نشریه اکولوژی انسانی
پیاپی 7 (تابستان 1403)

The trend of use and waste of natural resources by humans has increased sharply in recent years. Therefore, one of the most important concerns of scientists and environmentalists is the principled location and location of solar energy towns for sustainable and appropriate development, which can be done using a geographic information system. In this study, using the weighted linear combination strategy method, which is a conservative method by considering lower priorities, other thematic maps participating in the suitability assessment of suitable places for use are evaluated at lower degrees of suitability, which, of course, is also closer to what happens in nature in terms of summarizing the factors. Kerman province has a good advantage in solar energy due to its more than 300 days of sunlight per year, which is why the study of solar radiation assessment in Rayan city in Kerman province is of interest for potential solar energy applications. The total area intended for the construction of the solar town is about 700 hectares, of which about 600 hectares will be allocated for the installation of solar panels. Every 12 square meters in this area produces about 1 kilowatt of electricity. As a result, there is a potential to produce about 580,000 kilowatts of electricity in the study area. A solar module is made by placing the amounts of solar cells together, and by placing the solar modules next to each other, a solar panel is made, and for consumption, a large row of solar panels is placed together and forms a solar series. Silicon solar panels are made in two types: monocrystalline and polycrystalline. It is suggested that in future research, in addition to location options, technical options should also be examined.

Remote sensing is defined as the science and art of acquiring information about objects, land, or various phenomena through the collection of data without direct contact with the phenomena under investigation. In terrestrial resources, the use of aerial photographs, space images, and satellite-derived imagery for interpreting, identifying, and obtaining information about phenomena is referred to as remote sensing. Today, understanding the environment for planning based on the ecological potential of each region, in line with assessing capabilities in specific geographical areas, is considered a crucial phase in the implementation of projects, especially at macro and national levels. Therefore, the objective of this research is to classify land cover and land use in Mobarakeh County. To create the land use map, ENVI 3.5 software, which is designed for processing and analyzing remote sensing data, particularly satellite data, was utilized. Additionally, to identify land cover, products available in the Google Earth Engine platform were employed, which support various types of widely-used satellite data offered for free. Ultimately, to evaluate the accuracy of the classified results, the produced map was compared with ground truth data using Google Earth. Furthermore, to determine the overall accuracy of the classification, the overall accuracy and Kappa coefficient were calculated. The results of this research indicate that the assessment of the produced map's accuracy, which was examined against ground reality using 388 reference points in Google Earth, yielded an overall accuracy of 95.36% and a Kappa coefficient of 0.92, indicating a reliable measure. Finally, it is suggested that future studies consider using segmentations of satellite imagery with the assistance of remote sensing software to define units and assign them to compatible zones instead of employing pixel-based methods for managing such areas.

Elevated concentrations of particulate matter (PMs), particularly PM2.5, are significantly influenced by various anthropogenic activities, including industrial processes, population growth, and fossil fuel combustion, especially during peak urban hours. The burgeoning volume of environmental data often leads to crucial decisions being made with inadequate information. Data mining techniques offer a powerful approach to extract knowledge, compress data, and facilitate informed environmental decision-making. Regarding PM2.5 in Isfahan, understanding the characteristics and origins of each monitoring station is paramount. Specifically, determining the influence of various factors on each station and classifying them based on pollution source is crucial. Principal Component Analysis (PCA) was employed for this purpose. This study suggests that the urban stations (Parvin, Kharazi, Rodki, Ahmadabad, and Ostandari) are likely heavily influenced by fossil fuel combustion from transportation and building heating. The Estandari station, located in the city center with high traffic density, requires special attention due to its relatively large green space, which may influence particulate deposition and accumulation. The Segzi plain, characterized by severe wind erosion, predominantly exhibits PMs of natural origin. Mitigation strategies, such as mulching or afforestation with drought-resistant plants, are necessary to reduce wind erosion and subsequent particulate dispersion. Finally, the Mubarakeh area, a significant industrial hub in Isfahan, displays PMs primarily originating from industrial activities.

Air pollution is the presence of harmful substances in the air at concentrations sufficient to cause adverse effects. This includes solid, liquid, or gaseous pollutants, as well as radioactive and non-radioactive radiation, present at levels and durations that compromise human and environmental health, or damage property and cultural heritage. This research aims to model the extent and spatial distribution of air pollution from the Zagros Economic Zone Mini Refinery in Islamabad Gharb County, Kermanshah Province, Iran. A secondary objective is to quantify the contribution of background pollution to the overall pollution levels and its interaction with emissions from the refinery. The AERMOD model, requiring surface and upper atmospheric meteorological data, was employed. Minimum surface data included wind speed and direction, dry-bulb temperature, and cloud cover. Results indicate a maximum 24-hour sulfur dioxide concentration of 192 µg/m³ without considering background pollution, increasing to approximately 200 µg/m³ when background levels are included. In both scenarios, concentrations remained below permissible limits, although background pollution contributed a 4% increase. The methodological improvements presented in this research are generally applicable and not limited to a specific time or location.

Despite efforts to reduce reliance on landfilling, sanitary landfilling remains a significant waste management method in many cities, albeit with inherent environmental limitations. A major challenge, particularly in developing cities, is the scarcity of suitable landfill sites that meet stringent environmental regulations. Selecting a suitable landfill site necessitates a comprehensive evaluation of relevant criteria, including environmental, geographical, and socioeconomic factors. This study determined the most suitable sanitary landfill site using a multi-criteria decision analysis based on proximity to urban and rural centers, protected areas, and water bodies; distance from major roadways; slope; and proximity to wells. Optimal areas were identified using fuzzy logic within a GIS environment, integrating criteria maps. Spatial overlays incorporating minimum (Min) and maximum (Max) functions, representing fuzzy AND and OR operations respectively, were employed to delineate suitable and unsuitable areas based on the predefined criteria. The comparative analysis of results obtained using the fuzzy AND (Min) and OR (Max) functions revealed that the AND (Min) function yielded a more environmentally sound selection of potential landfill sites, as it minimized conflict with sensitive environmental features, such as protected areas and water bodies. This approach prioritized sites that met all criteria to a satisfactory degree, rather than those meeting just some.

By preparing and implementing land exploitation and productivity plans before the emergence of land planning science in the world, humans have tried to optimally use land resources (water and land) for major human uses. Such plans often fail due to the lack of involvement of the land's natural talents in the exploitation process, and as a result, environmental damage has been caused to humans following the implementation of such plans. Evaluating the ecological potential of land as one of the tools for moving towards sustainable development has sought to measure the availability and latent potential of the land with specific and pre-planned criteria and standards. Approaches to spatial planning are changing as societies become more complex. The purpose of this research is to locate industrial areas in Mobarakeh County with attention to air pollution criteria. To do this, considering the PM10 and NOx distribution map obtained from the AERMOD software, standardization and determination of the weight of the ecological, physical, and socio-economic criteria and sub-criteria of industrial use were carried out using the AHP model, and the suitability of evaluating the power of the region was obtained using the WLC method. Finally, the best spots for industrial use were identified using the TOPSIS method. The results of this research included prioritizing industrial options with attention to air pollution, which identified 4 options, the weight of the first option was 0.24, the second option was 0.19, the third option was 0.43, and the fourth option was 0.14, and as a result, the best spot for industrial use development was determined. The above shows that to achieve sustainable and appropriate development, it is better to use dynamic physical factors such as air pollution along with the use of ecological, socio-economic, and sustainable physical criteria in a region to obtain more acceptable results with minimal damage to the environment.