Quantifying COVID-19 enforced global changes in atmospheric pollutants using cloud computing based remote sensing

COVID-19 response in Africa: impacts and lessons for environmental management and climate change adaptation

The COVID-19 pandemic adds pressure on Africa; the most vulnerable continent to climate change impacts, threatening the realization of most Sustainable Development Goals (SDGs). The continent is witnessing an increase in intensity and frequency of extreme weather events, and environmental change. The COVID-19 was managed relatively well across in the continent, providing lessons and impetus for environmental management and addressing climate change. This work examines the possible impact of the COVID-19 pandemic on the environment and climate change, analyses its management and draws lessons from it for climate change response in Africa. The data, findings and lessons are drawn from peer reviewed articles and credible grey literature on COVID-19 in Africa. The COVID-19 pandemic spread quickly, causing loss of lives and stagnation of the global economy, overshadowing the current climate crisis. The pandemic was managed through swift response by the top political leadership, research and innovations across Africa providing possible solutions to COVID-19 challenges, and redirection of funds to manage the pandemic. The well-coordinated COVID-19 containment strategy under the African Centers for Disease Control and Prevention increased sharing of resources including data was a success in limiting the spread of the virus. These strategies, among others, proved effective in limiting the spread and impact of COVID-19. The findings provide lessons that stakeholders and policy-makers can leverage in the management of the environment and address climate change. These approaches require solid commitment and practical-oriented leadership.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-02956-0.

Evaluation of NOx emissions before, during, and after the COVID-19 lockdowns in China: A comparison of meteorological normalization methods

Meteorological normalization refers to the removal of meteorological effects on air pollutant concentrations for evaluating emission changes. There currently exist various meteorological normalization methods, yielding inconsistent results. This study aims to identify the state-of-the-art method of meteorological normalization for characterizing the spatiotemporal variation of NOx emissions caused by the COVID-19 pandemic in China. We obtained the hourly data of NO₂ concentrations and meteorological conditions for 337 cities in China from January 1, 2019, to December 31, 2020. Three random-forest based meteorological normalization methods were compared, including (1) the method that only resamples meteorological variables, (2) the method that resamples meteorological and temporal variables, and (3) the method that does not need resampling, denoted as Resample-M, Resample-M&T, and Resample-None, respectively. The comparison results show that Resample-M&T considerably underestimated the emission reduction of NOx during the lockdowns, Resample-None generates widely fluctuating estimates that blur the emission recovery trend during work resumption, and Resample-M clearly delineates the emission changes over the entire period. Based on the Resample-M results, the maximum emission reduction occurred during January to February 2020, for most cities, with an average decrease of 19.1 ± 9.4% compared to 2019. During April of 2020 when work resumption initiated to the end of 2020, the emissions rapidly bounced back for most cities, with an average increase of 12.6 ± 15.8% relative to those during the strict lockdowns. Consequently, we recommend using Resample-M for meteorological normalization, and the normalized NO₂ concentration dynamics for each city provide important implications for future emission reduction.

Spatiotemporal analysis of COVID-19, air pollution, climate, and meteorological conditions in a metropolitan region of Iran

The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO₂, and O₃ tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO₂), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO₂. Suitable policy implications are recommended to be performed for improving people's healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.

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.

Understanding the spatiotemporal variability and trends of surface ozone over India

With rising anthropogenic activities, surface ozone levels have increased across different parts of the world including India. Previous studies have shown that surface ozone shows distinct characteristics across India but these results are based on isolated locations and any comprehensive and spatiotemporally consistent study about surface ozone variability lacks thus far. Keeping these facts in mind, we utilize ground-based observations and reanalysis datasets to investigate spatiotemporal variations of surface ozone and its linkages with meteorology and precursors over Indian region. A validation exercise shows that the Copernicus Atmosphere Monitoring Service Reanalysis (CAMSRA) reasonably compares against the ground-based observations showing better correlations (> 0.7) over southern regions and relatively lesser (> 0.5) correlations over northern and eastern regions. We have further quantified this agreement in terms of range, mean absolute error (MAE), and root mean square error (RMSE). A time series analysis shows that the CAMSRA captures seasonal variations irrespective of location. Spatial distribution of surface ozone shows higher (lower) concentrations of about 40-60 ppb (15-20 ppb) during pre-monsoon (monsoon) months over northern and western parts and peninsular India. A prominent increase during May is noted over the northern region, especially over the Indo-Gangetic Plains (IGP). These seasonal variations are linked to solar radiation (SR), temperature, low-level circulation, and boundary layer height (BLH). CAMSRA-based surface ozone shows increasing trends across all four regions (north, east, west, and south India) and also India as a whole (0.069 ppb year^-1, p = 0.001) with highest trends over the eastern region. Furthermore, principal component analysis (PCA) reveals that the first (second) mode shows a high percentage variance explained, ranging between 30 and 50% (10-20%). The corresponding PC-1 time series exhibits a notable increase in the surface ozone over south and central India, which corroborates the trend obtained through the area averaged time series. The second mode (PC-2) indicates prominent interannual variability over the IGP (southern India) in the pre-monsoon (post-monsoon). During the monsoon season, an interesting dipole pattern is noticeable, which closely resembles the active and break spell patterns of the Indian summer monsoon. Further, we quantify the weightage of precursors and meteorological parameters on surface ozone concentrations. The analysis suggests that PC1 of surface ozone is strongly influenced by CO and NOx (the precursors) while meteorology seems to dominate the PC2 during the pre-monsoon season. Overall, the results indicate that changes in the precursors or meteorological conditions have significant influences on the surface ozone concentrations across India.