-142. (in Turkish)
Ertüre, S. (1974-1977). İstanbul'da fırtınalar. İstanbul Üniversitesi Coğrafya Enstitüsü Dergisi, 20-21: 253-262.
(in Turkish)
Gastineau, G., Soden, B. J. (2009). Model projected changes in extreme wind events in response to global
warming, Geophysical Research Letters, 36: L10810: doi:10.1029/2009 GL037500.
Grumm, R. H. (2010). The devastating Western European winter storm 27–28 February 2010. Retrieved from
Weather Case Studies for Central Pennsylvania: http://nws.met.psu.edu/severe/2010/28Feb2010.pdf
Grumm, R. H., Lambert, B. (2010). The convective high wind event of 16 April 2010. Retrieved from Weather
Case Studies for Central Pennsylvania: http://nws.met.psu.edu/severe/2010/16Apr2010.pdf
Jungo, P., Goyette, S., Beniston, M. (2002). Dailiy wind gust speed probabilities over Switzerland according to
three types of synoptic circulation. Int. J. Climatol., 22, 485-499.
Knox, J., A., Lacke, M., C., Frye, J., D., Stewart, A., E., Durkee, J., D., Fuhrmann, C., M., Dillingham, S.,
M. (2008). October. Non-Convective High Wind Events: A Climatology for the Great Lakes Region. In Proc. 24th
Conf. on Severe Local Storms, American Meteorological Society.
Knox, J., A., Frye, J., D., Durkee, J., D., Fuhrmann, C., M. (2011). Non‐Convective High Winds Associated
with Extratropical Cyclones. Geography Compass, 5(2), 63-89.
NWS (2019). National Weather Service, https://w1.weather.gov/glossary/index.php?letter=h, received date: Mar,
25, 2019.
Özdemir, E. T., Deniz, A. (2014). A Case Study Of The Wet Microburst On August 2, 2011 At Esenboga
International Airport (LTAC), XXXII Ostiv Congress, Leszno, Poland, 30 July - 6 August 2014.
Özdemir, E. T., & Deniz, A. (2016). Severe thunderstorm over Esenboğa International Airport in Turkey on 15
July 2013. Weather, 71(7), 157-161.
Özdemir, E. T., Deniz, A. (2016). Investigation of Severe Thunderstorms Over Esenboğa International Airport
in The Last Decade. Erad 2016, European Conference on Radar in Meteorology and Hydrology, 10th – 14th October
2016, Antalya, Turkey.
Özdemir, E.T., Korkmaz, F. M., Yavuz, V. (2018). Synoptic Analysis of Dust Storm over Arabian Peninsula:
A Case Study on Feb, 28, 2009. Natural Hazards, 92(2), 805-827. https://doi.org/10.1007/s11069-018-3226-y
Özdemir, E. T., Aslan, Z. (2018). Investigation of Wind Gusts at Airports in Turkey, Ostiv Met Panel 2018, 2-3
February 2018, Bremen, Germany.
Özdemir, E. T. (2018). Investigation of the Storms of Mega City Istanbul. Selcuk Univ. J. Eng. Sci. Tech, 6(2),
331-342. (in Turkish)
Saaroni, H., Ziv, B., Bitan, A., Alpert, P. (1998). Easterly wind storms over Israel. Theor. Appl. Climatol., 59:
61-77.
Sirdas, S. A., Özdemir, E. T., Sezen, İ., Efe, B., & Kumar, V. (2017). Devastating extreme Mediterranean
cyclone’s impacts in Turkey. Natural Hazards, 87(1), 255-286.
Toros, H., Geertsema, G., Cats, G. (2010). Evaluation of Hirlam and harmonie Precipitation forecasts for the
Istanbul flash flood event of September 2009. Hirlam Newsletter, 56: 37–46.
(1) https://en.wikipedia.org/wiki/Storm, Access: Mar, 25, 2019.
(2) https://en.wikipedia.org/wiki/RAAF_Base_Williamtown, Access: Mar, 25, 2019.
(3) https://en.wikipedia.org/wiki/June_2007_Hunter_Region_and_Central_Coast_storms, Access: Mar,
25, 2019.
