سامانه مدیریت نشریات علمی دانشگاه شهید بهشتی

رئیس پور, کوهزاد, خسروی, یونس. (1400). پایش بلندمدت غلظت آلاینده‌ کربن سیاه (BC) در ایران با استفاده از داده‌های مدل مبنای NASA/MERRA-2. , 19(3), 99-122. doi: 10.52547/envs.2021.33941
کوهزاد رئیس پور; یونس خسروی. "پایش بلندمدت غلظت آلاینده‌ کربن سیاه (BC) در ایران با استفاده از داده‌های مدل مبنای NASA/MERRA-2". , 19, 3, 1400, 99-122. doi: 10.52547/envs.2021.33941
رئیس پور, کوهزاد, خسروی, یونس. (1400). 'پایش بلندمدت غلظت آلاینده‌ کربن سیاه (BC) در ایران با استفاده از داده‌های مدل مبنای NASA/MERRA-2', , 19(3), pp. 99-122. doi: 10.52547/envs.2021.33941
رئیس پور, کوهزاد, خسروی, یونس. پایش بلندمدت غلظت آلاینده‌ کربن سیاه (BC) در ایران با استفاده از داده‌های مدل مبنای NASA/MERRA-2. , 1400; 19(3): 99-122. doi: 10.52547/envs.2021.33941

پایش بلندمدت غلظت آلاینده‌ کربن سیاه (BC) در ایران با استفاده از داده‌های مدل مبنای NASA/MERRA-2

فصلنامه علوم محیطی
مقاله 7، دوره 19، شماره 3، مهر 1400، صفحه 99-122    اصل مقاله (1.9 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.52547/envs.2021.33941
نویسندگان
کوهزاد رئیس پور* 1؛ یونس خسروی2
1گروه جغرافیا، دانشکده علوم انسانی، دانشگاه زنجان، زنجان، ایران
2گروه محیط زیست، دانشکده علوم پایه، دانشگاه زنجان، زنجان، ایران
چکیده
سابقه و هدف: جو یا اتمسفر سامانه‌ گازی طبیعی پویا و پیچید‌ه‌ای است که آلودگی آن بیش از هر آلودگی دیگری جان انسان‌ها را می‌گیرد. آلودگی هوا زمانی اتفاق می‌افتد که حجم زیادی از ذرات یا مواد مضر معلق وارد اتمسفر شود. ذرات معلق با قطر کمتر از 5/2 میکرون (PM 2.5) از جمله مهمترین آلاینده‌های هوا محسوب می‌شوند. ذرات کربن سیاه (BC)1 یکی از اجزاء بسیار مهم و خطرناک ذرات معلق با قطر کمتر از  µm5/2 به‌­شمار می‌رود. بر همین اساس، این پژوهش با هدف تحلیل رفتار و پراکنش زمانی‌ ـ مکانی آلاینده‌ کربن سیاه (BC) در گستره‌ جغرافیایی ایران با استفاده از داده‌های مدل مبنایMERRA-2 2 طی دوره‌ی آماری 40 ساله (2019 - 1980) انجام گردید.
مواد و روش‌ها: در این تحقیق در ابتدا داده‌های کربن سیاه با فرمت NetCDF با گام‌های زمانی ماهانه و مکانی 0.5° x 0.625° از وبگاه Earth data استخراج گردید. پس از استخراج داده‌ها، عملیات کنترل کیفی، پیش‌پردازش و پردازش روی آن­ها اِعمال شد. سپس محاسبات روی دو ماتریس ماهانه و فصلی (روی 740 پیکسل یا نقاط شبکه‌بندی شده) با استفاده از امکاناتی که نرم‌افزارهای کاربردیArcGIS  , Grads و Origin pro در اختیار کاربر قرار می‌دهد، انجام شد. در گام آخر برای ساخت لایه‌های رستری، وکتوری، نمودارها و جدول­های اطلاعاتی اقدام و خروجی‌های مورد نظر تهیه گردید.
