جستجوی مقالات مرتبط با کلیدواژه "مدل رگرسیون خطی" در نشریات گروه "محیط زیست"

The development of technology and the advancement of science and technology in large and industrial cities have been associated with the destruction of the environment and various pollutions in human societies. One of the most obvious types of pollution is noise pollution, which causes mental and nervous diseases. In this article, with the aim of evaluating the noise pollution and the impact of social, physical and environmental variables in the urban environment, the evaluation of the sound landscape during the peak activity hours of District2 of Tabriz metropolis has been discussed. In terms of research method, this article is a combination of descriptive-analytical, documentary and survey methods. First, district2 was divided into squares of 200×200 meters based on the 1996 ISO standard grid method, and in the center of each square as a sound recording station with a decibel meter (Bentec digital sound meter model GM1357) the level of sound equivalent (Leq) with The sound pressure level of network A was measured with Fast response speed for 3 minutes, in two time periods: morning (8 to 11) and evening (19 to 22) in the months of Tir to Azar 1400 (July to December 2021). The maps of each dependent and independent variables were drawn in GIS software environment and evaluated using multiple linear regression model in SPSS software. The results of this research show that district2 has more noise pollution in the evening than in the morning. At the end, solutions to reduce noise pollution in the area are suggested.

With the development of sciences and technologies, the growth and expansion of cities led to the destruction of the environment and production of various biological pollutions across human societies. Meanwhile, noise pollution has been one of the types of pollution that has adversely affected the comfort of urban residents and is found to be directly associated with the mental health of people in society. This type of pollution may cause mental diseases, irritability, allergies and other nervous and psychological diseases. This paper aimed to evaluate the noise landscape of District 4 of Tabriz and investigate the amount of this type of pollution in the peak hours of activities in this city, as well as the impacts of social, physical and environmental variables on the urban environment.

This paper used a methodology that combined descriptive-analytical, documentary and survey methods. District 4 of Tabriz was divided into squares of 200*200 m in dimensions, based on a standard square grid, with the center of each square designated as the noise acquisition station. The equivalent continuous sound level (Leq) of each station was measured for 3 minutes at two-time intervals of 8-11 a.m. and 7-10 p.m. in June to December of 2021. Noises were acquired by using a decibel meter device at a sound pressure level of Grid A with a Fast Response Speed. The dependent variable was the equivalent continuous sound level (Leq) at two morning and afternoon time intervals and independent social and physical variables were population density, construction density, the distance from pathway grids, the distance from administrative and police uses, the distance from educational uses, the distance from urban installation and equipment uses, the distance from commercial and service uses, the distance from treatment uses, the distance from industrial uses, the distance from barren land, the distance from green spaces and the distance from aerial corridors. Each of the maps pertaining to the independent and dependent variables of District 4 was separately sketched in GIS software, and then, the effects of each of the independent variables on dependent variables were examined by using a linear regression model in SPSS software.

Surveys indicated that the noise landscape of District 4 of Tabriz Metropolitan consisted of children game noises, noises caused by vehicle and motorcycle traffic, trash trucks when loading trash bins and the sound of construction workers across the neighborhoods, noises caused by motorcycle horns and their swerving noise, the passage of trucks and vans, as well as motor vehicles on the streets and other main axes, the traffic noise of inter-city buses and their horns, load trucks, international transit trucks on first degree axes (Pasdaran Highway and Santou Road), etc. The evaluation of independent social and physical variables with dependent variables (sound equivalent level (Leq) in the two intervals of morning 8 to 11 and evening 19 to 22) shows that out of 12 independent variables of district 4 of Tabriz metropolis in the morning time interval, 9 independent variables of population density , building density, distance from road network, distance from administrative and law enforcement use, distance from urban facilities and equipment use, distance from medical use, distance from industrial use, distance from green space use and in the evening period, 7 independent variables of population density , building density, distance from road network, distance from medical use, distance from industrial use, distance from green space use and distance from air corridor have a significant effect on the sound equivalent level (Leq) and the level of noise pollution in district 4 of Tabriz metropolis. And the variables of distance from administrative and law enforcement use due to the closure of this use in the evening period and commercial and service use despite the high population density of this use but due to the high distribution in the localities of the region, the distance from it do not have an effect on the sound equivalent level (Leq).

