The Relationship between Environmental Quality, Sustainable Health, and the Coronavirus Pandemic in European Countries

Abstract

The emission of air pollutants weakens the body’s immune system and can increase the prevalence of coronaviruses. This study examined the effects of six environmental pollutant gases, including Carbon Dioxide (CO2), Methane (CH4), Nitrous Oxide (N2O), Hydrofluorocarbons (HFC), Perfluorocarbons (PFC), and Sulphur Hexafluoride (SF6), on the prevalence of coronaviruses (i.e., coronavirus cases, total deaths, and active cases) in 30 European countries. Due to the benefits of ridge regression, this method was used to investigate the effects of those environmental pollutants on coronavirus cases. The results showed that all six gases had a positive effect on active coronavirus cases in European countries. This study concludes that industrialized European countries could focus on reducing environmental pollutants to decrease the effects of future pandemics.

1. Introduction

Environmental pollution can have adverse effects on human health and increase the chance of disease spreading. Air pollution represents one of the greatest environmental risks to human health today [1]. Air pollution has been linked to diverse unfavorable health outcomes, including respiratory and cardiovascular diseases [2,3,4]. Air pollutants are composed of a complicated aggregate of substances that have well-characterized adverse effects on human health [5]. Exposure to pollutants, including airborne particulate matter and ozone, has been associated with increases in mortality and hospital admissions due to respiratory and cardiovascular diseases [4]. Environmental pollution weakens the body’s immune system and spreads various diseases (Figure 1). The health effects of air pollution have been subject to intense study in recent years. Many studies have examined the effects of environmental pollution on weakening the body’s immune system [5,6,7].

Environmental pollution can increase the incidence of various diseases, including the weakening of the immune system [6], cancer [8], asthma [9], pneumonia [10], influenza [11], respiratory infections [12], and diabetes [13]. Many researchers have looked at the link between environmental pollution and coronavirus cases, and the results show that there is a significant link [14,15,16,17,18]. As shown in Figure 1, environmental pollution can increase the rate of transmission of infectious diseases by affecting humans and increasing the number of patients. Hence, environmental pollution can be considered one of the causes of coronavirus cases. The study of environmental pollution in different countries could show the reason for the difference in coronavirus cases in different countries.

COVID-19 is the disease caused by the recently discovered SARS-CoV-2, the coronavirus that was first identified in December 2019 in Wuhan [19]. The number of COVID-19 cases started to increase worldwide, and the governments of many countries started implementing measures that limited the number of people gathering together in public places [20]. COVID-19 showed a remarkable effect, resulting in massive plane emission savings [21]. Most global studies also reported a significant reduction in pollutants throughout the COVID-19 lockdown duration [22]. The proliferation of COVID-19 and the subsequent restrictive measures and lockdowns caused a brief period of improved environmental quality, specifically air quality, due to an extensive reduction in the emissions of GHGs into the atmosphere [23,24].

Data is a key resource in the development of various fields of science and is helpful in this study [25]. In 2020, worldwide GHG emissions dropped by 7% for the first time [26,27,28]. Several of the articles presented within the literature discuss the effective influences of the COVID-19 lockdown, including lowering air pollution (PM2.5, PM10, PM, NO2, O3, CO, and SO2) globally [29,30]. In successive months during the COVID-19 pandemic, the CO2 emissions varied, and the dimensions of modifications were clearly associated with the increase in infections and ailment cases [31]. Other than being infected with the COVID-19 disorder, exposure to air pollution can have an effect on different organs in people [32], including the respiratory, nervous, urinary, and digestive structures, amongst others [33].

CO2 emissions are a commonplace ecological variable that is related to climate change. During the COVID-19 pandemic, several studies have been carried out regarding the role of harmful fuel within the pandemic. For example, ozone, nitrogen dioxide, carbon monoxide, formaldehyde, and PM 2.5 were reported to be associated with higher COVID-19 infection or fatality rates [34,35,36]. Therefore, considering the importance of the issue, this article examined the relationship between environmental quality, sustainable health, and the coronavirus epidemic in European countries.

