key: cord-0775722-jnoe7u6b authors: Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu A.; Tenciu, Daniel V. title: Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain date: 2021-08-06 journal: Environ Res DOI: 10.1016/j.envres.2021.111849 sha: 14367ab337f1dd4ead0031a33625a68447e0fa2e doc_id: 775722 cord_uid: jnoe7u6b While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020–1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future. 6 average to 0.1µm in diameter (Mousavizadeh, Ghasemi, 2020; R. Lu et al., 2020; Shang et al, 2020; Bosch et al., 2003; Rivellese, Prediletto, 2020; Walls et al., 2020) , that can be attached to atmospheric particulate matter. PM2.5 and PM10 may have inorganic and organic components as well as biotic components (bacteria, fungi, viruses, and pollens), which are known as bioaerosols, constituting up to 25% of the total atmospheric aerosols (Gao et al., 2015; Du et al., 2018) . Bowers et al., 2013; Bosch et al., 2003; Cao C. et al., 2014; Cao Y. et al., 2020; Jones and Harrison, 2005; Khan et al., 2019; Kawasaki et al., 2019) . The atmosphere can be a significant transport vector for airborne microbiome (bacterial, fungal, viral) communities and their seasonal shift in both the concentration and biodiversity are strongly influenced by meteorological parameters seasonality and Planetary Boundary Layer heights (PBL) (Tignat-Perrier et al., 2020; Zoran et al., 2020b; Lepeule et al., 2014) and especially in urban areas (Mhuireach et al, 2019) . Currently, the pathogenesis of COVID-19 deadly epidemics is not yet very clear (Nishiura et al., 2020; Luo et al., 2020; Walls et al., 2020) , but its existence as viral bioaerosol indoors and outdoors explains its pathogenicity. The main physical climate variables generally considered with a potential effect on SARS-CoV-2 virus persistence outdoors, include air temperature, relative humidity, wind speed intensity and direction, Planetary Boundary Layer height and the important contribution of sunlight radiation. The solar UV region covers the wavelength range 100-400 nm and is divided into three bands:UVA (315-400 nm), UVB (280-315 nm) and UVC (100-280 nm). While UV-C irradiation is highly efective in inactivating SARS-CoV-2 replication on contaminated surfaces (Biasin et al., 2021) , UVB and UVA in sunlight are the primary virucidal agents in the environment (Herman et al., 2020; Giese, 1976; Lytle, Sagripanti, 2005; Coohill, Sagripanti, 2009) . Surface solar UV irradiance may affect the diffusion and the outcomes of the COVID-19 viral infection in patients in two pathways: 1) reduction of SARS-CoV-2 virions transmission through the virus inactivation during specific time periods of exposure (Sagripanti, Lytle, 2020) ; and 2) synthesis of vitamin D in the body, that plays an essential role in the innate and adaptative immune systems defense increasing Jayawardena et al., 2021; Calder et al., 2020; Ilie et al., 2020; Castillo et al., 2020) . J o u r n a l P r e -p r o o f 9 The SARS-CoV-2 genome has the capability of suffering rapid mutations as the virus spreads Mu et al., 2020) . Like its genetic and structural similarities and seasonality with previous pandemics reported from 1918 to 2015 (known as "Spanish flu"-produced by Influenza virus 1918 A/H1N1, SARS-CoV (2002 and MERS-CoV (2012 , COVID-19 disease show also multiwaves pattern, future infection waves are likely to occur, with unpredictable height and breadth of the waves (Bakhshandeh et al., 2021; Rayan, 2021; Baay et al., 2020; Wong et al., 2020) . The increased incidence and severity of new fast rapid mutations of SARS-CoV-2 genome, named variants of concern is associated with the increased risk to human health Shang et al., 2020; Bakhshandeh et al., 2021; Wang Y.et al., 2020; Grubaugh et al., 2020) . variants. Spain has known the severity of this first phase of COVID-19 in terms of cases and deaths. The second and the third COVID-19 waves were also hard tests for Madrid and Spain society, due to existence of socioeconomic differentials in COVID-19 disease exposure, and existing social inequalities and mobilities (Glodeanu et al., 2021) . More than one year into the global COVID-19 pandemic, the focus of attention has shifted to the seasonal mutual interaction between emergence and spread of SARS-CoV-2 and its new variants and environmental multifactors. Most respiratory viruses show pronounced seasonality Rayan, 2021; Du et al, 2018; Stewart, 2016) but for SARS-CoV-2, this still needs to be J o u r n a