The Improvement of Air Quality and Associated Mortality during the COVID-19 Lockdown in One Megacity of China: An Empirical Strategy

Change in disease burden associated with influenza and air pollutants during the COVID-19 pandemic in Hong Kong

Objectives

This study aimed to estimate the variation in disease burden associated with air pollutants and other respiratory viruses during the COVID-19 pandemic.

Methods

We adopted a machine learning approach to calculate the excess mortality attributable to air pollutants and influenza, during the pre-pandemic and pandemic period.

Results

In the first 2 years of the COVID-19 pandemic, there were 8762 (95% confidence interval, 7503-9993), and 12,496 (11,718-13,332) excess all-cause deaths in Hong Kong. These figures correspond to 117.4 and 167.9 per 100,000 population, and 12.6% and 8.5% of total deaths in 2020 and 2021, respectively. Compared to the period before the pandemic, excess deaths from all-causes, cardiovascular and respiratory diseases, pneumonia and influenza attributable to influenza A and B significantly decreased in all age groups. However, excess deaths associated with ozone increased in all age-disease categories, while the relative change of nitrogen dioxide (NO2) and particular matters less than 10 µm (PM10) associated burden showed a varied pattern.

Conclusions

A notable shift in disease burden attributable to influenza and air pollutants was observed in the pandemic period, suggesting that both direct and indirect impacts shall be considered when assessing the global and regional burden of the COVID-19 pandemic.

Air Pollution Alleviation During COVID-19 Pandemic is Associated with Renal Function Decline in Stage 5 CKD Patients

Introduction

Methods

Results

Conclusion

Air pollution and health impacts during the COVID-19 lockdowns in Grenoble, France

It is undeniable that exposure to outdoor air pollution impacts the health of populations and therefore constitutes a public health problem. Any actions or events causing variations in air quality have repercussions on populations' health. Faced with the worldwide COVID-19 health crisis that began at the end of 2019, the governments of several countries were forced, in the beginning of 2020, to put in place very strict containment measures that could have led to changes in air quality. While many works in the literature have studied the issue of changes in the levels of air pollutants during the confinements in different countries, very few have focused on the impact of these changes on health risks. In this work, we compare the 2020 period, which includes two lockdowns (March 16 - May 10 and a partial shutdown Oct. 30 - Dec. 15) to a reference period 2015-2019 to determine how these government-mandated lockdowns affected concentrations of NO₂, O₃, PM_2.5, and PM₁₀, and how that affected human health factors, including low birth weight, lung cancer, mortality, asthma, non-accidental mortality, respiratory, and cardiovascular illnesses. To this end, we structured 2020 into four periods, alternating phases of freedom and lockdowns characterized by a stringency index. For each period, we calculated (1) the differences in pollutant levels between 2020 and a reference period (2015-2019) at both background and traffic stations; and (2) the resulting variations in the epidemiological based relative risks of health outcomes. As a result, we found that relative changes in pollutant levels during the 2020 restriction period were as follows: NO₂ (-32%), PM_2.5 (-22%), PM₁₀ (-15%), and O₃ (+10.6%). The pollutants associated with the highest health risk reductions in 2020 were PM_2.5 and NO_2, while PM₁₀ and O₃ changes had almost no effect on health outcomes. Reductions in short-term risks were related to reductions in PM_2.5 (-3.2% in child emergency room visits for asthma during the second lockdown) and NO₂ (-1.5% in hospitalizations for respiratory causes). Long-term risk reductions related to PM_2.5 were low birth weight (-8%), mortality (-3.3%), and lung cancer (-2%), and to NO₂ for mortality (-0.96%). Overall, our findings indicate that the confinement period in 2020 resulted in a substantial improvement in air quality in the Grenoble area.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM1, PM2.5 and PM10 fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization. The models’ predictions were subsequently de-weathered by meteorological normalization using repeated random resampling of all predictive variables except the trend variable. Three pollution periods in 2020 were examined in detail: January and February, as pre-lockdown, the month of April as the lockdown period, as well as June and July as the “new normal”. An evaluation using normalized mass concentrations of particulate matter and Analysis of variance (ANOVA) was conducted. The results showed that no significant differences were observed for PM1, PM2.5 and PM10 in April 2020—compared to the same period in 2018 and 2019. No significant changes were observed for the “new normal” as well. The results thus indicate that a reduction in mobility during COVID-19 lockdown in Zagreb, Croatia, did not significantly affect particulate matter concentration in the long-term..

Ecological Civilization Demonstration Zone, Air Pollution Reduction, and Political Promotion Tournament in China: Empirical Evidence from a Quasi-Natural Experiment

Using the ecological civilization demonstration zone as a quasi-natural experiment, this study has explored the effect of it on air pollution in China by employing the difference-in-differences model and the spatial difference-in-differences model, and further tested the political promotion tournament in China by employing the binary logit model. The results show that the ecological civilization demonstration zone has basically and effectively reduced air pollution, except for carbon monoxide and ozone. In addition, the spatial spillover effects of the ecological civilization demonstration zone on air pollution are not only basically supported among the treated cities, but also extremely established in the untreated cities neighboring the treated cities. Furthermore, no clear evidence supports the establishment of the political promotion tournament in China, while local cadres tend to cope with the assessment of higher officials passively rather than actively. Overall, this study sheds light on the coordination of economic development and ecological civilization from the perspective of the career concerns of local cadres.