Associations between Air Quality and Covid-19 Infection

Yuye Chen

Department of Chemistry, University College London, London WC1E 6BT, U.K.

Keywords: COVID-19, Air Pollution, Particulate Matter, ACE2.

Abstract: Air pollution has been an urgent trouble for many regions. The clear relationship between various types of air

pollution and COVID-19 cases has not been well understood. The particulate matter (PM), as an air pollutant,

was found to act as a potential carrier of the SARS-CoV-2 virus. It might also cause higher angiotensin-

converting enzyme 2 (ACE2) activation when inducing airway inflammation, and eventually increase the risk

of COVID-19 infection. By concluding some of the existing studies, the statistical correlations between air

pollutants and COVID-19 infection can be visualised, such as positive correlations found between PM

2.5

, NO

, etc. and COVID-19 infection, while negative correlations with SO

, as well as some controversial

findings on O

, etc. Further research is required to address possible mechanisms of how PM might facilitate

the spreading of COVID-19. Monitoring air pollution levels and applying comprehensive models for analys-

ing associations between COVID-19 infection and air pollution appear to be useful for further studies.

1 INTRODUCTION

COVID-19 has caused a worldwide pandemic. Over

200 countries have suffered from the SARS-CoV-2

virus. As of 10th September 2021, over 200 million

infection cases and 4 million deaths have been re-

ported to World Health Organization (Geneva: World

Health Organization, 2020). COVID-19 patients usu-

ally undergo fever, cough; and fatigue, with conges-

tion, sore throat, etc. also could be seen in some cases

(Fu et al. 2020). Coronaviruses (CoVs) are enveloped

viruses with a positive single-stranded RNA genome

inside each virus. COVID-19 is caused by the SARS-

CoV-2, a very pathogenic form of virion (Borisova

and Komisarenko 2021) that enters the host

cell via binding through the angiotensin-converting

enzyme 2 (ACE2) receptor (Naqvi et al. 2020), which

is a membrane enzyme found in the lungs, arteries,

heart, kidney, and intestines’ cells (Lin et al., 2018).

Research has found that countries such as China

(Zhu et al. 2020, Hou et al. 2021, Yao et al. 2021) and

Italy (Bontempi 2020, Fattorini and Regoli 2020) that

reported a high incidence of COVID-19 together with

high levels of air pollution. For example, a study of

China with an average daily COVID-19 confirmed

cases of 12.94 calculated during the observation pe-

riod found that average daily concentrations of PM

2.5

https://orcid.org/0000-0003-3813-2466

, CO, NO

, and O

(46.43 μg/m

, 62.97 μg/m

0.85 mg/m

, 19.28 μg/m

and 78.22 μg/m

, respec-

tively) were significantly positively related to

COVID-19 confirmed cases (Zhu et al. 2020). More-

over, among these air pollutant particles, the mecha-

nism of how PM (particulate matter) might facilitate

the infection of COVID-19 was recently investigated

(Comunian et al. 2020). Previous studies found that

may cause airway inflammation (Choi et al.

2020) and PM

2.5

collected in China largely enhanced

the levels of expression of the inflammatory genes

(Bekki et al. 2016). In the case of inflammation

caused by PM, ACE2 as an anti-inflammatory peptide

generator is overactivated, leading to an increased

likelihood of COVID-19 entering the cells (Hayashi

et al. 2010).

This review introduces the possible mechanism of

COVID-19 infection facilitated by PM, as well as

summarizes and discusses the correlation between the

number of COVID-19 infection cases and air pollu-

tion. The different models chosen for the various

studies are also mentioned, which would give refer-

ences to the model constructions in further studies.

Chen, Y.

Associations between Air Quality and Covid-19 Infection.

DOI: 10.5220/0011255200003438

In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare (ICHIH 2022), pages 245-253

ISBN: 978-989-758-596-8

245

2 GENERAL MECHANISMS

2.1 Interaction between PM Particles

and COVID-19 Virus

PM as the global environmental issue is known to

cause irregular inflammatory and coagulation re-

sponses through the whole body (Choi et al. 2020).

There are many sources of PM classified by their di-

ameters. For example, PM

and PM

2.5

stand for par-

ticulate matter with diameters no more than 10 mi-

crometers and 2.5 micrometers respectively

(Comunian et al. 2020). Certain types of PM were

found to be able to interact with the plasma membrane

of nerve cells (Borisova and Komisarenko 2021).

