Regional improvement of global geopotential models using GPS/Leveling data

Studia Geophysica et Geodaetica - Global geopotential models are widely used in the remove-compute-restore technique for local gravity field modeling. In this paper, a method for regional...     

Shoreline spatial and temporal response to natural and human effects in Boujagh National Park,Iran

Shoreline variation and river deltas are among the most dynamic systems in marine environments. The related different variations in spatial and temporal scales play significant roles in land planning and different management applications. Modeling the dynamics of seashore of Boujagh National Park (BNP) which is located on the southern coast of the Caspian Sea in the Sefidrud Delta (SD), considering natural and anthropogenic factors, was the main objective of the current study. To achieve this goal, a combination of remote sensing data, historical data, and numerical simulations was utilized. The BNP covers an area of 3,270 ha and includes two international wetlands, Boujagh and Kiashahr. In earlier periods, this area faced severe morphological changes whereas recently its shoreline has experienced gradual variations. Accordingly, at the first stage, the shoreline variation from 2006 to 2017 was extracted by processing and classifying Operational Land Imager (OLI) and Thematic Mapper (TM) images from Landsat satellites using the Maximum Likelihood approach. In the second stage, the two dimensional MIKE21 model was utilized to identify wave and coastal current patterns and parameters for the year 2015. Morphologically, the results showed that, the shoreline of the BNP is affected by several natural and anthropogenic factors. Seaward advancement of the shoreline occurred in zones A (east zone) and C (west zone) due to Caspian Sea Level drop and sedimentation while retreating occurred at Zone B (north zone) influenced by wave and current patterns and reduction of the Sefidrud River flows. Also, the results imply that maintaining the existing conditions results in the disappearance of a considerable part of the ecological area in the BNP. Hence, to manage and preserve the coastline of the BNP complying with the current anthropogenic and natural factors, it is vital to take necessary management measures.     

Evidence for Mountain Glacier Changes in Semi-arid Environments based on Remote Sensing Data

Countries like Iran, which are geographically situated in a rather arid and warm regions, will suffer more from global warming than countries located in humid and semi-humid regions. In such environments, analyzing the variations of mountain glaciers can reveal several aspects of climate change patterns more efficiently in comparison to the other geo-indicators. The present study reports some evidence of changes for Alamkouh glacier between 1955 and 2010 based on several mediums to high-resolution satellite images. Considering that most part of the Alamkouh glacier is covered by debris and delineating its actual area is not possible, planimetric change analysis was restricted to the clean-ice regions. The object-oriented classification approach was used to estimate the clean ice areas. This technique takes into account the shapes of the features along with their spectral patterns. Results revealed that clean ice regions of Alamkouh glacier shrank since 1955 with an overall area reduction of about 59 %. Although the general observed trend is a clean ice area reduction, some advancement was detected over the period from 2000 to 2010. During 1992–2000, the maximum reduction in the clean ice area was observed (0.08 km².a^?1). However, clean ice area of the case study has partially increased about 0.028 km².a^?1 from 2000 to 2010. Supra-glacial lake change analysis illustrated that at the surface of the glacier, lakes have been enlarged remarkably in the past 55 years (about 4.75 times greater). In addition, clean ice area and the surface area of supra-glacial lakes oscillated in compliance with each other. The findings revealed that the maximum expansion of supra-glacial lake occurred during 1992–2000, which demonstrate the glacier maximum reduction during this period. This shrinkage in the Alamkouh glacier caused an extensive glacial lake outburst flood in Jun 2011. The results of this study agree with documented changes in other mountain glaciers located in arid and semi-arid environments and they also confirm the application of mountain glaciers in climate variations monitoring over such regions.     

An alternative method for density variation modeling of the crust based on 3-D gravity inversion

In this paper we are proposing an alternative method for determination of density variations of the crust from constrained inversion of the terrestrial gravity data. The main features of the method can be summarized as follows: (i) Constructing a band-pass filter to remove the long and short wavelength signals from the terrestrial gravity data. (ii) Using an iterative method for stabilization and solution of the inverse problem. The mentioned regularization method is first validated by simulated gravity data and next the methodology is used for development of a new regional density variation model of the crust in three layers based on real gravity data in geographical area of Iran. Application of the band-pass filter to the latter data resulted the residual gravitation variations in the range of − 300 to 50 (mGal) which next based on the iterative method resulted following ranges for residual densities: −120 to 40 (kg/m³) in first layer, −40 to 40 (kg/m³) in second layer, and − 40 to 40 (kg/m³) in third layer.     

Bayesian Spatial Prediction for Discrete Closed Skew Gaussian Random Field

Most approaches in statistical spatial prediction assume that the spatial data are realizations of a Gaussian random field. However, this assumption is hard to justify for most applications. When the distribution of data is skewed but otherwise has similar properties to the normal distribution, a closed skew normal distribution can be used for modeling their skewness. Closed skew normal distribution is an extension of the multivariate skew normal distribution and has the advantage of being closed under marginalization and conditioning. In this paper, we generalize Bayesian prediction methods using closed skew normal distributions. A simulation study is performed to check the validity of the model and performance of the Bayesian spatial predictor. Finally, our prediction method is applied to Bayesian spatial prediction on the strain data near Semnan, Iran. The mean-square error of cross-validation is improved by the closed skew Gaussian model on the strain data.     

