نقش جریانات باد بر منشأ غلظت گاز گلخانهای دیاکسیدکربن در مقیاس استانی
محورهای موضوعی : مدیریت محیط زیستسید محسن موسوی 1 , سامره فلاحتکار 2 , منوچهر فرج زاده 3
1 - کارشناس ارشد محیطزیست، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور، مازندران
2 - استادیار گروه محیط زیست دانشکده منابع طبیعی دانشگاه تربیت مدرس، نور، مازندران*(مسئول مکاتبات)
3 - استاد گروه سنجش از دور دانشکده علوم انسانی، دانشگاه تربیت مدرس، تهران
کلید واژه: توزیع مکانی, تغییر اقلیم, GOSAT, سرعت باد, دیاکسیدکربن,
چکیده مقاله :
زمینه و هدف: امروزه یکی از مهم ترین مشکلاتی که جهان با آن روبه رو شده افزایش تغییر آب و هوای جهانی به علت انتشار بیش از حد گازهای گلخانه ای می باشد. گاز دی اکسیدکربن به عنوان مهم ترین گاز گلخانه ای و اولین عامل در تغییر اقلیم شناخته شده است. عوامل مختلفی از جمله توپوگرافی، بارندگی، جریانات هوا و وجود باد از عوامل مهم در پخش، رقیق کردن و جابه جای گازهای گلخانه ای موجود در اتمسفر محسوب می شوند. روش بررسی: در مطالعه حاضر با استفاده از داده های سرعت باد ECMWF و داده های دی اکسید کربن ماهواره GOSAT به صورت تخصصی به بررسی نقش باد در پی بردن به منابع محلی یا منطقه ای انتشار گاز دی اکسید کربن و هم چنین پی بردن به منابع احتمالی انتشار این گاز در مقیاس استانی پرداخته شد. یافته ها: . بیش ترین تجمع گاز گلخانه ای دی اکسید کربن در هر دو فصل سرد و گرم در منطقه جنوب و جنوب شرق ایران قرار دارد. البته گستره پراکندگی و غلظت بالاتر این گاز در فصل زمستان بیش تر از فصل تابستان است. نتایج نشان داد که به طور عمده در اکثر استان های ایران منابع محلی عامل افزایش انتشار غلظت گاز دی اکسید کربن موجود در جو در فصل زمستان می باشد. بحث و نتیجه گیری: بالا بودن غلظت گاز دی اکسید کربن در فصل زمستان می تواند نشان دهنده مصرف بیش تر سوخت های فسیلی برای گرمایش نسبت به فصل تابستان و عدم انجام فرایند فتوسنتز توسط گیاهان در فصل سرد باشد. در صورتی که در فصل تابستان مطابق با موقعیت جغرافیایی استان های مورد مطالعه نقش منابع منطقه ای در انتشار دی اکسید کربن بیش تر از منابع محلی می باشد.
Background and Purpose: One of the most important problems in the world is the increase of global climate change due to excessive greenhouse gas emissions. Carbon dioxide gas is known as the most important greenhouse gas and the first factor in climate change. Various factors such as topography, rainfall, air currents and the presence of wind are important factors in the diffusion, dilution and displacement of greenhouse gases in the atmosphere. Method: In the present study, using ECMWF wind speed data and GOSAT satellite carbon dioxide data, the role of wind in detecting local sources or areas of carbon dioxide emissions and such an investigation was made into the possible sources of emissions of this gas on a provincial scale. Findings: The largest aggregate of carbon dioxide gas in both southern and southeastern Iran is located in both cold and hot seasons. However, the dispersion and concentration of this gas in winter is higher than in the summer. The results showed that in most of Iran's provinces, local resources are responsible for increasing the concentration of carbon dioxide gas in the atmosphere in winter. Discussion and Conclusion: High concentration of carbon dioxide gas in winter is due to the more consumption of fossil fuels for heating and lack of photosynthesis process in cold season. While in summer, according to the geographical location of the studied provinces, the role of regional sources of carbon dioxide emissions is more than local sources.