Thus, the objectives of this study are: (1) to examine the relationship between the six environmental pollutant gases and coronavirus cases. (2) To test the relationship between the six environmental pollutant gases and the active cases of coronavirus. (3) To investigate the relationship between the six environmental pollutants and total deaths. Considering the above, studying the prevalence of coronaviruses and the factors affecting their prevalence in European countries can provide important lessons about controlling the emission of environmental pollutants during a pandemic.

This paper includes the following six sections: Section 2 examines the lecture review. In Section 3, the Materials and Methods used in this paper are described. Section 4 shows the experimental results and statistical tables. In Section 5, the findings are discussed. Section 6 presents the conclusions and implications.

2. Literature Review

There have been many studies on the effects of environmental pollution on people of all ages, from childhood to old age. In recent years, new research has evaluated associations between environmental pollution and infant health. These evaluations offer a huge precis of this literature, comparing the state of epidemiological evidence for the outcomes of an extensive variety of environmental contaminants (air pollutants, heavy metals, organochlorine compounds, fluoroalkyl substances, polybrominated diphenyl ethers, pesticides, phthalates, and bisphenol A) on infant fitness outcomes [37]. Pneumonia, a leading cause of childhood mortality, is associated with household air pollution (HAP) exposure [38].

Within the last 15 years, the effect of air pollutants on cognitive impairment in the elderly has become a lively area of epidemiological study, and several studies have provided helpful evidence [2]. Ambient PM2.5 can also raise the threat of mortality from PC, especially in older populations. Pollution control policies can be bolstered to reduce health damage [39].

Air pollution represents one of the main reasons for extended inflammation, subsequently leading to innate immune system hyper-activation [40]. Air pollution can affect many parts of the human body. The health effects of air pollutants have attracted lots of interest. Exposure to air pollution such as particulate matter (PM) has been linked to lung and cardiovascular disorders and increases both hospital admissions and mortality [5]. There are also important effects of air pollutants on the gut. Many infectious and contagious diseases can be transmitted from human to human by water, food, etc. Air pollutants can contaminate meals and water that are then input into the human meal supply chain and ingested by humans [5,39].

Sustained human-to-human transmission of the novel coronavirus SARS-CoV-2, the etiologic agent of COVID-19, has been documented across the world, with COVID-19 declared a global pandemic affecting 198 countries as of 26 March 2020 [41]. SARS-CoV-2 is the pathogenic agent of COVID-19, a disease first reported in a small cluster in Wuhan, Hubei Province, China, in December 2019 and soon spreading all over the world. because of its high contagiousness, and it was declared a public health emergency of global concern by the World Health Organization (WHO). The course of the ailment is frequently mild and undistinguishable from common flu, but in a full-size range of cases, it may additionally require hospitalization, eventually leading to ARDS and death [40].

A report from the WHO maintains that short-distance droplet transmission is the main transmission route of Severe Acute Respiratory Syndrome (SARS) [42]. While contagious individual coughs or sneezes, sputum droplets containing infectious particles (SARS-CoV) are launched. On average, droplets are approximately three microns in diameter and, while inhaled, the protective mechanisms of the top breathing tract prevent infection. Droplets of 3 microns in length can live in the air for 3 hours. [43]. The wind is an important environmental parameter with respect to the suspending time of droplets in the air. Inside the outside surroundings, high wind velocity enables the dilution and elimination of the droplets and shortens their suspending time inside the air, reducing their transmission capability [44].

Environmental pollution has the most significant effect on the lungs, and the coronavirus also attacks the lungs. There is strong evidence to support a link between air pollution and respiratory infections like pneumonia [38,45,46,47,48]. As Figure 2 shows, as environmental pollutants increase the number of diseases: weakening of the immune system [49], cancer [50], asthma [51], pneumonia [16], influenza [17], respiratory infection [52], and diabetes [53], cases and deaths due to coronavirus will increase.

3. Materials and Methods

3.1. Variables and Data Source

In this section, first, the variables and data sources related to environmental pollutants and then the variables of coronavirus cases are described.