l P r e -p r o o f 10 scientific documented. Is an urgent need to confirm the important role of the climate and environmental factors in SARS-CoV-2 airborne diffusion route, from a reservoir to a susceptible host in densely populated urban areas. The paper explores the two hypotheses: a)COVID-19 viral infection is associated with air pollution, and climate factors, that may act as determinants of COVID-19 disease spreading; b)seasonality of environmental factors has impacts on COVID-19 disease seasonality. Using daily time series analyses we tested the association between daily changes in climate in air pollution and meteorological variables , and COVID-19 incidence and mortality in Madrid metropolitan region. The aim of this study was to examine the association between SARS-CoV-2 viral infection fast transmission under local/regional air pollution conditions and climate variables, and different synoptic atmospheric circulation patterns, related to the four COVID-19 waves start-up and evolution in the Madrid metropolitan region in Spain. This region has a wide range of air pollution exposure levels and climate variability with which to investigate inter and intra-urban relationships with COVID-19. By using in-situ and geospatial daily time series data, statistical analysis, regression methods, this study aims to compare air pollution and climate factors variability , which can trigger the transmission of SARS-CoV-2 viral infection during the all four COVID-19 pandemic waves. Also, this study aims to provide significant information regarding the mutual relationship between seasonality of environmental factors and the COVID-19 incidence and lethality in Madrid region during several seasons and over more than one pandemic year investigated period (1 January 2020-1 July 2021). Future optimized interventions during pandemics need accurate estimation and timely information of the local and regional seasonal environmental and epidemiological parameters variability for decision-making as well as to fight the post-pandemic era. J o u r n a l P r e -p r o o f 11 Madrid, the Spain's capital and largest metropolitan region with high population of 6.661millions inhabitants, and a density of 829.62 inhabitants/km 2 , representing 14.2% of country's population was the national COVID-19 epicenter, and one of Europe's region most affected by COVID-19 pandemic waves. This metropolis is composed of Madrid city (centred on latitude 40.40792 o N, and longitude 3.69281° W), with more than 3.3 million inhabitants and 26 satellite towns (Fig. 2) , with an area of 604.3 km² is located in the centre of the Iberian Peninsula, on the high Castilian Central Plateau. Total area of Madrid Community region is of 8,030.1 km 2 . Madrid's high levels of air pollution and O3 precursors are attributed to industry and transport sectors (Gómez-Losada et al., 2019) . Is recognized by extreme climate events especially summer frequent heat waves under urban heat island and trans-border Saharan dust intrusions (Diaz et al., 2006; Diaz et al, 2015; Diaz et al, 2019; Linares et al., 2020) . Road traffic-related air pollution (Monzón & Guerrero, 2004; Cuevas et al., 2014) represents 65% of NOx, 67% of CO, 87% of PM10 and 85% of PM2.5 and 14% of total VOCs emissions per year, respectively (Salvador, et al., 2004; Salvador et al, 2012; Montero & Fernández-Avilés, 2018; Valverde et al., 2016) . Although during the last years NO2 and PM10 ambient air concentrations have recorded a clear decreasing trend due to the emission reduction, Madrid experienced an increase of 30-40% of ambient air O3 levels (Saiz-López et al., 2017) . Regarding air quality, despite general downward trends in emissions over recent years, and due to COVID-19 lockdown total/partial restrictions during spring/fall 2020 and respectively winter/spring 2021, still presents exceedances of air quality legal limits according to the Directive 2008/50/EC. From a regional point of view, the mountain breeze circulation influences the wind J o u r n a l P r e -p r o o f 12 intensity and direction pattern and drives the transport of the urban air pollution over the Madrid metropolitan basin (Salvador et al., 2004; Salvador et al., 2012; Salvador et al., 2021) . From a synoptic scale, there are several trans-boundary transports of air pollutants and long-range transport events of Northern Africa dust intrusions over the spring-summer periods, that occurs predominately over the Atlantic Ocean as a result of the powerful West-ward trade