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   بررسی تغییرات شبانه‌روزی و فصلی باد و دمای هوا و آلاینده‌های Co و Pm10 در لایه‌ی سطحی جو شهر تهران  
   
نویسنده ثقفی محمدعلی ,علی اکبری بیدختی عباسعلی
منبع تحليل فضايي مخاطرات محيطي - 1393 - دوره : 1 - شماره : 1 - صفحه:17 -34
چکیده    براساس داده های بادسنج فوق صوتی سال 2007، بیشتر زمان ها تندی باد بینm/s 0.5 تا 2 و دامنه چرخه سالانه آن کوچک است که شرایط حاد آلودگی هوا را در تهران فراهم می کند. همچنین co و pm10 تغییرات فصلی از خود نشان می دهند که به شرایط هواشناختی و منابع آلاینده ها وابسته است. بررسی چرخه سالانه co و pm10 نشان می دهد که غلظت co در روزهای پاییز تا زمستان افزایش دارند. غلظت pm10 در روزهای زمستان تا بهار مقادیر پایینی دارد. افزایش غلظت آلاینده ها در زمستان عمدتا ناشی از کمبود سامانه های همدیدی فعال و وارونگی دمایی سطحی، بر اساس پارامتر پایداری n2، که در پاییز و زمستان نسبت به بهار و تابستان بیشتر است.) است. در چرخه سالانه براساس میانگین های شبانه روزی، ضریب همبستگی co و pm10، 0.4 و در زمستان، 0.7 است که نشانگر ارتباط قوی منابع این دو در این فصل است. در بهار، خودروها، گرد و غبار ناشی از سطح و یا از منابع دورتر، منشا pm10 هستند، اما در پاییز، منابع عمدتاً خودروها و وسایل گرمایشی هستند. دو بیشینه در نمودار تغییرات co در ابتدای صبح و شب رخ داده است که تقریباً با کمینه های تندی باد همزمان و وابسته به تغییرات فصلی نیز هستند. طی شب، شارش های کوه دشت (سرد) و نشست هوا ناشی از سامانه های پرفشار سبب ایجاد وارونگی دما بر روی منطقه می شوند که افزایش غلظت آلاینده ها را در پی دارد.نمودارهای سه بعدی مولفه های افقی سرعت باد، دمای هوا و آلاینده ها نشان می دهند که مولفه نصف النهاری باد، نقش برجسته تری در انتقال co که مستقل از دما است، به عهده دارد که با توجه به وضعیت توپوگرافی منطقه، می تواند نشانگر محلی بودن منابع آن باشد. در حالی که هردو مولفه سرعت باد در انتقال pm10 نقش دارند. همچنین بیشینه های pm10 در فصل سرد با باد کم همزمان و در فصل گرم مستقل از تندی باد هستند.
کلیدواژه تغییرات روزانه، تغییرات فصلی، باد، دما، پایداری، Co ,Pm10
آدرس دانشگاه تهران, ایران, دانشگاه تهران, ایران
 
   Study of Daily and Seasonal Variations of Wind, Temperature, CO and PM10 in the Atmospheric Surface Layer over Tehran  
   
Authors Aliakbari Bidokhti Abbas Ali ,Saghafi Mohammad Ali
Abstract    Nowadays air pollution in large cities such as Tehran have dramatic effects on public health, hence study of the way air pollutions varies with meteorological parameters appears to be important. One important aspect of sustainability of large cities such as Tehran, is controlling the emissions of pollutants as the meteorological (climatic) conditions are becoming more acute in terms of air pollution and temperature rise. In this paper some recent records of near surface meteorological parameters as well as some pollutants records are examine to observe how they change daily, monthly and annually and how they are correlated. Considering the variations of winds and temperature (extracted from a 2D sonic anemometer at 10 m at the Institute of Geophysics, Tehran University in the northern part of central Tehran, with one minute intervals) and hurly data of CO and PM10 concentrations for the same station for 2007, their relations were investigated. Also using upper air meteorological data (at 00.00 and 12.00 UTC) from Mehrabad Airport station, the stability of the atmosphere during this period was analysed. Here the buoyancy frequencies that are measure of stability of air column were calculated. For averaging of winds two methods based on the real wind vectors and wind unit vectors were used. By correlations between the pollutants concentrations and meteorological parameters, their relationships were considered. Based on the probability distributions of winds for 2007, it was found that most of the time wind speeds were in the range of 0.5 and 2 m/s. Hence most of the time due to this weak wind there was a condition of air pollution accumulations over the city and only local winds could move the polluted air over the area. Annual cycle of variations of mean surface winds had small litude that appears to be due to high mountain ranges that surround the city from north and east. The annual cycle of CO variations showed a peak in autumn and winter while PM10 amounts showed a trough in winter and spring. The higher values of CO in winter seems to be due to the surface temperature inversions and improper burnings of the fuel of vehicles as well as the domestic heating systems. This was indicated in the correlations between temperature and CO concentration. In annual cycle the correlation between CO and PM10 concentrations was about 0.4 which increased to 0.7 for spring time. This may indicate that in this season the sources of these two are similar and one of them may be used to estimate the others is the sources are not changed. There are two maxima in the daily variations of CO which coincides with minima of wind in morning and evening transition times. In this study it was found that due to calm meteorological conditions (often od local origin, called mountain breezes) over the city air pollution problem is a serious problem requiring more emission control. Also trend factors as the pollutant sources (traffic) and the depth of the atmospheric surface layer are important. It is particularly noticeable that during the midday as the depth of the mixed layer increases, the air pollution concentration is reduced substantially. At night surface drainage flow from north of the city and surface radiation cooling creates near surface inversions that can limit mixing and ventilation of the polluted air from the area leading to higher values of gaseous pollutant over the city. Also lager stability in the air over the city at higher levels in autumn and winter is due to subsidence inversions as a result of the prevailing meteorological conditions of high pressure systems over this area in these months. Such conditions seem to have increased the creation of more acute conditions for air pollution over the city. For a more resilient city in terms of air pollution, some mitigation need to be undertaken in the face of climate change effects that are deteriorating the atmosphere of the city.
Keywords daily variations ,seasonal variations ,wind ,temperature ,CO ,PM10 ,Tehran ,CO ,PM10
 
 

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