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

Climate change, driven by increasing greenhouse gas (GHG) emissions, demands attention (Hatami et al. 2024). Projected sea level rise under various scenarios underscores the urgency of mitigation efforts. Connecting CO₂ emissions to global warming, strategic actions can mitigate climate change impacts on critical water resources like groundwater, surface water, rainfall patterns, and floods (Safaeian et al. 2023; Mousavi et al. 2022a; Moshir Panahi et al. 2020; Fu et al. 2019) and led to global concerns in the international community (Bonneuil et al. 2021; Borhani et al. 2022); hence, environmentalists have been concerned about GHG emissions (Darvishi et al. 2024; Hatami et al. 2024; Khordehbin et al. 2020). In light of the Industrial Revolution's commencement, the surging demand for energy, primarily stemming from the combustion of fossil fuels, has precipitated a marked escalation in GHG emissions (Jenn et al. 2019; Fu et al. 2020; Mousavi et al. 2020). Atmospheric carbon dioxide (XCO₂) is a significant GHG arising from a combination of human activities and natural phenomena (Mehmood et al. 2020; Borhani et al. 2024). Thus, the average concentration of XCO₂ from 280 ppm in 1750 reached 417 ppm in 2021 (Tocco et al. 2021). The persistent emission of greenhouse gases into the atmosphere presents substantial challenges to the ecosystems of our planet, as well as to weather patterns and the broader sustainability of our environment (Cheraghi & Borhani 2016; Borhani et al. 2023a, 2023b). The Earth can be viewed as a dynamic system with various sources contributing to the input and output of carbon. Input sources release carbon dioxide (CO₂) into the atmosphere, while output sources are reservoirs that store carbon (Rahman et al. 2017). Carbon input sources encompass a range of factors, including the consumption of fossil fuels, soil processes, plant respiration, and alterations in land use. Conversely, carbon output sources involve phenomena such as plant photosynthesis and the absorption of carbon by marine ecosystems (Mac Dowell et al. 2017; Ghayoumi et al. 2022, 2023). The equilibrium between carbon input and output from natural sources was historically maintained.

Nevertheless, in recent decades, the equilibrium has been disrupted due to the escalation of anthropogenic activities and the resulting increase in CO₂ emissions. This disruption has precipitated climate change and global warming as consequential outcomes (Change 2007; Peiro et al. 2022; Sun et al. 2022). Comprehending the intricacies of the carbon cycle and the carbon budget is paramount when investigating the origins and reservoirs of XCO₂. Consequently, quantifying and categorizing sources contributing to emissions and absorption affecting XCO₂ concentration serve as valuable tools for environmental assessment and carbon management strategies.

Atmospheric carbon dioxide can be quantified using diverse techniques, including ground-based stations, tall towers, atmospheric measurements conducted via balloons, and data collected from ships and aircraft (O'Dell et al. 2018; Chiba et al. 2019; Shah et al. 2019; Bluestein et al. 2022; Pellegrini et al. 2022). Although these techniques produce accurate measurements, their major weakness is spatial restriction, as there is no ground station in many parts of the world, like Iran and the Middle East (Mousavi et al. 2023). Remote sensing science solves this issue by continuously tracking GHG levels across the planet and taking measurements everywhere (Pan et al. 2021). The XCO₂ is measured by a variety of satellites, including the ‘National Aeronautics and Space Administration (NASA)’ ‘Orbiting Carbon Observatory-2 (OCO-2)’ and OCO-3 satellites, the ‘Greenhouse Gas Observing Satellite (GOSAT),’ and GOSAT-2 satellite, and the ‘Scanning Imaging Absorption Spectrometer for Atmospheric CHartography (SCIAMACHY)’ satellite from the ‘European Space Agency’ (Butz et al. 2011; Kavitha & Nair 2016; Wunch et al. 2017; Shim et al. 2019; Suto et al. 2021).

The OCO-2 satellite, launched in 2014 and has been continually measuring to date, is one of the most accurate CO₂ monitoring satellites. According to validation research, this satellite has an uncertainty of less than 1% (Reuter et al. 2019; Kiel et al. 2021). Satellites for detecting GHG, such as the OCO-2, exclusively monitor the CO₂ concentration in the atmosphere. The CO₂ molecules are counted from the Earth's surface to the top of the atmosphere using these measurements (Liang et al. 2017; He et al. 2020). These observations only offer the XCO₂ data.