Linear regression model results for evaluating independent and dependent variables (equivalent continuous sound level (Leq)) at each time intervals (morning and afternoon time intervals) indicated that the semi-eastern neighborhoods of District 4 suffer from higher noise pollution, while semi-western neighborhoods were dealing with lower amounts of nose pollution.

Migration to cities and urban development have led to the irregular growth of cities and the uncontrolled transformation of natural land cover into artificial and impenetrable cover. As a result, it has created numerous environmental consequences for cities, including the phenomenon of heat islands, as a result of which the temperature of urban areas has increased compared to the surrounding areas, causing changes in ambient temperature, air pollution and harmful effects such as greenhouse emissions. Therefore, measuring and controlling the effects of urban heat islands, based on scientific and justifiable principles, helps decision-makers to overcome the resulting problems. Today, one of the most effective ways to control the effects of heat islands in developed countries is to use less heat-absorbing coverings, such as green infrastructure, high-albedo materials and flagstone, to cover the roofs of buildings. Therefore, in this study, an optimal planning based on spatial analysis, using the remote sensing and computational intelligence in the form of a spatial decision support system that can determine the effects of changing the roof covering of buildings in the study area.

To survey the research, a neighborhood from a central region of Tehran, the 7th region, was chosen to develop a software package for green roof planning. It is expected that the UHI effect has a significant role in this neighborhood since the region that the neighborhood belongs to, is one of the central regions in Tehran. Moreover, for developing the software package, map of parcels with attributes related to the area and land use and Images of Landsat 8 over the neighborhood are employed. Two main groups have a pivotal role in calculating UHI indices including vegetation and urban groups. When the indices are developed, the relationship between UHI and indices is investigated using the linear regression method (LRM) to obtain indices’ coefficients. Afterward, the software package tries to find some parcels, which constitute a certain and predefined percentage of area, that have a significant impact on UHI’s standard deviation by changing their roofs’ covers into three types cover including green, high albedo materials, and flagstones as the novelty of the research. Since there are a lot of feasible solutions, it is necessary to use a metaheuristic algorithm for finding the optimal solution. Therefore, in the second step of the proposed method, the optimal solution is conveyed by the Genetic algorithm (GA), as the most common algorithm in metaheuristic algorithms. After finding the optimum parcels for changing roofs’ cover, the UHI effect is computed once again to show the improvements.

As mentioned, the Genetic Algorithm is used to select the optimum subset of parcels for changing their roofs’ infrastructure with three covering classes including vegetation, high-albedo materials, and flagstones. This subset is assumed as 10 percent of all parcels in the area. However, some parameters should be set before using the algorithm such as the number of population and generation, the ratio of selection, crossover, and mutation. Besides, minimizing the standard deviation of SHI values was assumed as a fitness function for GA. As a result of the algorithm, the selected parcels and their appropriate roofs’ infrastructure for minimizing the standard deviation of SHI in the area are presented. This optimal solution was obtained through 252 generations that its convergence trend is presented. Additionally, based on the changes of selected parcels for roofs’ cover, the SHI values for the study area are computed again. These new values for the SHI and UHI effects are presented. However, the obtained standard deviation of SHI values for the changed roofs’ cover is 10.781°C while this value before changes is 13.222°C.
By examining the selected parcels obtained from the GA results with green spaces in and around the study area, it is found that the GA selects parcels for changing the roof covering with vegetation that is not contiguous with the green spaces in their surrounding area. whereas, according to results, the GA did not choose any parcel in these areas to change their roofs’ infrastructure to vegetation cover. However, highly efficient covering in SHI values such as vegetation and high albedo materials circumscribed the study area. This fact shows that in order to control the variation of UHI in the center of the area, it is necessary to curb the SHI values in the border of the study area. However, the less efficient cover compared to vegetation and high-albedo materials, which is flagstones, are located dominantly in the center of the study area since their influence is more limited and local than the other types.
It is also can be perceived that all changes in roofs’ infrastructure are not in line with changing to the vegetation cover, although this type of covering has the best effect to reduce SHI value. This consequence is because of the fitness function of GA, which is based on the standard deviation and not the mean value. The type of vegetation for covering decreases the SHI value, and thereby leads to decreasing mean value, while the objective of the software is to minimize the variation of SHI values. Therefore, vegetation cover is used in a location where the study area confronts with hotspot SHI value at that location. To verify this claim, the vegetation cover is utilized for all parcels selected by the GA to compute the SHI value for this scenario

