Correction to: A novel approach for ports’ container terminals’ risk management based on formal safety assessment: FAHP-entropy measure—VIKOR model

Natural Hazards - The original article can be found online at.     

Removal of the Alphazurine FG Dye from Simulated Solution by Electrocoagulation

The removal of Alphazurine FG (AF) dye from water by an electrocoagulation process has been studied. The effect of some operational parameters, such as anode material, current density, initial dye concentration, pH of solution, conductivity, and inter‐electrode distance, on the removal efficiency was investigated. Iron and aluminum were used as anodes in the electrocoagulation cell. It was found that the efficiency of the iron anode was better than that of the aluminum anode for AF removal. The factors that affected the removal efficiency were the current density and the initial dye concentration. The removal efficiency increased from about 35% at 25 A m^–2 to about 97% at 100 A m^–2, during 4 min of electrocoagulation. The results exhibited pseudo‐first‐order kinetics for AF removal by electrocoagulation. In addition, a mathematical model was successfully established for predicting the removal efficiency. A comparison between the model results and experimental data gave a high correlation coefficient (R² = 0.9925), which indicates that the model is able to predict the removal efficiency of AF.     

Intensification of future heat waves in Pakistan: a study using CORDEX regional climate models ensemble

Future trends in the occurrence of heat waves (HW) over Pakistan have been presented using three regional climate models (RCMs), forced by three different global climate models (GCMs) runs under RCP8.5 scenarios. The results of RCMs are obtained from CORDEX (Coordinated Regional climate Downscaling EXperiment) database. Two different approaches for the assessment of HWs are defined, namely Fixed and Relative approaches. Fixed approach is defined for a life-threatening extreme event in which the temperature can reach more than 45 °C for a continuous stretch of several days; however, Relative approach events may not be directly life-threatening, but may cause snow/ice melt flooding and impact on food security of the country in summer and winter seasons, respectively. The results indicate a consistent increase in the occurrence of HWs for both approaches. For the Fixed approach, the increase is evident in the eastern areas of Pakistan, particularly plains of Punjab and Sindh provinces which host many big cities of the country. It is argued that the effect of HWs may also be exacerbated in future due to urban heat island effect. Moreover, summer time HWs for Relative approach is most likely to increase over northern areas of the country which hosts reservoirs of snow and glacier, which may result in events like glacial lake outburst flood and snow/ice melt flooding. Furthermore, the increase in winter time HWs for Relative approach may affect negatively on the wheat production, which in turn can distress the overall food productivity and livelihoods of the country. It is concluded that this study may be a useful document for future planning in order to better adapt to these threats due to climate change.     

Metamorphosis of marine organic matter in the jurassic deposits from Sharab area,Taiz Governorate of southwestern Yemen: Thermal effect of tertiary volcanic rocks

The Tertiary volcanic rocks are widely exposed in the Sharab area of Taiz Governorate, southwestern Yemen. The Jurassic calcareous shale and black limestone deposits collected closely to theTertiary volcanic rocks were investigated to provide information regarding the thermal effects of Tertiary volcanic rocks on organic materials. The bulk geochemical results indicate that the analysed Jurassic deposits are organically lean with present-day TOC values less than 0.95% and very low HI values (< 50 mg HC/g TOC), with a predominantly Type IV kerogen (inert carbon). This is attributed to thermal effect on the original organic matter as indicated by high thermal maturity data, consistent with post-mature to metagenesis stage. The present study also suggests that the high thermal maturity of the Jurassic marine deposits is due to the presence of the alkali basalts which have invaded the Jurassic rocks during late Oligocene to early Miocene (~10 Ma). Thus, the heat flow caused by Tertiary basaltic rocks further increased the temperature level and led to metamorphosis of organic matter and converted it to graphitic materials (inert carbon).     

Prediction of the Shear Wave Velocity from Compressional Wave Velocity for Gachsaran Formation

Shear and compressional wave velocities, coupled with other petrophysical data, are very important for hydrocarbon reservoir characterization. In situ shear wave velocity (Vs) is measured by some sonic logging tools. Shear velocity coupled with compressional velocity is vitally important in determining geomechanical parameters, identifying the lithology, mud weight design, hydraulic fracturing, geophysical studies such as VSP, etc. In this paper, a correlation between compressional and shear wave velocity is obtained for Gachsaran formation in Maroon oil field. Real data were used to examine the accuracy of the prediction equation. Moreover, the genetic algorithm was used to obtain the optimal value for constants of the suggested equation. Furthermore, artificial neural network was used to inspect the reliability of this method. These investigations verify the notion that the suggested equation could be considered as an efficient, fast, and cost-effective method for predicting Vs from Vp.     

