The Climate Response to Emissions Reductions Due to COVID-19: Initial Results From CovidMIP

The worldwide COVID-19 lockdown impacts on global secondary inorganic aerosols and radiative budget

Global lockdown measures to prevent the spread of the coronavirus disease 2019 (COVID-19) led to air pollutant emission reductions. While the COVID-19 lockdown impacts on both trace gas and total particulate pollutants have been widely investigated, secondary aerosol formation from trace gases remains unclear. To that end, we quantify the COVID-19 lockdown impacts on NOx and SO2 emissions and sulfate-nitrate-ammonium aerosols using multiconstituent satellite data assimilation and model simulations. We find that anthropogenic emissions over major polluted regions were reduced by 19 to 25% for NOx and 14 to 20% for SO2 during April 2020. These emission reductions led to 8 to 21% decreases in sulfate and nitrate aerosols over highly polluted areas, corresponding to >34% of the observed aerosol optical depth declines and a global aerosol radiative forcing of +0.14 watts per square meter relative to business-as-usual scenario. These results point to the critical importance of secondary aerosol pollutants in quantifying climate impacts of future mitigation measures.

Urban air quality in Xinjiang and snow chemistry of Urumqi Glacier No. 1 during COVID-19's restrictions

The unprecedented COVID-19 outbreak impacted the world in many aspects. Air pollutants were largely reduced in cities worldwide in 2020. Using samples from two snow pits dug separately in 2019 and 2020 in Urumqi Glacier No. 1 (UG1) in the Xinjiang Uygur Autonomous Region (Xinjiang), China, we measured water-stable isotopes, soluble ions, and black and organic carbon (BC and OC). Both carbon types show no significant variations in the snow-pit profiles dated from 2018 through 2020. The deposition of anthropogenically induced soluble ions (K⁺, Cl^-, SO₄^2-, and NO₃^-) in the snow decreased to 20-40% of their respective concentrations between 2019 and 2020; however, they increased 2- to fourfold from 2018 to 2019. We studied the daily concentrations of SO₂ (2019-2020), NO₂ (2015-2020), CO (2019-2020), and PM_2.5 (2019-2020) measured in the sixteen major cities and towns across Xinjiang. The variabilities in these air pollutants were supposed to illustrate the air quality in the urban area and represent the change in the source area. The NO₂ decreased in response to mobility restrictions imposed by local governments, while SO₂, CO, and PM_2.5 did not consistently correspond. This difference indicates that the restriction measures primarily affected traffic. The increases in chemical species in the snow from 2018 to 2019 and the subsequent decreases from 2019 to 2020 were consistent with the variations in SO₂ and NO₂ measured in urban air and estimated by MERRA-2 model. Therefore, the pandemic could possibly have an impact on snow chemistry of the Tien-Shan glaciers via reduced traffic and industrial intensity; more evidence would be obtained from ice cores, tree rings, and other archives in the future.

Anthropogenic aerosol and cryosphere changes drive Earth's strong but transient clear-sky hemispheric albedo asymmetry

A striking feature of the Earth system is that the Northern and Southern Hemispheres reflect identical amounts of sunlight. This hemispheric albedo symmetry comprises two asymmetries: The Northern Hemisphere is more reflective in clear skies, whereas the Southern Hemisphere is cloudier. Here we show that the hemispheric reflection contrast from differences in continental coverage is offset by greater reflection from the Antarctic than the Arctic, allowing the net clear-sky asymmetry to be dominated by aerosol. Climate model simulations suggest that historical anthropogenic aerosol emissions drove a large increase in the clear-sky asymmetry that would reverse in future low-emission scenarios. High-emission scenarios also show decreasing asymmetry, instead driven by declines in Northern Hemisphere ice and snow cover. Strong clear-sky hemispheric albedo asymmetry is therefore a transient feature of Earth's climate. If all-sky symmetry is maintained, compensating cloud changes would have uncertain but important implications for Earth's energy balance and hydrological cycle.

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck the western United States in 2020, damaging properties and threating human lives. Meanwhile, the COVID-19 pandemic spread across the globe, which disrupted human activities. Here, we investigate the effects of the emissions reductions during the pandemic on fire weather in 2020 over the western United States by using an earth system model together with observations. We show that reductions in aerosols dominate the increases in wildfire risks, whereas greenhouse gas decrease counteracts this influence. The aerosol emissions reductions increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains one-third of the observed increase in wildfire risks during August-November over the western United States in 2020. This study suggests that COVID-19-related emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

Spatial Resolved Surface Ozone with Urban and Rural Differentiation during 1990-2019: A Space-Time Bayesian Neural Network Downscaler

