فصلنامه پژوهش در بهداشت محیط
سال هشتم شماره 2 (تابستان 1401)

The carbon monoxide is an important compound which can convert to different chemical materials which is harmful to environment and humans. Selecting the mechanism and absorbent to absorption pollutant gases is very important due to the efficiency. This study aimed to optimize the carbon molecular sieves prepared which cause the adsorption of more carbon monoxide.

In this study, a walnut shell was used to prepare a carbon molecular sieve and activate the carbon was used physical method. The adsorbents were optimized during two modifying and coating processes after granulation. The adsorbents were modified at pH = 4.5-6.5-9 which layered with oil-oil and oil-thinner mixtures (1: 1 ratio). The adsorption capacity of carbon monoxide by the adsorbents was measured by the volumetric method under the same conditions (2g of adsorbent, 25 °C temperature, and 2 bar pressure).

The highest efficiency among those without modified adsorbents for CMS (Ac) with 0.281 mmol CO/g adsorbents and among those coated with oil-kerosene adsorbents for CMS (Al-K) with 0/591 mmol CO/g adsorbent and among the adsorbents coated with oil -thinner and among all adsorbents for CMS (Al-T) with 0.858 mmol CO/g adsorbents.

A carbon molecular sieve can absorb and reduce the concentration of CO, which is an environmental pollutant. Optimization causes to increase the adsorption efficiency.

Regarding the status of air pollution in Isfahan, this study aims to evaluate the air quality of Isfahan due to Particulate Matter and find the relationship between landscape patterns and suspended particles.

to measure the concentration of the suspended particles using a Met One dust meter in 52 points, the city was randomly sampled. The land use map of Isfahan city was prepared after downloading satellite images from the site of the United States Geological Survey. The land use map was generated in six classes with the maximum likelihood classification method in Terrset software. To create the distribution map of suspended particles, the information of 52 stations and inverse distance weighting method in ArcGIS 10.5 was used. Landscape metrics (Normalized Entropy, Edge Density, Patch Area, Relative Richness, and Patch Compactness) were used to quantify the pattern of landscape. The landscape metrics were quantified using FRAGSTATS software.

The results showed that vegetation has a reducing effect on air pollution. A positive and significant correlation was observed between the amount of suspended particles and relative richness. Moreover, a significant negative correlation was observed between PM2.5 and (NDVI), which means that the amount of suspended particles decreased with increasing vegetation density. 

In general, by calculating the concentration of suspended particles in Isfahan, it was found that the southwest, south, and southeast are exposed to more suspended particles. The high density of green space landscaping leads to a reduction of particulate matter pollution. From the analysis of changes in suspended particles in the region, it was inferred that the more we move to areas with weaker vegetation, the higher the concentration of suspended particles.

This study aimed to measure heavy metal concentration in the suspended particles which compare it in five different land uses in district 21 of Tehran.

The procedure was performed based on the ASTM D4096 and EPA standards. The sampling was performed using a high-volume pump for 20 minutes. The sampling was done every six days from five stations in district 21 in the spring of 2021. A total of 20 active samples of total airborne particles were collected from the residential, semi-residential, industrial, semi-industrial, and park stations. The airborne particle concentration was analyzed by the gravimetric method, and heavy metals were attached to particles using the ICP-OES. Descriptive tests of SPSS statistical software were used to analyze the data.

The results show that the lowest concentration of TSP is in the residential station with 42.34 µg/m3 and the highest concentration is in the industrial station with 253.30 µg/m3. In all applications except the park station, the aluminum has the highest concentration, and the lithium has the lowest concentration. The average concentration of the heavy metals in district 21 is an increasing trend of Al> Cr> Zn> Fe> Mg> Sr> Ti> W> Pb> Li, respectively.

The heavy metals in the airborne particles of district 21 have a high concentration and diversity. The factors affecting pollution in the study area include the resources, such as the industries, airports, and light vehicles.

An accurate estimation of air quality and meteorological conditions is required to make the sound air pollution management decisions. Thus, the data analysis from monitoring stations is unavoidable in air pollution research.  The present study uses the statistical tests to survey the homogeneity of meteorological factors and air quality station data in Mahshahr.

At first, a decade's worth of meteorological station data and the data from air quality stations in Mahshahr were collected over 2016-2019. The minimum and maximum values, standard deviation, variance, skewness, and kurtosis of parameters were then calculated, and heterogeneities and improbable fluctuations in the data were examined.

The results indicated that an average of 12% of data from the meteorological station in the special region were invalid, and that the data from this station had a non-normal distribution. Moreover, 98% of meteorological data collected at Mahshahr airport were valid which had a normal distribution. Statistical analysis of pollutant concentration data from air quality stations revealed that among 21 pollutants monitored across four air quality stations in the study region, only PM2.5 in Mahshahr station, NO2 in the mobile station, and CO, O3 in the special region fix station yielded normal distributed data.

Consequently, when compared to other regional stations, the data from special zone's fixed air quality station, and Mahshahr meteorological station were the most reliable, with an average invalid data percentage of 16.4 and 0.48, respectively. Finally, it is recommended that the data should be adjusted to a more normal distribution over the desired period before using the data from other stations.

