جستجوی مقالات مرتبط با کلیدواژه « گرد و غبار » در نشریات گروه « پزشکی »

Background & objectives:

The phenomenon of dust is very critical and catastrophic in our country, especially in Kerman region. Part of the damage caused by this phenomenon is due to lack of sufficient recognition of the impact of dust on the environment. Therefore, the present study conducted to evaluate and prioritize the effects of dust on water, air, soil and animal and plant ecosystems in Kerman city in 2019 in order to inform citizens and authorities about the damage caused by this phenomenon and to plan for controlling them.

The research method was applied descriptive-analytical study. Five criteria including aquatic, soil, air, plant and animal ecosystems, each with 4 sub-criteria, were considered for measuring the environmental effects of dust. Library and field studies (in the form of questionnaires, observations and interviews) were used to collect the information. The statistical population of the study was all environmental experts in Kerman. VIKOR model was used to rank the measurement criteria.

Among the criteria studied using VIKOR model, air, water and soil criteria with quality level of 0, 0.105 and 0.351 were in the first, second and third ranks of negative dust effects, respectively. Animal and plant ecosystems with a quality level of 0.656 were ranked fourth. Among the research indices, the index of endangering the public health of citizens by increasing heavy metals, threatening the citychr('39')s drinking water resources and increasing respiratory diseases with an average of 4.07, 4.04 and 4.01were in the highest average of harmful effects of dust, respectively.

Based on the findings, among the 5 criteria studied, dust had the most negative effect on the air of Kerman and then on the water and soil of the region, respectively. Therefore, based on the priority obtained in this study and coherent planning, Kerman urban crisis management can take successful steps to reduce and deal with the dust phenomenon.

Dust storm typically occurs in arid and semi-arid regions. This phenomenon is more visible across the western, southwestern and central regions of Iran in the summertime. Previously conducted studies have reported that this phenomenon affects human health, agriculture, industry, infrastructure and transportation. The aim of this study is to investigate the economic effects of dust storms.

The present study is a descriptive investigation. The available articles and reports in valid Persian databases (Civilica, Magiran and SID) as well as English databases such as Web of Science, Scopus, Embase, PubMed and Google scholar were reviwed separately.

The dust storm phenomenon covers a wide range of geographical area. In fact, it occurs in all parts of the world and is considered as an international issue. During the occurrence of dust storm phenomenon, the concentration of various pollutants increases, which generally affects the atmosphere, biosphere, hydrosphere and throposphere. Dust storm have far-reaching environmental, health, and socio-economic effects that are linked in a chain, and ultimately each of these effects will have irreparable economic consequences. Therefore, the phenomenon of dust has wide economic effects such as the impact on the exports, delays in air travel, disruption of road transport, destructive effects on agriculture (agriculture and horticulture), road accidents, road damage, closure of schools, home appliances, electronic equipments, public billboards, irrigation canals, power plants and public health.

Dust storm phenomenon should not only be considered as an environmental issue, but due to the great economic consequences for the infrastructure of the affected areas and the country, it should be considered as a national and international concern. It is necessary to accompany many executive departments of the country to reduce its consequences. To reduce the man-made resources of the dust phenomenon, this study proposes integrated assessments and strategies that promote sustainable water and land management in farms, rangelands, deserts and urban areas, despite climate change.

