Air Pollution Impacts During 2020 COVID-19 Pandemic: Emphasis on Urban, Suburban and Rural Zones

doi:10.21203/rs.3.rs-442999/v1

Download PDF

Research Article

Air Pollution Impacts During 2020 COVID-19 Pandemic: Emphasis on Urban, Suburban and Rural Zones

https://doi.org/10.21203/rs.3.rs-442999/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Air quality improvements pollution changes due to COVID-19 restrictions have been reported for many urban developments and large metropolitan areas, but the respective impacts at rural and remote zones are less frequently analysed. This study evaluated air pollution changes across all Portugal (68 stations) considering all urban, suburban and rural zones. PM₁₀, PM_2.5, NO₂, SO₂, ozone was analysed in pre-, during, and post-lockdown period (January-May 2020) and for a comparison also in 2019. NO₂ was the most reduced pollutant in 2020, which coincided with decreased traffic. Significant drop (15– 240%) of traffic related NO₂ was observed specifically during lockdown period, being 55% for the largest and most populated region in country. PM was affected to a lesser degree (with substantial differences found for largely populated areas (Lisbon region 30–40%; North region: up to 95%); during lockdown traffic-related PM dropped 10–70%. PM₁₀ daily limit was exceeded 50% less in 2020, with 80% of exceedances before lockdown period. SO₂ decreased by 35%, due to suspended industrial productions, whereas ozone concentrations slightly (though not significantly) increased (83 vs. 80 µg m^− 3).

Environmental Policy

Environmental Engineering

environmental pollution

ambient air

COVID-19

continuous monitoring

road transport

In January 2020 the World Health Organization (WHO) declared a global health emergency because of the novel coronavirus disease (COVID-19) that has been uncontrollably spreading all over the world¹. Since then, the pandemic has affected our whole society; WHO has registered 123 million cases worldwide with a total of 2.7 million mortalities². To limit the spread of pandemic, governments in countries around the world have imposed various restrictions, which led to reduction of people movement, decrease in transport (road and aviation), and even suspended industrial activities³. While COVID-19 has caused many adverse changes to our society and economies^{4, 5} and even to environment (in a form of newly created medical waste⁶), some studies have emphasized a possible improvement of the state of the environment⁷. People confinement, restricted public transport and ceased airlines international flights have also resulted in changes in air pollutant emissions, with information many information for megacities (Rio de Janeiro and Sao Paolo^{8, 9]}; and highly populated urban zones and cities^{10, 11, 12 13, 14, 15, 16, 17}. On more global scale, during the COVID-19 pandemic, PM_2.5 dropped approximately 12% worldwide across the most polluted cities worldwide, with the greatest reduction in capitals of America, Asia and Africa¹⁸. While the current studies even show that there might be causality between air pollution and COVID-19 infection spread^{19, 20}, the main focus of the COVID air pollution studies is typically on large and densely populated urban areas^{21, 22, 23} during relatively a short (or part of) period of lockdowns. The changes in air pollution trends during the lockdown in rural or remote places have been reported to much lesser degree. Ceased air and road transport and restricted human movements during the lockdowns allow for a unique situation for prediction modelling and visualization of potential air pollution mitigation scenarios. However, the complete perspective requires first information on air pollution changes not only in urban but also in rural and remote areas. This work thus evaluates the air pollution evolution (PM₁₀, PM_2.5, NO₂, SO₂, ozone) in pre-, during and post-lockdown period (January 1- May 2020) in whole Portuguese territory (continent and islands; 7 regions) considering all rural, suburban, urban zones. To provide wider context, air pollution data are assessed and also compared to the same period of the previous year.

2.1 Air quality network

The assessment of air quality in Portugal is conducted by the Portuguese Environment Agency (APA). The air quality measurement stations are managed by the Regional Development and Coordination Commissions (CCDR) of the region in which they operate. The classification of seven regions of Portuguese territory (five for the continent – North, Centre, Lisbon and Tejo Valley (Lisbon TV), Alentejo, Algarve, two for islands – Madeira, and Azores) was also adopted for this work (Table 1S of the Supplementary Material). Each monitoring station is characterized based on its type of agglomeration zone (rural, suburban or urban). The predominant influence of anthropogenic emissions further determines sub-type of each site as traffic, industrial or background. The air pollution data are measured continuously at the all monitoring stations from which they are transmitted, in almost real time, to regional “centres”. From these they are communicated to the central information system of QualAr database²⁴, based at APA²⁵. The data are then made available to the public through QualAr portal²⁶. Table 1 and Fig. 1S of the supplementary material summarized the characteristics of monitoring stations per each district. All 68 monitoring stations were considered in this work.

2.2 Air pollution data

The state of emergency due to the spread of COVID-19 pandemic was enforced in 19 March until 2 May 2020, with a strict consequent phases until 1 June 2020²⁷. Up to this date, various limitations still apply in Portugal (among other restrictions for public gatherings, obligatory use of masks in enclosed public spaces such as transport, shops or public offices, restricted working hours for bars and restaurants, etc.). Air pollution data was thus retrieved from the public QualAr database for all five months of 2020, specifically between January 1 and May 31. The data from the same period of the previous year 2019 were also considered for comparison.

All air pollutants available online by QualAr were considered, namely: PM₁₀, PM_2.5, O₃, NO₂, and SO₂. For particles, daily (24 h) average concentrations are published whereas it was maximum hourly average for O₃, NO₂, and SO_2,CO and benzene could not be included in the study as online database contained less 1% data for the evaluated periods (days). Air quality standards in Portugal^{28, 29} are based on the existent European legislation govern by Directive 2008/50/EU³⁰, for a reader convenience the respective standards and the limit values are summarized in Table 2S).

