Effects of aerosol emission changes on sea ice concentration and thickness in the Russian Arctic during the 2020 lockdown

The two polar regions, the Arctic and Antarctic, significantly influence the climate across the entire globe. These areas appear to have an impact on the sea level (Dasarathy et al. 2021), wildlife coupled with numerous food chains, traditional human livelihoods, tundra vegetation, and natural ecosystems with excess productivity (Aas et al. 2019). The sea levels are altered when the snow over the land melts and also by the process of desalination. Accurate sea level estimation is important for designing effective intake systems, optimizing energy efficiency, and ensuring the protection of desalination plants from coastal flooding (Panagopoulos 2022). It also helps in managing salinity levels and preserving the quality of freshwater sources. Additionally, sea-level estimation guides long-term planning and investment decisions for desalination infrastructure in coastal areas (Panagopoulos & Giannika 2022). While comparing the two poles, it is often found that the Arctic Circle is more vulnerable to global warming compared with the Antarctic (Jang et al. 2022). One of the primary reasons for this could be the presence of human settlement in the Arctic (Allen 2020). The presence of human activity in the region causes the emission of hazardous aerosols (Sakib 2023), and these aerosols either absorb or reflect the incoming solar radiation into the atmosphere (Carslaw 2022). This process can lead to global warming when there is more absorption than reflection of this radiation (Vihma 2014). Global warming has caused greater shrinking (Duan et al. 2022) and thinning (Kwok et al. 2011) of Arctic sea ice during the recent decade (Kay et al. 2011). Since the modern satellite era began in 1979, researchers have observed a decline of 9.1% of sea ice per decade (Shibata et al. 2013), which was just 7.8% per decade during the pre-1979 period (Stroeve et al. 2012). However, the decline is higher (12.6% per decade) in recent years (2009–2019) (Wunderling et al. 2020). Hence, it is understood that the region demands more attention and scientific study.

Further, in 2020 as well, the decline in sea ice is found to prevail. During the beginning of this year, the outbreak of COVID-19 occurred, which caused major lockdowns across the globe. The lockdown impacted all sectors of society, ranging from economics to the environment, either directly or indirectly (Muhammad et al. 2020; NASA Global Climate Change 2022). Over the Arctic, pollution levels have decreased, which has greatly improved the air quality while reducing the amount of soot and other particles settling on the sea ice. However, over the Arctic, a rise in temperature was witnessed during the period, which accelerated the melt and decelerated the evolution of sea ice. During the recent decade, the region is already found to have experienced higher rates of warming temperature compared with the global average, a phenomenon also referred to as Arctic amplification (Screen & Simmonds 2010). The Arctic region is observed to have few sources of anthropogenic emissions, and additionally, there exists a long-range transport of aerosols from mid-latitudes to the poles that makes the presence of these emissions more intense (Screen et al. 2012; Cohen et al. 2014). The transported aerosol is often referred to as ‘Arctic haze’. A decline in aerosols lowers the cloud drop, resulting in a greater presence of low and dimmer clouds (Ekman & Schmale 2022), further leading to an increase in precipitation (Bintanja & Selten 2014), and thereby changing the lifetime of clouds (Albrecht 1989). Furthermore, reducing anthropogenic emissions would reverse the planet-cooling effect (Yadav et al. 2020), affecting the cloud properties as these particles have the ability to scatter back the incoming solar radiation (Im et al. 2021). Further, it is understood that during the 1980s and 1990s, changes in the extent of cloud cover caused cooling during summers and reduced warming in winters, through the radiative effect (Liu et al. 2012). Uncertainty about cloud properties has always prevailed over the North Pole (Kato et al. 2018). Accuracy about the behavior of polar clouds always helps in understanding the radiation happening at the top of the atmosphere, which further governs the polar climate system (Li et al. 2022).

According to Yang et al. (2020) and Diamond & Wood (2020), preliminary findings from the early lockdowns in China and Russia suggest that the decrease in aerosols during this time may have led to minor changes in cloud microphysics. The major decline of these aerosols was due to the most polluted industries (Aerosol Pollution 2022), which caused a short-term effect on temperature. Furthermore, as noted by Gettelman et al. (2020), some types of air pollution can have a cooling effect on the planet by reflecting sunlight back into space or by reducing the amount of incoming solar radiation that reaches the Earth's surface (Kok et al. 2023). Therefore, reducing pollution could have the opposite effect and lead to the warming of the planet (Gagné et al. 2015). Likewise, the impact of aerosol emissions on global temperatures is particularly significant in areas with high levels of pollution, resulting in warming of up to 0.37 °C across significant areas of the United States and Russia. Therefore, there exists a gap which needs to be addressed over the region.