Several studies have assessed the GHG emissions, trend variations, and their modeling in Iran, examining the issue from various perspectives. Notable among these are the works of Mousavi et al. (2017) who assessed the relationship between XCO₂ and meteorological parameters; Falahatkar et al. (2017) who investigated the spatial distribution of XCO₂ in Iran in different seasons; Mousavi & Falahatkar (2020) who assessed the relationship between CH₄ concentration and environmental variables, Mousavi et al. (2022b) who analyzed the spatiotemporal patterns of XCO₂, Siabi et al. (2019) who assessed the spatial distribution of XCO₂ in growing seasons by using eight environmental variables, Golkar & Shirvani (2020) who investigated the spatial and temporal distribution of XCO₂, Mousavi et al. (2018) who determined the relationship between XCO₂ and CH₄ concentration and environmental variables, and Golkar & Mousavi (2022) who studied the role of anthropogenic CO₂ emission on XCO₂ in the middle east.

So far, no research has been conducted to explore the influence of net CO₂ absorption and emission on XCO₂ levels in Iran. Therefore, the central question in the present research is to gain insights into how global fluctuations in XCO₂ levels impact the XCO₂ in Iran. Comparing CO₂ surface flux data obtained from the Copernicus Atmosphere Monitoring Service (CAMS), which reveals net CO₂ absorption and emission, with atmospheric CO₂ concentration data from OCO-2 allows us to examine the role of global fluctuations in XCO₂ levels and their impact on XCO₂ concentrations. This study aimed to examine and compare the quantity of net CO₂ emitting and absorption of Iran with its atmospheric concentration to determine the potential consequences of global CO₂ changes on its concentration in Iran. Reporting CO₂ levels aids policymakers and environmental planners in emission reduction and implementing mitigation strategies, which is crucial for managing water resources amidst climate change impacts. In this study, first, by using monthly XCO₂ data from the OCO-2 satellite, the monthly and yearly amplitude of XCO₂ from 2015 to 2020 were examined. Then, to examine the exact amount of CO₂ emission and absorption, the CAMS data were used for this period.

• 1.

  Atmospheric carbon dioxide concentration CO₂ dataset of OCO-2 satellite

NASA's first satellite mission to observe atmospheric column CO₂ concentration, the Orbiting Carbon Observatory-2 (OCO-2), was launched in 2014 (Frankenberg et al. 2014; Wunch et al. 2017). The OCO-2 satellite flies in a sun-synchronous, near-polar orbit that completes its rotation in 98.8 min each time, and the ascending node crosses the equator at 13:36 mean local time (GMT) (Crisp et al. 2004; National Aeronautics and Space Administration 2018, January 23). Passing in the early afternoon maximizes the available reflectance signals and minimizes measurements of daily CO₂ skewness associated with photosynthesis (Parkinson et al. 2006). The flight height of this satellite is 705 km, and its primary purpose is to measure CO₂ gas concentration on a continental and regional scale with a spatial resolution of approximately 3 km² (Eldering et al. 2017). The OCO-2 satellite carries a sensor that includes three network spectrometers with high magnification that measure the intensity of three bands in the spectral regions of the near-infrared and short-wave infrared in ranges of 0.76 μm (A band for O₂), 1.6 μm (weak CO₂ band), and 2 μm (strong CO₂ band), each specific to one of the three spectrometers (Yang et al. 2020). This satellite can track alterations on the surface by simultaneously measuring gases in the exact location over time (Frankenberg et al. 2014). Twenty-four spectra are recorded by each spectrometer per second (Osterman et al. 2016). Although about one million datasets are collected daily, only about 10% of these data will be suitable for calculating the amount of carbon CO₂ due to the limitation of cloud cover (Osterman et al. 2016; Richardson et al. 2017). This satellite's simultaneous collection of O₂ and CO₂ values with high spatial magnification reduces the random error and minimizes the influence of cloudiness, aerosols, and other disturbing sources on recording the CO₂ values (Parkinson et al. 2006). The OCO-2 satellite retrieves the XCO₂ in three observation modes: nadir, glint spot, and target.