2.3 Traffic data

There are 15 principal motorways in continental Portugal (Fig. 2S). As there is no public database that would provide summarized information on number of vehicles in Portugal, the existing data regarding traffic counts were retrieved from available (annual and quartile reports) of companies^{31, 32} that ensures the majority operations of motorways system in country. Additional information was then retrieved from public reports and research projects, published on web portals of city halls of Metropolitan Areas of Lisbon and of Oporto^{33, 34, 35}.

2.4 Statistical analysis

All statistical tests for this study were performed by SPSS (IBM SPSS Statistics 26) and Microsoft Excel 2013 (Microsoft Corporation). Medians and means were compared through the non-parametric Mann−Whitney U test as the obtained data did not display normal distributions (confirmed by Shapiro−Wilk’s test). Statistical significance was set as p<0.05.

3.1 Air pollution monitoring network

As shown in Table 1 and Fig. 2S, most of the monitoring sites were situated in the districts of North and Lisbon TV. These two regions accounted for 67% of all monitoring stations in while they compose approximately 35% of the Portuguese territory area (Table 1S). Centre region accounted for 13% of the monitoring sites, whereas in Alentejo (30% of the total area) and Algarve district (5%) there are 7 and 6% of the monitoring stations, respectively. Portuguese islands represent a much smaller area (~ 3.5%) and hence a limited amount of monitoring stations (6%).

Evaluating the zone impact of each station (i.e. rural vs. suburban and urban) it is noteworthy that monitoring stations in urban zones are predominantly situated in North and Lisbon TV regions (47%). This is understandable considering that these two regions contain the two largest Metropolitan Areas in the country (of Oporto and Lisbon, respectively), with approximately 45% of the total Portuguese population (17 and 28% for area, respectively, in 2019)³⁶. In fact, monitoring sites of urban zones account for 55 and 83% in each of these regions, respectively. In addition, the North was the region with the highest number of monitoring sites in suburban zones (10%), whereas the monitoring stations for rural areas are relatively uniformly distributed among all regions (4–6 % in North, Centre, Lisbon TV and Alentejo, 1–3% in the remaining regions).

Evaluating the specific emission sources, 40% of all monitoring sites with traffic influence were situated in Northern monitoring network where it consists 28% of all the district’ stations. In addition, 65% of all background sites were situated in the most populated regions of Lisbon TV (67% the district’ stations) and in North (63%). On the national perspective, monitoring stations under influence of industrial emissions were the least existent (10%), being uniformly distributed between North, Lisbon TV and Alentejo region.

3.2 Traffic data

Evaluation of daily average traffic (on motorways) in 2018–2020^{31, 32} is shown in Fig. 3S. It is clear that quarterly (Q1–Q4) evolution trends of traffic were the same between 2018 and 2019, with the highest peak always observed during the summer months, i.e. 3rd quarter (Q3: 25530 vs. 25916 vehicles day^− 1, respectively). Furthermore, when compared to previous year, in 2019 traffic showed a consistent growth of 3.7%, for each quarter as the following: 5.6 % for Q1, 6.3% for Q2, 1.5% for Q3 and 2.1% for Q4. It noteworthy, that heavy vehicle traffic showed a higher growth rate (4.5%) than light vehicles (3.6%). In agreement, additional data showed that road transport supply (for transport of passengers) increased to 29.4 billion seats-km, with 83.1% of its total being made available on regular transport³⁴. The number of national transport services increased by 9.2% to 20.5 million, while 543.1 million passengers were carried, representing an increase of 5.5% compared to the previous year of 2018³⁴.

On the contrary, due to the restrictions associated with COVID-19, the average daily traffic decreased during the first quarter of 2020: 12% in a comparison with 2019 and 7% when compared with 2018 (Fig. 3S). Due to the state emergency and the limitations of the consequent return phases, the predicted traffic drop is expected being even higher during the second quarter of 2020, but up to this date (31st July 2020) the respective data has not been released by the responsible organizations. Furthermore, the available data shows that light vehicles were more impacted by the traffic reductions than heavy vehicles, with the respective decrease of 12 and 2% respectively³².

3.3 Air pollution data: 2019 vs. 2020

3.3.1. Particulate matter

The levels of air pollutants, namely PM₁₀, PM_2.5, NO₂, SO₂ and O₃ in seven Portuguese regions are summarized Fig. 1, which show the statistics across all monitoring stations for the three types of zoning (rural – urban). Specifically, in 2019 daily levels of PM₁₀ measured at 68 monitoring stations demonstrated large variations of the obtained data (Fig. 1a), with detailed descriptive statistics summarized in Table 3S. Average daily PM₁₀ means were between 12 and 20 µg m^− 3 (absolute range 1–74 µg m^− 3) in rural zone of the five regions of the Continental Portugal, 18–21 µg m^− 3 (2–82 µg m^− 3) in suburban zones and 20–24 µg m^− 3 (1–116 µg m^− 3) in urban ones. Regions of Portuguese islands showed lower concentrations, especially at rural zones with the corresponding means of 11 µg m^− 3 (Madeira, range 2–71 µg m^− 3) and 7 µg m^− 3 at Azores (2-–17 µg m^− 3). These results demonstrated that for all 7 regions daily PM₁₀ concentrations were the lowest at rural zones being significantly (p < 0.05) different (approximately 15% in Algarve – 60% for North) that the respective means at urban zones (or suburban for Alentejo). Regarding the EU limits daily (50 µg m^− 3), for urban zones the exceedances were observed in 30% of the rural stations: two in Centre, one in Lisbon TV, one in Madeira one in Alentejo (the respective monitoring station is with industrial influence due to the industrial power plan). It though necessary to point out that EU legislation stipulates a tolerance of exceedance 35 per year and in that regard all the monitoring stations fulfilled the conditions as the registered exceedances occurred 1–7 times per the same station (Table 3S). Furthermore, it is necessary to enhance that the raw data were considered in this work and the possibility of subtracting contributions to the measured concentrations from natural sources and winter road sanding/salting has not been considered. In all the other regions (North, Algarve and Azores islands), no concentrations higher than daily limit were registered in rural zones. On the contrary, suburban and urban zones of Portugal exhibited exceeded the daily limits in all regions/zones. These were especially high for North (total of 57) and in Lisbon TV (64), which were the regions with the higher number of stations. In Centre, the limits were approximately 3 times less (21 times), whereas in Alentejo and Algarve the exceedance were even less frequent (6 and 12 times, respectively); in all stations the margin of tolerance (35 exceedance) fulfilled in all monitoring sites.

