Introduction {#Sec1}
============

COVID-19 infected cases were first reported in the last December in Wuhan, China (Gautam [@CR11]; Huang et al. [@CR14]; Tomar and Gupta [@CR31]). It was a third outbreak of coronavirus after the severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS). A public health emergency was declared by the World Health Organization (WHO) on January 30, 2020 keeping in view the international concern. (Bashir et al. [@CR5]; WHO [@CR35]). Initially, different case studies reported that COVID-19 had shallow fatality rate (2.3%) (Shi et al. [@CR30]; She et al. [@CR29]) as compared to MERS (34.4%) and SARS (9.2%) (Wu et al. [@CR36]; Ceccarelli et al. [@CR9]). Nevertheless, a research study found that the number of COVID-19 patients doubled every 6.4 days, identifying that COVID-19 was a much more dangerous and infectious disease than expected (Wu et al. [@CR36]).

The COVID-19 was reported to have reached the [US](https://en.wikipedia.org/wiki/United_States)A in early January 2020. In the USA, the first confirmed COVID-19 case of [local transmission](https://en.wikipedia.org/wiki/Local_transmission) was found on January 15, 2020, in Washington state (Bashir et al. [@CR6]; Ghinai et al. [@CR12]), and COVID-19 spread quickly throughout the country. California, Florida, Louisiana, North Carolina and Alabama states were the some of most infected states with the maximum number of cases and deaths in the USA. As of July 15, 2020, the total number of cases and deaths in California, Florida, Louisiana, North Carolina and Alabama states were 329,162 (7086), 282,435 (7277), 79,827 (3315), 87,528 (1510) and 55,545 (1124), respectively. On the other hand, the current situation in China may be different as the number of new cases and the death toll dropped significantly due to lockdown measurements (Bao and Zhang [@CR4]). [China](https://www.theguardian.com/world/china) has reported zero new cases for the first time since January on April 15, 2020.

Human health was significantly affected by air pollution. Globally, according to the State of Global Air Report 2019, air pollution approximately killed 5 million people in 2017, and the USA and China ranked among the top 10 countries with the maximum mortality rate (Health Effects Institute (HEI), <https://www.healtheffects.org/>). In addition to human-to-human transmission, environmental parameters play an important role in terms of transmission, distribution viability, the timing of infections and range of viruses spread (Anser et al. [@CR3]; Lemaitre et al. [@CR17]; Şahin [@CR25]; Shi et al. [@CR30]; van Doremalen et al. [@CR32]; Zhu et al. [@CR40]).

The majority of the world population faced lockdown during these hard times. By this nationwide COVID-19 lockdown, transport, as well as industrial activities, significantly reduced. Besides the possible side effects of this unprecedented lockdown, environmental pollution drastically decreased in many countries. In India, as a result of lockdown, the air pollution in 88 cities across the country dramatically reduced down only after four days of commencing lockdown (Mahato et al. [@CR19]; Sharma et al. [@CR28]). European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) pollution monitoring satellites have identified significant reductions in NO~2~ emissions over Italy during the lockdown period (ESA [@CR10]; Muhammad et al. [@CR20]; NASA [@CR21]). Similarly, the IESM (Institute of Environmental Science and Meteorology) reported that the emissions of PM~10~ and PM~2.5~ were reduced due to decreased industrial activities as a result of lockdown measurements. Additionally, Finland's center for research on energy and clean air studied and accounted that almost 25% of CO~2~ emissions reduced due to factory closures and travel restrictions in China (Carbon Brief [@CR8]).

Since COVID-19 is an acute respiratory disease and could remain feasible in aerosols for hours (van Doremalen et al. [@CR33]), the main objectives of this study are to investigate the effect of reduced human activities and lockdown on environmental indicators and changes in air quality in the USA and China, and to examine the correlation between COVID-19 spread and the environmental pollutants in those respective states and provinces. Data about the various air pollutants such as CO, NO~2~, SO~2~, PM~2.5~ and PM~10~ was used (Abdul-Wahab et al. [@CR1]).

Methods {#Sec2}
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According to our objectives, California, Florida, Louisiana, North Carolina, and Alabama were selected from the USA. While Hubei, Beijing, Shanghai, Guangdong, and Zhejiang were chosen from China, these provinces were considered as the industrial hubs in China and they were also among the worst hit by COVID-19 (Kucharski et al. [@CR16]; Leung et al. [@CR18]).

