Changes in air quality in Poland in 2020 in the context of the COVID-19 pandemic: spatial and seasonal analysis

Changes in air quality in Poland in 2020 in the context of the COVID-19 pandemic: spatial and seasonal analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Changes in air quality in Poland in 2020 in the context of the COVID-19 pandemic: spatial and seasonal analysis Joanna Strużewska, Aleksander Norowski, Grzegorz Jeleniewicz, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5888206/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The COVID-19 pandemic, which began in 2019, compelled governments worldwide to implement various measures to limit the spread of the virus, including restrictions on mobility and economic activity. These restrictions directly impacted air pollutant emissions, typically linked to heavy road traffic, industry, air transport, and other forms of human activity. In Poland, as in many other countries, a notable change in air quality was observed in 2020, which became the focus of numerous studies. This article analysed the impact of the pandemic on air pollution in Poland in 2020, comparing data from this period with that of the previous year, 2019. The study was based on data from the General Inspectorate for Environmental Protection (GIOŚ), which included measurements of the concentrations of particulate matter (PM10, PM2.5), nitrogen dioxide (NO₂), and benzo(a)pyrene. The analysis results indicated an evident reduction in pollutant concentrations in 2020 compared to 2019. This decrease was especially noticeable during lockdowns, when transport, industry, and other emission sources faced restrictions. The pollution reduction was most pronounced in urban areas, where transport and economic activity were most concentrated. Another important element of the study was spatial differentiation, which considered differences in pollution levels between large cities and rural areas. It is also worth noting that the pandemic's impact on air quality was seasonal, resulting from meteorological conditions such as temperature, humidity, and wind speed. These conditions were crucial for the spread of pollutants and their concentration in different parts of the year. In addition, the article emphasises the role of transport, especially road transport, in pollutant emissions, indicating the impact that reducing the number of vehicles on the roads had on improving air quality. Findings highlight the substantial impact of reduced human activity on air pollutant levels during pandemic restrictions. However, it also draws attention to the need for further actions to improve air quality in the long term. The conclusions from this study can provide a basis for developing more effective environmental policies that consider both health and ecological aspects of air pollutant emissions. PM10 PM2.5 COVID-19 air pollution NO2 B(a)P Poland Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction The first media reports of disease cases caused by a previously unknown type of coronavirus, SARS-CoV-2, emerged in November 2019. Until January 2020, cases primarily occurred in Wuhan, located in central China, and gradually spread throughout the country and then to other nations. On 30 January 2020, the WHO Emergency Committee advised declaring a public health emergency of international concern. In the latter half of February 2020, outbreaks of infections emerged in Europe, particularly in Italy. On 13 March 2020, the WHO announced that Europe was the epicentre of the pandemic caused by the SARS-CoV-2 coronavirus. Since 4 March 2020, infections have also been reported in Poland. Most published studies on pollution reduction have examined various regions of Asia and Latin America (e.g., Broomandi et al., 2020 ; Dantas et al., 2020 ; Mahato et al., 2020 ; Siciliano et al., 2020 ; Velásquez and Lara, 2020 ; Zambrano-Monserrate and Ruano, 2020 ; Shi and Brasseur, 2020 ). In Europe, the analyses have primarily concentrated on Western European nations. Based on measurements from monitoring stations in the Barcelona region of Spain, Tobias et al. (2020) reported decreases of 45–51% in black carbon and NO2 concentrations and 28–31% in PM10 concentrations. An increase in the daily maximum ozone concentration from 33–57% was also reported. In Spain, the introduced restrictions were treated as a basis for quantifying the possible decrease in NO 2 pollution due to reduced car traffic. In the case of the two largest cities in Spain (Madrid and Barcelona), the reductions in NO 2 concentrations were 62% and 50% (Baldasano, 2020 ). The impact of economic restrictions was also assessed using satellite data, the total NO2 content in the cross-section of the atmosphere. In the work of Bauwens et al. ( 2020 ), using TROPOMI and OMI observations, there was a significant decrease in NO 2 concentration in the tropospheric column over Western Europe from 20–38%. In addition, a study by Putaud et al. ( 2023 ), covering many European countries, showed significant reductions in concentrations of particulate matter (PM10 and PM2.5), especially in urban agglomerations, as a result of reductions in transport and industrial activity. However, the authors pointed out that there was considerable regional variation due to local emission sources and meteorological conditions. A systematic review by Bakola et al. ( 2022 ) for Europe and North America showed consistent results for decreases in NO₂, PM10 and PM2.5 concentrations during lockdown periods. They highlighted the particular impact of traffic and industrial reductions on improving urban air quality and the need for further research on the sustainability of these changes and their relevance to environmental policies. Sicard et al. ( 2020 ) conducted a comparative analysis for five European cities (Nice, Marseille, Milan, Madrid, Budapest), showing NO₂ reductions in excess of 50% and more variable changes for particulate matter, depending on local circumstances. Filonchyk et al. (2021) examined the impact of economic restrictions on air quality in Poland. The research used satellite observations of the aerosol optical thickness (AOD) from the MODIS instrument and the NO 2 tropospheric column observed by the OMI instrument. The quantitative assessment of changes in air pollution also used concentrations of PM2.5, PM10, NO 2, and SO 2 from air quality monitoring stations in five major cities across the country. Ground and satellite data showed a reduction in pollution from March to May, compared to the same months in 2018 and 2019. April and May 2020 saw the most significant decrease in concentrations at monitoring stations - in the case of PM2.5 in April 2020, from 11.1–26.4% and in May from 8.7 to 21.1% compared to 2019. PM10 reductions ranged from 8.6–33.9% in April 2020 and from 8.5–31.5% in May, respectively, compared to the same months in 2019. The European Environment Agency report also referred to the impact of economic restrictions on European pollution levels. Data from the European Environment Agency (EEA) confirmed significant decreases in air pollution concentrations - in particular nitrogen dioxide (NO 2 ) concentrations - mainly due to restricted movement and other restrictions, especially in large cities (EEA, 2020 ). The conclusions from the work confirm the impact of economic limits, especially travel restrictions on NO 2 concentrations and a relatively small impact on PM10 dust concentrations, among others, due to specific meteorological conditions in March 2020, which were conducive to the accumulation of pollutants. European experience with the rapid spread of the COVID-19 epidemic meant that shortly after the first cases were detected in Poland, steps were taken to limit the spread of this virus. Not only were decisions made to recommend more significant attention to hygiene, disinfection, and covering the mouth and nose, but also restrictions on cross-border traffic, limited services and trade, and closed places of entertainment and culture. Regulations of the Council of Ministers or the Minister of Health most often introduced these restrictions. Many sectors of the economy have been forced to modify their operations and service delivery. A major change has been the widespread introduction of remote learning and remote work. The aim of this study was to assess the impact of the COVID-19 pandemic on air quality in Poland in 2020 by analysing changes in concentrations of selected atmospheric pollutants (PM10, PM2.5, NO₂ and benzo(a)pyrene) compared to 2019. The analysis covered both spatial variation, taking into account individual provinces and types of measurement stations (urban, traffic and non-urban), and seasonal variation, broken down by quarters of the year. Particular attention was paid to the periods of strict pandemic restrictions (March-May and October-December 2020), as well as to the potential impact of meteorological conditions, such as temperature and precipitation, on observed concentrations. The results are presented in the form of tabular summaries and maps illustrating the spatial variation of changes, allowing for a comprehensive assessment of the impact of pandemic restrictions on the state of air quality in Poland. 2. Stages and nature of pandemic-related restrictions in Poland 2.1 The first wave of the pandemic The first wave of the COVID-19 pandemic in Poland began on 12 March 2020, with the declaration of an epidemic emergency. Initial restrictions included the closure of schools, nurseries, restaurants (limited to takeaway), shopping malls, and cultural and fitness facilities. Public gatherings over 50 people were banned. From 24 March, movement was limited to essential activities such as work, shopping, and medical needs. Public transport capacity was reduced, assemblies were banned, remote work was advised, and air travel was suspended (Regulation of the Minister of Health of 20 March 2020). On 31 March, stricter measures were introduced: limits on customers in shops, special shopping hours for seniors, and the closure of hotels, personal care services, and access to public spaces. From 9 April, wearing masks in public became mandatory, and all previous restrictions remained in force (Act of 31 March 2020, item 568). 2.2 Lifting restrictions As daily infection numbers began to decline in mid-April, the Polish government initiated a phased plan to lift restrictions. The first phase began on 20 April, allowing more people in shops and restoring access to green areas. Restrictions on sports were lifted shortly after, with venues reopening in early May and professional leagues resuming by the end of that month. The second phase, introduced on 4 May, allowed shopping malls and large stores to reopen with occupancy limits (Act of 31 March 2020, item 568). Nurseries and kindergartens resumed on 6 May, and hotels reopened, excluding leisure facilities like pools and gyms. Cultural institutions also resumed activity. From 18 May, hairdressers, beauty salons, restaurants, and cafés reopened under sanitary protocols, and public transport capacity was increased. The final phase began on 30 May, lifting face-covering rules in open spaces and removing most limits in shops, restaurants, and public venues. Events with up to 150 participants were permitted, and facilities such as pools, gyms, playrooms, and amusement parks reopened. Fairs, exhibitions, and congresses were also allowed to resume. 2.3 Second wave of the pandemic On 17 October 2020, Poland introduced a regional sanitary regime with yellow and red zones, depending on the local infection rate (Ordinance of the Council of Ministers of 6 November 2020, item 1972). Just a few days later, on 23 October, the entire country was classified as a red zone, and strict nationwide restrictions were reinstated — similar to those from the first wave. Remote learning was introduced for grades 4–8, remote work was recommended, and sanatoriums, restaurants, and public gatherings were limited. Children under 16 could leave home only under adult supervision during school hours. Cemeteries were closed between 30 October and 2 November (Ordinance of the Council of Ministers of 30 October 2020, item 1917). In early November, restrictions were extended to include remote learning in grades 1–3, closure of cultural institutions, and limitation of shopping malls to essential services (e.g. groceries, pharmacies, construction stores). Hotels were closed, except for business-related stays. Overall, two main periods of strict restrictions occurred in 2020: March–April and October–December. While the summer months brought temporary easing, the autumn surge in infections led to a rapid nationwide return to strict measures. 3. Data and method of analysis The study was based on data from the National Air Quality Monitoring Network, managed by the Chief Inspectorate for Environmental Protection (GIOŚ). Measurements of concentrations of particulate pollutants (PM10 and PM2.5), nitrogen dioxide (NO₂) and benzo(a)pyrene (B(a)P) were analysed in accordance with the requirements of Directive 2008/50/EC and relevant national air quality legislation. Data came from urban background, traffic and non-urban measurement stations located throughout Poland (Fig. 1). Meteorological data used to support the interpretation of the results, including temperature anomalies and circulation conditions, were obtained from the Institute of Meteorology and Water Management – National Research Institute (IMGW-PIB). The comparative analysis included data from 2019 and 2020, and additionally a multi-year background from 2016–2020 was included to assess the context of long-term changes in concentrations. In order to identify the impact of the COVID-19 pandemic on air quality, annual and quarterly average pollutant concentrations were collated, analysing spatial (at the level of provinces and individual stations) and seasonal variability. Particular attention was paid to the periods of the most stringent socio-economic restrictions (March-May and October-December 2020), which were associated with restrictions on mobility and activities of many economic sectors. The results are presented in the form of tables showing the differences in concentrations between the years analysed on a provincial and quarterly basis, and maps showing the spatial variability of changes in concentrations. An analysis of changes depending on the type of measuring station was presented separately, allowing the influence of local emission sources, such as road transport or municipal and household emissions, to be taken into account. Dolnośląskie - A diverse area in terms of terrain - the south is dominated by the Sudetes Mountains with the highest peak of Śnieżka (1 602 m), while the north is made up of lowlands and river valleys (mainly the Oder). The climate is moderate, with higher precipitation and lower temperatures in the mountainous areas. Kujawsko-pomorskie - Mainly lowland area, covering part of the Pomeranian Lake District and the Toruń-Bydgoska Basin. A temperate transitional climate prevails, with little thermal and rainfall variation and relatively frequent temperature inversions. Lubelskie – Diverse landscape - from the Lublin Uplands and Roztocze in the south to the plains of Polesie Lubelskie and river valleys (e.g. of the Bug and Vistula rivers) in the north. Continental climate, with a high number of days with frost, less precipitation and a greater temperature amplitude. Lubuskie – Mainly lowland, with numerous forest areas and lakes. Sand and glacial plains predominate. Mild maritime climate with fairly