Journal of Geography and Regional Development

Comparison of Correlation between Climatic Clements Affecting the Time Dispersion of CO and SO2 in Mazandaran Province

Document Type : Research

Authors

Aliasghar Shirzad 1
Ali Mohammad Khorshiddoost 2
Saeid Jahanbakhsh Asl 2

1 PhD student in Climatology and Environmental Planning, University of Tabriz, Tabriz, Iran.

2 Professor, Department of Climatology and Planning, University of Tabriz, Tabriz, Iran

https://doi.org/10.22067/jgrd.2024.90939.1496
Abstract
Urban air pollution currently stands as one of the most significant global environmental challenges, with extensive research confirming its detrimental effects on human health and ecosystems. Recent advancements in computer and atmospheric sciences have unveiled new opportunities for assessing the health impacts associated with air pollution. In line with this approach, the present study investigates the relationship between influential climatic elements and key air pollutants, i.e. carbon monoxide (CO) and sulfur dioxide (SO₂). This applied research employs an analytical-software-based methodology. Satellite imagery from various sensors,  including Sentinel-5, was utilized across different time scales. After filtering out cloudy days, data pertaining to CO and SO₂ pollutants were coded and extracted on a monthly basis using the Google Earth Engine platform. Subsequently, the extracted data was subject to analysis in the Minitab software using Pearson correlation coefficients. The results suggest that among the climatic elements studied, monthly precipitation (31%) demonstrated the highest correlation with carbon monoxide, while albedo (9.5%) exhibited the lowest. For sulfur dioxide, the highest and the lowest correlation was found for the latent heat flux (34%), and shortwave radiation (14%), respectively. Furthermore, the findings suggest that certain climatic variables have a low impact on the distribution of these pollutants within the province. Considering the escalating population growth, comprehensive development, and multifaceted environmental changes in the province, the results underscore the importance of addressing air pollution and the role of atmospheric pollutants. This highlights further attention from officials, policymakers, and the public alike.
 
 
 
 
 
 
 