Distribution of air pollutants in industrial units is one of the issues that always affects the environment and ecosystem of adjacent areas. Air pollution is an inevitable part of modern life, and the knowledge of air pollution existed in the past and must be continued to make policies. The cement manufacturing process produces millions of tons of byproducts each year, including dust, toxic gases and heavy metals, which will pose health and respiratory hazards and environmental pollution. Therefore, awareness of pollutant concentrations can be used as key information in pollution control programs. There are still many activities to complete effective control strategies for the prevention, continuous improvement and application of modern technologies to substantially reduce dust in the cement industry. The amount of dust produced can be significantly reduced using modern technologies such as cyclones, bag filters, and electrostatic filters. There are various types of dust in the cement industry including, raw materials such as limestone, marl, clay, iron ore, mixing dust, dryer outlet dust, furnace outlet dust, clinker dust, gypsum dust, and cement dust. In this study, the purpose of dust is the furnace outlet dust. Air pollution is a very complex process that depends on many factors. Therefore, it is very difficult to predict such data with nonlinear dynamics and to determine how the pollutants are to be dispersed and propagated in the atmosphere, which will also be extremely costly. Then, each section can be modeled using this data and solving the equations involving atmospheric processes in the form of data networks. Air quality modeling can be considered as a suitable tool for predicting future air quality and determining emission control strategies. In recent years, one of the best models that has shown good performance in pattern and control modeling is intelligent systems, which include neural networks. Multilayer perceptron neural networks are a model for information processing made by mimicking biological neural networks such as the human brain. The key element of this model is the new structure of its information processing system, consisting of a large number of elements (neurons) with strong internal communications that work together to solve specific problems. Artificial neural networks by empirical data processing transmit knowledge by the law behind the data into the network structure; this is called learning. Ability to learn is essentially the most important feature of an intelligent system. A system that can learn is more flexible and easier to program, so it is better responsive to new problems and equations. Artificial neural networks have been employed for various purposes such as simulation, pattern recognition, classification, prediction, and optimization in engineering sciences. The ability of these networks to map between input and output information with acceptable error has made this method a useful tool for modeling engineering processes. In the basic state, a neural network consists of three layers, input layer, hidden layer, and output layer. Also, each layer contains a number of neurons. In the neural network, neurons are active (on or 1) and inactive (off or 0) and each wing (synapse or communication between nodes) has a weight. Positive-weighted wings trigger or activate the next inactive node, and negative-weighted edges inactivate or inhibit the next inactive node (if it was active). To calculate the output, each of the previous layer inputs is multiplied by the network weights and summed with the corresponding bias. Sabzevar city is located on the west of Khorasan Razavi province in Mashhad-Tehran highway. This city is bounded by Esfarayen in the north, Neyshabur in the east, Kashmar and Bardeskan in the south, Shahroud city in Semnan province in the west. Based on the latest country divisions, Sabzevar has five Bakhsh including, Markazi, Roudab, Khoshab, Davarzan, and Sheshtamad. Sabzevar Cement Factory is one of the sources of dust emission in southwest of Sabzevar in Roudab Bakhsh. The plant started operating on an area of 150 hectares, with a capacity of 3400 tons per day, with Portland cement type 2, 1-325, and 1-425 from October 2007. The plant also uses Bag filter, Bag house, and electrostatic filters for dust, and allocates an area of 50 hectares to build a green belt to protect the environment. The purpose of this research was to predict the amount of dust from the main chimney (baking furnace of Sabzevar cement plant) using a perceptron neural network model.

In this study, first, the amount of dust emitted from the main chimney of Sabzevar cement plant was studied through field surveying in three seasons in 2017-18 by the Experts of Mashhad Environmental Trust Company (Pak Afarinan Avizheh). All sampling and measurement procedures were in accordance with the requirements of the Iranian Environmental Protection Agency. 180 dust samples were collected and then, compared with Iranian Environmental Protection Agency standards and the US Environmental Protection Agency (EPA). The parameters of output gas velocity parameters, temperature, voltage, fuel, and furnace feed were used as perceptron neural network input. Perceptron neural network with 5 neurons as input in the first layer, 10 neurons in the hidden layer, and 1 neurons in the hidden layer. The Levenberg-Marquardt algorithm was used to train the network, which is one of the most used and fastest optimization algorithms. Perceptron neural network is one of the supervised learning methods. To evaluate this method, the data were divided into two training and test groups. The model was trained on the training data. The model error was estimated on the test data. In order to include all data in both training and test groups, k-fold cross-validation method with k = 5 was used. In this way, the data were divided into 5 sections and at each run, 4 groups were considered as training and 1 groups as testing. The network with the least error over the test data was selected. The amount of dust concentration was estimated based on input parameters with the above mentioned neural network (input, hidden and output three layers) and above method. In order to observe the effect of each of the input parameters on the estimation of dust concentration with the perceptron neural network, all possible scenarios should be considered. Since five input parameters are selected, so 25, there are 32 subsets, which results in 31 cases with the removal of the null set. The perceptron neural network was run with 10 neurons in the hidden layer and one neuron in the output layer on each mode (subset). Thus, all subsets of one-member, two-member, three-member, four-member and five-member problem parameters were investigated. In each case, the number of input layer neurons is equal to the number of selected parameters. For each subset of input parameters a neural network was constructed and the amount of dust was estimated. The subset that had the least error in predicting dust concentration was selected as the influencing parameter. For each subset, 5 models were trained, validated each time, and the model with the least error mean squared on the test data was selected. Correlation coefficients and mean squared error were used to evaluate the accuracy of the model in predicting dust concentration. All implementations were performed in MATLAB software.