Long-term exposure to ambient ozone (O₃) can lead to a series of chronic diseases and associated premature deaths, and thus population-level environmental health studies hanker after the high-resolution surface O₃ concentration database. In response to this demand, we innovatively construct a space-time Bayesian neural network parametric regressor to fuse TOAR historical observations, CMIP6 multimodel simulation ensemble, population distributions, land cover properties, and emission inventories altogether and downscale to 10 km × 10 km spatial resolution with high methodological reliability (R² = 0.89-0.97, RMSE = 1.97-3.42 ppbV), fair prediction accuracy (R² = 0.69-0.77, RMSE = 5.63-7.97 ppbV), and commendable spatiotemporal extrapolation capabilities (R² = 0.62-0.76, RMSE = 5.38-11.7 ppbV). Based on our predictions in 8-h maximum daily average metric, the rural-site surface O₃ are 15.1±7.4 ppbV higher than urban globally averaged across 30 historical years during 1990-2019, with developing countries being of the most evident differences. The globe-wide urban surface O₃ are climbing by 1.9±2.3 ppbV per decade, except for the decreasing trends in eastern United States. On the other hand, the global rural surface O₃ tend to be relatively stable, except for the rising tendencies in China and India. Using CMIP6 model simulations directly without urban-rural differentiation will lead to underestimations of population O₃ exposure by 2.0±0.8 ppbV averaged over each historical year. Our original Bayesian neural network framework contributes to the deep-learning-driven environmental studies methodologically by providing a brand-new feasible way to realize data fusion and downscaling, which maintains high interpretability by conforming to the principles of spatial statistics without compromising the prediction accuracy. Moreover, the 30-year highly spatial resolved monthly surface O₃ database with multiple metrics fills in the literature gap for long-term surface O₃ exposure tracing.

Effective Radiative Forcings Due To Anthropogenic Emission Changes Under Covid-19 and Post-Pandemic Recovery Scenarios

With the continuation of the Coronavirus Disease 2019 (Covid-19) pandemic, the impacts of this catastrophe on anthropogenic emissions are no longer limited to its early stage. This study quantitatively estimates effective radiative forcings (ERFs) due to anthropogenic well-mixed greenhouse gases (WMGHGs) and aerosols for the period 2020-2050 under the three latest Covid-19 economic-recovery scenarios using an aerosol-climate model. The results indicate that reductions in both WMGHG and aerosol emissions under the Covid-19 green recoveries lead to increases ranging from 0 to 0.3 W m^-2 in global annual mean anthropogenic ERF over the period 2020-2050 relative to the Shared Socioeconomic Pathway 2-4.5 scenario (the baseline case). These positive ERFs are mainly attributed to the rapid and dramatic decreases in atmospheric aerosol content that increase net shortwave radiative flux at the top of atmosphere via weakening the direct aerosol effect and low cloud cover. At the regional scale, reductions in aerosols contribute to positive ERFs throughout the Northern Hemisphere, while the decreased WMGHGs dominate negative ERFs over the areas away from aerosol pollution, such as the Southern Hemisphere oceans. This drives a strong interhemispheric contrast of ERFs. In contrast, the increased anthropogenic emissions under the fossil-fueled recovery scenario lead to an increase of 0.3 W m^-2 in global annual mean ERF in 2050 compared with the baseline case, primarily due to the contribution of WMGHG ERFs. The regional ERF changes are highly dependent on local cloud radiative effects.

A New Methodology for Reference Evapotranspiration Prediction and Uncertainty Analysis under Climate Change Conditions Based on Machine Learning, Multi Criteria Decision Making and Monte Carlo Methods

In the present study, a new methodology for reference evapotranspiration (ETo) prediction and uncertainty analysis under climate change and COVID-19 post-pandemic recovery scenarios for the period 2021–2050 at nine stations in the two basins of Lake Urmia and Sefidrood is presented. For this purpose, firstly ETo data were estimated using meteorological data and the FAO Penman–Monteith (FAO-56 PM) method. Then, ETo modeling by six machine learning techniques including multiple linear regression (MLR), multiple non-linear regression (MNLR), multivariate adaptive regression splines (MARS), model tree M5 (M5), random forest (RF) and least-squares boost (LSBoost) was carried out. The technique for order of preference by similarity to ideal solution (TOPSIS) method was used under seven scenarios to rank models with evaluation and time criteria in the next step. After proving the acceptable performance of the LSBoost model, the downscaling of temperature (T) and precipitation (P) by the delta change factor (CF) method under three models ACCESS-ESM1-5, CanESM5 and MRI-ESM2-0 (scenarios SSP245-cov-fossil (SCF), SSP245-cov-modgreen (SCM) and SSP245-cov-strgreen (SCS)) was performed. The results showed that the monthly changes in the average T increases at all stations for all scenarios. Also, the average monthly change ratio of P increases in most stations and scenarios. In the next step, ETo forecasting under climate change for periods (2021–2050) was performed using the best model. Prediction results showed that ETo increases in all scenarios and stations in a pessimistic and optimistic state. In addition, the Monte Carlo method (MCM) showed that the lowest uncertainty is related to the Mianeh station in the MRI-ESM2-0 model and SCS scenario.