نتایج و بحث: استفاده از داده‌های مدل مبنای MERRA-2 نتایج بسیار خوبی از توزیع زمانی ـ مکانی پراکنش آلاینده‌ کربن سیاه در گستره‌ ایران ارائه داده ‌است. نتایج بررسی نشان ‌داد که تفاوت‌های ماهانه و فصلی بسیار چشمگیر بوده ‌است، به‌طوریکه به لحاظ ماهانه، بیشترین میزان کربن سیاه در ماه دسامبر و کمترین میزان آن در ماه ژوئن برآورد شده ‌است. در میان فصل­ ها نیز، بیشترین و کمترین میزان کربن سیاه مربوط به فصل­های زمستان و تابستان است. به لحاظ مکانی نیز، بیشترین پراکنش کربن سیاه در نیمه‌ غربی ایران و بویژه روی کلان‌شهرهای تهران و اهواز مشاهده شد. واکاوی روند سری زمانی غلظت کربن سیاه در جو ایران نشان‌داد که غلظت این آلاینده در طول دوره‌ آماری افزایشی و این افزایش بویژه از سال 2000م به بعد اتفاق ‌افتاد. همچنین در بررسی پارامترهای هواشناسی مؤثر بر غلظت کربن سیاه، نتایج حاصله به­خوبی بیانگر همبستگی مثبت معنی‌دار میان غلظت کربن سیاه با فشار هوا و منفی معنی‌دار با سرعت باد است.
نتیجه‌گیری: نتایج حاصله به ­خوبی درک روشنی از غلظت کربن سیاه (BC) را در جو ایران نشان داد. این نتایج که از واکاوی آماری و اِعمال الگوریتم‌های بهینه روی اطلاعات مکان‌دار (GIS) آلاینده‌ کربن سیاه در گستره‌ی جغرافیایی کشور ایران حاصل گردید؛ بیانگر تفاوت آشکار در توزیع زمانی و مکانی غلظت کربن سیاه در طول دوره‌ آماری 40 ساله (2019 – 1980) بوده‌ است. افزون بر نتایج بالا، آلاینده‌ کربن سیاه از برخی پارامترهای هواشناسی از قبیل فشار هوا و سرعت باد متأثر است. به­ طور کلی صرف‌نظر از ساز و کارهای تکوین، ماهیت و انتشار این آلاینده در نواحی مختلف ایران، رفتار غلظت این آلاینده‌ در بستر زمان، بیانگر هشداردهنده‌ بودن خطر آن در بخش‌های وسیعی از کشور ایران می‌باشد. بنابراین اتخاذ راهکارهای مدیریتی و اجرایی لازم در راستای کاهش این آلاینده، بویژه در کلان ‌شهرهای همراه با غلظت بالای کربن سیاه امری ضروری به نظر می‌رسد.
کلیدواژه‌ها
آلودگی هوا؛ ذرات معلق؛ تحلیل زمانی ‌ـ مکانی؛ کربن سیاه؛ مدل MERRA-2
عنوان مقاله [English]
Long-term monitoring of the concentration of carbon black pollutants in Iran using NASA/MERRA-2 base model data
نویسندگان [English]
Koohzad Raispour1؛ younes khosravi2
1Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan, Iran
2Department of Environment, Faculty of Basic Sciences, University of Zanjan, Zanjan, Iran
چکیده [English]
Introduction: The atmosphere is a dynamic and complex natural gas system whose pollution kills humans more than others. Air pollution occurs when large amounts of suspended particles or harmful substances enter the atmosphere. Suspended particles with a diameter of fewer than 2.5 μm (PM2.5) are among the most important air pollutants. Black carbon (BC) particles are one of the most important and dangerous components of PM2.5 suspended particles. The aim of this study was to analyze the behavior and time-space distribution of BC pollutants in Iran using the data of the MERRA-2 base model during a statistical period of 40 years (1980-2019).
Material and methods: In this study, black carbon data in NetCDF format with initial monthly and spatial time steps of 0.5° x 0.625° were first extracted from the Earth data website. After extracting the data, qualitative control, pre-processing and, processing operations were performed. Then, the calculations were performed on monthly and seasonal matrices (on 740 pixels or networked points) using the facilities that the user's software applications ArcGIS, Grads, and Origin pro provide. In the last step, steps were taken to create raster, vector, charts layers and, information tables and the desired outputs were prepared.