In 2020 the levels of PM₁₀ (Fig. 1a, Table 4S) were slightly lower in a comparison with the previous year. Daily means of PM₁₀ for Continental Portugal were observed as the following: 8 µg m^− 3 (North) to 17 µg m^− 3 (Algarve) in rural zones, 17 µg m^− 3 (Alentejo) – 24 µg m^− 3 (Centre) in suburban one, and 17 µg m^− 3 (North) and 25 µg m^− 3 (Algarve) for urban zones. These results showed that in rural zones, PM₁₀ concentrations in 2020 were significantly lower than in the previous year (p < 0.05; overall mean of 12 µg m^− 3 vs. 17 µg m^− 3 in 2020), with the respective percentage being between 30% (Lisbon TV) and 80% in Alentejo. In urban zones the respective PM were lower in 2020 only in Centre and Lisbon TV regions (~ 30%), whereas PM no differences were observed in North and Alentejo region. Within the urban areas, ambient air pollution is often dominated by motor vehicles traffic ), but due to the variables such as number of junctions, distance to roadways, traffic flows, surrounding road length, and others the respective pollution may vary greatly^{37,38, 39}. It is assumed that the lesser traffic in 2020 (Fig. 3S) might be the cause for the lower PM levels in some of the urban zones.

The analysis of PM₁₀ levels across the urban zones with traffic emissions specifically (i.e. 22 monitoring urban-traffic sites) showed that in terms of monthly evolution (Fig. 2a) PM₁₀ started to decrease in February 2020, with the minimal levels observed in April (when the state of emergency was implemented) and then increased in May (state of emergency ended). However, when comparing both years (Fig. 2b), the largest concentration drops were observed, as expected in month of April (10–70% in Madeira and Algarve) but also February (up to 70% in North). These data may be in agreement with the road transport trend that shows a significant decrease during the first trimester (January– March; Fig. 3S). However, correlations between the road transport changes on monthly basis (when available) and traffic-related pollutants would provide much deeper understanding of respective association. At the same time, as the traffic density decreased on the international level (due to the restrictions taking place in majority of European countries), PM₁₀ levels at rural ones were most likely affected due to the lesser transport of long-distance emissions.

On the contrary, in suburban sites, PM₁₀ in 2020 (Fig. 1) were higher (overall 21 µg m^− 3 vs. 20 µg m^− 3), though these differences were not statistically significant, with the highest changes observed in North and Centre region (20 and 30%). On European level road transport contributes only ~ 11% of PM in EU, the main sources of PM₁₀⁴⁰ are commercial, institutional and households sector (39%) and industrial processes (20%), which could be linked with the unchanged trends of PM in suburban zones. In terms of PM₁₀ legislation, 24 h limit was exceeded in all three types of zones in 2020. However, majority of the exceedances were observed in urban zones (87%, Table 4S) and furthermore, 80% of these exceedances occurred in January and February (i.e. before the state emergency regulations took place). In addition, it is necessary to highlight that in 2020, for the respective period of 5 months, PM₁₀ daily limits were exceeded approximately 50% less (107 vs. 218 in 2019). Thus, the results indicate that PM concentrations were positively influenced in 2020, most likely also by the lower vehicle road traffic. It is necessary to highlight that Algarve was the only region that exhibited in 2020 very different evolution of PM at urban traffic sites (and higher concentrations at urban traffic sites during all 5 months of 2020) than rest of the territory (Fig. 2a). While previous work emphasized the impacts of long–range transport of mineral dust from North Africa with high frequency and prevalence namely in southern parts of Portugal^{41, 42} it needs to be highlighted that the respective data (urban traffic) is based on 1 monitoring station (Table 1). Thus these values will need to be confirmed when the final registry of APA is released.