With the widespread growth of cities and the increase in population, natural covers have been changed to artificial and impenetrable land cover, which lead to several environmental problems for cities, including UHI effects. Due to these changes, which are caused by the UHI effects, the temperature of urban areas becomes higher than the surrounding areas. One of the most practical and efficient methods for controlling the effects of urban heat islands is utilizing the green infrastructure and high albedo materials for roofs’ infrastructures; however, previous studies did not model this subject in quantitative practice. Based on this shortcoming, the present study proposed a software package to investigate quantitatively the changes of UHI effects based on the substitution of present roofs’ infrastructures to three selected types of covering class including vegetation, high-albedo materials, and flagstones. Additionally, the software used GA as a sub-model of the software to select the best set of parcels in the study area for changing their roofs’ infrastructure according to a specified fitness function. The fitness function assumed for this research is the standard deviation of the SHI values in the study area. This fitness function controls the variation of the SHI values and prevents the creation of UHI hotspots in the study area. . Examining the selected parcels obtained from the results of the GA with the surrounding green space and the study area, it was found that the genetic algorithm selects parcels to change the roof covering with vegetation that is not adjacent to the green space. This fact shows that in order to control the change of UHI in the center of the region, it is necessary to limit these values at the border of the region. However, less efficient cover compared to vegetation and high albedo materials, which is flagstone, is predominantly studied in the center of the area. It can be also seen that not all changes in roof infrastructure are consistent with changes in vegetation, although this type of cover has the best effect on reducing the amount of urban heat islands. This result is due to the fitness function of the genetic algorithm, which is based on minimizing the standard deviation of SHI in the area. Therefore, the vegetation is used in a place where the study area is exposed to a high amount of urban heat islands. Additionally, this cover type is more effective in the range of 100 and 150 meters of green areas.

