نشریه علوم و تکنولوژی محیط زیست
سال بیست و چهارم شماره 3 (پیاپی 118، خرداد 1401)

The aim of this study is to explain to the theoretical model in order to find a new solution for the production and development of spatial arrangement of architectural plans based on interactive and integrated methods with the help of machine learning and genetic algorithms. Evolutionary algorithms alone are not effective, but machine learning algorithms can learn plans and form the basis of practical models that can develop and generate new samples through the use of genetic algorithms.

In this regard, the combined research method includes library studies, collecting raw data, reviewing case samples, and using computational formulas as objective and penalty functions.

Studies show that the genetic algorithm does not have the ability to store memory and on the other hand, the basis of its calculations is jumping and random action that this process is not effective in the production of architectural plans alone and research.

 findings show that the algorithm Machine learning, due to its exemplary structure, can store and recognize examples, and the genetic algorithm, which is a searchable and scalable algorithm, can produce more examples of architectural plans each time based on the proposed mathematical model.

Estimating aboveground carbon (AGC) of forest is a fundamental task for sustainable management of forest ecosystems; therefore, there is a critical need for appropriate approaches for quantifying of AGC. The most commonly used approaches for estimating include global regression models that estimate the target variable over a wide range using cost-effective auxiliary data. Traditional regression models with fixed regression coefficients at all locations do not consider heterogeneity and spatial structure in modeling. The objective of this study is estimating the AGC using Regression Kriging, Geographically Weighted Regression Kriging and Landsat 8 data and compare methods.

The study was carried out in part of Zagros Forest, in Kohgiluyeh and Boyer-Ahmad Province. Totally, 184 plots (30×30 meters) surveyed and AGC were calculated by allometric equations. 32 variables were extracted from Landsat 8 as auxiliary data in the modeling process. The assessment of accuracies of methods was evaluated by K-fold cross validation via criteria such as coefficient of variation (R2), root mean square error (RMSE).

The results showed that Geographically Weighted Regression Kriging (R 2 = 0.66, RMSE= 21) had a better performance compared to Regression Kriging.

Hybrid methods with heterogeneity and spatial correlation can be a good alternative to early regression methods for estimating aboveground carbon (AGC).

The present study investigates the water quality of Sufi Chay river in Maragheh, Iran using Benthos groups and their population structures in 2015.

Overall, 9samplingsites were selected in the region and Macrobenthos were sampled in triplicate at each siteusing a 25×50 surber. The samples were stabilized by Formaldehyde 4% and their species, family and genus were identified. A total of20Macrobenthos species from 19 families, 10 orders and 2 classes were evaluated. Baetis sp. was the dominant species in winter and summer.

The results indicate that the 7 and 9 sites with the aggregation of 47 and 128 Macrobenthos per m2 were dominant in winter and summer, respectively. Regarding Welch model, water quality of Sufichay river was moderate at most sites in both seasons. However, the water quality at the 7 site in winter and the 8 and 5 sites in summer was unsuitable. According to the BMWP Index, water quality of the river, except the 8 and 9 sites in winter, was suitable.

Regarding the results of this research it can be concluded that Macrobenthos community is an effective bioindicator to assess environmental conditions of the Sufi chay river. In addition, the results of this study display the relatively suitable water quality of Sufi Chay river.

The distribution of canopy classes is the most important structural characteristics of Zagros forest stands. Determining the fitting pattern of canopy classes in Zagros forests shows that, the overall status of these forests from the destruction process and ecological sequence points of view at different times. The aim of this research was to evaluate of probability-statistical functions in order to fit canopy classes of trees in Chartagh forests of Ardal city, Chaharmahal ve Bakhtiari, Iran.

For this purpose, an area of 50 hectares in Ardal forests was selected (3157 trees) were fully callipered and statistically analyzed. Exponential, Gamma, Normal, Beta, Weibull and Log-normal probability distribution patterns were fitted to crown canopy classes. Characteristics of distribution patterns were estimated using maximum likelihood method. Kolmogorov-Smirnov, Anderson-Darling and Chi-square tests were used for comparing of actual probability and probability which derived from functions.

The results of fitting tests showed that log-normal probability distribution was suitable for canopy classes modelling in Chartagh forests.  

Log-normal probability distributions can be used for those who want to simulate changes of forests

Regarding to importance and widespread of wild Pistachio in arid and semi-arid regions and problems of germination, this study was conducted to identify effect of physiography on seed germination of Pistacia vera in Khajeh Kalat Forest, northeast of Iran (N 36°54' - 36°64', E 54°35' - 54°45').

