Effect of diurnal changes in VOC source strengths on performances of receptor models

Introduction

The effect of diurnal changes in strengths of volatile organic compound (VOC) sources on the performances of positive matrix factorization (PMF) and principal component analysis (PCA) was investigated using ambient measurement results that were taken during daytime and nighttime hours between March 24 and May 14, 2011, within Davutpasa Campus of Yildiz Technical University (Istanbul, Turkey).

Methods

Forty-five VOC species, ranging from C₅ to C₁₁ in volatility, were measured in the samples, 40 of which are included in the analyses. Ambient samples were grouped as daytime, nighttime, and all day datasets, and both PMF and PCA were applied to each dataset. A total of six source groups were extracted from each dataset: solvent use, general industrial paint use, gasoline and diesel vehicle exhausts, and biogenic as well as evaporative emissions. Estimated source contributions showed great diurnal variations.

Results

The results suggested that extraction of possible sources by PCA depends greatly on the number of samples and the strength of the sources, while PMF produced stable results regardless of number of samples and source strengths.

Conclusion

Although PMF was unable to resolve gasoline vehicle and evaporative emissions, it was found to be successful in explaining diurnal fluctuations in source strengths, while the performance of PCA depends on the strength of emission source.     

A detailed investigation of ambient aerosol composition and size distribution in an urban atmosphere

This research was executed between March 2009 and March 2010 to monitor particulate matter size distribution and its composition in Istanbul. Particulate matter composition was determined using ion chromatography and inductively coupled plasma optical emission spectrometry. The sampling point is adjacent to a crowded road and the Bosporus Strait. Two prevailing particulate modes are found throughout PM₁₀ by sampling with a nine-stage low-volume cascade impactor. First mode in the fine mode is found to be between 0.43 and 0.65 μm, whereas the other peak was observed between 3.3 and 4.7 μm, referring to the coarse mode. The mean PM₁₀ concentration was determined as 41.2 μg/m³, with a standard deviation of 16.92 μg/m³. PM_0.43 had the highest mean concentration value of 10.67 μg/m³, making up nearly one fourth of the total PM₁₀ mass. For determining the effect of traffic on particulate matter (PM) composition and distribution, four different sampling cycles were applied: entire day, nighttime, rush hour, and rush hour at weekdays. SO ₄ ^?2 and organic carbon/elemental carbon proportions are found to be lower in night samples, representing a decrease in traffic. The long-range transports of dust storms were observed during the sampling periods. Their effects were determined analytically and their route models were run by the HYSPLIT model and validated through satellite photographs taken by the NASA Earth Observatory.     

Metal accumulation in sediment,water, and freshwater fish in a Dam Lake

Metal concentrations were determined in water, sediment, and freshwater fish samples (Squalus cephalus, Barbus esocinus, and Barbus xanthopterus) collected from Karakaya Dam Lake, Turkey, to estimate the risk of human consumption and pollution. Metal concentrations differed between the species (p??Zn?=?Cu in water and Fe?>?Zn?>?Mn?>?Ni?>?Cu in sediment. In general, the accumulation order of elements in the tissues all of the species sampled were found as Fe?>?Zn?>?Se?>?Mn?>?Cu?>?Ni?>?Cd in muscle, Zn?>?Fe?>?Mn?>?Se?>?Cu?>?Ni?>?Cd in gills, Fe?>?Zn?>?Se?>?Mn?>?Cu?>?Ni?>?Cd in liver and gonad, and Zn?>?Fe?>?Cu?>?Mn?>?Se?>?Ni?>?Cd in kidney. It was concluded that the fish from the dam lake are not heavily burdened with metals, but they should be controlled periodically to avoid excessive intake of trace metals by humans, and to monitoring the pollution of aquatic environment.     

Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method

Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth’s surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~?88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning.     

Unsustainable urban development for Zonguldak metropolitan area (NW Turkey)

Since Turkey is located on a region that is prone to the risks of natural disasters like earthquake, flooding, and avalanche; a majority of the residential areas are facing these risks at various levels. Before determination of these risks, taking action in order to decrease the vulnerability levels of the residential areas will help keep the damage at the minimum level in case of a disaster. Urban planning decisions which are made in accordance with vulnerability studies aiming to determine natural disaster risks will not only help prevent loss of life but also help decrease negative social and economic effects of disasters. The Zonguldak city has been chosen as a case study area since Zonguldak metropolitan area has endured almost all kinds of threats that a city can face. In this study disaster-producing factors in the area are primarily considered which can be named as topography, destruction of forest lands, geological and karstic structure, mining activities, and misuse of the land, and later risk assessment is conducted with geographic information system (GIS). It has been assessed that more than half of the buildings within the study area were constructed in areas not suitable for housing. It is concluded that there is a need for urgent urban development plan for the city.