The study of variability in sea ice due to induced emissions gives a unique opportunity for climate change research as it allows scientists to examine the impact of reduced human activities on the Arctic environment. By analyzing the fluctuations in sea ice during this period, researchers can gain valuable insights into the relationship between emissions and Arctic sea ice decline, aiding in the refinement of climate models and predictions. Additionally, understanding these variabilities helps evaluate feedback mechanisms, such as the albedo effect, where melting sea ice leads to increased heat absorption, further accelerating ice loss and contributing to climate change (Stroeve & Notz 2018). This knowledge can guide policy decisions and mitigation strategies by highlighting the benefits of long-term emission reduction and sustainable practices. Furthermore, the socioeconomic implications of sea ice changes in the Arctic are significant, affecting indigenous communities and biodiversity (Serreze & Barry 2011). Overall, studying the sea ice variability during the 2020 lockdown provides crucial insights into the intricate interactions between human activities, emissions, climate change, and Arctic ecosystems, informing global efforts to mitigate climate change and safeguard vulnerable regions. Therefore, the goal of this paper is to carry out a preliminary spatiotemporal analysis of the sea ice condition during the COVID-19 pandemic in the Russian Arctic region. The effect of emissive aerosol particles on sea ice conditions in the region is closely studied for the years 2019 and 2020. The Russian Arctic is considered to be the region of interest as there exists human intervention with the presence of sea ice.

The year 2019 is considered so as to understand the situation of the sea before the lockdown. Temperatures rise during the pandemic, even though man-made emissions are expected to be low. The region is carefully selected in order to comprehend the land-related effects that cause a reduction in the reflection of incoming solar radiation back into space, ultimately altering the temperature of the air above it. This study highlights the influence of various kinds of emissions from numerous sources, like power plants, motor vehicles, industrial facilities, etc. Additionally, outgoing radiation is also observed as these aerosols are seen to be in direct contact with them. The impact of these on clouds and the potential of it to reflect radiation back into the atmosphere are understood. However, there are other greenhouse gases, such as carbon dioxide, that have a reverse effect: they trap warm air near the land surface and cause a temperature hike.

This paper consists of three variants of datasets: atmospheric variables, atmospheric aerosols, and cryospheric variables.

For the current study, aerosols like ammonia (NH₃), black carbon (BC), carbon dioxide (CO₂), carbon monoxide (CO), sulfur dioxide (SO₂), organic carbon (OC), nitrous oxide (N₂O), and non-methane volatile organic compounds (NMVOCs) are considered and are extracted from Community Earth System Model version 2 (CESM2) (Danabasoglu et al. 2020). The model is coupled ocean–sea-ice–atmosphere–land configuration at 1° horizontal resolution. Later, two sets of simulations: one with historical aerosol emissions from 1979 to 2020, and one with reduced aerosol emissions during the 2020 lockdown based on satellite observations, are performed. Daily data are available on the websites https://doi.org/10.5281/zenodo.3957826 and https://doi.org/10.5281/zenodo.3952959. Daily averages are a running seven-day mean that eliminates any weekday effects.

As the considered region of study is closer to the North Pole (Arctic), the impact of atmospheric conditions on cryospheric parameters is crucial. For understanding the influence of the aforementioned atmospheric parameters on sea ice conditions, sea ice concentration (hereafter referred to as SIC) and sea ice thickness (hereafter referred to as SIT) are considered. SIC values are from the CEDA Archive: AMSR-E and AMSR-2 at spatial resolution of 0.25° × 0.25° (https://catalogue.ceda.ac.uk/uuid/1dcb79727b313a281233afc3c3e10519) (Hadley Centre for Climate Prediction & Research 2007). SIT datasets are derived from CryoSat-2 and Envisat with a spatial resolution of 0.25° × 0.25°. SIT error is estimated to be between 0.04 and 0.06 m (Table 1).