even precipitation and moderate winters. Łódzkie – Lowland and upland areas, without distinct mountain forms - dominated by the Łódzka Plain and the Łódzka Upland. Transitional climate, with high variability of weather conditions and relatively short winter period. Małopolskie – Distinctly diversified landforms - from lowlands in the northern part of the region to the Carpathian Mountains (Tatra Mountains, Beskidy Mountains, Gorce Mountains) in the south. Mountain climate in the Podhale region, with low temperatures and a large number of days with snow cover. In the central part - moderate continental climate. Mazowieckie – Predominantly lowland (Mazowiecka Lowland), with numerous river valleys (e.g. of the Vistula, Narew and Bug rivers). Transitional climate with a continental trend - winters relatively cool and summers warm, with average precipitation. Opolskie – Slightly undulating terrain, comprising fragments of the Silesian Upland and the Sudeten Foreland. In the south there are fragments of the Opawskie Mountains. Moderate climate, with local influence of mountain conditions in the southern part. Podkarpackie – Region strongly diversified topographically - the southern part is occupied by the Carpathian Mountains (Bieszczady, Beskid Niski), and the northern part by uplands and plains. Continental climate, cooler in the mountains, with a high number of frosty days and high precipitation in the foothills. Podlaskie – Mainly lowland and flat, with extensive forest areas (e.g. Białowieża Forest). Continental climate - lowest average annual temperatures in Poland, long winters, moderate precipitation. Pomorskie – Varied - from the Baltic coast, through the Kashubian Lake District, to uplands and moraine hills. Maritime climate, with mild winters, cool summers and high humidity. Śląskie – Heavily urbanised and diverse - includes the Silesian Lowlands, the Silesian Uplands and the Beskids. The south of the region is a mountainous area (Silesian and Zywiec Beskids). Transitional to mountainous climate, with marked differences in temperature and precipitation depending on altitude. Świętokrzyskie – Characteristic relief - dominated by the Świętokrzyskie Mountains and Kielce Upland. A region with a temperate, transitional climate with local continental features. Warmińsko-mazurskie – Lakeland and lowland region with numerous lakes, forests and sand plains. A cooler climate than the national average, with long winters and moderate rainfall. Wielkopolskie – Predominantly flat and lowland, with some moraine hills. Temperate climate, drier than the national average, with pronounced continental influences. Zachodniopomorskie – Lowland and coastal area, including a strip of the Baltic coast and numerous lakes. Maritime climate - mild, with a high number of cloudy days, moderate rainfall and short winters. 4. Analysis of results 4.1 Spatial distribution of concentration anomalies The differences between the concentrations in 2020 and 2019 were calculated for the individual provinces to address the spatial variability of concentrations. Tables 1 , 2 , 3 , and 4 present the average differences between the years and quarters. In the case of PM10 concentrations in 2020 compared to 2019, there was a reduction on average across the country - the smallest in the Świętokrzyskie Voivodship (-0.06 µg/m 3 ), the largest in the Podkarpackie Voivodship (-3.52 µg/m 3 ). A concentration increase was shown only for Podlaskie Voivodship (5.45 µg/m 3 ). The decreases in the first quarter are mainly due to important differences in February, which was anomalously warm, and no restrictions had yet been introduced in Poland. The most important decrease in concentrations in the first quarter occurred in the Silesian Voivodship (-13.52 µg/m 3 ), as well as in the Opolskie and Podkarpackie Voivodship (-9.4 µg/m 3 and − 9.86 µg/m 3 ), respectively. In the second quarter, the values of decreases are smaller and concern other voivodship - the largest reduction occurred in the Pomorskie (-7.11 µg/m 3 ), Warmińsko-Mazurskie (-7.6 µg/m 3 ) and Zachodniopomorskie (-6.47 µg/m 3 ) Voivodship. The third quarter was characterised by relatively small differences (except the Małopolskie Voivodship, where concentrations decreased by -2.53 µg/m 3 ). The fourth quarter was dominated by a downward trend in PM10 concentrations in 2020, resulting mainly from important decreases in October. The observed changes in PM10 concentrations in 2020 compared to 2019 can be explained by a combination of environmental and socio-economic factors. Meteorological conditions were of particular importance – February 2020 was exceptionally warm (average temperature in many regions over 3°C higher than normal), which resulted in reduced consumption of solid fuels in the household sector. In addition, in the period from March to May, mobility restrictions related to the COVID-19 pandemic were introduced in Poland, which significantly reduced road traffic – a source of secondary dust emissions and primary emissions from transport. In some regions, the observed decrease could also have been supported by local low emission reduction programs, e.g. under the “Clean Air” program. It is also worth noting that in the winter of 2019/2020 there was no heavy snowfall or the need to intensively sprinkle roads with sand and salt, which reduced the phenomenon of dust resuspension from the road surface. Table 1 Differences in PM10 concentrations (in µg/m 3 ) between concentrations in 2020 and 2019 (2020 − 2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Voivodship Year I-III IV-VI VII-IX X-XII Dolnośląskie -2.80 -6.15 -3.67 -0.45 -0.94 Kujawsko-pomorskie -2.59 -3.77 -5.94 0.70 -1.35 Lubelskie -1.62 -1.83 -1.53 -0.62 -2.49 Łódzkie -3.27 -5.97 -2.77 -0.70 -3.63 Lubuskie -2.29 -6.51 -4.60 1.13 0.81 Małopolskie -3.44 -6.05 -3.19 -2.53 -1.97 Mazowieckie -1.28 -3.61 -2.70 1.25 -0.06 Opolskie -3.44 -9.40 -3.49 0.43 -1.32 Podlaskie 5.46 9.48 -3.02 2.51 12.87 Podkarpackie -3.52 -9.86 -2.26 -0.77 -1.20 Pomorskie -2.01 -2.66 -7.11 1.29 0.44 Świętokrzyskie -0.06 -0.27 0.39 0.33 -0.71 Śląskie -4.85 -13.52 -1.71 0.04 -4.22 Warmińsko-mazurskie -2.54 -4.43 -7.60 0.68 1.20 Wielkopolskie -3.46 -6.18 -5.14 -0.01 -2.53 Zachodniopomorskie -2.75 -4.86 -6.47 0.74 -0.42 The spatial distribution of the differences between the annual average PM10 concentrations in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 2–3 µg/m 3 on average (Fig. 2 .). An increase in concentrations compared to the previous year occurred at several stations in the Podlaskie, Lubelskie, Mazowieckie, Świętokrzyskie and Małopolskie Voivodship. It should be noted that in Podlaskie Voivodship, the analyses are based on measurements from only one station. This explains the different characteristics of the interannual variability of concentrations in Podlaskie Voivodship, as described earlier. The differences in concentrations in the second quarter of 2020 relative to 2019 are slightly more important in absolute value than the annual average change. For selected provinces, changes in PM10 concentrations are particularly pronounced: in the Silesian province, the average decrease was − 4.85 µg/m³, which, given the level of around 34 µg/m³ in 2019, means a decrease of around 14%. In turn, the increase in the Podlaskie province (+ 5.46 µg/m³) compared to the average values from 2019 (approx. 17 µg/m³) constitutes an increase of over 30%, which indicates a local deviation from the national trend and confirms the need for cautious interpretation of results based on data from a single station. When comparing 2020 and 2019 in terms of PM2.5 concentrations, on average, across the country, there was a decrease - the smallest difference was in the Podlaskie Voivodship (-0.07 µg/m 3 ), the largest in the Podkarpackie Voivodship (-4.67 µg/m 3 ). The decreases in the first quarter are mainly due to important differences in February, which was much warmer than the previous year and in which no restrictions had yet been introduced in Poland. The most important decrease in concentrations in the first quarter occurred in the Podkarpackie Voivodship (-13.35 µg/m 3 ), as well as in the Śląskie and Opolskie Voivodship (-10.25 µg/m 3 and − 8.01 µg/m 3 ), respectively. In the second quarter, the values of decreases are smaller and concern other provinces - the most important reduction occurred in the Zachodniopomorskie Voivodship (-4.72 µg/m 3 ), Pomorskie Voivodship (-4.70 µg/m 3 ) and Warmińsko-Mazurskie Voivodship (-4.00 µg/m 3 ). The third quarter was characterised by relatively small differences (except for the Łódzkie Voivodship: -2.33 µg/m 3 and the Pomorskie Voivodship: -3.6 µg/m 3 ). In the fourth quarter, a downward trend in PM2.5 concentrations prevailed in 2020, resulting mainly from important decreases in October; however, increases prevailed in December. The reductions in PM2.5 concentrations in 2020 compared to 2019 had similar causes as for PM10 – a mild winter, pandemic restrictions and reduced transport and economic activity. These declines are most visible in the southern provinces, where the share of low emissions is particularly significant. The effects of the lockdown were also visible in the declines recorded at transport stations, which indicates a significant share of the transport sector in generating PM2.5 in urban areas. Table 2 Differences in PM2.5 concentrations (in µg/m 3 ) between concentrations in 2020 and 2019 (2020 − 2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Voivodship Year I-III IV-VI VII-IX X-XII Dolnośląskie -1.72 -4.41 -1.91 -0.06 -0.48 Kujawsko-pomorskie -2.16 -4.00 -3.48 0.84 -1.99 Lubelskie -0.66 -1.35 0.01 -0.42 -0.87 Łódzkie -3.30 -6.25 -1.67 -2.33 -2.97 Lubuskie -2.03 -4.47 -3.01 -0.77 0.11 Małopolskie -1.94 -4.58 -2.28 -2.04 1.15 Mazowieckie -2.64 -5.39 -3.08 -0.53 -1.54 Opolskie -1.27 -8.01 -0.82 1.50 2.25 Podlaskie -0.07 0.27 -2.03 0.49 1.00 Podkarpackie -4.67 -13.35 -2.08 -0.69 -2.56 Pomorskie -1.95 -3.47 -4.70 3.6 2.20 Świętokrzyskie -0.51 -1.94 0.93 -0.66 -0.37 Śląskie -3.07 -10.25 -0.91 -0.26 -0.87 Warmińsko-mazurskie -1.63 -3.38 -4.00 -0.04 0.91 Wielkopolskie -2.42 -5.64 -2.72 -1.74 0.40 Zachodniopomorskie -2.84 -5.10 -4.72 0.08 -1.63 The spatial distribution of the differences between annual average PM2.5 concentrations in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 3–5 µg/m 3 on average (Fig. 3 .). The highest reductions, up to -6.5 µg/m 3 , occurred at stations located mainly in the southern and central parts of the country. An increase in concentrations about the previous year was recorded at several stations in the Podlaskie, Lubelskie, Świętokrzyskie, Opolskie and Małopolskie Voivodship. The differences in concentrations in the second quarter of the year are greater in absolute terms. Importantly, the reduction is lower than the annual average in the southern part of the country. Also, concentrations increased at more stations in the second quarter of 2020. This indicates that the quarantine period did not importantly reduce PM2.5 concentrations between 2020 and 2019. For example, in the Podkarpackie province, the average annual decrease in PM2.5 was − 4.67 µg/m³ – which, compared to the base value of about 23 µg/m³, means a reduction of over 20%. In the Silesian province, the decrease was − 3.07 µg/m³ (about 11%), while in the Opole province it was only − 1.27 µg/m³, which may indicate lower effectiveness of local measures or a greater share of industrial sources, less susceptible to changes in population mobility. In the case of nitrogen dioxide concentrations, on average in the country, there was a reduction - the smallest in the Podlaskie Voivodship (-0.33 µg/m 3 ), the largest in the Małopolskie Voivodship (-3.44 µg/m 3 ). Only the Lubuskie Voivodship showed a concentration increase (1.06 µg/m 3 ). In the first quarter, the decreases were mainly due to important differences in February. It was much warmer in 2020 than 2019, and no restrictions had yet been introduced in Poland. Concentrations decreased most importantly in the first quarter in the Śląskie Voivodship (-4.95 µg/m 3 ) and the Wielkopolskie, Świętokrzyskie, and Opolskie Voivodship (-3.67 µg/m 3 , -3.47 µg/m 3, and − 3.40 µg/m 3 , respectively). In the second quarter, the values of decreases are smaller and concern other provinces - the largest reduction occurred in the Małopolskie Voivodship (-4.12 µg/m 3 ) and Pomorskie Voivodship (-3.20 µg/m 3 ). The third quarter was characterised by relatively small differences (except the Lubuskie Voivodship: -2.23 µg/m 3 and the Małopolskie Voivodship: -2.17 µg/m 3 ). In the fourth quarter, nitrogen dioxide concentrations tended to decrease in 2020, mainly due to large drops in October; only in the Lubuskie Voivodship did concentrations increase by 2.02 µg/m 3 . In the case of NO₂, the significant decreases in concentrations in 2020 can be largely attributed to road traffic restrictions introduced in March and April 2020. Since the main source of NO₂ in urban areas is road transport, its reduction directly translated into lower levels of this pollutant – especially in cities. Meteorological conditions, including favourable ventilation in spring 2020, may have had a smaller impact. Table 3 Differences in nitrogen dioxide concentrations (in µg/m 3 ) between concentrations in 2020 and 2019 (2020 − 2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Voivodship Year I-III IV-VI VII-IX X-XII Dolnośląskie -1.35 -2.43 -1.17 0.10 -1.91 Kujawsko-pomorskie -1.29 -0.18 -2.02 -0.74 -2.23 Lubelskie -1.39 -0.86 -0.69 -1.59 -2.41 Łódzkie -0.87 -1.29 -1.07 0.86 -1.99 Lubuskie 1.06 -2.06 2.04 2.23 2.02 Małopolskie -3.44 -2.71 -4.12 -2.17 -4.79 Mazowieckie -2.06 -1.92 -2.18 -1.47 -2.67 Opolskie -2.38 -3.40 -1.39 -1.51 -3.22 Podlaskie -0.33 1.57 -1.22 -0.20 -1.48 Podkarpackie -1.61 -1.27 -0.80 -1.44 -2.92 Pomorskie -1.23 0.29 -3.20 0.61 -2.64 Świętokrzyskie -2.28 -3.47 -0.14 -1.13 -4.36 Śląskie -2.64 -4.95 -1.88 -0.61 -3.12 Warmińsko-mazurskie -0.95 -1.57 -1.18 -0.32 -0.72 Wielkopolskie -2.21 -3.67 -0.82 -0.88 -3.45 Zachodniopomorskie -0.56 -1.36 -1.67 1.96 -1.15 The spatial distribution of the differences between the annual average NO concentration 2 in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 2–5 µg/m 3 on average (Fig. 4 .). An increase in concentrations compared to the previous year occurred at several stations in the following voivodship: Lubelskie, Mazowieckie, Podkarpackie, Małopolskie, Kujawsko-Pomorskie, Lubuskie and Zachodniopomorskie. The differences in concentrations in the second quarter of the year are spatially differentiated. Slightly more locations show a positive difference, indicating higher concentrations in 2020, while at other places, the reduction in concentrations in 2020 relative to 2019 is higher than the annual average. In the Małopolskie province, the decrease in NO₂ concentrations in 2020 reached − 3.44 µg/m³, which in relation to the base level of approx. 