Environmental impacts of bench blasting at Hisarcik Boron open pit mine in Turkey

This paper presents the results of ground vibration measurements carried out in Hisarcik Boron open pit mine located on the west side of central Anatolia near Kütahya province in Turkey. Within the scope of this study to predict peak particle velocity (PPV) level for this site, ground vibration components were measured for 304 shots during bench blasting. In blasting operations, ANFO (blasting agent), gelatin dynamite (priming), and delay electric detonators (firing) were used as explosives. Parameters of scaled distance (charge quantity per delay and the distance between the source and the station) were recorded carefully and the ground vibration components were measured for all blast events using two different types of vibration monitors (one White Mini-Seis and one Instantel Minimate Plus Model). The absolute distances between shot points and monitor stations were determined using GPS. The equation of square root scaled distance extensively used in the literature was taken into consideration for the prediction of PPV. Then, the data pairs of scaled distance and particle velocity obtained from the 565 event records were analyzed statistically. At the end of statistical evaluation of the data pairs, an empirical relation which gives 50% prediction line with a reasonable correlation coefficient was established between PPV and scaled distance.     

Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey

The aim of this study is to estimate the monthly mean relative humidity (MRH) values in the Aegean Region of Turkey with the help of the topographical and meteorological parameters based on artificial neural network (ANN) approach. The monthly MRH values were calculated from the measurement in the meteorological observing stations established in Izmir, Mugla, Aydin, Denizli, Usak, Manisa, Kutahya and Afyonkarahisar provinces between 2000 and 2006. Latitude, longitude, altitude, precipitation and months of the year were used in the input layer of the ANN network, while the MRH was used in output layer of the network. The ANN model was developed using MATLAB software, and then actual values were compared with those obtained by ANN and multi-linear regression methods. It seemed that the obtained values were in the acceptable error limits. It is concluded that the determination of relative humidity values is possible at any target point of the region where the measurement cannot be performed.     

The analysis of ground vibrations induced by bench blasting at Akyol quarry and practical blasting charts

Ground vibrations arising from excavation with blasting is one of the fundamental problems in the mining industry. Therefore, the prediction of ground vibration components plays an important role in the minimization of environmental complaints. In this study, 582 events were recorded during limestone production at a quarry (Akyol Quarry) during a period of time. The blasting parameters of these shots were also carefully recorded. During the statistical analysis of the collected data, three predictor equations proposed by the United States Bureau of Mines (USBM), Ambraseys–Hendron and Langefors–Kihlstrom were used to establish a relationship between peak particle velocity and scaled distance described by these prediction equations. As a result of this analysis, the most powerful relationship was determined and proposed to be used in this site. And also, this equation was used in the derivation of the practical blasting charts specific to this site as a practical way of predicting the peak particle velocity and maximum charge amount per delay for future blasting.     

Bench blasting design based on site-specific attenuation formula in a quarry

This research was performed on the quarry that will be opened to produce aggregates and rock filling material at Catalagzi region at Zonguldak province in Turkey. However, there are some structures which can be adversely affected by blasting at the quarry. These structures are a methane exploration drill hole and a house at the distances of 340 and 390 m, respectively. One of the main goals of this study is to perform a preliminary assessment of possible damage effect of ground vibrations induced by blasting on these structures by risk analysis based on ground vibration measurements. In order to propose a preliminary blast design models separately for aggregate and rock filling material production, six test shots with different maximum charge per delay were planned and fired at the quarry. In these shots, 90 events were recorded. To predict peak particle velocity (PPV), the relationship between the recorded peak particle velocities and scaled distances were investigated. During this investigation, the data pairs were statistically analyzed and a PPV prediction equation specific to this site with 95% prediction line were obtained. And also, this equation was used in the derivation of the practical blasting charts specific to this site as a practical way of predicting the peak particle velocity and maximum charge per delay for future blasting. A risk analysis was performed by using this equation. In the light of this analysis, preliminary blast design models were proposed to be used in this quarry for aggregate and rock filling material production.     

Automatic extraction of sparse trees from high-resolution ortho-images

Obtaining information about tree species distribution in agricultural lands is a topic of interest for various applications, such as tree inventory, forest management, agricultural land management, crop estimation, etc. This information can be derived from images obtained from modern remote sensing technology, which is the most economical way as compare to field surveys covering large geographic areas. Therefore, in this study, a new method is proposed for extraction and counting of sparse and regular distributed individual pistachio trees from agricultural areas on large scale from high-resolution digital ortho-photo maps, which were obtained using an airborne sensor (Ultracam-X). The input images were first smoothed by applying Gaussian filter to reduce the impact of noise. Normalized difference vegetation indices (NDVI) were then derived to obtain vegetation areas followed by Otsu’s global thresholding algorithm to obtain candidate tree areas. Further, connected component (CC) analysis was applied to segregate each object. Morphological processing was performed to fill holes within tree objects and get smooth contours, which were obtained by using the Moore-neighbor tracing method (MNTM) for each CC, while geometrical constraints were applied to undermine possible non-tree elements from output image. To further improve the segmentation results for sparse trees, a new method was applied, called quadratic local analysis (QLA). QLA helped to segment the trees, which were missed by the Otsu method due to low contrast and resulted in improved accuracy (3–6%). The obtained results were compared with well-known support vector machine (SVM) classifier. Proposed method produced slightly better results (1–5%) than SVM for extraction of pistachio trees and obtained accuracy for QLA and SVM were 96 and 91% for region 1, while 91 and 90% for region 2 respectively.     