COVID-19 virus has an envelope that can contain li-

pid components of host neuron cells as well as mem-

brane fragments of infected cells (Borisova and

Komisarenko 2021). Evidence has shown that some

fine/ultrafine PM was be able to interact with the

plasma membrane of nerve terminals in brains

(Borisova and Komisarenko 2021). Therefore, these

water-suspended PM particles in turn forms com-

plexes with the COVID-19 virus that contains mem-

brane segments of brain nerve cells. The complexes,

when dried, then serves as carriers of the COVID-19

virus in the transmission (Borisova and Komisarenko

2021). The viruses are immobilized to the surfaces of

these particles, leading to possible changes in the

characteristics of the original virus. For example, the

virus becomes more stable when grouping with these

PM. Moreover, these SARS-CoV-2-PM complex

possibly may enter the cells without binding to the

ACE2 receptor (Borisova and Komisarenko 2021).

2.2 PM Activating ACE2 Causing

COVID-19 Infection

ACE2 is a receptor on the cell membrane that binds

to the spike-like proteins on the surface of the

COVID-19 virus. It can regulate blood pressure by

catalyzing the breaking of vasoconstrictor peptide,

angiotensin 2 and turn them into angiotensin 1-7

(Comunian et al. 2020). ACE1 and ACE2 cooperating

in the renin-angiotensin system could lead to the pro-

tection of organs and blood vessels by anticoagulant,

anti-inflammatory, anti-oxidative stress activity, etc.

(Gemmati et al. 2020). As SARS-CoV-2 depends on

ACE2 to enter the host cell, various pathological con-

ditions that could further activate ACE2 have been

listed as possible hazards for COVID-19 (Wang et al.

2021). One of the possible mechanisms could be in-

flammation. Due to the anti-inflammatory function of

angiotensin 1-7 peptide, ACE2 can make lung impair-

ment from hyperoxia less severe by inhibiting the in-

flammatory response. Therefore, when there is in-

flammation, the activity of ACE2 would increase

(Comunian et al. 2020). Chronic PM

2.5

exposure was

found to increase the risk of systemic inflammation

and oxidative stress in the lung epithelial cells (Pun et

al. 2017). Also, research showed that exposure to PM

particles can cause an inflammatory response, which

might activate ACE2 and thus facilitate the infection

of COVID-19 (Comunian et al. 2020). Therefore, PM

may increase the risk of COVID-19 infection via

ACE2 expression, as shown in Fig.1. In addition, the

increased inflammation may also aggravate lung in-

jury (Tung et al. 2021).

Figure 1: PM facilitating SARS-CoV-2 binding to ACE2 receptors to enter the host cell.

ACE2 receptors

SARS-CoV-2

TMPRSS2

PM induced oxidative

stress and inflammatory

response

Activated ACE2; upregulated

ACE2 expression

Increased risk of COVID-19

infection

Viral

Attachment

Host cell

Virus Entry

ICHIH 2022 - International Conference on Health Big Data and Intelligent Healthcare

246

2.3 Nose-to-brain Entering Pathways

of PM Particulates and

CoronaVirus and Their Influence

on Brain Nerve Terminals

PM, the inhalable corpuscles, can lead to various

health problems because of their small size

(Comunian et al. 2020). For example, the water-sus-

pended smoke PM was found to affect exocytosis in

nerve terminals (Borisova and Komisarenko 2021).

The air pollution PM influenced exocytosis in nerve

terminals, which in turn changed the transfer activity

of CoVs between neurons. Air pollution PM and

CoVs can be inhaled through the same nasal cavity

path, pass through the axon of olfactory nerves, and

eventually reach the brain (Borisova and

Komisarenko 2021). They can then act separately

and/or as a SARS-CoV-2-PM complex. Their neuro-

logical effects can meddle and intensify each other,

being additive or even synergetic. When acting as a

complex, the SARS-CoV-2-PM may disturb synaptic

vesicle recycling in the process of exo-/endocytosis

due to their larger size (Borisova and Komisarenko

2021).

