To date, epidemiologic evidence regarding the underlying relationships of ambient atmospheric pollutants on COVID-19 outbreak is insufficient. In this study, we analyzed multisite data on airborne pollutants and daily newly COVID-19 confirmed cases in 41 Chinese cities, although Wuhan (the worst affected city of China) was not included. We observed modest correlations between daily newly COVID-19 confirmed cases and acute exposure to NO2, and to a lesser extent, with PM2.5, O3 and SO2. In the analysis of main models for pollutants, we observed the RRs (95% CI) for the associations between daily newly COVID-19 confirmed cases and PM2.5, O3, SO2 and NO2 were 1.050 (1.028, 1.073) at lag 0−14, 1.011 (1.007, 1.015) at lag 0−1, 1.052 (1.022, 1.083) at lag 0 and 1.094 (1.028, 1.164) at lag 0−14 per each 10 μg/m3 increment, respectively. These results conform the assumption that viruses attach to air pollutants (Reche et al. 2018) and pollutants actually act as the airborne medium of SARS-CoV-2 (Contini &Costabile 2020), potentially explaining the spread of SARS-CoV-2 and its infectious capacity.
Some research has shown that acute exposure to air pollutants is correlated with COVID-19 prevalence or fatality. For example, a meta-analysis by Cao et al. based on estimates from 71 cities across China reported an increase of interquartile range in PM2.5, O3, SO2 and NO2 at lag 4 corresponding to 1.40 (1.37, 1.43), 1.28 (1.27, 1.29), 1.01 (1.00, 1.02) and 1.08 (1.07, 1.10) odd ratios of daily COVID-19 confirmation, respectively (Cao et al. 2020). Study conducted carried out in 120 cities across China revealed increases in daily counts of confirmed cases of 2.24%, 4.76%, -7.79% and 6.94% each 10 μg/m3 increment in PM2.5, O3, SO2 and NO2 as well (Zhu et al. 2020). Comparing our results to the aforementioned analysis, our findings for SO2 and COVID-19 incidence are completely opposite to their results. It is not clear why the correlations between air pollution and daily COVID-19 morbidity would be different in our study from associations reported by different studies, but it might be explained by factors such as the different scale of the study city and amount of data, fewer considered meteorological variables, and relative higher concentrations and big fluctuation of pollutants during study period (Li &Chen 2020). Futhermore, uncontrolled residual confounding or chance as possible explanations should also be considered.
Moreover, several multi-city studies about individual pollutants have also been reported. A multi-city study (Wang et al. 2020) in 72 cities (excluding Wuhan) reported a summary estimate for daily COVID-19 confirmed cases of 1.016 (1.015, 1.018) per 10 μg/m3 rise in the level of PM2.5 at lag 0−14. A national American analysis observed a significant increment of 7.1% (1.2%, 13.4%) and 11.2% (3.4%, 19.5%) in COVID-19 case-fatality and mortality per IQR in NO2 (Liang et al. 2020). In England, studies also reported increases in COVID-19 incidence in addition to mortality alongside rises in NOx or SO2, meaning regional variations in the two pollutants may predict the numbers of COVID-19 cases and death (Travaglio et al. 2021). A study conducted in 120 Chinese cities (excluding Wuhan) by multivariate negative binomial regression implicated the increased number of COVID-19 confirmed cases was accompanied by acute exposure to elevated levels of PM2.5 and O3 and reduced levels of SO2 (Zhou et al. 2021). It should be noted that some studies summarized above reported a negative significant association between SO2 and COVID-19 incidence, this may due to the relatively low levels of SO2. Our two−pollutant models found a non-significant association between SO2 and COVID-19 incidence after adjusting for other pollutants such as PM2.5 and O3, suggesting that the mechanism of the interaction between SO2 and other pollutants should be explored in future studies.
Whether the observed correlations between air pollutants are independent of other pollutants is a significant issue for air quality control and health risk assessment. In the present study, although the degree of the correlation between PM2.5 and O3 has changed in two-pollutant models, the correlation between the two remained mostly significant, which provides evidence supporting the independent health impacts of PM2.5 and O3. It is remarkable that the estimates of relative risk of COVID-19 incidence per 10 μg/m3 rise with the decrease of PM2.5 levels and has no significant effects, a finding that may reflect the close correlations of PM2.5 with PM10 caused by similar sources. As for SO2, the two-pollutant models indicated that the estimated effect of SO2 on COVID-19 incidence was attributable to confounding by other air pollutants (except NO2). In addition, although NO2 are key O3 precursors (Naja &Lal 2002), the two-pollutant model indicated NO2 has a strong and independent influence on COVID-19 incidence, meaning that the influence of NO2 may not mediated by O3.
