Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.
In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.
The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert
[1] Final Reanalysis
1. Introduction The geographical study of the corona virus shows that this virus is like the global cholera disease, whose first homeland was Wuhan (the vast capital of central China's Hubei province) and then it was transferred to other countries. The spread of this virus in a very short period of time has become one of the biggest international challenges after World War II, and examining the economic consequences of the spread of this disease is also very important and necessary for policy making.The Covid-19 virus has been able to change the lifestyle of people in different societies, and people finally changed their activities accordingly (Werf et al, 2021); (Staton et al, 2021) The visual and to some extent auditory consumption pattern has had a special place in the lifestyle of Iranians during the Covid-19 virus (Trabels, 2020). During the days of quarantine, social networks became very popular. People could not visit their family or friends and many of them kept in touch with each other using virtual networks. In fact, the spread of the corona virus has led to the further development of online social life. . Individual isolation and quarantine and the increase in consumption and tendency towards virtual and video entertainment media have intensified in this era (Staton & et al, 2021). 2. Methodology Leading research is applied in terms of purpose and based on descriptive-analytical nature. The method of collecting data to answer the research questions was library and questionnaire. The tool used in the survey method was a questionnaire. Face validity has been used to determine the reliability and validity of the questionnaire, and the face validity of the research tool was confirmed using the opinions of professors (fifteen people) in the field of rural development and experts in the field of health (ten people). 3. Results The statistical description of the characteristics of the sample in terms of gender showed that there were 302 men (83.4%) and 60 (16.6%) of them were women. Also, 56.9% of participants were married. The number of 146 people from the studied sample was between 41 and 50 years old, and the highest frequency was 40.3%. 4. Discussion To evaluate the effects of covid-19 on the lifestyle of the border villagers of Zabol city compared to before and after the disease outbreak, first one-sample T-test was used. The above test was performed at the 95% confidence level. In this regard, according to the 6-spectrum of the items (not at all = 0, very much = 5), the measurement and analysis of the indicators was evaluated at an average level (average 3). The results showed that lifestyles in media-oriented, community-oriented and livelihood indicators were below average before the outbreak of the Covid-19 disease, and after the outbreak of the disease, they were above average. In the health-oriented index of style status. Before the outbreak of the disease, life was below average and after that it was in an almost average state. In the leisure-oriented index, the life style before the outbreak of the disease was in an almost average state and after that it was in an above average state, and in the culture index The axis of lifestyle status changed after the outbreak of the Covid-19 disease and was in a higher than average status. To investigate the existence of differences between lifestyle indicators among the border villagers of Zabol city, before and after the outbreak of the Covid-19 disease, the paired or dependent t-test was used at the 95% confidence or significance level. 5. Conclusion Limiting communication and face-to-face interactions of people with each other, closing down gatherings, improving the level of personal and public hygiene such as frequent hand washing, using masks and sanitary gloves, maintaining distance from others and observing other protocols. health services, reforming the society's consumption pattern, improving social capital and increasing the level of empathy and social harmony and paying more attention to the lower classes of society, changing the type of entertainment, closing religious centers and holy places, modern social life in the context of virtual space and improving the level media literacy, reduction of air and ground travel traffic, internet shopping and sales, more convergence of family members, The growth of the culture of reading books, watching more series and movies, moving sports from group type to individual type, reducing fashion trends, holding distance education courses and many other such things, many changes. has created in the lifestyle of people. Of course, these changes are relative and are not the same in all societies and for all social strata, and not everyone has been equally affected by these changes. Keywords: Corona, lifestyle, community-oriented, subsistence
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