winds (Díaz et al., 2017) , characterized by an intense seasonal cycle, which may be a an additional risk factor for daily mortality especially during pandemic COVID-19 incidence. It is well recognized that the atmospheric circulation and low pressure fields, amplified by local thermodynamically mechanisms including soil moisture deficit has a significant role in increasing temperature extremes in Madrid metropolitan area. The time series analysis of climate and air pollution seasonality relationship with COVID-19 incidence and mortality seasonality in Madrid is based on a large global dataset built by collecting information from various freely available sources from January 2020 up to end of July 2021. Based on the global criteria for main air pollutants (O3, PM10, NO2, SO2, CO) air quality index is classified in six classes from very good to very poor (respectively: < 10-very good; 10 -20-good; 20 -30-satisfactory; 30 -50sufficiently; 50 -80-poor; > 80-very poor) . In order to analyze lower atmospheric circulation conditions associated with people's exposure to air pollutants and COVID-19 disease fast diffusion in Madrid metropolitan region during 1 January 2020-1 July 2021, we extracted geopotential heights at 500 mb anomalies and Omega at 850 mb surface charts provided by NASA, Reanalysis Data Project NCEP/NCAR PSD, Boulder, Colorado, USA (http://www.esrl.noaa.gov/psd/). According to content of meteorological information of daily anomalies of geopotential height 500 hPa (at about 5.5 km heightabove the ground), positive anomalies are associated with the anticyclones stability conditions like as, blocking systems, and negative anomalies with cyclones conditions. Also, in Omega surface charts, downwards airflows are associated with high stability conditions are given by positive values of omega (in Pa/s), while upwards airflow associated with instability conditions are given by negative values of omega surface charts. J o u r n a l P r e -p r o o f 15 This multiwaves pattern of COVID-19 in Madrid metropolitan region makes possible the further analysis of climate drivers, with descriptive statistical analysis method for transient correlations that identifies similar variation in the daily time series climate and air quality (considered independent variables) data together daily COVID-19 incidence and mortality over localized windows of time, corresponding to the four CVID-19 waves. First, a descriptive analysis was done to provide an overview of COVID-19 incidence and air quality during the study period. Next, for time series of data we used a linear regression model to fit the dependent variables (COVID-19 incidence) for each independent variable: daily average ambient air pollutants (particulate matter PM2.5, PM10, ozone O3 and NO2) and daily average meteorological parameters (air temperature-, air relative humidity-RH, wind speed intensity -w, surface solar irradiation) and daily maximum Planetary Boundary Planetary Boundary Layer -PBL. The dependence between pairs of time series was quantified in this study by standard tools of statistical analysis, Spearman and rankcorrelation non-parametric test coefficients. The normality of data was evaluated using Kolmogorov-Smirnov Tests of Normality for time-series data sets. As the data on daily new COVID-19 cases (DNC) and daily new COVID-19 deaths (DND) showed non-normal distribution, Spearman rank correlation was selected to investigate the association between COVID-19 incidence and mortality and climate and air quality data, using ORIGIN 10.0 software. The main reason for using non-parametric statistical tests is that compared with parametric statistical tests, are thought to be more suitable for non-normally distributed data, which are involved in our time series air pollution and climate variables data. The values for levels of correlation are bound in the range [0, +1], with 0 for no association and +1 for complete positive association and [0, -1] with -1 as negative correlation. Associated parameter "p-value" tells us if the result of an experiment is statistically significant. P values of < 0.01 and <0.05 were considered 16 statistically significant. Though correlation and p-value provides us with the relationship between variables, care should be taken to interpret them correctly. Over the last decades, environmental factors have become an increasingly serious global public health concern. Rapid urbanization has increased the amount of air pollution (particulate matter PM2.5, PM10 and