25 µg/m³ means a reduction of 13.8%. The greatest relative decreases were recorded in provinces with a large share of urban transport and intensive traffic (Śląskie, Wielkopolskie, Mazowieckie). Analysis of benzo(a)pyrene concentrations shows that, on average across the country, concentrations increased and decreased between 2020 and 2019. The smallest concentration increase occurred in the Małopolskie and Mazowieckie Voivodship (0.02 ng/m 3 ), the largest in the Podlaskie Voivodship (0.62 ng/m 3 ). In the case of decreases, the largest decrease in benzo(a)pyrene concentrations occurred in the Lubuskie Voivodship (-1.57 ng/m 3 ). In the first quarter, the reductions were mainly due to important differences in February, which was much warmer in 2020 than in 2019, and restrictions were not yet in place in Poland. The most important decrease in concentrations in the first quarter occurred in the Śląskie Voivodship (-4.05 ng/m 3 ) and also in the Lubuskie and Pomorskie Voivodship (-3.09 ng/m3 and − 2.94 ng/m 3 ), respectively. In the second quarter, the values of concentrations of benzo(a)pyrene increased; the highest increase occurred in the Voivodship Lubelskie (1.37 ng/m 3 ), Łódzkie (0.84 ng/m 3 ) and Pomorskie (0.83 ng/m 3 ). A decrease occurred only in the Lubuskie Voivodship (-0.52 ng/m 3 ). The third quarter was characterised by relatively small differences - concentrations in 2020 were mostly lower, except for the Warmińsko-Mazurskie Voivodship, where concentrations increased by 0.31 ng/m 3 . In the fourth quarter, in the majority of voivodship, there was a decreasing tendency of benzo(a)pyrene concentrations in 2020; the most important decrease concerned the Lubuskie Voivodship (-2.69 ng/m 3 ), whereas the highest increase occurred in the Dolnośląskie Voivodship (2.65 ng/m 3 ). Changes in benzo(a)pyrene concentrations did not have a clear direction, which may be due to the fact that the sources of this compound are closely related to the individual heating sector (burning of biomass and coal), which was subject to pandemic restrictions to a small extent. Increases noted in some regions (e.g. Podlaskie, Kujawsko-pomorskie) may result from local meteorological conditions (e.g. inversions) or changes in the structure of fuels used by households. Further analyses of correlation with local anti-smog policies are needed. Table 4 . Differences in benzo(a)pyrene concentrations (in ng/m 3 ) between concentrations in 2020 and 2019 (2020 - 2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Province Year I-III IV-VI VII-IX X-XII Dolnośląskie 0.53 -0.71 0.18 0.02 2.65 Kujawsko-pomorskie 0.08 0.53 0.45 0.01 -0.65 Lubelskie 0.38 1.61 1.37 -0.39 -1.08 Łódzkie -0.46 -0.50 0.84 -0.21 -1.99 Lubuskie -1.57 -3.09 -0.52 0.02 -2.69 Małopolskie 0.02 -1.28 0.48 -0.21 1.11 Mazowieckie 0.02 0.00 0.45 -0.20 -0.17 Opolskie -0.57 -2.38 0.02 -0.23 0.30 Podlaskie 0.62 1.37 0.24 -0.11 0.97 Podkarpackie - 0.08 -2.08 0.32 -0.08 1.53 Pomorskie -0.72 -2.94 0.83 -0.32 -0.47 Śląskie -0.88 -4.05 0.74 -0.08 -0.14 Warmińsko-mazurskie -0.31 -1.09 0.14 -0.08 -0.19 Wielkopolskie 0.13 -1.42 0.09 0.31 1.54 The spatial distribution of the differences between annual average benzo(a)pyrene concentrations in 2020 and 2019 for individual stations shows that in the predominant area of the voivodship of Podkarpackie, Śląskie, Opolskie, Łódzkie, Lubuskie, Pomorskie and Warmińsko-Mazurskie there was a reduction on average in the range of 0.5 - 1.0 ng/m 3 (Figure 5.). An increase in concentrations compared to the previous year occurred at stations in the following voivodship: Podlaskie, Mazowieckie, Lubelskie, Małopolskie, Dolnośląskie, Kujawsko-Pomorskie and Wielkopolskie. Differences in concentrations between 2020 and 2019 in the year's second quarter show an increase at most stations. 4.2 Change in concentrations at traffic, urban background and non-urban background stations Most stations measuring benzo(a)pyrene belong to a single type, so the following analysis has been carried out for PM10, PM2.5 and NO 2 . Where reference is made to "urban stations”, these are only urban background stations, excluding traffic stations, which form a separate category in the analysis. 4.2.1 PM10 About 2018, a decrease in annual mean PM10 concentrations was marked at all station types. The trend continued between 2019 and 2020 for traffic stations, while the trend was slightly weaker for the other station types. This may support the thesis of the impact of reduced travel in urban areas on the levels of PM10 concentrations measured within the range of influence of traffic routes. At the same time, this may result from reduced secondary lift due to a hot winter during which no sanding and salting of streets took place. The downward trend at non-urban stations is relatively the weakest (Fig. 6 .). The analysis of the variability of monthly PM10 concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at urban and traffic (urban) background type stations shows a slightly higher gradient than at non-urban stations (Fig. 7 ). Comparing 2020 and the average of the last 5 years, the most important difference in PM10 concentrations occurred at traffic stations, which may be related to the quarantine period and reduced car traffic in urban areas. The differences between PM10 concentrations in the second and fourth quarters of 2020 compared to the corresponding quarter of 2019 are shown in Table 5 . Differences are given for stations of different types - non-urban, suburban and urban (including traffic). Differences are also included for March, in the middle of which restrictions were introduced, and there was an increase in concentrations in 2020 compared to the previous year. The decrease in concentrations is more important in the second quarter of 2020 and weaker in the fourth quarter due to the increase in concentrations recorded in December and March 2020, marked increases in PM10 concentrations compared to 2019. Table 5 The difference in PM10 concentrations (in µg/m 3 ) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including traffic) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Type of area Year III IV - VI X - XII urban -3.59 3.35 -3.95 -1.58 suburban -1.93 8.02 -3.64 0.06 extra-urban -2.37 4.06 -4.46 -0.39 4.2.2 PM2.5 Since 2018, annual mean concentrations of PM2.5 at all station types have importantly decreased, although the trend has continued since 2017. The variability is very similar to PM10 (Fig. 8 ). The analysis of the variability of monthly average PM2.5 concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at urban and traffic (urban) background type stations shows a slightly greater gradient than at non-urban stations (Fig. 9 ). The highest difference in PM2.5 concentrations in 2020 compared to the average of the last 5 years occurred at traffic stations, which may be related to the quarantine period and reduced traffic in urban areas. Table 6 shows the differences between PM2.5 concentrations in the second and fourth quarters of 2020 and the corresponding quarter of 2019. Differences are also included for March, during which restrictions were introduced, and concentrations increased in 2020 compared to the previous year. Only suburban stations showed harmful concentration decreases in the fourth quarter for all three months. At urban background stations, concentrations in November and December of 2020 were higher than in the previous year. Table 6 The difference in PM2.5 concentrations (in µg/m 3 ) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including transport) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Type of area Year III IV - VI X - XII urban -2.57 2.55 -2.21 -0.66 suburban -3.15 5.12 -2.74 -3.43 extra-urban -1.57 2.16 -2.29 -0.40 4.2.3 NO 2 For NO 2 , the downward trend has continued since the beginning of the analysed period in 2016. While the differences are not important for non-urban stations, and a slight decrease has been recorded for urban background stations since 2018, the variability at traffic stations shows an apparent decline in values in 2020 (Fig. 10 ). The analysis of the variability of nitrogen dioxide concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at stations of the urban background and traffic (urban) type shows a greater gradient than at non-urban stations (Fig. 11 ). The highest difference in NO 2 concentrations in 2020 compared to the average of the last 5 years occurred at traffic stations, which may be related to the quarantine period and reduced traffic in urban areas. Table 7 shows the differences between NO 2 concentrations in the second and fourth quarters of 2020 compared to the corresponding quarter of 2019. It also includes the differences for March, in the middle of which restrictions were introduced, in which concentrations increased in 2020 compared to the previous year. The relatively important decrease in concentrations at urban and suburban stations in the fourth quarter is due to the reduction in October. Table 7 The difference in NO 2 (in µg/m 3 ) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including transport) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB) Type of area Year III IV - VI X - XII urban -2.06 0.13 -1.96 -3.14 suburban -1.34 0.94 -0.85 -1.49 extra-urban -0.67 0.68 -1.09 -0.11 5. Discussion The analysis conducted in Poland shows a decrease in the average annual concentrations of PM10, PM2.5, NO 2 , and benzo(a)pyrene since 2018. The introduction of restrictions related to the COVID-19 pandemic, such as lockdowns and quarantines, impacted road traffic, which could have contributed to reducing concentrations of these pollutants. However, the observations show that the impact of the pandemic on concentration reduction is unclear and varies depending on the region and measuring stations. A comparison of the results of the conducted studies with the results of the systematic review entitled "The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review" indicates consistency in the observations regarding the impact of the COVID-19 pandemic on air quality (Bakola et al.). In Poland and other countries in Europe and North America, a decrease in the concentrations of pollutants such as NO 2 , PM10 and PM2.5 was observed during the lockdown periods. Both cases emphasised that the pandemic restrictions had a particularly pronounced impact on reducing traffic and industrial pollution, confirmed by reducing these pollutant concentrations in cities. At the same time, both the studies in Poland and the systematic review point to the need for further research to better understand the long-term effects of the pandemic restrictions on air quality and to consider other emission reduction programmes. Ultimately, these results have important implications for air protection policy, emphasising the importance of reducing emissions from transport and industry to improve air quality. China also experienced important decreases in air pollution concentrations during the most stringent restrictions. In Poland, a reduction in PM10, PM2.5 and NO2 concentrations was observed, similar to Wuhan, where the average monthly air quality index (AQI) decreased by 33.9% compared to the period before the lockdown, and NO 2 concentrations decreased by 53.3%. Both studies indicated the reduction in traffic pollution as the main factor in reducing the levels of these pollutants (Lian et al.). Studies have also shown that lockdowns importantly impacted reducing air pollution levels. Still, the differences in the results indicate the complexity of emission processes and the need for further research and mathematical modelling to understand better the long-term effects of pandemic restrictions on air quality. A study published in Atmospheric Chemistry and Physics analyses the effects of COVID-19 lockdowns on PM2.5 and PM10 pollution in Europe (Putaud et al.). It shows that restrictions on mobility and industrial activity importantly reduced pollutant concentrations. The largest reductions were observed in urban areas, where road traffic was the primary source of emissions. However, regional differences were related to local emission sources and meteorological conditions, such as temperature and wind. The analysis highlights that the impact of lockdowns was evident in the transport sector. In the context of the obtained results, it is worth emphasizing the clear differentiation of the effects observed between the analysed pollutants. For NO₂, the main source of emissions of which is road transport, the decreases in concentrations were most visible during periods of limited mobility and concerned in particular communication stations in cities. In the case of benzo(a)pyrene, emissions are strongly related to the residential and municipal sector, which was not subject to significant restrictions during the pandemic. As a result, changes in B(a)P concentrations were less pronounced and more dependent on local conditions - e.g. meteorological conditions, fuel structure or intensity of individual heating sources. The differentiation in the responses of individual types of measurement stations also confirms that population mobility and reduced economic activity played a significant role. Communication stations showed the strongest decrease in NO₂, PM10 and PM2.5 concentrations during the lockdown periods, which clearly indicates the dominant impact of transport on the levels of these pollutants in urban areas. In the case of non-urban stations, the changes were less significant, which may indicate a lower importance of mobility and a greater share of diffuse sources (e.g. agriculture, biomass). The spatial differentiation of concentration changes (e.g. increases in B(a)P in north-eastern provinces, despite the nationwide downward trend) suggests that local emission conditions and meteorology could mask or amplify the effects of the pandemic. This suggests the need for further model analyses that will allow for better separation of the impact of pandemic restrictions from other factors - such as temperature, inversions, fuel consumption structure or locally implemented air protection programs. The conclusions from this analysis show that only in the case of substances strongly related to mobility and road traffic (NO₂, partially PM10 and PM2.5) the impact of the pandemic was significant and measurable on a national scale. In the case of substances of heating origin (B(a)P), the effect was more complex and local. 