3.1.1. Environmental Pollutant Gases in the European Countries

The number of patients and deaths from the coronavirus increased every day. Researchers were looking for the causes of the spread of the disease and the reasons for its different distribution in different countries and regions. This study shows that the emission of air pollutants in different regions, by weakening the body’s immune system, could be the cause of an increase in the prevalence of coronaviruses.

In this study, the most important air pollutants considered, including greenhouse gases, were the most dangerous gases for air pollution. This group of gases consists of Carbon dioxide (CO2), Methane (CH4), Nitrous oxide (N2O), Hydrofluorocarbons (HFC), Perfluorocarbons (PFC), and Sulphur hexafluoride (SF6). Data on these pollutant gases were collected from the Organization for Economic Co-operation and Development (OECD.org) (accessed in Figure 3), which shows the characteristics of six environmental pollutants in 30 European countries. As shown in Figure 3, the emissions of CO2, CH4, N2O, and HFC gases were higher but less scattered, and the emissions of PFC and SF6 gases had the lowest values but the highest scatter. Among all environmental pollutants, CO2 is the most widely distributed in European countries.

3.1.2. Coronavirus Cases in the European Countries

COVID-19 was first reported on 31 December 2019, in Wuhan, China. This disease was first observed in China and then quickly spread to all countries in the world [98]. Total cases (TC), total deaths (TD), and total active (TA) cases of coronavirus in European countries are shown in Figure 3.

As it turns out, coronavirus cases were highly prevalent in European countries. The reason for the difference between coronavirus cases in European countries can help explain and control the virus. Data on coronavirus cases, total deaths, and active cases for 30 European countries were collected from worldometers.info (accessed on 31 December 2022).

3.2. Statistical Methods

Regression is a good way to examine the effect of independent variables on a dependent variable. Regression seeks to find a line that is the shortest distance from the available points. Regression is designed to minimize the distance between observed values ($y_i$) and predicted values (${\widehat{y}}_i$). According to [99], a simple regression model can be shown as follows:

$$y_i={\widehat{y}}_i(\omega ,x_i)+e_i$$

(1)

$${\widehat{y}}_i(\omega ,x_i)={\omega }_0+{\omega }_1{x}_{i1}+\dots +{\omega }_n{x}_{in}$$

(2)

where $y={\left[y_1,y_2,\dots ,y_m\right]}^T$ and $\widehat{y}={\left[{\widehat{y}}_1,{\widehat{y}}_2,\dots ,{\widehat{y}}_m\right]}^T$ are the vectors of the observed and predicted values of the dependent variable. The vector of $x={\left[x_{i1},x_{i2},\dots ,x_{in}\right]}^T$ is the vector of independent variables, and the vector of $\omega ={\left[{\omega }_1,{\omega }_2,\dots ,{\omega }_n\right]}^T$ is its coefficients. The OLS method is based on minimizing the sum of squared error:

$$f(\omega )={\displaystyle \sum _{i=1}^m{(y_i-x_i^T\omega )}^2}$$

(3)

Ridge regression adds a penalty term $\lambda {\displaystyle \sum {\omega }_i{}^2}$, and the cost function for ridge regression can be written as [99]:

$$f(\omega )={\displaystyle \sum _{i=1}^m{(y_i-x_i^T\omega )}^2}+\lambda {\displaystyle \sum _{i=1}^n{\omega }_i{}^2}$$

(4)

The amount of lambda in the above equation is very important because it controls the amount of shrinkage. By solving the above equation, the coefficients of the regression model can be obtained. These coefficients are obtained by the following relations using ridge regression:

$$\frac{\partial f(\omega )}{\partial \omega }=-2x^T(y-x\omega )+2\lambda \omega =0$$

(5)

$$\omega ={(x^{T}x+\lambda I)}^{-1}{x}^{T}y$$

(6)

Due to the objective function in ridge regression, the vectors can be rewritten as follows:

$$\omega =\omega -\alpha \frac{\partial f(\omega )}{\partial \omega }=\omega +2\alpha \left[x^T(y-x\omega )-\lambda \omega \right]$$

(7)

Figure 4 clearly shows the difference between the coefficients obtained from the two methods of OLS regression and ridge regression.

