Konu "Air quality" ile Avrasya Yer Bilimleri Enstitüsü'a göz atma
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Ögeİstanbul'daki Evsel Isınma Kaynaklı Emisyonların Cmaq Hava Kalitesi Modeli Kullanılarak İncelenmesi(Eurasia Institute of Earth Sciences, 2016-07-07) Öksüz, Elvin ; Ünal, Alper ; 601121007 ; Climate and Marine Sciences ; İklim ve Deniz Bilimleri Anabilim DalıIstanbul is the most populated city of Turkey as well as Europe. The population is over than 14 million. The city is economical center of the country. Labour and social opportunities makes the city attractive to live and this situation causes inevitable increasing on urbanization of the province. According to authorities, it is expected that the population will be over 16 million in 2030. Due to high population, house holding is also increasing. Distribution of buildings is expending over the city. Residential heating is the main requirement of the people in cold, winter season. By the high population and urbanization, residential heating emissions significantly affects air pollution over the city. Results of many epidemiological studies proves that air pollution causes negative impact on cardiovascular and respiratory system, serious diseases such as cancer and hearth attack. Especially for sensitive people such as elders, children, babies or pregnant the effects may be higher and vitally important. This study aims to examine residential heating impact over Istanbul city by atmospheric modelling. For this purpose WRF (Weather Research and Forecasting) meteorology model and CMAQ (Community Multiscale Air Quality) chemistry and transport model was applied. The first step was preparing emission inventory as input of the model. More complete and current emission inventory provides more trustable outputs. Residential heating emissions are generated with activity data and emission factor. The calculated emissions are also compared with TNO and EMEP emissions. Another purpose of this study was developing region specific emission factors of residential heating for Istanbul. The main fuels which are commonly used in the city are determined and combustion system is analysed. Residential heating is commonly supplied from natural gas and solid fuels such as coals and wood. The coals are classified as domestic and import coal. The fuels were burned in conventional stoves that is commonly used individual combustion system in Istanbul and pollutant concentrations are measured. The measurements for solid fuels were continuous and the concentration values of each pollutants are reported minutely. For natural gas, individual combustion system was combi and concentrations were measured instantaneously. Combustion systems, burning efficiency and calorific values of the fuels are essential for burning regime and pollutant concentrations. Moreover, fuel consumption per unit time is a critical parameter for emission factor calculation. By considering all these parameters and concentrations emission factors are calculated for each fuels and pollutants. The main pollutants of this source are SOx, NOx, CO, PM10. Moreover, uncertainties of region specific emission factors that are calculated with continuous measurements are evaluated for solid fuels. Statistical methods are used in order to quantify the factors. Both parametric and non-parametric bootstrapping techniques applied and many distribution fitting models and related diagnostics were applied in the study. The emissions via using calculated region specific emission factors and WRF meteorological model outputs were used as input of CMAQ. The study episode was three months that is from December 1, 2009 to February 30, 2010. As reference case CMAQ model is applied with TNO inventory and then the model is run for the same episode with new emission inventory that is updated with calculated residential emissions. The difference of concentrations between two model outputs provide to understand contribution of the revised residential emissions over the city. The days and hours that have maximum concentration differences are determined as giving the highest response to the new inventory.