The results showed that the perceptron model has a good accuracy in predicting the dust concentration of Sabzevar cement plant. Perceptron neural network model was able to Show the correlation coefficient as much as 0.98168 and 0.98249, and Mean square error as much as 0.709 and 280, respectively in two modes of using all parameters (output gas speed, temperature, voltage, fuel, and furnace feed) and the influential parameter (temperature). This indicates a higher correlation and lower error of the perceptron neural network model in using only the temperature parameter than in the prediction of dust concentration in all parameters.

Achieving environmental pollution standards in the cement industry requires proper design and increased efficiency of dust collecting equipment to reduce dust particles. Nowadays, due to the increasing development of cement factories to produce cement needed in the country as well as the growing importance of environmental considerations in various industries, especially the cement industry, the need for better and more efficient technologies to control pollutants and wastes from cement plants has become more and more prevalent. The cement industry is one of the industries that is always referred to as the pollutant of the environment. Although in recent years the industry has tried to meet the environmental standards required by modernizing its equipment and machinery, it is still one of the most important contributors to air pollution. The results of this study showed that the, this model can be a suitable and fast way to better manage industrial dust concentration and ensure quality monitoring results and reduce costs because of the high capability of perceptron neural network in predicting dust concentration.

Dust modeling can be considered as an appropriate tool for predicting future industrial dust and identifying pollutant emission control strategies. Perceptron (MLP) and radial base (RBF) neural networks were used as a means for predicting the outflow dust from the main cogeneration of Sabzevar cement factory located in Khorasan Razavi Province. the concentration of dust from the main cement chimney in the study area was measured through field measurements. Then, the parameters of the production line (temperature, speed of gas output, voltage, fuel, raw materials, and time of sampling) were used as input data to the nerve networks to predict the concentration of dust. The values obtained from the implementation of the models were compared with the results of field measurements as a superior model selection. The analysis of figures and statistical parameters showed that the mean squared errors for the two MLP and RBF models were as much as 1.787 and 21.263, respectively, and the correlation coefficients were as much as 0.99693 and 0.95811, respectively, which indicates a lower error and greater correlation between the MLP and RBF model in predicting the concentration of dust. Because of the high ability of perceptron nervous networks to predict dust concentration, this model can be a convenient and fast solution to predict the amount of dust in the industry.

Dust phenomenon is one of the most harmful disasters that has caused a lot of problems in different parts of the world. In Iran, the Zabol area is heavily influenced by this phenomenon. Therefore, the necessity of conducting research on the effects of these effects on the health of people is necessary. Therefore, the purpose of this study is to investigate the effects of dust on mental health of students in Zabol University of Medical Sciences. A descriptive-analytic study was conducted in Zabol University of Medical Sciences during the period of 2018-2019. In this study, a sample of 320 students was selected randomly. To collect data on the effects of dust on Students' mental health was a researcher-made questionnaire with 27 questions using the Likert scale method. The validity of the questionnaire was performed by multi-expert opinion and reliability was calculated with Cronbach's alpha coefficient of 92%. About 82% of the participants were indigenous people of Zabol city and 17.8% of them were non-native. The mean and standard deviation of mental health score were 70.89 ± 12.44 in gairls and 72.38 ± 12.54 in boys. About 73% of the subjects had moderate mental health and 6.6% had mild health and about 20% had no mental health. Mental health at undergraduate level was better than other levels, but there was no relationship between mental health and other variables. Psychological issues are factors that may be more frequent with the subsequent occurrence of dust. During the dusty phenomenon, people are at risk and suffer from stress. Also, the tolerance threshold may decrease and cause aggression and anger, so the authorities should In order to make the students happy, they should provide facilities for exposure to dust and provide students with the necessary training on health and safety issues.