Results and discussion: The use of MERRA-2 base model data has provided very good results of the spatio-temporal distribution of BC in Iran. The results of the study showed that the monthly and seasonal differences were significant. In terms of monthly differences, the highest amount of BC was estimated in December and the lowest in June. Among seasons, the highest and lowest levels of BC were related to the winter and summer. Spatially, the highest distribution of BC was observed in the western half of Iran, especially in the metropolises of Tehran and Ahvaz. Analysis of the time series of BC concentrations in the Iranian atmosphere showed that the concentration of this pollutant increased during the statistical period and this increase occurred especially from 2000 AD onwards. Also, in the study of meteorological parameters affecting the concentration of BC, the results showed a significant positive correlation between the concentration of BC and air pressure and a significant negative correlation with wind speed.
Conclusion: The results showed a clear understanding of the concentration of BC in the Iranian atmosphere. We showed that BC pollution is affected by some meteorological parameters such as air pressure and wind speed. In general, regardless of the mechanisms of development, nature, and emission of this pollutant in different parts of Iran, the behavior of the concentration of this pollutant in the context of time indicates the warning of its danger in large parts of Iran. Therefore, it is necessary to take the necessary management and executive measures to reduce this pollution, especially in metropolitan areas with high concentrations of BC.
کلیدواژه‌ها [English]
Air pollution, particulate matter, temporal-spatial analysis, black carbon, MERRA-2 model
مراجع

Aaheim, H.A., Fuglestvedt, J.S. and Godal, O., 2006. Cost’s savings of a flexible multi‐gas climate policy. The Energy Journal. 13, 485-502.
Abbatt, J.P., Benz, S., Cziczo, D.J., Kanji, Z., Lohmann, U. and Mohler, O., 2006. Solid ammonium sulfate aerosols as ice nuclei: A pathway for cirrus cloud formation. Science. 313, 1770-1779.
Abdul-Razzak, H. and Ghan, S.J., 2000. A parameterization of aerosol activation: Multiple aerosol types. Journal Geophysical Research. 105, 6837- 6844.
Afyoni, M. and Arfan-Manesh, M., 2015. Environmental pollution: water, soil and air. Eleventh Edition., Arkan Danesh Publications, Isfahan, Iran.
Ajami-Trichan, N., Omidvar, K. and Shahaeyan, S., 2015. Assessing the effect of air pollution on mortality from heart attacks in Mashhad. The First International Conference and the Fourth National Conference on Tourism, Geography and Sustainable Environment, Hamedan.P.36. (In Persian with English Abstract).
Arhami, M., Hosseini, V., Shahne, M.Z., Bigdeli, M., Lai, A. and Schauer, J., 2017. Seasonal trends, chemical speciation and source apportionment of fine PM in Tehran. Atmospheric Environment. 153, 70-82 .
Bell, G., Mora, S., Greenland, P., Tsai, M., Gill, E. and Kaufman, J.D., 2017. Association of air pollution exposures with high density lipoprotein cholesterol and particle number: the multi-ethnic study of atherosclerosis. National Library of Medicine. 7, 976-982.
Bian, H., Colarco, P.R., Chin, M., Chen, G., Rodriguez, J.M., Liang, Q. and Diskin, G., 2013. Source attributions of pollution to the Western Arctic during the NASA ARCTAS field campaign. Atmospheric Chemistry and Physic. 13, 4707-4721.
Bigdeli, A., 2001. The effect of climate and air pollution in Tehran on heart attack disease. Journal of Geographical Research. 6, 27-41. (In Persian).
Bisiaux, M.M., Edwards, R., Mcconnell, J.R., Albert, M.R., Anschutz, H., Neumann, T., Isaksson, E. and Penner, J.E., 2011. Variability of black carbon deposition to the East Antarctic Plateau, AD 1800–2000. Atmospheric Chemistry and Physics. 11, 31091–31114.