6. Conclusions Analysis of PM10, PM2.5, benzo(a)pyrene and nitrogen dioxide (NO₂) pollution concentrations indicates a continuation of the downward trend in 2016–2020, with the differences between 2019 and 2020 being smaller than between 2018 and 2019. The exceptions are individual months in which a concentration increase was observed in 2020 (e.g. March, September, and December for particulate matter and NO₂). An important decrease in concentrations in the winter months of 2020 (January and February) can be associated with a warmer winter compared to previous years. In turn, the greatest decrease in concentrations was recorded at communication stations, which suggests the impact of pandemic restrictions, such as reduced car traffic. The variability of concentrations across provinces and seasons shows that southern Poland experienced the highest reductions, particularly in the winter (February) and autumn (October) months. However, simultaneous actions related to air protection programmes, such as "Czyste Powietrze" or "Mój Prąd", and the development of renewable energy sources make it difficult to attribute the decreases to the COVID-19 pandemic unequivocally. At the same time, the analysis results allow for the formulation of specific conclusions regarding the impact of the COVID-19 pandemic on air quality in Poland. The most unequivocal effects of pandemic restrictions were observed in the case of nitrogen dioxide (NO₂), the concentrations of which dropped significantly during periods of reduced mobility, especially at transport stations in large cities. In the case of suspended particulate matter (PM10 and PM2.5), decreases in concentrations were observed during lockdowns, especially in the second quarter of 2020. Still, their scale was strongly dependent on meteorological conditions, the regional emission structure and the type of measuring station. For benzo(a)pyrene, the main source of which is individual heating systems, the effects of the pandemic were the least visible and did not show a uniform nationwide trend. A comparison of data from different types of stations shows that mobility restrictions had the greatest impact in locations dominated by transport emissions, and a smaller impact in non-urban areas and with dispersed emission sources. The results indicate that actions restricting economic activity and transport can lead to temporary improvement of air quality, but their impact is complex, dependent on local conditions and difficult to maintain without support from permanent environmental policies. This requires further, in-depth analyses, including emission and dispersion modelling, to separate meteorological and emission effects and to accurately indicate directions for effective long-term actions. Declarations Funding Statement: This work was carried out under Agreement No. GIOŚ/ZP/32/2021/DMŚ/NFOŚ dated February 15, 2021, financed by the National Fund for Environmental Protection and Water Management. Ethics, Consent to Participate, and Consent to Publish Declarations: Not applicable. Conflict of Interest Statement: The authors declare that they have no competing interests. Author Contribution JS and PJ wrote the main text of the manuscript, including the introduction and discussion.GJ prepared Figures 1-3 and Table 1 and took care of their formatting.MK performed the statistical analyses and provided data for the methodology section.MK, AN carried out the experimental study and collected the data that were used in the article.AS edited the text for grammar and style and prepared the print version.All authors reviewed the manuscript and made comments on the final version. References Bakola M, Carballo IH, Jelastopulu E, Stuckler D. The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review. European Journal of Public Health. 2022; 32(6):962-968. https://doi.org/10.1093/eurpub/ckac118 Baldasano JM. COVID-19 lockdown effects on air quality by NO2 in the cities of Barcelona and Madrid (Spain). Science of the Total Environment. 2020; 741. https://doi.org/10.1016/j.scitotenv.2020.140353 Bauwens M, Compernolle S, Stavrakou T, Müller J-F, van Gent J, Eskes H, et al. Impact of coronavirus outbreak on NO2 pollution assessed using TROPOMI and OMI observations. Geophysical Research Letters. 2020; 47:e2020GL087978. https://doi.org/10.1029/2020GL087978 Broomandi P, Karaca F, Nikfal A, Jahanbakhshi A, Tamjidi M, Kim JR. Impact of COVID-19 Event on the Air Quality in Iran. Aerosol Air Quality Research. 2020; 20:1793-1804. https://doi.org/10.4209/aaqr.2020.05.0205 Dantas G, Siciliano B, França BB, da Silva CM, Arbilla G. The impact of COVID-19 partial lockdown on the air quality of the city of Rio de Janeiro, Brazil. Science of the Total Environment. 2020; 729:139085. https://doi.org/10.1016/j.scitotenv.2020.139085 EEA, Report No 09/2020. Air quality in Europe - 2020 report. 2020; https://www.eea.europa.eu/publications/air-quality-in-europe-2020-report Filonchyk M, Hurynovich V, Yan H. Impact of COVID-19 lockdown on air quality in Poland, Eastern Europe. Environmental Research. 2020; 110454. https://doi.org/10.1016/j.envres.2020.110454 Lian X, Huang J, Huang R, Liu C, Wang L, Zhang T. Impact of city lockdown on the air quality of COVID-19-hit Wuhan city. Science of the Total Environment. 2020; 742:140556. https://doi.org/10.1016/j.scitotenv.2020.140556 Mahato S, Pal S, Ghosh KG. Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Science of the Total Environment. 2020; 730:139086. https://doi.org/10.1016/j.scitotenv.2020.139086 Putaud J-P, Pisoni E, Mangold A, Hueglin C, Sciare J, Pikridas M, et al. Impact of COVID-19 lockdowns in 2020 on particulate matter air pollution in Europe. Atmospheric Chemistry and Physics. 2023; 23:10145–10161. https://doi.org/10.5194/egusphere-2023-434 Shi X, Brasseur GP. The response in air quality to the reduction of Chinese economic activities during the COVID-19 outbreak. Geophysical Research Letters. 2020; 47:e2020GL088070. https://doi.org/10.1029/2020GL088070 Sicard P, De Marco A, Agathokleous E, Feng Z, Xu X, Paoletti E, et al. Amplified ozone pollution in cities during the COVID-19 lockdown. Science of the Total Environment. 2020; 735:139542. https://doi.org/10.1016/j.scitotenv.2020.139542 Siciliano B, Carvalho G, da Silva CM, Arbilla G. The impact of COVID-19 partial lockdown on primary pollutant concentrations in the atmosphere of Rio de Janeiro and São Paulo Megacities (Brazil). Bulletin of Environmental Contamination and Toxicology. 2020; 105(1):2-8. https://doi.org/10.1007/s00128-020-02907-9 Tobías A, Carnerero C, Reche C, Massagué J, Via M, Minguillón MC, et al. Changes in air quality during the lockdown in Barcelona (Spain) one month into the SARS-CoV-2 epidemic. Science of the Total Environment. 2020; 726:138540. https://doi.org/10.1016/j.scitotenv.2020.138540 Velásquez RMA, Lara JVM. Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima. Urban Climate. 2020; 33:100664. https://doi.org/10.1016/j.uclim.2020.100664 Zambrano-Monserrate MA, Ruano MA. Has air quality improved in Ecuador during the COVID-19 pandemic? A parametric analysis. Air Quality, Atmosphere & Health. 2020; 13:929-938. https://doi.org/10.1007/s11869-020-00866-y Regulation of the Minister of Health of 20 March 2020 on the declaration of an epidemic state in the territory of the Republic of Poland. Journal of Laws 2020, item 491. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200000491/O/D20200491.pdf Act of 31 March 2020 amending the Act on unique solutions related to the prevention, prevention and combating of COVID-19, other infectious diseases and crises caused by them, and some other acts. Journal of Laws 2020, item 568. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200000568/T/D20200568L.pdf Ordinance of the Council of Ministers of 30 October 2020 amending the Ordinance on the establishment of certain restrictions, orders and prohibitions in connection with the outbreak of an epidemic. Journal of Laws of 2020, item 1917. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200001917/O/D20201917.pdf Ordinance of the Council of Ministers of 6 November 2020 amending the Ordinance on the establishment of certain limits, orders and prohibitions in connection with the outbreak of an epidemic. Journal of Laws of 2020, item 1972. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200001972/O/D20201972.pdf Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5888206","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448843974,"identity":"e202f373-86dc-4e56-a7a1-852db69de7c6","order_by":0,"name":"Joanna Strużewska","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"","lastName":"Strużewska","suffix":""},{"id":448843975,"identity":"0873adcc-9596-4f96-a286-4f27c0e5f595","order_by":1,"name":"Aleksander Norowski","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Aleksander","middleName":"","lastName":"Norowski","suffix":""},{"id":448843976,"identity":"1fa64931-e79e-4d5b-81af-7930a6406303","order_by":2,"name":"Grzegorz Jeleniewicz","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Grzegorz","middleName":"","lastName":"Jeleniewicz","suffix":""},{"id":448843977,"identity":"3db34dba-6000-43d7-86e7-6eee16be7494","order_by":3,"name":"Maria Kłeczek","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Kłeczek","suffix":""},{"id":448843978,"identity":"6d48b382-e555-4a4e-8505-754667bfd1f4","order_by":4,"name":"Marcin Kawka","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Kawka","suffix":""},{"id":448843979,"identity":"fac5b939-2243-4f4f-b97a-4fd9b1286152","order_by":5,"name":"Paulina Jagiełło","email":"","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Paulina","middleName":"","lastName":"Jagiełło","suffix":""},{"id":448843980,"identity":"9cab5d48-d178-40b1-abb4-2a4ab3d49fca","order_by":6,"name":"Aleksandra Starzomska","email":"data:image/png;base64,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","orcid":"","institution":"Institute of Environmental Protection National Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Aleksandra","middleName":"","lastName":"Starzomska","suffix":""}],"badges":[],"createdAt":"2025-01-23 12:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5888206/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5888206/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81629166,"identity":"7e3d571a-a78c-4c93-91ce-a20e96ab801a","added_by":"auto","created_at":"2025-04-29 11:04:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138285,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of GIOŚ measurement stations used for research, divided by station type (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by: IOŚ-PIB)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/d7cff5f4c7a6fc6f4028668d.png"},{"id":81628927,"identity":"1e9fea2a-a9e4-4354-926c-0c0c50f36121","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":152788,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of differences in PM10 concentrations between 2020 and 2019; left panel - the difference in annual average concentrations, right panel - the difference in Q2 concentrations (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by: IOŚ-PIB)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/f9888d936ca7096ed7a275b7.png"},{"id":81628925,"identity":"6fcf1395-72b3-4eaf-a6e6-f3b438d2b828","added_by":"auto","created_at":"2025-04-29 10:56:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89206,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of differences in PM2.5 concentrations between 2020 and 2019; left panel - the difference in annual average concentrations, right panel - the difference in Q2 concentrations (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by: IOŚ-PIB)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/99924050dd09c40f38572cf4.png"},{"id":81628929,"identity":"7d1fffea-b378-45d0-ac47-6c0c36687ed0","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98998,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of differences in nitrogen dioxide concentrations between 2020 and 2019; left panel - the difference in annual average concentrations, right panel - the difference in Q2 concentrations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by: IOŚ-PIB)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/3727a68d768f24d952674d1b.png"},{"id":81628928,"identity":"4def6f13-7494-4cc8-89ed-e6736b0f6eef","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":103297,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of differences in benzo(a)pyrene concentrations between 2020 and 2019; left panel - the difference in annual average concentrations, right panel - the difference in Q2 concentrations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by: IOŚ-PIB)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/b3cdb00d2f87ec7ae90c634a.png"},{"id":81629171,"identity":"03ef2288-b9db-497e-9535-14c66c16af7e","added_by":"auto","created_at":"2025-04-29 11:04:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":93277,"visible":true,"origin":"","legend":"\u003cp\u003eAverage annual concentration of PM10 dust in Poland in the period 2016 - 2020 at urban background stations - red line, at non-urban stations - green line, at communication (urban)- blue line (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/fb2691e4a5447c0253e69e7a.png"},{"id":81628938,"identity":"928c8abb-0a7c-46fe-8e62-c5b1b2fc41a4","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":162596,"visible":true,"origin":"","legend":"\u003cp\u003eAverage monthly concentrations of PM10 dust in Poland in 2020 (solid line) and averaged for the period 2016 - 2020 (dashed line) at urban background stations - red line, at non-urban stations - green line, at transport (urban) stations - blue line (Data source: State Environmental Monitoring - Main Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/dccb39bc6207a15f0d53262e.png"},{"id":81629167,"identity":"2b231681-1228-4f45-8fa7-4937477a9fa8","added_by":"auto","created_at":"2025-04-29 11:04:59","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":77653,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual average concentrations of PM2.5 in Poland in the period 2016 - 2020 at urban background stations - red line, at non-urban stations - green line, at transport (urban) stations - blue line (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/535eb6c29eb1c4caa6efb263.png"},{"id":81629904,"identity":"3d59b46f-3786-4544-aadd-607c8b9d039b","added_by":"auto","created_at":"2025-04-29 11:12:59","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":147893,"visible":true,"origin":"","legend":"\u003cp\u003eAverage monthly concentrations of PM2.5 in Poland in 2020 (solid line) and averaged for the period 2016 - 2020 (dashed line) at urban background stations - red line, at non-urban stations - green line, at transport (urban) stations - blue line (Data source: State Environmental Monitoring - Main Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/28550c4cde561c2731a0fc80.png"},{"id":81628961,"identity":"a046b326-93d0-41e9-9db2-7be56fc45f6a","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":83505,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual average NO\u003csub\u003e2\u003c/sub\u003e in Poland in the period 2016 - 2020, at urban background stations - red line, at non-urban stations - green line, at transport (urban) stations - blue line (Data source: State Environmental Monitoring - Chief Inspectorate of Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/14106ca5fbcd16c1ed7fb694.png"},{"id":81628932,"identity":"4e920e64-b74f-4aeb-967d-b775e78cd3cc","added_by":"auto","created_at":"2025-04-29 10:56:59","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":137813,"visible":true,"origin":"","legend":"\u003cp\u003eAverage monthly concentrations of nitrogen dioxide in Poland in 2020 (solid line) and averaged for the period 2016 - 2020 (dashed line) at urban background stations - red line, at non-urban stations - green line, at transport (urban) stations - blue line (Data source: State Environmental Monitoring - Main Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/8d132a3fde8b362c5e568c31.png"},{"id":81696809,"identity":"398ca057-1fb9-48c3-acb1-0bd62fdd605c","added_by":"auto","created_at":"2025-04-30 12:26:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2268736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5888206/v1/46eb1f4d-42e0-42f2-bfdf-8c4cd3fdfaa8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Changes in air quality in Poland in 2020 in the context of the COVID-19 pandemic: spatial and seasonal analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe first media reports of disease cases caused by a previously unknown type of coronavirus, SARS-CoV-2, emerged in November 2019. Until January 2020, cases primarily occurred in Wuhan, located in central China, and gradually spread throughout the country and then to other nations. On 30 January 2020, the WHO Emergency Committee advised declaring a public health emergency of international concern.\u003c/p\u003e \u003cp\u003eIn the latter half of February 2020, outbreaks of infections emerged in Europe, particularly in Italy. On 13 March 2020, the WHO announced that Europe was the epicentre of the pandemic caused by the SARS-CoV-2 coronavirus. Since 4 March 2020, infections have also been reported in Poland.