LEE- Çevre Bilimleri Mühendisliği ve Yönetimi Lisansüstü Programı
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ÖgeInvestigation of SO2 pollution from coal-fired and geothermal power plants using high resolution satellite retrievals(Graduate School, 2022-01-10) Değer, Sümeyye Sena ; Kaynak, Burçak ; 501191733 ; Environmental Sciences Engineering and Management ; Çevre Bilimleri Mühendisliği ve YönetimiAir pollution, which emerged with the increasing industrialization after the industrial revolution, has become an important problem in Turkey, as in many parts of the world, due to its negative effects on human health and the environment. Air pollution causes serious health problems such as asthma, allergies, lung cancer, heart diseases, skin and eye damage and even death, as well as environmental problems such as acid rain, dust formation, turbidity and fog. In addition, air pollutants have direct and indirect effects on the climate. Known as one of the criteria and common pollutants, sulfur dioxide (SO2) originates primarily from large point sources such as power plants, volcanoes, smelters and oil and gas industries, or from residential heating with coal. Since Turkey has a significant share with 2 % of the current world reserves, it follows a coal-oriented energy policy. However, since the existing domestic lignite in Turkey has a low calorific value, it is generally used in power plants, and domestic lignite, which has a higher sulfur content than other types of coal, causes a high amount of SO2 pollution. Especially due to the high SO2 pollution levels and its negative effects on the environment and human health, the determination and monitoring of SO2 pollution in the region, like other air pollutants, plays an important role. Although air quality measurement stations (AQMSs), which are a common and old method for monitoring air pollutants, capture the diurnal changes with hourly measurements in their located region, they may be insufficient to understand the distribution of pollution especially in large areas, since they are located in certain regions and in limited numbers. In addition, the meteorological factors and land characteristics in the region where they are located, also have an effect on the ground-based measurements. On the other hand, the remote sensing technology, which was developed for the detection of air pollutants in the 1980s, facilitates the determination of the distribution of air pollutants globally and the detection of air pollution sources with its gradually developing spatial resolution and wide coverage area. The adventure of remote sensing, which started with the detection of the SO2 plumes originating from the El Chicón volcanic eruption with the Total Ozone Mapping Spectrometer (TOMS) instrument in the 1982, continued to develop with measurement of tropospheric SO2 with the Global Ozone Monitoring Experiment (GOME) instrument in the following years. With the changing and developing spatial resolution and global coverage in the following years, Atmospheric Infrared Sounder (AIRS) and the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instruments started to measure atmospheric air pollutants in 2002, Ozone Monitoring Instrument (OMI) in 2004, and GOME-2 and Infrared Atmospheric Sounding Interferometer (IASI) in 2006, and Ozone Mapping and Profiler Suite (OMPS) in 2011, respectively. The TROPOspheric Monitoring Instrument (TROPOMI), which finally started its measurements in 2019, has a higher spatial resolution of 5.5 km × 7 km compared to previous instruments such as GOME (320 km × 40 km), SCIAMACHY (60 km×30 km) and OMI (13×). In this thesis, SO2 Level 2 retrievals from the TROPOMI instrument on the Sentinel-5 platform, which is launched by European Space Agency (ESA) in October 2017, are used to monitor two-year (2019-2020) SO2 pollution in and around Turkey and determine its spatial and temporal distribution. First of all, TROPOMI SO2 Level 2 retrievals from National Aeronautics and Space Administration (NASA) Goddard Earth Sciences Data and Information Services Center (GES DISC) were processed using Phyton programming language and filtered according to the quality criteria in the TROPOMI Readme file. Spatial average was calculated with a grid resolution of 1 km × 1 km and the SO2 data were spatially matched with the grids to calculate the average monthly gridded SO2 column concentrations. Using different oversampling diameters, the 10 km radius oversampling method was applied, where the best distribution was observed for SO2 retrievals. In order to represent the pollution levels of coal-fired power plants (CPPs) and geothermal power plants (GPPs), SO2 retrievals at a distance of 10 km from the locations of CPPs were selected. Monthly statistics for SO2 retrievals were calculated using the Rstudio programming language, and then the data opened in the ArcGIS software program was visualized and average SO2 maps of Turkey for 2019-2020 were created. Emission inventory and ground measurements were used for comparisons. After the hourly ground-based measurements were selected according to the TROPOMI transit time, their daily and monthly averages are calculated. The energy production of power plants was examined using EPIAS electricity data. The impact of