جستجوی مقالات مرتبط با کلیدواژه « co » در نشریات گروه « محیط زیست »

Industrialization, urbanization, and population growth are considered as the main causes of urban air pollution that is responsible for millions of deaths per year worldwide. Besides, the impact of urban air pollution on health is considerable. Respiratory, lung diseases, and heart attacks are largely due to urban air pollution. However, there is a lack of air pollution monitoring stations (hereafter simply stations) in most cities worldwide because of their high expenses, and, thus, access to high spatial and temporal coverage of air pollutants and their distribution is limited. To address this issue, the main purpose of this study was to estimate CO concentration in Isfahan, Iran, based on air pollution monitoring stations and Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2018 to 2019.

In the present work, we used ANFIS and Random Forest (RF) algorithms to estimate the CO concentration level. To implement the ANFIS algorithm, based on collected air pollution data from the stations and Aerosol Optical Depth (AOD) data from MODIS imagery, the basic fuzzy rules were extracted. Further, with the integration of fuzzy rules and artificial neural network algorithm, ANFIS algorithm was implemented to model the dispersion of CO level in Isfahan city. To model the dispersion of CO using the RF algorithm, air pollution data and AOD data were used. Since the number of trees and the number of variables in each node are two basic parameters in the success of the RF algorithm, a 10-fold cross-validation method was used to identify value for these two variables.

Our findings indicated that the RF algorithm was more efficient and accurate in spatial modeling the dispersion of CO because it achieved better RMSE and MAE results than the ANFIS algorithm. The RMSE error value of the RF and ANFIS algorithms were 0.724 and 0.809 ppm, respectively. Furthermore, the MAE error value of the RF and ANFIS algorithms were 0.636 and 0.792 ppm, respectively. In the case of spatial dispersion of CO pollutants, the ANFIS algorithm showed that the amount of this pollutant varies in the city. For example, the central and northern regions of Isfahan had the most pollution and the eastern and western regions of Isfahan had the least pollution based on the ANFIS algorithm. Regarding the RF algorithm, it was observed that by moving from the southeast to the northwest of Isfahan, the amount of CO pollutant increases, and the northwestern regions of Isfahan had the highest CO pollution. The examination of numerical values obtained from the ANFIS algorithm showed that the lowest amount of CO pollution in Isfahan city was equal to 1.43 ppm and the highest amount was 2.13 ppm. In contrast, obtained results from the RF algorithm showed that the lowest amount of CO pollution in the city was equal to 0.57 ppm and the highest amount was 2.27 ppm.

Overall, it can be concluded that since ANFIS and RF algorithms are appropriate and accurate methods in modeling environmental problems due to their nonlinear modeling, the ability to reduce the negative effects of outgoing data, and less sensitivity to the local minimum problem. It should be noted that a significant part of the error observed in the results of ANFIS and RF methods was related to the intrinsic properties of MODIS imagery (i.e., cloud cover and mixed pixel problem due to the coarse resolution of MODIS imagery), point measurements of air pollution data collected from the stations, and recorded data error at the stations.

Determination of pollutant emission factors by time is the most important initial data in air pollution modeling. EPA's AP 42 documents provide the most comprehensive emission factor system for all industries based on process type, fuel, and control types. Target of this study, wasto investigate concentrations, emission factors of SO2, NO2 and CO in Ilam gas refinery.

In this study, concentrations of SO2, NO2 and CO and other required parameters such as temperature, pressure, flow rate and diameter of the 6 main stacks were measured by direct field measurements by Testo 350 XL. By results of these measurements and measurements of previous years in the refinery, the mean average for the two normal scenarios and the worst condition, and then the emission values ​​were calculated. Data analysis was carried out with a confidence level of 95%.

The estimated secondry, hourly, daily, monthly, and annual emissions from Ilam gas refinery was calculated and analyzed based on 2 normal and worst-case scenarios. Field measurement of flue concentrations showed that the highest concentrations of carbon monoxide (3565 ppm) and sulfur dioxide (5099 ppm) relates to SRU1 unit, the highest produced nitrogen dioxide (188 ppm) produced by SRU2, 1396 were the most polluted year according to the measured gases. The results of environmental measurements showed that CO at the sewage station is, 4/12 ppm and in Mehran road with an undetectable amount, the lowest amount of NO2 in the Chegae with 0.6 and Mehran road with the undetectable, the lowest amount, the amount of SO2 at the laboratory point with a maximum of 0.13 ppm and in the housing camp with an undetectable amount, the lowest It was.

