مدل سازی و تخمین آلودگی صوتی در سکوی ایستگاه های متروی دروازه دولت و تجریش کلان شهر تهران | ||
| فصلنامه علوم محیطی | ||
| مقاله 6، دوره 20، شماره 1، 1401، صفحه 113-128 اصل مقاله (930.92 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.52547/envs.2021.1004 | ||
| نویسندگان | ||
| حمید سرخیل* 1؛ زینب کریمی اصل2؛ محمد طلائیان عراقی2 | ||
| 1گروه زمین شناسی کاربردی، دانشکده علوم زمین، دانشگاه خوارزمی، تهران، ایران | ||
| 2گروه محیط زیست انسانی، دانشکده محیط زیست، کرج، ایران | ||
| چکیده | ||
| سابقه و هدف: مشکل آلودگی صدا جدی ترین مسئله ای است که بیشتر مردم به صورت عمومی با مقادیر بیش از حد مجاز آن، مواجه می باشند. هدف این پژوهش، بررسی میزان آلودگی صوتی حاصل از تردد قطار مترو شهری تهران در زمان ورود و خروج در ایستگاه های زیر زمینی دروازه دولت و تجریش می باشد. مواد و روش ها: در این پژوهش که در ماه های تابستان و پاییز سال 1398 روی ایستگاه های دروازه دولت و تجریش از خط یک متروی تهران صورت گرفته است، مقادیر بیشینه و کمینه شدت صوت، در عرض سکو در فاصله های معین از لبه سکو و در دو نوبت صبح و عصر در فاصله زمانی هر سه روز یکبار، به تعداد 48 ایستگاه اندازه گیری شده و تحلیل شده است. در ادامه تحقیق در ایستگاه تجریش با انجام برداشت های محدود با استفاده از شبکه عصبی مصنوعی به تخمین توزیع آلودگی صوتی پرداخته شده است. نتایج و بحث: مقادیر اندازه گیری شده در فاصله های معین از لبه سکو نشان می دهد که میزان آلودگی صدای حاصل از ورود قطار به سکو، ورود همزمان دو قطار به سکو، ورود قطار بدون توقف و عبور از سکو در بیشتر زمان ها، بالاتر از حد استاندارد بوده و در برخی ایستگاه های برداشت، به بالای 100 دسی بل هم می رسید که این خود نشان دهنده شرایط بحرانی آلودگی صوتی در این سکوهای مترو می باشد. نتیجه گیری: روش های مورد استفاده در تحقیق حاضر به منظور تخمین میزان آلودگی صوتی در سکوهای مترو کارآمد بوده است. به طوری که می توان با شناسایی محدوده های بحرانی، با ارائه تمهیداتی صدمه های حاصل از آلودگی صدا بر سلامت شهروندان را مدیریت نمود. | ||
| کلیدواژهها | ||
| ایستگاه مترو؛ نرم افزار مدل ویژن پرو؛ آلودگی صوتی؛ مدل شبکه عصبی مصنوعی | ||
| عنوان مقاله [English] | ||
| Modeling and estimating noise pollution on metro platforms of Darvazeh Doulat and Tajrish Stations in Tehran metropolis | ||
| نویسندگان [English] | ||
| Hamid Sarkheil1؛ Zeinab Karimi Asl2؛ Mohammad Talaeian Araghi2 | ||
| 1Department of Applied Geology, Faculty of Earth Sciences, Kharazmi University, Tehran, Iran | ||
| 2Department of Human Environment, College of Environment, Karaj, Iran | ||
| چکیده [English] | ||
| Introduction: The problem of noise pollution is the most severe problem that most people encounter with in public. The purpose of this study was to investigate the amount of noise pollution caused by Tehran metro train traffic at the time of arrival and departure at the underground stations of Darvazeh Doulat and Tajrish. Material and methods: This study was conducted in the summer and autumn of 1398 in Darvazeh Doulat and Tajrish stations of Tehran Metro Line 1. The maximum and minimum values of noise pollution Intensity were recorded at specific distances from the edge of the platforms in the morning and evenings. Once every three days, 48 stations were measured and analyzed. In the continuation of the research in Tajrish Station, the distribution of noise pollution has been estimated by performing limited impressions using artificial neural network. Results and discussion: The values measured at specific distances from the edge of the platform show that the amount of noise pollution from the arrival of trains to the platform, the simultaneous entry of two trains to the platform, the arrival of non-stop trains, and crossing the platform in most times, was higher than standard. In some harvesting stations, it reached over 100 decibels, which indicates the critical situation of noise pollution in these subway platforms. Conclusion: The methods used in the present study have effectively estimated the amount of noise pollution in subway platforms. By identifying critical areas and providing measures to manage noise pollution, the damage on the health of citizens caused by noise pollution can be managed. | ||
| کلیدواژهها [English] | ||
| Metro Station, Model Vision Pro Software, Noise Pollution, Artificial Neural Network Model | ||
| مراجع | ||
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