بررسی روند وارونگی‏ های دمایی کلان‏ شهرهای ایران (تهران، مشهد، و تبریز)

نوع مقاله: مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری اقلیم‏ شناسی، گروه جغرافیای طبیعی، دانشگاه سیستان و بلوچستان

2 استاد اقلیم ‏شناسی، گروه جغرافیای طبیعی، دانشگاه سیستان و بلوچستان

3 استادیار اقلیم‏ شناسی، گروه جغرافیا، دانشگاه فردوسی مشهد

10.22059/jphgr.2019.277884.1007353

چکیده

هدف از این پژوهش بررسی روند وارونگی دمای لایة مرزی کلان‏شهرهای تهران، مشهد، و تبریز است. در این راستا، از داده‏های پیمایش قائم جو سال‏های 20۰7- 20۱7 ساعت صفر (00) ایستگاه‏های هواشناسی تهران، مشهد، و تبریز از پایگاه داده‏های اقلیمی وایومینگ استفاده شد. برای تعیین انواع وارونگی دما، نمودارهای تفی‏گرام داده‎های جو بالا با استفاده از نرم‏افزار RAOB ترسیم شد. سه نوع وارونگی تابشی، فرونشستی و جبهه‏ای به‏عنوان سه تیپ اصلی و چهار نوع دیگر به‏عنوان تیپ‏های ترکیبی متشکل از این سه نوع وارونگی مشخص و توزیع زمانی فراوانی و درصد هر یک از 7 تیپ وارونگی در هر ماه محاسبه شد. روند یازده‏سالة هر یک از تیپ‏های وارونگی با استفاده از روش ناپارامتریک من- کندال و تخمینگر شیب سن تعیین و مقایسه شد. نتایج نشان داد تیپ وارونگی تابشی در همة ایستگاه‏ها کاهش معنادار در سطح اطمینان 01/0 (Z>2.58) و برعکس وارونگی فرونشستی روند افزایشی معناداری در سطح اطمینان 05/0 (z>1.96) نشان داده است. از میان تیپ‏های ترکیبی، تیپ تابشی- فرونشستی روند افزایشی معنادار داشت. در مجموع، نوع تیپ‏های وارونگی در دورة 20۰7-20۱7 از تیپ‏های وارونگی خالص به تیپ‏های ترکیبی و چندلایه و به‏طور شاخص تیپ تابشی- فرونشستی تغییر یافته است.

کلیدواژه‌ها


عنوان مقاله [English]

A comparative Study of the Trend of Temperature Inversions of Iranian Metropolises in Tehran, Mashhad and Tabriz

نویسندگان [English]

  • Nsrin Hosian 1
  • Taghi Tavousi 2
  • Abbas Mofidi 3
  • M. Khosravi 2
1 Sistan and Balouchestan
2 Sistan and Balouchestan
3 Ferd
چکیده [English]

Introduction
The temperature in the troposphere usually decreases with increasing height, therefore, with increasing distance from the ground, the air temperature will be lower (roughly 0.6 degrees Celsius per 100 meters. However daily atmosphere evaluation shows unlike the above description, in many cases the opposite is seen to be called inversion. The purpose of this study was to investigate the adaptive trend of inversion of the temperature of the boundary layer of Tehran, Mashhad and Tabriz metropolis in 2007-2017 on the daily, monthly and annual time scale.
Materials and methods
The atmospheric sounding data from the Meteorological stations of Tehran, Mashhad and Tabriz for the years 2007-2017 were extracted from the Wyoming climate database at 0 o'clock. In order to determine the types of temperature inversion in each metropolis, the graphs of the atmospheric data of each station were mapped using RAOB software and the total number of days with temperature inversion was extracted at the stations. Three types of radiation, superstructure and frontal inversion were identified as three main types and four other types as combinational types of these three types of inversion. Then the frequency distribution and percent of each of the seven inversion types were calculated for each station in the 12 months of the year. The eleven-year process of each inversion type was determined using the non-parametric Man-Kendall method and the estimator of the Estimator slope and compared with each other.
Results and discussion
Results analysis indicated that from the seven inversion types, the inversion type of radiation in the three stations under study in all months of the year has been quite decreasing and significant trend at 95% and 99% levels. The subsurface inversion type at all three stations showed a positive and significant trend at 95% and 99% levels in the most months of the year.
The trend of forward inversions in the stations under study has been decreasing for the most months (the Z score and Sen’s Estimator Slope is negative). Radiation-submerged-frontal combined type inversion in the study period in all studied stations in most months has no significant trend. Among the seven types of inversion observed at the studied stations, the combination of radiation-subsidence type has the most significant and incremental trend in all three stations. In all three stations, for 6 months of the year, the increasing frequency of radiation-subsidence type at 95% and 99% confidence levels was significant and the most frequent increase in this type of inversion occurred in the winter and autumn seasons. The combined type of radial-frontal inversion and the Subsidence- frontal type at all stations in Tehran, Mashhad and Tabriz have not been significantly trendy for most of the months. The investigation results of the number of inversion layers in the stations showed that in all three stations in all months of the year, the number of inversion layers increased significantly at 99% and 95% confidence levels. An annual review of the frequency of inversion days in all three stations showed a significant increase in the annual scale. In this study, using the inversion layer temperature difference, the thickness of the inversion layer and the station height were used to calculate the intensity of the inversions.
Formula (1) I=((Δθ)2)/(3+Z(Δz))
The inversions were calculated only for inversions of the surface of the earth up to the surface of 500 hPa, then by applying the two conditions of the Haffter ((Δθ / (Δz)> 0/005 km ^ (-1) and θ_"t" -θ_"b" >2( Critical inversion was investigated by the total inversion occurred and the severity of the inversions trends. The results of applying the Mann-Kendall test and the Sen’s Estimator Slope on the data of the severity of critical inversions in different months of the year showed that except for the months of October, November and December at the Mehrabad station, the rate of critical invertebrates was significant at 95 % level. For the rest of the months, the trend of severity of critical inversions has been increasing, but they are not significant at all levels of confidence. In February, the trend of inversion was decreasing in all three stations.
Conclusion
The results showed that the radiation type inversion occurred in the period 2007-2017 at all three stations decreased significantly, conversely, the subsidence inversion type showed a significant increase in all three stations. Radiation- Subsidence combined type had a significant increase in all three stations. It can be concluded that the types of inversion in the period of 2007-2017 have changed from pure inversion types to combine and multi-layer types and, specifically, to the Radiation- Subsidence type. The significance of the increasing trend of inversion layers was also confirmed by statistical tests. Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.