\u003c/p\u003e \u003cp\u003eMost published studies on pollution reduction have examined various regions of Asia and Latin America (e.g., Broomandi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dantas et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mahato et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Siciliano et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Vel\u0026aacute;squez and Lara, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zambrano-Monserrate and Ruano, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shi and Brasseur, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In Europe, the analyses have primarily concentrated on Western European nations. Based on measurements from monitoring stations in the Barcelona region of Spain, Tobias et al. (2020) reported decreases of 45\u0026ndash;51% in black carbon and NO2 concentrations and 28\u0026ndash;31% in PM10 concentrations. An increase in the daily maximum ozone concentration from 33\u0026ndash;57% was also reported. In Spain, the introduced restrictions were treated as a basis for quantifying the possible decrease in NO\u003csub\u003e2\u003c/sub\u003e pollution due to reduced car traffic. In the case of the two largest cities in Spain (Madrid and Barcelona), the reductions in NO\u003csub\u003e2\u003c/sub\u003e concentrations were 62% and 50% (Baldasano, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The impact of economic restrictions was also assessed using satellite data, the total NO2 content in the cross-section of the atmosphere. In the work of Bauwens et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), using TROPOMI and OMI observations, there was a significant decrease in NO\u003csub\u003e2\u003c/sub\u003e concentration in the tropospheric column over Western Europe from 20\u0026ndash;38%.\u003c/p\u003e \u003cp\u003eIn addition, a study by Putaud et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), covering many European countries, showed significant reductions in concentrations of particulate matter (PM10 and PM2.5), especially in urban agglomerations, as a result of reductions in transport and industrial activity. However, the authors pointed out that there was considerable regional variation due to local emission sources and meteorological conditions.\u003c/p\u003e \u003cp\u003eA systematic review by Bakola et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) for Europe and North America showed consistent results for decreases in NO₂, PM10 and PM2.5 concentrations during lockdown periods. They highlighted the particular impact of traffic and industrial reductions on improving urban air quality and the need for further research on the sustainability of these changes and their relevance to environmental policies.\u003c/p\u003e \u003cp\u003eSicard et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) conducted a comparative analysis for five European cities (Nice, Marseille, Milan, Madrid, Budapest), showing NO₂ reductions in excess of 50% and more variable changes for particulate matter, depending on local circumstances.\u003c/p\u003e \u003cp\u003eFilonchyk et al. (2021) examined the impact of economic restrictions on air quality in Poland. The research used satellite observations of the aerosol optical thickness (AOD) from the MODIS instrument and the NO\u003csub\u003e2\u003c/sub\u003e tropospheric column observed by the OMI instrument. The quantitative assessment of changes in air pollution also used concentrations of PM2.5, PM10, NO\u003csub\u003e2,\u003c/sub\u003e and SO\u003csub\u003e2\u003c/sub\u003e from air quality monitoring stations in five major cities across the country. Ground and satellite data showed a reduction in pollution from March to May, compared to the same months in 2018 and 2019. April and May 2020 saw the most significant decrease in concentrations at monitoring stations - in the case of PM2.5 in April 2020, from 11.1\u0026ndash;26.4% and in May from 8.7 to 21.1% compared to 2019. PM10 reductions ranged from 8.6\u0026ndash;33.9% in April 2020 and from 8.5\u0026ndash;31.5% in May, respectively, compared to the same months in 2019.\u003c/p\u003e \u003cp\u003eThe European Environment Agency report also referred to the impact of economic restrictions on European pollution levels. Data from the European Environment Agency (EEA) confirmed significant decreases in air pollution concentrations - in particular nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e) concentrations - mainly due to restricted movement and other restrictions, especially in large cities (EEA, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The conclusions from the work confirm the impact of economic limits, especially travel restrictions on NO\u003csub\u003e2\u003c/sub\u003e concentrations and a relatively small impact on PM10 dust concentrations, among others, due to specific meteorological conditions in March 2020, which were conducive to the accumulation of pollutants. European experience with the rapid spread of the COVID-19 epidemic meant that shortly after the first cases were detected in Poland, steps were taken to limit the spread of this virus. Not only were decisions made to recommend more significant attention to hygiene, disinfection, and covering the mouth and nose, but also restrictions on cross-border traffic, limited services and trade, and closed places of entertainment and culture. Regulations of the Council of Ministers or the Minister of Health most often introduced these restrictions.\u003c/p\u003e \u003cp\u003eMany sectors of the economy have been forced to modify their operations and service delivery. A major change has been the widespread introduction of remote learning and remote work.\u003c/p\u003e \u003cp\u003eThe aim of this study was to assess the impact of the COVID-19 pandemic on air quality in Poland in 2020 by analysing changes in concentrations of selected atmospheric pollutants (PM10, PM2.5, NO₂ and benzo(a)pyrene) compared to 2019. The analysis covered both spatial variation, taking into account individual provinces and types of measurement stations (urban, traffic and non-urban), and seasonal variation, broken down by quarters of the year. Particular attention was paid to the periods of strict pandemic restrictions (March-May and October-December 2020), as well as to the potential impact of meteorological conditions, such as temperature and precipitation, on observed concentrations. The results are presented in the form of tabular summaries and maps illustrating the spatial variation of changes, allowing for a comprehensive assessment of the impact of pandemic restrictions on the state of air quality in Poland.\u003c/p\u003e"},{"header":"2. Stages and nature of pandemic-related restrictions in Poland","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The first wave of the pandemic\u003c/h2\u003e \u003cp\u003eThe first wave of the COVID-19 pandemic in Poland began on 12 March 2020, with the declaration of an epidemic emergency. Initial restrictions included the closure of schools, nurseries, restaurants (limited to takeaway), shopping malls, and cultural and fitness facilities. Public gatherings over 50 people were banned.\u003c/p\u003e \u003cp\u003eFrom 24 March, movement was limited to essential activities such as work, shopping, and medical needs. Public transport capacity was reduced, assemblies were banned, remote work was advised, and air travel was suspended (Regulation of the Minister of Health of 20 March 2020).\u003c/p\u003e \u003cp\u003eOn 31 March, stricter measures were introduced: limits on customers in shops, special shopping hours for seniors, and the closure of hotels, personal care services, and access to public spaces.\u003c/p\u003e \u003cp\u003eFrom 9 April, wearing masks in public became mandatory, and all previous restrictions remained in force (Act of 31 March 2020, item 568).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Lifting restrictions\u003c/h2\u003e \u003cp\u003eAs daily infection numbers began to decline in mid-April, the Polish government initiated a phased plan to lift restrictions. The first phase began on 20 April, allowing more people in shops and restoring access to green areas. Restrictions on sports were lifted shortly after, with venues reopening in early May and professional leagues resuming by the end of that month.\u003c/p\u003e \u003cp\u003eThe second phase, introduced on 4 May, allowed shopping malls and large stores to reopen with occupancy limits (Act of 31 March 2020, item 568). Nurseries and kindergartens resumed on 6 May, and hotels reopened, excluding leisure facilities like pools and gyms. Cultural institutions also resumed activity.\u003c/p\u003e \u003cp\u003eFrom 18 May, hairdressers, beauty salons, restaurants, and caf\u0026eacute;s reopened under sanitary protocols, and public transport capacity was increased.\u003c/p\u003e \u003cp\u003eThe final phase began on 30 May, lifting face-covering rules in open spaces and removing most limits in shops, restaurants, and public venues. Events with up to 150 participants were permitted, and facilities such as pools, gyms, playrooms, and amusement parks reopened. Fairs, exhibitions, and congresses were also allowed to resume.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Second wave of the pandemic\u003c/h2\u003e \u003cp\u003eOn 17 October 2020, Poland introduced a regional sanitary regime with yellow and red zones, depending on the local infection rate (Ordinance of the Council of Ministers of 6 November 2020, item 1972). Just a few days later, on 23 October, the entire country was classified as a red zone, and strict nationwide restrictions were reinstated \u0026mdash; similar to those from the first wave. Remote learning was introduced for grades 4\u0026ndash;8, remote work was recommended, and sanatoriums, restaurants, and public gatherings were limited. Children under 16 could leave home only under adult supervision during school hours. Cemeteries were closed between 30 October and 2 November (Ordinance of the Council of Ministers of 30 October 2020, item 1917).\u003c/p\u003e \u003cp\u003eIn early November, restrictions were extended to include remote learning in grades 1\u0026ndash;3, closure of cultural institutions, and limitation of shopping malls to essential services (e.g. groceries, pharmacies, construction stores). Hotels were closed, except for business-related stays.\u003c/p\u003e \u003cp\u003eOverall, two main periods of strict restrictions occurred in 2020: March\u0026ndash;April and October\u0026ndash;December. While the summer months brought temporary easing, the autumn surge in infections led to a rapid nationwide return to strict measures.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Data and method of analysis","content":"\u003cp\u003eThe study was based on data from the National Air Quality Monitoring Network, managed by the Chief Inspectorate for Environmental Protection (GIOŚ). Measurements of concentrations of particulate pollutants (PM10 and PM2.5), nitrogen dioxide (NO₂) and benzo(a)pyrene (B(a)P) were analysed in accordance with the requirements of Directive 2008/50/EC and relevant national air quality legislation. Data came from urban background, traffic and non-urban measurement stations located throughout Poland (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003eMeteorological data used to support the interpretation of the results, including temperature anomalies and circulation conditions, were obtained from the Institute of Meteorology and Water Management \u0026ndash; National Research Institute (IMGW-PIB).\u003c/p\u003e\n\u003cp\u003eThe comparative analysis included data from 2019 and 2020, and additionally a multi-year background from 2016\u0026ndash;2020 was included to assess the context of long-term changes in concentrations. In order to identify the impact of the COVID-19 pandemic on air quality, annual and quarterly average pollutant concentrations were collated, analysing spatial (at the level of provinces and individual stations) and seasonal variability.\u003c/p\u003e\n\u003cp\u003eParticular attention was paid to the periods of the most stringent socio-economic restrictions (March-May and October-December 2020), which were associated with restrictions on mobility and activities of many economic sectors.\u003c/p\u003e\n\u003cp\u003eThe results are presented in the form of tables showing the differences in concentrations between the years analysed on a provincial and quarterly basis, and maps showing the spatial variability of changes in concentrations. An analysis of changes depending on the type of measuring station was presented separately, allowing the influence of local emission sources, such as road transport or municipal and household emissions, to be taken into account.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDolnośląskie\u003c/strong\u003e - A diverse area in terms of terrain - the south is dominated by the Sudetes Mountains with the highest peak of Śnieżka (1 602 m), while the north is made up of lowlands and river valleys (mainly the Oder). The climate is moderate, with higher precipitation and lower temperatures in the mountainous areas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKujawsko-pomorskie\u003c/strong\u003e - Mainly lowland area, covering part of the Pomeranian Lake District and the Toruń-Bydgoska Basin. A temperate transitional climate prevails, with little thermal and rainfall variation and relatively frequent temperature inversions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLubelskie\u003c/strong\u003e \u0026ndash; Diverse landscape - from the Lublin Uplands and Roztocze in the south to the plains of Polesie Lubelskie and river valleys (e.g. of the Bug and Vistula rivers) in the north. Continental climate, with a high number of days with frost, less precipitation and a greater temperature amplitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLubuskie\u003c/strong\u003e \u0026ndash; Mainly lowland, with numerous forest areas and lakes. Sand and glacial plains predominate. Mild maritime climate with fairly even precipitation and moderate winters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eŁ\u0026oacute;dzkie\u003c/strong\u003e \u0026ndash; Lowland and upland areas, without distinct mountain forms - dominated by the Ł\u0026oacute;dzka Plain and the Ł\u0026oacute;dzka Upland. Transitional climate, with high variability of weather conditions and relatively short winter period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMałopolskie\u003c/strong\u003e \u0026ndash; Distinctly diversified landforms - from lowlands in the northern part of the region to the Carpathian Mountains (Tatra Mountains, Beskidy Mountains, Gorce Mountains) in the south. Mountain climate in the Podhale region, with low temperatures and a large number of days with snow cover. In the central part - moderate continental climate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMazowieckie\u003c/strong\u003e \u0026ndash; Predominantly lowland (Mazowiecka Lowland), with numerous river valleys (e.g. of the Vistula, Narew and Bug rivers). Transitional climate with a continental trend - winters relatively cool and summers warm, with average precipitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpolskie\u003c/strong\u003e \u0026ndash; Slightly undulating terrain, comprising fragments of the Silesian Upland and the Sudeten Foreland. In the south there are fragments of the Opawskie Mountains. Moderate climate, with local influence of mountain conditions in the southern part.