Keywords

CO and SO₂ Pollutants
Temporal Analysis of Air Pollution
Influential Climatic Elements
Mazandaran Province
Subjects
  1. احسانی، ا. ه؛ و بیگدلی، م. (1399). تخمین غلظت ذرات5 در تهران با استفاده از داده‌های دورسنجی عمق نوری هواویزها. پژوهش­های اقلیم‌شناسی، 43(11)، 108-99.
  2. امیدوار، ک؛ شهائیان، س؛ و امیری‌اسفندقه م. (1399). بررسی ارتباط غلظت آلاینده‌ها و برخی پارامترهای اقلیمی با میزان مرگ‌های ناشی از بیماری‌های قلبی و تنفسی در شهر شیراز. مجلۀ علمی پژوهشی دانشگاه علوم پزشکی شهید صدوقی یزد، 28(۳)، ۲۴78-۲۴67.
  3. خورشیددوست، ع. م؛ محمدپور، ک؛ و بیورانی، ح. (1392). تأثیر عناصر اقلیمی و آلاینده‌ها بر روی بیماریهای سکته قلبی و آسم. فصلنامۀ علمی- پژوهشی فضای جغرافیایی، 13(42)، 120- 105.
  4. شفیع‌پور، م. (1387). مهندسی آلودگی هوا. چاپ اول. تهران: مؤسسه نشر شهر.
  5. عبدالمنافی‌جهرمی، ن؛ موسوی‌بایگی م؛ و ضیابی، ع. (1392). برآورد خسارت ناشی از آلاینده‌های جوی بر محصولات کشاورزی در شرایط مختلف هواشناسی. فصلنامۀ آب‌وخاک (علوم و صنایع کشاورزی)، 26(2)، 532- 523.
  6. عزتیان، و؛ و هاشمی‌نسب، س. (1392). انتشار آلاینده‌های جوی چالش زیست محیطی شهر اصفهان. مطالعات و پژوهش‌های شهری و منطقه‌ای، 4(16)، 160- 145.
  7. فرجی، ع؛ و رحیمی، ن. (1401). واکاوی پراکنش زمانی-مکانی آلاینده CO در دوران همه‌گیری COVID-19 (مطالعه موردی: استان خوزستان، اصفهان، تهران). جغرافیا و پایداری محیط (پژوهشنامۀ جغرافیایی)، 12(43)، 108-95.
  8. قربانی‌سالخورد، ر. (1389). اعتبارسنجی داده‌های سنجنده مودیس در رابطه با آلودگی جوی در مناطق شهری. پایان‌نامۀ کارشناسی‌ارشد گروه فتوگرامتری و سنجش از دور، دانشکدۀ ژئودزی و زئوماتیک،  دانشگاه خواجه‌نصیرالدین طوسی.
  9. Alimissis, A., Philippopoulos, K., Tzanis, C., & Deligiorgi, D. (2018). Spatial estimation of urban air pollution with the use of artificial neural network models. Atmospheric environment,191, 205-213.
  10. Almubaidin, M. A., binti Ismail, N. S., Latif, S. D., Ahmed, A. N., Dullah, H., El-Shafie, A., & Sonne, C. (2024). Machine learning predictions for carbon monoxide levels in urban environments. Results in Engineering, 22, 102114.
  11. Arshad, K., Hussain, N., Ashraf, M. H., & Saleem, M. Z. (2024). Air pollution and climate change as grand challenges to sustainability. Science of The Total Environment, 172370.
  12. Asikainen, A., Carrer, P., Kephalopoulos, S., Fernandes. Ede O., Wargocki, P., Hanninen, O. (2016). Reducing burden of disease from residential indoor air exposures in Europe (HEALTHVENT project) Environ Health,15 (Suppl 1): 35 - PMC – PubMed, 62-72.
  13. Bourdrel, T., Bind, M. A., Béjot, Y., Morel, O., & Argacha, J. F. (2017). Cardiovascular effects of air pollution. Archives of cardiovascular diseases, 110(11), 634-642.
  14. Burnham, K. P., & Anderson, D. R. (2004). Multimodel Inference Understanding AIC and BIC in Model Selection. Sociological Methods & Research, 33(2), 261-304.
  15. Hannah, L. (2014). Carbon Sinks and Sources in: L, Hannah. Climate change biology Second Edition, Elsevier: Academic Press, pp. 403-422.
  16. Kim, J. B., Prunicki, M., Haddad, F., Dant, C., Sampath, V., Patel, R., …, & Nadeau, K. C. (2020). Cumulative Lifetime Burden of Cardiovascular Disease From Early Exposure to Air Pollution. Journal of the American Heart Association, 9(6), e014944. https://doi.org/10.1161/JAHA.119.014944
  17. Neira, M., Erguler, K., Ahmady-Birgani, H., Al-Hmoud, N. D., Fears, R., Gogos, C., ... & Christophides, G. (2023). Climate change and human health in the Eastern Mediterranean and Middle East: Literature review, research priorities and policy suggestions. Environmental research, 216, 114537.
  18. Rosenzweig, C., Solecki, W., Hammer, S. A., & Mehrotra, S. (2010). Cities lead the way in climate–change action. Nature, 467(7318), 909-911.
  19. Valari, M., & Menut, L. (2008). Does an increase in air quality models’ resolution bring surface ozone concentrations closer to reality?. Journal of Atmospheric and Oceanic Technology, 25(11), 1955-1968.
  20. Yıldırım, E. (2023). The relationship between PM10 and SO2 exposure and Covid-19 infection rates in Turkey using nomenclature of territorial units for statistics level 1 regions. Heliyon, 9(11), e21795.
  21. Zhang, K., Thé, J., Xie, G., & Yu, H. (2020). Multi-step ahead forecasting of regional air quality using spatial-temporal deep neural networks: A case study of Huaihai Economic Zone. Journal of Cleaner Production, 277, 123231.
  22. Zheng, C., Zhang, H., Cai, X., Chen, L., Liu, M., Lin, H., & Wang, X. (2021). Characteristics of CO2 and atmospheric pollutant emissions from China’s cement industry: A life-cycle perspective. Journal of Cleaner Production, 282, 124533.

 

Send comment about this article
Enter Name.
Enter a valid email address.
Enter a vaid affiliation.
Enter comments (At leaset 10 words)
CAPTCHA Image
Enter Security Code Correctly.

Home

Submit Manuscript

Contact Us