فهرست مطالب mohsen hoseinalizadeh

Industrial development and human activities intensify the propagation of various contaminants in the environment. Heavy metals from various sources, such as industrial and agricultural activities, cause serious environmental hazards for the ecosystem. Environmental dusts are sometimes manmade, due to the activity of industries and human units, known as industrial dusts. The purpose of this study was to investigate the effect of industrial dust emitted from the Bauxite crasher located in the upstream of Jajarm Alumina Factory on the level of soil pollution. The study is focused on two heavy metals: Arsenic (As) and Nickel (Ni).

In this research, with regard to the wind roses of the area, first the direction of the dominant and erosive winds was determined. Then, two transects were considered: a transect in the direction of erosive wind (transect A) with 3 km length, and a transect in the direction of the dominant wind (transect B) with 5 km length. Samples from the soil surface (at a depth of 0-2 cm) were taken on these transects at regular intervals from the source of dust, i.e. Bauxite crusher. In total, 46 soil samples were collected. The concentration of Arsenic and Nickel in the soil samples was determined by the method of Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES), after acid digestion by chemical means in the laboratory. Finally, the indicators of land accumulation, pollution, comprehensive pollution and enrichment were used to determine the contamination level. Significance of increase in Arsenic and Nickel concentrations, as well as the other contamination coefficients were analyzed in SPSS software using ANOVA and T-test.

The Earth's accumulation index in the direction of erosive wind for Arsenic, at a distance of 200 to 250 m from the source, showed a medium to severe contamination. For nickel, from the source of dust production to 350 m distance, the area was identified unpolluted to medium contaminated. For Arsenic, in the dominant wind direction at a distance of 150 m and 250 to 450 m, moderate to severe pollution was determined. For Nickel, up to 900 m from the source of dusts, the area was identified unpolluted to medium contaminated.For Arsenic and Nickel, The pollution index in the direction of erosive wind up to 450 meters from the source of dust production shows a high to medium pollution level. And show medium and low to end transect, for Arsenic and Nickel. By this indicator, the high pollution levels in the dominant wind direction were determined for Arsenic up to 1200 m from the source of dusts, and medium pollution levels of the index of pollution was determined for Nickel, from the source of dust production up to 500 m far apart. And show medium and low to end transect, for Arsenic and Nickel. Comprehensive index of pollution in the case of erosive and prevailing winds for Arsenic and Nickel showed high and medium pollution levels, respectively. Enrichment factor in the direction of erosive wind indicated medium concentration of Arsenic at 350 and 400 m from Bauxite crusher, and a low enrichment for Nickel at all points. In the dominant wind direction, a medium enrichment factor for Arsenic was observed up to 250 m from bauxite crusher, while the level of Nickel enrichment at all locations was low. Finally, the statistical analysis justified the significance of the measured concentrations of Arsenic and Nickel, as well as the other coefficients of pollution level in the direction of prevailing and erosive winds.

The analysis of spatio-temporal series is crucial but a challenge in different sciences. Accurate analyses of spatio-temporal series depend on how to measure their spatial and temporal relation simultaneously. In this article, one-sided dynamic principal components (ODPC) for spatio-temporal series are introduced and used to model the common structure of their relation. These principal components can be used in the data set, including many spatio-temporal series. In addition to spatial relations, trends, and seasonal trends, the dynamic principal components reflect other common temporal and spatial factors in spatio-temporal series. In order to evaluate the capability of one-sided dynamic principal components, they are used for clustering and forecasting in spatio-temporal series. Based on the precipitation time series in different stations of Golestan province, the efficiency of the principal components in the clustering of hydrometric stations is investigated. Moreover, forecasting for the SPI index, an essential indicator for detecting drought, is conducted based on the one-sided principal components.

The most important human impact on the hydrological cycle of watershed is land use change. Improper management of land use increases the volume of runoff and the frequency of floods. The main purpose of this study is to investigate the effect of land use change on discharge outflow in Karkhane Watershed using the Parameter Allocation Approach. Then, utilizing the philosophy of a modelling framework proposed by Bahremand (2016), we show how calibration of most model parameters can be avoided by allocating or presetting these parameters utilizing knowledge gained from sensitivity analyses, field observations and a priori specifications as a part of a parameter allocation procedure. Evaluation of the WetSpa model performance using the Allocation Parameter Approach to simulate the daily hydrograph based on the Nash-Sutcliffe and Kling-Gupta showed that the values of these criteria are 60.18 percent and 76 percent respectively. Based on this efficiency criterion, the model in the parameter allocation approach has a good performance and shows consistency in the validation period. The results showed that land use change affects the runoff of the Karkhane watershed so that in the pessimistic scenario 2, the peak discharge has increased by 15.74% and in the optimistic scenario 3; the peak discharge has decreased by 11.33.

The effects of a change in the temperature and particularly precipitation around the world are not well known due to their complexity and spatial variations. In this research, the impacts of climate change on some climatic variables (temperature and precipitation) has been studied  in Hableh Roud Basin due to ecological sensitivity and special situation of this area and HadCM3 model data were analyzed using LARS-WG model according to A2, B2 and A1B scenarios. The seasonal variations of precipitation, minimum and maximum temperature of the synoptic stations of Firouzkooh and Garmsar were investigated in two periods of 2030-2011 and 2046-2065. Results showed that precipitation between 0.23 to 0.48 mm will increase in the near future and will decrease between 0.08 to 0.15 mm in the middle future. The minimum temperature will increase between 0.5 to 0.67° C in near future and between 1.54 to 1.97° C for the middle future. Maximum temperature will increase in near future between 0.43 to 0.6° C and between 1.47 to 1.89° C in middle future. Finally, the climatic conditions of the Hableh Roud Basin will have a significant difference compared to current conditions in upcoming periods. Therefore, regarding to this issue, as well as awareness of the direct and indirect negative effects of climate change in the various parts of the basin (agriculture, water resources, environment, natural resources, health, industry and economics), long-term planning and strategic management of new situations is essential.

In order to develop management plans for water and soil conservation and erosion control, it is necessary to identify the sources of sediment yield and the contribution of each source in watersheds. The aim of this study was to determine the contribution of different geological units to sediment yield of the Toulbane watershed in Golestan province. In view of this, samples were collected from different geological units. Collecting suspended sediment samples was carried out using Philips time-integrated sediment sampler over a one-year period (2017). Afterward, the concentration of 34 geochemical properties was examined for 41 source samples and 8 suspended sediment samples in the laboratory using the ICP device. Next, the optimal composite fingerprints were determined to discriminate sediment sources by using three statistical tests including mass conservation test, Kruskal-Wallis and stepwise discriminant function analysis. As a result, 15 tracers were selected as the optimal composite fingerprints and the contribution of different geological units to sediment yield was determined using the data derived from these tracers and implementing the multivariate mixing model. According to the results, the Qal and Jsl s.sh units had the highest contribution to sediment yield with the respective values of 68.22% and 28.75%. The Qal contains quaternary deposits and the Jsl s.sh (Shemshak formation) consists of sandstone and shale materials; both of which are highly sensitive to erosion. Hence it is necessary to carry out erosion control actions on erodible units to reduce sediment entrance to the river.