3 AIR QUALITY CHANGES

DURING COVID-19

LOCKDOWN

Results for a study in China showed that the signifi-

cant decreases in NO

and other air pollution emis-

sions in the lockdown period due to COVID-19 con-

tributed to considerable increases in O

, which in-

duced elevated atmospheric oxidizing ability and

boosted the forming of secondary PM in eastern

China (Huang et al. 2021). Another study of America

found that the CO concentration fell more rapidly

than NO

and PM

2.5

concentrations during the

COVID-19 situation, while NO

emissions dropped

over places of main power plants and rose over

densely populated residential regions, especially

those functioning as transportation centres at the junc-

tions of national highways (Liu et al. 2021). A study

in Korea found that from January 2020 to April 2020,

monthly mean concentrations of PM

2.5

, PM

, NO

and CO were significantly lower than those in the

three previous years (Ju et al. 2021). Another study of

the Bangkok Metropolitan Region found that NO and

the AQI declined during the COVID-19 lockdown.

By comparison, CO, NO

, SO

, O

, and PM

2.5

in-

creased considerably during the lockdown period

compared to the corresponding period of last year

(Sangkham et al. 2021). Another study in China also

witnessed a sharp reduction in the concentrations of

air pollutants during the COVID-19 outbreak. In con-

trast to the same period in 2019 (from December 2018

to April 2019), the concentration of ambient air pol-

lutants decreased 9.31%, 14.49%, 11.54%, and

13.89% for PM

2.5

, SO

, NO

, and CO respectively.

However, PM

and O

concentrations increased

0.57% and 6.90% (Zhang et al. 2021).

4 STATISTICAL CORRELATION

BETWEEN COVID-19 CASES

AND AIR QUALITY

MEASUREMENTS IN

DIFFERENT REGIONS

Many studies have been investigating the long-term

(over one year) and short-term (less than one year)

relationships between the number of COVID-19 in-

fection cases and air quality with several models. For

example, a study of Italy summarized their data using

the number of confirmed cases against the detection

date and the correspondent PM

concentration values

(Bontempi 2020), and another study in China focused

on the percentage change of daily COVID-19 infec-

tors with a unit rise (10 μg/m

rise in PM

2.5

, PM

, NO

, O

and 1 mg/m

in CO) in pollutant con-

centration among six different pollutants (Zhu et al.

2020). Though different conclusions were also drawn

from these studies. Hence, this review is to compare

these differences and analyse the possible reasons for

proposing a new possible model for further studies.

4.1 Short Term Studies

An Italian study (from 10th February 2020 to 27th

March 2020) focused on the PM

concentration in

Lombardy cities, as well as some Piedmont cities,

though no overall relationship was found (Bontempi,

2020). This study compared the pattern of PM

con-

centration changes with the increase in COVID-19

confirmed cases about 20 days later. In some Lom-

bardy cities like Bergamo and Brescia, the high PM

concentration (over 50 μg/m

/day) from 22nd to 26th

of February, was corresponding to the increase in

COVID-19 cases on the 11th and 12th of March.

However, there were other cities, such as Pavia and

Cremona, that also experienced high concentrations

of PM

, but reported a limited number of infection

cases throughout the whole period. In some adjoining

piedmont cities that also experienced high levels of

pollution, no close relationship was found between

Associations between Air Quality and Covid-19 Infection

247

and COVID-19 cases. The lack of a direct con-

tribution owing to PM

acting as carriers for COVID-

19 spreading was suggested in this study. One possi-

ble reason was that COVID-19 cases remained unde-

tected for the investigated period, resulting in delayed

countermeasures (Bontempi 2020).

A short-term study in China witnessed a clear cor-

relation between the daily increase in COVID-19

cases from 23rd January 2020 to 29th February 2020,

and the concentration of six pollutants: PM

2.5

, PM

, NO

, CO, and O

. Except for SO

, the other five

pollutants all showed significant positive correlations

with reported COVID-19 infectors (Zhu et al. 2020).

A brief California study using the dataset from 4th

March 2020 to 24th April 2020 found that ambient air

pollutants were remarkably related to COVID-19

cases and mortality. PM

, PM

2.5

, SO

, CO, and NO

had significant associations with the total number of

cases and deaths for both Spearman and Kendall

models, with higher magnitudes resulted for PM

2.5

, SO

, and NO

using the Spearman model

(Bashir et al. 2020). The limitations of this study in-

clude not accounting for socio-economic indicators,

social distancing, and personal hygiene.

In another study for Saudi Arabia, the degrees of

air pollution for the three pollutants (PM

, NO

, and

) investigated from 9th March 2020 to 19th No-

vember 2020 were all positively related to the number

of daily COVID-19 infectors. Other meteorological

parameters like temperature and wind speed were also

investigated in the study, revealing a significant asso-

ciation with the daily number of COVID-19 infec-

tions (Ben Maatoug et al. 2021).