Concerning the fine fraction, 2019 average daily PM_2.5 means (Fig. 1b) were between 5 and 9 µg m^− 3 (absolute range 1–47 µg m^− 3) in rural zone of the five regions of the Continental Portugal, 9–21 µg m^− 3 (1–60 µg m^− 3) in suburban zones and 5–15 µg m^− 3 (1–53 µg m^− 3) in urban ones. In agreement with PM₁₀, these results demonstrated that for all 7 regions daily PM_2.5 concentrations were the lowest at rural zones being significantly (p < 0.05) different (approximately 15% in Alentejo – 90% for Centre) that the respective concentration at urban zones. In 2019, for the considering period, the overall mean (7 µg m^− 3 across 68 monitoring stations) was well below the annual target (Table 1S), though these results need to be implicated carefully, once the considered work of this study included 5 months (i.e. 42% of the calendar time).Worldwide, Portugal is among the countries with the better air quality in terms of PM_2.5⁴³; in 2017 it ranked as 7th country in European Union with the lowest PM_2.5 across 27 members⁴⁰. Furthermore, it is noteworthy that for fine fraction, that out of the three different zones, suburban areas presented the highest PM_2.5 (overall mean of 16 µg m^− 3 ) with 80–265% higher concentrations than the respective levels at each regions of the rural zones. Still, the exposure concentration obligation (20 µg m^− 3; calculated based on the levels of PM_2.5 at suburban and urban background sites) are typically obliged⁴⁰.

In 2020, The lowest PM_2.5 concentrations were observed in rural zones where they ranged between 4 µg m^− 3 (Algarve) and 7 µg m^− 3 (Centre and Lisbon TV). The corresponding levels in suburban and urban areas were 30–90% higher with, respectively, overall means of 6 µg m^− 3 (Alentejo) and 12 µg m^− 3 (Lisbon TV) in suburban and 5–13 µg m^− 3 (Madeira and Centre region) in urban zones. In comparison with 2019, PM_2.5 emissions decreased in year after. Whereas the changes were statistically insignificant in rural zones (overall means of 6 µg m^− 3 vs. 7 µg m^− 3), the highest differences was observed in suburban (10 µg m^− 3 vs. 16 µg m^− 3 in 2020), and urban zones (8 µg m^− 3 vs. 10 µg m^− 3) being especially substantial for North (95%) and Lisbon TV region (~ 40%). While the data for urban traffic zones are limited (Fig. 5S), in agreement with the previous results, April was the month the lowest concentrations.

3.3.2 Gaseous pollutants

For the gaseous pollutants the overall mean of NO₂ concentrations in 2019 (Fig. 1c) were 12 µg m^− 3 (range of Azores 3 µg m^− 3 – North 16) for rural zones, 42 µg m^− 3 for suburban (33 µg m^− 3in Centre to 64 µg m^− 3 in North) and 54 µg m^− 3 (37 µg m^− 3 in Algarve − 74 µg m^− 3 in North) for urban zones. These results shown the strong impact of anthropogenic emissions of level of NO₂, being typically considered as indicator of traffic emissions^{44, 45}. On European level, approximately 40% of NOx emissions are contributed by road transport sector⁴⁰. The population exposure to ambient NO₂ concentrations is especially relevant in urban areas because its emissions are close to the ground and are distributed across densely populated areas. Furthermore, the highest concentration of NO₂ were observed in suburban and urban zones of North region (i.e. 40% of coverage for traffic emissions monitoring in Portugal; Table 1). Concerning the limits for heath protection, 9 exceedances of hourly limit value in 2019 were registered in 5.9% (4 stations) of all monitoring station (North and Lisbon TV region), all of them being urban sites (and 3 traffic influence).

In 2020, the mean of NO₂ concentrations at rural zones (Fig. 1c) were between 2 µg m^− 3 (Algarve) and 10 µg m^− 3 (North). In suburban zones, depending on each region the respective levels were 3–7 times higher, with means between 14 µg m^− 3 in Alentejo and 64 µg m^− 3 in North, whereas in urban zones the respective NO₂ levels were even higher (4–18 times in a comparison with in rural zones) with range of 29–53 µg m^− 3 in Algarve and North, respectively. In agreement with the previous year, the highest levels of NO₂ (up to 6 times) were observed for the zones (all) of North region. However, in 2020 NO₂ levels were significantly (p < 0.05) lower in a comparison with the previous year, being approximately half for the rural and 30% lower in suburban and urban zones as follows: overall mean 6 µg m^− 3 vs. 12 for rural zones, 33 µg m^− 3 vs. 43 µg m^− 3 in suburban and 43 µg m^− 3 vs. 56 µg m^− 3 in urban ones. Thus in 2020, NO₂ pollution was significantly lower (p < 0.05) in all types of zones and in all regions of Portugal. NO₂ was the pollutant with more significant changes during the two year and the restrictions associated with the COVID-19 pandemic seemed to have significant implications for NO₂ levels in air, both on local (direct) and international level, the latter being demonstrated by the much lower concentrations of the pollutant observed at rural sites in 2020. Concerning the urban traffic zones specifically (Fig. 2c), the concentrations of NO₂ were lower than in previous year in all regions between February and May. A significant decrease of NO₂ levels was though registered in March, April was the month with the minimal means in 2020 in all the regions (range 17–33 µg m^− 3). It is noteworthy that in North the NO₂ levels were still almost twice higher (mean of 57 µg m^− 3) during the state emergency period than in the rest of country. In addition, evaluating then decrease of NO₂ (Fig. 2d), the biggest changes between the two years were observed in March and April of 2020 when NO₂ decreased by 15% (North) and 240% (Algarve). Considering the two largest and most populated urban areas in country (Lisbon MA and Oporto MA in Lisbon TV and North region, respectively; Table 1S), NO₂ cumulative decrease was 55% (40 and 15%, respectively) which from the national perspective may represent several health benefits⁴⁶. These results clearly confirm that NO₂ levels were significantly lowered during restrictions associated COVID-19 outbreak (especially in months of March and April). Finally, in 2020 over the period analysed in this work all monitoring stations fulfilled the limit value for the health protection and no exceedances were observed, unlike the previous year.