کلیدواژه‌ها [English]

  • Tehran
  • Mashhad
  • Tabriz
  • inversion

اسماعیلی، ر. (1396). بررسی ساختار وارونگی دمایی شهر مشهد، پایان‏نامة کارشناسی ارشد آب و هواشناسی شهری، گروه جغرافیا، دانشگاه فردوسی مشهد.

پناهی، ع. (1395). بررسی الگوهای همدیدی براساس دوره‏های بحرانی آلودگی هوا در وارونگی دمایی شدید شهر تبریز، پژوهش‏های جغرافیای طبیعی، 4: ۶۰۷-625.

جهان‏بخش اصل، س. و روشنی، ر. (1392). بررسی وضعیت و شدت وارونگی‏های سطح پایین ‏شهر تبریز طی دورة 2004 تا 2008، فصل‏نامة تحقیقات جغرافیایی، 4: 45-54.

جهان‏بخش اصل، س. و روشنی، ر. (1393). بررسی شرایط الگوی سینوپتیکی حاکم بر وضعیت وارونگی دمای بسیار شدید شهر تبریز، نشریة جغرافیا و برنامهریزی، 48: ۸۱-96.

حسین‏زاده، س.‏ر.؛ دوستان، ر. و حقیقت ضیابری، س.‏م. (139۲). بررسی الگوهای همدید مؤثر بر آلودگی هوا در کلان‏شهر مشهد، مجلة جغرافیا و توسعة ناحیه‏ای، 11: ۸۱ -۱۰۱.

صادقی، س.؛ مفیدی، ع.؛ جهانشیری، م. و دوستان، ر. (1393). نقش الگوهای گردش منطقه‏ای جو بر وقوع روزهای بسیار آلوده در شهر مشهد، جغرافیا و مخاطرات محیطی، 10: ۱-35.

صفوی، ی. و علیجانی، ب. (1385). بررسی عوامل جغرافیایی در آلودگی هوای تهران، پژوهش‏های جغرافیایی، 58: 99-۱۱۲.

طاوسی، ت. (1397). آب و هواشناسی فیزیکی، انتشارات دانشگاه سیستان و بلوچستان.

عظیمی، ف. (1387)، ارزیابی تأثیر وارونگی دما بر روند آلودگی هوای شهر اهواز؛ فصل‏نامةجغرافیایی سرزمین، 19: ۱۰۵-112.

علیجانی، ب. و نجفی نیک، ز. (1388). بررسی الگوهای سینوپتیکی اینورژن در مشهد با استفاده از تحلیل عاملی جغرافیا و توسعة ناحیه‏ای،  7(12): ۱-11.

کرم‏پور، م.؛ سلیقه، م.؛ طولابی‏نژاد، م. و زارعی چغابلکی، ز. (1395). بررسی آلودگی هوای شهر تهران به روش وارونگی بحرانی هافتر، تحلیل فضایی مخاطرات محیطی، 1: ۵۱-64.

کیخسروی، ق. و لشکری، ح. (1393). تحلیل رابطه بین ضخامت ارتفاع وارونگی و شدت آلودگی هوا در شهر تهران، جغرافیا و برنامهریزی، 49: ۲۳۱-۲۵۷.

نوروزیان، م. (1394). بررسی ساختار وارونگی دما در کلانشهر تهران، پایان‏نامة کارشناسی ارشد جغرافیای طبیعی، دانشگاه فردوسی مشهد.

وثوقی، ا. و صراف‏زاده، م.ح. (1390). مطالعه و بررسی پدیدة وارونگی هوا و اثر آن روی آلودگی کلان‏شهرها، اولین همایش فناوری‏های پالایش در محیط زیست، تهران، دانشگاه شریف، دانشکدة مهندسی شیمی و نفت.

