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Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.

This paper presents the results of a study carried out to assess the probable seismic loss, in terms of damage to residential buildings, in the case of the west segment of the North Tehran Fault (NTF) seismic scenario in Karaj, Iran. Accordingly, it is crucial to first properly estimate the ground motion intensities. However, most of empirical ground motion prediction equations are poorly constrained at short ranges, and the data may only partially account for the rupture process. Hence, the stochastic finite-fault method with dynamic corner frequency was applied. This is an appropriate tool for addressing source, path, and near-source effects. It is noted that this method is dependent on many parameters which should be properly tuned. Thus, a set of sensitivity analyzes for the hypocenter locations and the quality factors were performed. The results from the simulations were used to develop a curve for estimating the ground motion values. Then, a high-quality building exposure model composed of 26 building classes based on the most recent census data was compiled. Finally, by applying appropriate fragility curves, damages to buildings from potential earthquakes were assessed. The outcomes showed that the mean damage ratio for the whole of the city is about 18.2% ± 5.3. In addition, a disaggregation analysis is done to identify the most vulnerable building types. The results showed that adobe and low-quality masonry buildings contribute the most to loss. The findings from this study can be used to provide risk reduction plans in Karaj.

National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure–the Healthcare Quality and Access (HAQ) Index–on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0–42·8) in 1990 to 53·7 (52·2–55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. Bill & Melinda Gates Foundation.

High concentrations of NO 3 ̄ in water resources are detrimental to both human health and aquatic ecosystems. Identification of NO 3 ̄ sources and biogeochemical processes is a crucial step in managing and controlling NO 3 ̄ pollution. In this study, land use, hydrochemical data, dual stable isotopic ratios and Bayesian Stable Isotope Mixing Models (BSIMM) were integrated to identify NO 3 ̄ sources and estimate their proportional contributions to the contamination of the Karaj Urban Aquifer (Iran). Elevated NO 3 ̄ concentrations indicated a severe NO 3 ̄ pollution, with 39 and 52% of groundwater (GW) samples displaying the concentrations of NO 3 ̄ in exceedance of the World Health Organization (WHO) standard of 50 mg NO 3 ̄ L −1 in the rainy and dry seasons, respectively. Dual stable isotopes inferred that urban sewage is the main NO 3 ̄ source in the Karaj Plain. The diagram of NO 3 ̄/Cl‾ versus Cl‾ confirmed that municipal sewage is the major source of NO 3 ̄. Results also showed that biogeochemical nitrogen dynamics are mainly influenced by nitrification, while denitrification is minimal. The BSIMM model suggested that NO 3 ̄ originated predominantly from urban sewage (78.2%), followed by soil organic nitrogen (12.2%), and chemical fertilizer (9.5%) in the dry season. In the wet season, the relative contributions of urban sewage, soil nitrogen and chemical fertilizer were 87.5, 6.7, and 5.5%, respectively. The sensitivity analysis for the BSIMM modeling indicates that the isotopic signatures of sewage had the major impact on the overall GW NO 3 ̄ source apportionment. The findings provide important insights for local authorities to support effective and sustainable GW resources management in the Karaj Urban Aquifer. It also demonstrates that employing Bayesian models combined with multi-parameters can improve the accuracy of NO 3 ̄ source identification.

This study has used Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6). Hence, the runoff simulation was done in near-future period (2030–2050) scenarios by applying climate change conditions for HadGEM2-ES model under three representative concentration pathways RCP2.6, 4.5 and 8.5 scenarios and for HadGEM3-GC31-LL model under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. Examining the climatic precipitation variables and minimum and maximum temperature under climate change conditions showed a temperature increase of 1.51–2.91 °C for all models and scenarios and a precipitation decrease of 0.05–11.15% for most of them, and the SWAT model simulation showed a runoff decrease in all four stations under SSP scenarios and a runoff increase in three stations under RCP scenarios. Since the climate data for SSP scenarios have become available only recently, results of this study predict that the overall future flow will vary in the −5 to 28% range, resulting in a 5–35% decrease in the flow and, hence, a decrease in the inflow to the dam reservoir. Based on the results, there is a possibility of a 5–30% reduction of the runoff entering the dam reservoir.