Previous experiments on coronaviruses in controlled conditions show that it can survive at around 4°C and a relative humidity of 20−80%, and inactivates rapidly above 20°C (Casanova et al. 2010). It seems that specific climate conditions, especially ambient temperature and humidity modulate the survival and spread of SARS-CoV-2. A systematic review suggested that warm and humid climates seem to weaken the transmission of COVID-19 while the certainty of the evidence produced was graded as low (MecenasI et al. 2020). Analogously, a time-series analysis in mainland China found with a relative humidity of 67%−85.5%, every 1°C elevation in temperature resulted in a decrease in the daily confirmed cases of 36%−57% (Qi et al. 2020). A global study also reported that the incidence of COVID-19 decreased by 6% and 3% after adjusting for daily maximum temperature and RH (Islam et al. 2020), while Wan et al. found the transmission capacity of COVID-19 peaked about 6.3°C and then decreased under high temperature conditions of human intervention (Wan et al. 2020). Contrary to the above conclusion, a study across China suggests that the spread speed of the COVID-19 outbreak is independent of temperature, while the temperature-dependence of the propagation reported in earlier related work was likely to be an artifact since the temperature-dependence blurred with a prevailing zonal pattern of spread across the north-temperature zone, reflecting the primary patterns of human activities (Jamil et al. 2020). Pawar also indicates that although a strong relationship between recovered cases and death cases was observed, changes in temperature showed no significant correlation with confirmed cases in China by linear regression models (Pawar et al. 2020). In addition, ultraviolet photons has also been considered to play the possible role in the modulation of COVID-19 epidemiology (Nicastro et al. 2020).
The underlying pathophysiological mechanism for developing COVID-19 is perplexing and very few toxicological literature on biological plausibility have been published. It has been reported (Frontera et al. 2020) that chronic exposure to PM2.5 leads to overexpression of alveolar angiotensin-converting enzyme 2 (ACE-2) receptor, which is crucial in protecting lung from air pollution (Alifano et al. 2020, Lin et al. 2018), as well as the main receptor of SARS-CoV-2 (Zhou et al. 2020). This may increase the viral load in a body exposed to pollutants, thus occupying ACE-2 receptors and weakening host defenses. Furthermore, exposure to NO2 may bring a second hit after exposure to PM2.5, causing severe forms of SARS-CoV-2 to appear in the lungs where ACE-2 depleted, leading to worse results. The current toxicology literature suggests that exposure to ambient ground level ozone is pertinent to the emergence of respiratory diseases such as asthma, influenza and SARS (Zoran et al. 2020). O3 is a potential oxidizer and may induce oxidative stress, which may harm the immune systems and organs such as lung and heart, by changing the host’s resistance to viral and bacterial infections (Ciencewicki &Jaspers 2007). A study in northern Italy (Conticini et al. 2020) has shown that an overexpression of IL-8, IL-17 and TNF-α, induced by O3, contributes to prolonged systemic and respiratory system inflammation and eventually leads to an innate immune system hyper-activation. Compared to PM2.5 and O3, fewer research has studied the biological pathways of harmful effects of NO2 and SO2. The virological explanation might be that NO2 causes the reactions of components in the airway surface fluids (ASF) of the respiratory tract and lungs, resulting in highly reactive proteins and lipid oxidation products that can cause inflammation by subsequently damaging epithelial cells through secondary reactions (Gamon &Wille 2016). Another study by Chauhan et al.(Chauhan et al. 2003) has done research on the relation between NO2 exposure and respiratory disease caused by proven respiratory viral infections including coronavirus.
Our study indicates that air pollutants are important in analyzing the pathogenesis of COVID-19 and that the effect of air pollutants on the disease deserves more attention. It is also subject to some limitations. Primarily, the correlations between air pollutants and COVID-19 confirmation were affected by many other factors, such as strict prevention measure and population migration. Secondly, as the definitions of COVID-19 cases changed at different stage of the epidemic, the number of COVID-19 confirmed cases may be affected. Next, we only focused on cities across China where the cumulative COVID-19 confirmed cases exceeds 100 and the environmental data are available (except Wuhan) during the study period, so the estimate of air pollutants effects cannot be generalized to other countries. Finally, stratified analysis by gender or age on were not analyzed in our study due to a lack of detailed information on each infectious case. Future studies should be developed to overcome these limitations and the mechanisms of the impact on COVID-19 risk deserve further study.