gaseous ozone -O3, nitrogen dioxide -NO2, carbon monoxide -CO, volatile organic compounds -VOCs) to dangerous levels. Also, various sources of air and water pollution have impacted the composition of the environment and weather conditions with direct and indirect effects on the physiology and psychology of human health. The epidemiological studies linked exposure to ambient air pollution with particulate matter and gaseous pollutants under different meteorological conditions and occurrence of numerous respiratory viral infectious diseases transmission during several seasons (Wilson, Suh, 1997; Baklanov et al., 2016; Qian et al., 2010) . Also was established, that in large urban areas air pollution and climate factors variability including extreme climate events (heat waves, cold waves, floods, storms) are associated with multiple adverse outcomes in humans, including acute and chronic respiratory infections, chronic obstructive pulmonary disease (COPD), asthma, coronary artery diseases, and lung cancer (Sundell et al., 2016; Jones and Harrison, 2004; Wilson,Suh 1997) . The scientific studies during ongoing worldwide COVID-19 pandemic period found also that air pollution and climate parameters may promote the transmission of SARS CoV-2 viral infection pathogens and increase the incidence and lethality of COVID-19 cases (Landguth et al., 2020; van Doremalen et al.,2020; Luo W. et al., 2020; . Currently, is considered that the main pathways of COVID-19 transmission in humans are: a) inhalation of respiratory droplets sprays of aerodynamic diameter particle size ϴ> 5 µm (Thompson et al., 2021; Vejerano, Marr, 2018; Harrison et al., 2005; Gralton et al., 2011; Karimzadeh et al., 2021) ; b) via airborne transmission, through inhalation of nano-droplets/dried nano-droplets nuclei/ aerosol (PM) of virus-laden respiratory tract fluid with diameter particle size ϴ< 5 µm (Ram et al., 2021; Belosi et al., 2021; Nor et al., 2021) . c) direct contact with infected persons; d) direct contact with contaminated surfaces with SARS-CoV-2; e) possible oral/fecal contamination through wastewater and sewage sludge produced by hospitals and houses with infected people (Collivignarelli et al., 2020b; Carraturo et al, 2020; Wurtzer et al., 2020; Wurtzer et al., 2021) . In hospitals were found two distinct size ranges of bioaerosols with SARS-CoV-2 pathogens, with aerodynamic dominant diameter ϴ, in the range 0.25 µm <ϴ< 1.0 µm (Baboli et al., 2021; Liu F. et al.,2020) . Viral infectivity of SARS-CoV-2 pathogens is of fundamental importance for current and future COVID-19 waves adopting strategies. In Madrid metropolis, industry and traffic related are the predominant emission sources of primary pollutants, PM2.5, PM10 and fossil-fuel combustion by-products, like as NO2, which are especially prevalent with a significant threat to human health (Linares et al.,2018; Borge et al., 2019) . Table 1 summarizes descriptive statistics of the total Daily New of COVID-19 (DNC) incidence and mortality (DND) cases per periods and means of daily average concentrations of the main air pollutants (PM2.5, PM10, O3, and NO2) at the ground level, together air quality index and standard deviations recorded during 1 January 2020 -1 July 2021 in Madrid metropolitan region. Table 1) shows that during COVID-19 periods have been recorded reductions of air pollution levels (PM2.5 and PM10) across the Madrid metropolitan region as a result of the lockdown, with respectively (PM2.5: 26% for the first and the third COVID-19 waves, with 22% for the second COVID-19 wave, and 37% for the fourth COVID-19 wave; PM10: with 28% for the first COVID-19 wave, 20.7% for the second COVID-19 wave with partial lockdown, and with 23.2% for the third COVID-19 wave, and 39% for the fourth COVID-19 wave). The increased reduction of PM2.5 and PM10 concentrations during the fourth COVID-19 wave in spring 2021 can be associated to efficient interventions for daily mobility patterns in the metropolitan area of Madrid, (Glodeanu et al., 2021) . Physicochemical reactivity and adherence properties of particulate matter in different size fractions (PM0.1 µm, PM2.5 µm and PM10 µm) to SARS-CoV- J o u r n a l P r e -p r o o f 21 Daily mean of ground level average ozone concentrations follow also a seasonal pattern variation, but the concentrations during the four COVID-19 waves were increased in comparison with prelockdown period by the following factors : during lockdown and first wave period was an increase of 2.98 factor (explained by traffic and industrial related sources reduction and partially by spring seasonality), during heat wave period the increase of O3 was by a factor of 1.47 (attributed to summer seasonality and traffic-related sources), during second wave the increase of O3 was by a factor of 1.92, during the third wave the increase of O3 was by a factor of 1.44, and during the fourth wave the increase of O3 was by a factor of 2.20. During the entire investigated period in this study, mean daily average NO2 ground level concentrations recorded decreased values as compared with the pre-lockdown period as follows: during first wave COVID-19 lockdown of 53% , during heat waves period with 43%, during the second COVID-19 wave with 24%, during the third COVID-19 wave with 20%, and during the fourth COVID-19 wave with 72%, explained by traffic-related sources reduction, seasonal inversely variation pattern of NO2 with O3 during spring-summer seasons, when seasonal patterns of daily ground level NO2 concentrations record minimum values. Our results support the hypothesis that induced oxidative stress of the cardio-respiratory and immune systems, and altering the host resistance to viral and bacterial infections, urban air pollutants can increase susceptibility to morbidity and lethality from respiratory infections (Martelletti, Martelletti, 2020; Alghamdi et al., 2014; Asadi et al., 2020; Carugno et al., 2016; Romano et al., 2020; Cohen and Kupferschmidt, 2020) . Recent studies considered epigenetic alteration of genes by combustion-related pollutants that can generate new viral mutations,which can favor the evolution of the COVID-19 pandemic (Bakadia et al., 2021) . Clearly, urban air quality is associated with COVID-19 viral infections, and pathophysiologically, PM exposure J o u r n a l P r e -p r o o f 22 could facilitate COVID-19 disease by increasing angiotensin-converting enzyme in the lung (Tung et al., 2021) The anthropogenic emission sources that were affected by the lockdown during the first COVID-19 wave and the implementation of other sanitary restrictions and partial lockdown during the second, and mainly the third COVID-19 waves, were mostly on-road mobile sources such as motor vehicles, and to a lesser extend the aircraft and industrial emissions. Like was expected that the main primary air pollutants from these combustion sources, nitrogen oxides (NOx), PM2.5, PM10, carbon monoxide (CO) and Volatile Organic Compounds (VOC) such as toluene, benzene, xylenes will be decreased. But in case of ozone, a secondary pollutant, the effect can be complex and the level can increase or decrease depending on the location due to interaction of meteorology driving the dispersion of primary pollutants NOx, VOCs and the photochemical reactions forming the ozone levels across the Madrid region. Fig. 4 presents temporal patterns of daily average ground levels concentrations of ozone and nitrogen dioxide during 1 January 2020 -1 July 2021 showing the effect of total lockdown during the first COVID-19 wave and partial lockdowns during the next COVID-19 waves in Madrid as well as their impacts on daily new COVID-19 infections and daily new COVID-19 fatalities during the multiwaves COVID-19 pandemic. As can be seen in Table 1 and The results demonstrate that urban ground surface level of air pollution with gaseous toxic especially NO2 may enhance COVID-19 incidence cases and fatality rates. Ozone is a potential oxidizer and pulmonary irritant causing an inflammatory response in the lungs as well as a cascade of subsequent responses (Arjomandi et al., 2018; Fuller et al., 2020; Uetake et al., 2019; Zoran et al., 2013) . As a highly reactive exogenous oxidant, NO2 can induce inflammation and enhance oxidative stress, which may eventually deteriorate the cardiovascular and immune systems, being a comorbidity factor in case of SARS-CoV-2 viral infections. The trends between O3 and NOx are strongly anti-correlated, showing that the O3 is strongly depressed by high NOx (Gao W., et al., 2017) . According with scientific studies in the field Chen N. et al., 2020; Cohen, Kupferschmidt, 2020) , the presence of existing comorbidities associated with patients'' age, immunity system, sex, genetic and nutritional status, etc., might be essential factors for the etiology and severity of COVID-19 symptoms. The role of pre-existing J o u r n a l P r e -p r o o f 26 immune disorders induced by long-term or short-term exposure to high ground levels of air pollutants (gaseous