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

The pandemic effect on GHG emission variation at the sub-national level and translation into policy opportunities

Greenhouse gas (GHG) emissions inventories are commonly compiled at country level to monitor national progress towards nationally or internationally agreed targets. While they can support national climate change mitigation strategies, accounting for the intra-national heterogeneity of a country can draw different conclusions directly linked to the socio-economic and environmental sub-national context. This means that more refined and accurate policies and mitigation strategies can be designed when supported by GHG inventories at sub-national scale. The differences between sub-national territorial emissive behavior can be revealed by subjecting different territories to the same stress factors. A complete GHG emissions inventory, based on the Intergovernmental Panel on Climate Change (IPCC) Guidelines, is compiled for three diverse administrative territories, in terms of scale, socio-economic contexts, and environmental conditions. By selecting three diverse sub-national contexts belonging to the same national territory - Italy - the analysis provides highly detailed information on the emissive status and behavior and delivers insights that national inventories fail to provide. The COVID-19 pandemic is considered as a stress factor; therefore, the reference years are 2019 and 2020 during which GHG emissions are detected. The study will test the capacity of sub-national GHG emission inventories, compiled by scaling the IPCC methodology to the sub-national level, to detect such differences through the lens of the pandemic. This allows obtaining detailed information and linking the pandemic effect to the GHG emissions of particular activities, which can inspire effective sub-national context-specific mitigation actions. Furthermore, we show that environmental and economic metrics are not as strictly coupled as they would appear at national level.

Global Burden of Chronic Obstructive Pulmonary Disease Through 2050

Importance

Chronic obstructive pulmonary disease (COPD) is a respiratory condition that is associated with significant health and economic burden worldwide. Previous studies assessed the global current-day prevalence of COPD, but to better facilitate resource planning and intervention development, long-term projections are needed.

Objective

To assess the global burden of COPD through 2050, considering COPD risk factors.

Design, Setting, and Participants

In this modeling study, historical data on COPD prevalence was extracted from a recent meta-analysis on 2019 global COPD prevalence, and 2010 to 2018 historical prevalence was estimated using random-effects meta-analytical models. COPD risk factor data were obtained from the Global Burden of Disease database.

Main Outcomes and Measures

To project global COPD prevalence to 2050, generalized additive models were developed, including smoking prevalence, indoor and outdoor air pollution, and development indices as predictors, and stratified by age, sex, and World Bank region.

Results

The models estimated that the number of COPD cases globally among those aged 25 years and older will increase by 23% from 2020 to 2050, approaching 600 million patients with COPD globally by 2050. Growth in the burden of COPD was projected to be the largest among women and in low- and middle-income regions. The number of female cases was projected to increase by 47.1% (vs a 9.4% increase for males), and the number of cases in low- and middle-income regions was expected to be more than double that of high-income regions by 2050.

Conclusions and Relevance

In this modeling study of future COPD burden, projections indicated that COPD would continue to affect hundreds of millions of people globally, with disproportionate growth among females and in low-middle income regions through 2050. Further research, prevention, and advocacy are needed to address these issues so that adequate preparation and resource allocation can take place.

Predictive modeling and analysis of air quality - Visualizing before and during COVID-19 scenarios

Quality air to breathe is the basic necessity for an individual and in recent times, emission from various sources caused by human activities has resulted in substantial degradation in the air quality. This work focuses to study the inadvertent effect of COVID-19 lockdown on air pollution. Pollutants' concentration before- and during- COVID-19 lockdown is captured to understand the variation in air quality. Firstly, multi-pollutant profiling using hierarchical cluster analysis of pollutants' concentration is performed that highlights the differences in the cluster compositions between before- and during-lockdown time periods. Results show that the particulate matter (PM₁₀ and PM_2.5) in air that formed the primary cluster before lock-down, came down to close similarity with other clusters during lockdown. Secondly, predicting air quality index (AQI) based on the forecasts of pollutants' concentration is performed using neural networks, support vector machine, decision tree, random forest, and boosting algorithms. The best-fitted models representing AQI is identified separately for before- and during-lockdown time periods based on its predictive power. While deterministic method reactively evaluates present AQI when current pollutants' concentration at a particular time and place are known, this study uses the best fitted data-driven model to determine future AQIs based on the forecasts of pollutant's concentration accurately (overall RMSE<0.1 for before lockdown scenario and <0.3 for during lockdown scenario). The study contributes to visualize the variation in pollutants' concentrations between the two scenarios. The results show that the reduced economic activities during lockdown period had led to the drop in concentration of PM₁₀ and PM_2.5 by 27% and 50% on an average. The findings of this study have practical and societal implications and serve as a reference mechanism for policymakers and governing bodies to revise their actions plans for regulating individual air pollutants in the atmospheric air.