In contrast to the nadir and glint modes regarded as scientific, the target mode is intended to test the OCO-2 XCO₂ products' accuracy by focusing on validation sites. This satellite performs its measurements in the SWIR regions, and its measurement accuracy is 0.3% (Crisp et al. 2004; Miller et al. 2005; Pillai et al. 2010; Cortesi et al. 2014). Daily CO₂ gas data from level 2 of the OCO-2 satellite from 2015 to 2020 were used in this investigation. It should be emphasized that level 2 data, verified using ground-based sources, only provides 10% of all the data that are reliable for public use.

• 2.

  Carbon dioxide surface flux data

In 2020, the CAMS, managed by the European Centre for Medium-Range Weather Forecasts (ECMWF), provided a series of global surface flux data products for CO₂, CH₄, and nitrous oxide (N₂O) at 3-h intervals at a spatial resolution of 1.875° × 3.75°. Mousavi et al. (2024) validated these data with ground stations and stated that the CO₂ flux data have high reliability with less than 1 ppm error. For this investigation, according to the purpose of the research, the latest version (v20r3) was used from January 2015 to January 2020, whose data include (a) natural CO₂ emission and absorption, (b) anthropogenic CO₂ emission, and (c) total CO₂ emission caused by natural and human activities.

In this study, the researchers categorized the seasons based on the respective months of the year: winter (JFM), spring (AMJ), summer (JAS), and autumn (OND) as outlined (Luo et al. 2013).

• 1.

  Monthly and annual changes in atmospheric CO₂ concentration:

In the case of monthly and seasonal amplitude, XCO₂ had intra-annual fluctuations. It demonstrated a notable cyclic pattern, reaching its peak during late winter in March and extending into early spring in April and May (Figure 4). These fluctuations were such that the XCO₂ increased from January and reached its highest value in spring and May. The atmospheric concentration of this gas decreased from May onward and reached its minimum value in summer and September. Another increase from September onward followed it, and this was repeated during different years. The details of these changes are shown in Figure 5. Overall, these findings align with prior research studies conducted by Mousavi et al. (2022b), Falahatkar et al. (2017), Sheng et al. (2023), Gupta et al. (2019), and Chhabra & Gohel (2019).

In addition, we observed a notable surge in XCO₂ levels during the transition from summer to autumn, with an approximately 4 ppm increase. However, as we transitioned from autumn to winter, the growth rate of XCO₂ declined, suggesting a marginal increase or a stable XCO₂ level. Monthly and seasonal variations in XCO₂ are influenced by factors such as CO₂ emissions, terrestrial ecosystems, temperature, rainfall, and other contributors (Cao et al. 2019; Lv et al. 2020).

• 2.

  Annual and monthly changes in CO₂ surface flux in Iran

Based on the results presented in Figure 8, the net CO₂ emissions and absorption resulting from natural processes were in the negative range throughout the months of March, April, and May. This indicates that natural activities' absorption of atmospheric carbon dioxide outweighs its emission in these specific months. During the spring season, spanning from March through May, the peak in vegetation cover results in a notable surge in photosynthesis relative to respiration. Consequently, this season induces an increased uptake of atmospheric carbon dioxide by the prevailing vegetation (Yuan et al. 2018). The seasonal cycle of atmospheric CO₂ is notably enhanced in northern mid-high latitudes, driven by the extended growing season resulting in increased photosynthesis and CO₂ drawdown (Forkel et al. 2016). This amount was positive in other months of the year, indicating that CO₂ emissions through natural activities (respiration) exceed CO₂ absorption (photosynthesis). In cold seasons, reduced photosynthesis in plants, combined with continuous respiration by living organisms, results in more CO₂ being released into the atmosphere than absorbed, contributing to the cyclic variation in atmospheric CO₂ levels (Nogia et al. 2016; Gayathri et al. 2021). This phenomenon is affected by global temperatures, cellular respiration, and temperature responses to photosynthesis and respiration in plants (Aspinwall et al. 2016; Crous et al. 2022).