regional conditions was evaluated using meteorology and land use throughout all investigations. Considering the SO2 pollution in and around Turkey, hot spots are generally associated with CPPs. In October 2020, when the cleanest and highest signals was seen, the highest SO2 levels in Turkey were detected in the provinces of Kahramanmaraş and Muğla. The highest SO2 pollution in the region was observed in 10 of 18 months around Afşin Elbistan Power Plants. Following Kahramanmaraş, the SO2 pollution is at a remarkable level in Muğla, where there are three large-capacity CPPs. In addition, high SO2 pollution from CPPs was detected in Şırnak and Sivas provinces, and Aydın, Kocaeli, Malatya provinces where minor hotspots were observed, were also investigated. It has been determined that large-capacity GPPs in Aydın may also be an indirect source of SO2. High SO2 concentrations from CPPs have been observed in Turkey's district countries, Bulgaria, Iraq and Syria. The performance of AQMSs and the TROPOMI instrument were investigated by comparing the ground-based measurements where pollution is intense and the satellite retrievals around 10 km of AQMSs. Firstly, the daily SO2 ground-based measurements, satellite retrievals around the power plants and total electricity production variations of the CPPs that were temporarily closed with the decision taken on 31 December 2019 were examined and the current situation in the 2019-2020 period, the effect of the temporary shut down, the change in SO2 levels during reopening period has been investigated. Satellite retrievals often show similar changes with total electricity production, while ground-based measurements were insufficient to capture the variations. Especially the missing data at ground-based measurements and the limited number of satellite retrievals in winter months make comparisons difficult. For the selected large-capacity CPPs, the individual correlations are higher when SO2 and NO2 are compared to electricity generation, as well as high correlations between NO2 and SO2 (R2=0.62-0.96). The highest correlation between satellite SO2 retrievals and electricity production for Afşin Elbistan Power Plants with R2=0.84. SO2 pollution levels in Afşin Elbistan Power Plant, where the highest signals are observed, were investigated considering land use and meteorological factors. Ground-based measurements and meteorological factors show that the pollution in Kahramanmaraş is more intense in autumn and winter and is transported to south every season. Monthly gridded average SO2 retrievals show high concentrations (>2 DU) around the power plants in summer and autumn months. The correlation between electricity production and satellite SO2 retrievals is higher with R2=0.84 on a monthly basis than the daily correlation (R2=0.45). In the comparison made by subtracting the winter months due to limited number of SO2 retrievals, the correlation between satellite retrievals around the power plant and satellite retrievals around the AQMS (R2=0.86) is higher than the correlation between satellite retrievals around the power plant and ground measurements (R2=0.20). However, there is a low correlation (R2=0.20) between satellite retrievals and ground-based measurements around the AQMS. Similarly, the effect of three power plants in Muğla, where high signals were observed, on SO2 concentrations, the relationship between ground-based measurements, satellite retrievals and total electricity production were investigated. When ground-based measurements and meteorological factors were examined, it was seen that the intense pollution in Muğla transported to the southeast in the summer and autumn months, and to the northwest in the winter and spring months. Monthly gridded average SO2 retrievals show high concentrations (>2 DU) in the region in November, July and April 2020. While the pollution is generally distributed around the three CPPs, the AQMS can only detect the pollution originating from Yatağan Power Plant in summer and autumn months due to the land characteristics and location. Contrary to Afşin Elbistan Power Plants, correlations are low for three power plants in Muğla, but Yatağan Power Plant has the highest correlation (R2=0.27) between them. Similarly, for Muğla, the correlation between satellite retrievals 10 km around the power plant and satellite retrievals around the AQMS (R2=0.54) was found to be higher than the correlation between satellite retrievals around the power plant and ground-based measurements (R2=018). There is a low correlation (R2=0.27) between satellite retrievals and ground-based measurements around AQMS. In order to improve the ground-based measurements, it should be located close to the power plants, taking into account the wind and land characteristics. Finally, the contribution of GPPs to SO2 pollution is investigated, starting from the province of Aydın, where small hot spots are seen. The monthly average gridded SO2 distributions clearly show the pollution around GPPs especially in April, May and November months. Daily time series of satellite SO2 retrievals around the power plant also prove the contribution of geothermals to SO2 pollution with high SO2 concentrations in April 2019, May 2019, April 2020 and November 2020. In May 2019, the maximum concentrations were determined as 5.39 DU for Efeler, 3.45 DU for Ken-3, 2.54 DU for Mis-3 and 4.85 DU for Alaşehir. Concentration above 0.5 DU is observed in Ken-3 GPP with a capacity of 25 MWe in 34%, and with 165 MWe in Kızıldere GPP only in 20% of the days.