The available data have already been simulated for COVID-19 perturbations. The data consisted of temperature nudging because it was collected on the ground. However, Forster et al. (2020) have tried removing and controlling the role of temperature on these parameters. For the current study as well, the daily averages for the considered domain are calculated, and for the daily difference between them, the present-day emission value is subtracted from the past day. This way, the decline or rise in value with respect to each day could be understood. Additionally, the Sea-Ice–Aerosol–Cloud Feedback (SIACF) Index in S. M. Nazmuz Sakib's Hypothesis can be applied to the aerosol emission changes. The SIACF Index serves as a quantitative measure to assess the influence of aerosol emission variations on sea ice conditions (Sakib 2023).

The Arctic cryospheric variables SIT and SIC are extracted for the monthly timeframe from the aforementioned sources for the years 2019 and 2020. The region is then constrained and cropped to the chosen region of interest. As per standard practice, SIT and SIC are replaced with zero (‘0’) in the grid wherever the values are missing or ‘NaN’ (undefined), as the absence of sea ice corresponds to zero thickness and concentration. Later in the case of SIT, the months March and April are considered, and for SIC, the months March, April, May, and June are considered. Monthly averages are considered for both parameters. Later, the differences are analyzed to understand the extent of change in sea ice conditions during the years 2019 and 2020. The spatial differences between SIT and SIC are illustrated in the paper.

The monthly variation in temperature over the Russian Arctic region is clearly based on seasonal classification. Winters (December, January, and February) have the lowest temperature, followed by spring (March, April, and May), and the highest is during summer (June, July, and August). Again, by autumn (September, October, and November), the temperature change is lower when compared with that during the previous stage, summer. Although the temperature gradually rises in the spring, it can still be extremely frigid. The hottest season is summer, which features higher temperatures and longer daylight hours. Autumn comes after summer, and while the temperature drops, the transition may be less pronounced than in other areas. The Russian Arctic has a wide variety of temperatures, with winter being the coldest and summer being the hottest.

The extent and the amount of aerosols emitted over the region is analyzed daily in the upcoming section. The validation of the extent of the difference in the net solar radiation between the two timelines is provided in Figure 4 based on the temporal frame. During February 2019, the average solar radiation is 2.09 W m⁻² and that during February 2020 is 2.14 W m⁻², making the difference ΔS = 0.04 W m⁻². The lowest solar radiation is observed during this month, ultimately causing the month to experience winter. Further, in March 2019 and 2020, the value of net solar radiation is seen to be twice that of February. The hike in incoming solar radiation also marked the onset of spring. The amount of solar radiation received during the years 2019 and 2020 is represented in Table 3 along with the differences. Table 3 shows that by the beginning of summer, in June, ΔS = 0.15 W m⁻². Later in July, we see lower net solar radiation than the previous month, ΔS = 0.06 W m⁻².

From the observations, it is evident that temperature and absorption of solar radiation inside the Earth's atmosphere have gone up significantly during the lockdown. One of the main reasons for such a trend is the presence of greenhouse gases. Greenhouse gases and water vapor trap heat and prevent it from escaping into space, leading to a rise in temperature inside the atmosphere. With the closure of industries, there was a decrease in the use of energy derived from fossil fuels, leading to a reduction in greenhouse gas emissions during the COVID-19 lockdown. Therefore, the nature and presence of aerosols need to be examined in the upcoming sections.

The range of Arctic aerosol mass lies between 0.09 and 0.76 μg m⁻³, and over the Russian Arctic, it lies between 0.34 and 1.01 μg m⁻³. This is primarily due to the presence of human activities such as industrial processes, transportation, and energy production in the region. The Russian Arctic is home to several industrial centers and oil and gas fields, which can release significant amounts of aerosol and other pollutants into the atmosphere. In addition to human activities, the geography and weather patterns of the region may also contribute to higher aerosol concentrations over the Russian Arctic. The region is surrounded by mountains (from the topographic plot in Figure 1), which can trap pollutants in the air, and it experiences frequent weather inversions that can prevent the dispersion of pollutants.

