Sema Topcu

Chemical composition of rainwater at EMEP station in Ankara, Turkey

Abstract The chemical characteristics of rainfall and its seasonal variation at the EMEP (The Cooperative Programme for Monitoring and Evaluation of the Long-Range Transmission of Air Pollutants in Europe) station located in Cubuk, Ankara were studied for the period between September 1994 and December 1996. The station is located in a rural area about 50 km north of Ankara and is considered as a background station for air pollution. The rainwater samples collected were analyzed for pH, major ions concentrations and conductivity. Seasonal variations for some major ions are pronounced. Generally, maximum concentrations appeared in winter or autumn, and minimum concentrations in spring or summer seasons. The average pH of rainwater samples is around 6.3 due to neutralization. Only about 4% of the rain samples had a pH below 5.0 and about 15% of the total rainwater samples had a pH below 5.6. This reflects strong inputs of alkaline species to rainwater samples in this location. The average pH of the samples higher than 5.6 observed in rural area of Ankara is due to a high loading of calcium ions in the form of CaCO 3 because of the alkaline nature of the soil. There is a strong relationship between pHs and other ions in summer. However, in winter, a weak relationship is found between SO 4 2− , NO 3 − , Na + and Mg 2+ . On the other hand, relationships between the conductivity and SO 4 2− concentration are stronger in summer than in winter. The low concentrations of H + found in rainwater samples from Cubuk suggests that an important portion of H 2 SO 4 and HNO 3 have been neutralized by alkaline particles in the atmosphere. Weak correlations are found between the hydrogen ions and SO 4 2− or NO 3 − ions for all seasons because of neutralization of these ions with alkaline particles. The dust-rich local and surrounding limestone environment might have caused the high concentration of Ca 2+ in Cubuk area. The relatively high concentration of NH 4 + observed at Cubuk is suspected to be due to surrounding agricultural activity. This agricultural activity has been found to be effective not only in spring, but also in autumn and winter to cause neutralization of the rainwater.

The impact of anthropogenic and biogenic emissions on surface ozone concentrations in Istanbul.

Surface ozone concentrations at Istanbul during a summer episode in June 2008 were simulated using a high resolution and urban scale modeling system coupling MM5 and CMAQ models with a recently developed anthropogenic emission inventory for the region. Two sets of base runs were performed in order to investigate for the first time the impact of biogenic emissions on ozone concentrations in the Greater Istanbul Area (GIA). The first simulation was performed using only the anthropogenic emissions whereas the second simulation was performed using both anthropogenic and biogenic emissions. Biogenic NMVOC emissions were comparable with anthropogenic NMVOC emissions in terms of magnitude. The inclusion of biogenic emissions significantly improved the performance of the model, particularly in reproducing the low night time values as well as the temporal variation of ozone concentrations. Terpene emissions contributed significantly to the destruction of the ozone during nighttime. Biogenic NMVOCs emissions enhanced ozone concentrations in the downwind regions of GIA up to 25ppb. The VOC/NO(x) ratio almost doubled due to the addition of biogenic NMVOCs. Anthropogenic NO(x) and NMVOCs were perturbed by ±30% in another set of simulations to quantify the sensitivity of ozone concentrations to the precursor emissions in the region. The sensitivity runs, as along with the model-calculated ozone-to-reactive nitrogen ratios, pointed NO(x)-sensitive chemistry, particularly in the downwind areas. On the other hand, urban parts of the city responded more to changes in NO(x) due to very high anthropogenic emissions.

Analysis of surface ozone and nitrogen oxides at urban, semi-rural and rural sites in Istanbul, Turkey