4.2 Long Term Studies

A study of Italy that analysed the average concentra-

tions of O

, NO

, PM

2.5

, and PM

for a long period

from 2016 to 2019 suggested a significant correlation

between a long-term, chronic exposure to air pollu-

tants and the enhanced spreading of the COVID-19

virus (Fattorini and Regoli 2020). However, this

study did not consider other crucial factors of

COVID-19 incidence and mortality, for example, age

structure, lifestyle factor, and the duration of the con-

finement.

A significant positive relationship between

COVID‐19 infections and the number of people ex-

posed to SO

, NO

, and PM

showed that pollution-

related morbidity induced the COVID‐19 infection

across Mumbai (Chattopadhyay and Shaw 2021).

This research suggested that Mumbai as a subtropical

city having high temperature and humidity probably

had not undergone the ill effect of PM

during the

COVID-19 situation. They also revealed a low-low

association between air pollution and COVID-19 in

the southern areas, which could be owing to a smaller

quantity of industries, the predominance of corporate

offices, defence areas, etc., and partially for its loca-

tion of facing the open sea in both west and east parts

where the wind could flow freely (Chattopadhyay and

Shaw 2021).

The long-term association between exposures to

common air pollutants and the COVID-19 case fatal-

ity rate (CFR) in China was investigated (Hou et al.

2021). The relationships between CFR and air quality

indicators (air quality score, AQI, and PM

2.5

concen-

tration) in the past 1,3, and 5 years were examined,

and the results showed that the CFR of COVID‐19

infectors rose for higher levels of long‐term AQI,

2.5

, and PM

. However, there was no statistically

significant association between the CFR and the lev-

els of SO

, NO

, and O

found (Hou et al. 2021). Lim-

itations of this study include those specific patient

comorbidities, ethnic characteristics, and social fac-

tors, such as access to care and pollution density, as

well as the relatively small sample size which may

affect the CFR for this population‐level study.

A study in the Netherlands focused on the period

2015-19 (Cole et al. 2020) found that PM

2.5

concen-

trations had a statistically significant positive correla-

tion with COVID-19 cases, hospital admissions, and

deaths. For NO

, a statistically significant positive as-

sociation was found between the number of COVID-

19 cases and deaths but was not associated with hos-

pital admissions. For SO

a trend of positive relation-

ship was also found with COVID-19, but not statisti-

cally significant. A further application of the Fisher

combination test suggested that both PM

2.5

and NO

significantly affect the overall COVID-19 outcomes,

but SO

did not. The results indicated that, with other

conditions under control, a district with 1 μg/m

extra

2.5

concentrations than another would on average

report 9.4 and 15.1 more COVID-19 infections, var-

ying from the model used. It would also result in from

2.9 to 4.4 more COVID-19 hospital admissions and

from 2.2 to 2.8 more COVID-19 deaths. In this study,

it was also found that average household income was

inversely related to COVID-19 infection, while the

average household size and the share of small housing

were both positively correlated with COVID-19

spreading.

ICHIH 2022 - International Conference on Health Big Data and Intelligent Healthcare

248

4.3 Combination of Both Short-term

and Long-term Models in One

Study

Both single-year and five-year average models at sub-

regional and individual levels were discussed in an

England study; the two models (subregional and indi-

vidual) have significantly different patterns

(Travaglio et al. 2021). In the individual model, PM

2.5

and PM

were the most significant contributors to the

higher incidence of COVID-19, with similar statistics

in both long-term and short-term studies. Nitrogen

oxides and dioxides were also positively related,

while ozone showed a lack of relevance with COVID-

19 infection. However, in the subregional study, only

nitrogen oxides and nitrogen dioxides had infectivity

rate ratios over 1 for both the single-year and multi-

year models. PM

2.5

, PM

, and O

were negatively re-

lated to the infectivity of COVID-19. It was proposed

that the inverse correlations between O

levels and the

number of COVID-19 cases and deaths may be be-

cause less nitrogen oxide converted to ozone in met-

ropolitan regions, a phenomenon that had been de-

clared in regions with heavy traffic. In addition, due

to the high reactivity of ozone, the negative associa-

tion between O

levels and COVID-19 cases is com-

patible with extended nitric oxide scavenging nearly

reaching levels of emissions.