Frost is one of the most hazardous natural phenomena which it is at times accompanied by abundant damages in the life and properties. Freezing and frost are very important for agricultural products in different stages of the growth. This is because, in case of happening, it results in the reduction of the products. Frost is the stage of water freezing. In such condition, when the air temperature decreases to dew point, ice cover is formed over the surface. Mojarrad Gharehbagh in addition to presenting a new definition of frost, he analyzed and extracted the frost characteristics based on 16 indices systematically. Mirmousavi and Hosseinbabaei studied the temporal-spatial distributions of the frost occurrence probability in Zanjan province. They found that, on average, the first frost events of the region are occurred in autumn season from 19th of September to 15th of November, and generally the frosts events are ended from 9th of April to 20th of May. Montazeri attempted to study the agricultural frosts in NajafAbad city. This results showed that the general frequency of frost days were not decreased, meanwhile the occurrence of the severe frosts have been decreased as well as the frequency of the occurrence of zero-temperature frosts have been highly increased. Jahanbakhsh et al. attempted to analyze the springtime frosts of Tabriz in view of synoptic. Their results indicated that the longest and the severest frosts occurred between 27th March – 1st April 2003 and 5th April 2004, which this is due to the formation of low pressure centers and deepening the related troughs over the north of Caspian Sea. Masoudian and Darand investigated the widespread frosts of Iran and found that 5 patterns of sea level pressures (SLPs) result in severe and widespread frosts in Iran. They also concluded that the severity of the frost events in different regions of Iran is in good agreement with those the path of the anticyclonic systems. Thom and Show proved that the occurrence dates of frosts are random and are based on a normal distribution. For this reason, using mean and standard deviation are considered as valid indices to study the frost events. Tavakoli and Hosseini analyzed the frost indices and its autumn-time occurrence in Ekbatan-Hamedan station and presented a model to predict the autumn-time frosts. Zolfaghari et al. predicted the last date of spring-time frosts in west and northwest of Iran. Their results showed that it was possible to predict the last dates of the spring-time frosts among the stations in the study area using error post-distribution network. The computed error was low in all the stations. The highest error measured in Arak station with %1.1142, while the lowest error computed in Mahabad station with %0.254. Easterling attempted to investigate the recent changes in days with frost and no frost in the USA and he found that during the period 1948-1999 the frequency of frost days declined, but the length of the days without frost increased. Home studied the temporal distribution of seasonal-annual frosts in relation to their trends in the past years. Karl investigated the precipitation and minimum and maximum temperatures, and found that these parameters can be statistically predicted. Bootsma analyzed the minimum temperature and possible occurrence of frost in mountainous regions of Canada. In a research, Behyar studied the cold event of 27th of April, 2003 in Charmahale-e-Bakhtiari province using different meteorological variables to identify the dynamical-synoptic factors responsible for this cold event in the region. Rabani and Karami attempted to study the frequency trend of frost days in Northern Khorasan province. Their results showed that the number of frost’s days during the examined period indicated a descending trend in such a way that it is in good agreement with the increasing trend of annual temperature in the study area. Soltani et al. studied the meteorological aspects of an abnormal cooling event over Iran in April 2009. Their results showed that a polar vortex was responsible for the freezing event over the country extending southward extraordinarily in such a way that its ridge influenced most parts of Iran. This was recognized as an abnormal extension of a polar vortex in the recent years. The sea-level pressure fields indicated that a ridge of large-scale anticyclone centered over Black Sea extended southward and prevailed over most parts of Iran. This resulted in the formation of a severe cold air advection from high latitudes (Polar region) over Iran. Data and In order to investigate the frosts characteristics in synoptic station of Saghez, the frequency of frost days is extracted for the period 1976-2007 and then the minimum temperature data are analyzed on the basis of Jouliosi calendar. The geographic position of the study station is shown in Fig. 1. The homogeneity of the data series verified using Runs Test. After that, the days with a temperature less than 0 ͦC are extracted as a frost day, and the frosts are classified into three categories: weak (ranging from 0 ͦC to -1.1 ͦC); moderate (ranging from -1.1 ͦC to -3.3 ͦC), and severe (less than -3.3 ͦC). Table 1 shows the frequency of occurrence and the beginning/ending date of the frosts with different thresholds during the examined period in Saghez station. In addition, to determine the trend of frost days in Saghez station, a correlation equation was applied between the number of the frost days and length of records (years), which the linear equation is as follows: Which X is the length of records; Y is the total of frost days. It is worthwhile to mention that the above equation is significant at 5%. The knowledge and experience of scientists have presented some solutions over the course of the time, which have been useful in reducing the damages from climatic disasters like frost.. The maps of frost occurrence probability and the first data of autumn-time frosts as well as the last date of spring-time frosts are a simple example, but very significant in studying the frosts for agricultural purposes. Through studying of the temperature data and frosts days in Saghez station during a 32-year period, we found that the minimum temperature over the past two decades had an increasing (positive) trend in such a way that this trend was most severe in the past five years indicating the effect of global warming as a result of a natural process or human activities in the globe. The findings indicate that the severe frosts in Saghez station are mostly occurred in January, February and December months, and the moderate frosts happen in January, February, November, December and March months, and finally the weak frosts usually take place in the months of March, October and April. The trend of frosts days and minimum temperature in Saghez station indicates a vice versa correlation as well as an increasing trend in frost days and decreasing trend in minimum temperature. This trend, which is unusual, is due to the decrease of temperature from 1986 to 1989, which is clear for the number of frost days, as well. The important point in studying the frosts in Saghez station is that, according to the obtained equation, there is a meaningful/significant correlation between the beginning dates of autumn frosts and ending dates of springtime frosts as well as the minimum temperatures of September and April of the same year. So that, the sooner the springtime frosts are ended accompanied by a high minimum temperature of September and April, the later the autumn frosts are started and vice versa. Furthermore, it was determined that the soonest autumn frost occurred on the 2nd day of 2002, and the latest springtime frost took place on the 247th day of the year 2002. Therefore, generally it can be said that through studying and predicting the frost events on time, we will be able to protect the agricultural products against frosts using different methods such as: using heating systems like stove/heater, wind generator machines or helicopters, producing artificial fog etc.