Groundwater is one of the most important water resources on earth, and groundwater level and groundwater salinity studies are very important to protect and plan the water resources, especially in the arid and semiarid areas, such as Iran. Groundwater quantitative and qualitative testing is time-consuming and costly. Therefore, using the models to simulate the quantity and quality of groundwater has become common.

In recent decades, the artificial intelligence models were tested for the simulation of aquifers in terms of the complex and nonlinear properties of groundwater systems. The present study stimulated the groundwater level and groundwater salinity parameters of Dezful-Andimeshk plain using ANN and ANN + GA models, and finally compared their results with measured data. The data collected for input to two models include meteorological data and groundwater quality parameters gathered from 2011 to 2018.

The results showed that the optimal model is to simulate ANN + GA (Artificial Neural Network + Genetic Algorithm) groundwater level with sigmoid tangent stimulus function, and the optimal model is to simulate ANN + GA groundwater salinity with sigmoid logarithm stimulus function. MAE and RMSE statistics have the minimum and  has maximum value for the model (In test phase, for the groundwater level RMSE=7.47, MAE=9.5 and R2=0.979 and for the groundwater salinity RMSE=6.81, MAE=7.74, and R2=0.99).

Therefore, optimizing the artificial neural network model using a genetic algorithm is very useful, effective and reduces errors and saves time and money.

This study aimed to evaluate the performance of biological process treatment (Modified Ludzack Ettinger) of municipal wastewater treatment plant No. 4 in Mashhad- Alteymur.

The performance of treatment plant was evaluated in a 12-month period from March 2020 to February 2021. Based on flow changes, a sampling of raw sewage inlet and outlet effluent was done in combination.  Moreover, studied parameters, including BOD5, COD, TSS, TDS, EC, pH, total coliform, and fecal coliform were measured according to the methods presented in the standard method book for water and wastewater tests. ANOVA test was used to analyze the data and compare them.

Based on the results, the highest removal efficiencies are related to the parameters of T.C, FC, TSS, BOD5, COD, TDS, and EC, respectively, with 100, 100, 98.48, 97.88, 48.96, 25.97, and 25.88 percent, respectively. The significant removal efficiency of measured parameters in the effluent from wastewater treatment plant No. 4 of Mashhad (Altimour) shows the proper performance of MLE process system. The results of the ANOVA test to compare the removal efficiency of parameters in different seasons showed that the performance of treatment plant was not affected by the change of seasons.

The amounts of pollutants were compared with the standard of the Environmental Protection Organization of Iran for discharge to the environment and using the wastewater. According to the studies performed on the tested parameters, the effluent is in line with the standards of the Environmental Protection Organization for irrigation and agriculture, surface water, and absorption wells, but for other uses and proper efficiency of the effluent, all aspects should be considered.

Gold Mining companies are one of the industries that if not properly act in accordance with the sustainable development goals, they will cause a lot of environmental contamination in the environment. In these factories, tailings dams are places where effluents and tailings materials from gold mining factories are collected and stored, and if not properly controlled and monitored, they can be a significant source of cyanide and heavy metals contamination. In this study, cyanide and heavy metals contamination of groundwater, soil and tailings of Takab gold mine were studied.

In this descriptive cross-sectional study, 19 stations were selected for sampling of piezometric wells, soils around the mine, and tailings dam of the Takab gold mine during a one-year period. Water samples were transferred to the laboratory after stored at 4 °C. The Heavy metals in water samples, soil, and tailings were measured by Atomic Absorption Spectrophotometry (AAS) method.

The amount of cyanide, mercury and arsenic were measured in the range of 0-105, 0-83.7 µg L-1 and 0-120.4 mg L-1 in water samples, respectively. Also the amount of these contaminants (cyanide, mercury and arsenic) in soil samples were in the range of 37.02 - 58 mg kg-1, 0 - 25.6, and 27.6 - 420 µg kg-1, respectively.

The results showed that, there was no significant difference in the mean concentration of arsenic in the water samples of the studied wells. But in the case of mercury and cyanide, the studied wells have a significant difference. Tailings samples had the highest concentration of cyanide and heavy metals, and had significant differences with soil and water samples.

The environmental sustainability is a requirement for modern urban transportation systems. Selecting the appropriate option for the public transport in any urban system does not lead only to the sustainable urban transportation development, but will adapt planning process to its people's characteristics and encourage the people to use it by increasing its productivity. Therefore, this study aims to assess the environmental effect of developing an electric public transport system in Tehran.

In this study, after obtaining the documented and published data, including (books, transportation articles, and obtaining transportation statistics of Tehran from the bus companies and Municipal Transportation and Traffic Organization), AHP-TOPSSIS method was used to select the best option for developing the public transportation in Tehran.

The results showed that the option of implementing an electric transportation system with the private sector investment and government facilities (0.5798), using the electric transport systems in city center (0.3972), converting BRTs to electricity (0.2886), and non - implementation option (0.2672), respectively, had the highest and lowest priority among the development methods of public transport systems in Tehran.

To eliminate the use of fossil fuels in near distant future to prevent the climate change and eliminate environmental pollution from fossil fuels, Tehran's urban transportation system should be implemented to eliminate the fossil fuels, develop and transform its fleet into the electrical systems