Ögeİzmir'deki Hava Kirliliğinin Atmosferik Modelleme Yoluyla Analizi(Eurasia Institute of Earth Sciences, 2016-05-02) Özçomak, Duygu ; Ünal, Alper ; 601131001 ; Climate and Marine Sciences ; İklim ve Deniz Bilimleri Anabilim DalıBesides being Turkey's third largest city with a population exceeding 4 million, İzmir is among the metropolitans that have major economic improvements. Economic growths of big cities inevitably bring some social and environmental issues as well. Among these, air pollution is the most serious and common one that both developed and developing countries are encountered. Air quality problem is affected from a lot of parameters especially in big cities. These include meteorology, topography, population, altitude, industrialization and social-economical developments. Exposure to pollution increases with the increasing human population living in developing urban areas. United Nations announced in 2000 that approximately half of the world population (48%) live in cities and every 3 years 2% growth is expected in the city populations. According to a research in 2013, twenty-three cities in the world have populations higher than 10 million. Air pollution is the existence of the foreign substances suspended in different phases of the atmosphere in varying amount, density and duration that damage human health, living organisms, and ecological balance. Therefore being exposed to air pollution became one of the inevitable results of urban life due to intense anthropogenic activities. Different researches are done on air pollution, which is a significant problem for both developed and developing countries. Especially air pollutants can threaten human health in various ways and levels. While there are high amounts of air pollutants, especially in urban areas, increase in mortality and morbidity rates has been discovered. Particularly lung diseases, neurobehavioral disorders and the effects of cardiovascular diseases are the main adverse effects of air pollution. Growing city population and industrialization level result in increasing energy demand. In densely populated areas, air pollution emission increases by rapid urbanization, transportation, energy production and industrial activities. Air quality management is one of the issues that need to be implemented urgently in the cities where strategical planning is limited or does not exist. Thus, developing emission inventories is one of the most important steps for air quality determination and improvement. These inventories are necessary tools for evaluating human and environmental risks, which are based on anthropogenic sources. Air quality control strategies are determined by air quality and emission standards defined by authorities in regional, national and global scales. Developing emission control strategies, determining applicability of control programs are required for creating reliable emission inventory. It is required to estimate the spatial and temporal density of emission sources in the best possible resolution for forming a healthy air quality control strategy and planning air pollution control reduction strategies. Having a reliable emission inventory is a primary requirement for qualified air quality management system. An emission inventory system supports pollution evaluation activities by data collection and scanning, storing, data organization. Also it creates databases for emission scenarios that will be prepared in the future. In this study, by improving existing emission inventory, activity data, which is more up-to-date and with reduced uncertainty, is compiled thus more reliable entries are provided for the air quality model. Via this model, which is run by the new inventory, temporal and spatial distribution of pollutants is investigated according to the sources. In the model, compiling of pollutants that are distributed according to the sources is set up based on sectoral distributions. Three types of source data is collected in the repository then are calculated depending on the calculation methods of source types. In the model, industry emissions are in SNAP-34 sector, traffic emissions exist in SNAP-7 sector. SNAP-7 also is divided into five based on source emissions. Regional sources named as domestic heating are calculated for SNAP-2 sector. While preparing emission inventory, for each sector required data is obtained from enterprises, calculations are done according to the related sector. Traffic emissions are calculated using COPERT 4 model, which is used in the transportation sector section of the İzmir's inventory. COPERT 4 traffic emission calculation model is commonly used for the calculation of vehicle emissions in several European countries. For industrial emissions, plants' direct emission measurements, which are provided by Izmir Provincial Directorate of Environment and Urban Planning, are calculated and used in the SNAP-34 sector of the study. For domestic heating emissions, which are provided by Izmır Provincial Directorate of Environment and Urban Planning by using the natural gas consumption and coal sales data, are calculated for SNAP-2 sector. In this study, WRF/CMAQ models included in EPA Models-3 system are used together. Meteorological and chemical transport models are run as two domains. Main domain includes whole Europe, North Africa and Eastern Asia, second domain covers whole Turkey and the resolutions are 30 km and 10 km respectively. WRF model is with 3 days spin-up timing is run for January 2010. For the result of the model, temperature and wind speed/direction data that is provided by İzmir Turkish State Meteorological Service is used and Gaziemir station performance analysis is done. When the temperature and station data are evaluated together, it is found that at temperatures in 2 m, for the trend and temperature values partially in line with the model estimations. For the evaluations of the wind speed and direction, at lower levels of wind speed, model estimates are compatible with station observations, although there are some deviations at certain days. There are some uncertainties in the model estimates regarding the wind direction and which is an expected situation. Following the evaluation of the changing model parameters' effects on emissions, air quality model is run to understand how these effects will be reflected into air quality. TNO/MACC-II inventory is used as a baseline scenario and run for 30 km and 10 km. Then CMAQ model is run once again for İzmir SNAP-2, SNAP-34 and SNAP-7 sectors with up-to-date emission data. For TNO inventory and new inventory that is created by new emission calculations, analyses are done by using different analysis methods and the affects of sectoral changes on the model results are investigated. For the emissions as TNO-OUR, total emission maps are created separately for each, the differences from each others are drawn as maps. In OUR emissions, for all pollutants changes are monitored according to the increases and decreases based on sectors. While PM10 emissions are decreased in SNAP-2, increased in SNAP-34 and SNAP-7, as a result overall PM10 emissions are increased. While CO is declined in SNAP-2 sector dramatically, it is increased sharply in SNAP-34 and SNAP-7 sectors. NOx is increased in the sectors except for SNAP-34. SO2 from pollutants is increased in all sectors. As a result of all these changes in emissions, different results are observed in the concentrations for each pollutant. In this study, distributions based on sectors takes into account for the spatial distribution of TNO inventory. Thus, the differences are considered based on the TNO spatial distribution. It is found that for all pollutant emissions and concentrations over İzmir, maximum changes are observed in city center. Through more detailed examinations, days and hours are determined where the maximum differences occur in concentrations and affects and results of these on emissions are investigated. Our findings indicate that the maximum impact of the CMAQ model's concentration results which are used by the newly developed emission inventory as an input, is observed in the İzmir city center where the most emission sources exist.