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ÖgeInvestigation of the change of NO2 pollution during the pandemic period using satellite retrievals in Marmara region(Graduate School, 2022-01-10) Ceker, Ali Osman ; Kaynak, Burak ; 501191703 ; Environmental Sciences Engineering and Management ; Çevre Bilimleri Mühendisliği ve YönetimiAir pollution has been a great problem during the history of mankind with its effects on human health and the environment. Among the major air pollutants, nitrogen oxides (NOx=NO+NO2) are still an issue with significant emissions, and their contribution especially on urban areas to ozone (O3) and secondary particulate matter formation. Satellite-based measurements have been used for monitoring of the air pollutants for obtaining information on the global distribution of these pollutants in the last decade, and their performance was increased in terms of both resolution and data reliability. In addition to being a leading country in Europe and Asia with its increasing industry and population, Turkey is struggling with air pollution with high ambient levels. Past studies showed that air pollution reaches dangerous concentrations, especially in city centers. This thesis aims to analyze the NO2 pollution in the Marmara Region, which is the most populated and developed Region of Turkey, with the help of satellite retrievals and ground-based measurements. The effect of human activities and restrictions on NO2 during the pandemic period, which is the study time interval, was also examined, and the study showed the effects of urbanization, industrialization, increasing human population, and the NO2 pollution of these parameters. A deductive approach was used in the study and Turkey, Marmara Region, and Istanbul province were examined in terms of NO2 pollution with detailed analyses, respectively. With this aspect of the study, both the high-resolution data technology of the TROPOMI instrument and the technology of measuring large areas were used. These measurements were supported by the ground-based measurements, the relationship between them was examined and the differences were interpreted. TROPOMI is an instrument onboard ESA's Sentinel-5. TROPOMI NO2 retrievals obtained from ESA were processed, and gridded monthly NO2 tropospheric columns were calculated to a uniform spatial distribution. In this thesis, both satellite and ground-based measurements were investigated for two years: 2019 and 2020. Differences between the examined periods were analyzed and the effect of restrictions during the pandemic period and different urban indicators (such as traffic density or natural gas usage for domestic heating) on NO2 pollution was examined. Ground-based measurements were also used for Marmara Region, which are located in provinces of Istanbul, Kocaeli, Bursa, Canakkale, Balikesir, Sakarya, Tekirdag, Yalova, Edirne, Bilecik and Kırklareli. Ground-based measurements were selected according to the overpass time (around local time 13:00) of TROPOMI. Also, the Marmara Region, which is the study area, was divided into 1×1 km2 grids and satellite retrievals were selected only for the grids which have urban residences and 1 km around them for further comparison with ground-based measurements. All the data used in the study were eliminated according to the measurement criteria determined by the ESA, the days deemed invalid for comparison (with less than 75% data) were eliminated, and the data obtained as a result of the process were processed and/or visualized with programming and mapping programs, and possible errors were analyzed and interpreted. Firstly, national NO2 pollution levels over Turkey were examined. As a result of the examinations performed using satellite retrievals, Marmara was found to be the most polluted Region of Turkey in terms of NO2 pollution. The most polluted provinces are Istanbul, Kocaeli, Ankara, and Izmir, and for Marmara Region, those are Istanbul, Kocaeli, Bursa, and Yalova, respectively. It was found that the winter months have noticeably higher values than the summer months of 2019 and 2020 possibly because of domestic heating in period and meteorological factors, and the most polluted month is November 2019 for all of Turkey. In addition, it has been observed that NO2 pollution in various cities in Turkey, especially in Mugla, during the summer months is equivalent to and sometimes higher than, the crowded provinces due to point sources such as thermal power plants. When an analysis was made based on districts with the clustering method using monthly averaged measurements, it was seen that the districts of the provinces with dense vehicles and populations such as Istanbul were included in the same cluster. In addition, it has been observed that the central districts of cities with less population have close pollution and show the same seasonal variation. When the same clustering method was performed using ground-based measurements and satellite retrievals separately, it was seen that the