Ozone (O(3)) mixing ratios were measured at three different sites (urban/traffic, semi-rural and rural/island) in Istanbul from September 2007 to December 2009 in order to determine the diurnal, monthly and seasonal variations of O(3) and nitrogen oxides (NO(x)) and to study the local and regional impacts. This is the first study that evaluates the O(3) levels in semi-rural and rural sites in Istanbul in addition to the urban sites. The diurnal O(3) variations are generally characterized by afternoon maxima (64 ppb at the urban, 80 ppb at the semi-rural and 100 ppb at the rural site) and the nighttime minimum being more pronounced at the polluted urban site. The monthly mean O(3) mixing ratios start to increase in March, reaching their maximum values in August for the urban (~25 ppb) and semi-rural sites (30 ppb). However, at the rural site, the monthly mean O(3) levels reach their maximum value in June (35 ppb). The O(3) mixing ratios for weekends were higher than those on weekdays at each site by up to 28%, possibly due to changes in VOC sensitivity and reduction in NO(x) levels. In order to better understand and characterize the relationship between air masses and O(3) levels, cluster analysis was applied to the back-trajectories calculated by the HYSPLIT model for the semi-rural site. The analyses clearly showed that major transport is characterized by northern and western clusters, particularly from the Eastern Europe and the Mediterranean region, as well as recirculation over Istanbul due to high pressure systems leading to accumulated levels of O(3). The results clearly suggest that extended measurement networks from urban to rural sites should be considered for a more comprehensive evaluation of O(3) levels.

Surface ozone measurements and meteorological influences in the urban atmosphere of Istanbul

Hourly measurements of ozone concentration in the urban atmosphere of Istanbul were carried out from February 1998 to July 1999. An assessment of the annual variations and relationships of ozone concentrations and meteorological variables was made. Annual variations were first examined without considering meteorological variables, and meteorological influences on ozone seasonal values were then examined. Furthermore, a typical ozone threshold period was analysed by considering meteorological variables for a case study. Meteorological conditions favourable for high ozone concentrations appeared when Istanbul and its surrounding region were dominated by an anticyclonic pressure system. During conducive ozone days, southerly and southwesterly winds with low speeds (daytime mean value <11m1s-1) influence Istanbul.

Surface Ozone Concentrations and its Relation to Wind Field in Istanbul

In this study, an assessment has been made on the wind speed; temperature and atmospheric pressure were analyzed by considering meteorological variables for selected high ozone cases. The Systems Applications International Meso-scale Model (SAIMM), a prognostic meteorological model was used to develop the 3-dimensional meteorological inputs to a chemical model. Meteorological conditions favorable for high ozone concentrations appear when Istanbul and the surrounding region is dominated by an anticyclonic pressure system. During the ozone favorabledays, south and southwesterly winds with low wind speed influence Istanbul. We presented wind field simulations for a case study in explaining the ozone formation mechanism over Istanbul.

Total ozone variation in south eastern Europe

This paper attempts to discuss regional changes in total column ozone over south eastern Europe and the eastern Mediterranean. In this study, we have examined the spatial and temporal variation over the region using the data of five locations in south eastern Europe and one from eastern Mediterranean location. The findings from the region support the stratospheric ozone in mid‐latitudes is strongly influenced by meteorological variability. The highest deviations in total ozone from TOMS overpass data (1979–2003) are seen in winter–spring. This result may be explained by the dynamical influences on ozone over the region in these seasons. Strong correlations found between total ozone and lower stratospheric temperatures (100 mbar) are expected due to both dynamical and radiative processes.

An Application of a Photochemical Model For Urban Airshed in Istanbul

Stratospheric ozone shields us from the sun’s harmful UV rays. But ground level ozone is a harmful air pollutant. Surface ozone is formed when NOx emitted by cars, power plants and other industrial sources react chemically in the presence of intense sunlight. High smog levels have been linked to increases in the severity of asthma attacks and other respiratory health problems. When concentrations rise, even from relatively low levels the need for increased medication of asthmatic for especially children and elderly. Otherwise ozone can initiate damage to the lungs as well as damage to trees, crops and materials. In urban areas of Turkey, there has been a decrease in concentrations of and particulates in the 1990s. This is largely due to major changes in the fuel mix used in city centers: domestic coal with high sulfur content has been prohibited for heating and replaced by imported coal. However, as a result of economic growth and despite environmental protection efforts and significant shifts in energy supply emissions of NOx are growing at a very high rate. The transportation by car is growing rapidly in the cities. According to OECD Report (1999) NOx emissions totaled 844,000 tons in 1997 figures, almost two and half times those recorded in 1980s in Turkey. NOx emissions increases have accelerated since the early 1990s. Mobile sources contribute 43 per cent to total emissions, industrial energy use 19 per cent and power generation 10 per cent. Emissions per capita (13.3 kg) are three times less than the OECD average (39.7 kg). Total NOx emissions have continued to increase. However we do not have emission inventory at national and city level for a range of pollutants, including NOx and VOCs. Istanbul has experienced a rapid growth in urbanization, industrialization and the number of motor vehicles. The city experienced serious and TSP air pollution episodes in between 1980-1995 with economical expanding. Following the banning of poor quality coal burning for domestic and industrial activities in the city, air pollution

