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Tourism is one of the most important economic sectors in the world and is heavily influenced by climate conditions. Insight into tourists' weather preferences within contexts of extremely arid climates is particularly useful, not only for regions and tourism destinations that currently display such characteristics, but also for regions and tourism destinations for which climate change forecasts predict radicalization in terms of their weather conditions. The objective of this study was to identify the weather preferences of Iranians in relation to nature-based tourism (NBT) in regions with extremely arid climates in Iran. To achieve this aim, the study used a survey to identify the optimal preferences with respect to temperature (maximum and minimum), rainfall, wind speed, sunshine hours, and cloud cover, as well as the thresholds past which the conditions in relation to these elements were considered intolerable. The results of this research may be useful for designing tourism climate indices and/or associated rating scales—adapted to the segment under consideration—that enable the present and future evaluation of the tourism suitability of a region's climate. [ABSTRACT FROM AUTHOR]

Hydrocarbon exploration has long been based on such costly and time-intensive methods as geophysical surveys, geological studies, and drilling. In recent years, however, researchers have started to consider such inexpensive alternatives as surface geochemistry for hydrocarbon exploration. Some 100 years ago, the leakage of hydrocarbons onto the surface in the form of micro- and macro-seepages motivated researchers toward drilling a well in the Khourian Desert in the south of Semnan Province, Iran. Upon drilling the well, researchers found evidences of non-released (free) hydrocarbons. These findings drove further study of the area using surface geochemistry while considering the nearby hydrocarbon accumulation in Qom Formation. Conventional and indirect surface geochemical methods provide an insight into the relationship between surface and subsurface hydrocarbons. In the present work, the results of the Rock–Eval pyrolysis showed total organic carbon (TOC) values in the range of 0.31–4.13 wt.% and S1 peaks between 0.07 and 27.35. Sulfur isotope analysis showed a sulfur isotopic value of −0.4. The study of hydrocarbon-oxidizing bacteria showed the presence of bacterial colonies in MSM at 1.22 × 106 cfu/g of soil sample. We further investigated surface changes due to the presence of free hydrocarbons and pH variations (4.9–8) resulted from the changes in the concentrations of calcium carbonate and iron. According to the results and given the presence of organic sulfur in the samples, the occurrence of Gach-i-turush and alike phenomena was proposed in this area. The results of geo-microbial prospecting method, surface secondary changes, and sulfur isotope studies were well in agreement with the characteristics of the existing hydrocarbon reserves in this area. Surface geochemical surveys can precede other geochemical and geophysical surveys to identify surface anomalies and hence focus on more probable locales of hydrocarbon accumulation in the Khourian Desert, central Iran. [ABSTRACT FROM AUTHOR]

[Display omitted] • A stream sediment geochemical survey is conducted in a pilot area in central Iran. • Elastic velocities, porosity, and Schmidt hammer rebound values are measured. • An index for rock weathering rate in the case study is presented. • Introducing the weatherability explains a part of geochemical variability. • Regression model has some limitations highlighted by the results. The chemical composition of stream sediments is heavily influenced by weathering processes occurring in upstream lithological units. Despite their importance, these processes are frequently ignored in the examination of stream sediment geochemical data when identifying mineralized zones. Instead, existing geochemical background estimation procedures rely on the area size of upstream rocks as an indicator of their contribution to elemental concentrations of sediments. To address this limitation, a stream sediment geochemical survey was conducted in a pilot area in central Iran, and the physico-mechanical properties of upstream rock types, including elastic velocities, porosity, and Schmidt hammer rebound values, were evaluated. A new weathering index, "W ij ," was developed, utilizing proxies of rock weathering to estimate the geochemical background attributed to lithology at sediment sampling sites. The regression model was constructed by combining weathering proxies (W ij) with other independent variables, including the presence or absence of rocks in catchments, area size (X ij), and the weathering-corrected contributing factor (X ij W ij). The results suggested the significant capability of weathering proxies in explaining the geochemical variability of major elements such as Al, K, Fe, Ca, and Na. However, the regression model using weathering-corrected contributing factors delivered better overall accuracy than other independent variables. Nevertheless, our results also identified some limitations of the application of regression model in stream sediment data analysis. [ABSTRACT FROM AUTHOR]