SO₂ (Fig. 1d) maximum of 1 h mean concentrations ranged between 2–12 µg m^− 3 in rural zones, 3–13 µg m^− 3 and 3–29 µg m^− 3 in suburban and urban zones, respectively. The levels of SO₂ were especially high in North region, where for suburban and urban zones concentrations were 3–6 times higher than in the other regions. However, across all monitoring stations, 1 h limit alert threshold (500 µg m^− 3) and 1 h limits value (350 µg m^− 3) of SO₂ concentrations were fulfilled. In addition, in general SO₂ levels were below the 24 h limit value; in 2019 only 3 stations (North region) registered 1 h maximum concentrations above the daily limit value, but the 24 h concentrations during those exceedance were fulfilled. In 2020 (Fig. 1d) the 1 h maximum means ofSO₂ were 5 µg m^− 3 (range of 1–10 µg m^− 3) in rural zones, and 9 µg m^− 3 (3–23 µg m^− 3) and 10 µg m^− 3 (5–18 µg m^− 3) in suburban and urban zones, respectively. For all three types of zones, the highest SO₂ were observed in North region (up to 6 times for suburban zones and 9 times for urban ones) than in other regions. The North region was also the only one where 1 h maximum concentrations exceeded one time the 24 h limit value (on urban industrial site). Finally, 1 h alert and 1 h limit were obliged in all 68 monitoring stations. Though SO₂ is a not a pollutant associated with traffic emissions, in 2020 the overall levels were approximately 65% lower than in the period of the previous year with overall means of 5 vs. 8 µg m^− 3 which could be due to suspended industrial emissions. Nevertheless, evaluating the industrial sites specifically (suburban and urban Table 1), the means obtained between both years were not significantly different (6.3 vs. 6.9 µg m^− 3in 2019). In addition, the monthly evolution trend of did not show any change of patterns in the lock down period, however, assessment of 24 h means (oppose to 1 maxima used in this work) should be conducted when available.

Data for ozone in 2019 (Fig. 1e) that maximum 1 h mean ranged between 74 µg m^− 3 (North) and 104 µg m^− 3 (Algarve) of rural zones, 62 µg m^− 3 (North) and 90 µg m^− 3 (Alentejo) in suburban and 67 µg m^− 3 (North) and 101 µg m^− 3 (Algarve) in urban ones. These results show that registered 1 h maxima concentrations were higher (p < 0.05) at rural sites than those in suburban and urban ones, in agreement with other studies reporting the “ozone paradox” [47]. Production of background ozone exhibits both long-term trends and substantial annual variability [48] due to the variations in air-flow, air pressure or temperature^{49, 50, 51}. In addition, peak ozone episodes are strongly influenced by emissions of its precursors, such as nitrogen oxides and volatile organic oxides, the latter being relevant in rural zones⁵² and by meteorological conditions (being favoured by warm, stagnant high-pressure conditions). For all zones, the registered 1 h maxima were the lowest in north of country consistently increasing towards the south, being the highest in southern regions of country (Algarve and Alentejo for suburban zones, Fig. 1e); in agreement the north of the country being the coldest and south being the warmest with mean air temperature as the follows: 13.8°C in North, 15.1°C for Centre, 16,8 Lisbon TV, 16.9°C in Alentejo and 17.0°C in Algarve⁵³. From the legislative perspective, the European hourly alert of 180 µg m^− 3 was exceeded once (North regions), whereas 1 h information threshold of 180 was reached once in Lisbon TV region (120 µg m^− 3, expressed as daily 8 h mean) though could not be clearly assessed, once the continuous measurements of ozone are not public yet. Finally, in 2020 the overall levels of ozone slightly (though not significantly) increased (83 vs. 80 µg m^− 3). One h maximum levels ranged between 79 µg m^− 3 (North) and 92 µg m^− 3 (Alentejo) in Continental Portugal whereas levels in islands were higher (92–97 µg m^− 3). In agreement with previous year, suburban and urban sites of Continental Portugal exhibited, respectively, significantly lower concentrations of ozone as follows: 59–80 µg m^− 3 (North and Alenetejo), and 70–80 µg m^− 3 (Centre and Lisbon TV). However, no differences were observed between the levels during the two years with the means as 87 µg m^− 3 vs. 89 µg m^− 3 in 2020 and 2019 in rural sites, 73 µg m^− 3 vs. 79 µg m^− 3 for suburban, and 85 µg m^− 3 (in both years) at urban zones. The European hourly alert of 240 µg m^− 3 was not exceeded in 2020.

This work assessed air pollution levels and trend during COVID-19 period in Portugal (January–May 2020) in a comparison with the previous year. The issued lockdown of the country enforced by the Portuguese government resulted in some positive, yet non uniform, changes of air pollution. NO₂ was the pollutant that show the most consistent decrease all over the country and across all different zones of urbanizations, in accord with reduced transport. Considering that annually road transport causes between 184,00 and 242,000 premature deaths worldwide^{54, 55} public health benefits from reduction of the respective emissions might be significant. Regarding particulate matter, the major decreases were observed in remote and urban zones, suburban areas were impacted to a lesser degree and most dominantly in terms of fine PM. Whereas improved air quality will persist in long-term is uncertain, nonetheless the restrictions of COVID-19 conducted on large scale and in many countries simultaneously will provide a unique opportunity to re-examine current air quality policies and possible recovery scenarios to for air pollution reduction on global level.

Acknowledgments

This work was supported by Base Funding – UIDB/00511/2020 of the Laboratory for Process Engineering, Environment, Biotechnology and Energy – LEPABE –, and by PCIF/SSO/0017/2018 funded by national funds through the FCT/MCTES (PIDDAC).