and PM) contributes to the impressive SARS-CoV-2 lethality in Madrid (Baldasano, 2020; Aleta, Moreno, 2020) . As can be seen in Fig.3 and Fig. 4 , temporal patterns of Daily New Confirmed COVID-19 cases and Daily New COVID-19 Deaths in Madrid, this pandemic is ongoing and air pollution is a dominant environmental factor which must be considered in future COVID-19 waves decisions. Public health actions are needed to protect populations from COVID-19 disease in Madrid region with historically high NO2 and O3 exposure. Thus, air quality plays a complex role in the spreading of viral respiratory infection like novel coronavirus (Manoj et al., 2020) . As Table 2 shows, like several recent studies investigating the relationship between COVID-19 incidence and air pollution of urban large areas this study highlights that higher air pollution levels recorded in Madrid metropolitan region lead to greater mortality COVID-19 rates (Cole et al., 2020; Copat et al., 2020; López-Feldman et al., 2021; Pozzer et al., 2020; Travaglio et al., 2021) . As ambient air (Jin T., 2020) is contaminated by particulate matter, gases, bacteria, fungi and viruses, specific climate conditions can be top predictors of airborne novel coronavirus diffusion (Poole, 2020; Setti et al., 2020a; Setti et al., 2020b) . Besides human behavior, environmental parameters are the main major factors contributingfor the seasonal nature of respiratory viral infections with a high impact on respiratory SARS-CoV-2 virus stability and transmission rates (Moriyama et al., 2020) . Various diffusion patterns of COVID-19 disease transmissibility among humans, are influenced by the geographic location, season, and the local and regional climate conditions (wind speed intensity and direction, air relative humidity, air temperature and pressure, precipitation, Planetary Boundary Planetary Boundary Layer, and synoptic atmospheric circulation patterns) in which pathogen and host meet both outdoor as well as indoors (Collivignarelli et al., 2020; Poole, 2020; Conticini et al., 2020; Nuvolone at al., 2018) . The specific weather conditions and their seasonal variability in big cities (atmospheric thermal inversions, fog or haze, and extreme climate events) can have a high impact on local, regional and trans-border air pollutants and bioaerosols Bontempi E., 2020). All types of seasonal viral human infections have been directly associated with the main climate parameters (ambient air temperature, relative air humidity, wind speed intensity, UV solar radiation, atmospheric pressure, precipitation rate) variability Bashir et al., 2020; Ciencewicki and Jaspers, 2007; Barreca et al., 2012; Carugno et al., 2018; Coccia, 2020; Ballabio et al., 2013) . Madrid metropolitan region during the four COVID-19 waves. Table 3 presents a descriptive statistics of the daily mean main air climate parameters and ranges recorded during six analyzed periods for 1 January 2020 -1 July 2021 in Madrid metropolitan region. As Table 2 shows, for each of the four COVID-19 waves, daily COVID-19 disease incidence From Table 5 , can be seen that for more than one year study period (1 January 2020 -1 July 2021) daily average temperature was inversely correlated with daily average relative humidity (Spearman correlation coefficient being r= -0.75, and p<0.01). 30 Air temperature is one of the major environmental factors that is related with seasonal and regional variation. Environmental temperature has strong and regulatory effect on the duration of survival and transmission of SARS-CoV-2 through droplet, aerosols and bioaeosols. According to results of this study, cold weather is much more susceptible for the Daily New Also, our findings are consistent with the hypothesis that higher air temperatures and summer sunlight can reduce the spread of SARS-CoV-2 and the prevalence of COVID-19, which was also suggested by most of the previous studies examining the same hypothesis with different data and approaches Qi, et al., 2020; Shi et al., 2020) . Daily average relative humidity is an essential meteorological variable of SARS-CoV-2 airborne diffusion, being involved in the formation and size of aerosol droplets, used as a medium to infect (Baker et al., 2019; Obando-Pacheco et al., 2018) . As Table 4 and Fig.6 show, the results of this study highlight the mutual invers correlation of the daily average surface solar global irradiance with COVID-19 disease transmission in Madrid, during summer season being recorded lower daily COVID-19 