The influence of meteorological conditions and stringent emission control on high TSP episodes in istanbul

Istanbul has faced serious air pollution problems since the mid-80s. This is mainly due to particulate air pollution coming from poor quality lignite in areas, which are heavily populated and industrialized. As a consequence of severe air pollution problems, stringent control on the emissions in the city started in the year of 1994. In this work, in order to study the relationship between emissions and meteorological conditions, an assessment of air pollution episodes and air pollution potential in the city is presented for the terms at the changed emission schedule as the influence of an emission reduction strategy. The influence of meteorological conditions on the TSP (total suspended particulates) levels is considered for two consecutive winter periods. On this occasion, the city has faced different TSP levels and episode characteristics depending on stringent emission reductions covering the banned, poor-quality lignite and fuel switching. For this purpose, climatological conditions and air quality analyses were performed.

72hr forecast of wind power in Mani̇sa, Turkey by using the WRF model coupled to WindSim

Wind power forecasting has recently become important to fulfill the increasing demand on energy usage. Two main approaches are applied to the wind power forecasting which can vary from 6 hours to 48 hours. One way is to model the atmosphere dynamically and the other method is to analyze wind speed and direction statistically. Although dynamical models forecast better than statistical models, since the former solves the problem physically, statistical models can be preferable when short term forecasting is needed due to their quick response time. Most of the currently available wind power forecasting systems analyzes the effect of wind field on wind power based on numerical weather prediction models. However, the resolution of these models is not sufficient enough when the scale of the turbines on the wind farms is considered. It is possible to overcome this problem by using computational fluid dynamics (CFD) models, which can provide both linear and nonlinear solutions on the turbine scale in terms of both wind speed and wind power forecasting. In this study, the WRF model is used for 72-hour wind speed and direction forecasting. The initial and boundary conditions of the model are provided by ECMWF operational forecasting data with the resolution of 0.25 degree. The WRF model is downscaled to 1 km resolution over Manisa Soma wind farm and 72-hour forecasts for each day of 2010 are accomplished. WindSim uses wind speed and direction values, which are solved on the nearest grid point of the WRF model to the location of a wind turbine, to simulate high-resolution wind speed values for 72hours. These WRF to WindSim coupled model results are compared to the wind power observations. As a result, we found that daily wind power generation errors per turbine vary between 90kW and 200kW for the seasons of spring, summer, and fall, whereas the error is about 150-350kW for winter. We also compared the errors of 24 hourly model outputs and we found that there is no significant difference among the first, the second, and the third 24 hourly forecasts. We finally applied model output statistics to the WRF to WindSim coupled model results in order to minimize their errors.

Total ozone over Ankara and its forecasting using regression models

The present study is concerned with the total ozone variation in Ankara, Turkey (39°57′ N; 32°53′ E) and developing a total ozone prediction model by Total Ozone Mapping Spectrometer (TOMS) and single-site aerological data (1984–2006). The daily averages of the total column ozone over Ankara show a seasonal variation, with larger values in spring/winter and lower in autumn/summer and a large day-to-day variability. In this study, in order to forecast the total column ozone over Ankara, a multi-linear regression equation was performed. Predictors are selected by stepwise regression method. The ozone value on the previous day, temperature at the 100 hPa pressure level, previous days temperature for the 700 hPa pressure level and temperature difference for 50 hPa and 500 hPa are the most important predictors. The success of monthly prognostic total column ozone models built up for Ankara is tested by using Brewer MK III Spectrophotometer data and satellite (OMI) data with the upper-air data in 2007. The Brewer MKIII has been in operation since November 2006 in Ankara. The ground-based one-year data show good agreement with the satellite OMI data.