Considering that the amount of environmental pollution and concentration of pollutants in the production units are more significant. So, planning for corrective actions to reduce emission of pollutants in production units, seems to be necessary. As well as the recovery and reduction of feed of flaring, can have a significant impact on the emission of pollutants.

How pollutants enter, as well as the speed of releasing pollutants into the atmosphere, affect air pollution. Pollutants may be freed freely, periodically or periodically, either from a source or from several sources or from point and point sources. Also, the dispersion of pollutants depends on how they enter the atmosphere. Lack of information on the distribution of pollutants makes it difficult to determine the impact of their dissemination outside the boundaries of the site and in surrounding residential areas (Shin et al, 2005). Mobarakeh Steel Complex in Iran, due to the production of large amounts Pm10 and Co, the focus of many environmental scientists has attracted. In the presence of amounts of sulfur dioxide gas in the atmosphere, fine particles in the air react with PM10 and become toxic and dangerous substances, which is one of the main causes of urban air quality problems in Mobarakei province of Isfahan. The CALPUFF model is approved by USEPA as an appropriate model for modeling non-uniform and complex currents, including those with complicated earth conditions, as well as in locations where flow and recurrence flow are important. The modeling system consists of three main parts: CALMET, CALPUFF and CALPOST. CALMET is a meteorological meteorological model that calculates meteorological meteorological data from meteorological meteorological models and calculates values for smaller scales using more accurate network layout data using land-use and land-use data. CALPUFF: In fact, a uniform model Lagrangian fluid motion -Gvsy the following procedures for networking time changes, weather conditions in three dimensions, the effects of terrain, wet and dry sessions, interaction plume of smoke and Terrain, broadcast and distribution on the marine environment, Currents are at the bottom of the buildings. CALPOST: Use this section to preprocess output and process simulation files(USEPA(A), 2004). AERMOD is a Gaussian plume model for steady state and for near-site objects based on the structure and implications of planetary boundary layer turbulence. In addition to the AERMOD's primary processor, it is a meteorological pre-processor called AERMET and a ground-based pre-processor, and air pollution is one of the challenges facing the industrial area (USEPA (B), 2004). In this research, the performance estimation of the models has been done in two ways: First, by comparing the observational data of the output models, at the receiver points determined for the models (based on the UTM coordinates), the accuracy of the modeling is obtained at each point in the time periods considered. In the second step, The performance of models is compared with each other.

Today pollution in the large cities has become a basic challenge for the environment. In Ahwaz, 60% of the pollution is related to the mobile sources which produce a huge amount of various pollutants including CO and PM10 that affect the life of the residents in Ahwaz. CO is an important pollutant emitted to the atmosphere from traffic. Generally, pollutant emission to the air has a significant effect on air pollution control. Therefore, the of this study was to investigate the dispersion and density of CO and PM10 from mobile sources.
In this study, at first the study area was zonned (3×3 Km). Then, in each net the number of cars were estimated according to the types of car and hours of traffic. Consequently, the whole diffusion of CO and PM10 concentration in each net was estimated according to gram per second for each car considering the diffusion factors, type of consumed fuel and the distance drived. Finally, for better illustration of places, graphic exhibition, distribution way of the mentioned pollutant and diffusion, GIS a software was used.
The pattern of pollutant diffusion for CO and PM10 emitted from cars, which is calculated by the model, shows that most of the polluted areas are the business and administrative centers. These pollutants were calculated to be very low and even zero at the outskirts of the city.