Nitrous oxide (N₂O) also behaves in a similar fashion as SO₂ (Figure 8(c)). N₂O alternates between negative and positive values between 3 February and 8 March 2020. During the initial phase (3–15 February 2020), it remains positive. Later, from 16 to 21 February, it turns positive. From 22 to 28 February, the daily differences become negative. From 29 February to 8 March, it again becomes positive. Furthermore, it turns negative once more during 9–13 March. Later, from 14 to 17 March, it is once again positive. The daily differences continue to be negative after 18 March 2020. The lowest daily difference is observed on 4 April 2020, with a value of −0.11 kt/day. When this aerosol is exposed to sunlight and oxygen in the stratosphere, it gets converted to nitrogen oxide. Later, this has the potential to deplete the ozone layer nearly 300 times more than CO₂. However, it has a shorter life span than CO₂. Therefore, it is believed that even slight fluctuations in N₂O can greatly contribute to global warming.

Further, CO₂ and CO are also found to maintain a similar trend, which is well evident from Figure 8(d) and 8(e). There is a gradual decline in the month of March, followed by a steady situation post-April. The notable feature about these elements is that the daily difference of CO₂ and CO lie within the tenth and unit place, respectively, whereas for NH₃ and BC, the magnitude is quite small, occupying the hundredth and thousandth place values (position), respectively. CO₂ absorbs energies with wavelengths ranging from 2 × 10³ to 15 × 10³ nm. This is also the range that overlaps with that of IR (infrared) radiation. The decline in this molecule further hampers the energy radiation budget. CO, like BC, follows a similar trend and remains positive until 18 March. Following 18 March, a gradual downward trend is observed, eventually reaching −8.35 kt/day in April 2020. However, it is alleged that CO does not have a direct effect on atmospheric temperature, like CO₂ and methane. The NMVOCs (Figure 8(f)) behave somewhat similarly to OC. NMVOCs remain positive until 18 March 2020 (Figure 8(f)). Later, from 19 March onward, the aerosol shows a negative difference. This declining trend prevails thereafter. The lowest daily difference is observed on 4 April 2020, with a value of −3.14 kt/day.

As the role of Arctic haze and its associated aerosols in altering the atmospheric conditions over the Russian Arctic region is now thoroughly understood, it is vital to assess the influence of these parameters on the sea ice conditions prevailing over the region. Significant atmospheric fluctuation occurred in 2020, and therefore, the differences in cryospheric parameters due to the difference in these variables are discussed in this section.

SIC in the Russian Arctic has been declining over the past 20 years due to the effects of climate change. The Russian Arctic SIC has been declining at a rate of approximately 2.7% per decade since the late 1970s (Rodrigues 2008), with some of the most significant declines occurring over the past ten years (2010–2020). Detailed monthly variation of SIC over the region is illustrated in Figure 10(a). The range over the considered region is found to vary between 2% and 14%, indicating that the region experiences low sea ice conditions. Additionally, the annual average of the Russian region shows a declining trend with values of 7.55% and 7.82% during 2016 (the year which is also recorded to have the lowest sea ice condition over the Arctic region) and 2012, respectively. Overall from Figure 10(a), it is difficult to contemplate if any change has been caused to the sea ice environment during the pandemic leading to its acceleration or deceleration. Figure 10(a) shows the annual area average SIC of 7.72% and 7.64% during 2019 and 2020, respectively, with no much significant difference between the two spans.

One of the key aspects of the locations under consideration (the Russian Arctic) is that not only is the area closer to the North Pole (Arctic), but it also serves as a massive sea ice production reservoir. The area surrounding the Barents Sea, Kara Sea, and Laptev Sea is frequently seen to be sparse during the summer and rich in thick sea ice during the winter. The spatial plot in Figure 10 illustrates the variation in SIC for the months of March, April, May, and June between 2019 and 2020. This trend in the drop of SIC during 2020 is well expected given the variations in atmospheric conditions along with the decrease in industrial aerosol emissions. It has been noted that the SIC difference in the area surrounding Svalbard, Franz Josef Land, the Kara Sea, and the Laptev Sea ranges from 0 to 25%. The Barents Sea, on the other hand, is observed to have a negative SIC, with values ranging from −25% to 0%. Positive values are high in the region south of the Barents Sea. Similarly, the region right next to Russia has a positive SIC. Further in the month of April (Figure 10(c)), a positive difference in SIC during 2019 and 2020 is highly visible to the north of the Laptev Sea. The region around and north of the Kara Sea is observed to show slightly negative values of SIC difference. Additionally, the SIC percentage in the area east of Russia fluctuates between positive and negative values, showing that SIC is highly variable. However, the same location was noted to have strong positive SIC values in March (Figure 10(b)). Positive values are leaning more toward the Arctic region in this month than the region around the land (Russia). By May (Figure 10(d)), the sea ice starts to respond to the meteorological shift that occurred way back in March, when the country was put under rigorous lockdown. During May, the majority of the Arctic seas, the Barents Sea, Kara Sea and Laptev Sea, showed positive SIC. The Kara Sea has the highest fluctuation of any sea, surpassing the Laptev and then the Barents. Additionally, there is a significant positive variability in the SIC percentage in the area surrounding Svalbard, Franz Josef Land, and places that are closer to the Russian coasts. However, during June (Figure 10(e)), the highest variability over the seas of the Arctic is observed. It is evident that the Laptev Sea, in particular, exhibits both positive and negative SIC. June is seen as having more positive SIC values in the north than May. A similar trend has been observed east and north of Kara. It is evident from Figure 10 that a rise in temperature has a negative impact on the melting of sea ice. When comparing the years before the pandemic (2019) and the pandemic itself (2020), it is projected that the influence of the pandemic lockdown on sea ice conditions cannot be judged with the current data resolution.