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- Yue, T. X., Zhao, M. W., and Zhang, X. Y. (2015) “A high-accuracy method for filling voids on remotely sensed XCO2 surfaces and its verification”, Journal of Cleaner Production, 103, 819-827.
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- Huang, J., Yu, H., Guan, X., Wang, G., and Guo, R. (2015) “Accelerated dryland expansion under climate change”, Nature Climate Change.
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- Raible, C. C., Yoshimori, M., Stocker, T. F., and Casty, C., (2007) “Extreme mid latitude cyclones and their implications for precipitation and wind speed extremes in simulations of the Maunder Minimum versus present day conditions”, Climate Dynamics, 28(4), 409-423.
- Ruti, P. M., Marullo, S., D'Ortenzio, F., and Tremant, M., (2008) “Comparison of analyzed and measured wind speeds in the perspective of oceanic simulations over the Mediterranean basin: Analyses, QuikSCAT and buoy data”, Journal of Marine Systems, 70(1), 33-48.
- Cantrell, C. A., (2008) “Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems”, Atmospheric Chemistry and Physics, 8(17): 5477-5487.
- Francis, D. P., Coats, A. J., and Gibson, D. G., (1999) “How high can a correlation coefficient be Effects of limited reproducibility of common cardiological measures”, International Journal of Cardiology, 69(2): 185-189.
- Sun, B., Zhou, S., & Zhao, Q., (2003) “Evaluation of spatial and temporal changes of soil quality based on geostatistical analysis in the hill region of subtropical China”, Geoderma, 115(1): 85-99.
- Mahesh, P., Sharma, N., Dadhwal, V. K., Rao, P. V. N., Apparao, B. V., Ghosh, A. K., ... and Ali, M. M. (2014) “Impact of Land-Sea Breeze and Rainfall on CO2 Variations at a Coastal Station”, Journal of Earth Science & Climatic Change, 5(6), 1.
- Guo, M., Wang, X. F., Li, J., Yi, K. P., Zhong, G. S., Wang, H. M., and Tani, H., (2013). Spatial distribution of greenhouse gas concentrations in arid and semi-arid regions: A case study in East Asia. Journal of Arid Environments, 91: 119-128.
- Shim, C., Lee, J., and Wang, Y., (2013). Effect of continental sources and sinks on the seasonal and latitudinal gradient of atmospheric carbon dioxide over East Asia. Atmospheric Environment, 79(85): 853-860.
- Prasad, P., Rastogi, S., and Singh, R. P., (2014). Study of satellite retrieved CO2 and CH4 concentration over India. Advances in Space Research, 54(9): 1933-1940.
- Guo, M., Xu, J., Wang, X., He, H., Li, J., & Wu, L., 2015. Estimating CO2 concentration during the growing season from MODIS and GOSAT in East Asia. International Journal of Remote Sensing, 36(17): 4363-4383.
- Mousavi, S.M, Falahatkar, S., & Farajzadeh, M. (2017). Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data. Natural Resources Forum, doi: 10.1111/1477-8947.12121.
- Mousavi, S. M., Falahatkar, S., & Farajzadeh, M. (2017). Monitoring of Monthly and Seasonal Methane Amplitude in Iran using GOSAT Data. Physical Geography 49 (2), 327-340 [In persian].
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- Mackenzie, F. T., )1981 (“Global carbon cycle: Some minor sinks for CO2, Flux of Organic Carbon by Rivers to the Oceans”, GE Likens, FT MacKenzie, JE Richey, JR Sedell, KK Turekian, 360-384.
- World Meteorological Organization) 2015 (“WMO WDCGG Data Summary No. 39; Japan Meteorological Agency/WMO: Tokyo, Japan, 2015; pp. 17–22.
- Hannah, L., )2014(“Carbon Sinks and Sources in: L, Hannah”, Climate change biology Second Edition, Elsevier: Academic Press, pp. 403-422.
- IPCC., )2007 (“Summary for Policymakers. In Climate Change 2007: The Physical Science Basis”, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., QIN, D., Manning, M., Chen, Z., Marquis, M., Averyte, K.B., Tignor, M., Miller, H.L. (Ed.). pp.18 (Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press).