Street dust is an important factor in urban pollution which consists of soil, particulate matters and heavy metals. At present, over half of the world’s population lives in urban areas. Therefore, this study aimed to investigate health risks of heavy metals in street dusts in Zahedan. The samples of street dust were collected in Zahedan. After preparation, the samples, were injected to ICP-MS for determination the amount of Hg and Cu. According to the measured concentrations, Hazard quotient (HQ) and hazard index (HI) were calculated to evaluate the health risk assessment. Results showed that Hazard quotient for both Hg and Cu was less than 1 for children and adult. HQ for Hg and Cu was in order of HQingestion >HQdermal >HQinhalation> HQvapour for adults and HQvapour > HQingestion > HQdermal > HQinhalation for children. HI was also less than 1. The value of HQ showed that inhalation of mercury vapor and ingestion were the main routes of exposure to Hg for children and adults. The non-carcinogenic risk was within the safe value (HI <1) in this study.

Tuberculosis is a chronic bacterial disease that can be transmitted from the affected persons to others through air when the airway and lung drops of patients are released in the air and inhalled by healthy ones. This disease has a high prevalence in Zabol/ Iran due to the drought, rainfall status, high temperature, severe storms and dusty condition in this region. This descriptive-analytical research was conducted from June 2005 to June 2015 using weather data and the 10-year statistics of tuberculosis patients in Zabol city, of whom 62 patients had been treated. A researcher-made questionnaire was used to identify the factors affecting the disease. Data analysis was done through SPSS22 software and using Pearson correlation and regression analyses. Climatological data showed increasing rate of wind speed over the past ten years. There was a negative correlation between the prevalence of tuberculosis and mean of annual rainfall during the ten years (P≤0.014). The results of regression test showed that wind speed had been very effective in the prevalence of tuberculosis (P = 0.711). To control tuberculosis, regular periodic screening, continuous education and more serious plans for providing specialized care and services are recommended. Meanwhile, appropriate measures including mulching and increasing plant coverage of the region should be taken to control dust.   Key words: Tuberculosis, Drought, Dust, Weather station, Zabol city   Citation: Malakootian M, Mish MastNehi M. A study on the Effect of Draught and Dust Amount on the Prevalence of Tuberculosis in Zabol City. Journal of Health Based Research 2018; 4(1): 1-11.

Street dust mainly is influenceed by pollution Polycylic aromatic hydrocarbons (PAH). PAHs are organic compounds which are formed from carbon and hydrogen and two or more benzene rings. Presence of these compounds in the dust of the street, from various sources in the city, like traffic and industry and may also affect human health and the environment. The aim of this study was to evaluate the effect of compounds on human health and the environment.
In order to assess and determine the possible origin of polycyclic aromatic hydrocarbons (PAHs) in the street dust of Ahvaz city, 10 samples of dust were collected from the city in March 2014. After preparation, the samples were analyzed by GC / MS. To determine the possible source of polycyclic aromatic hydrocarbons, geochemical aromatic ratios, statistical analysis, cluster analysis (CA), and principal components analysis (PCA) were used.
Findings: From 16 PAHs determined by the EPA, 13 PAHs were detected in dust samples. The total concentrations of PAHs were detected between 271.56 to 3211.58 Ppb. The ΣCOMB / ΣPAH was between 0.53 to 0.71 Ppb with 0.66 Ppb average. Ant / (Ant Phe) was between 0.10 to 0.37 Ppb and BaA / (BaA Chr) between 0.17 and 0.57 Ppb and IND / (IND BGP) between 0.28and 0.37Ppb respectively. Probable carcinogenic were calculated by the toxicity equivalent factor (TEF) for PAHs in all sampling stations, it was lower than value of which is determined by Canada to protect human health (600BaPeq Ppb).
Discussion & The results indicate pyrogenic source for PAH of street dust and combustion of fossil fuels. B (a) P is most cancer PAH compound, were detected in all sampling stations with different concentrations. Also, the result indicate that Ahvaz city is intensively affected by the oil and gas upstream and down industries and PAHs can correlate with this industries.