The purpose of equivalence assessement is to recognize a significant shift between values of the same variables (elements in geochemical surveys) in two datasets. To merge two or more independent datasets that are somehow linked together to create a new integrated dataset, the significance of the difference between datasets must be determined. Merging data originated from two or more geochemical surveys can be highly beneficial to establish geochemical maps with an increased resolution and/or a covered area. Different methods of sampling, preparation and analysis are being used in various geochemical surveys which have a major impact on the measurement of the concentration of elements, and there might be a systematic shift in the concentration of the same elements. Therefore, studying the presence of a significant shift between datasets, and leveling them as a pre-processing stage is essential to combine geochemical data and provide an integrated map of a few independent surveys. While combining datasets to provide integrated maps, not assessing the equivalence and leveling the datasets leads to invalid maps. Determining the equivalence assessment between datasets is done by different methods. Quantile–Quantile Dispersion Diagram and Multiple Frequency Histogram methods have already been introduced by researchers. These methods are visual and dependent on expert judgment. In this study the Fisher test, T-student test, and Quantile–Value Diagram (QVD) are introduced to assess the equivalence between two datasets for the first time. Fisher and T-student tests are applied to compare the variance and average of the same elements in two datasets. In this study, we propose an original method for assessing the equivalence. QVD is introduced as a new method of determining the shift between multiple datasets. The case study is the equivalence assessment and shift determination between two independent geochemical surveys in north of Sarduiyeh and south of Rayen sheets (Hanza, southern part of Urmia–Dokhtar metalogenic belt, Iran). The equivalence assessment was performed for twelve elements including Zn, Pb, Ag, Ni, Bi, Cu, As, Sb, Co, W, Mo, and Mn. Based on Quantile-Quantile Dispersion Diagram and Multiple Frequency Histogram methods, some elements of the two databases were considered as equivalent, but the analysis of QVD method shows a significant shift for them. Fisher and T-student tests confirm the results of QVD. QVD is an exact method for the equivalence assessment that is not dependent on the expert judgment. Eventually, Fisher test, T-student test, and QVD are recommended simultaneously to assess the equivalence between datasets. [ABSTRACT FROM AUTHOR]

The weighted mean and the multiple regression techniques are two methods that are employed to estimate elemental background concentration of lithologies upstream of stream sediment samples and the background value of elements at catchment basin outlets due to the lithology. However, these techniques have not previously been validated against real background values by sampling from lithological units. A geochemical survey was completed in central Iran by collecting samples from stream sediments along with rock samples from upstream lithologies. The accuracy and the precision of both techniques were examined graphically and statistically. The results demonstrated the advantage of multiple regressions over the weighted mean method. However, estimated background values from both techniques show high deviations from the analyzed values for some elements including Cr, Ni, Pb and Zn. While the weighted mean method is not as sensitive as the multiple regression approach to small areas of lithological units (independent variables), the estimated background values emerging from the weighted mean technique follow narrow ranges among different lithological units and cannot highlight the differences between elemental concentrations in various lithologies. However, multiple regression analysis is more successful than the weighted mean method in estimating expected background values of sediments at the catchment basin outlet. The multiple regression method uses the areas of all lithologies to estimate the background value of a particular lithology, whereas in the weighted mean method, only the area of the lithology is involved in the background estimation of that lithology. The existing equations essentially take into account only mechanical dispersion but overlook hydromorphic dispersion of elements in fluvial systems. Moreover, these equations only use area of rock units as the weighting factor or independent variables. Several parameters such as rate of weathering and erodibility, transportation mode, scavenging effects, the sediment delivery ratio of a catchment basin and each lithological unit control sediment chemistry at the basin outlet and should also be taken into account. [ABSTRACT FROM AUTHOR]

Abstract The Shahin Dezh Region is one of several areas prospective for geothermal energy in the West Azerbaijan Province of Iran. Hot spring spewing fluids at 30 °C is regarded as the first surface signature for the existence of a subsurface geothermal reservoir in this region. To determine the geothermal energy potential for the region we carried out geological, geochemical and geophysical surveys in the study area. Field observation, thin section studies and XRD analysis reveal the existence of a zone of pervasive hydrothermal alteration in this region. Based on the geochemical analysis, the hydrothermal spring fluids falls into the bicarbonate water family. The results of geothermometric calculations indicate that geothermal reservoir temperature ranges between 40 and 51 °C. Euler deconvolution of geophysical data over the region suggests the reservoir is shallow. This shallowness together with groundwater mixing are factors that played a role in decreasing the reservoir temperature. Integrating geological, geochemical and gravity studies revealed that geothermal reservoir contains 2.3 × 107 kJ thermal energy. Highlights • Geothermal susceptibility of Shahin Dezh area is considerable. • All the geologic, geochemical and geophysical data confirmed existence of hot reservoirs. • The geothermal prospect contains 2.3 × 107 kJ thermal energy. • The site can provide a wide variety of applications from hot fluid. [ABSTRACT FROM AUTHOR]

