New Developments in Climate Change, Air Pollution, Pollen Allergy, and Interaction with SARS-CoV-2

In recent years, the environmental impacts of climate change have become increasingly evident. Extreme meteorological events are influenced by climate change, which also alter the magnitude and pattern of precipitations and winds. Climate change can have a particularly negative impact on respiratory health, which can lead to the emergence of asthma and allergic respiratory illnesses. Pollen is one of the main components of the atmospheric bioaerosol and is able to induce allergic symptoms in certain subjects. Climate change affects the onset, length, and severity of the pollen season, with effects on pollen allergy. Higher levels of carbon dioxide (CO2) can lead to enhanced photosynthesis and a higher pollen production in plants. Pollen grains can also interact with air pollutants and be affected by thunderstorms and other extreme events, exacerbating the insurgence of respiratory diseases such as allergic rhinitis and asthma. The consequences of climate change might also favor the spreading of pandemics, such as the COVID-19 one.

Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan.

We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020-2022 were calculated relative to those for the preceding 9-year period (2011-2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, - 36 ± 7%, and - 12 ± 8%, respectively, (- 10 ± 9% for JFM overall) relative to 2011-2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, - 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, - 3 ± 10%, and - 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai. Supplementary Information: The online version contains supplementary material available at 10.1186/s40645-023-00542-6.

Dramatic decline of observed atmospheric CO2 and CH4 during the COVID-19 lockdown over the Yangtze River Delta of China

The temporal variation of greenhouse gas concentrations in China during the COVID-19 lockdown in China is analyzed in this work using high resolution measurements of near surface △CO2, △CH4 and △CO concentrations above the background conditions at Lin'an station (LAN), a regional background station in the Yangtze River Delta region. During the pre-lockdown observational period (IOP-1), both △CO2 and △CH4 exhibited a significant increasing trend relative to the 2011-2019 climatological mean. The reduction of △CO2, △CH4 and △CO during the lockdown observational period (IOP-2) (which also coincided with the Chinese New Year Holiday) reached up to 15.0 ppm, 14.2 ppb and 146.8 ppb, respectively, and a reduction of △CO2/△CO probably due to a dramatic reduction from industrial emissions. △CO2, △CH4 and △CO were observed to keep declining during the post-lockdown easing phase (IOP-3), which is the synthetic result of lower than normal CO2 emissions from rural regions around LAN coupled with strong uptake of the terrestrial ecosystem. Interestingly, the trend reversed to gradual increase for all species during the later easing phase (IOP-4), with △CO2/△CO constantly increasing from IOP-2 to IOP-3 and finally IOP-4, consistent with recovery in industrial emissions associated with the staged resumption of economic activity. On average, △CO2 declined sharply throughout the days during IOP-2 but increased gradually throughout the days during IOP-4. The findings showcase the significant role of emission reduction in accounting for the dramatic changes in measured atmospheric △CO2 and △CH4 associated with the COVID-19 lockdown and recovery.

NOTES AND CORRESPONDENCE Did Atmospheric CO2 and CH4 Observation at Yonagunijima Detect Fossil-Fuel CO2 Reduction due to COVID-19 Lockdown?

Synoptic-scale variabilities of atmospheric CO2 and CH4 observed at Yonagunijima (Yonaguni Island, YON, 24.47 degrees N, 123.01 degrees E) during winter (from January to March) in 1998 - 2020 were examined. The monthly mean variability ratios (Delta CO2 /Delta CH4) based on correlation slopes within 24 h time windows showed a clear increasing trend, which is mainly attributed to the unprecedented increase in the fossil fuel-derived CO2 (FFCO2) emissions from China. A similar increasing trend of the Delta CO2 /Delta CH4 ratio had been reported for the observation at Hateruma Island (HAT, 24.06 degrees N, 123.81 degrees E), located at approximately 100 km east of YON. Nevertheless, the absolute values for YON were 34 % larger than those for HAT. Additionally, the monthly average in February 2020 for YON showed no marked change, whereas that for HAT showed an abrupt considerable decrease associated with the FFCO2 emission decrease in China presumably caused by the COVID-19 lockdown. Investigating the diurnal variations, we found that the local influences were larger at YON, especially during daytime, than at HAT. Using nighttime data (20-6 LST) and a longer time window (84 h), we succeeded in reducing the local influences and the resulting monthly mean Delta CO2 /Delta CH4 ratio showed considerable similarity to that observed at HAT including the abrupt decrease in February 2020. These results convinced us that the Delta CO2 /Delta CH4 ratio could be successfully used to investigate the relative emission strength in the upwind region.