Due to electrical charge and high specific surface area, clay minerals, such as sepiolite, are widely used for the removal of heavy metals from environment. However, limited information is available to identify their ability for heavy metals removal from multi-ionic solutions. This study was conducted to determine the ability of Fariman sepiolite for the removal of Cd, Co, and Zn from aqueous solutions, and the effect of different factors, such as contact time and initial solution pH, as well as application of heating pretreatments (150 and 250 Cᵒ) on adsorption process of the mentioned elemnts. .
All the experiments were done in 11 contact times from 5 to 2880 minutes, in three replications and at pH values of 4 and 5. After determining the remained amounts of each heavy metal in the centrifuged suspension solutions by atomic absorption machine, the experimental data were fitted by pseudo first order, pseudo second order, and intraparticle diffusion kinetic models.
Findings: The results showed that the adsorption potential of the heavy metals depended on contact time, solution pH, and physicochemical characteristics of the elements. Accordingly, by increasing the contact time and pH of solutions, adsorption rate of the heavy metals increased in an order of Co>Zn>Cd. Moreover, the results illustrated that application of heat treated sepiolite particles, compared to natural sepiolite, increases the removal efficiency of the heavy metals from aqueous solutions.
Results illustrated that application of heating pretreated sepiolite leads to greater removal of heavy metals in the solutions studied. Besides, greater efficiency in removal of heavy metals would be attained in pH= 5 as compared to pH=4.