Due to the benefits of ridge regression, this method was used to investigate the effects of environmental pollution on coronavirus cases.

4. Results

As mentioned earlier, the effect of the six greenhouse gases on coronavirus cases was estimated in the form of three models for coronavirus cases, total deaths, and active cases. The results of estimating the effect of greenhouse gas emissions on cases of coronavirus in European countries are given in

Table 1. Effect of six environmental pollutant gases on coronavirus cases.

Lambda	6.582			(+1 SE):38.55			(+2 SE):67.36
	Coef	Std	t-Stat	Coef	Std	t-Stat	Coef	Std	t-Stat
C	−0.579	0.1774	−3.263	0.701	0.2198	3.189	1.247	0.4147	3.007
CO2	0.164	0.0513	3.199	0.084	0.0239	3.521	0.065	0.0196	3.32
CH4	0.091	0.013	7.002	0.074	0.0079	9.347	0.06	0.0062	9.652
N2O	0.069	0.002	34.023	0.073	0.0019	37.881	0.061	0.0015	39.74
HFC	0.09	0.0034	26.609	0.067	0.0025	27.146	0.056	0.002	27.89
PFC	0.114	0.0265	4.305	0.136	0.0184	7.379	0.13	0.0144	9.01
SF6	0.241	0.0178	13.522	0.131	0.0109	12.047	0.101	0.0093	10.85
R2	0.763			0.705			0.659

All coefficients were significant at the 95% confidence level.

. Findings in Table 1 show that the effect of all six environmental pollutants on coronavirus cases was positive. In other words, with the increase of these six greenhouse gases, the rate of coronavirus outbreaks increased: each country that emitted more environmental pollutants had more coronavirus cases.

Among these six gases, the effects of SF6 and CO2 gases were the highest. In other words, a one percent increase in the emission of SF6 and CO2 gases increased the number of coronavirus cases by 0.24% and 0.16%, respectively. After these two gases, PFC, CH4, HFC, and N2O were in the next positions. Also, the results of estimating the model with different values of lambda are shown in Figure 5, which again shows the strong effect of the two gases, SF6, and CO2.

The results of the greenhouse gas effect on the active cases of coronavirus in European countries are given in

Table 2. Effect of six environmental pollutant gases on the active cases of coronavirus.

Lambda	6.769			(+1 SE):39.64			(+2 SE):63.13
	Coef	Std	t-Stat	Coef	Std	t-Stat	Coef	Std	t-Stat
C	−0.8666	0.2545	−3.405	0.6034	0.1539	3.921	1.0766	0.2558	4.209
CO2	0.1666	0.0514	3.239	0.0836	0.0243	3.441	0.0675	0.017	3.962
CH4	0.1174	0.0166	7.067	0.0785	0.0092	8.507	0.0653	0.0071	9.146
N2O	0.0827	0.0028	29.64	0.0754	0.0022	34.712	0.0637	0.0017	37.003
HFC	0.1103	0.0046	24.241	0.0716	0.0027	26.58	0.0598	0.0022	27.073
PFC	0.0982	0.0188	5.218	0.124	0.0166	7.452	0.1205	0.0145	8.305
SF6	0.1969	0.0172	11.427	0.1168	0.0114	10.229	0.0956	0.0095	10.046
R2	0.74			0.681			0.644

All coefficients are significant at the 95% confidence level.

. Findings in Table 2 show that the emission of environmental pollutants also had a direct effect on the active cases of coronavirus. That is, countries that emitted more environmental pollutants were more likely to be exposed to coronaviruses. Among these six gases, the effects of the two gases SF6 and CO2 were much greater, so a one percent increase in the emission of these two gases increased the active cases of coronavirus by 0.19% and 0.16%, respectively. After these two gases, there were CH4 and HFC gases, both of which affected the coronavirus by about 0.11%. Also, the coefficients of PFC and N2O gases were 0.098% and 0.082%, respectively.