There are many pollutants in the air that can be harmful to human health. Their impact varies based on factors such as the kind of pollutant, duration of exposure, and concentration levels. Volatile organic compounds are particularly significant carcinogens among the various pollutants present in the air. Consequently, people who are exposed to these harmful airborne pollutants suffer permanent consequences. This study examines the properties of BTEX compounds—benzene, toluene, ethylbenzene, and xylene—as well as their sources and risk assessments throughout a one-year period from March 21, 2019, to March 20, 2020, in Karaj, Iran’s largest industrialized city. First, utilizing a geographical information system that covered the entire city, 17 locations within Karaj were chosen for this purpose. Then, samplings were carried out in the spring, summer, autumn, and winter months with the NIOSH 1501 method. During the research period, 68 samples of BTEX compounds were collected. The adsorption of these contaminants on the activated carbon adsorbents was performed using an environmental sampling pump with a flow rate of 0.2 L/min for 1 h. The samples were subsequently prepared using a carbon disulfide solution and injected into a GC-FID for analysis. In this research, the average annual concentration of BTEX compounds in the air of Karaj city was obtained at 33.01 µg/m 3 . Autumn and spring had the highest and lowest average concentrations of BTEX compounds, respectively. In addition, sites 5 and 8 had the highest average annual concentrations of these pollutants. The sourcing conducted in this study showed that transportation and fuel consumption, as well as industries, were the primary sources of pollution in the city. In addition, the excess lifetime cancer risk was higher than the guideline value in some sites and lower in others. Furthermore, the Hazard Quotients were lower than 1, but in general, the citizens of Karaj were at serious risk from exposure to this group of pollutants.

Models for land cover/land use simulation are appropriate and important tools for decision-makers, helping them build future plausible landscape scenarios. Due to the fact that the simulation results of different models may be different, it is sometimes difficult for users to choose a suitable model. Therefore, in this study, an integrated approach is used, combining the data obtained from remote sensing and GIS with Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to simulate and predict land cover/land use changes for 2028 in Karaj metropolis (Northern Iran as a poor region—in terms of data—which is under intense and rapid urbanization. In this sense, three land cover/land use maps related to the study area were primarily generated using satellite image data for the period 2006, 2011, and 2017. They were used as a basis to define two scenarios: business-as-usual (BAU) scenario and participatory plausible scenario (PPS) for 2028. Afterwards, the necessary input data used in running of both models were prepared and, then, the outputs of the models were interpreted and compared. According to the results, while human-made coverage and low-density grasslands increased by about 74% and 12%, respectively, it was from 2006 to 2017 that agricultural lands, gardens, and high-density grasslands decreased by 42%, 34%, and 7%, respectively. According to the business-as-usual scenario, which was projected using the LCM model, the increase in human-made cover will continue by about 29% by 2028, and the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will experience decrease by about 20%, 3%, 11%, and 9%, respectively. The participatory plausible scenario for 2028, which was defined using the InVEST model, confirmed the same results, but having different quantities. Accordingly, while human-made cover will increase by about 73%, the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will decrease by about 41%, 10%, 16%, and 1%, respectively. The output quantities of InVEST scenario model seem to be closer to reality with less uncertainty, because this model estimates the quantity of demand for land and its suitability for different uses, based on the views of different stakeholders, and considers landscape development future policies and plans. In contrast, the LCM model is based solely on trend extrapolation from the past to current time and changes in the landscape structure.