Another study in China (Yao et al. 2021) focused

mainly on the correlation between NO

concentration

and spreading capability (basic reproductive number,

R0) of COVID-19 in 63 cities in China. R0 was pos-

itively related to the average NO

level from 2016 to

2019 with adjusted temperature and relative humid-

ity. Moreover, no significant relationships were found

between the other examined air pollutants (SO

, CO,

, PM

2.5

, and PM

) and R0. The study also investi-

gated the daily R0 values for 11 cities in Hubei (ex-

cept Wuhan) and normalized the data based on daily

R0 value in Wuhan to exterminate the influences by

other covariates. 11 Hubei cities (except Xianning

City) reported significantly positive association for

with R0, indicating a positive correlation be-

tween daily NO

concentration and COVID-19 diffu-

sion on the transient scale.

Table 1: Correlation between air pollutant particles and COVID-19 cases.

Coun-

try/Re-

gion

Short-

term/long-term

study

Pollutant(s) Type(s) of the model

used

Association with

COVID-19 infection

Refer-

ence

Italy

(Lom-

bardy and

Piedmont)

Short term

(from 10th Feb-

ruary 2020 to

27th March

2020)

Confirmed infection

cases against the detec-

tion day and corre-

sponding PM

concen-

tration values

No clear association (Bonte

mpi

2020)

China

(120 cit-

ies)

Short term

(from 23rd Jan-

uary 2020 to

29th February

2020)

2.5

, PM

, NO

, CO,

and O

Generalized additive

model, including both

single-pollutant model

and two-pollutant

model

Significant positive asso-

ciations with PM

2.5

, CO, NO

, and O

;

negative association with

(Zhu et

al.

2020)

California Short term

(from 4th

March 2020 to

24th April

2020)

VOC, Pb, PM

2.5

, SO

, CO,

and NO

Spearman and Kendall

correlation tests

Significant associations

with PM

, PM

2.5

, SO

CO, and NO

(Bashir

et al.

2020)

Saudi

Arabia

Short term

(from 9th

March 2020 to

19th November

2020)

, NO

, and

Poisson and binomial

negative models

Positive associations with

, NO

, and O

(Ben

Maatou

g et al.

2021)

Italy Long term

(from 2016 to

2019)

, NO

, PM

2.5

and PM

Average concentrations

of NO

, PM

2.5

, and

and number of

days exceeding the con-

trolled limits (averages

of the last 3 years) for

Significant associations

with O

, NO

, PM

2.5

, and

(Fattori

ni and

Regoli

2020)

Associations between Air Quality and Covid-19 Infection

249

and PM

versus the

number of COVID-19

confirmed cases

Mumbai Long term

(from 2017 to

2019)

, NO

, and

Ordinary Least Square

model, spatial lag

model, spatial error

model, and spatially ad-

justed regression model

Significant positives as-

sociation with SO

, NO

and PM

(Chatto

padhyay

and

Shaw

2021)

China Long term

(from 2015 to

2020)

2.5

, PM

, NO

, and

Shapiro–Wilk test,

Pearson correlation, and

Spearman test

Positive associations with

2.5

and PM

; no sig-

nificant associations with

, NO

, and O

(Hou et

al.

2021)

Nether-

lands (355

munici-

palities)

Long term

(from 2015 to

2019)

2.5

, NO

, and

Fisher combination test,

negative binomial count

model, Operational Pri-

ority Substances disper-

sion model, spatial

econometric models

Significant positive asso-

ciations with PM

2.5

and

; not significant posi-

tive association with SO

(Cole et

al.

2020)

England Both short term

(2018) and long

term (from

2014 to 2018)

2.5

, PM

NO, NO

, and

Negative binomial re-

gression model, bino-

mial regression model,

including both subre-

gional and individual

models

Individual model: posi-

tive associations with

2.5

, PM

, NO, and

; lack of association

with O

Subregional model: posi-

tive associations with NO

and NO

; negative associ-

ations with PM

2.5

, PM

and O

(Travagl

io et al.

2021)

China Both short term

(from 1st Janu-

ary 2020 to 8th

February 2020)

and long term

(from 2016 to

2019)

, PM

2.5

, SO

, CO,

and O

Linear regression

model

Significant positive asso-

ciation with NO

; no sig-

nificant associations with

2.5

, PM

, SO

, CO,

and O

(Yao et

al.