Street dust is consisting of solid particles with complex compositions which can be an appropriate indicator to determine urban environmental contamination. Therefore, the purpose of this study was to determine spatial patterns and heavy metals contamination in the street dusts of Kashan.
A total of 48 urban street dust samples were collected and total concentrations of Pb, Cu, Zn, Fe, Cr, Ni, and Cd were determined in the dust samples. The geoaccumulation index was applied to assess heavy metals contamination. In addition, the spatial patterns of heavy metals concentrations in the street dust were determined using GIS.
The results showed that the average concentrations of Zn, Cd, Cr, Fe, Ni, Pb and Cu in the street dust samples were 237.21, 0.43, 37.12, 16589.77, 13.62, 45.18 and 45.58 mg/kg, respectively. The average concentrations of Pb, Cu, Zn, and Fe were higher than their local background values. Based on geoaccumulation index, the heavy metals in the street dust were in the following decreasing order: Pb > Zn > Cu > Ni > Cd > Cr. According to the spatial analysis results, higher concentrations of heavy metals were observed in the city center and Kashan-Qom highway; whereas, lower concentrations were found in the residential regions.
Based on the obtained results, it seems the high concentrations of Pb, Zn and Cu and to a lesser extent Fe and Cd concentrations in the dust samples was derived from anthropogenic activities; whereas the concentration of Cr and Ni has been mostly affected by natural sources. The high concentrations of heavy metals in the street dusts of Kashan could be attributed to vehicle emissions and industrial activities.

Exposure to pollution due to bioaerosols almost is an inescapable feature of urban living throughout the world. Contact with ambient microorganisms with a wide range of harmful effects on health. Air microbes can cause respiratory infections in patients with immune deficiency and are responsible for communicable diseases. The main objective of this study was to measurement of Actinomycets concentration and impact of environmental parameters on concentration of actinomycetes in normal and dusty conditions and in Ahvaz city.

In this descriptive- cross-sectional study, The air sampling was performed by Air trapping method from the level of respiratory (height 5.1 meters) by the quick take 30 system with a flow rate of 14.3 L/min within 5 and 15 minutes at different stations during the summer, fall and winter in Ahvaz for 9 months (183 samples in total). Sampling was performed at normal conditions in two times per day: morning (9–12) and afternoon (14:00–17:00) and for dusty condition (morning, noon and afternoon). Colonies grown on a nutrient medium (TSA) was counted by using direct method and colony counter and was expressed in terms of colony forming units per cubic meter (CFU m-3). The obtained data was analyzed by SPSS and Excel software.

The number of colonies of actinomycetes in dusty days was 2.5 times than normal days (1.66 times). Winter was more polluted in the case of actinomycets concentration. There was a significant association between particle concentration with the number of colonies formed in cubic meter of air and there was a negative relationship between actinomycets concentration and ambient temperature, while a positive association was observed between wind speed, PM2.5, PM10 with actinomycets concentration.

whatever environment has more population density and traffic, and low vegetation, the concentration of bacteria and actinomycets in environment is high.

Cement industries are a major source of pollution. Cement dust deposition affects photosynthesis، plant production and reproductivity. High dust concentration in air causes a severe reduction in the photosynthetic capacity of the leaves، fertility and plant growth. In this work، the effects of dust particles from Shahroud cement plant on diversity and density of the vegetation were studied. Quadrate method was used to assess type of the dominant vegetation and the diversity. The type and amount of the dust deposited on the plants، vegetation diversity and density were measured in different directions and distances from the emission source. Analysis of dust samples from the plants surface showed that the main component of contamination due to cement industry is calcium oxide (CaO). The results of the evaluation of plants density and diversity and the amount of particles deposited on plant surface showed that there is an inverse correlation between the amount of dust deposition and the vegetation density and diversity. As the distance from the source of particles emission increased، the particle deposition rate decreases and the density and diversity of the vegetation increase. In this region، the plants are replaced by the resistant species such as Artemisia aucheri and Hulthemia persica.