104
ABNORMAL CHANGES IN THE RADON FIELD IN THE UNDERGROUND
WATER OF AZERBAIJAN IN THE PREPARATION OF STRONG
EARTHQUAKES (on the example of local and remote earthquakes)
Keramova R. A., Yusifova Kh.Kh., Badalova M.G., Gurbanzadeh S.N.
Republican Center of Seismological Service (RСSSS) at NAS of Azerbaijan
Abstract
Currently, the influence of seismicity on the short-term change in the seismic geodynamic field during year-round
monitoring of fluids is an indisputable fact. It is established that the radioactive gas radon dissolved in the
underground water is an informative parameter for the forecasting earthquakes. In Azerbaijan the year-round
seismic geodynamics researches carried out from 1979 to the present. A year-round monitoring of the radon field
in the underground water was carried out during 1986-1991 and 2014-2019 at 7 objectes in the 2 seismic zones.
These waters differ in the genesis, temperature, ion-salt and gas compositions. The purpose of the our works is to
identify the criteria for the operational forecast of the earthquakes and develop software to solve this problem.It
was found that abnormal concentrations of radon in the short-period (1÷16 days), befor earthquake may exceed
background values (0÷15 Bk/m3) up to 3000%. The most important controlling conditions are: the depth of the
hearth and the magnitude of the earthquake. Abnormal concentrations of radon were found in preparation for the
realization of close hearths (ml≥4.0;mb≥4.9;h≥20 km;Δ=0÷300 km) of the Caucasus-Caspian region, and in the
hypocenters of the planetary strong earthquakes (mb≥6.0;h≥40 km;Δ=0÷8000 km: Indonesia, Japan, Chile).
Keywords: radon, concentration, earthquake, focus, concentration
Currently, the influence of seismicity on short-period changes in the seismogeodynamic field of fluids (ZFGD) is
an indisputable fact, which is proved by the results of numerous studies in different seismic regions of the world.
This area became priority after the catastrophic earthquake, which happened n Soviet Union, Tashkent in 1966.
Then, the Uzbek scientists for the first time in the world, the discovery was made–chemical and gas composition
in the underground waters prior to a strong earthquake abnormally changed for a short period time. They found
that in the period preceding the earthquake, and at the time of the catastrophe itself, the concentration of the
chemical parameters of the ion-salt composition, inert gases (helium, radon, argon, etc.) that contained in the
underground water, as well as the isotopic composition of the radioactive elements (uranium, coal, hydrogen, etc.)
variates.
As a result of the conducted researches in seismic regions of different countries it was found that one of the
informative seismic parameters is radioactive gas–radon (Rn), which is released from the strata of geological rocks
and penetrates into the air. Usually it accumulates in the basements of the houses and other buildings, so it is
recommended that they are often ventilated. This is necessary for the health of people that they were not ill
oncology. Also it should be noted that radon (Rn) has the following important features: a) well soluble in
groundwater; b) 7.5 times heavier than air; c) it is impossible to determine without special devices, since it is an
inert gas without color and smell; d) when entering a large concentration in the lungs, it causes micro–burns and
can lead to cancer; e) the half-life of it a little more than three days, but the products of its decay are no less
dangerous: among them are toxic metals-lead, bismuth, polonium.
However, it is important to emphasize another, no less important feature of radon - in strictly measured
concentrations, it not only does not harm the person, but even able to treat. In many resorts radon baths are used
for therapeutic purposes, as an analgesic and to accelerate the healing process, improve cardiac activity, as well as
- to normalize blood pressure.
In Azerbaijan year-round seismogeodynamics (SFGD) research are presented seismic geochemical and
seismogeodynamics monitoring of the fluids from 1979 to the present (2019). This fluids are represented by
105
the underground water in the boreholes, wells and mineral springs, as well as by sea water of the Caspian coast
(2001-2019). All of them have different ion-salt, gas compositions, genesis and migration conditions. The
purpose of theour research is to identify seismic forecasting criteria for the operational earthquake's prediction
and also - development of software to solve this problem.