The trend of the effect of six greenhouse gases on the active cases of coronavirus for different Lambda is given in Figure 6. The changes in the effect of CO2 gas and the almost constant effect of SF6 gas, as well as the not-so-high effect of N2O, can be noted.

The effect of the release of the six environmental pollutant gases on the number of deaths caused by coronavirus in European countries is given in

Table 3. Effect of six environmental pollutant gases on total deaths.

Lambda	6.191			(+1 SE):39.800			(+2 SE):76.330
	Coef	Std	t-Stat	Coef	Std	t-Stat	Coef	Std	t-Stat
C	−4.4341	0.7757	−5.716	−2.1678	0.6768	−3.203	−1.1779	0.2455	−4.799
CO2	0.2447	0.0451	5.428	0.1222	0.0176	6.934	0.0901	0.0118	7.642
CH4	0.16	0.0169	9.442	0.1142	0.0108	10.563	0.0877	0.0072	12.158
N2O	0.1591	0.0042	38.195	0.1192	0.0028	42.522	0.091	0.002	45.076
HFC	0.1566	0.0054	29.163	0.104	0.0031	33.181	0.0804	0.0021	37.909
PFC	0.1357	0.0185	7.322	0.1782	0.0197	9.071	0.1691	0.0149	11.338
SF6	0.2982	0.0228	13.056	0.1737	0.0113	15.374	0.1297	0.0071	18.169
R2	0.769			0.705			0.645

All coefficients are significant at the 95% confidence level.

. Findings in Table 3 show that all six environmental pollutant gases had a direct and positive effect on the total number of deaths caused by coronaviruses. A one percent increase in the two SF6 and CO2 gases increased the number of deaths by 0.29 and 0.24 percent, respectively. In the next positions, the coefficients of CH4 and N2O gas were 0.16 and 0.159, respectively, and in the end, HFC and PFC gases had the least effect.

Figure 7 shows the trend of the coefficient of six environmental pollutant gases for different lambda. The high effect of CO2 gas on the primary lambda and the constant path of SF6 gas were significant. The effect of CH4, N2O, HFC, and PFC gases was small in all lambdas.

5. Discussion

In December 2019, pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China [100]. Then the coronavirus spread to all parts of the world. Importantly, various cases were reported in various countries. The European countries were one of the areas most affected by the coronavirus. But one important question is why coronavirus cases in different European countries are so different. One of the reasons could be the different environments in different countries, which have affected humans in different regions for many years. People in different regions have been exposed to polluting gases for many years. That is why their bodies reacted so differently to the coronavirus infection.

In this study, the effects of six environmental pollutant gases (CO2, CH4, N2O, HFC, PFC, and SF6) on coronavirus cases in European countries were investigated. The models were estimated for three modes (coronavirus cases, total deaths, and active cases). The results of Table 1 show that all six environmental pollutant gases had a positive effect on the cases of coronavirus, so the higher the emission of these gases in a country, the higher the cases of coronavirus in that country. This effect was 0.16, 0.09, 0.06, 0.09, 0.11, and 0.24 for the six gases, respectively.

Table 2 results also show that all six gases had a positive effect on active cases in the European countries, with the following coefficients: 0.16, 0.11, 0.08, 0.11, 0.09, and 0.19. The results of Table 3 also show that the emission of environmental pollutants had a direct effect on total deaths from coronaviruses, which for the six gases were: 0.24, 0.16, 0.15, 0.15, 0.13, and 0.29, respectively.

So environmental pollutants over time weaken the body against the coronavirus. The results show that each area that has been exposed to more environmental pollutants over the years has had higher levels of coronavirus cases, total deaths, and active cases. However, the findings of this study in Figure 7 shows that the six gases studied had different effects:

Carbon dioxide (CO2): CO2 was the second-most effective gas in all three cases. In other words, CO2 was the second-most dangerous gas, with the highest mortality rate. Methane (CH4): Although CH4 gas has a lesser effect on coronavirus cases, it has the same effect on total deaths and active cases, and in both cases, it has a third place.