The process of optimal operation of multipurpose reservoirs is accompanied by large dimensions of decision variables and the uncertainty of hydrological parameters and water demands. Therefore, in determining the optimal operation policies (OOPs), the decision making for water allocation is faced with problems and complexities. One of the effective approaches for sustainable management and optimal allocation from water resources is the multi-objective structural development based on the uncertainty of input parameters. The purpose of this study is to provide OOPs from Karaj AmirKabir multi-purpose reservoir with applying uncertainty in the inflow to reservoir and downstream water demand. The proposed approach has been investigated in two certain and uncertain models, and three objective functions of the system including maximizing hydropower generation, water supply demands, and flood control have been considered to formulate OOPs. Non-dominated sorting genetic algorithm-II (NSGA-II) was performed to optimize the three proposed objective functions and by applying multi-criteria decision-making (MCDM) methods, the best operation scenario was selected. In the uncertainty model, using the interval method and repeated implementation of the deterministic model for completely random scenarios that generated based on the variation interval of the uncertain parameters, the non-deterministic optimal allocation values were produced. Based on these optimal allocation values and the fitting of the standard probability distribution on it, the probability of occurrence of the deterministic allocation values was determined. Production of optimal probabilistic allocation policies can be very useful and efficient in providing real vision to managers to select appropriate policies in different conditions and rare hydrological events. The results obtained from the certain model shows that as a result of optimal allocation to demands, the fuzzy reliability, resiliency, and system stability indexes were improved to 67.81, 21.99, and 24.98 percentage, respectively. Also, in an uncertain model, applying changes of 48% and 22%, respectively, for the inflow and downstream demand has led to changes of 23%, 55%, and 18%, respectively, in the first, second, and third objective functions. The highest impact from uncertain conditions, has been related to the water supply demands with 55% of the range of variations So, the water supply demands, has a higher sensitivity and priority than other reservoir objective functions under uncertain conditions. Another important result extracted from this study is to determine the monthly probability of optimal allocations achievement. Accordingly, in the warm seasons and years in which the reservoir is facing drought, the occurrence probability of the optimal allocations decreases. Given the comprehensiveness of the proposed methodology, this approach is a very suitable tool for determining the optimal water allocations as probabilistic based on the scenarios desired by managers and reservoir operators.

Recently, natural and environmentally friendly materials have been highly considered for soil reinforcement and stabilization in road and geo-environment infrastructures and constructions. In the present research, laboratory experiments are conducted to evaluate the potential of combining barley fibers and nanoclay to enhance the mechanical properties of clay subgrade while maintaining its affordability and environmental sustainability. Also, it is aimed to explore the potential for extensive use of barley fiber waste, which ranks as the second most abundant agricultural product globally. The laboratory samples were produced by including nanoclay at concentrations of 0.5%, 1%, and 1.5% and barley fibers at concentrations of 0.3%, 0.6%, and 0.9% with fiber lengths of 5 mm, 10 mm, and 15 mm. The primary objective was to determine the optimal content of nanoclay and the most effective fiber length through the unconfined compressive strength (UCS) test. Afterward, the nanoclay was used at its optimal concentration along with different ratios of fibers to perform California bearing ratio (CBR), direct shear, indirect tensile strength, and freeze/thaw (F/T) tests. In addition, scanning electron microscopy (SEM) imaging was employed to examine the mechanism of soil reinforcement by incorporating fibers and the enhancement achieved by the nanoclay introduction into the prepared samples. The results revealed that adding nanoclay to clay caused the development of a cohesive gel between particles and fibers, resulting in improved interlocking and friction. The results also demonstrated a significant increase in the UCS by 142%, tensile strength by 178%, CBR by 120%, and shear strength characteristics. Furthermore, the samples containing an appropriate amount of nanoclay exhibited enhanced durability and greater strength when subjected to F/T cycles. This research determined the optimal fiber length and dose as 10 mm and 0.6%, respectively. Additionally, the highest UCS was achieved with a nanoclay concentration of 1%. Overall, the test results illustrate the effectiveness of these stabilizers in improving the mechanical properties of clay subgrades.

Like other dangerous pollutants in the air, asbestos has negative and adverse effects on human and animal health. The present study is designed to determine the concentration of asbestos in the air of the most industrial city of Iran (Karaj) in 2018–2019. For this purpose, 4 samples were taken from different areas of the air of Karaj during a year with an SKC pump and flow of 6 L/min for 8 h and in 45 days, and a total of 68 samples of asbestos fibers were collected. Then, the samples were analyzed by phase-contrast microscope (PCM) and scanning electron microscopy (SEM). Eventually, the health effects of asbestos fibers were evaluated by the IRIS EPA method. The average concentration of asbestos fibers was 1.84 f/L PCM and 18.16 f/L SEM. Also, the results of statistical correlation analysis indicated that asbestos fibers are positively correlated with wind speed but negatively correlated with the other three parameters (temperature, relative humidity, and pressure). On the other hand, the average annual risk of asbestos fiber in the ambient air of Karaj for all samples was in the range of 4.32 × 10 −6 to 1.81 × 10 −4 which in some places had more danger than the recommended risk range. According to the EPA guidelines, carcinogenicity acceptable levels are in the range of 10 −4 and 10 −6 . Values higher than 10 −4 have more carcinogenic risk and values lower than 10 −6 have a lower carcinogenic risk.