- Bajracharya, S. (2008) “Community carbon forestry: remote sensing of forest carbon and forest degradation in Nepal”, Netherlands International Institute for Geo-Information Science and Earth Observation, 14-26.
- Fu, L., Zhao, Y., Xu, Zh., and Wu, B., )2015 (“Spatial and temporal dynamics of forest aboveground carbon stocks in response to climate and environmental changes”, Soils Sediments. 15(2): 249-259.
- Nayak, R. K., Deepthi, E. N., Dadhwal, V. K., Rao, K. H., & Dutt, C. B. S. (2014). Evaluation of NOAAcarbon tracker global carbon dioxide products. The International Archives of Photogrammetry,Remote Sensing and Spatial Information Sciences, 40(8), 287–290.
- Yue, T. X., Zhao, M. W., and Zhang, X. Y. (2015) “A high-accuracy method for filling voids on remotely sensed XCO2 surfaces and its verification”, Journal of Cleaner Production, 103, 819-827.
- Brewer, W., Hoffman, G., Silver, E., DiLeonardo, C., Henderson, J. R., and Vigil, S., )2012 (“Evaluating Use of Satellite Observations for Detecting Large CO2 Leaks and Carbon Sequestration Monitoring United States”, Lawrence Livermore National Laboratory1(1):1-35.
- Bell, T. W., Menzer, O., Troyo‐Diéquez, E., and Oechel, W. C. (2012) “Carbon dioxide exchange over multiple temporal scales in an arid shrub ecosystem near La Paz, Baja California Sur, Mexico”, Global Change Biology, 18(8), 2570-2582.
- Mousavi, S. M., & Falahatkar, S. (2019). Spatiotemporal distribution patterns of atmospheric methane using GOSAT data in Iran. Environment, Development and Sustainability, 1-17.
- Huang, J., Yu, H., Guan, X., Wang, G., and Guo, R. (2015) “Accelerated dryland expansion under climate change”, Nature Climate Change.
- Britter, R. E. (1989). Atmospheric dispersion of dense gases. Annual review of fluid mechanics, 21(1), 317-344.
- Oldenburg, C. M., and Unger, A. J., (2004) “Coupled vadose zone and atmospheric surface-layer transport of carbon dioxide from geologic carbon sequestration sites”, Vadose Zone Journal, 3(3), 848-857.
- 15.Chow, F. K., Granvold, P. W., and Oldenburg, C. M., (2009) “Modeling the effects of topography and wind on atmospheric dispersion of CO2 surface leakage at geologic carbon sequestration sites”, Energy Procedia, 1(1): 1925-1932.
- Deng, S., Shi, Y., Jin, Y., and Wang, L., (2011) “A GIS-based approach for quantifying and mapping carbon sink and stock values of forest ecosystem: A case study”, Energy Procedia, 5:1535-1545.
- World research institute, (2015). http://www.wri.org. last visited at 15/8/2015.
- ENI. (2016). Encyclopaedia Iranica. http://www.iranicaonline.org. Accessed December 6, 2017.
- Emissions database for global atmospheric research. http://edgar.jrc.ec.europa.eu/.
Accessed February 8, 2017. - Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and Maksyutov, S., (2009) “Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results”, Sola, 5: 160-163.
- Parker, R., Boesch, H., Cogan, A., Fraser, A., Feng, L., Palmer, P. I., ... and Wennberg, P. O. (2011) “Methane observations from the Greenhouse Gases Observing SATellite: Comparison to ground-based TCCON data and model calculations”, Geophysical Research Letters, 38(15).
- Yoshida, Y., Ota, Y., Eguchi, N., Kikuchi, N., Nobuta, K., Tran, H., ... and Yokota, T., (2011) “Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite”, Atmospheric Measurement Techniques, 4(4): 717-734.
- Miao, R., Lu, N., Yao, L., Zhu, Y., Wang, J., and Sun, J., (2013) “Multi-year comparison of carbon dioxide from satellite data with ground-based FTS measurements (2003–2011). Remote Sensing, 5(7): 3431-3456.
