مدلسازی الگوی پراکنش آلاینده های NOx و SO2 با استفاده از مدل AERMOD (مطالعه موردی نیروگاه شهید سلیمی نکا)

نوع مقاله : مقاله پژوهشی

نویسندگان

پردیس علوم و فناوریهای نوین، دانشگاه سمنان، سمنان، ایران

10.22034/jess.2023.375831.1919

چکیده

نیروگاه‌های حرارتی یکی از منابع اصلی انتشار آلاینده‌ها هستند. در پژوهش حاضر وضعیت تولید و انتشار آلاینده‌های گازی نیروگاه حرارتی شهید سلیمی شهرستان نکاء مورد بررسی قرار گرفته است. برای این منظور از مدل AERMOD جهت تخمین غلظت‌های آلاینده‌ها با میانگین زمانی 1 ساعته، 24 ساعته و فصلی استفاده شد. مدلسازی فصلی آلودگی هوا در بازه زمانی سال 1395 تا انتهای تابستان سال 1398 برای دو آلاینده اکسیدهای نیتروژن و دی اکسید گوگرد انجام شد. براساس اندازه گیری‌های صورت گرفته، CO2 بیش‌ترین سهم انتشار را نسبت به سایر آلاینده‌ها به خود اختصاص داد. براساس خروجی‌های مدل، بیشینه غلظت تخمین زده شده آلاینده SO2 در میانگین زمانی 1 ساعته، در تمام فصول سال‌های مورد مطالعه بالاتر از حد مجاز استاندارد بود. در میانگین زمانی 24 ساعته نیز بیشترین غلظت تخمین زده شده در زمستان 1395 مشاهده شد. نتایج بیشینه غلظت‌های تخمین زده شده آلاینده NOx بیانگر آن بود که در برخی فصول به ویژه در پاییز 1395، تجمع این آلاینده گازی بالاتر از حدود استانداردهای ملی و بین‌المللی قرار گرفته است. تجمع این آلاینده‌ها عمدتاً در ضلع جنوبی نیروگاه و در دامنه ارتفاعات جنوب شرقی و جنوب نیروگاه و در مجاورت شهرهای بهشهر و نکا قرار داشت. با توجه به فعالیت مراکز جمعیتی در این نواحی، اعمال روش‌های مدیریتی و افزایش کیفیت سوخت نیروگاه شهید سلیمی ضروری به نظر می‌رسد.

کلیدواژه‌ها


عنوان مقاله [English]

Dispersion modeling of NOx and SO2 pollutions using AERMOD model (Case study of Shahid Salimi power plant, Neka)

نویسندگان [English]

  • Ahmad Farhad Talebi
  • Hossein Ghorbani
Faculty of New Sciences and Technologies, Semnan University, Semnan, Iran.
چکیده [English]

Introduction
Nowadays, non-stop population growth as well as development of industrial activities has led to increasing the consumption of energy resources. Further energy production has caused air pollution problems in many countries. Reduced air quality has a significant effect on human health and welfare. Due to the increasing energy consumption in different communities, the pressure on excessive consumption of conventional fossil fuels (e.g. coal, fuel oil and natural gas) has considerably increased. The variety of industrial activities related to fossil fuels will emit large amounts of gaseous, liquid and solid waste pollutants, which have many adverse effects and various consequences for the environment.
The behavior of gaseous pollutants once they are emitted into the atmosphere is investigated in the topic of air pollution meteorology. In this topic, scientists are trying to analyze and monitor the air pollution in the atmospheric boundary layer of communities and study the effects of pollutants using computational approaches and machine learning algorithms. Atmospheric modeling is used by air quality managers to make decisions on effective and efficient ways to implement the National Ambient Air Quality Standards (NAAQS). Such monitoring and prection approaches might lead to improve air quality.
AERMOD model is a a state-of-the-art dispersion model for regulatory applications, modeling short range (up to 50 km) dispersion from a variety of polluting sources (e.g. point, area, and volume sources) using a number of model configurations which include different sets of urban or rural dispersion coefficients as well as simple and complex topography.
Air pollution modeling is too important in monitoring of the concentrations of pollutants produced by the power plant. It also could be useful to control pollution and meet the air quality regulations. This study aims to assess the environmental impact of Shahid Salimi thermal power plant, located in the north of Iran, Neka. The effect of two types of fuel consumption on emission and distribution of NOx and SO2 pollutants has been studied. Finally, suggestions to reduce the pollution emission have been presented.