In this paper, we have understood the effects of COVID-19 emissions changes on the sea ice conditions over the Russian Arctic region in 2020. It is found that the decrease in anthropogenic aerosol emission increases the air temperature, indicating that few aerosols play the role of scattering radiation. It was quantitatively understood that there was an increase in temperature during the pandemic, while comparing the year 2020 with 2019. The highest temperature difference between the two periods was observed in the months of February (ΔT = 3.23 K) and November (ΔT = 3.55 K), with a difference ΔT > 3 K. Additionally, the solar flux trapped at the top of the atmosphere was significantly higher in 2020 than in 2019. The majority of the seas (Barents Sea, Kara Sea, and Laptev Sea) in the region have radiation levels greater than 13 W m⁻². The highest difference in radiation was observed in the month of May, with the value of ΔS = 0.28 W m⁻². By the onset of summer, in June 2019, ΔS = 0.15 W m⁻². It is numerically calculated and understood that during May 2020, the flux increased by 37.15% compared with May 2019. Further, the causative factor of such an incline in temperature over the region was understood by analyzing the emissions of aerosols like NH₃, BC, CO₂, CO, SO₂, OC, N₂O, and NMVOCs. The Arctic haze aerosols’ lifecycle (surface and mass-wise) reveals that they are at their maximum during March, when the sea ice is at its maximum. The daily trend of aerosols experiences a downward trend after 18–19 March 2020. That was the majority time when the region was put under strict lockdown. The highest negative difference was observed between 3 April and 5 April 2020, with a daily difference value of −0.04, −0.02, −1.51, −0.02, −0.11, and −3.14 kt/day for NH₃, BC, SO₂, OC, N₂O, and NMVOCs, respectively. The impact of these ultimately altered the growth and decay of sea ice over the region which was understood using the SIC parameters. The positive values of SIC were discovered to be leaning more toward the Arctic region than the land region (Russia). From the observations, it is evident that the lockdown was short-lived and the process of sea ice formation occurs over a long period of time. Therefore, associating the two does not yield a positive impact with the current data resolution used. Overall, the COVID-19 pandemic has had both positive and negative indirect impacts on the environment, with the negative effects likely to outweigh the positive ones. While the reduction of aerosol emissions and greenhouse gas concentrations during the pandemic may seem like a quick fix, it is not a sustainable long-term solution for addressing environmental challenges. Moreover, the pandemic has also brought about a range of additional environmental issues that could persist for a long time and may be even more difficult to address if not given adequate attention by countries. The results can be used to further understand S. M. Nazmuz Sakib's Hypothesis, which provides an aerosol sea ice feedback which can be expressed through a comprehensive formula, encompassing the key factors involved. This formula accounts for both positive and negative feedback loops, shaping the interactions within the system.

The findings of this study have important implications for theory, practice, and policy. However, they also come with limitations and complexities. The inherent uncertainties and variability of Russian Arctic sea ice make it challenging to accurately predict its future conditions. Feedback mechanisms triggered by sea ice changes introduce additional uncertainties, as they can amplify the effects of climate change. These findings help in policy implications, particularly for climate change mitigation and adaptation strategies. Here, in this case, it is difficult to strictly establish a relationship between the anthropogenic aerosols and cryospheric parameters as the lockdown imposed was short-lived.

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

The authors declare there is no conflict.