To perform the comparison study between pollutants in the first quarter of 2019 and 2020, data was collected between January 1 and April 30 of 2019 and 2020 from an online platform of the Environmental Protection Agency (EPA) (<https://www.epa.gov/>) and the MEE (<http://datacenter.mee.gov.cn/>) websites for the USA and China, respectively. In this study, daily 24-h concentrations of pollutants such as carbon monoxide (CO), nitrogen dioxide (NO~2~), sulfur dioxide (SO~2~), PM~2.5~ and PM~10~ were measured. For the USA, concentrations were taken between March 19, 2019 to April 30, 2019, and March 19, 2020 to April 30, 2020 (this was the lockdown time in the USA). While for China, environmental indicators concentrations were taken between Jan 23, 2019 to March 29, 2019, and Jan 23, 2020 to March 29, 2020 (this was the lockdown time in China).

The data of confirmed COVID-19 cases and deaths of the USA were retrieved from the official website of the Centers for Disease Control (CDC) (<https://www.cdc.gov/>). While for China, data on COVID-19, including the number of confirmed cases and deaths, were extracted from the China National Health Commission website (CNHC, <http://www.nhc.gov.cn/>). To find the association between COVID-19 and environmental pollutants, COVID-19 data between January 18, 2020 to March 25, 2020, for China and March 1, 2020 to April 30, 2020, for the USA was used. As the data was not normally distributed, therefore, Spearman and Kendall rank correlation tests were used to determine the correlation between variables.

Results and discussion {#Sec3}
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Changes in air quality and environmental pollutants {#Sec4}
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Data in Table [1](#Tab1){ref-type="table"} shows the reduction percentage of daily concentration of environmental pollutants in the first quarter of 2019 and 2020 in the five states/provinces of the USA and China.Table 1Percentage of reduction of the environmental pollutants (average concentration) in the first quarter of 2019 and 2020 among the significantly hit states of the USA and China (*NA*= not available)PollutantReduction %Reduction %*CaliforniaHubei*CO (ppm)NA11.02NO~2~ (ppb)44.2249.21SO~2~ (ppb)88.79.33PM~2.5~ (ug/m^3^)27.6716.20PM~10~ (ug/m^3^)19.8631.0*FloridaBeijing*CO (ppm)4.7011.02NO~2~ (ppb)35.4125.64SO~2~ (ppb)73.3342.64PM~2.5~ (ug/m^3^)33.726.48PM~10~ (ug/m^3^)32.2979.07*LouisianaShanghai*CO (ppm)33.3318.21NO~2~ (ppb)61.1643.78SO~2~ (ppb)82.2631.19PM~2.5~ (ug/m^3^)10.8326.60PM~10~ (ug/m^3^)− 61.6429.14*North CarolinaGuangdong*CO (ppm)12.5925.69NO~2~ (ppb)29.2432.38SO~2~ (ppb)− 39.89− 10.32PM~2.5~ (ug/m^3^)29.2119.82PM~10~ (ug/m^3^)35.1726.41*AlabamaZhejiang*CO (ppm)NA66.83NO~2~ (ppb)NA43.89SO~2~ (ppb)88.7018.96PM~2.5~ (ug/m^3^)30.7119.78PM~10~ (ug/m^3^)NA23.62

Figure [1](#Fig1){ref-type="fig"} shows the concentrations with and without lockdown in the studied states of the USA. In California, the concentrations of all five pollutants significantly decreased during the lockdown period than the previous year. The maximum reduction (23.1%) in the concentration was observed in NO~2~. Moreover, 19.6% and 17.7% reductions were detected in PM~10~ and PM~2.5~, respectively. In Florida, a higher reduction was observed in NO~2~ concentration (21.1%), and almost similar reductions were reported in both CO and SO~2~ concentrations. Moreover, in the PM~2.5~ and PM~10~ concentration, 32.29% and 33.72% reduction was observed. In Louisiana, the concentrations of CO, NO~2~, SO~2~ and PM~2.5~ were decreased with 36.3%. 59.8%, 8.28% and 22.2%, respectively. While PM~10~ had a 24.5% increase as compared with the previous year. The increase in the concentration of PM~10~ might be due to anthropogenic sources (Klimont et al. [@CR15]). In North Carolina, significant reductions were seen in all environmental pollutants except for SO~2~. The maximum reduction was observed in PM~2.5~ (30.8%) than other pollutants. On the other hand, PM~2.5~ significantly increased up to 23.8% in Alabama state.Fig. 1Changes in the concentrations of environmental pollutants with and without lockdown condition in the five states of the USA. In some sub-figures, data about a few states is missing; we were not able to find the data of particular pollutants in those states (Lous is Louisiana; NCarolina is North Carolina and Albm is Alabama)

