Journal of Spatial Analysis

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Air pollution has become one of the main problems of cities. Among the sources of air pollution, vehicular traffic plays an important role. Planning for efficient management and control of the air pollution caused by vehicular traffic requires accurate information on spatio-temporal dispersion of the pollutions. This research studies 3D spatio-temporal dispersion of NOx pollution caused by vehicular traffic at Valieasr-Fatemi intersection resides in Tehran, Iran. It is selected for being crowded and having the required meteorological and pollution data sensed by the Air Quality Control Corp. of Tehran Municipality.

This study uses GRAL that is a local micro-scale air dispersion model defined based on Euleran-Lagrangian dispersion models. It investigates the level of spatio-temporal autocorrelation generated by GRAL simulations at both 2D and 3D modes and discusses how it adapts with the reality.

Adopting the GRAL air pollution dispersion model, streets are defined as the linear source of pollution of NOx caused by vehicular traffic. The traffic rate is estimated based on street areas and directions, the designed average traffic velocity, traffic volume and car passage counting at the intersection. The 3D geometry of the buildings is also added to the model. All the required data that were available for winter of 2007 are gathered and introduced into the model.

The model is executed at 9 heights vary from 1.7 m to 52.5 m. These heights are defined covering a range from an average human level height to average building height and above. These levels are considered both separately in 2D mode and integrated into a 3D mode. The formation of NOx clusters is investigated analyzing their autocorrelation using Moran Index at global and local scale.

The calculated Moran-I at global scale at each 9 levels of heights, varies from 0.7 to 0.9 that depicts the validity of the GRAL model adopted to simulate the expected autocorrelation of pollution density affected by spatial issues. The Moran-I increases at higher levels as less air turbulence happens. However the result show that the turbulence increases temporarily at about 10m to 15m which are the average building heights. At local scale, the Moran-I/Anselin shows that HH clusters dominate at lower levels, around streets central areas that are farther from the buildings, and around the intersections. At higher levels, esp. higher than buildings average height, the LL clusters dominate. However the HH clusters formed around intersections, while are shrank, are still visible at high levels. The turbulence caused by building fronts and their down wash effect is also shown in the result as no definite cluster is formed near the buildings front and back.

The autocorrelation analysis is also carried for an integrated 3D model consists of all the 9 levels of heights. Considering the weight matrix for a 20m 2D neighborhood and 1m/s dispersion of the pollution vertically, the global calculated Moran-I equals 0.229 which shows existence of a spatio-temporal autocorrelation of the results generated by GRAL. At local scale the results show that the HH clusters have higher temporal dispersion rate than LL clusters.

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Abstract
Air pollution is one of the most important problems in many countries in the world, which, besides the environmental damage and human health, imposes many adverse social and economic impacts. Therefore, considering the vital importance of air and the rising course of increasing the contaminating agents in recent decades, it is necessary to study the elements and their pollutant gases in order to be aware of the existing situation and to adopt the necessary solutions. The phenomenon of atmospheric air pollution in Iran, as part of the world's atmosphere, is one of the goals of the industrial revolution, which has been increasing day by day as industrialization; population growth and urbanization have grown dramatically. Carbon monoxide (CO) is a colorless, odorless, and tasteless gas that is slightly less dense than air. In the atmosphere, it is spatially variable and short lived, having a role in the formation of ground-level ozone. Carbon monoxide consists of one carbon atom and one oxygen atom, connected by a triple bond that consists of two covalent bonds as well as one dative covalent bond. Carbon monoxide is produced from the partial oxidation of carbon-containing compounds; it forms when there is not enough oxygen to produce carbon dioxide (CO₂), such as when operating a stove or an internal combustion engine in an enclosed space.
Carbon monoxide is one of the most dangerous air pollutants. Due to its importance, many techniques and methods have been used to monitor the Earth's atmosphere in recent years. as well as, the use of satellite data has become widespread because of the availability and availability of features such as spatial, temporal and spatial resolution. In this study, the data from Aqua / AIRS Carbon Monoxide data can be used to study the rate and trend of carbon monoxide gas changes in the atmosphere of the entire world, including Iran.The relevant data in NetCDF format, with one-day and 13.5 x 13.5km spatial resolution of during the 16-year statistical period (2003-2018), was extracted from ttps://disc.gsfc.nasa.gov/datasets/AIRS3STM_006 using ArcGIS software And Grads are processed, represented, analyzed.
The results indicate that the amount of carbon monoxide was reduced during the monthly and annual time series. Of course, monthly and seasonal variations have been impressive. Monthly, the highest concentration of carbon monoxide in January, February and March, and the lowest in August, September and October. Among the seasons, the highest and lowest levels of carbon monoxide were observed in the seasons of winter and summer, respectively. In spatially, the highest amount of surface carbon monoxide with an average of 150 ppb above the city of Tehran and the coastal area of the Caspian Sea and its lowest level with an average of 115 ppb on the Zagros heights was observed.
The results clearly show a clear picture of the dispersion of carbon monoxide gas in the horizontal and vertical direction of Iran's atmosphere. Based on the results obtained from the monthly carbon monoxide data collected during the statistical period (2003-2018), conducted in a three dimensional and regional area extending to the geographical area of Iran, The average surface carbon monoxide of more than 150 ppb above the Tehran metropolitan area and northern coast of Iran is less than 115 ppb on Zagros altitudes. Among other results, there are significant differences between the monthly carbon monoxide average in the surface troposphere of Iran, so that in the twelve months, the highest amount of carbon monoxide was observed in cold months and the lowest was observed in the warm months of the year, respectively. Seasonally, the highest level of seasonal carbon monoxide has been observed in winter and its seasonal season has peaked in summer. The results of vertical profiles (vertical aspect) of carbon monoxide changes in Iran's atmosphere in line with latitude and longitude indicate the maximum carbon monoxide concentration at lower levels of barley so that the maximum amount of carbon monoxide in the Iranian atmosphere is concentrated in the lower levels and Rarely exceeds the level of 250 hPa. Also, the results indicate that the rate of carbon monoxide emissions in the atmosphere of Iran has decreased, so that in the last years of the statistical period, about 30% of the amount of carbon monoxide in the atmosphere of Iran has been reduced, compared to the early years of the statistical period.
 