Funding: This work was supported by Base Funding – UIDB/00511/2020 of the Laboratory for Process Engineering, Environment, Biotechnology and Energy – LEPABE – and by BioFirEx – PCIF/SSO/0017/2018 funded by national funds through the FCT/MCTES (PIDDAC).

Conflicts of interest/Competing interests: The authors have no conflicts of interest to declare that are relevant to the content of this article.

Availability of data and material: The data to obtain the findings of this study were retrieved from publicly available QualAr database. The datasets analysed during the current study are available from the corresponding author on reasonable request.

Authors' contributions: Klara Slezakova – Conceptualization, Formal analysis Data curation, Critical Revisions, Writing-original draft, Maria do Carmo Pereira – Conceptualization, Methodology, Critical revision.

Code availability (software application or custom code): Not applicable

Ethics approval and consent to participate: Not applicable

Consent for publication: Not applicable as this manuscript does not contain any personal information or data.

World Health Organization (WHO) (2020). WHO Director-General's statement on IHR Emergency Committee on Novel Coronavirus (2019-nCoV). Accessed online 12.8.2020, available at https://www.who.int/dg/speeches/detail/who-director-general-s-statement-on-ihr-emergency-committee-on-novel-coronavirus-(2019-ncov).
World Health Organization (WHO) (2020). Coronavirus disease (COVID-19) Situation Report–205. Accessed online 12.3.2021, available at https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200812-covid-19-sitrep-205.pdf?sfvrsn=627c9aa8_2
Zambrano-Monserrate, M. A., Ruano, M. & Sanchez-Alcalde, L. Indirect effects of COVID-19 on the environment. Sci Total Environ. 728, 138813 https://doi.org/10.1016/j.scitotenv.2020.138813 (2020).
Chakraborty, I. & Maity, P. COVID-19 outbreak: migration, effects on society, global environment and prevention. Sci Total Environ. 728, 138882 https://doi.org/10.1016/j.scitotenv.2020.138882 (2020).
Dutheil, F., Baker, J. S. & Navel, V. COVID-19 and air pollution: the worst is yet to come. Environ Sci Pollut Res. 27, 44647–44649 https://doi.org/10.1007/s11356-020-11075-6 (2020).
Saadat, S., Rawtani, D. & Hussain, C. M. Environmental perspective of COVID-19 Exposure to air pollution and respiratory symptoms during the first 7 years of life in an Italian birth cohort. Sci Total Environ. 728, 138870 https://doi.org/10.1016/j.scitotenv.2020.138870 (2020).
Arora, S., Bhaukhandi, K. D. & Mishra, P. K. Coronavirus lockdown helped the environment to bounce back. Sci Total Environ. 742, 140573 https://doi.org/10.1016/j.scitotenv.2020.140573 (2020).
Krecl, P., Targino, A. C., Oukawa, G. Y. & Cassino Junior, R. P. Drop in urban air pollution from COVID-19 pandemic: Policy implications for the megacity of São Paulo. Environ Pollut. 265, 114883 https://doi.org/10.1016/j.envpol.2020.114883 (2020).
Siciliano, B., Dantas, G., da Silva, C. M. & Arbilla, G. Increased ozone levels during the COVID-19 lockdown: Analysis for the city of Rio de Janeiro, Brazil. Sci Total Environ. 737, 139765 https://doi.org/10.1016/j.scitotenv.2020.139765 (2020).
Abdullah, S. et al. Air quality status during 2020 Malaysia Movement Control Order (MCO) due to 2019 novel coronavirus (2019-nCoV) pandemic. Sci Total Environ. 729, 139022 https://doi.org/10.1016/j.scitotenv.2020.139022 (2020).
Cui, Y. et al. Levels and sources of hourly PM2.5-related elements during the control period of the COVID-19 pandemic at a rural site between Beijing and Tianjin. Sci Total Environ. 744, 140840 https://doi.org/10.1016/j.scitotenv.2020.140840 (2020).
Chu, B., Zhang, S., Liu, J., Ma, Q. & He, H. Significant concurrent decrease in PM2.5 and NO2 concentrations in China during COVID-19 epidemic. J Environ Sci. 99, 346–353 (2021). https://doi.org 10.1016/j.jes.2020.06.031
Latif, L. D., Dominick, D., Hawari, N. S. S., Mohtar, A. A. A. & Othman, M. (2021). The concentration of major air pollutants during the movement control order due to the COVID-19 pandemic in the Klang Valley, Malaysia. Sustain. Cities Soc 66, 2021, article number 102660. https://doi.org/10.1016/j.scs.2020.102660
Lian, X. et al. Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city. Sci Total Environ. 742, 140556 https://doi.org/10.1016/j.scitotenv.2020.140556 (2020).
Kumar, P. et al. (2020). Temporary reduction in fine particulate matter due to ‘anthropogenic emissions switch-off’ during COVID-19 lockdown in Indian cities. Sustain. Cities Soc 62: article number 102382. https://doi.org/10.1016/j.scs.2020.102382
Shehzad, K., Sarfraz, M. & Shah, S. G. M. The impact of COVID-19 as a necessary evil on air pollution in India during the lockdown. Environ Pollut. 266, 115080 https://doi.org/10.1016/j.envpol.2020.115080 (2020).
Wang, Q. & Su, M. A. A preliminary assessment of the impact of COVID-19 on environment – A case study of China. Sci Total Environ Sci Total Environ. 728, 138915 https://doi.org/10.1016/j.scitotenv.2020.138915 (2020).
Rodríguez-Urrego, D. & Rodríguez-Urrego, L. Air quality during the COVID-19: PM 2.5 analysis in the 50 most polluted capital cities in the world. Environ Pollut. 266, 115042 https://doi.org/10.1016/j.envpol.2020.115042 (2020).
Pei, L. et al. Do air pollutants as well as meteorological factors impact Corona Virus Disease 2019 (COVID-19)? Evidence from China based on the geographical perspective. Environ Sci Pollut Res, in press. 1–13 https://doi.org/10.1007/s11356-021-12934-6 (2021).
Coccia, M. Effects of the spread of COVID-19 on public health of polluted cities: results of the first wave for explaining the dejà vu in the second wave of COVID-19 pandemic and epidemics of future vital agents. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-11662-7 (2021).
Briz-Redóna, A., Belenguer-Sapiña, C. & Serrano-Arocac, S. Changes in air pollution during COVID-19 lockdown in Spain: A multi-city study. J Environ Sci. 101, 16–26 https://doi.org/10.1016/j.jes.2020.07.029 (2021).
Tobías, A. et al. Changes in air quality during the lockdown in Barcelona (Spain) one month into the SARS-CoV-2 epidemic. Sci Total Environ. 726, 138540 https://doi.org/10.1016/j.scitotenv.2020.138540 (2020).
Collivignarelli, M. C. et al. Lockdown for CoViD-2019 in Milan: What are the effects on air quality? Sci Total Environ. 732, 139280 https://doi.org/10.1016/j.scitotenv.2020.139022 (2020).