As we all know, China was the first country that reported COVID-19 patients in the Wuhan seafood market (Nishiura et al. [@CR22]). As of January 19, 2020, the Chinese authorities declared a public health emergency, and then Wuhan underwent a complete lockdown. Environmental pollutants were significantly affected by lockdown measurements. Overall, an apparent reduction can be seen in the first quarter of 2020 as compared with 2019. Figure [2](#Fig2){ref-type="fig"} represents the comparisons of the average concentrations of environmental pollutants in the first quarter of 2019 and 2020 among the different provinces of China.Fig. 2Changes in the concentrations of environmental pollutants with and without lockdown condition in the five provinces of China (Gdong is Guangdong)

In China, in all five provinces, the environmental pollutants significantly decreased during the lockdown period as compared to a similar period of 2020. In Hubei, the reduction concentrations were 11.02%, 49.21%, 9.33%, 16.20% and 31% for CO, NO~2~, SO~2~, PM~2.5~ and PM~10~ respectively (Fig. [2](#Fig2){ref-type="fig"}). Beijing is the capital of China, with 21.54 million populations and air pollution significantly affected the community in this city. During this pandemic period, air pollution significantly decreased as compared with the previous year. The concentrations of PM~2.5~ in Beijing, Shanghai, Guangdong and Zhejiang decreased by 6.48%, 26.6%, 19.82% and 19.78%, respectively, while PM~10~ decreased by 79.07%, 29.14%, 26.41% and 23.62%, respectively. In Shanghai, the reductions in the concentrations of CO, NO~2~ and SO~2~ were 18.21%, 43.73% and 31.19%, respectively. Similar conclusions can be derived from Guangdong and Zhejiang provinces.

Globally, air pollution dramatically decreased due to unprecedented lockdown (Bao and Zhang [@CR4]). According to our results, significant concentrations of pollutants were reduced in the first quarter year of 2020 as compared with 2019 (Figs. [1](#Fig1){ref-type="fig"} and [2](#Fig2){ref-type="fig"}). Our results were similar to recent research studies (Bao and Zhang [@CR4]; Sharma et al. [@CR28]). In Italy, NO~2~ concentrations were decreased during the lockdown period (Reuters [@CR24]). According to Sharma et al. ([@CR28]), concentrations of PM~10~, PM~2.5~ and NO~2~ were reduced in north India, clearly showing the positive effect of lockdown on air quality measurements. During the COVID-19 pandemic, almost every country closed its industrial as well as commercial activities to stop the spread of the COVID-19. This might be the main reason for the reduction of environmental pollutants. Wang et al. ([@CR34]) found that the concentration of environmental pollutants, especially PM~2.5~, significantly decreased due to the suspension of industry and transportation in China.

Correlation coefficient analysis was used to reveal the interaction between pollutants (first quarter of 2020) of states and provinces of the USA and China, respectively (Fig. [3](#Fig3){ref-type="fig"}). In the USA, all five environmental pollutants showed strong associations with states except SO~2~ (Fig. [3a](#Fig3){ref-type="fig"}). However, in China, CO, SO~2~, PM~2.5~ and PM10 had shown a positive correlation with each other, but a negative correlation was observed in NO~2~ (Fig. [3b](#Fig3){ref-type="fig"}).Fig. 3Correlation between environmental pollutants in (**a**) the USA and (**b**) China in the first quarter of 2020

Association between COVID-19 and environmental pollutants {#Sec5}
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In the USA, the number of confirmed COVID-19 cases and deaths increases rapidly than China. As of June 15, 2020, a total of 3,296,599 confirmed cases with 134,884 deaths had been reported by the Centers for Disease Control (CDC) (<https://www.cdc.gov/>) in the USA. It might be possible that environmental pollutants play an important role in the transmission of COVID-19 disease. Table [2](#Tab2){ref-type="table"} shows the empirical results of the association between COVID-19 (cases and deaths) and environmental pollutants across all the study states and provinces of the USA and China, respectively.Table 2The correlation coefficient between COVID-19, confirmed cases and deaths across all the study states and provinces of the USA and China, respectivelyUSAChinaPollutantsCasesMortalityCasesMortalitySpearman correlation coefficientCO− 0.024− 0.0440.186− 0.053NO~2~− 0.067\*− 0.139\*\*− 0.516\*\*\*− 0.397\*\*\*SO~2~0.0180.115− 0.161− 0.088PM~2.5~− 0.392\*− 0.263\*− 0.081\*\*− 0.166\*PM~10~0.086\*0.356\*\*\*− 0.529\*\*\*− 0.507\*\*\*Kendall correlation coefficientCO− 0.015− 0.0240.153− 0.034NO~2~− 0.042− 0.095− 0.353\*\*\*− 0.273\*\*\*SO~2~0.0130.077− 0.112− 0.533PM~2.5~− 0.279\*− 0.184\*− 0.049\*\*− 0.112\*PM~10~0.053\*0.233\*\*\*− 0.362\*\*\*− 0.360\*\*\*