2021)

4.4 General Trends in the 10 Selected

Studies

Table 1 represents the correlation between air pollu-

tant particles and COVID-19 infectivity. From the 10

studies, PM

2.5

, PM

, and NO

showed a significant

positive correlation with COVID-19 cases in both

long and short terms. It was, therefore suggested that

concentrations of pollutants like NO

should be mon-

itored, especially in urban areas (Bashir et al. 2020).

Moreover, colder regions of the world should adopt

stricter measures (Iqbal et al. 2021). Similarly, the

significance of PM

2.5

and PM

suggested that reduc-

ing air pollutants could be a useful way to control

COVID-19 infection (Zhu et al. 2020), and the adop-

tion of green environmental policies should be further

promoted (Bashir et al. 2020). In addition, the burning

of fossil fuels is the main source of NO

emissions.

Therefore, variations in NO

levels can be applied to

show alternations in human activity and population

movement due to the COVID-19 lockdown (Yao et

al. 2021). SO

was under debate. For the association

discussed in 6 of the studies, three of them indicated

a lack of significance with COVID-19 infection (Hou

et al. 2021, Yao et al. 2021, Cole et al. 2020), two of

them found significant association (Bashir et al. 2020,

Chattopadhyay and Shaw 2021), while one study

showed a negative association with COVID-19 cases

(Zhu et al. 2020). Similar trends can be found with

, which showed significant association (Zhu et al.,

2020, Ben Maatoug et al. 2021), no significant rele-

vance (Hou et al. 2021, Yao et al. 2021, Travaglio et

al. 2021), or negative association, which may be due

to less nitrogen oxide converting to ozone in urban

areas (Travaglio et al. 2021). Hence, more laboratory

ICHIH 2022 - International Conference on Health Big Data and Intelligent Healthcare

250

research needs to be carried out to clarify the under-

lying mechanism (Zhu et al. 2020). CO has not been

frequently discussed in these studies and the potential

associations remain unclear.

5 CURRENT EFFORTS IN

CONTROLLING COVID-19

AND FUTURE EXPECTATIONS

Along with the research about the possible ways of

COVID-19 spreading and infection, efforts have been

done for the prevention and treatment of COVID-19.

Preventions involve the use of personal protective

equipment including masks, gloves, and googles (Qu

et al. 2021). Vaccines have also been applied widely.

As of 5th September 2021, a total of 5,352,927,296

vaccine doses have been administered as reported to

WHO (Geneva: World Health Organization 2020).

Studies are working on developing antiviral therapeu-

tics. A recent study focusing on the nsp14 MTase ac-

tivity suggested that development in this field would

be viable for the COVID-19 pandemic treatment

(Devkota et al. 2021). Another research targeting the

SARS-CoV-2 Nsp13 Helicase also drew the same

conclusion that potential inhibitor compounds could

be identified and applied (White et al. 2020). On the

other hand, it was proposed that the COVID-19 epi-

demic could not only be resolved through medicinal

analysis and experiment, but also be promoted

through environment-related sustainable research

(Iqbal et al. 2021). Future research could involve a

more in-depth study of characterization of SARS-

CoV-2 virion’s sorption onto atmospheric particulate

matter (Duval et al. 2021) and thus find methods to

alleviate the spreading of COVID-19 virus through

air pollution.

6 CONCLUSIONS

An increasing amount of data are available to illus-

trate the correlation between COVID-19 infectivity

and exposure to air pollutants. This review summa-

rized the results of multiple studies, including infor-

mation about country/region, length of data collected,

pollutants, type(s) of the model used, and associations

between the pollutants and COVID-19 infection, as

shown in Table 1. In the selected research, PM

2.5

, and NO

were found to have the most signifi-

cant positive association with COVID-19 confirmed

cases. Different perspectives were oriented for SO

and O

among different studies, while CO was not fre-

quently discussed in these studies. COVID-19 lock-

down also showed significant association with the air

quality changes in the same period. These statistics

also suggested a possible mechanism of PM facilitat-

ing the spreading of SARS-CoV-2. Studies have

found that PM would lead to COVID-19 infection by

introducing inflammation and thus increasing the ac-

tivity of the ACE2 receptor, the binding site of SARS-

CoV-2. PM in water surrounding can also bind with

the coronavirus, forming the SARS-CoV-2-PM com-

plex, which could serve as carriers of the COVID-19

virus or disturb synaptic vesicle recycling if entering

the brain. Further research in this area may involve

more complex models and focus on the multifaceted

conditions including weather, age groups, income

level, population density, etc.

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