ground-based measurements did not show seasonality, and many Regions were found to have high NO2 pollution levels whereas satellite retrievals were clustered as less polluted. As a result of the correlation analysis performed using satellite retrievals and ground-based measurements, it was observed that Ground-based measurements of the Marmara Region were not correlated with satellite retrievals. They were measuring lower signals than satellite retrievals in the time intervals when the data was not missing. Especially the low correlation values of the stations in the densely populated areas have revealed that the difference in the NO2 pollution measurements of the Region is high and that improvements should be made. With the statistical analyses performed, it was observed that the highest rate of change was observed in the Istanbul Region and the NO2 pollution decreased by 60% for March, April, November, and December months compared to the previous year. When comparing the same months of 2019 and 2020 throughout Turkey decrease rates were found to be decreased in direct proportion as the population and industrialization rates of cities, while increases were seen in some eastern provinces of Turkey such as Mugla and Aydin. It is thought that the most important reason for these increases, which are intense in the winter period, is the decrease of seasonal temperatures. Both satellite retrievals and ground-based measurements showed elevated concentrations of NO2 in and around highly populated areas. When the pollution changes of the Marmara Region were examined during the COVID-19 pandemic, the effects of human behavior on pollution were observed, especially in the days of full restriction and in the associated months. Districts grouped by clustering method, from districts with dense industry to districts with high population, were interpreted with the help of these groups and examined in terms of both provincial and urban status during the pandemic period. The study has shown that situations such as domestic heating, a change in the number of vehicles, and the closure of some businesses have caused a visible effect on NO2 pollution. During the study period, a comparison was made between the pre-pandemic period and the pandemic period for the densely populated cities of Marmara provinces. As a result of the comparison, a decrease in NO2 pollution was observed in the districts, especially in November and December 2020 (weekend curfew period) compared to November and December 2019. As a result of the calculations, the decrease between 10-20% is proportional to the population. Lastly, urban indicators and NO2 pollution in Istanbul were also examined in detail for 2019. As a result of the correlations made with indicators such as population, natural gas use, socio-economic status of the districts, a high correlation was found between NO2 pollution and population and natural gas use (R = 0.81 and 0.83 respectively), and a moderate correlation between socio-economic score (R = 0.35). The fact that the strong relationship between urban indicators and NO2 pollution is high in mega cities such as Istanbul results in taking precautions, and making more detailed analyses. As shown in the thesis, Istanbul is the largest province in the whole of Europe in terms of population, urbanization, and traffic, and the study showed the NO2 pollution that the people of Istanbul are exposed to in daily life under these conditions, district by district. In addition, in this section, the correlation between ground-based measurement and satellite retrievals in Istanbul were examined, and it was understood that the Ground-based measurements had lower levels than satellite retrievals in many districts. These low levels, especially in regions with high population and vehicle traffic, were attributed to the non-representativeness of the ground-based measurements. As a result of the study, the highest NO2 values in Istanbul were found as 6.44×1015 molecules/cm2 (Gungoren) and 94.12 μg/m3 (Aksaray) annual average on a monthly basis satellite retrievals and ground stations, respectively. The results showed the extent of NO2 pollution in Istanbul, proved to be directly related to urban factors, and created an initial analysis for future studies to be repeated in more detail for the future years. In conclusion, this thesis showed TROPOMI can detect temporal variation of NO2 pollution over different districts, and the impact of COVID-19 pandemic restrictions over Turkey, specifically in Marmara Region. The results also gave important information about the evaluation and status of ground-based measurements, the relationship between urban indicators and NO2 pollution, and the changing NO2 pollution during the pandemic period. The thesis also showed that NO2 pollution in dense urban areas decreased during the pandemic period with the help of satellite retrievals. The study examined important points in this respect and prepared a basis for future studies and it explained, interpreted, and discussed the seasonal distribution of pollution and the effects of the districts with statistical analyses and spatial distribution of NO2. This thesis is the first study in terms of applied Region, high-resolution satellite retrievals, and time interval.