Methodology
Shahid Salimi power plant is a complex with high electricity power generation with a nominal capacity of 2214 MW. Shahid Salimi power plant is located in 25 km north of Neka city on the Caspian coast and consists of two independent parts, including 4 steam units and a combined cycle unit. Each of the four steam units has a nominal power of 440 MW. The combined cycle section consists of two gas units with a nominal capacity of 137.6 MW which are combined with two heat recovery steam generators with a 160 MW nominal capacity. The power plant also has two Turbo Expanders, each with a nominal power of 4.9 MW. The power plant always consumes two types of fuel, natural gas as the main fuel and also alternative fuel, which is Fuel oil.
In this study, the dispersion pattern of gaseous pollutants of Shahid Salimi power plant has been simulated by AERMOD model while consuming two types of fuel, natural gas and fuel oil. Pollutant emission data have been received seasonally from Mazandaran Environmental Protection Organization for several consecutive years from March 20, 2016 to September 22, 2019. The pollutants studied are nitrogen oxides and sulfur dioxide. Also, at the end, the amount of carbon dioxide emissions in the discussed seasons is presented.
The center of the power plant was considered as a reference point. Modeling area composed of the reference point at the center, a distance of 20 km to the north side (Caspian Sea), 50 km to the east side (Miankaleh Peninsula and coastal strip), 40 km to the west side (coasts located in the city of Joybar) and finally 30 km to the south of the region (including the cities of Behshahr, Neka and part of the heights with forest cover) have been monitored by 1229 receptors in the study area. Dasht e Naz meteorological station has been used to receive the required surface meteorological data through the service (NCEI) in the database (NOAA)from the beginning of 2016 to the end of 2019 comprehensively. To determine the topography of the study area, the digital elevation model was entered from the WEBGIS site in GTOPO30 / SRTM30 format.
Discussion of Results
The concentration of pollutants were simulated in 3 time averages, which includes 1 hour, 24 hours and seasonal period. During the spring, the prevailing wind in the studied area has been blown to the east and northeast. Als the wind direction in the area was widely to the south in the summer. According to windroses, during the cold period of the year (autumn and winter), the prevailing wind has been blown toward the southwest. Based on the windroses of the studied years, it is predictable that the distribution of gaseous pollutants can be hazardous for the population centers and agricultural activities in the region.
The results of dispersion modeling of gaseous pollutions are classified seasonally; The results are presented based on the estimation of the maximum amount of pollution for the studied years for NOx and SO2 pollutants, respectively. CO2 emissions are also provided for all seasons in the reviewed years. According to the emission calculations based on the measurements, CO2 has the largest share of emissions compared to other pollutants. Based on the model plot for SO2 pollutant in the 1 hour averaging time, The maximum concentrations estimated in all seasons in the studied years when the steam units used fuel oil, especially in the winter of 2016, were relatively high, So that the average of these values was 5 times higher than the standard, And in the 24 hours averaging time, only in the autumn of 2017 and summer of 2019, the estimated maximum pollution were lower than the limits set by the WHO. The results of the maximum concentrations of NOx pollutants showed that in some seasons, especially in the fall of 2016, it was 356 micrograms per cubic meter above national and international standards (200 micrograms per cubic meter), And in the 24 hours averaging time, in the time periods that included autumn of 2017 and 2018 and winter of 2019 were lower than standard limit, And in other seasons of the reviewed years, the average value of the estimated maximum amounts was 12 micrograms per cubic meter higher than the WHO standard (25 micrograms per cubic meter).
Conclusions
According to the outputs, high concentrations of pollution that are beyond the standards are located in the south slopes of the southeast and south heights of the studied area, near the Behshahr and Neka cities. Accumulated pollution can be dangerous for people living in these areas and have irreversible effects on their health. Accumulated pollution can be dangerous for people who live in these areas and have irreversible effects on their health. Also, the accumulation of pollution in the highlands with the occurrence of acid rain can damage the tissues of forest cover, trees and plants and it will have a negative impact on their growth. Another area where the maximum concentration of pollution has been observed is the area near to the power plant, which is located in the southern part from east to west, and includes agricultural and rural lands, which are highly affected by the accumulation of pollution, and it will even cause problems in food supply by affecting the agricultural products of these areas. According to the results, producing pollution with maximum concentrations in the study area occurs when fuel oil consumption exceeds natural gas. Fuel oil consumption in the steam units due to sulfur dioxide emissions will have much more harmful effects on the environment. Therefore, proper management must be done to reduce its consumption, to protect the adverse effects on humans who live in the region, the ecosystem of the Miankaleh Peninsula, forest cover, as well as agricultural lands in the region. To achieve this target, two solutions must be considered, first, reducing the consumption of fuel oil with proper management, and second, refining and using fuel oil with very low sulfur content in the steam units. Also, using Mazut Nano-Emulsion as a fuel to reduce pollution will be effective.
Keywords
Thermal power plants; Air pollution modeling; AERMOD; Sulfur dioxide; Nitrogen oxides

کلیدواژه‌ها [English]

  • Thermal power plants
  • Air pollution modeling
  • AERMOD
  • Sulfur dioxide
  • Nitrogen oxides