QualAr (2020)a. The Monitoring Network (in Portuguese). Available at https://qualar.apambiente.pt/node/rede-de-medicao-da-qualidade-do-ar, retrieved 27.7.2020.
Agência Portuguesa do Ambiente – APA (2020). Ambient air. Available at https://apambiente.pt/index.php?ref=16&subref=82&sub2ref=316, retrieved 27.7.2020.
QualAr (2020b). The observed pollution (in Portuguese). Available at https://qualar.apambiente.pt/downloads, retrieved 13.6.-–30.6.2020.
The Portugal News (2020). President announces end of the state of emergency. The Portugal´s National Newspaper in English, published 30.4.2020, retrieved on 27.7.2020 from https://www.theportugalnews.com/news/president-announces-end-of-the-state-of-emergency/53920. Copyrights Anglopress Lda, The News Group of Newspaper agência.
Decreto-Lei 102/2010 (in Portuguese). Diário da República, 1.ª série – N.º186, 4177–4205.
Decreto-Lei 43/ 2015 (in Portuguesse). Diário da República n.º 61/2015, 1711–1713.
European Parliament Directive 2008/50/EC of the European Parliament and of the Council on ambient air quality and cleaner air for Europe. Official Journal of European Union. L152, 1–44 (2007).
(2020). FY 2019 Traffic Update. IRISA Brisa Concessão Rodoviária (BCR) & Concessão Rodoviária, S. A. published on 29th January 2020, retrieved from https://www.brisaconcessao.pt/Portals/0/comunicados/EN/BCR%202019%20Traffic%20Update_v2.pdf, https://web3.cmvm.pt/sdi/emitentes/docs/FR75326.pdf
Brisa Concessão Rodoviária (BCR) (2020). Update de tráfego 1T 2020 (in Portuguese). BRISA Concessão Rodoviária, S.A, published on 22th April 2020, retrieved from https://web3.cmvm.pt/sdi/emitentes/docs/FR75326.pdf, on 27th July 2020.
International Transport & Forum Urban Mobility System Upgrade. Corporate Partnership Board Report (OECD/ITF, 2015).
Statistics Portugal. Estatísticas dos Transportes e Comunicações 2018 (in Portugesse) (Instituto Nacional de Estatística, Lisbon, Portugal, 2019).
Statistics Portugal. Mobilidade e funcionalidade do território nas Áreas Metropolitanas do Porto e de Lisboa: 2017 (in Portugesse) (Instituto Nacional de Estatística, Lisbon, Portugal, 2018).
PORDATA, 2020. População residente: total e por grandes grupos etários (in Portuguese). Available at https://www.pordata.pt/DB/Municipios/Ambiente+de+Consulta/Tabela, retrieved 28.72020.
Fuertes, E. et al. A longitudinal analysis of associations between traffic-related air pollution with asthma, allergies and sensitization in the GINIplus and LISAplus birth cohorts. PeerJ. 1, e193 https://doi.org/10.7717/peerj.193 (2013).
Ranzi, A. et al. Exposure to air pollution and respiratory symptoms during the first 7 years of life in an Italian birth cohort. Occup Environ Med. 71 (6), 430–436 https://doi.org/10.1136/oemed-2013-101867 (2014).
Nieuwenhuijsen, M. J. & Khreis, H. Car-free cities: pathways to healthy urban living. Environ Int. 94, 251–262 https://doi.org/10.1016/j.envint.2016.05.032 (2016).
European Environment Agency. Air quality in Europe 2019. EEA Report 10/2019 (European Environment Agency, Luxembourg, EEA, 2019a).
Conceição, R. et al. Saharan dust transport to Europe and its impact on photovoltaic performance: A case study of soiling in Portugal. Sol. Energy. 160, 94–102 https://doi.org/10.1016/j.solener.2017.11.059 (2018).
Monteiro, A., Fernandes, A. P., Gama, C., Borrego, C. & Tchepel, O. Assessing the mineral dust from North Africa over Portugal region using BSC–DREAM8b model. Atmos Pollut Res. 6 (1), 70–81 https://doi.org/10.5094/APR.2015.009 (2015).
Health Effects Institute (HEI). State of Global Air 2019. Special Report (Health Effects Institute, Boston, MA, 2019).
Frey, H. C. Trends in onroad transportation energy and emissions. J Air Waste Manag Assoc. 68 (6), 514–563 https://doi.org/10.1080/10962247.2018.1454357 (2018).
Hooftman, N., Messagie, M., Van Mierlo, J. & Coosemans, T. A review of the European passenger car regulations – Real driving emissions vs local air quality. Sustain Energy Rev. 86, 1–21 https://doi.org/10.1016/j.rser.2018.01.012 (2018).
Khreis, H. et al. The health impacts of traffic-related exposures in urban areas: Understanding real effects, underlying driving forces and co-producing future directions. Journal of Transport and Health. 3 (3), 249–267 https://doi.org/10.1016/j.jth.2016.07.002 (2016).
Jaff, D. A. et al. (2018). Scientific assessment of background ozone over the U: Implications for air quality management. Elementa 6(1), 56. https://doi.org/10.1525/elementa.309.
Lin, M., Horowitz, L. W., Payton, R., Fiore, A. M. & Tonnesen, G. S. Quantifying the roles of rising Asian emissions, domestic controls, wild-fires, and climate. Atmos Chem Phys. 17, 2943–2970 https://doi.org/10.5194/acp-17-2943-2017 (2017). US surface ozone trends and extremes from 1980 to 2014
Fiore, A. M., Naik, V. & Leibensperger, E. M. Air quality and climate connections. J Air Waste Manag Assoc. 65 (6), 645–685 https://doi.org/10.1080/10962247.2015.1040526 (2015).
Jaffe, D. A. & Zhang, L. Meteorological anomalies lead to elevated O3 in the western U.S. in June 2015. Geophys. Res. Lett. 44 (4), 1990–1997 https://doi.org/10.1002/2016GL072010 (2017).
Shen, L. & Mickley, L. J. (2017). Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns. Proceedings of National Academy of Science of the United States of America 114: 2491–2496. https://doi.org/10.1073/pnas.1610708114
European Environment Agency. Greenhouse gas emissions from transport in Europe (European Environment Agency, Luxembourg, EEA, 2019b).
Statistics Portugal. Average temperatura of air (°C) (in Portuguesse) (Instituto Nacional de Estatística, Lisbon, Portugal. avaibale from 2020b).
Bhalla, K. et al. (2014). Transport for Health: The Global Burden of Disease From Motorized Road Transport. World Bank Group, Washington, DC. Available at http://documents.worldbank.org/curated/en/2014/01/19308007/transport-health-global-burden-disease-motorized-road-transport, accessed 30.7. 2020.
Chambliss, S. E., Silva, R., West, J. J., Zeinali, M. & Minjares, R. Estimating source-attributable health impacts of ambient fine particulate matter exposure: Global premature mortality from surface transportation emissions in 2005. Environ Res Lett. 9 (10), 104009 https://doi.org/10.1088/1748-9326/9/10/104009 (2014).