Relation between respiratory problems and presence of air bacteria and fungi has been shown in many studies. Exposure to pollution due to bioaerosols almost is an inevitable feature of urban living throughout the world, and contact with fresh air microorganisms associated with a wide range of harmful effects on health. The present study aimed to study of type and density of isolated bacteria in normal and dusty conditions of different locations and seasons in Ahvaz city. The air sampling was conducted by using a microbial air sampler (Quick Take-30, SKC, USA), with a flow rate of 14.3 L/min; placed at (1.5–2 m height) as a representative of human respiratory height. The sampling duration were 15 and 5 minutes at different sampling stations during summer, autumn and winter seasons (Totally 183 samples). Sampling was performed at normal conditions two times a day: morning (9–12) and afternoon (14:00–17:00) for normal and dusty air, respectively. The colonies were cultured in nutrient media and the type and density of microorganisms were detected by staining and viewed by microscope and based on biochemical tests and detection and counting of colonies have been reported in terms of CFU/m3. Average of total bacterial concentrations for normal and dusty days in ahvaz were 442.34, 889.93 CFU/m3, respectively. The total number of bacteria in dusty days was 2 twice more than normal days. The mean concentrations for Mohit Zist, Naderi, Behdasht Ghadim, and Havashenasi stations were 665.2, 943.4, 657.6, and 437.8 CFU/m3, respectively and the average bacteria concentrations in winter, spring and fall, were observed 760, 84, 515.15 and 479.87 CFU/m3, respectively. In this study, 9 genera of bacteria were isolated including environmental, opportunistic, human body flora and even series of unknown bacteria. Common bacteria in normal and dusty conditions are Bacillus, Streptomyces and Corynebacterium. Among gram-positive bacteria had the highest concentration with more than 89%, and Bacillus species are most abundant genera were isolated from the air in Ahwaz.Discussion & whatever environment has more population density and more traffic, and low vegetation, the concentration of bacteria in environment is high which this concentration of bacteria is inversely related to temperature and UV index of environment. In this study the most important reasons for an increasing in number of bacillus isolated was gram-positive bacteria resistant than drought environment and sporulation in Bacillus which lead to their survival in adverse conditions.

Dust or particulate matters (PM) is one of the most important air pollutants that are considered as a risk factor for health. Change of behaviors is crucial in prevention of health related risk factors. One of the models for behavior change in individual level is Health Belief Model (HBM). The aim of this study was to investigate the effect of education based on health belief model on the maintenance of protective behaviors in exposure to dust air pollution. Through a semi-experimental study design، 200 teachers were randomly assigned into intervention and control groups (n=100، in each group) in Ahvaz، 2013. A researcher-made questionnaire consisting of four parts of demographic characteristics، knowledge، and health belief model’s constructs and protective behaviors in exposure to dust pollution was used for data gathering. The questionnaire was completed by both groups before intervention. The educational program was designed based on the results of pre-test and then the intervention group received the education for 4، 90 minutes sessions with lecture and discussion. The data were collected immediately and two months after the intervention and were analyzed with SPSS-16، by descriptive and analytical statistics. P-values less than 0. 05 were considered significant. The findings showed that knowledge (p<0. 001) and the mean scores of health belief model constructs including perceived susceptibility (p<0. 001)، perceived severity (p<0. 001)، perceived benefits (p<0. 001)، perceived barriers (p<0. 002)، perceived self-efficacy (p<0. 001)، cue to action (p<0. 007) and behavior (p<0. 001) significantly increased in the case group compared to control group immediately and two months after the intervention. Planning and implementation of educational program based on Health Belief Model can be effective in promoting and maintenance of protective behaviors of teachers exposed to dust particles.