- Morino, I., Uchino, O., Inoue, M., Yoshida, Y., Yokota, T., Wennberg, P., ... and Rettinger, M., (2010) “Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra”, Atmospheric Measurement Techniques, 4(2):1061-1076.
- Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T., (2009) “Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring”, Applied Optics, 48(35): 6716-6733.
- Guo, M., Wang, X. F., Li, J., Yi, K. P., Zhong, G. S., Wang, H. M., and Tani, H., (2013) “Spatial distribution of greenhouse gas concentrations in arid and semi-arid regions: A case study in East Asia”, Journal of Arid Environments, 91: 119-128.
- Wang, T., Shi, J., Jing, Y., Zhao, T., Ji, D., and Xiong, C., (2014) “Combining XCO2 measurements derived from SCIAMACHY and GOSAT for potentially generating global CO2 maps with high spatiotemporal resolution”, PLoS ONE 9(8): 1-9.
- Boon, A., Broquet, G., Clifford, D. J., Chevallier, F., Butterfield, D. M., Pison, I., ... and Ciais, P. (2016) “Analysis of the potential of near-ground measurements of CO2 and CH4 in London, UK, for the monitoring of city-scale emissions using an atmospheric transport model”, Atmospheric Chemistry and Physics, 16(11), 6735-6756.
- Raible, C. C., Yoshimori, M., Stocker, T. F., and Casty, C., (2007) “Extreme mid latitude cyclones and their implications for precipitation and wind speed extremes in simulations of the Maunder Minimum versus present day conditions”, Climate Dynamics, 28(4), 409-423.
- Ruti, P. M., Marullo, S., D'Ortenzio, F., and Tremant, M., (2008) “Comparison of analyzed and measured wind speeds in the perspective of oceanic simulations over the Mediterranean basin: Analyses, QuikSCAT and buoy data”, Journal of Marine Systems, 70(1), 33-48.
- Cantrell, C. A., (2008) “Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems”, Atmospheric Chemistry and Physics, 8(17): 5477-5487.
- Francis, D. P., Coats, A. J., and Gibson, D. G., (1999) “How high can a correlation coefficient be Effects of limited reproducibility of common cardiological measures”, International Journal of Cardiology, 69(2): 185-189.
- Sun, B., Zhou, S., & Zhao, Q., (2003) “Evaluation of spatial and temporal changes of soil quality based on geostatistical analysis in the hill region of subtropical China”, Geoderma, 115(1): 85-99.
- Mahesh, P., Sharma, N., Dadhwal, V. K., Rao, P. V. N., Apparao, B. V., Ghosh, A. K., ... and Ali, M. M. (2014) “Impact of Land-Sea Breeze and Rainfall on CO2 Variations at a Coastal Station”, Journal of Earth Science & Climatic Change, 5(6), 1.
- Guo, M., Wang, X. F., Li, J., Yi, K. P., Zhong, G. S., Wang, H. M., and Tani, H., (2013). Spatial distribution of greenhouse gas concentrations in arid and semi-arid regions: A case study in East Asia. Journal of Arid Environments, 91: 119-128.
- Shim, C., Lee, J., and Wang, Y., (2013). Effect of continental sources and sinks on the seasonal and latitudinal gradient of atmospheric carbon dioxide over East Asia. Atmospheric Environment, 79(85): 853-860.
- Prasad, P., Rastogi, S., and Singh, R. P., (2014). Study of satellite retrieved CO2 and CH4 concentration over India. Advances in Space Research, 54(9): 1933-1940.
- Guo, M., Xu, J., Wang, X., He, H., Li, J., & Wu, L., 2015. Estimating CO2 concentration during the growing season from MODIS and GOSAT in East Asia. International Journal of Remote Sensing, 36(17): 4363-4383.
- Mousavi, S.M, Falahatkar, S., & Farajzadeh, M. (2017). Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data. Natural Resources Forum, doi: 10.1111/1477-8947.12121.
- Mousavi, S. M., Falahatkar, S., & Farajzadeh, M. (2017). Monitoring of Monthly and Seasonal Methane Amplitude in Iran using GOSAT Data. Physical Geography 49 (2), 327-340 [In persian].