Sharif Digital Repository

This study focused on the tolerance of fungi strains including Aspergillus niger, Aspergillus foetidus and Penicillium for different metals (Ni, Co, Mo, V, Mn, Mg, Fe, W and Zn ). Then Aspergillus niger was exposed to mixture of Mo, V and Mn (at a mass ratio of 1:2:6 as approximately present in the spent refinery processing catalyst). The degree of tolerance was measured from the growth rate in the presence of various metals and compared to a control which contained no metals. Effect of type of strains, type of metal and metal concentration on adaptive tolerance of fungus was evaluated. Adaptation experiments with single metals showed Aspergillus niger tolerated up to 1000 mg/l Ni, Zn, 1500... 

In recent decades, the concentration of carbon dioxide in the atmosphere has increased. Carbon dioxide is a greenhouse gas that raises the Earth’s temperature, and it can endanger life on Earth. This study uses the 6.2 version of the Regional Atmospheric Modeling System (RAMS) with its simple biosphere model (SiB-2) to simulate and forecast the concentration of carbon dioxide over the Daintree rainforest in Australia. This analysis helps to better understand the interaction between the biosphere and the atmosphere. Results of the carbon dioxide simulation were compared and validated with the observed values of the satellite product (MultiInstrumentFusedXCO2). Based on effective parameters,... 

This study consists of two parts. In the first part, the performance of the LISFLOOD-FP model, which is raster-based, and the HEC-RAS model, are compared and evaluated. This work studied different scenarios under various digital models in two study areas, the Kashkan study basin with mountainous topography and the basin in Nebraska, which has a plain surface. The flood events are among the most severe floods in both study areas that occurred in March and April 2019. This study showed that in mountain topography, the performance of both models is good even with the 30 m high digital models. Although two models perform well, in the Nebraska basin, the performance of the two models in the... 

Forested areas can cause positive impacts on ecosystems and water supply for agriculture, electricity generation, industry, and human. On the other hand, large-scale deforestation affects the water and energy budget on a regional and global scale. Considering the importance of this issue, this study evaluates the impact of land use and land cover changes (LULC) on the water cycle components, including precipitation, evapotranspiration, runoff, and hydroclimatic variables such as soil moisture, air temperature, soil temperature, and sensible heat flux in southeastern Australia using an ecosystem model called Integrated Biosphere Simulator (IBIS). For this purpose, a two-year time span with... 

Wildfires are complex phenomena with many indeterminate and highly unpredictable driving factors that have remained unresolved. During the last decade, machine learning methods have successfully excelled in wildfire prediction as an alternative to traditional field research methods by elucidating the relationship between historical wildfire events and various important variables. The main purpose of this research is to evaluate the random forest machine learning approach and the logistic regression statistical approach to prepare a wildfire susceptibility map using data related to historical wildfires and effective variables in the Okanogan region in Washington province of the United States... 

Clustering presents valuable information in discovery of the climatic zones. To use clustering approaches, similarity measure, clustering algorithm, and clustering validity index should be determined. To find climatic zones over Middle East nad North Africa (MENA), this study performs k-means clustering with Euclidean distance as the similarity measure on four monthly precipitation datasets (CRU, GPCC, UDEL, and PREC/L) and two monthly temperature datasets (CRU, NOAA GHCN-CAMS). This study aims to validate clustering results and find a proper number of clusters. For this purpose, five traditional validity indices are examined on experimental datasets. Results show significant differences... 

In recent decades, the earth is affected by climate change and the seasons has been warmer than the last. Furthermore, the efficiency of agricultural irrigation is low, and it leads to surface water drought and decrease in groundwater level. The Middle East is known for its warm desert climate. Lack of water resources is considered the most limiting factor for sustainable agriculture and water management of irrigation is a crucial issue for agriculture in Middle East. So it’s necessary to devote the cropping pattern considering above changes. The FAO56 Penman-Monteith equation is the standardized ETo equation. A comparison was made between 8 selected methods and FAO56-PM. Thus the method... 