Revision of 22-year Records of Atmospheric Baseline CO2 in South Korea: Application of the WMO X2019 CO2 Scale and a New Baseline Selection Method (NIMS Filter)

The Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has monitored atmospheric CO2 at Anmyeondo (AMY) World Meteorological Organization (WMO) Global Atmosphere Watch Programme (GAW) regional station since 1999, and expanded its observations at Jeju Gosan Suwolbong station (JGS) in the South and at Ulleungdo-Dokdo stations in the East (ULD and DOK) since 2012. Due to a recent WMO CO2 scale update and a new filter (NIMS) to select baseline levels at each station, the 22 years of CO2 data are recalculated. After correction for the new CO2 scale, we confirmed that those corrected records are reasonable within the compatibility goal (+/- 0.1 ppm of CO2) between KMA/NIMS and National Oceanic and Atmosphereic Administration (NOAA) flask-air measurements with the new scale. With the new NIMS filter, CO2 baseline levels are now more representative of the large-scale background compared to previous values, which contained large CO2 enhancements. Atmospheric CO2 observed in South Korea is 4 to 8 ppm greater than the global average while the amplitude of seasonal variation is similar (10 similar to 13 ppm) to the amplitude averaged over a comparable latitude zone (30 degrees N-60 degrees N). Variations in CO2 growth rate are also similar, increasing and decreasing similar to global values, as it reflects the net balance between terrestrial respiration and photosynthesis. In 2020, atmospheric CO2 continued increasing despite the COVID-19 pandemic. Even though fossil emission was reduced (around -7% globally), we still emitted large amounts of anthropogenic CO2. Overall, since CO2 has large natural variations and its source was derived from not only fossil fuel but also biomass burning, the small fossil emission reduction could not affect the atmospheric level directly.

Global to local impacts on atmospheric CO2from the COVID-19 lockdown, biosphere and weather variabilities

The worldwide lockdown in response to the COVID-19 pandemic in year 2020 led to an economic slowdown and a large reduction in fossil fuel CO2 emissions (Le Quéré 2020 Nat. Clim. Change 10 647-53, Liu 2020 Nat. Commun. 11);however, it is unclear how much it would slow the increasing trend of atmospheric CO2 concentration, the main driver of climate change, and whether this impact can be observed considering the large biosphere and weather variabilities. We used a state-of-the-art atmospheric transport model to simulate CO2, and the model was driven by a new daily fossil fuel emissions dataset and hourly biospheric fluxes from a carbon cycle model forced with observed climate variability. Our results show a 0.21 ppm decrease in the atmospheric column CO2 anomaly in the Northern Hemisphere latitude band 0-45 N in March 2020, and an average of 0.14 ppm for the period of February-April 2020, which is the largest decrease in the last 10 years. A similar decrease was observed by the carbon observing satellite GOSAT (Yokota et al 2009 Sola 5 160-3). Using model sensitivity experiments, we further found that the COVID and weather variability are the major contributors to this CO2 drawdown, and the biosphere showed a small positive anomaly. Measurements at marine boundary layer stations, such as Hawaii, exhibit 1-2 ppm anomalies, mostly due to weather and the biosphere. At the city scale, the on-road CO2 enhancement measured in Beijing shows a reduction by 20-30 ppm, which is consistent with the drastically reduced traffic during the COVID lockdown. A stepwise drop of 20 ppm during the city-wide lockdown was observed in the city of Chengdu. The ability of our current carbon monitoring systems in detecting the small and short-lasting COVID signals at different policy relevant scales (country and city) against the background of fossil fuel CO2 accumulated over the last two centuries is encouraging. The COVID-19 pandemic is an unintended experiment. Its impact suggests that to keep atmospheric CO2 at a climate-safe level will require sustained effort of similar magnitude and improved accuracy, as well as expanded spatiotemporal coverage of our monitoring systems. © 2021 The Author(s). Published by IOP Publishing Ltd.

Time-frequency co-movement between COVID-19, crude oil prices, and atmospheric CO2 emissions: Fresh global insights from partial and multiple coherence approach.

This paper endeavors to analyze and provide fresh global insights from the asymmetric nexus between the recent outbreak of COVID-19, crude oil prices, and atmospheric CO2 emissions. The analysis employs a unique Morlet's wavelet method. More precisely, this paper implements comprehensive wavelet coherence analysis tools, including continuous wavelet coherence, partial wavelet coherence, and multiple wavelet coherence to the daily dataset spanning from December 31, 2019 to May 31, 2020. From the frequency perspective, this paper finds significant wavelet coherence and vigorous lead and lag connections. This analysis ascertains significant movement in variables over frequency and time domain. These results demonstrate strong but varying connotations between studied variables. The results also indicate that COVID-19 impacts crude oil prices and the most contributor to the reduction in CO2 emissions during the pandemic period. This study offers practical and policy implications and endorsements for individuals, environmental experts, and investors.