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePodkarpackie\u003c/strong\u003e \u0026ndash; Region strongly diversified topographically - the southern part is occupied by the Carpathian Mountains (Bieszczady, Beskid Niski), and the northern part by uplands and plains. Continental climate, cooler in the mountains, with a high number of frosty days and high precipitation in the foothills.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePodlaskie\u003c/strong\u003e \u0026ndash; Mainly lowland and flat, with extensive forest areas (e.g. Białowieża Forest). Continental climate - lowest average annual temperatures in Poland, long winters, moderate precipitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePomorskie\u003c/strong\u003e \u0026ndash; Varied - from the Baltic coast, through the Kashubian Lake District, to uplands and moraine hills. Maritime climate, with mild winters, cool summers and high humidity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eŚląskie\u003c/strong\u003e \u0026ndash; Heavily urbanised and diverse - includes the Silesian Lowlands, the Silesian Uplands and the Beskids. The south of the region is a mountainous area (Silesian and Zywiec Beskids). Transitional to mountainous climate, with marked differences in temperature and precipitation depending on altitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eŚwiętokrzyskie\u003c/strong\u003e \u0026ndash; Characteristic relief - dominated by the Świętokrzyskie Mountains and Kielce Upland. A region with a temperate, transitional climate with local continental features.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWarmińsko-mazurskie\u003c/strong\u003e \u0026ndash; Lakeland and lowland region with numerous lakes, forests and sand plains. A cooler climate than the national average, with long winters and moderate rainfall.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWielkopolskie\u003c/strong\u003e \u0026ndash; Predominantly flat and lowland, with some moraine hills. Temperate climate, drier than the national average, with pronounced continental influences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZachodniopomorskie\u003c/strong\u003e \u0026ndash; Lowland and coastal area, including a strip of the Baltic coast and numerous lakes. Maritime climate - mild, with a high number of cloudy days, moderate rainfall and short winters.\u003c/p\u003e"},{"header":"4. Analysis of results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Spatial distribution of concentration anomalies\u003c/h2\u003e\n \u003cp\u003eThe differences between the concentrations in 2020 and 2019 were calculated for the individual provinces to address the spatial variability of concentrations. Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, and \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e present the average differences between the years and quarters.\u003c/p\u003e\n \u003cp\u003eIn the case of PM10 concentrations in 2020 compared to 2019, there was a reduction on average across the country - the smallest in the Świętokrzyskie Voivodship (-0.06 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), the largest in the Podkarpackie Voivodship (-3.52 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). A concentration increase was shown only for Podlaskie Voivodship (5.45 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). The decreases in the first quarter are mainly due to important differences in February, which was anomalously warm, and no restrictions had yet been introduced in Poland. The most important decrease in concentrations in the first quarter occurred in the Silesian Voivodship (-13.52 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), as well as in the Opolskie and Podkarpackie Voivodship (-9.4 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and \u0026minus;\u0026thinsp;9.86 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), respectively. In the second quarter, the values of decreases are smaller and concern other voivodship - the largest reduction occurred in the Pomorskie (-7.11 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), Warmińsko-Mazurskie (-7.6 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) and Zachodniopomorskie (-6.47 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) Voivodship.\u003c/p\u003e\n \u003cp\u003eThe third quarter was characterised by relatively small differences (except the Małopolskie Voivodship, where concentrations decreased by -2.53 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). The fourth quarter was dominated by a downward trend in PM10 concentrations in 2020, resulting mainly from important decreases in October.\u003c/p\u003e\n \u003cp\u003eThe observed changes in PM10 concentrations in 2020 compared to 2019 can be explained by a combination of environmental and socio-economic factors. Meteorological conditions were of particular importance \u0026ndash; February 2020 was exceptionally warm (average temperature in many regions over 3\u0026deg;C higher than normal), which resulted in reduced consumption of solid fuels in the household sector. In addition, in the period from March to May, mobility restrictions related to the COVID-19 pandemic were introduced in Poland, which significantly reduced road traffic \u0026ndash; a source of secondary dust emissions and primary emissions from transport. In some regions, the observed decrease could also have been supported by local low emission reduction programs, e.g. under the \u0026ldquo;Clean Air\u0026rdquo; program. It is also worth noting that in the winter of 2019/2020 there was no heavy snowfall or the need to intensively sprinkle roads with sand and salt, which reduced the phenomenon of dust resuspension from the road surface.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferences in PM10 concentrations (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) between concentrations in 2020 and 2019 (2020\u0026thinsp;\u0026minus;\u0026thinsp;2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVoivodship\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-III\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV-VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVII-IX\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX-XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDolnośląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKujawsko-pomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubelskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŁ\u0026oacute;dzkie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubuskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMałopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMazowieckie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-9.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodlaskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodkarpackie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-9.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-7.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚwiętokrzyskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-13.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWarmińsko-mazurskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-7.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWielkopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZachodniopomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe spatial distribution of the differences between the annual average PM10 concentrations in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 2\u0026ndash;3 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e on average (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.). An increase in concentrations compared to the previous year occurred at several stations in the Podlaskie, Lubelskie, Mazowieckie, Świętokrzyskie and Małopolskie Voivodship. It should be noted that in Podlaskie Voivodship, the analyses are based on measurements from only one station. This explains the different characteristics of the interannual variability of concentrations in Podlaskie Voivodship, as described earlier. The differences in concentrations in the second quarter of 2020 relative to 2019 are slightly more important in absolute value than the annual average change.\u003c/p\u003e\n \u003cp\u003eFor selected provinces, changes in PM10 concentrations are particularly pronounced: in the Silesian province, the average decrease was \u0026minus;\u0026thinsp;4.85 \u0026micro;g/m\u0026sup3;, which, given the level of around 34 \u0026micro;g/m\u0026sup3; in 2019, means a decrease of around 14%. In turn, the increase in the Podlaskie province (+\u0026thinsp;5.46 \u0026micro;g/m\u0026sup3;) compared to the average values from 2019 (approx. 17 \u0026micro;g/m\u0026sup3;) constitutes an increase of over 30%, which indicates a local deviation from the national trend and confirms the need for cautious interpretation of results based on data from a single station.\u003c/p\u003e\n \u003cp\u003eWhen comparing 2020 and 2019 in terms of PM2.5 concentrations, on average, across the country, there was a decrease - the smallest difference was in the Podlaskie Voivodship\u003c/p\u003e\n \u003cp\u003e(-0.07 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), the largest in the Podkarpackie Voivodship (-4.67 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). The decreases in the first quarter are mainly due to important differences in February, which was much warmer than the previous year and in which no restrictions had yet been introduced in Poland. The most important decrease in concentrations in the first quarter occurred in the Podkarpackie Voivodship (-13.35 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), as well as in the Śląskie and Opolskie Voivodship (-10.25 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and \u0026minus;\u0026thinsp;8.01 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), respectively. In the second quarter, the values of decreases are smaller and concern other provinces - the most important reduction occurred in the Zachodniopomorskie Voivodship (-4.72 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), Pomorskie Voivodship (-4.70 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) and Warmińsko-Mazurskie Voivodship (-4.00 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). The third quarter was characterised by relatively small differences (except for the Ł\u0026oacute;dzkie Voivodship: -2.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and the Pomorskie Voivodship: -3.6 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). In the fourth quarter, a downward trend in PM2.5 concentrations prevailed in 2020, resulting mainly from important decreases in October; however, increases prevailed in December.\u003c/p\u003e\n \u003cp\u003eThe reductions in PM2.5 concentrations in 2020 compared to 2019 had similar causes as for PM10 \u0026ndash; a mild winter, pandemic restrictions and reduced transport and economic activity. These declines are most visible in the southern provinces, where the share of low emissions is particularly significant. The effects of the lockdown were also visible in the declines recorded at transport stations, which indicates a significant share of the transport sector in generating PM2.5 in urban areas.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferences in PM2.5 concentrations (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) between concentrations in 2020 and 2019 (2020\u0026thinsp;\u0026minus;\u0026thinsp;2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVoivodship\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-III\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV-VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVII-IX\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX-XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDolnośląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKujawsko-pomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubelskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŁ\u0026oacute;dzkie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubuskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMałopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMazowieckie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-8.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodlaskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodkarpackie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-13.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚwiętokrzyskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-10.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWarmińsko-mazurskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWielkopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZachodniopomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe spatial distribution of the differences between annual average PM2.5 concentrations in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 3\u0026ndash;5 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e on average (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.). The highest reductions, up to -6.5 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, occurred at stations located mainly in the southern and central parts of the country. An increase in concentrations about the previous year was recorded at several stations in the Podlaskie, Lubelskie, Świętokrzyskie, Opolskie and Małopolskie Voivodship. The differences in concentrations in the second quarter of the year are greater in absolute terms. Importantly, the reduction is lower than the annual average in the southern part of the country. Also, concentrations increased at more stations in the second quarter of 2020. This indicates that the quarantine period did not importantly reduce PM2.5 concentrations between 2020 and 2019.\u003c/p\u003e\n \u003cp\u003eFor example, in the Podkarpackie province, the average annual decrease in PM2.5 was \u0026minus;\u0026thinsp;4.67 \u0026micro;g/m\u0026sup3; \u0026ndash; which, compared to the base value of about 23 \u0026micro;g/m\u0026sup3;, means a reduction of over 20%. In the Silesian province, the decrease was \u0026minus;\u0026thinsp;3.07 \u0026micro;g/m\u0026sup3; (about 11%), while in the Opole province it was only \u0026minus;\u0026thinsp;1.27 \u0026micro;g/m\u0026sup3;, which may indicate lower effectiveness of local measures or a greater share of industrial sources, less susceptible to changes in population mobility.\u003c/p\u003e\n \u003cp\u003eIn the case of nitrogen dioxide concentrations, on average in the country, there was a reduction - the smallest in the Podlaskie Voivodship (-0.33 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e), the largest in the Małopolskie Voivodship (-3.44 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). Only the Lubuskie Voivodship showed a concentration increase (1.06 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). In the first quarter, the decreases were mainly due to important differences in February. It was much warmer in 2020 than 2019, and no restrictions had yet been introduced in Poland.