Heat waves and cold waves are among the most important extreme weather events, which could directly affect human health. The heat wave and cold wave are defined as a period of consecutive days (usually at least 3 days) when hot or cold air persists over a region. However, there is no universal definition of these two phenomena in different scientific references, and the available definitions differ depending on the type of temperature index, the minimum required duration, and the defined threshold temperature. This research aims to examine the main indices of heat waves and cold waves and analyze them in 6 major cities: Tehran, London, Madrid, New York, Shanghai, and Vancouver which have... 

Climate and extreme hydrometeorological studies are required to reduce risk and vulnerabilities. This study uses different cumulus and microphysics schemes in Weather Research and Forecasting (WRF) model to simulate heavy rainfall events and Cyclone Sidr in Bangladesh, where many extreme events occur. Results show that WRF can capture the cyclone track, intensity, and landfall position. In addition, regionalization and an ensemble method through Bayesian regression model (BRM) are used to improve WRF rainfall simulations. Although regionalization can improve results of the experiments with different schemes, BRM leads to the best performance. To consider uncertainty and evaluate hazards, a... 

Dry bed of lakes and surrounding areas play an important role in dust production. This work tries to develop an Aerosol Type Detection Index for the two regions of Lake Hamon in Sistan, Iran, and the Aral Sea in Central Asia. Using the parameters of Extinction Coefficient and Depolarization Ration of CALIPSO satellite, the proposed index differentiates and categorizes fine dust particles and clouds according to the physical behavior of each in absorbing and backscattering satellite rays. This index shows values between zero and 0.15 for desert dust and -0.3 to zero for polluted desert dust particles. In order to verify the accuracy of determining the type of particles by the proposed index,... 

In recent decades, especially with the increase of greenhouse gases and global warming, land degradation has become one of the important global environmental issues. Land degradation has significant impacts on soil performance, vegetation cover, crops, and even the dispersion of dust particles. Land degradation is a complex phenomenon that is affected by multiple factors. Thus, it is necessary to identify these factors and then assess the degree of vulnerability and resilience to it globally. Proper indicators can clarify the integration and effective linkage between related parameters. This study aims to develop a Land Degradation Vulnerability Index (LDVI) using parameters such as... 

Due to climate change and the increase in the emission of greenhouse gasses, the temperature of the large cities is increasing. Tehran, which is the capital of Iran and the most populated city of it, is no exception. One of the significant tools for characterizing heat in the cities is having access to the temperature field of the region. Different tools can be used for achieving the temperature field. Two methods for doing so are remote sensing and numerical models. Each one of the mentioned methods has their own strength and weaknesses. In this research, the WRF-ARW model (version 3.7) is used for deriving meteorological fields for the city of Tehran. One of the many merits of using... 

This study seeks to evaluate reliability of wind power density over Khouzestan province using WRF simulations. Based on 10 meter wind speed data extracted from eight synoptic stations over Khouzestan province, two different domains were selected in south and south-west of khouzestan as promising regions with strong wind speeds. WRF model were used to simulate atmospheric data during 2016 and over two selected regions with 2 kilometers grid spacing. Simulated data were verified with comparing to in-situ data via three parameters of RMSE, BIAS and correlation. Results indicate that model configuration had acceptable accuracy in simulating wind speed data. In this study, Monte Carlo... 

Lake Urmia, the largest domestic lake in Iran due to climate change and lack of attention to sustainable development in the past two decades, has lost a significant part of its area. The contaminated bed of dried lakes is one of the main centers of dust generation.These materials are transported along with the wind to distant areas and have an irreversible impact on human health and the environment, so it is very important to determine the sources of dust production on the lake of Urmia to reduce the adverse effects of it.In this study, after determining the arid areas in the Lake Urmia basin using the Angstrom Exponent (AE) and the Aerosol Optical Depth (AOD), an index has been introduced... 

The effect of climate change on agricultural productivity and efficiency is a major concern and challenge for the agricultural industry. Different hydrometeorological variables, such as extreme temperature, precipitation, and their variations affect the growth and yield of the agricultural products. Saffron is one of the most important agricultural products in Iran. Iran produces the largest amount of Saffron globally and Hamadan Province is one of the major saffron-producing regions in Iran. This study uses different Artificial Intelligence methods not only for clustering and sensitivity analysis of the hydroclimatological variables but also for evaluating the impacts of climate change on...