The date palm cultivation has a long history in Bushehr province. Throughout the recent decade; the dusts, in addition to direct harmful effects on humans, have adverse effects on health of the population living in this area. The infestation of pests in the southern province of Bushehr has groves. Due to the importance of dates in this area, the total ash and acid insoluble ash as indexes for assessing of chemical pollution and also, mold and yeast as indicators for microbial contamination were evaluated. Recently in a number of dates packaging industries, washing the products after the harvest is done. In current study, the effects of rinsing to decrease the dust pollution on date palm along with, the time effect on the quality and durability of washed and un-washed dates were investigated. Overall, 48 washed and un-washed dates were sampled from traditional and technologically advanced packaging industries, equally, and were confirmed according to ISIRI methods. The Averages of total and acid insoluble ashes in washed date samples were:1.05±0.14 and 3.32±0.32%, and for un-washed samples were 1.36±0.27 and 4.59±1.64 percent, respectively. In all date samples were presented the yeast, however, their means were lower than the maximum limit (1×104 CFU). Also, all date samples were moldy. The Mean percentage of total ash samples in un-rinsed and rinsed dates were approximately, 1.84 and 1.33 times more than the maximum permissible limit, respectively. The mean of acid insoluble ash in all samples (100%), and 98% of total ash were higher than acceptable levels (p<0.05). The results revealed that the average percentage difference between the two groups were transpicuous, while this difference was not significant (p=0.13). Under the similar conditions, the average amount of yeast in washed date samples, were significantly different (p<0.05) and more than un-wash samples. The Mold levels in un-rinsed and rinsed samples; were 83.3 and 75% higher than the maximum permissible limit. According to the results, regardless of a decrease in amount of molds in washed samples than un-wash samples, the rinsing, was unable to eliminate the pollution, or even decreased it to acceptable levels. According to the findings, present rinsing is not an appropriate method for long storage. Observations, after one year upkeep in the same conditions, expressed that all un-washed date samples were apparently healthy, without any pests and insects. While 91.6% of the washed samples were insectivores, also their textured appearances were very unpleasant.

One of the most important health concerns is dust phenomenon causing adverse effects on health. It often leads to serious problems in the city of Ahvaz. In most communities there are a larger number of schools comparing to health centers, as a consequence we can easily use them for health education and promotion. Therefore, the aim of this study is to determine knowledge, attitude and protective behaviors of teachers against dust phenomenon based on the health belief model. This descriptive- analytic study has been conducted on 200 female teachers in different elementary schools in Ahvaz city. The tools for collecting information was a multi section questionnaire consisting of demographic information, knowledge, attitude and behavior. In addition its validity and reliability were ensured previously. Data were analyzed by SPSS software in significance level of P< 0/05. The findings showed the mean age of teachers Was 39/76 ± 6/97 years. The mean score of behavior obtained 33/56 ± 4/45. The mean of perceived susceptibility 27/2 ± 2/66, perceived severity 28/89 ± 2/19, perceived benefits 28/42 ± 2/9, perceived barriers 16/18 ± 4/56 and perceived self-efficasy 12/79 ± 2/34 obtained. It seems necessary to devise and implement various educational and interventional programs in schools to promote awareness regarding protective behaviors against dust.

The importance of clean air in industrial workplaces is well known. Cement dust, due to its silica content, is very dangerous. The aims of this study were to assess and control the release of cement dust from silos of concrete batching units during charging and production processes in a dam project. In this study, dust particule mass released from the cement silos were investigated by performing environmental samplingandpersonal sampling from 15 operators of batching machine. Samples were analyzed by gravimetric method. Control methods were used to control the released dust. Data collected before and after the intervention were analyzed through SPSS19 and using paired t- test and one sample t- test. Mean concentrations of dust particles masses in personal and environmental samples were respectively 15.56 and 30.77mg/m3 and both were higher than the standard exposure limit values in Iran. After implementation of dust control methods, mean concentrations of dust in personal and environmental samples decreased respectively to 4.1 and 5.2 mg/m3 that show the efficiency of control methods. The control method applied in the present study is a novel and cost-effective method to control the released particles from batching units of cement silos. It is possible to decrease the dust concentration in industrial workplaces to the standard levels, by performing simiar methods.