\u003c/p\u003e\n \u003cp\u003eConcentrations decreased most importantly in the first quarter in the Śląskie Voivodship (-4.95 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) and the Wielkopolskie, Świętokrzyskie, and Opolskie Voivodship (-3.67 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, -3.47 \u0026micro;g/m\u003csup\u003e3,\u003c/sup\u003e and \u0026minus;\u0026thinsp;3.40 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e, respectively). In the second quarter, the values of decreases are smaller and concern other provinces - the largest reduction occurred in the Małopolskie Voivodship (-4.12 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) and Pomorskie Voivodship (-3.20 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). The third quarter was characterised by relatively small differences (except the Lubuskie Voivodship: -2.23 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e and the Małopolskie Voivodship: -2.17 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). In the fourth quarter, nitrogen dioxide concentrations tended to decrease in 2020, mainly due to large drops in October; only in the Lubuskie Voivodship did concentrations increase by 2.02 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eIn the case of NO₂, the significant decreases in concentrations in 2020 can be largely attributed to road traffic restrictions introduced in March and April 2020. Since the main source of NO₂ in urban areas is road transport, its reduction directly translated into lower levels of this pollutant \u0026ndash; especially in cities. Meteorological conditions, including favourable ventilation in spring 2020, may have had a smaller impact.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDifferences in nitrogen dioxide concentrations (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) between concentrations in 2020 and 2019 (2020\u0026thinsp;\u0026minus;\u0026thinsp;2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVoivodship\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-III\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV-VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVII-IX\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX-XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDolnośląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKujawsko-pomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubelskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŁ\u0026oacute;dzkie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLubuskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMałopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMazowieckie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOpolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodlaskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePodkarpackie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚwiętokrzyskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eŚląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWarmińsko-mazurskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWielkopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZachodniopomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe spatial distribution of the differences between the annual average NO concentration\u003csub\u003e2\u003c/sub\u003e in 2020 and 2019 for individual stations shows that over the majority of the country, there was a reduction in the range of 2\u0026ndash;5 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e on average (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.). An increase in concentrations compared to the previous year occurred at several stations in the following voivodship: Lubelskie, Mazowieckie, Podkarpackie, Małopolskie, Kujawsko-Pomorskie, Lubuskie and Zachodniopomorskie. The differences in concentrations in the second quarter of the year are spatially differentiated. Slightly more locations show a positive difference, indicating higher concentrations in 2020, while at other places, the reduction in concentrations in 2020 relative to 2019 is higher than the annual average.\u003c/p\u003e\n \u003cp\u003eIn the Małopolskie province, the decrease in NO₂ concentrations in 2020 reached \u0026minus;\u0026thinsp;3.44 \u0026micro;g/m\u0026sup3;, which in relation to the base level of approx. 25 \u0026micro;g/m\u0026sup3; means a reduction of 13.8%. The greatest relative decreases were recorded in provinces with a large share of urban transport and intensive traffic (Śląskie, Wielkopolskie, Mazowieckie).\u003c/p\u003e\n \u003cp\u003eAnalysis of benzo(a)pyrene concentrations shows that, on average across the country, concentrations increased and decreased between 2020 and 2019. The smallest concentration increase occurred in the Małopolskie and Mazowieckie Voivodship (0.02 ng/m\u003csup\u003e3\u003c/sup\u003e), the largest in the Podlaskie Voivodship (0.62 ng/m\u003csup\u003e3\u003c/sup\u003e). In the case of decreases, the largest decrease in benzo(a)pyrene concentrations occurred in the Lubuskie Voivodship (-1.57 ng/m\u003csup\u003e3\u003c/sup\u003e). In the first quarter, the reductions were mainly due to important differences in February, which was much warmer in 2020 than in 2019, and restrictions were not yet in place in Poland. The most important decrease in concentrations in the first quarter occurred in the Śląskie Voivodship (-4.05 ng/m\u003csup\u003e3\u003c/sup\u003e) and also in the Lubuskie and Pomorskie Voivodship (-3.09 ng/m3 and \u0026minus;\u0026thinsp;2.94 ng/m\u003csup\u003e3\u003c/sup\u003e), respectively. In the second quarter, the values of concentrations of benzo(a)pyrene increased; the highest increase occurred in the Voivodship Lubelskie (1.37 ng/m\u003csup\u003e3\u003c/sup\u003e), Ł\u0026oacute;dzkie (0.84 ng/m\u003csup\u003e3\u003c/sup\u003e) and Pomorskie (0.83 ng/m\u003csup\u003e3\u003c/sup\u003e). A decrease occurred only in the Lubuskie Voivodship (-0.52 ng/m\u003csup\u003e3\u003c/sup\u003e). The third quarter was characterised by relatively small differences - concentrations in 2020 were mostly lower, except for the Warmińsko-Mazurskie Voivodship, where concentrations increased by 0.31 ng/m\u003csup\u003e3\u003c/sup\u003e. In the fourth quarter, in the majority of voivodship, there was a decreasing tendency of benzo(a)pyrene concentrations in 2020; the most important decrease concerned the Lubuskie Voivodship (-2.69 ng/m\u003csup\u003e3\u003c/sup\u003e), whereas the highest increase occurred in the Dolnośląskie Voivodship (2.65 ng/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e\n \u003cp\u003eChanges in benzo(a)pyrene concentrations did not have a clear direction, which may be due to the fact that the sources of this compound are closely related to the individual heating sector (burning of biomass and coal), which was subject to pandemic restrictions to a small extent. Increases noted in some regions (e.g. Podlaskie, Kujawsko-pomorskie) may result from local meteorological conditions (e.g. inversions) or changes in the structure of fuels used by households. Further analyses of correlation with local anti-smog policies are needed.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eDifferences in benzo(a)pyrene concentrations (in ng/m\u003csup\u003e3\u003c/sup\u003e) between concentrations in 2020 and 2019 (2020 - 2019) in the provinces for the periods: the whole year, Q1 (January, February, March), Q2 (April, May, June), Q3 (July, August, September) and Q4 (October, November, December), (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProvince\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eI-III\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIV-VI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVII-IX\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX-XII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eDolnośląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eKujawsko-pomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eLubelskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eŁ\u0026oacute;dzkie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eLubuskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eMałopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eMazowieckie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eOpolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003ePodlaskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003ePodkarpackie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e- 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003ePomorskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eŚląskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eWarmińsko-mazurskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 171px;\"\u003e\n \u003cp\u003eWielkopolskie\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eThe spatial distribution of the differences between annual average benzo(a)pyrene concentrations in 2020 and 2019 for individual stations shows that in the predominant area of the\u0026nbsp;voivodship\u0026nbsp;of Podkarpackie, Śląskie, Opolskie, Ł\u0026oacute;dzkie, Lubuskie, Pomorskie and Warmińsko-Mazurskie there was a reduction on average in the range of 0.5 - 1.0 ng/m\u003csup\u003e3\u003c/sup\u003e (Figure 5.). An increase in concentrations compared to the previous year occurred at stations in the following voivodship: Podlaskie, Mazowieckie, Lubelskie, Małopolskie, Dolnośląskie, Kujawsko-Pomorskie and Wielkopolskie. Differences in concentrations between 2020 and 2019 in the year\u0026apos;s second quarter show an increase at most stations.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2 Change in concentrations at traffic, urban background and non-urban background stations\u003c/h2\u003e\n \u003cp\u003eMost stations measuring benzo(a)pyrene belong to a single type, so the following analysis has been carried out for PM10, PM2.5 and NO\u003csub\u003e2\u003c/sub\u003e. Where reference is made to \u0026quot;urban stations\u0026rdquo;, these are only urban background stations, excluding traffic stations, which form a separate category in the analysis.\u003c/p\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.1 PM10\u003c/h2\u003e\n \u003cp\u003eAbout 2018, a decrease in annual mean PM10 concentrations was marked at all station types. The trend continued between 2019 and 2020 for traffic stations, while the trend was slightly weaker for the other station types. This may support the thesis of the impact of reduced travel in urban areas on the levels of PM10 concentrations measured within the range of influence of traffic routes. At the same time, this may result from reduced secondary lift due to a hot winter during which no sanding and salting of streets took place. The downward trend at non-urban stations is relatively the weakest (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.).\u003c/p\u003e\n \u003cp\u003eThe analysis of the variability of monthly PM10 concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at urban and traffic (urban) background type stations shows a slightly higher gradient than at non-urban stations (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). Comparing 2020 and the average of the last 5 years, the most important difference in PM10 concentrations occurred at traffic stations, which may be related to the quarantine period and reduced car traffic in urban areas.\u003c/p\u003e\n \u003cp\u003eThe differences between PM10 concentrations in the second and fourth quarters of 2020 compared to the corresponding quarter of 2019 are shown in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Differences are given for stations of different types - non-urban, suburban and urban (including traffic). Differences are also included for March, in the middle of which restrictions were introduced, and there was an increase in concentrations in 2020 compared to the previous year. The decrease in concentrations is more important in the second quarter of 2020 and weaker in the fourth quarter due to the increase in concentrations recorded in December and March 2020, marked increases in PM10 concentrations compared to 2019.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe difference in PM10 concentrations (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including traffic) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of area\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV - VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX - XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eurban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esuburban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eextra-urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.2 PM2.5\u003c/h2\u003e\n \u003cp\u003eSince 2018, annual mean concentrations of PM2.5 at all station types have importantly decreased, although the trend has continued since 2017. The variability is very similar to PM10 (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe analysis of the variability of monthly average PM2.5 concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at urban and traffic (urban) background type stations shows a slightly greater gradient than at non-urban stations (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e). The highest difference in PM2.5 concentrations in 2020 compared to the average of the last 5 years occurred at traffic stations, which may be related to the quarantine period and reduced traffic in urban areas.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e shows the differences between PM2.5 concentrations in the second and fourth quarters of 2020 and the corresponding quarter of 2019. Differences are also included for March, during which restrictions were introduced, and concentrations increased in 2020 compared to the previous year. Only suburban stations showed harmful concentration decreases in the fourth quarter for all three months. At urban background stations, concentrations in November and December of 2020 were higher than in the previous year.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe difference in PM2.5 concentrations (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including transport) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of area\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV - VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX - XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eurban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esuburban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eextra-urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e4.2.3 NO\u003csub\u003e2\u003c/sub\u003e\u003c/h2\u003e\n \u003cp\u003eFor NO\u003csub\u003e2\u003c/sub\u003e, the downward trend has continued since the beginning of the analysed period in 2016. While the differences are not important for non-urban stations, and a slight decrease has been recorded for urban background stations since 2018, the variability at traffic stations shows an apparent decline in values in 2020 (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe analysis of the variability of nitrogen dioxide concentrations in 2020, taking into account station types, shows that there are differences of a systematic nature. However, the decrease in concentrations from March to May at stations of the urban background and traffic (urban) type shows a greater gradient than at non-urban stations (Fig. \u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e). The highest difference in NO\u003csub\u003e2\u003c/sub\u003e concentrations in 2020 compared to the average of the last 5 years occurred at traffic stations, which may be related to the quarantine period and reduced traffic in urban areas.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e shows the differences between NO\u003csub\u003e2\u003c/sub\u003e concentrations in the second and fourth quarters of 2020 compared to the corresponding quarter of 2019. It also includes the differences for March, in the middle of which restrictions were introduced, in which concentrations increased in 2020 compared to the previous year. The relatively important decrease in concentrations at urban and suburban stations in the fourth quarter is due to the reduction in October.