Rainfall and rainy days trend in Iran

In this study, long-term annual and monthly trends in rainfall amount, number of rainy days and maximum precipitation in 24?h are investigated based on the data collected at 33 synoptic stations in Iran. The statistical significance of trend and climate variability is assessed by the Mann-Kendall test. The Linear trend analysis and the Mann-Kendall test indicate that there are no significant linear trends in monthly rainfall at most of the synoptic stations in Iran. However, the maximum number of stations with negative trends have been observed in April (29 station), and then in May (21 stations) and February (21 stations) and with positive trends in December (26 stations) and July (24 stations). The significant linear trends, with a significant level of 0.05, in annual rainfall have been noticed only at five stations. The monthly number of rainy days does not show any significant linear trend for most areas in Iran. The maximum number of stations with monthly negative trends in rainy days has also been observed in April with the minimum in December. In April, out of 24 stations with negative trends, 12 stations have a significant negative trend. Contrary to that, in October there is no significant linear trend. Most stations have positive trends in annual number of rainy days. Also, the monthly maximum precipitation in 24?h does not show any significant linear trend for most areas in Iran. The maximum number of stations with monthly negative trends in maximum precipitation has also been observed in February with the minimum in December. In spite of that, there are almost no significant precipitation variations in Iran during the last 50-odd years, the tendency of decreasing rainfall amount in April and increasing rainfall amount in December and July could indicate an eventual climate change in this area in the future.     

Spatial modelling of hazardous elements at waste dumps using geostatistical approach: a case study Sarcheshmeh copper mine,Iran

Mining activities and resulting wastes can be considered as one of the most important sources of hazardous elements in the environment. Knowledge of the spatial distribution of toxic elements in waste dump systems is necessary to assess environmental hazard and strategy. To achieve this goal, this paper investigates spatial distribution of toxic elements using statistical and geostatistical analysis. A total of 58 soil samples were collected, and the amount of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb and Zn was then determined at “Sarcheshmeh” copper mine waste dumps. In order to evaluate the presence of multivariate outliers, Mahalanobis distance technique (D ²) was applied and the multivariate outlier samples were removed. This resulted in an increase in correlation coefficient. To reduce dimension of data set, principal component analysis was applied and four principal components were determined which indicate 83.463% of the total variance of data set. Estimated PCs together with the toxic elements maps based on the ordinary kriging display aggregation of toxic elements in some parts, and validity of predictions was evaluated using the leave-one-out cross-validation method. The regression coefficients of estimated and observed values presented the reliability of the kriging estimates. Sequential Gaussian simulation method was applied for principal components due to similar results of estimated principal components and toxic elements. The results of simulation maps are almost identical to estimated outcomes.     

Prediction of blasting-induced fragmentation in Meydook copper mine using empirical,statistical, and mutual information models

One of the most important aims of blasting in open pit mines is to reach desirable size of fragmentation. Prediction of fragmentation has great importance in an attempt to prevent economic drawbacks. In this study, blasting data from Meydook mine were used to study the effect of different parameters on fragmentation; 30 blast cycles performed in Meydook mine were selected to predict fragmentation where six more blast cycles are used to validate the results of developed models. In this research, mutual information (MI) method was employed to predict fragmentation. Ten parameters were considered as primary ones in the model. For the sake of comparison, Kuz-Ram empirical model and statistical modeling were also used. Coefficient of determination (R ²), root mean square error (RMSE), and mean absolute error (MAE) were then used to compare the models. Results show that MI model with values of R ², RMSE, and MAE equals 0.81, 10.71, and 9.02, respectively, is found to have more accuracy with better performance comparing to Kuz-Ram and statistical models.     

Wetland cover change detection using multi-temporal remotely sensed data

Lake Urmia, located in northwest Iran, contains a number of wetlands significantly affecting the environmental, social, and economic conditions of the region. The ecological condition of Lake Urmia has degraded during the past decade, due to climate change, human activities, and unsustainable management. The poor condition of the lake has also affected the surrounding wetlands. This study analyzes the land cover change of one of the wetlands in the southern part of Lake Urmia, known as Ghara-Gheshlagh wetland, in the period 1989–2015 using post-classification change detection and machine learning image classification. For this analysis, three Landsat images, acquired in 1989 (TM), 2001 (TM), and 2015 (Landsat-8), were used for the classification and change detection. Support vector machine learning algorithm, a supervised learning method, is employed, and images are classified into four main land cover classes namely “water,” ”barren,” “salty land,” and “agriculture and grassland.” Change detection was carried out for pairs of years 1989 to 2001 and 2001 until 2015. The results of this classification show that there is a sharp increase in the area of salt-saturated land as well as a decrease in the area of water resources. Overall classification accuracy obtained were high for the individual years: 1989 (91.48%), 2001 (90.63%), and 2015 (88.6%). Also, the Kappa coefficients for individual maps were high: 1989 (0.89), 2001 (0.8742), and 2015 (0.84). After that, the land cover change map of the study area is obtained between 1989 to 2001 and then 2001 to 2015. The results of this analysis suggest that more efforts should be taken to effectively manage water resources in the region and point to potential locations for focused management actions within the wetland area.