In this research, it is observed that in Iran, the monthly variations in CO₂ surface flux depict discrepancies in comparison to XCO₂ values. The difference in the dataset demonstrates the substantial impact of extra-regional and global factors on the regulation of atmospheric CO₂ concentrations within Iran, thereby bearing significant implications for comprehending and mitigating environmental challenges in this realm. Substantive further examination and rigorous analysis are imperative to determine the root causes of these fluctuations. Carbon dioxide is a well-mixed gas renowned for its swift and uniform dispersion throughout the atmosphere (Roberts et al. 2017). Its existence is not limited to localized sources but rather arises from a multifaceted spectrum of global emissions, demonstrating its pervasive ubiquity and consequential impact on the Earth's climate (Crippa et al. 2022).

Weir et al. (2021) and Zeng et al. (2021) investigated global atmospheric carbon dioxide concentrations, revealing that during the COVID-19 pandemic, XCO₂ levels experienced a notable reduction in all regions worldwide, even in areas with minimal emissions. This finding indicates that greenhouse gases emitted from any location have a far-reaching impact on people worldwide. Furthermore, the increase in atmospheric carbon dioxide concentration is a consequence of its widespread global influence, leading to a rise in its concentration throughout all regions of the world (Morgan 2000; Tyfield & Urry 2009).

Natural emissions in Iran began decreasing in January. By March, April, and May, they had reached negative levels, revealing not only a lack of emissions but also a phase of absorption during these months. Subsequently, initially in May, nature resumed CO₂ emissions, reaching their peak in July and August. After that, there was a gradual reduction in the volume of natural CO₂ emissions, with this recurring cycle happening annually. Figures 9 and 10 display a comprehensive compilation of CO₂ surface flux emissions in Iran, including both natural and anthropogenic sources. In July, when anthropogenic and natural emissions reached their zenith, a noticeable pattern emerged, demonstrating the prevalence of natural emissions over anthropogenic counterparts during this specific seasonal period. The combined sum of natural and anthropogenic emissions initiated a decline in January, eventually reaching its lowest level during the spring, particularly in May. Due to rising temperatures, resulting in reduced vegetation and heightened soil and plant respiration in the aftermath of this period, a significant increase in emissions occurred. This recurring cycle persisted over multiple years (LeMay & Kurz 2017).

During the study period, Iran experienced an increasing trend in the annual change of XCO₂. Meanwhile, the annual changes in the CO₂ surface flux caused by natural and anthropogenic activities not only do not show growth but also show a decrease in this period. These consequences serve as compelling evidence of the global impact of CO₂ on atmospheric concentrations of this gas within Iran. As previously mentioned, the monthly patterns of the CO₂ surface flux in Iran exhibit notable distinctions from XCO₂, demonstrating the global impacts of XCO₂ on the concentration of this gas in Iran. Mousavi et al. (2017) and Falahatkar et al. (2017) investigated the changes in XCO₂ without considering the amount of surface flux in Iran; however, in the current study, besides considering XCO₂, the CO₂ surface flux in Iran was examined, which includes anthropogenic emissions, natural emissions, and absorption, as well as the total of natural and anthropogenic emissions.

• 3.

  Spatial distribution of CO₂ surface flux and XCO₂ in Iran

The spatial distribution map of atmospheric carbon dioxide reveals notable variations in concentration levels across different seasons in Iran. The highest concentrations are observed during the spring season, predominantly in the central and southern regions of the country. Conversely, the lowest atmospheric carbon dioxide levels are evident during the summer, particularly in the northern regions of Iran (Figure 11). These findings highlight seasonal disparities in carbon dioxide distribution, shedding light on regional dynamics and contributing factors.

Meanwhile, the analysis of total carbon emissions and net absorption depicts the highest values during the summer season, particularly concentrated in Iran's northern and western regions. Conversely, the lowest values are observed in the spring season, primarily in the northern and northwestern areas of the country (Figure 12). This observation underscores seasonal emissions and absorption pattern variations, providing valuable insights into the regional dynamics of carbon balance within Iran. As can be seen, the spatial distribution of atmospheric carbon dioxide and the net amount of emission and absorption of Iran are different, so these spatial differences between the seasonal XCO₂ and f CO₂ surface fluxes in Iran demonstrate the effect of CO₂ global change on the atmospheric concentration of CO₂ in the study area. The seasonal changes of XCO₂ in Iran are in line with global changes (Tans & Keeling 2023).