Bisiaux, M.M., Edwards, R., McConnell, J.R., Curran, M.A., Vanommen, T.D., Smith, A.M., Neumann, T.A., Pasteris, D.R., Penner, J.E. and Taylor, K., 2012. Changes in black carbon deposition to Antartica from two high-resolution ice core records, 1850-2000 AD. Atmospheric Chemistry and Physics.12, 4107-4115.
Bloom, S., Takacs, L., DaSilva, A. and Ledvina, D., 1996. Data assimilation using incremental analysis updates. Monthly Weather Review. 124,1256-1271.
Bond, T.C., Doherty, S.J., Fahey, D.W. and Forster, P., 2013. Bounding the role of black carbon in the climate system: a scientific assessment. Journal of Geophysical Research: Atmosphere. 118, 5380-5552.
Buchard, V., Silva, A.M., Colarco, P.R., Darmenov, A., Randles, C.A., Govindaraju, R., Torres, O., Campbell, J. and Spurr, R., 2015. Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis. Atmospheric Chemistry and Physics. .15, 5743-5760.
Buchard, V., Silva, A.M., Randles, C.A., Colarco, P., Ferrare, R., Hair, J., Hostetler, C., Tackett, J. and Winker, D., 2016. Evaluation of the surface PM 2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States. Atmospheric Environment.125, 100-111.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B.N., Duncan, B.N., Martin, R.V., Logan, J.A., Higurashi, A. and Nakajima, T., 2002. Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and Sun photometer measurements. Journal Atmospheric Science. 59, 461-483.
Colarco, P., Dasilva, A., Chin, M. and Diehl, T., 2010. Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. Journal of Geophysical Research Atmospheres. 115, 1-17.
Dubovik, O., Smirnov, A., Holben, B.N., King, M.D., Kaufman, Y.J., Eck, T.F. and Slutsker, I., 2000. Accuracy assessments of aerosol optical properties retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance measurements. Journal of Geophysical Research Atmospheres. 105, 9791-9806.
Dutkiewicz, V., Alvi, S., Ghauri, B.M., Choudhary, M. and Husain, L., 2009. Black carbon aerosols in urban air in South Asia. Journal Atmospheric Environment. 4310, 1737-1744.
Farzad, K., Taheri, A. and Khorsandi, B., 2018. Estimation of health effects due to exposure to carbon black pollution using BenMAP software in Tehran in the second half of 2017 and the first six months of 2018. 7th National Conference on Air and Sound Pollution Management, Tehran, Shahid Beheshti University, Clean Air Scientific Association Iran.P.76.
Hansen, A.D., Rosen, H. and Novakov, T., 1984. The aethalometer an instrument for the real-time measurement of optical absorption by aerosol particles. Science of the Total Environment, 36, 191-196 .
Hoek, G., Krishnan, R.M. and Beelen, R., 2013. Long-term air pollution exposure and cardio-respiratory mortality: a review. Environ Health. 12, 43-47.
Holben, B.N., Eck, T.F., Slutsker, I., Tanre, D., Buis, J.P., Setzer, A., Vermote, E., Reagan, J.A., Kaufman, J. and Nakajima, T., 1998. AERONET a federated instrument network and data archive for aerosol characterization. Remote Sensing Environment. 66, 1-16.
Inness, A., Inness, A., Ades, M., Agustipanareda, A., Barre, J., Benedictow, A., Blech Schmidt., A.M. and Dominguez, J.J., 2019. The CAMS reanalysis of atmospheric composition. Atmospheric Chemistry Physic. 9, 3515-3556.
Jose, S., and Singh, S., 2018. Long term characteristics of black carbon measurements at an urban location in IGP and the assessment of MERRA-2 black carbon dataset. American Geophysical Union. 32, 95-113.
Julia, S., Mark, F., Shichang, K., Michael, S., Qianggong, Z., Junming, G., Yang, L., Margit, S. and Daniel F., 2017. Modulation of snow reflectance and snowmelt from Central Asian glaciers by anthropogenic black carbon. Scientific Reports. 7, 465-478.
Julie, C., 2010. Black carbon a significant factor in melting of himalayan glaciers. Bringing Science Solutions. 17, 486-510 .
Karcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K and Sarofim, M.C., 2013. Bounding the role of black carbon in the climate system: A scientific assessment. Journal of Geophysical Research: Atmospheres. 118, 5380-5552.
Kaspari, S.D., Painter, T.H., Gysel, M., Skiles, S.M. and Schwikowski, M., 2014.Seasonal and elevational variations of black carbon and dust in snow and ice in the Solu-Khombu, Nepal and estimated radiative forcings. Atmospheric Chemistry Physic. 14, 8089-8103.
Kaspari, S.D., Schwikowski, M., Gysel, M., Flanner, M,G., Kang, S. and Hou, S., 2011. Recent increase in black carbon concentrations from a Mt. Everest ice core spanning 1860–2000 AD. Geophysical Research Letter. 38, 1-6.
Kristofer, L., Krishna, P.V., Thanh, T. and Nhat, N., 2018. Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets. PLoS ONE. journal Pone. 13, 1-17.
Laden, F., Schwartz, J. and Speizer, F.E., 2006. Reduction in fine particulate air pollution and mortality: Extended follow-up of the Harvard six cities study. National Library of Medicine. 173, 667-672.
Lerato, S., 2019. Long-term observation of global black carbon, organic carbon and smoke using CALIPSO and MERRA-2 data. Remote Sensing Letters. 10, 373-380.
Mckenzie, S. and Thomas, P.m., 2017. Daily evolution in dust and black carbon content snow grain size and snow albedo during snowmelt Rocky Mountains Colorado. Journal of Glaciology, 63, 118-132.
Menon, S., Koch, D., Beig, G., Sahu, S., Fasullo, J. and Orlikowski, D., 2010. Black carbon aerosols and the third polar ice cap, Atmospheric Chemistry and Physics. 10, 4559-4571.
Ming, J., Xiao, C., Cachier, H., Qin, D. and Qin, X., 2009. Black Carbon (BC) in the snow of glaciers in west China and its potential effects on albedos. Journal of Atmospheric Research. 92,
132-154.
Molod, A., Takacs, L., Suarez, M., Bacmeister, J., Song, I.S. and Eichmann, A., 2012. The GEOS-5 atmospheric general circulation model: mean climate and development from MERRA to fortuna; NASA technical report series on global modeling and data assimilation. Greenbelt. 117, 28-45.
Nowottnick, E., Colarco, P., Ferrare, R., Chen, G., Ismail, S., Anderson, B. and Browell, E., 2010. Online simulations of mineral dust aerosol distributions: Comparisons to NAMMA observations and sensitivity to dust emission parameterization. Journal of Geophysical Research Atmospheres. 115, 1-19.
Omidvar, K. and Narangi-Fard., 2013. Analysis of similar patterns of Farin days contaminated with suspended particles in Shiraz. Journal of Geography and Environmental Studies. 2 , 49-62. (In Persian).
Pope, C.A and Dockery, D.W., 2006. Health effects of fine particulate air pollution: lines that connect. Journal of the Air and Waste Management Association. 56, 709–742.
Puett, R.C., Hart, J.E. and Yanosky, J.D., 2009. Chronic fine and coarse particulate exposure, mortality and coronary heart disease in the Nurses’ Health Study. Environ Health Perspect. 117, 1697–1701.
Putero, D., Landi, T.C., Cristofanelli, P., Marinoni, A., Laj, P. and Duchi, R., 2014. Influence of open vegetation fires on black carbon and ozone variability in the southern Himalayas. Environmental Pollution. 184, 597–604.
Qin, W., Zhang, Y., Chen, J., Yu, Q., Cheng, S., Li, W., Liu, X. and Tian, H., 2019. Variation, sources and historical trend of black carbon in Beijing, China based on ground observation and MERRA-2 reanalysis data. Environmental Pollution. 245, 853-863.
Raispour, K., Fahimi, H., Poorkarim, R., 2020. Analysis of Spatio-temporal Distribution of Surface Wind Speed in Geographical Area of Iran Using MERRA-2 Model. Journal of Natural Geography.13 (48), 89-104. (In Persian).