Evolution of Pollution Levels from COVID-19 Lockdown to Post-Lockdown over India

The spread of the COVID-19 pandemic forced the administration to lock down in many countries globally to stop the spread. As the lockdown phase had only the emergency use of transportation and most of the industries were shut down, there was an apparent reduction in pollution. With the end of the lockdown period, pollution is returning to its regular emission in most places. Though the background was abnormally low in emissions (during the lockdown phase) and the reduced pollution changed the radiation balance in the northern hemispheric summer period, a modified pollution pattern is possible during the unlock phases of 2020. The present study analysed the unlock 1 and 2 stages (June-July) of the COVID-19 lockdown over India. The rainfall, surface temperature and cloud cover anomalies of 2020 for understanding the differences in pollutants variation were also analysed. The unlock phases show remarkable differences in trends and mean variations of pollutants over the Indian region compared to climatological variations. The results indicated changing high-emission regions over India to climatological variations and identified an AOD dipole with future emissions over India.

The Atmospheric Environment Effects of the COVID-19 Pandemic: A Metrological Study

Since the COVID-19 outbreak, the scientific community has been trying to clarify various problems, such as the mechanism of virus transmission, environmental impact, and socio-economic impact. The spread of COVID-19 in the atmospheric environment is variable and uncertain, potentially resulting in differences in air pollution. Many scholars are striving to explore the relationship between air quality, meteorological indicators, and COVID-19 to understand the interaction between COVID-19 and the atmospheric environment. In this study, we try to summarize COVID-19 studies related to the atmospheric environment by reviewing publications since January 2020. We used metrological methods to analyze many publications in Web of Science Core Collection. To clarify the current situation, hotspots, and development trends in the field. According to the study, COVID-19 research based on the atmospheric environment has attracted global attention. COVID-19 and air quality, meteorological factors affecting the spread of COVID-19, air pollution, and human health are the main topics. Environmental variables have a certain impact on the spread of SARS-CoV-2, and the prevalence of COVID-19 has improved the atmospheric environment to some extent. The findings of this study will aid scholars to understand the current situation in this field and provide guidance for future research.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM_2.5 concentrations and an enhancement in the O₃ concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O₃ formation, comprising 89.4%, 83.1%, and 88.9% of the O₃ sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O₃ concentrations at the surface layer. Compared with the Pre1 period, the O₃ enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O₃ removal rate by horizontal transport. During the Tri period, a slower consumption of O₃ by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O₃. Emission and aerosol processes constituted the major positive contributions to the net surface PM_2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM_2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM_2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM_2.5 production from emission and aerosol processes. The increased vertical transport rate of PM_2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM_2.5 during the Lock periods.

Changing Air Quality and the Ozone Weekend Effect during the COVID-19 Pandemic in Toronto, Ontario, Canada

Air pollutants, NO, NO2, and O3, were examined from April to June 2020 and compared to a 10-year (2010–2019) climatology of these pollutants for two monitoring sites in Toronto, Ontario, Canada, coinciding with local lockdown measures during the first wave of the COVID-19 pandemic. NO and NO2 values were lower than any of the preceding 10 years at the two Toronto sites for both weekdays and weekends. Ozone concentrations did not have a corresponding decrease and in fact increased for weekdays, similar to other parts of the world. The well-documented ozone weekend effect was considerably muted during the morning rush hour throughout this pandemic period. A Fisher exact test on hourly averaged data revealed statistically significant record hourly minimums for NO and NO2, but this was not found for ozone, consistent with the aggregate ranking results. These findings are likely the result of considerably reduced vehicular traffic during this time and ozone chemistry in a NOx-saturated (VOC limited) environment. This has important implications for ozone abatement strategies.