Statistical significance at the \**P* \< 0.05; \*\**P* \< 0.01; \*\*\**P* \< 0.001

Our findings show that COVID-19 cases and deaths are significantly correlated with environmental pollutants in both the USA and China. In the USA, we observed significant positive associations of NO~2~, PM~2.5~ and PM~10~ with COVID-19 confirmed cases and deaths in Spearman correlation. While in the Kendall correlation coefficient, we found that PM~2.5~ and PM~10~ had a significant correlation with COVID-19 cases and mortality. Moreover, PM~10~ showed a strong association with mortality rates in both Spearman and Kendall correlations. In China, statistical analysis showed that NO~2~, PM~2.5~ and PM~10~ had a significantly positive correlation with COVID-19 cases and deaths in both Spearman and Kendall correlations (Table [2](#Tab2){ref-type="table"}).

After continuous scientific research, clear shreds of evidence are showed that human health was significantly affected by air pollution, particularly in urban areas. Bashir et al. ([@CR5]) studied and analyzed that CO, PM~2.5~, PM~10~ and SO~2~ were positively associated with COVID-19 cases and deaths in the California state. Xiao et al. ([@CR37]) also found a strong correlation between environmental pollutants and COVID-19. He also proposed that only 1 μg m^−3^ increase in the concentration of PM~2.5~ can increase up to 15% in the fatality rate. A study from Thailand showed that CO, PM~10~, NO~2~, O~3~ and SO~2~ significantly increased the risk of respiratory diseases (Phosri et al. [@CR23]). Yao et al. ([@CR38]) also analyzed the spatial correlation of PM~2.5~ and PM~10~ and the COVID-19 casualty rate by using multiple regression methods in China and found that PM~2.5~ and PM~10~ with higher concentration had a positive association with COVID-19 deaths. Zhao et al. ([@CR39]) studied and showed that highly pathogenic avian influenza (HPAI) virus was carried by fine particulate matter (PM~2.5~) in Iowa state, from infected places both within a state and neighboring states. On March 16, 2020, Setti et al. ([@CR26]) published a study and found that an airborne route was a possible additional factor for interpreting the anomalous COVID-19 outbreaks notified in Northern Italy, known to be one of the European areas characterized by highest PM concentration. Another research study showed that a higher concentration of PM~10~ (\> 50 μg m^−3^) results in a spread acceleration of COVID-19, suggesting a "boost effect" for the viral infection (Setti et al. [@CR27]). Additionally, the other researchers showed that pollution caused by PM~10~ affects the prognosis of COVID-19 patients (Bashir et al. [@CR5]). On the other hand, Bernardini et al. ([@CR7]) studied the association between environmental pollutants (CO, NO~2~, O~3~, and PM) and COVID-19 in Italy and found a significant positive correlation between them. Likewise, other researchers such as Adach et al. ([@CR2]), Ha ([@CR13]), and Zhu et al. ([@CR40]) also observed similar findings. This evidence supports our study and suggests that COVID-19 might spread through environmental pollutants.

This study may have some limitations. Firstly, we studied the association between COVID-19 infection and environmental pollutants, but our findings were not globally representative as we only included five states and five provinces of the USA and China, respectively. Secondly, in this study, we could not examine the impact of all elements of lockdown measurements (smart lockdown or complete lockdown) due to the lack of data availability. Thirdly, this study did also not include age or gender-specific COVID-19 confirmed cases and deaths; therefore, we could not perform subgroup analyses. Future studies should address these limitations.

Conclusions {#Sec6}
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The study includes the comparison release of environmental pollutants (CO, NO~2~, SO~2~, PM~2.5~ and PM~10~) in the first quarter of 2019 and 2020 with a lockdown period of five states of the USA and five provinces of China. The results suggest that restricted human activities during the lockdown period have significantly reduced the concentrations of environmental pollutants in both countries. Among selected pollutants, NO~2~, PM~2.5~ and PM~10~ were observed significantly correlated with COVID-19 disease. The study helps to understand the implication of restricted anthropogenic activities in the reduction of environmental pollutants and to speculate the execution of some meticulous measures to improve the air quality.

Electronic supplementary material
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 {#Sec7}

ESM 1(DOCX 23 kb).

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The authors declare that they have no conflict of interest.