ÖgeLong-range Aerosol Transport From Europe To Istanbul, Turkey(Avrasya Yer Bilimleri Enstitüsü, ) Kindap, Tayfun ; Karaca, Mehmet ; İklim ve Deniz Bilimleri ; Climate and Marine Sciences
ÖgeWrf/cmaq Modelleme Sistemi İle Hava Kirliliğinden Kaynaklanan Avrupa'daki Tarımsal Zararın İncelenmesi(Eurasia Institute of Earth Sciences, 2016-05-02) Öztaner, Yaşar Burak ; Ünal, Alper ; 601131005 ; Climate and Marine Sciences ; İklim ve Deniz Bilimleri Anabilim DalıThe population of Europe, including non-EU countries located in continental Europe, is estimated to be around 740 million, which corresponds to 10% of the world's population (United Nations-UN, 2015). Wheat production in between 1996-2014 in Europe is 133.9 million tons (Mt). This corresponds to 21% of world's wheat production (FAO, 2015). In addition, because of Industrial Revolution in Europe an increasing trend in air pollution and pollutants that persists up to present day can be observed. This increase in air pollution is the cause of critical environmental impacts. Even though there are various studies in Europe about impacts of ozone on human health, not many studies exist to investigate ozone's impact on agriculture. Besides the negative impact on human health, exposure to high concentrations of ozone is a threat to food security and agricultural activities. Elevated O3 concentrations and changes in the concentrations affect plant life functions such as photosynthesis, transpiration, and gas exchanges. It has been found by many scientific studies that ground-level ozone exposure reduces photosynthesis of crops since it damages substomatals apoplast, cell membranes and walls. Decreased photosynthesis result in low growth rates in terms of volume or biomass. In Europe and United States of America (USA), various observational and experimental studies conducted on this subject. These studies resulted in different empirical ozone exposure equations for different parts of the world. Agricultural production losses can be calculated because of these equations. In Europe, AOT40 (cumulative summation of differences in high ozone concentrations over 40 ppb) is a widely used method which is a product of experimental studies conducted in Europe. However, in USA, W126 method (summation of weighted ozone concentrations in day light time by using sigmoidal distribution equation) is being widely used. Other than these two methods there are many other methods used around the world to calculate agricultural production loss due to ozone impacts. Some of these methods are daily summation of difference of threshold values (SUM-X method) or daily mean calculation (M-X method). There are several studies from different parts of the world that were conducted on the impacts of ozone on agricultural crops (i.e., wheat, soybean, rice, potato), their yield losses, and relative yield losses. In a study by USEPA, a 10% crop loss due to ozone was observed in agricultural production in USA. A similar study for the Europe found that the loss was around 5% in Europe. Tropospheric ozone as a regional and global threat to plants threatens our current and future food security. In literature, there are studies conducted on impacts of ozone on agricultural productions for different regions in the world. Even though these studies can show the local loss, they fail to perform well for regional impacts. For this reason, some scientific studies focused on quantifying the impact of ozone pollution on crops using regional or global atmospheric models. Low spatial resolution of global models affects the level of representation of results. Spatial resolution is better in regional studies compared to global ones, however, there are studies utilizing this higher resolution to calculate agricultural production losses. In a study, in India, conducted on impacts of ozone on wheat production loss using WRF/Chem regional chemical transportation model it was found that wheat production loss was 5 Mt for 2005. In a similar study, Eta-CMAQ regional chemical transport model was used to estimate the soybean loss in USA (2005), and found that amount of loss was in range of 1.7-14.2 %. Due to regional changes in ozone concentrations, working with a regional chemistry model yields better results for the calculation of agricultural production loss. In global models, there are many uncertainties due to low resolutions. In this study, WRF/CMAQ modeling system with three different ozone crop exposure indices (AOT40, W126, and M7) was used to estimate