At the present work reflects the results of year-round monitoring of the radon fields in the underground water
of Azerbaijan in the preparation of strong earthquakes in the Caspian Sea and in the Republic. Interpretation
and analysis of the databases was carried out for the period of the observations 2014-2019 on the 7 objects of
the all the year-round monitoring in the two seismic active zones (Absheron and Khachmaz district of
Azerbaijan). The studied underground waters in these regions have different ion-salt and gas compositions, as
well as genesis.
The Absheron Peninsula (Absheron), which is located close to the Caspian sea (Δ=0÷40 km), is rich in
exploited oil and gas fields. It is located on the southeastern end of the meganticlinorium of the Greater
Caucasus. Here to the informative objects for the seismic forecasting concern the following 4 objects of the all
the year-round SFGD monitoring:
a) The thermal water (T°C =45÷52) in the well “Shikhovo-1” concerns to the petroleum prospecting
wells, with the highly mineralize (M=13÷18 g/l), which migrates to the surface of the Earth from a depth of
789 m. According to the ion-salt composition, it refers to waters with a slightly alkaline (pH=7.2÷7.4) reaction
and has chloride-hydrocarbonate, sodium-magnesium-calcium composition. It is obvious that the formation of
this water occurs in sharply reducing conditions (Eh= - 360 ÷ -300).
b) Subthermal water (T°C =18÷24) in the wells “Shikhovo-2 and Surakhani” are located are located
outside of an oil deposit developed oil fields. But they very greatly in all hydrogeochemical parameters:
migration conditions, genesis, mineralization, ion-salt and gas compositions.
In particular, water in the well “Shikhovo-2” is a highly mineralized brine (M=260÷280 g/l), has a neutral
(pH=7.1÷7.2) alkaline-acid reaction of the migration medium, sodium-magnesium chloride composition, refers
to nitrogen waters of the fracture- type. Despite the considerable depth of the well h≥800 m, the water migrating
to the surface is in contact with the sea water of the Caspian Sea. This is indicated by the high value of the
oxidative properties of the water (Eh=+140÷+170) and the proximity to the sea coast (Δ=100÷140 m).
Formation water in the well “Surakhani” takes place in a strongly reducing enviroment (Eh= -300 = -270),
which is similar to the water in the well “Shikhovo-1”. But on the conditions of migration, it belongs to the
layer type and situated from the out side of the oil field (h=24÷60 m). This water has of chloride-bicarbonate,
sodium-magnesium-calcium the ionic-salt composition and refers to weakly acidic (pH=6.6÷6.7), middle
mineralized (M=5.0÷6.0 g/l) waters. In the gas composition has the hydrosulfide -hydrogen sulfide-methane-
radon.
c) The water in the boreholes “Digah” is a soft water, whith neutral (pH=7.1=7.2) acid-base reaction,
slightly mineralized (M=0.8=1.2 g/l). It has an ionic-salt composition of bicarbonate-sulfate, calcium-
magnesium-sodium and refers to cold (T°C=18÷24) drinking water, of the layer type. On the gas composition,
it is attributed to the nitrogen. It should be noted that the formation of such waters occurs in the migration
zone, which is close to the Earth’s surface (h=40÷60 m), that is, in an oxidizing environment (Eh=+60 ÷70).
Khachmaz seismic active zone is located on the end of the North-Eastern slope of the Greater Caucasus, in the
plains, which is also close to the Caspian Sea (Δ=0÷40 km), but oil and gas fields here is hitherto unknown.
Probably they are at depths more h≥2000 m. Here are the following 4 objects of year-round SFGD monitoring.
They belong to informative objects for the seismic forecasting. These waters are cold in temperature
(T°C=10÷13), artesian, that is they are pressure, formation and are formed under similar conditions of
oxidizing conditions (Eh=+90÷+120). These waters were found at the depths h=250÷300 m. They have alkaline
(pH=8.2) properties, low mineralization (M=0.8÷1.2 g/l) and, in general, similar to each other to ion-salt
composition - hydrocarbonate-sulfate-chloride. Also these underground waters are similar in the gas
composition. They have nitrogen-radon composition.