incidence and mortality cases, and during winter season higher cases. Daily average precipitation rates contribution might be reflected in the daily average temperature and relative humidity and also in the atmospheric pressure. The mean value of daily maximum PBL height level during all investigated period in Madrid was of (1591.52 ± 846.12) m in the range of (132 -3717) m. As Several studies revealed that urban air pollution depends on local or regional emission sources, photochemical reactions, and meteorological variables, including the thermodynamic structure of the Planetary Boundary Layer(PBL), which determines the vertical atmospheric mixing of air pollutants. While in a cyclonic convective boundary layer, air quality is influenced by the dispersion/transport processes of air pollutants due to wind shears and convective turbulence, in an anticyclonic stable boundary layer, with potential temperature inversions, vertical mixing is weak, which leads to the accumulation of air pollutants (Miao, Liu, 2019; Tang et al., 2010; Li et al., 2017; Yadav et al., 2016) . So, diurnal variation pattern of the PBL thermodynamic structure can affect surface concentrations of particulate matter (PM2.5 and PM10) and gaseous air pollutants (e.g. O3, NO2, CO2, SO2). Because COVID-19 disease temporal variability is function of air pollution and meteorological seasonal variables (air temperature, relative humidity, Planetary Boundary Layer heights, solar surface irradiance, air pressure, local and regional winds and precipitation rates), like as other viral infections (human influenza virus, coronaviruses, etc.) is also seasonal sensitive. SARS-CoV-2 and its variants could exhibit seasonal patterns (Ye et.al. 2020; Byun et al., 2021; Rahimi et al., 2021) . Anyway seasonality of climate variables alone is not sufficient to curb the SARS-CoV-2 and its new variants transmission without intervention measures . Even though the spreading of the COVID-19 pandemic is affected by several countermeasures and medical interventions, our results confirm that there is a close bidirectional seasonality of COVID-19 incidence and lethality with air pollutants and climate variables. Spearman correlation coefficients for air pollutants and climate variable pairs for the study period are given in Table 5 . Across the study period, PM2.5 concentrations were closely correlated with PM10 concentrations (Spearman rank correlation's coefficient r = 0.66), but less so of PM2.5 with NO2 (r= 0.56), and PM10 with NO2 (r= 0.49), and only weakly negative correlated of PM2.5 and respectively PM10 with O3 (r= -0.15 and r= -0.19). In addition, air temperature was highly positive correlated with O3 (r= 0.73), and negatively correlated with NO2 concentrations (r= -0.37).Air relative humidity was highly negatively correlated with ozone concentrations and air temperature, and no correlated with particulate matter PM2.5 and PM10. As is expected, surface solar irradiance is strongly positively correlated with ground level ozone concentrations (r= 0.75) and air J o u r n a l P r e -p r o o f 35 temperature (r= 0.81), and negatively correlated with ground level nitrogen dioxide concentrations (r= -0.61), PM2.5 (r= -0.18) and PM10 (r= -0.12) and air relative humidity (r= -0.71). Table 5 . Spearman correlations between main air pollutants and climate variables in Madrid metropolitan region during the entire study period (1 January 2020-1 July 2021). J o u r n a l P r e -p r o o f 39 Is well known that climate warming and changes can play an important role in the dynamics of infectious diseases spreading (Altizer et al., 2013; Willox et al., 2015; Costello et al., 2009) . Favorable environmental conditions are needed for survival, reproduction, and spread of viral infections pathogens, of their vectors and hosts (Facciola et al, 2021) . Scientific literature documented significant correlations between climate parameters variability and the COVID-19 pandemic transmission (Araújo and Naimi, 2020; Aribi and Sghaier, 2020; Barcelo, 2020; Bashir et al., 2020) . The Madrid metropolitan area with Mediterranean transitions to a cold semi-arid climate, is characterized by blocking anticyclone atmospheric circulation systems and stagnant air conditions (high pressure/geopotential, low wind intensity favourable to accumulation of high levels of air pollutants due to urban traffic, industrial sources and long-distance transport of Saharan dust intrusions (Garrido-Perez et al., 2018; Borge et al., 2018; Russo et al., 