The findings unequivocally demonstrate that the global impact of CO₂ fluctuations significantly influenced the annual and monthly variations in Iran's XCO₂. Golkar & Shirvani (2020) depicted that the principal factor contributing to the rise in XCO₂ in Iran was identified as the increasing emissions from fossil fuel sources. In contrast, the results of this research revealed that certain factors extending beyond the confines of local changes in Iran exerted influence on the variations in XCO₂. These findings indicate that the effects of global CO₂ fluctuations predominantly contributed to these variations. The research studies of Mousavi et al. (2018), Siabi et al. (2019) also exclusively relied on atmospheric GHG concentrations, even though it was suggested that surface flux data be applied in future modeling investigations.

In studies by Zeng et al. (2020) and Dacre et al. (2021), which investigated the impact of carbon dioxide emission reduction during the COVID-19 lockdown, it was observed that, during this period, when carbon dioxide emissions decreased, atmospheric carbon dioxide levels also diminished, even in regions with no emissions. This underscores the global influence of atmospheric carbon dioxide fluctuations on local environments, confirming our results regarding the role of global fluctuations of XCO₂ on local XCO₂.

This research utilized atmospheric CO₂ concentration and CO₂ surface flux data obtained from OCO-2 and CAMS, respectively, to investigate the influence of global CO₂ changes on annual and monthly local variations in XCO₂ levels across Iran.

• In Iran, the XCO₂ levels displayed a consistent upward trend over six years, surging by 12.66 ppm, from 399.77 ppm in 2015 to 412.43 ppm in 2020. This equates to an average annual increase of approximately 2.11 ppm. This steady ascent closely parallels the ongoing global surge in atmospheric CO₂ concentrations.

• The total surface flux of CO₂ emissions, comprising anthropogenic and natural sources, peaked in July, while its nadir was observed in May. Meanwhile, data from the OCO-2 satellite revealed the highest atmospheric CO₂ concentration in May and the lowest in September.

• The observed disparities in monthly and annual variations between XCO₂ and surface flux in Iran underscore the significant influence of external and global factors on the country's atmospheric CO₂ levels. This underscores the need for policymakers and environmental planners to consider local emissions and global CO₂ fluctuations when developing strategies to manage water resources amidst climate change impacts.

• The findings underscore the urgent requirement for a coordinated global initiative to enact science-based policies that reduce escalating CO₂ emissions, essential for addressing global warming and minimizing its adverse impacts on water resources. It is imperative to curb greenhouse gas emissions worldwide to alter the current course of climate change, which profoundly affects the hydrologic cycle, including precipitation patterns, storm intensities, drought frequency, and flood timing.

• Quantitative analysis of CO₂ concentrations and surface fluxes offers valuable insights into the carbon cycle, aiding in predicting and mitigating climate change's impact on water resources. Such data can inform the development of adaptation strategies, including water conservation, flood control infrastructure, and drought preparedness plans.

• Qualitatively, the research highlights the interconnectedness of global climate change, greenhouse gas emissions, and local water resource management, emphasizing the importance of international cooperation, knowledge sharing, and collaborative efforts to address these interconnected challenges effectively.

This research highlights the significant influence of global CO₂ fluctuations on local XCO₂, underscoring the necessity for international collaboration in addressing escalating emissions and their detrimental effects, such as climate changeapos;s effect on water resources. To enhance analytical accuracy and conduct further investigation, it is advisable to incorporate the latest atmospheric CO₂ data sources, such as GOSAT-2 and OCO-3. Additionally, the utilization of GRACE satellite data is proposed to examine changes in water resources, facilitating a more accurate understanding of the connection between the water and carbon cycles.

This work is based upon research funded by Iran National Science Foundation (INSF) under project No. 4014326. The authors gratefully acknowledge the National Aeronautics and Space Administration (NASA), the OCO-2 team for making the XCO₂ dataset available, and the Copernicus Atmosphere Monitoring Service (CAMS) for GHG fluxes data provision.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.