106
From the published works on the distribution in space and time of radon dissolved in the underground water
it is known that the presence of its elevated concentrations in water, soil and atmosphere indicates the presence
of a degassing zone of methane or hydrogen. In seismic zones radon is released more actively than in other
regions. Moreover, these authors found that abnormal emissions of this gas occur shortly before earthquakes.
However, it should be noted that the results of our researches not only confirm the findings of these authors,
but also complement them.
For example, on the fig. 1-8 are reflected of the variations of radon in the studied underground waters, and all the
data about past earthquakes in 2014-2017. The results, which were accompanied by anomalous concentrations of
radon, confirm that this radioactive element is extremely informative precursor to those earthquakes, the foci of
which were located in Azerbaijan and the Caspian Sea at depths h≥18 km, and in the more remote seismic activity
regions at depths h≥40 km. These data have been repeatedly confirmed during the preparation of remote strong
and catastrophic earthquakes, which happened in Indonesia, Japan, Chile during 2014-2019. These abnormal
changes have been found out our remote researches to the radon field in the underground water of Azerbaijanian
on the fon of the seismic calm within the Caucasus-Caspian region at the distance Δ=0÷300 km from our
observational objects in Azerbaijan.
References
Keramova R. A.-Seismicity and geochemical fields of the fluids of Azerbaijan. Abstract of doctoral dissertation.
Moscow. Institute of Physics of the Earth Russian Academy of Sciences. 2004.
Well “Shikhov-1” (Absheron)
107
Well “Shikhov-2” (Absheron)
Well “Shikhov-2” (Absheron)
Figure 1-3. Variations of radon (Rn) dissolved in the underground water of Azerbaijan.
Well “Shikhov-2” (Absheron)
108
Well “Surakhany” (Absheron)
Well “Surakhany” (Absheron)
Figure 4-6. Variations of radon (Rn) dissolved in the underground water of Azerbaijan.
Well “Surakhany” (Absheron)
109
Well “Arik bagi” (Khachmaz area)
Figure 7-8. Variations of radon (Rn) dissolved in the underground water of Azerbaijan.
110
CLIMATE CHANGE IMPACTS ON WATER RESOURCES OF
SHAKIZAGATALA REGION, AZERBAIJAN
Gulnur Salmanova
National Hydrometeorological Department, Azerbaijan
Abstract
Shaki-Zagatala region of Azerbaijan is characterized by small mountain streams, which are rather vulnerable to
changing climatic patterns. Analysis of the temperature and precipitation time series of the last 100 years
demonstrate negative trends in precipitation and positive trends in temperature. This circumstance may negatively
shape region’s agricultural development and reduce food scarcity. Under these circumstances, a planned
development strategy are necessary, which may include complex adaptation measures.
Keywords: climate changes, water resources, temperature, precipitation
111
CONTEMPORARY CHANGES IN HIGH MOUNTAIN LANDSCAPES IN
SOUTHERN SLOPES OF GREAT CAUCASUS, AZERBAIJAN
Sevinj Burzuyeva
Baku State University, Azerbaijan
Abstract
The landscape-ecological systems of the southern slope of the Greater Caucasus region are characterized by the
complex factors, which include rather complex geological and climatic conditions and human related activities of
last decades. The morphometric characteristics of the study area have played an important role in the formation
and development of natural and anthropogenic landscapes. It is they justify the location of the landscape
complexes, the extent of their size, the degree of disintegration, and so on. determines. In addition to the
morphometric tension assessment scale, landscape boundaries have been identified. Although global warming is
not felt in the region, climate change is likely to continue to rise along the slopes. Simultaneously, anthropogenic
activates such as overgrazing and deforestation played a major role in transformation of contemporary landscapes.
Keywords: mountain landscapes, anthropogenic activities, overgrazing
112
![[G. T. Csanady] Air-Sea Interaction Laws and Mech(BookFi.org)](https://img.pdfslide.us/doc/110x75/5534145f4a795968588b4a52/g-t-csanady-air-sea-interaction-laws-and-mechbookfiorg.jpg)
