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

Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand

OBJECTIVES

Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous.

METHODS

This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels.

RESULTS

Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak.

CONCLUSIONS

Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.

Modeling NO2 air pollution variation during and after COVID-19-regulation using principal component analysis of satellite imagery

By implementing Principal Component Analysis (PCA) of multitemporal satellite data, this paper presents modeling solutions for air pollutant variation in three scenarios related to COVID-19 lockdown: pre, during, and after lockdown. Tropospheric NO2 satellite data from Sentinel-5P was used. Two novel PCA-models were developed: Weighted Principal Component Analysis (WPCA) and Rescaled Principal Component Analysis (RPCA). Model results were tested for goodness-of-fit to empirical NO2 data. The models were used to predict actual near-surface NO2 concentrations. Model-predicted NO2 concentrations were validated with NO2 data acquired at ground monitoring stations. Besides, meteorological bias affecting NO2 was assessed. It was found that the weather component had substantial impact on NO2 built-ups, propitiating air pollutant decrease during lockdown and increase after. WPCA and RPCA models well fitted to observed NO2. Both models accurately estimated near-surface NO2 concentrations. Modeled NO2 variation results evidenced the prolongated effect of the total lockdown (up to half a year). Model-predicted NO2 concentrations were found to highly correlate with monitoring station NO2 data collected on the ground. It is concluded that PCA is reliable in identifying and predicting air pollution variation patterns. The implementation of PCA is recommended when analyzing other pollutant gases.

A decreased impact of air pollution on hospital pneumonia visits during COVID-19 outbreak in northeastern Thailand

Background

The coronavirus disease 2019 (COVID-19) pandemic had effects on changes in people, society, and pollutant sources. This was a unique research opportunity to assess the effects on the risk of pneumonia resulted from the changes in air pollution and personal hygiene regarding city lockdown.

Methods

This study, we estimated time-series relative risks (RRs) of pneumonia (n=94,288) associated with PM10, PM2.5, NO2, and O3 in Khon Kaen province and its vicinity, using Poison regression with generalized additive model and compared air pollutant-associated risk of pneumonia before vs. during the COVID-19 outbreak [2018-2021].

Results

During the COVID-19 period, pneumonia cases, PM2.5, PM10, and NO2 levels were lower than those before the COVID-19 but the O3 level was significantly higher. The single-pollutant analyses showed that the increase in PM10, PM2.5, and NO2 were significantly associated with pneumonia risks at single-day lag 0 in the earlier two years (2018-2019). For multi-pollutant analyses, there were higher RRs in PM2.5 at lag 0 [RR =1.078, 95% confidence interval (CI): 1.004 to 1.157], lag 4 (RR =1.054, 95% CI: 1.011 to 1.098) and lag 5 (RR =1.090, 95% CI: 1.021 to 1.165) and for all cumulative-day lags, greatest was at lag 0-5 (RR =1.314, 95% CI: 1.200 to 1.439) before the COVID-19 period while there were lower pneumonia RRs of a 10-µg/m3 increase in PM2.5 at single-day lag 1 (RR =1.064, 95% CI: 1.002 to 1.130) and for all cumulative-day lags, greatest was at lag 0-5 (RR =1.201, 95% CI: 1.073 to 1.344) during the COVID-19 outbreak. Multi-pollutant of NO2 significantly increased pneumonia risk in cumulative day exposure before the COVID-19 outbreak at lag 0-3 (RR =1.050, 95% CI: 1.001 to 1.100). It was significantly greater than that risk during the outbreak.

Conclusions

This study revealed that the lockdown measures to control COVID-19 were effective in improving air quality and lowering associated pneumonia risk. These findings would help raise awareness about measures and policies to preserve the air quality to increase respiratory health benefits.

Source apportionment of PM2.5 before and after COVID-19 lockdown in an urban-industrial area of the Lisbon metropolitan area, Portugal

The lockdowns held due to the COVID-19 pandemic conducted to changes in air quality. This study aimed to understand the variability of PM_2.5 levels and composition in an urban-industrial area of the Lisbon Metropolitan Area and to identify the contribution of the different sources. The composition of PM_2.5 was assessed for 24 elements (by PIXE), secondary inorganic ions and black carbon. The PM_2.5 mean concentration for the period (December 2019 to November 2020) was 13 ± 11 μg.m^-3. The most abundant species in PM_2.5 were BC (19.9%), SO₄ ^2- (15.4%), NO₃ ^- (11.6%) and NH₄ ⁺ (5.3%). The impact of the restrictions imposed by the COVID-19 pandemic on the PM levels was found by comparison with the previous six years. The concentrations of all the PM_2.5 components, except Al, Ba, Ca, Si and SO₄ ^2-, were significantly higher in the winter/pre-confinement than in post-confinement period. A total of seven sources were identified by Positive Matrix Factorisation (PMF): soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust, and industry. Sources were greatly influenced by the restrictions imposed by the COVID-19 pandemic, with vehicle exhaust showing the sharpest decrease. Secondary sulphate predominated in summer/post-confinement. PM_2.5 levels and composition also varied with the types of air mass trajectories.