Biodegradation of crude oil and n-alkanes by fungi isolated from Oman

Ten fungal species isolated from tar balls collected from the beaches of Oman were tested for their abilities to grow and degrade n-alkanes and crude oil. The abilities of Aspergillus niger, A. ochraceus and Penicillium chrysogenum to degrade n-alkanes (C13-C18), crude oil were compared and their mycelial biomass was measured. Significant differences were found in the utilization of C15, C16, C17 and C18 by the three fungi. Similarly, significant differences we found in the amount of biomass produced by the three fungi growing on C13, C17, C18 and crude oil. The correlation coefficient of biomass and oil utilization was not statistically significant for Aspergillus niger, significant for Aspergillus terreus and highly significant for P. chrysogenum.     

A new damage criteria norm for blast-induced ground vibrations in Turkey

Environmental problems such as vibration and air blast are often faced and discussed in mining, quarrying, civil construction, shaft tunnel, pipeline, and dam operations, where blasting is inevitable. It is necessary to establish national standards in order to minimize environmental problems induced by blasting and judicial matters in our country as it is in the USA, European Union (EU) countries, and other developed countries. This necessity and the obligation of Turkey, which has started the procedure of joining the EU, to accept EU criteria emphasize the importance of this study. In other words, the establishment of a particular national standard related with this subject is inevitable for Turkey. This will be possible only by studying and applying scientific methods and techniques by experts. This paper presents a new damage criterion norm for blast-induced ground vibrations in Turkey. In this study, first, numerous vibration records were taken in blasting operations performed at different sites and rock units. For these rock units, particle velocity predictions and frequency analysis were done. At the same time, structures in the neighborhoods of these blasts were also observed and investigated. Finally, a damage criterion norm based on risk analysis was established and proposed by using these collected data. In light of the norm to be obtained from the data that were collected in the research, it will lead the excavation work in our country to be performed in such way that they are more effective and will cause minimum environmental problems.     

Discussion on “Correction of soil parameters in calculation of embankment settlement using a BP network back-analysis model” By Zhi-liang Wang, Yong-chi Li, R.F. Shen [Engineering Geology 91 (2007) 168–177]

The paper studied by Yong-chi Li and R.F. Shen (2007) includes some problems regarding the application of the proposed Neural Network (NN) approach. A very limited number of data has been used as testing set (only 3 among 52 data sets) which should be 20–30% of the database. The NN application in the study is not a function approximation problem where same input must always lead to the same output. NNs cannot be used for such an application. Moreover the generalization capability of the NN model has not been investigated. This discussion, aims to points out controversial points of the paper.     

An Extended Approach of Particle Swarm Optimization for Shoreline Extraction from RASAT Imagery

This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment.     

Removal of Selected Micropollutants from Synthetic Wastewater by Electrooxidation Using Oxidized Titanium and Graphite Electrodes

Micropollutants cover a variety of compounds that mainly originate from the pharmaceutical and agricultural sectors. Even at trace concentrations, the discharge of micropollutants into water bodies pose a serious threat to the environment and human health. Their removal from wastewaters at treatment plants before their discharge into the environment has become one of the leading topics of research. Physical, chemical, and biological treatment methods have been listed in the literature for efficient removal of a variety of pollutants. In this study, seven micropollutants, namely 4‐tert‐octylphenol, atrazine, 2,4,6‐trichlorophenol, fluoxetine, estrone, penconazole, and di‐n‐octyl phthalate, are spiked into municipal simulated synthetic wastewater and treated by a laboratory‐scale electrooxidation (EO) system using oxidized titanium and graphite electrode as anode and cathode, respectively. Sensitive determination of the selected micropollutants by gas chromatography–mass spectrometry (GC‐MS) before and after treatment is performed after their pre‐concentration using an eco‐friendly switchable solvent liquid‐phase microextraction method (SSLPME). The pH value, applied current, and reaction period are optimized to enhance the removal efficiency of micropollutants. Results show that the highest removal efficiency of all micropollutants is obtained at pH 3, 20 min reaction period, and 3 A applied current. The operational costs are also investigated in this study.