Key words: Air Pollution, Carbon Monoxide, AIRS, Remote Sensing, Iran.
 
 
 

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Air pollution, as one of the most important environmental hazards in urban areas, is closely related to weather conditions. Today, pollution in metropolitan areas has become an important issue that requires the study and presentation of practical solutions to improve living conditions in this area. Therefore, understanding the relationship between synoptic systems and air pollutants helps a lot in how to solve environmental problems and future planning. Therefore, in this study, compression algorithms of carbon monoxide emission and transfer from domestic and foreign sources were analyzed. For this purpose, GEOS-5 / GMAO / NASA satellite images were used. The results showed that the highest amount of pollution from the seasonal point of view is related to the cold and early morning seasons and the lowest is related to the early afternoon and hot season of the year. And Khuzestan are densely populated carbon monoxide cores. Low pressures of the eastern Mediterranean play an important role in reducing pollutants in the southwest of the country and in the south of the country, under the influence of atmospheric currents from the topographic cut of Bandar Abbas, air streams polluted with carbon monoxide are able to penetrate into the interior to the southern half of Kerman. Increased by low pressure systems in Afghanistan and Pakistan. The Zagros Mountains also play an important role in preventing the entry of pollutants produced by western neighbors into Iran. In summer, Iran is polluted by carbon monoxide carriers by monsoon currents from central and southern Africa to Iran and has caused a lot of pollution

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Abstract:
Clean air is a necessity for human well-being and health. Air pollution is a major threat to humans and other organisms and is considered as one of the environmental challenges. Today, with the increase in air pollution, the need to know more about the causes of its occurrence has been raised. The various consequences of air pollution have made air quality monitoring and control inevitable in all societies at the forefront of environmental issues. In recent years, air pollutants have caused serious risks to human health and the environment. One of these pollutants Tropospheric ozone is the cause of health and environmental problems, especially respiratory problems and lung dysfunction and asthma attacks. Other effects of tropospheric ozone can be reduced lung capacity, cough, chest pain, sore throat, condition Nausea, damage to plants (growth disorders and the effect on germination) and reduced tire life, hence, it is necessary to know and study the tropospheric ozone in large and industrial cities. Tropospheric ozone is a pollutant because it plays an effective role in converting primary pollutants into secondary pollutants. Therefore, the aim of this study was to investigate the trend of changes in tropospheric ozone concentration with meteorological parameters, ozone precursors (nitrogen dioxide and nitrogen oxides). In this study, data from Kermanshah synoptic station and air quality station of Kermanshah General Department of Environmental Protection (Ziba Park station) in a long-term period of 10 years (2007-2016) have been used. Also, in this study using sensor images The OMI satellite Aura was surveyed in February and July 2016. Tropospheric ozone is known as a pollutant in Kermanshah. Therefore, no systematic studies have been conducted on the recognition of tropospheric ozone and the relationship between tropospheric ozone and meteorological parameters in Kermanshah over a long period of time. Tropospheric ozone and its relationship with changes in nitrogen oxides, nitrogen dioxide and synoptic parameters in Kermanshah were studied and the correlation between tropospheric ozone concentration and meteorological parameters was studied by Pearson test and the relationship between them was studied by linear regression. Based on the results. The maximum concentration of ozone occurs in the afternoon between 14:00 and 17:00 and the maximum amounts of nitrogen oxides occur at night and in the early morning of the year. Also, the study of seasonal changes in ozone concentration showed that in warm seasons due to the conditions of tropospheric ozone formation, including the intensity of sunlight, temperature and time of radiation and the presence of pollutants including nitrogen oxides, the concentration of tropospheric ozone was much higher. Ozone concentrations are highest in June, July, August, and spring and summer. The results also showed that there is a direct relationship between solar radiation and ozone concentration. Simultaneously with increasing solar radiation, it increases the air temperature, which increases the photochemical activity and thus increases the ozone concentration. This can be seen in the warm months of the year (June, July and August). Wind speed is also directly related to the concentration of tropospheric ozone. As the wind speed increases, the reactants mix faster and the tropospheric ozone concentration increases. However, precipitation is inversely related to the concentration of tropospheric ozone, which decreases with the occurrence of precipitation in the months associated with the onset of precipitation, and in the dry months of the year, the concentration is increasing. Therefore, meteorological factors and parameters play an important role in tropospheric ozone changes. Which can be seen by linear regression and Pearson test. The results of the study of nitrogen dioxide and nitrogen oxides showed that the highest concentration of nitrogen dioxide and nitrogen oxides during the day is the opposite of the concentration of tropospheric ozone and the lowest concentration of ozone occurs in summer due to increased solar radiation, increased oxidation of di Nitric oxide and nitrogen oxides, and as a result increase the concentration of tropospheric ozone, in autumn and winter, this amount has an increasing trend. Therefore, the trend of changes in tropospheric ozone concentration is the opposite of the concentration of nitrogen dioxide and nitrogen oxides, which can be seen in the daily, monthly and seasonal sections, which linear regression and Pearson test show this important and OMI sensor images confirm this fact. In conclusion of this study, all parameters related to the concentration of pollutants along with meteorological parameters have been effective factors in the concentration of tropospheric ozone.
Keywords: air pollution, meteorological parameters, ozone tropospheric, NO₂, NO_X