Nitrous oxide (N2O): Although N2O gas has the least role in increasing coronavirus cases and active cases, this gas has had a significant effect on the number of deaths and has been very dangerous in this regard. Hydrofluorocarbons (HFC): HFC gas has been ranked fifth, fourth, and fifth in influencing coronavirus, active, and death cases.

Perfluorocarbons (PFC): The release of PFC gas has increased the incidence of coronavirus, but it has had the least effect and the lowest position on the number of deaths. Sulfur hexafluoride (SF6): SF6 gas has had the greatest effect on cases of coronavirus, total deaths, and active cases, and is arguably the most dangerous of the six.

Figure 8 shows the position of six polluting environmental gases due to the emission of coronavirus. The findings show that in recent years, the emission of polluting gases has led to an increase in various diseases, and coronaviruses are on the rise with attacks on people with implicit diseases and overcoming them. The results of this study showed that the prevalence of coronaviruses is directly related to the emission of environmental pollutants. Any country that produces more environmental pollutants is more likely to have coronaviruses. Findings from other researchers’ studies confirm the results of this study [14,15,16,17,18].

This study showed that the emission of two gases, SF6, and CO2, had the greatest impact on the infection and death caused by the coronavirus, respectively. To control CO2, the consumption of fossil fuels, especially oil, gas, and coal, as well as cement production, must be strategically managed. To control CH4, fossil fuels, livestock production, human waste, and wastewater are involved and must be strategically managed. To reduce N2O, meat production, cattle, and animal manure should be controlled. Using new technologies instead of old refrigerators and air conditioners could help reduce HFC gas. Inventing new technologies and innovation in industrial production can control PFC emissions. Reducing the use of SF6 gas in the power industry, according to the Kyoto Protocol, can be highly helpful.

6. Conclusions, Limitations, and Future Research Directions

6.1. Conclusions

For many years, countries have been focusing on production practices that increase gas emissions. This study showed that all six gas emissions (CO2, CH4, N2O, HFC, PFC, and SF6) had a direct effect on the prevalence of coronavirus in European countries. Unfortunately, those environmental pollutants were helping the spread of infectious viruses, including coronaviruses. This has policy implications for those who think about controlling environmental pollutants. It is argued that policymakers must be proactive and plan for controlling greenhouse gases to control future pandemics.

It is suggested that, in order to deal with the next pandemic, countries should join the international conventions against the emission of environmental pollutants and observe international regulations. To reduce mortality, people with underlying diseases should be given priority in quarantine, especially in areas with high emissions. Any area with more environmental pollution needs to be quarantined longer. In addition, a carbon tax policy is recommended. The carbon tax may limit production in the short run, but in the long run, by reducing greenhouse gases and environmental pollution, it could help with epidemic control and management; countries would face fewer economic problems, and the quarantine period would be shorter in scope and time, having long-term economic benefits. Therefore, this study showed that people with implicit diseases who are exposed to environmental pollution are more likely to get coronavirus. To prevent future epidemics, industrialized countries must focus on reducing environmental pollutants; otherwise, the next epidemic may be even more costly. To do this, countries must balance their short-term interests and economic growth with long-term human health benefits and sustainability. Also, a smart quarantine system based on the measurement of environmental pollutants could be helpful to reduce infection rates and deaths during an epidemic. People with underlying diseases need to be identified early by local clinics during the epidemic period to get special attention and treatment.

6.2. Limitations

The limitations of this study are the following: This research investigated the relationship between environmental quality, sustainable health, and the coronavirus pandemic in European countries. This research is only related to 30 European countries; we did not have access to the data of some other European countries. Furthermore, this research is for the period of COVID-19; we did not have access to longer-term data. The effect of the six environmental pollutant gases was investigated, but the amount of emission of other gases was not available.

6.3. Future Research Directions

The suggestions for future research are the following: one can use the same model for the other countries in a cross-country study that can be very informative. It is recommended to investigate and compare the effects of polluting gases on the epidemic of COVID-19 in developed and developing countries. Our results were obtained using cross-sectional data with the quantile regression method. It is suggested to use combined f time series, cross-sectional data, and panel data techniques for analysis. It is recommended to investigate the specific mechanisms through which polluting gases affect the immune system.