Abrupt emissions reductions during COVID-19 contributed to record summer rainfall in China

Record rainfall and severe flooding struck eastern China in the summer of 2020. The extreme summer rainfall occurred during the COVID-19 pandemic, which started in China in early 2020 and spread rapidly across the globe. By disrupting human activities, substantial reductions in anthropogenic emissions of greenhouse gases and aerosols might have affected regional precipitation in many ways. Here, we investigate such connections and show that the abrupt emissions reductions during the pandemic strengthened the summer atmospheric convection over eastern China, resulting in a positive sea level pressure anomaly over northwestern Pacific Ocean. The latter enhanced moisture convergence to eastern China and further intensified rainfall in that region. Modeling experiments show that the reduction in aerosols had a stronger impact on precipitation than the decrease of greenhouse gases did. We conclude that through abrupt emissions reductions, the COVID-19 pandemic contributed importantly to the 2020 extreme summer rainfall in eastern China.

Erratic Asian summer monsoon 2020: COVID-19 lockdown initiatives possible cause for these episodes?

The summer (June through September) monsoon 2020 has been very erratic with episodes of heavy and devastating rains, landslides and catastrophic winds over South Asia (India, Pakistan, Nepal, Bangladesh), East Asia (China, Korea, and Japan), and Southeast Asia (Singapore, Thailand, Vietnam, Laos, Cambodia, Philippines, Indonesia). The withdrawal of the summer monsoon over India was delayed by 2 weeks. The monsoon season over East Asia has been the longest. China recorded a Dam burst in the twentieth century. Furthermore, the Korean Peninsula has experienced back-to-back severe tropical cyclones. Could the lockdown activities initiate to control the COVID-19 spread a possible cause for these major episodes? The strict enforcement of the lockdown regulations has led to a considerable reduction of air pollutants-dust and aerosols throughout the world. A recent study based on satellites and merged products has documented a statistically significant mean reduction of about 20, 8, and 50% in nitrogen dioxide, Aerosol Optical Depth (AOD) and PM_2.5 concentrations, respectively over the megacities across the globe. Our analysis reveals a considerable reduction of about 20% in AOD over South as well as over East Asia, more-over East Asia than over South Asia. The reduced aerosols have impacted the strength of the incoming solar radiation as evidenced by enhanced warming, more-over the land than the oceans. The differential warming over the land and the ocean has resulted in the amplification of the meridional ocean-land thermal contrast and strengthening of the monsoon flow. These intense features have supported the surplus transport of moisture from the oceans towards the main lands. Some similarity between the anomalous rainfall pattern and the anomalous AOD pattern is discernable. In particular, the enhancement of rainfall, the reduction in AOD and the surface temperature warming match very well over two regions one over West-Central India and the other over the Yangzte River Valley. Results further reveal that the heavy rains over the Yangzte River Valley could be associated with the preceding reduced aerosols, while the heavy rains over West-Central India could be associated with reduced aerosols and also due to the surface temperature warming.

COVID-19 lockdown closures of emissions sources in India: Lessons for air quality and climate policy

Reduced anthropogenic activities during the COVID-19 pandemic caused significant reductions in ambient fine particulate matter (PM_2.5), SO₂ and NO_x concentrations across India. However, tropospheric O₃ concentrations spiked over many urban regions. Moreover, reductions in SO₂ and NO_x (atmospheric cooling agents) emissions unmask heating exerted by warming forcers. Basing governmental guidelines, we model daily emissions reductions in CO₂ and short-lived climate forcers (SLCFs) during different lockdown periods using bottom-up regional emission inventory. The transport sector, with maximum level of closure, followed by power plants and industry reduced nearly -50% to -75% emissions of CO₂, primary PM_2.5, SO₂ and NO_x, while warming SLCFs (black carbon, CH₄, CO and non-methane VOCs) showed insignificant reduction from continuing activity in residential and agricultural sectors. Consequently, the analysis indicates that reduction in the emission ratio of NO_x to NMVOC coincided spatially with observed increases in O₃, consistent with reduced uptake of O₃ from night-time NO_x reactions. Also, similar reductions, occurring for longer timescales (say, a year), can potentially increase the annual warming rate over India from the positive regional temperature response, estimated using climate metric. Further, by linking ongoing policies to sectoral reductions during lockdown, this study shows that the relative pacing of implementation among policies is crucial to avoid counter-productive results. A key policy recommendation is introduction and improving efficacy of programs targeting reduction of NMVOC and warming SLCF emissions (shifts away from biomass cooking technologies, household electrification and curbing open burning of crop residues), must precede the strengthening of policies targeting NO_x and SO₂ dominated sectors.