Environmental pollution by heavy metals is one of the most commonly-encountered problems in many areas in which biological controls have not been implemented. As these metals are non-biodegradable, they remain in the nature for a long time, and through deep percolation into underground water they can cause degradation of ecosystems. The uptake of these elements by plants and their inclusion in the chain of human and animal food is a great risk for the environment and the human being health. Due to non-biodegradable property of Cadmium and some other toxic heavy metals, these metals remain in the environment for a long time. Cadmium is one of the most toxic heavy metals and it has been reported to cause renal dysfunction, hyper-tension, lung insufficiency, bone lesions, cancer, and etc. The principal industrial sources of Cd in the environment are electroplating, smelting, alloy manufacturing, pigments, plastic, battery, mining and refining processes. In the recent years there have been some reports on the use of inorganic absorbents for separating and removing heavy metals from aqueous solutions. Due to the availability, cost-effectiveness, stability against oxidation and reduction conditions and the possibility of recycling, inorganic adsorbents are economically viable. Traditional inorganic adsorbents with a low surface area lose their ability to absorb. Thus, making high capacity adsorbents for fast and easy removal of contaminants is a necessary step. One of the outstanding characteristics of fast-emerging nanotechnology studies is the high surface area to volume ratio of nanomaterials. Because of these outstanding features and other unique properties, nanoparticles may have potential to absorb pollutants from contaminated environments. So far, many technologies to remove heavy metals from aqueous solutions including chemical precipitation, ion exchange, membrane technologies, electrodialysis, and biosorption have been developed. Many of these methods have disadvantages such as high cost of operation, the high sludge, and secondary contamination. Nanoparticles with extremely small size and high ratio of surface-area to volume, provide better kinetics for the adsorption of metal ions from aqueous solutions. Hydroxyapatite as one of the major components of bones and teeth are widely used in biomedical and dental applications, drug delivery, and waste water remediation because of biocompatibility, low solubility, ion exchange and high sorption capacity of heavy metals. Magnetic separation technology as an efficient, fast and economical method for separating magnetic materials has been widely used in textile, biology, and environmental protection. In this study, magnetic hydroxyapatite nanoparticles were synthesized by co-precipitation method. The nanoparticles were characterized by x-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform Infrared spectroscopy (FT-IR), Vibrating Sample Magnetometer (VSM). Finally, the produced nanoparticles were used as adsorbents for the removal of cadmium ions from aqueous solutions. In batch experiments, the effects of pH, evaluation time and initial concentration of Cd2+ ions on adsorption were investigated. FeCl2·4H2O, FeCl3·6H2O, NH4OH (25%), Ca (NO3) 2·4H2O and (NH4)2HPO4 were purchased from Merck. All the solutions for the metal adsorption experiments were prepared using their nitrate salts. The amount of FeCl2·4H2O (1.85 mmol) and FeCl3·6H2O (3.7 mmol) was dissolved in 30mL of deoxygenated water under nitrogen atmosphere at room temperature, and then 10mL of NH4OH solution was added to the resulting solution under vigorous mechanical stirring (300 rpm). A black precipitate was produced instantly. After 15 min, up to 50mL of Ca(NO3)2·4H2O (33.7 mmol) and 50mL of (NH4)2HPO4 (20 mmol) solutions whose pH were all adjusted to 11 were drop wise added, simultaneously to the obtained precipitate solution for 30 min with mechanical stirring. The resulting puce suspension was heated at 110 ◦C for 2 h and then the mixture was cooled to room temperature and aged for 24 h without stirring. The obtained precipitate was separated by a magnet, washed repeatedly with deionized water till neutrality, dried in the drying oven at 110◦C, and grinded with mortar. The final products were the prepared magnetic hydroxyapatite nanoparticles adsorbents. The adsorption behavior of the magnetic hydroxyapatite nanoparticles for Cd2+ions was investigated by means of the batch experiments at 24±1°C. A known amount of magnetic hydroxyapatite nanoparticles was mixed with 50 mL of the corresponding Cd2+ solution over a period of time on a shaker at 150rpm. After that, the aqueous phase was separated by magnetic decantation; the concentration of Cd2+ in the solution was determined by using an atomic absorption spectrometer. In order to determine the optimum of pH, 0.05g of magnetic hydroxyapatite nanoparticles were added to 8 flask containing cadmium and under different pH conditions, the removal efficiency of cadmiumions by the adsorbent was detected. To evaluate the optimum dosage of magnetic hydroxyapatite nanoparticles adsorbent, 3–10 mg of freshly prepared magnetic hydroxyapatite nanoparticles was added to 50.0mL of aqueous solution containing 50.0mg/L Cd2+. The results showed that increasing the amount of adsorbent, the adsorption efficiency of Cd2+ due to increased absorption of available sites, has increased the effect of contact time on the adsorption of Cd2+ by magnetic hydroxyapatite nanoparticles (pH of the solution: 5.5, amount of adsorbent: 0.1g, Cd2+ concentration 50 ppm; temperature: 25±1°C). Sorption isotherms were obtained by equilibrating magnetic hydroxyapatite nanoparticles with metal solutions of different initial concentrations: 10-300 mg/l for 30 min. After separation, the final concentrations of metal in the solutions were measured. The adsorption capacity was calculated according to the following equation: qe = (C0 − Ce)V/m The removal efficiency of lead ions was calculated by the difference of lead ion concentrations in aqueous solution using the equation expressed as follows: R% = (C0 – Ce)/C0× 100 Where, qe (mg/g) is the amount of lead ions adsorbed onto the unit amount of the adsorbent, C0 (mg/L) is the initial lead ion concentration, Ce (mg/L) is the final or equilibrium lead ion concentration, V (L) is the volume of the solution, and m (g) is the adsorbent weight in dry form. The Langmuir and Freundlich models were used to describe the relationship between the absorbed amount of Cd2+ and its equilibrium concentration in solution. To determine whether the Cd2+ adsorption process by magnetic hydroxyapatite nanoparticles is favorable or unfavorable for the Langmuir type adsorption process, the isotherm shape can be classified by a term “RL”. RL values are ranged from 0 to 1 and indicate favorable adsorption, while RL >1, RL =1,and RL =0 indicate unfavorable, linear, and irreversible adsorption isotherms. Phase composition of the samples were characterized using a X-ray diffractmeter (XRD, Model pw-18/40, Philips, Germany) with CuKα (λ = 1.5418 Å) incident radiation over the 2θ range of 10–80◦ at room temperature with a step size of 0.02◦. The morphology of particles was investigated by scanning electron microscopy (SEM, Model VEGAII, XMU, Tescan, Czech Republic). To study the chemical structure of samples, Fourier Transform Infrared spectroscopy (FTIR, Model: EQUINOX55, Bruker, Germany) was used. For this, the samples prepared from 1:80 magnetic hydroxyapatite nanoparticles -KBr mixtures (by weight) were compacted into pellet form and then scanned from 4000 to 400 cm−1. The magnetization measurements were performed at room temperature using vibrating magnetometer. The concentration of Cd2+ in the solution was determined by using an atomic absorption spectrometer (Analytic jena- verio6). In this study, magnetic hydroxyapatite nanoparticles were synthesized by co- precipitation method, and the adsorption potential of nanoparticles for the removal of Cd2+ from aqueous solutions was investigated. The experimental results confirm that this adsorbent has the potential application for removal of Cd2+ from aqueous solution. The nanoparticles were characterized by x-ray diffraction, Field emission scanning electron microscopy, FTIR, and vibrating sample magnetometer. The effect of contact time, initial metal ions concentrations, pH, adsorbent dosage was discussed. The XRD patterns of samples confirm the hexagonal structure of hydroxyapatite and tetragonal structure of maghemite. This pattern indicates that the diffraction peaks are in agreement with the standard card (0566-074-01 ICSD) of hydroxyapatite and (0566-013-01 ICSD) of the tetragonal of maghemite. FESEM image of the nanoparticles showed almost spherical shape. The average size of nanoparticles was 19±2.FTIR spectroscopyreveals expected bondsformation. Magnetic properties of nanoparticles prepared at room temperature were studied in the range of 10000 ± Oe. Hysteresis curves of nanoparticles showed that the saturation magnetization and coercivity of the nanoparticles was 2.8 emu/g and 0 Oe, respectively. The nanoparticles indicate super-paramagnetic behavior. The super-paramagnetic property of the magnetic hydroxyapatite nanoparticles is critical for their application in industrial catalysis, environmental protection, biomedical and bioengineering field, which prevents them from aggregation and enables them to re-disperse rapidly when the magnetic field is removed. Finally, the produced nanoparticles were used as adsorbents for the removal of Cd2+ from aqueous solutions. In batch experiments, the effects of pH, evaluation time, adsorbent dosage and initial concentration of Cd2+ ions on adsorption were investigated. The highest removal efficiency of Cd2+ was in the range pH = 5-7. The removal efficiency increases with time in the first 30 min. Then, the adsorption curve reached equilibrium after this time. Removal efficiency increased as the adsorbent dosage was raised. When a dosage of 0.1 g was used, the removal efficiency reached 96%, indicating that the composite adsorbent magnetic hydroxyapatite nanoparticles showed strong affinity to Cd2+. The adsorption was relatively fast and the equilibrium was established within 30 min to be considered the adsorption isotherm data could be well described by Longmuir equation. The RL values in this study were in the range from 0.045 to 0.488 which indicated the favorable adsorption between Cd2+ and magnetic hydroxyapatite nanoparticles sorbent. Maximum adsorption capacities of Cd2+ were 84.746 mg/g. The results of adsorption experiments indicated that magnetic hydroxyapatite nanoparticles have high adsorption efficiency with short reaction time (30 min) and can be very effective to remove Cd2+ ions from aqueous solution. The most prominent advantage of prepared magnetic hydroxyapatite nanoparticles adsorbents with super-paramagnetism and adsorption capacities was the separation convenience from aqueous solutions.