Ramanathan, V. and Carmichael, G., 2008. Global and regional climate changes due to black carbon. Nature geoscience. 1, 221–227.
Randles, C.A., Dasilva, A., Buchard, V., Colarco, P.R, Darmenov, A.S., Govindaraju, R.C., Smirnov, A., Ferrare, R.A., Hair, J.W. and Shinozuka, Y., 2017. The MERRA-2 Aerosol Reanalysis, 1980-onward, Part I: System description and data assimilation evaluation. Journal Climatology. 30, 6823-6850.
Rienecker, M.M., Suarez, M.J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E. and Bosilovich, M.G., 2011. MERRA: NASA’s modern-era retrospective analysis for research and applications. Journal Climatology. 24, 3624–3648.
Rizza, U., Miglietta, M.M., Mangia, C., Ielpo, P., Morichetti, M., Iachini, C., Virgili, S. and Passerini, G., 2018. Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region). Atmospheric Research. 201, 168–180.
Shahbazi, H., Reyhanian, M., Hosseini, V. and Afshin, H., 2016. The relative contributions of mobile sources to air pollutant emissions in Tehran, Iran: an emission inventory approach. Emission Control Science and Technology. 2, 44-56. (In Persian).
Shariapoor, Z., Akbari-Bidakhti, A., 2014. Spatial distribution study of air pollutants in Tehran for the cold months of 201-2013. Journal of Environmental Science and Technology. 16, 149-166. (In Persian).
Sitnov, S.A., Mokhov, I.I. and Likhosherstova, A.A., 2020. Exploring large-scale black-carbon air pollution over Northern Eurasia in summer 2016 using MERRA-2 reanalysis data. Atmospheric Research. 235, 1217-1228.
Sterle, K.M., McConnell, J.R, Dozier, J., Edwards, R. and Flanner, M.G., 2013. Retention and radiative forcing of black carbon in the Eastern Sierra Nevada snow. The Cryosphere. 7, 365-374.
Taheri, A., Ali-Asghari, P. and Hosseini, V., 2017. Investigating the effect of moving diesel vehicles in Tehran on black carbon pollution. Quarterly Journal of Engineering Research. 49, 19-28. (In Persian).
Taheri, A., Ali-Asghari, P. and Hosseini, V., 2018. Evaluation of black carbon annual measurement data in Tehran and evaluation of particle specifications. 7th National Conference on Air and Sound Pollution Management. Tehran, Shahid Beheshti University, Iranian Clean Air Scientific Association.P.120. (In Persian).
Virkkula, A., Chi, X., Ding, A., Shen, Y., Nie, W., Qi, X. and Petaja, T., 2015. On the interpretation of the loading correction of the aethalometer. Atmospheric Measurement Techniques. 8, 4415-4427.
Wendl, I.A, Menking, J.A., Farber, R., Gysel, M., Kaspari, S.D., Laborde, M.J. and Schwikowski, M., 2014. Optimized method for black carbon analysis in ice and snow using the single particle soot photometer. Atmospheric Measurement Techniques. 7, 2667-2681.
Wu, W.S., Purser, R.J. and Parrish, D.F., 2002. Three-dimensional variational analysis with spatially inhomogeneous covariances. Monthly Weather Review. 130, 2905-2916.
Yuan, C ., Mathieu, F., Cen, K. and Xiu-li, L., 2016. Long-term variation of black carbon and PM2.5 in Beijing, China with respect to meteorological conditions and governmental measures.Environmental Pollution. 212, 269-278.
Zare, M., 2003. Quantitative and qualitative study of some air pollutants in Yazd city and urban planning to control it. Master's thesis. Yazd University. (In Persian).
Zhang, T., Wooster, M.J, Green, D.C. and Main, B., 2015. New field-based agricultural biomass burning trace gas, PM 2.5 and black carbon emission ratios and factors measured in situ at crop residue fires in Eastern China. Atmospheric Environment. 121,22-34.

آمار
تعداد مشاهده مقاله: 11,916
تعداد دریافت فایل اصل مقاله: 6,204