Sharif Digital Repository

An assessment of trends in main air pollutant concentrations (including CO, SO2, NO2, O3, PM2.5, and Asbestos) is conducted for the years 2005–2016 for the city of Tehran, Iran. The focus has been on the contribution of anthropogenic emissions to the observed trend, particularly the role of related mitigation plans implemented in the period of interest. A significant decreasing trend (about 50%) was observed in CO and SO2 concentrations during the considered time interval, which was explained by improvement plans in fuel quality and vehicle emission standards. While a substantial elevation (more than 50%) in NO2 levels was detected over the study period, variant trends were observed during... 

Contaminant materials in lubricants are signs for prediction and measurement of wear in engines. Therefore oil monitoring is considered as one of the most effective techniques for maintaining the heavy equipments. However based on oil analysis data, the identification of engine problem is very hard due to different contribution factors. Hence, this paper is purposed to analyze the wear behavior of some sets of selected heavy equipment engine based on documented oil analysis data during two years in different conditions to track engine failures using trend analysis. Furthermore the selected equipments are divided into two major groups (plantation and forestry, and general construction) based... 

Lake Urmia is the second-largest hypersaline lake in the world. There has been a drastic water level drop of 7.2 m from 1995 to 2016. Beginning in October 2013, the Lake Urmia Restoration Plan (LURP) launched a 10-year program. An increase in water level and a relative improvement in Lake Urmia condition has been observed since 2017. It is an undecided and controversial issue whether the recent positive trend of Lake Urmia has been due to the LURP activities or it is a natural contribution of climate factors variations. To shed some light on this issue, we examine three other lakes, adjacent to the Lake Urmia basin, with similar rainfall variability to investigate their status during the... 

This study presents a steady-state Markov chain model to predict the long-term probability of drought conditions. The research aims to propose a rigorous framework for statistical analysis of drought characteristics and its trends over time for a large area of aquifers and plains in Iran. For this purpose, two meteorological indicators called the Standardized Precipitation Index (SPI), and the Groundwater Resource Index (GRI) are examined. The groundwater drought study includes more than 26,000 wells in about 600 meteorological stations over 20 years being surveyed daily. This study discusses the spatial interpolation of drought steady-state probabilities based on recorded SPI and GRI data... 

Data science as a flourishing interdisciplinary domain of computer and mathematical sciences is playing an important role in guiding the porous material research streams. In the present narrative review, we have examined recent trends and issues in data-driven methods used in the image-based porous material research studies relevant to water resources researchers and scientists. Initially, the recent trends in porous material data-related issues have been investigated through search engine queries in terms of data source, data storage hub, programing languages, and software packages. Subsequent to a diligent analysis of the existing trends, a review of the common concepts of porous material... 

This study presents a comprehensive review of the Land subsidence (LS) cases, as a worldwide environmental, geological, and global geohazard concern. Here, 290 case studies around the world mostly conducted in large metropolitan cities (e.g. Bangkok, Beijing, California, Houston, Mexico City, Shanghai, Jakarta, and Tokyo) in 41 countries were collected. The spatial distribution of LS characteristics (e.g. intensity, magnitude, and affected area), impacts, and influential factors are scrutinized. Worldwide attempts to remedy the crisis of LS were also investigated in this review. It is shown that the coastal plains and river deltaic regions are of high-frequent subsided areas around the world... 

Frequent air pollution episodes have been reported for Tehran, Iran, mainly because of critically high levels of fine particulate matter (PM2.5). The composition and sources of these particles are poorly known, so this study aims to identify the major components and heavy metals in PM2.5along with their seasonal trends and associated sources. 24-hour PM2.5samples were collected at a main residential station every 6 days for a full year from February 2014 to February 2015. The samples were analyzed for ions, organic carbon (including water-soluble and insoluble portions), elemental carbon (EC), and all detectable elements. The dominant mass components, which were determined by means of... 

Currently PM2.5 is a major air pollution concern in Tehran, Iran due to frequent high levels and possible adverse impacts. In this study, which is the first of its kind to take place in Tehran, composition and sources of PM2.5 and carbonaceous aerosol were determined, and their seasonal trends were studied. In this regard, fine PM samples were collected every six days at a residential station for one year and the chemical constituents including organic marker species, metals, and ions were analyzed by chemical analysis. The source apportionment was performed using organic molecular marker-based CMB receptor modeling. Carbonaceous compounds were the major contributors to fine particulate mass...