The sample catchment basin approach (SCBA) is one of the methods mainly used to assess the expected chemical composition of a stream sediment sample considering the geolithological variability of the catchment basin upstream of its collection point. In the original SCBA, the catchment surface considered for the purpose is limited to the area between two subsequent collected samples; in the true sample catchment basin approach (TSCBA), the catchment area of each collected sample is limited upstream only by the actual watershed. In both approaches, the dilution is generally assessed in relation to the extension of the single geolithological units falling within the sample catchment area used. However, it makes sense to think that when multiple geolithological units are outcropping upstream of a sampling location, the sediments originating from the ones closer to the collection point (which have traveled a shorter distance) could have a major influence on the geochemical composition of the samples. It is plausible that the degree of dilution occurring during the transport from the source to a given point could also be a function of the distance traveled by the sediments along the fluvial pattern. This also holds in the case of mineralization occurring within the catchment: the farther a mineralization is from a sampling point, the more its geochemical signal should be diluted at the sampling site. In the present study, using the TSCBA, a modification of the existing algorithm is proposed to include both the extension of the geological units and their position relative to the catchment outlet (represented by the sampling point). The territory around Feshark village (Isfahan, central Iran), where stream sediment and rock samples have been collected and analyzed, has been used as the study area. The geochemical background values (corresponding to the expected geochemical values following dilution) for each stream sediment sample were determined using the modified algorithm. The results were compared with those obtained by applying the original equation to the same dataset. The results demonstrated that the new equation could more accurately estimate background (expected) concentrations at the basin outlet, showing a better performance of the new method compared to the original one. [Display omitted] • Sample catchment basin has been employed to estimate background values. • Spatial position of lithological units were taken into account. • A new equation has been proposed for background value calculation. • The Bhattacharyya distance was used to evaluate the efficiency of new equation. [ABSTRACT FROM AUTHOR]

This study reports a comprehensive approach for analysis of increasing hydrogen sulfide (H 2 S) concentration after 10 years of sweet gas production from Kangan and Dalan formations (Khuff) in a gas field. Increasing H 2 S concentration as a toxic and corrosive component in gas phase will affect the project economics and needs immediate action in terms of production/surface processing facilities and also prediction of future gas contamination. Thus, a comprehensive study was conducted to determine the possible mechanisms behind increasing H 2 S concentration in some wells. Geological, engineering and field data were analyzed and all possible contributing parameters were studied in an integrated approach. All possible reasons including producing formations, water level movement, cumulative gas production, individual well gas rate, water composition/production, well completion (flow behind casing, leakage, etc.), faults, regional production, etc. were examined. Migration from a deeper gas formation was concluded to be the source of local increase in H 2 S concentration. To confirm the hypothesis, sampling of gas from 10 wells were performed and a geochemical survey was conducted based on sulfur isotope. Results showed a relation between increasing concentration of H 2 S and sulfur isotope values. Heavier values of sulfur isotope were obtained for those wells showing most increase in H 2 S concentration. In addition, sulfur isotope of contaminated wells were in agreement of that for deeper anhydrite formation. Results of geochemical analysis confirmed gas migration from deeper formation which was proposed by geological/engineering survey. • Integrated geological/engineering and geochemical approach for determination of source of H 2 S increasing in a carbonate gas field. • Sampling and sulfur isotope analysis in gas phase. • Agreement between H 2 S increasing tend and heaviness of sulfur isotope in gas phase (δ34S H2S). • Migration from deeper anhydrite formation has been confirmed. [ABSTRACT FROM AUTHOR]

Heavy metal contamination has become an important environmental hazard in recent years. In this study a soil-based geochemical survey in the mining district of Ahangaran Malayer (Hamedan province, west of Iran) was carried out. The concentrations of Pb, Zn, Cu, Cd, As, and Sb were determined in 40 topsoil samples. A number of calculation methods have been put forward for quantifying the contamination level of heavy metals on the basis of geoaccumulation index (Igeo), enrichment factor (EF), pollution index (PI). The calculated results of Igeo and EF of heavy metals reveal the order of Igeo is Pb > Sb > Cd > As > Cu > Zn and the order of EF is Pb > Sb > Cd > Zn > Cu > As. The high Igeo and EF for Pb, Sb, and Cd in the soils indicate that there is considerable Pb, Sb, and Cd pollution, which mainly originates from mining activities. The Igeo and EF of Zn, As and Cu are low and the assessment results indicate this pollution is not significant. Assessment results of PI indicate soils are seriously polluted. [ABSTRACT FROM AUTHOR]