2014; L´opez et al., 2019; Salvador et al., 2013; Salvador et al., 2014; Russo et al., 2020; Valverde et al. 2015; . Based on results in Table 2 can be attributed to different infectivity rates of new variants of SARS-CoV-2 as well as to adopted prevention and interventions strategies both at the regional and at the municipality level. Considering that timely and properly intervention polices, such as intensive contact tracing followed by quarantine and isolation, and intense vaccination procedure, can effectively reduce the spreading risk of the new more contagious SARS-CoV-2 variants (Cevik et al., 2021; Diao et al., 2021; Jin et al., 2021) . disease ability to develop into a seasonal disease, and to provide scientific evidence for early public health strategies to reduce viral infections impacts. This study has added strength in having a longer observation time period over environmental factors related to COVID-19 epidemiology in Madrid metropolitan region, that spanned several seasons during 1 January 2020 till 1 July 2021, allowing us to examine a larger range of time series meteorological and air quality data over multiple months. Was also possible to make a comparison between the first and the fourth COVID-19 waves that spanned during spring the same seasons belonging to respectively 2020 and 2021 years in Madrid. Furthermore, in an observational time series analysis of COVID-19 epidemiological data over more than one year period, we do not expect human individual risk factors to vary meaningfully over the study period. However, few studies have been focused on Madrid metropolitan region environmental factors seasonal mutual relationship with ongoing COVID-19 pandemic event. This study has some limitations. Despite the use of official COVID-19 incidence and mortality data, undertesting and underreporting throughout the course of the pandemic may have resulted in uncertainties of COVID-19 cases, limiting this study's capability to capture all COVID-19 cases. Also, due to COVID-19-related economic policies and sanitary restrictions, like lockdowns and stay-at-home measures, it is possible to be recorded lower air pollution at the ground levels, Nevertheless, being known that the airborne microbial temporal pattern is most affected by seasonal changes, we attempted to address the role of several environment parameters in driving the COVID-19 pandemic, and compare the four COVID-19 waves in Madrid. Our analysis was carried out at a metropolitan scale, to assess if the interactions between the seasonality of environmental factors could be captured and related with viral infection seasonality, being known that the airborne microbial temporal pattern is most affected by seasonal changes. Among the investigated climate variables, air temperature, relative humidity, solar surface global irradiance, Planetary Boundary Layer height, wind speed intensity and synoptic meteorological patterns are the most effective for controlling the novel coronavirus spread seasonality with higher incidence during winter-early spring and lower incidence during summer seasons. Time series analysis of Daily New COVID-19 incidence (DNC) and lethality (DND) cases in Madrid metropolitan region revealed a higher risk of mortality for the population consistently exposed to low levels of air quality and densely populated large cities. This paper demonstrates that climate factors seasonality and urban air quality are strongly implicated in the pathogenesis of COVID-19 infection and its sustained transmission. Moreover, the spatiotemporal atmospheric changes in air pollutants concentrations, and synoptic meteorological patterns may have encouraged COVID-19 multiwaves seasonality evolution to the more ubiquitous and possibly more contagious variants. This study considered also synergy effects of climate factors impacts and possible correlation among these variables with regional atmospheric circulation and COVID-19 waves start-up, synoptic meteorological patterns that may play a role in reducing or amplifying COVID-19 transmission. Also, this paper highlights a reciprocal relationship between the seasonality of COVID-19 pandemic waves and seasonality of local air pollution and climate factors, which are J o u r n a l P r e -p r o o f 51 actively controlled by regional meteorological formation of extensive stationary anticyclone conditions with blocking effects over the region and higher COVID-19 incidence infection rates. 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