Table 1. Air pollution monitoring network in Portugal: summary of zone- and emission influence-specific monitoring sites in each region

Region	Stations n (%)	Type n (%)
		Rural			Suburban			Urban
		Background	Traffic	Industrial	Background	Traffic	Industrial	Background	Traffic	Industrial
North	22 (32)^a	3 (14)^b	–	–	6(27)	–	1(5)	5(23)	6(27)	1(5)
Centre	9 (13)	4 (44)	–	–	2(22)	–	–	1(11)	2(22)
Lisbon TV	24 (35)	3 (13)	–	–	–	–	1(4)	13(54)	5(21)	2(8)
Alentejo	5 (7)	2(40)	–	1(20)	1(20)	–	–	–	–	1(20)
Algarve	4 (6)	1(25)	–	–	–	–	–	2(50)	1(25)	–
Madeira	3 (4)	1 (33)	–	–	–	–	–	1(33)	1(33)	–
Azores	1 (2)	1	–	–	–	–	–	–	–	–
Total	68	15	–	1	9	–	2	22	15	4

Note: ^a% considering the whole territory

^bindicated % is estimated considering of abundance of a station/type in each district

Note: depending on the density and distribution of buildings, stations are classified as the folloing: rural – all other areas; suburban – largely built-up; urban area urban – continuously built-up urban area; background stations – pollution levels are representative of the average exposure of the general population or vegetation; traffic – situated in a close proximity to a single major road; industrial stations – situated in close proximity to an industrial area or an industrial source (EEA, 2019a)

No competing interests reported.

Supplementarymaterial.docx

Download PDF

Editorial decision: Major revision
23 Jul, 2021
Reviews received at journal
24 Jun, 2021
Reviewers agreed at journal
18 Jun, 2021
Reviews received at journal
31 May, 2021
Reviewers agreed at journal
13 May, 2021
Reviewers agreed at journal
13 May, 2021
Reviewers invited by journal
13 May, 2021
Editor assigned by journal
28 Apr, 2021
Editor invited by journal
27 Apr, 2021
Submission checks completed at journal
27 Apr, 2021
First submitted to journal
20 Apr, 2021

You are reading this latest preprint version

Air Pollution Impacts During 2020 COVID-19 Pandemic: Emphasis on Urban, Suburban and Rural Zones

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material And Methods

3. Results And Discussion

3.1 Air pollution monitoring network

3.2 Traffic data

3.3 Air pollution data: 2019 vs. 2020

3.3.1. Particulate matter

3.3.2 Gaseous pollutants

Conclusion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1