• A multivariate modeling of primary geochemical haloes in a gold ore deposit was performed. • A new approach was used to provide anomaly model based on the MAF and U-spatial statistic methods. • Provides new target area for exploration under cover in the study area. An accurate separation of anomalous areas (values) in primary geochemical halos with heterogeneous spatial variations requires an appropriate algorithm that considers the complex patterns and multivariate relationships of the input geochemical data. There are several problems in multivariate modeling of geochemical compositional data, because such data present spurious values of spatial correlation between the variables. To address this problem, this paper proposes an improved U-spatial statistic algorithm for 3D multivariate anomaly modeling of the geochemical dataset with compositional nature at the Sari Gunay epithermal gold deposit, NW Iran. To perform 3D multivariate modeling, isometric logarithmic ratio (ilr), as an effective method to transform compositional data from the simplex to real space, and minimum/maximum autocorrelation factor (MAF), as a multivariate geostatistical method, were used in an integrated analysis. In comparison to the other separation techniques, this integrated approach has an advantage to control the heterogeneous spatial variations in the input data. In this approach, we improved the U-spatial statistic method by using the variogram tool theory. By using this approach, we identified the primary geochemical haloes associated with Au-As-Sb-Hg front halo elements, Cu-Ag-Pb near-ore halo elements and Ni-Co tail halo elements at the Sari Gunay gold depsoit. The results were validated by using contrast coefficient and exploratory index tools. By examining the 3D multivariate primary anomalous geochemical halos, zones of possible hidden epithermal gold and porphyry copper–gold mineralizations were recognized at this deposit for future exploration. [ABSTRACT FROM AUTHOR]

Merging geochemical datasets of a few adjacent areas (areas with uniform geology) originated from two or more independent geochemical surveys can be highly beneficial to generate the integrated geochemical maps. To merge two or more independent datasets that are somehow linked together and create a new combined dataset, the significance of the shift between these datasets must be determined. Method of sampling, sample preparation, and chemical analysis are among the factors that critically impact on the measurement of the element concentration, thus explaining the inconsistency in the concentration of the same elements in various geochemical surveys. Therefore, studying the presence of a shift between datasets and leveling them as a pre-processing stage are necessary to combine geochemical datasets of adjacent areas and generate the integrated geochemical map. The purpose of assessing the equivalence is to recognize if there is a significant shift between values of the same variables (elements in geochemical surveys) in several datasets. The assessment is done by different methods, such as Quantile-Quantile Dispersion (QQD) diagram and a visual method dependent on expert's judgment to be introduced in this study. In this study, the Fisher test, T-student test, and Quantile-Value Diagram (QVD), a valid method showing the least shift between multiple datasets, were applied for the equivalence assessment between two or more datasets. Fisher and T-student tests were run to compare the variances and means of the same elements in two datasets from adjacent areas. The aim of the study was to generate an integrated geochemical map out of two independent geochemical surveys, in the north of Sarduiyeh and south of Rayen geological sheets with uniform geology (southern part of Urmia–Dokhtar metallogenic belt of Iran), to identify new anomalous areas. The equivalence assessment was performed for twelve elements, including Zn, Pb, Ag, Ni, Bi, Cu, As, Sb, Co, W, MO, and Mn. Based on QQD diagram method, some elements of the two databases such as Pb, Ni, and Bi were considered as equivalent, yet the QVD method showed a significant shift for them. Fisher and T-student tests confirmed the results of QVD. All the chemical elements of this survey exhibited shift in the adjacent maps and therefore required to be adjusted. For so doing, QQD diagram was drawn based on quantile pairs of shifted and reference datasets. A linear regression equation fitted in quantile pairs determined the relationship between the shifted and reference datasets. To adjust, it is important to select the reference dataset, which is the one with the best analysis method. Yet, it is difficult to select the reference dataset when the analysis method of the two geochemical surveys is the same. To timely address the problem, one of the two datasets was selected as the reference and an integrated geochemical map was separately generated for each element. It is deduced that if the dataset with larger quantile values is selected as the reference, more anomalies are shown, and vise verse. This approach, however, is based on the expert's judgment and may lead to unreal and unusual results. In another approach, which is more objective and cost-effective, the dataset, the median of which is close to the average of continental crust or the regional background if available, is used as the reference. This led to just one integrated geochemical map. Median Absolute Deviation (MAD) method was then applied to calculate the threshold of elements in integrated geochemical maps. Unlabelled Image • Estimating a shift between values of the same variable in two geochemical datasets • Merging data originated from two or more geochemical surveys • Fisher test, T-student test, and Quantile-Value Diagram (QVD) are used. • QVD is not dependent on the expert judgment. • QVD can compare several datasets simultaneously and detect the least shift. [ABSTRACT FROM AUTHOR]