Air pollution and childhood asthma

PURPOSE OF REVIEW

Asthma is the most common chronic disease of childhood. Environmental exposures, such as allergens and pollutants, are ubiquitous factors associated with asthma development and asthma morbidity. In this review, we highlight the most recent studies relevant to childhood asthma risk, onset, and exacerbation related to air pollution exposure.

RECENT FINDINGS

In this article, we review current research that has been published between 2021 and 2022, demonstrating the effects of early-life exposure to key air pollutants (e.g., particulate matter (PM), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ) and ground-level ozone (O 3 ), environmental tobacco smoke, radon, and volatile organic compounds (VOC) on respiratory health.

SUMMARY

Air pollution continues to be a global burden with serious consequences related to respiratory health. Interventions aimed at reducing air pollution in the environment must be achieved in an effort to improve asthma outcomes and pediatric health.

Catalytic removal of 2-butanone with ozone over porous spent fluid catalytic cracking catalyst

To remove harmful volatile organic compounds (VOCs) including 2-butanone (methyl ethyl ketone, MEK) emitted from various industrial plants is very important for the clean air. Also, it is worthwhile to recycle porous spent fluid catalytic cracking (SFCC) catalysts from various petroleum refineries in terms of reducing industrial waste and the reuse of discharged resources. Therefore, Mn and Mn-Cu added SFCC (Mn/SFCC and Mn-Cu/SFCC) catalysts were prepared to compare their catalytic efficiencies together with the SFCC catalyst in the ozonation of 2-butanone. Since the SFCC-based catalysts have a structure similar to that of zeolite Y (Y), the Mn-loaded zeolite Y catalyst (Mn/Y) was also prepared to compare its activity for the removal of 2-butanone and ozone to that of the SFCC-based ones at room temperature. Among the five catalysts of this study (Y, Mn/Y, SFCC, Mn/SFCC, and Mn-Cu/SFCC), the Mn-Cu/SFCC and Mn/SFCC catalysts showed the better catalytic decomposition activity than the others. The increased distributions of the Mn³⁺ species and the O_vacancy sites in Mn/SFCC and Mn-Cu/SFCC catalysts which could supply more available active sites for the 2-butanone and ozone removal would enhance the catalytic activity of them.

Epigallocatechin Gallate Relieved PM2.5-Induced Lung Fibrosis by Inhibiting Oxidative Damage and Epithelial-Mesenchymal Transition through AKT/mTOR Pathway

Oxidative damage and epithelial-mesenchymal transition (EMT) are main pathological processes leading to the development of PM2.5-induced lung fibrosis. Epigallocatechin gallate (EG), a natural polyphenol extracted from green tea, possesses the ability to combat oxidative stress and inflammation. However, the potential roles of EG in PM2.5-induced lung fibrosis have not been reported yet. In the present study, we investigated whether EG could relieve PM2.5-induced lung injury and fibrosis in vivo and in vitro. To mimic PM2.5-induced lung fibrosis, C57/BL6 mice were intranasally instilled with PM2.5 suspension, and MLE-12 lung epithelial cells were stimulated with PM2.5 (100 μg/mL) in vitro. The results showed that intragastric administration of EG (20 mg/kg/d or 80 mg/kg/d for 8 weeks) significantly prevented lung injury, inflammation, and oxidative stress in PM2.5-induced mice, apart from inhibiting collagen deposition. Additionally, EG treatment also suppressed the activation of AKT/mTOR signaling pathway in lung tissues challenged with PM2.5. In vitro experiments further demonstrated that EG treatment could enhance cell viability in a concentration-dependent manner in PM2.5-treated MLE-12 lung epithelial cells. Also, the overexpression of constitutively active AKT could offset the inhibitory effects of EG on EMT and oxidative stress in PM2.5-treated MLE-12 lung epithelial cells. Finally, AKT overexpression also blocked the inhibitory effect of EG on the phosphorylation of mTOR in PM2.5-treated MLE-12 lung epithelial cells. In conclusion, EG could improve PM2.5-induced lung fibrosis by decreasing oxidative damage and EMT through AKT/mTOR pathway, which might be a potential candidate for the treatment of PM2.5-induced lung fibrosis.