Introduction & Air pollution is one indication of the urbanization, population incensement, excessive use of fossil fuel resources, lack of utilizing environmentally friendly technologies and most importantly lack of proper environmental management are some the factors which play big roles in this matter. Establishment more than ten million people and excessive concentration of industries and factories, alongside with the geographical situation, topography and specific climatic region, have made Tehran one of the seven polluted cities in the world. In the assessment of air quality, concentration of carbon monoxide gas (CO), among the various pollutants, has a main role and importance. In this study, the probability of persistence of two to seven days unauthorized amounts of pollutants CO in city of Tehran was investigated. For this purpose, the 5-year data (2002- 2006) related to five stations measuring air quality of pollution control companies of Tehran were collected and then using first-order, two-state Markov chain were modeled. Results showed that the highest probability of persistence of pollutant CO exist in Fatemi station, Bazar and Aqdasiyeh stations are sat at next orders. Many months of the year, Fatemi station has the highest probability of CO and two stations, Bazar and Aqdasiyeh, are located in next ranks. Meanwhile, the persistence of pollutant CO in Shahr-e-Rey station compared to other stations is the least.

Carbon monoxide is one of the most important air pollutant gases. It has very serious destructive effects on human health. It use an index gas in the projects of tunnel ventilation planning. For this research, the CO concentration was measured by gas analyzser model Emicont 70 equipment in 5 tunnel of Haraz road in the morning and afternoon of 3 deys. Sampling was done in the 6 minutes at an altitude of 1 meter with the earth surface –respiratory altitude- during the spring. The results show the high concentration of this pollutant gas in investigated tunnels. The concentration of CO was in 9-300 ppm range, that it shows positive correlation with the length of tunnels and real transport.