To do so land unit map was provided and sampling was done based on land units. Then, sampled seeds from 23 sampling unites were transferred to seed physiology lab for operational experiments. After operational experience, germination percent, germination value and mean time to germination for each unit were determined.

The results showed that germination percent of pistachio seeds has had significant positive correlation with altitude, but hasn’t had significant correlation with slope and aspect (p<0.01). Correlation between germination value and altitude wasn’t significant, while slope and aspect have had significant correlation with germination value (p<0.01).

 Regarding to results, germination percent in high altitudes was more than low altitudes. Germination value in law altitude and 0-30 percent slope was more than other aspects and slopes. Seeds that were collected from north and south aspects and above 60 percent slope have had more germination value than other aspects and slopes. Mean time to germination for east aspect and 30-60 percent slopes were less than other aspects and slopes.

Development of agriculture, industry and population growth, the exploitation of groundwater resources has increased and has affected its quality. In order to prevent the occurrence of quantitative and qualitative problems of aquifers, management of optimal operation of groundwater resources is essential. Therefore, the purpose of this study is the optimal utilization of groundwater resources and to investigate its quantitative and qualitative effects on the Shahriar plain aquifer.

Groundwater level changes and its quality from the perspective of index (TDS) in Shahriar plain aquifer have been simulated by ANN. Then (TDS) of groundwater has estimated by regression. Finally, the multi-objective genetic algorithm (NSGA-II) was used for optimal utilization of groundwater resources and with the aim of minimizing groundwater level changes and total dissolved solids of groundwater.

According to the results of the study, the evaluation criteria (RMSE) in three modes of training, testing and validation for groundwater level changes are equal to 1.27e-06, 0.0025 and 0.003, respectively, and for total dissolved solids of groundwater was calculated to be 0.24, 27.64 and 14.608 and the correlation coefficient (R) at the level (0.05) in three situations was significant for both variables. Also, during the study period, the volume of optimal withdrawal from the aquifer has decreased by 29.12 percent and the optimal amount (TDS) of groundwater on average, 120.87 Mg./l, has been calculated less than the estimate of artificial neural network. And Groundwater level has also increased by an average of 9.27 meters per year.

The results confirm that the proposed simulation-optimization method as an application tool with good performance, low cost and desirable speed can support several effective factors simultaneous with optimal operation policy. It also reduces the quantitative and qualitative problems of the aquifer and cause increases the stability of the groundwater system.

Urban green space has a very important role in the sustainability of the city. Green space per capita is one of the main factors to planning and management of a city. In this study, green space per capita estimation of Khomein city was investigated.

Satellite imagery was used to measure green space and parks per capita. For this purpose, using Sentinel-2 imagery, land use map was developed in four classes including: Bare lands, habitat, urban parks and farmlands. The urban park layer was extracted and combined to the four district of Khomein city layer. Then, the green space per capita of each area was calculated.

Green space per capita survey using remote sensing approach shows a severe shortage of urban green space in this city, especially zone 3 in the southeast of the city with 1.66 m2 per capita, meanwhile, this zone had the lowest value among all zones. In this city, green space has an inappropriate distribution and the highest green space per capita value was 3.43 in zone 1. Zones 2 and 4 had an average of 3.22 and 3.27 m2, respectively.

the results show that the green space per capita of the city is very low compared to the standards and requires special attention of decision makers to increase and expand the green space in the city. So in the near future, a comprehensive analysis of the green space and the reasons for this shortage should be addressed.

The growing popularity of cryptocurrencies, especially bitcoin, has led miners to use the cheapest energy available through fossil fuels and to pay little attention to the release of pollutants and their destructive effects on the environment and future generations of humans. Therefore, the purpose of our research is to investigate the effects of cryptocurrency extraction on greenhouse gas emissions and, consequently, on the environment.

In this study, the effects of bitcoin mining on greenhouse gas emissions and environmental pollution were investigated using the method of "continuous wavelet transform and wavelet coherence". To achieve this, data such as bitcoin hash rate (energy consumption due to bitcoin extraction), and emission of four greenhouse gases, namely; Methane (CH4), carbon dioxide (CO2), nitrogen dioxide (N2O), and sulfur hexafluoride (SF6) were used monthly from 2009 to 2020.

Although from the point of view of bitcoin crypto industry miners in the short run, the results showed that its effects and destructive effects on the environment can be seen in the long term.