Opportunistic experiments to constrain aerosol effective radiative forcing

Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments" (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery

The pandemic in 2020 caused an abrupt change in the emission of anthropogenic aerosols and their precursors. We estimate the associated change in the aerosol radiative forcing at the top of the atmosphere and the surface. To that end, we perform new simulations with the CMIP6 global climate model EC-Earth3. The simulations use the here newly created data for the anthropogenic aerosol optical properties and an associated effect on clouds from the simple plumes parameterization (MACv2-SP), based on revised SO₂ and NH₃ emission scenarios. Our results highlight the small impact of the pandemic on the global aerosol radiative forcing in 2020 compared to the CMIP6 scenario SSP2-4.5 of the order of +0.04 Wm^-2, which is small compared to the natural year-to-year variability in the radiation budget. Natural variability also limits the ability to detect a meaningful regional difference in the anthropogenic aerosol radiative effects. We identify the best chances to find a significant change in radiation at the surface during cloud-free conditions for regions that were strongly polluted in the past years. The post-pandemic recovery scenarios indicate a spread in the aerosol forcing of -0.68 to -0.38 Wm^-2 for 2050 relative to the pre-industrial, which translates to a difference of +0.05 to -0.25 Wm^-2 compared to the 2050 baseline from SSP2-4.5. This spread falls within the present-day uncertainty in aerosol radiative forcing and the CMIP6 spread in aerosol forcing at the end of the 21st century. We release the new MACv2-SP data for studies on the climate response to the pandemic and the recovery scenarios. Our 2050 forcing estimates suggest that sustained aerosol emission reductions during the post-pandemic recovery cause a stronger climate response than in 2020, i.e., there is a delayed influence of the pandemic on climate.

On the Detection of COVID-Driven Changes in Atmospheric Carbon Dioxide

We assess the detectability of COVID-like emissions reductions in global atmospheric CO2 concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO2 sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon-concentration feedbacks obscure the detectability of short-term emission reductions in atmospheric CO2. COVID-driven changes in the simulated, column-averaged dry air mole fractions of CO2 are eclipsed by large internal variability. Carbon-concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions-driven signal in the atmosphere carbon reservoir and further confound signal detection.

Aerosol Loading and Radiation Budget Perturbations in Densely Populated and Highly Polluted Indo-Gangetic Plain by COVID-19: Influences on Cloud Properties and Air Temperature

Aerosols emitted in densely populated and industrialized Indo-Gangetic Plain, one of the most polluted regions in the world, modulate regional climate, monsoon, and Himalayan glacier retreat. Thus, this region is important for understanding aerosol perturbations and their resulting impacts on atmospheric changes during COVID-19 lockdown period, a natural experimental condition created by the pandemic. By analyzing 5 years (2016-2020) data of aerosols and performing a radiative transfer calculation, we found that columnar and near-surface aerosol loadings decreased, leading to reductions in radiative cooling at the surface and top of the atmosphere and atmospheric warming during lockdown period. Further, satellite data analyses showed increases in cloud optical thickness and cloud-particle effective radius and decrease in lower tropospheric air temperature during lockdown period. These results indicate critical influences of COVID-19 lockdown on regional climate and water cycle over Indo-Gangetic Plain, emphasizing need for further studies from modeling perspectives.

Lightning Behaviour during the COVID-19 Pandemic

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson's correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March - July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.

Lightning Behaviour during the COVID-19 Pandemic

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson's correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March - July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.

Lightning Behaviour during the COVID-19 Pandemic

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson's correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March - July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.

East Asian climate response to COVID-19 lockdown measures in China

The COVID-19 pandemic caused disruptions of public life and imposed lockdown measures in 2020 resulted in considerable reductions of anthropogenic aerosol emissions. It still remains unclear how the associated short-term changes in atmospheric chemistry influenced weather and climate on regional scales. To understand the underlying physical mechanisms, we conduct ensemble aerosol perturbation experiments with the Community Earth System Model, version 2. In the simulations reduced anthropogenic aerosol emissions in February generate anomalous surface warming and warm-moist air advection which promotes low-level cloud formation over China. Although the simulated response is weak, it is detectable in some areas, in qualitative agreement with the observations. The negative dynamical cloud feedback offsets the effect from reduced cloud condensation nuclei. Additional perturbation experiments with strongly amplified air pollution over China reveal a nonlinear sensitivity of regional atmospheric conditions to chemical/radiative perturbations. COVID-19-related changes in anthropogenic aerosol emissions provide an excellent testbed to elucidate the interaction between air pollution and climate.