Selection of wastewater treatment process based on the analytical hierarchy process and fuzzy analytical hierarchy process methods

This paper presents an application of the analytical hierarchy process and fuzzy analytical hierarchy process methods for selecting the best wastewater treatment process. The analytical hierarchy process is one of the best ways for deciding among the complex criteria structure in different levels, and the fuzzy analytical hierarchy process is a synthetic extension of the classical method when the fuzziness of the decision makers are considered. After reviewing aerobic treatment processes operated in Iran’s industrial estates and determining the main criteria used for treatment process evaluation, they are arranged in a hierarchy structure. Selection of the best wastewater treatment process is a multi-criteria decision making problem. Conventional methods are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, the fuzzy analytical hierarchy process is proposed for dealing with the vagueness of decision makers’ judgments. The alternatives consist of extended aeration, absorption bio-oxidation, integrated fixed-film activated sludge, sequencing batch reactor, aerated lagoon. Based on the general condition of industrial estate’s wastewater treatment plants, technical/administrative, economic and environmental criteria and their sub-criteria are weighted and then criteria evaluated and priorities of alternatives have been done by analytical hierarchy process and fuzzy analytical hierarchy process methods by the use of triangular fuzzy numbers. Finally, selection of the best process and ranking of these five processes are carried out by these foregoing methods, and some sensitivity analyses are conducted to show the results’ sensitiveness to the changes of the weights of the evaluation criteria.     

Enhancement of nickel biosorption on fungal biomass by enzymatic and alkali pretreatments

Enzymatic and alkali pretreatments were employed to improve nickel biosorption capacity of Rhizomucor pusillus biomass. Pretreatment with 0.002–80 g l^?1 NaOH and 0.0001–0.1 Anson Unit (AU) g^?1 protease enhanced the biosorption capacity of fungal biomass. Increasing the concentration of NaOH from 0.002 to 5 g l^?1 improved nickel removal from 93.2 to 100.0 % while untreated biomass showed 64.6 % Ni(II) removal. Pretreatment with higher concentrations of NaOH, 5–80 g l^?1 resulted in nearly complete removal of nickel ions. Pretreatment of the biomass with 0.0001 AU g^?1 protease improved the nickel removal to over 91 %, while increasing the enzyme loading to 0.1 AU g^?1 improved the removal to 93 %. Untreated biomass removed 78.4, 63.0, and 96.3 % of chromium, copper, and lead ions, respectively, from a mixture solution of the ions. Respective metal removals were increased to 100, 98.9, and 100 % after pretreatment with 0.2 g l^?1 NaOH solution and to 87.8, 86.7, and 100 % after the enzymatic pretreatment with 0.1 AU g^?1 protease. Scanning electron microscopy analysis indicated that alkali and enzymatic pretreatments enhanced the porosity of the biomass. Furthermore, compositional analysis showed that both of the pretreatments removed a major part of fungal proteins (2.1–95.8 % removal). Glucosamine, N-acetyl glucosamine, and phosphates were the major ingredients of the pretreated biomass.     

Response of sediment-dwelling annelida community in relation to geochemical parameters in the Gorgan Bay,Caspian Sea

This study aimed to investigate the population of annelida communities in relation to environmental factors and heavy metals accumulated in sediments of the Gorgan Bay. The pollution load index and potential ecological risk (PER) were calculated. The results indicated mean concentrations (ppm) of heavy metals were (mean ± SD) Pb: 11.5 ± 4.88, Cu: 18 ± 8.83, Zn: 42 ± 22.15, Ni: 29.20 ± 14.68, Co: 10.56 ± 14.68, As: 7.77 ± 2.12, Sr: 1,449 ± 902.59 and V: 26.64 ± 10.25. Considering PER, sediments of the Gorgan Bay had low ecological risk. Based on abundance data, dominant species were Streblospio gynobranchiata, Nereis diversicolor, Tubificoides fraseri and Tubificidae unknown, respectively. Results of redundancy analysis displayed that T. fraseri and N. diversicolor were associated with high values of Sr. All the species were negatively correlated with As. There were positive correlation between S. gynobranchiata and N. diversicolor with values of clay, salinity, depth and silt. The present study provided the relative importance of heavy metals and environmental variables which partly assist in structuring assemblages of annelida in a transitional area.     

Understanding experts’ views and risk perceptions on carbon capture and storage in three European countries

The challenge of making the transition to a sustainable energy regime is not limited to engineering; it has important social and political dimensions. Therefore, implementation of new technologies, such as carbon capture and storage (CCS), requires not only economic and technical capacities but also an understanding of social factors. These factors include experts’ views and risk perceptions. Understanding them will contribute to the risk governance of CCS by demonstrating who is concerned about what and why with respect to CCS and how risk perception and stakeholders’ concerns vary in different countries. This research is based on analysis and mapping of data collected from case studies of three countries: Germany, Norway and Finland. Our analysis shows that in countries where opposition to CCS is the strongest, like Germany, risk perceptions can be driven by such factors such as the lack of trust and doubts about the need of the project. At the same time as in countries with moderate opposition, such as Norway or Finland, risk perceptions are more connected with the risk for investment. We also conclude that the strongest polarization in risk perceptions is among NGOs in different countries, followed by scientists. The positions of private sector stakeholders and government are more homogenous. Such large variation in risk perceptions of experts could be influenced by several factors, including cultural orientation, attitudes and views of stakeholders, and the social, political and technical settings for deployment of technology in each country.