Assessing the impact of global carbon dioxide changes on atmospheric fluctuations in Iran through satellite data analysis

Journal of Water and Climate Change, Journal Year: 2024, Volume and Issue: 15(6), P. 2774 - 2791

Published: April 3, 2024

ABSTRACT Atmospheric Carbon Dioxide (CO2), a significant greenhouse gas, drives climate change, influencing temperature, rainfall, and the hydrologic cycle. This alters precipitation patterns, intensifies storms, changes drought frequency timing of floods, impacting ecosystems, agriculture, water resources, societies globally. Understanding how global CO2 fluctuations impact regional atmospheric levels can inform mitigation strategies Facilitate resources management. The study investigates affect concentrations (XCO2) in Iran from 2015 to 2020, aiming against change. XCO2 data OCO-2 satellite surface flux Copernicus Atmosphere Monitoring Service (CAMS) were analyzed. Over 6 years, increased steadily by 12.66 ppm, mirroring rises. However, Iran's decreased, with slight increases anthropogenic emissions but decreased natural total fluxes. Monthly patterns exhibited variations, reaching its zenith spring dipping lowest point during summer, while peaked summer months. results reveal discrepancy between trends. While barely 2015–2020, fluxes decreased. over this period, indicating dominant rather than local factors on XCO2. Curbing worldwide gas output is imperative disrupt current trajectory Reporting plans, reducing combat warming minimize impacts

Language: Английский

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Unveiling the drivers of atmospheric methane variability in Iran: A 20-year exploration using spatiotemporal modeling and machine learning

Environmental Challenges, Journal Year: 2024, Volume and Issue: 15, P. 100946 - 100946

Published: April 1, 2024

Understanding the factors controlling spatial and temporal variability of atmospheric methane concentration (XCH4) is crucial for mitigating its impacts implementing emission reduction strategies. This study comprehensively investigates XCH4 driving (environmental, meteorological, anthropogenic activity) across Iran over 20 years, from 2003 to 2022. It combines multi-source satellite observations, advanced spatiotemporal modeling techniques, correlation analysis, machine learning algorithms. The analysis showed notable variation, with high levels in central, southern, eastern lower northwest north. Moreover, distinct seasonal cycles emerged, maximum occurring during summer (August-September) minimum spring (April-May). Correlation variable importance assessment were developed elucidate key drivers governing dynamics. revealed that vegetation cover, precipitation, soil moisture negatively correlated XCH4, while temperature indices a positive correlation, exhibiting highest time dispersion quantity among studied variables. Permutation Importance technique, used Random Forest classifier, learning-based approach considers role all variables together, land surface temperature, wind speed, moisture, cover are dominant controls, their ranked respectively. Surprisingly, emissions played relatively minor shaping distributions at regional scale. These findings highlight significant influence meteorological ecosystem processes on modulation, revealing intricate Earth system feedbacks inform targeted mitigation strategies predictive models curbing greenhouse gas climate change impacts.

Language: Английский

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Spatiotemporal Analysis of Atmospheric Methane Concentrations and Key Influencing Factors Using Machine Learning in the Middle East (2010–2021)

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 101406 - 101406

Published: Nov. 1, 2024

Language: Английский

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Detection of internal dust storm centers and their transport and dispersion modelling in southwestern Iran

Acta Geophysica, Journal Year: 2025, Volume and Issue: unknown

Published: April 9, 2025

Language: Английский

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A Comprehensive Assessing of Renewable Energy Sources Ranking by Fuzzy DANP and Fuzzy MULTIMOORA (Case Study Isfahan Province, IRAN)

International Journal of Environmental Research, Journal Year: 2025, Volume and Issue: 19(4)

Published: May 26, 2025

Language: Английский

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Machine learning models application for spatiotemporal patterns of particulate matter prediction and forecasting over Morocco in north of Africa

Atmospheric Pollution Research, Journal Year: 2024, Volume and Issue: 15(9), P. 102239 - 102239

Published: Sept. 1, 2024

Language: Английский

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The role of environmental social governance on achieving sustainable development goals in Gulf Cooperation Council countries

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Language: Английский

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Promoting environmental sustainability and climate change resilience at healthcare facilities: a pilot study in Iran

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: July 25, 2024

Language: Английский

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