هدایت، پ. و لشکری، ح. (1385). تحلیل الگوی سینوپتیکی اینورژن‏های شدید شهر تهران، پژوهش‏های جغرافیایی، 56: ۶۵-82.

Alijani, B. and Najafi Nik, Z. (2009). Investigation of Inverted Synergistic Patterns in Mashhad Using Geographic Factor Analysis and Regional Development, 7(12): 1-11.

Azimi, F. (2008). Assessing the Impact of Temperature Inversion on Air Pollution Trends in Ahvaz City, Geographical Journal of Territory, 19: 105-112.

Bei, N.; Li, G.; Huang, R.; Cao, J.; Meng, N.; Feng, T.; Liu, S.; Zhang, T.; Zhang, Q. and Molina, L.T. (2016). Typical synoptic situations and their impacts on the wintertime air pollution in the Guanzhong basin, China, Journal Atmospheric Chemistry and Physics, NO. 0: 1-34.

Brümmer, B. and Schultze, M. (2015). Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast, Meteorologische Zeitschrift, 24(5): 481-494.

Cannarozzo, M.; Noto, L.V. and Viola, F. (2006). Spatial Distribution of Rainfall Trends in Sicily, Journal of Physics and Chemistry of the Earth, 31: 1201-1211.

Chappelka, H. and Pan, S. (2007). Influence of ozone pollution and climate variability on net Primary productivity and carbon storage in China's grassland ecosystems from 1961 to 2000, Environmental Pollution, 149: 85-94.

Hedayat, P. and Lashkari, H. (2006). Synoptic pattern of very intense inversions in Tehran, Geographical studies, 56: 65-82.

HosseinZadeh, S.; Dostan, R.; Hagigat Ziyabari, S.M. and Hagigat Ziyabari, S.M. (2013). Investigating the synoptic patterns affecting air pollution in the metropolis of Mashhad, Journal of Geography and Regional Development, 11(21): 81-101.

Iacobellis, S.F.; Norris, J.R.; Kanamitsu, M.; Tyree, ‎‏ M. and Cayan, D.C. (2009). Climate ‎Variability and‏ California Low-level Temperature Inversions, California Climate Change Center, 1- 47.

Ismaili, R. (2017). Investigation of the Structure of Temperature Inversion in Mashhad, M.Sc. in Urban Meteorology, Department of Geography, Ferdowsi University of Mashhad.

JahanBakhsh ASL, S. and Rohsnai, R. (2014). Synoptic pattern of very intense inversion in Tabriz, Iran, Journal of Geography and planning, 96: 81-96.

JahanBakhshasl, S. and Rohsnai, R. (2013). Low-level inversion and intensity in Tabriz, Iran from 2004 to 2008, Seasonal Journal of Geographical Studies, 4: 45-54.

Karampour, M.; Saligheh, M.; Toulabinejad, M. and Zarei Choghabaki, Z. (2016). Evaluation of air pollution in Tehran city by Hefter's critical Inversion method, Jsaeh, 3(1): 51-64.

Keykhosrowi, GH. and Hasan Lashkari, H. (2014). Analysis of the Relationship between the Thickness and Height of the Inversion and the Severity of Air Pollution in Tehran, Journal ofGeography and planning, 18(49): 231-257.

Lin, J. and Michael B.M. (2010). Impacts of boundary layer mixing on pollutant vertical profiles in the lower troposphere: Implications to satellite remote sensing, Atmospheric Environment, 44: 1726-1739. DOI: 10.1016/j.atmosenv.2010.02.009.

Nowruzian, M. (2015). Investigation of Temperature Inversion Structure in Tehran Metropolis, M.Sc. in Natural Geography, Ferdowsi University of Mashhad.

Panahi, AS. (2016). Investigation of Synoptic Patterns Based on Critical Periods of Air Pollution in Severe Temperature Inversion in Tabriz, Geography Research, 4: 625-607.

Sadegi, R.; Mofidi, A.; Jahanshiri, M. and Dostan, R. (2014). Investigating the role of regional scale atmospheric circulation patterns on heavily polluted days in the city of Mashhad, Journal of Geography and Environmental Hazards, 3(10): 1-35.

Safavi, Y. and Alijani, B. (2006). Effective geographical factors in Tehran air pollution, Geographical studies, 58: 99-112.

Tavousi, T. (2018). Physical Climatology, Sistan and Baluchestan University Press.

Vosoughi, A. and Sarrafzadeh, M.H. (2011). Investigation of air inversion phenomenon and its effect on metropolitan pollution Case study, First Conference on Environmental Purification Technologies, Tehran, Sharif University, Faculty of Chemical and Petroleum Engineering.

Yasmeen, Z. (2011). Inversion Layer and its Environmental Impact over Karachi, Pakistan Journal of Meteorology, 7: 53-62.

Zeng, S. and Zhang, Y. (2017). The Effect of Meteorological Elements on Continuing Heavy Air Pollution, A Case Study in the Chengdu Area during the 2014 Spring Festival, Atmosphere, 8(4): 85-94.