wheat production loss in Europe. Growing season was selected as May – July for wheat in Europe. European Environmental Agency (EEA) AirBase database ozone observations were used to calculate mean ozone values for growing season of years 2008 to 2012. The highest growing season average (45.6 ppb) was found in 2009. Averages for other years are as follows, 33.28 ppb for 2008, 29.29 ppb for 2010, 39.12 ppb for 2011, and 30.42 for 2012. This is the reason behind the selected study period growing season (May-July) of 2009. Country based total wheat production data for 2009 were obtained from Food and Agriculture Organizations (FAO). Spatial distribution of country based total wheat production data was performed by using gridded global wheat production map (for year 2000) from studies of Monfreda et al. (2008) and Ramankutty et al. (2008). For each grid cell countries contain a total value was found. These totals then divided by number of grid cells countries contain and grid cell ratios were calculated. These ratios were multiplied with total wheat production data of FAO 2009 and spatially distributed. This created map then remapped according to model area and resolution. In this study, modeling method is WRF / CMAQ modeling system with 30 km spatial resolution. As Meso-scale Atmosphere Circulation Model, WRF-ARW 3.6 (Weather Research and Forecast-Advanced Research WRF) was used with 35 horizontal levels, and with 191 cells in east-west and 159 cells in north-south direction. Also, 0.75 degree ECWMF Era-Interim Reanalysis data was used to prepare initial and boundary conditions of the model. For land-use, MODIS-30 20-class data was prepared. DUMANv2.0 emission model (developed by Istanbul Technical University, Eurasia Institute of Earth Science) was used for emission modeling. Inputs of emission model were anthropogenic, biogenic, and fire emissions. Anthropogenic emissions are created from TNO-2009 database by using DUMANv2.0 with CB05-AERO5 chemical mechanism. MEGAN v2.10 biogenic emission model was used for biogenic emissions. Fire emissions were calculated by data obtained from GFASv1.0 satellite dataset. CMAQv4.7.1 model with CB05-AERO5 chemical mechanism was used for chemical transportation modeling. WRF outputs were converted into M3MODEL structure by using MCIP (Meteorology-Chemistry Interface Processor). ICON (Initial Cond.) and BCON (Boundary Cond.) were used to create initial and boundary conditions. Inputs for these modules were obtained from ECMWF – MACC 3-hour model output with spatial resolution of 80-100 km. Open sky photolysis data were prepared with JPROC (Photolysis Rate Processor). Ozone variable was obtained from CMAQv4.7.1 model and applied to three ozone exposure indices. Gridded map of wheat production map of 2009 were multiplied with these values, thus calculated the wheat loss in each cell. Total economic loss was calculated by multiplication of calculated production loss and FAO 2009 country based wheat production price index. In order to calculate economic loss between countries, each country's 2009 GDP was normalized. The highest wheat loss was found in Russia (7.14 Mt - 11.6% and 17.3 Mt – 28%) by AOT40 and M7 methods while W126 method found the highest loss in Italy (1.54 Mt-24%). Following countries generally have higher wheat loss in every method, Turkey (6.8 Mt), France (3.47 Mt), Germany (2.45 Mt), and Egypt (5.54 Mt). According to the regional results the highest loss was found in South (8.3 Mt – 61%) and East (12.8 Mt – 37%) Europe, the lowest loss was found in Northern European countries (2.2%- 0.65Mt). Greatest losses were found in M7 method while W126 method has the lowest loss values. This provides a range (min-max) for ozone caused wheat loss in Europe. The highest economic loss was in Russia with 2.23 billion American Dollar (USD). Turkey ($2.24 bn), Italy ($1.64 bn), and Egypt ($ 1.59 bn) were other countries with high economic loss, right after Russia. Eastern Europe has the highest regional economic losses with ($1.6 bn) USD and Southern Europe ($2.8 bn). The lowest economic loss was in Northern Europe ($0.01 bn). Reason behind the high wheat loss values in Southern and Eastern Europe region is due to ozone precursor transport from Middle – Western European region via southerly – easterly meteorological systems. This causes higher ozone concentrations in Southern and Eastern Europe and affect wheat loss. Emission regulations should be more focused and applied in Middle – Western European countries.