The cryptocurrencies industry is one of the main factors in the emission of pollutants and greenhouse gases, and most of their extraction has a positive and significant effect on the emission of environmental pollutants and their fluctuations, in the long term. With the help of this research, the index of the impact of cryptocurrencies on the environment, future generations and intergenerational justice can be considered as a criterion for approving or disapproving of this industry in the Islamic financial framework.

Many cities in our country, including Tehran, are facing the phenomenon of obsolescence and inefficiency of urban neighborhoods. Such areas can have devastating environmental, economic, or social effects. In the current era, proper management of such urban spaces requires up-to-date and valid data. Due to the large size of outdated and inefficient neighborhoods, collecting and updating this amount of data by organizations is time-consuming and costly. Therefore, using the capacity of citizen participation is a good opportunity for city managers, which is the main purpose of this research.

Citizen-centered GIS strategy has been introduced in recent years, and in many applications, enterprise location data acquisition has been replaced by volunteered geographic information (VGI). This research presents an object-oriented design for collecting spatial information about urban deterioration. Accordingly, a web-based implementation based on open-source components is on the agenda.

With the help of the proposed solution, first, spatial information can be collected in a categorized and thematic manner. According to the definition of worn-out texture, ten different classes were considered in the object-oriented approach, which include undesirable paths, unsafe and old buildings, ruined and dirty lands, narrow access networks, and places for offenders and addicts. A web-based system was also implemented based on open-source frameworks such as Django and components such as GeoDjango, PostGIS, and OpenLayers.

Citizen science is a new approach to collecting spatial information on worn-out tissue. The result of the implementation of the method used is the rapid and low-cost provider of information and enhances the role of experts in municipalities and urban design organizations, mainly professional supervisors instead of data providers. Cost-benefit analysis showed that in a one-year period, this approach could lead to an approximate savings of 15%.

Spatial pattern study of forest species could provide us important and useful information about relationship between species and also forest dynamic. Therefore, it could be an important tools for better management of forest resources. The objectives of this study were to determine special pattern of Tecomella undulata stands in Bushehr province and also, evaluation of different functions capability in T. undulata spatial pattern determination.

In the present study, two stands include Aliabad and Shahnia with 10 and 2 hectares, respectively, were selected in spring 2015 and 100 percent inventory was used. Then to determine the spatial distribution pattern of T. undulate, distance- azimuth method was used. Finally, Ripley's K, L, F, and G functions were used to evaluate T. undulate spatial distribution pattern.

The Kolmogorov-Smirnov goodness of fit test calculation indicated that T. undulata trees distribution in the both studied sites were significantly heterogeneous (P < 0.001). Ripley's K and L heterogeneous functions showed aggregated pattern of T. undulata trees in the study sites. But G function showed aggregated pattern in Aliabad up to 150 meter. While in Shahnia G function indicted different patterns in different distances.

In conclusion, four studied functions showed an aggregated but G function revealed more detail in determination of T. undulata spatial pattern. Such aggregated pattern in T. undulata stands could be because of dry condition and lack of moisture. Based on the results, to revival and afforestation of suitable sites, using aggregated pattern could be useful method to provide shadow and maintaining humidity in soil. That could result in more successful reestablishments of this valuable species.

Today, the use of pesticides somehow indicates just some of deterioration of agricultural standards. Due to the effects of the pesticide contaminants in animal and human life, our country's commitment to the implementation of related rules and regulations, Improve the quality and utilization of pesticides is much more accurate. In this Regard, the role of organizations such as the judiciary, the Environmental Protection Agency, Ministry of Health, Agricultural Jihad, Plant Protection Organization, it is clear in the formulation and implementation of rules and regulations related to pesticides. In this Study, Explanation the legal status and managerial governing the production and consumption of pesticides and chemical fertilizers, is considered legal aspects, environmental and executive management. Ahead cross-sectional study based on the principles and methods, and this research has been done on the basis of library studies and official statistics. According to the study about the legal status and managerial governing the production and consumption of pesticides and chemical fertilizers, legal, environmental, managerial and administrative aspects are mentioned. In the Light of what has been reached by this study, Exploration of Rules and regulations related to pesticides in Iran, as well as Effective approaches and strategies in the light of the existing procedures to control pests and pesticides has been Studied. Results, Shows the limitation rules in the excretion of toxins pests in Iran and it does seems that, these rules must be complemented through effective framework that can better model to be implemented.