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe difference in NO\u003csub\u003e2\u003c/sub\u003e (in \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e) in 2020 compared to the corresponding period in 2019 calculated for the whole year, the month of March, and for Q2 and Q4; for non-urban, urban (including transport) and suburban stations (Data source: State Environmental Monitoring - Chief Inspectorate for Environmental Protection. Prepared by IOŚ-PIB)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of area\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIV - VI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX - XII\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eurban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esuburban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eextra-urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe analysis conducted in Poland shows a decrease in the average annual concentrations of PM10, PM2.5, NO\u003csub\u003e2\u003c/sub\u003e, and benzo(a)pyrene since 2018. The introduction of restrictions related to the COVID-19 pandemic, such as lockdowns and quarantines, impacted road traffic, which could have contributed to reducing concentrations of these pollutants. However, the observations show that the impact of the pandemic on concentration reduction is unclear and varies depending on the region and measuring stations.\u003c/p\u003e \u003cp\u003eA comparison of the results of the conducted studies with the results of the systematic review entitled \"The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review\" indicates consistency in the observations regarding the impact of the COVID-19 pandemic on air quality (Bakola et al.). In Poland and other countries in Europe and North America, a decrease in the concentrations of pollutants such as NO\u003csub\u003e2\u003c/sub\u003e, PM10 and PM2.5 was observed during the lockdown periods. Both cases emphasised that the pandemic restrictions had a particularly pronounced impact on reducing traffic and industrial pollution, confirmed by reducing these pollutant concentrations in cities. At the same time, both the studies in Poland and the systematic review point to the need for further research to better understand the long-term effects of the pandemic restrictions on air quality and to consider other emission reduction programmes. Ultimately, these results have important implications for air protection policy, emphasising the importance of reducing emissions from transport and industry to improve air quality.\u003c/p\u003e \u003cp\u003eChina also experienced important decreases in air pollution concentrations during the most stringent restrictions. In Poland, a reduction in PM10, PM2.5 and NO2 concentrations was observed, similar to Wuhan, where the average monthly air quality index (AQI) decreased by 33.9% compared to the period before the lockdown, and NO\u003csub\u003e2\u003c/sub\u003e concentrations decreased by 53.3%. Both studies indicated the reduction in traffic pollution as the main factor in reducing the levels of these pollutants (Lian et al.). Studies have also shown that lockdowns importantly impacted reducing air pollution levels. Still, the differences in the results indicate the complexity of emission processes and the need for further research and mathematical modelling to understand better the long-term effects of pandemic restrictions on air quality.\u003c/p\u003e \u003cp\u003eA study published in Atmospheric Chemistry and Physics analyses the effects of COVID-19 lockdowns on PM2.5 and PM10 pollution in Europe (Putaud et al.). It shows that restrictions on mobility and industrial activity importantly reduced pollutant concentrations. The largest reductions were observed in urban areas, where road traffic was the primary source of emissions. However, regional differences were related to local emission sources and meteorological conditions, such as temperature and wind. The analysis highlights that the impact of lockdowns was evident in the transport sector.\u003c/p\u003e \u003cp\u003eIn the context of the obtained results, it is worth emphasizing the clear differentiation of the effects observed between the analysed pollutants. For NO₂, the main source of emissions of which is road transport, the decreases in concentrations were most visible during periods of limited mobility and concerned in particular communication stations in cities. In the case of benzo(a)pyrene, emissions are strongly related to the residential and municipal sector, which was not subject to significant restrictions during the pandemic. As a result, changes in B(a)P concentrations were less pronounced and more dependent on local conditions - e.g. meteorological conditions, fuel structure or intensity of individual heating sources. The differentiation in the responses of individual types of measurement stations also confirms that population mobility and reduced economic activity played a significant role. Communication stations showed the strongest decrease in NO₂, PM10 and PM2.5 concentrations during the lockdown periods, which clearly indicates the dominant impact of transport on the levels of these pollutants in urban areas. In the case of non-urban stations, the changes were less significant, which may indicate a lower importance of mobility and a greater share of diffuse sources (e.g. agriculture, biomass).\u003c/p\u003e \u003cp\u003eThe spatial differentiation of concentration changes (e.g. increases in B(a)P in north-eastern provinces, despite the nationwide downward trend) suggests that local emission conditions and meteorology could mask or amplify the effects of the pandemic. This suggests the need for further model analyses that will allow for better separation of the impact of pandemic restrictions from other factors - such as temperature, inversions, fuel consumption structure or locally implemented air protection programs.\u003c/p\u003e \u003cp\u003eThe conclusions from this analysis show that only in the case of substances strongly related to mobility and road traffic (NO₂, partially PM10 and PM2.5) the impact of the pandemic was significant and measurable on a national scale. In the case of substances of heating origin (B(a)P), the effect was more complex and local.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eAnalysis of PM10, PM2.5, benzo(a)pyrene and nitrogen dioxide (NO₂) pollution concentrations indicates a continuation of the downward trend in 2016\u0026ndash;2020, with the differences between 2019 and 2020 being smaller than between 2018 and 2019. The exceptions are individual months in which a concentration increase was observed in 2020 (e.g. March, September, and December for particulate matter and NO₂). An important decrease in concentrations in the winter months of 2020 (January and February) can be associated with a warmer winter compared to previous years. In turn, the greatest decrease in concentrations was recorded at communication stations, which suggests the impact of pandemic restrictions, such as reduced car traffic.\u003c/p\u003e \u003cp\u003eThe variability of concentrations across provinces and seasons shows that southern Poland experienced the highest reductions, particularly in the winter (February) and autumn (October) months. However, simultaneous actions related to air protection programmes, such as \"Czyste Powietrze\" or \"M\u0026oacute;j Prąd\", and the development of renewable energy sources make it difficult to attribute the decreases to the COVID-19 pandemic unequivocally.\u003c/p\u003e \u003cp\u003eAt the same time, the analysis results allow for the formulation of specific conclusions regarding the impact of the COVID-19 pandemic on air quality in Poland. The most unequivocal effects of pandemic restrictions were observed in the case of nitrogen dioxide (NO₂), the concentrations of which dropped significantly during periods of reduced mobility, especially at transport stations in large cities. In the case of suspended particulate matter (PM10 and PM2.5), decreases in concentrations were observed during lockdowns, especially in the second quarter of 2020. Still, their scale was strongly dependent on meteorological conditions, the regional emission structure and the type of measuring station. For benzo(a)pyrene, the main source of which is individual heating systems, the effects of the pandemic were the least visible and did not show a uniform nationwide trend.\u003c/p\u003e \u003cp\u003eA comparison of data from different types of stations shows that mobility restrictions had the greatest impact in locations dominated by transport emissions, and a smaller impact in non-urban areas and with dispersed emission sources. The results indicate that actions restricting economic activity and transport can lead to temporary improvement of air quality, but their impact is complex, dependent on local conditions and difficult to maintain without support from permanent environmental policies. This requires further, in-depth analyses, including emission and dispersion modelling, to separate meteorological and emission effects and to accurately indicate directions for effective long-term actions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Statement:\u003c/h2\u003e\n\u003cp\u003eThis work was carried out under Agreement No. GIOŚ/ZP/32/2021/DMŚ/NFOŚ dated February 15, 2021, financed by the National Fund for Environmental Protection and Water Management.\u003c/p\u003e\n\u003ch2\u003eEthics, Consent to Participate, and Consent to Publish Declarations:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConflict of Interest Statement:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eJS and PJ wrote the main text of the manuscript, including the introduction and discussion.GJ prepared Figures 1-3 and Table 1 and took care of their formatting.MK performed the statistical analyses and provided data for the methodology section.MK, AN carried out the experimental study and collected the data that were used in the article.AS edited the text for grammar and style and prepared the print version.All authors reviewed the manuscript and made comments on the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBakola M, Carballo IH, Jelastopulu E, Stuckler D. The impact of COVID-19 lockdown on air pollution in Europe and North America: a systematic review. European Journal of Public Health. 2022; 32(6):962-968. https://doi.org/10.1093/eurpub/ckac118\u003c/li\u003e\n\u003cli\u003eBaldasano JM. COVID-19 lockdown effects on air quality by NO2 in the cities of Barcelona and Madrid (Spain). Science of the Total Environment. 2020; 741. https://doi.org/10.1016/j.scitotenv.2020.140353\u003c/li\u003e\n\u003cli\u003eBauwens M, Compernolle S, Stavrakou T, M\u0026uuml;ller J-F, van Gent J, Eskes H, et al. Impact of coronavirus outbreak on NO2 pollution assessed using TROPOMI and OMI observations. Geophysical Research Letters. 2020; 47:e2020GL087978. https://doi.org/10.1029/2020GL087978\u003c/li\u003e\n\u003cli\u003eBroomandi P, Karaca F, Nikfal A, Jahanbakhshi A, Tamjidi M, Kim JR. Impact of COVID-19 Event on the Air Quality in Iran. Aerosol Air Quality Research. 2020; 20:1793-1804. https://doi.org/10.4209/aaqr.2020.05.0205\u003c/li\u003e\n\u003cli\u003eDantas G, Siciliano B, Fran\u0026ccedil;a BB, da Silva CM, Arbilla G. The impact of COVID-19 partial lockdown on the air quality of the city of Rio de Janeiro, Brazil. Science of the Total Environment. 2020; 729:139085. https://doi.org/10.1016/j.scitotenv.2020.139085 \u003c/li\u003e\n\u003cli\u003eEEA, Report No 09/2020. Air quality in Europe - 2020 report. 2020; https://www.eea.europa.eu/publications/air-quality-in-europe-2020-report \u003c/li\u003e\n\u003cli\u003eFilonchyk M, Hurynovich V, Yan H. Impact of COVID-19 lockdown on air quality in Poland, Eastern Europe. Environmental Research. 2020; 110454. https://doi.org/10.1016/j.envres.2020.110454 \u003c/li\u003e\n\u003cli\u003eLian X, Huang J, Huang R, Liu C, Wang L, Zhang T. Impact of city lockdown on the air quality of COVID-19-hit Wuhan city. Science of the Total Environment. 2020; 742:140556. https://doi.org/10.1016/j.scitotenv.2020.140556 \u003c/li\u003e\n\u003cli\u003eMahato S, Pal S, Ghosh KG. Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India. Science of the Total Environment. 2020; 730:139086. https://doi.org/10.1016/j.scitotenv.2020.139086 \u003c/li\u003e\n\u003cli\u003ePutaud J-P, Pisoni E, Mangold A, Hueglin C, Sciare J, Pikridas M, et al. Impact of COVID-19 lockdowns in 2020 on particulate matter air pollution in Europe. Atmospheric Chemistry and Physics. 2023; 23:10145\u0026ndash;10161. https://doi.org/10.5194/egusphere-2023-434 \u003c/li\u003e\n\u003cli\u003eShi X, Brasseur GP. The response in air quality to the reduction of Chinese economic activities during the COVID-19 outbreak. Geophysical Research Letters. 2020; 47:e2020GL088070. https://doi.org/10.1029/2020GL088070 \u003c/li\u003e\n\u003cli\u003eSicard P, De Marco A, Agathokleous E, Feng Z, Xu X, Paoletti E, et al. Amplified ozone pollution in cities during the COVID-19 lockdown. Science of the Total Environment. 2020; 735:139542. https://doi.org/10.1016/j.scitotenv.2020.139542 \u003c/li\u003e\n\u003cli\u003eSiciliano B, Carvalho G, da Silva CM, Arbilla G. The impact of COVID-19 partial lockdown on primary pollutant concentrations in the atmosphere of Rio de Janeiro and S\u0026atilde;o Paulo Megacities (Brazil). Bulletin of Environmental Contamination and Toxicology. 2020; 105(1):2-8. https://doi.org/10.1007/s00128-020-02907-9 \u003c/li\u003e\n\u003cli\u003eTob\u0026iacute;as A, Carnerero C, Reche C, Massagu\u0026eacute; J, Via M, Minguill\u0026oacute;n MC, et al. Changes in air quality during the lockdown in Barcelona (Spain) one month into the SARS-CoV-2 epidemic. Science of the Total Environment. 2020; 726:138540. https://doi.org/10.1016/j.scitotenv.2020.138540 \u003c/li\u003e\n\u003cli\u003eVel\u0026aacute;squez RMA, Lara JVM. Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima. Urban Climate. 2020; 33:100664. https://doi.org/10.1016/j.uclim.2020.100664 \u003c/li\u003e\n\u003cli\u003eZambrano-Monserrate MA, Ruano MA. Has air quality improved in Ecuador during the COVID-19 pandemic? A parametric analysis. Air Quality, Atmosphere \u0026amp; Health. 2020; 13:929-938. https://doi.org/10.1007/s11869-020-00866-y \u003c/li\u003e\n\u003cli\u003eRegulation of the Minister of Health of 20 March 2020 on the declaration of an epidemic state in the territory of the Republic of Poland. Journal of Laws 2020, item 491. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200000491/O/D20200491.pdf \u003c/li\u003e\n\u003cli\u003eAct of 31 March 2020 amending the Act on unique solutions related to the prevention, prevention and combating of COVID-19, other infectious diseases and crises caused by them, and some other acts. Journal of Laws 2020, item 568. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200000568/T/D20200568L.pdf \u003c/li\u003e\n\u003cli\u003eOrdinance of the Council of Ministers of 30 October 2020 amending the Ordinance on the establishment of certain restrictions, orders and prohibitions in connection with the outbreak of an epidemic. Journal of Laws of 2020, item 1917. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200001917/O/D20201917.pdf \u003c/li\u003e\n\u003cli\u003eOrdinance of the Council of Ministers of 6 November 2020 amending the Ordinance on the establishment of certain limits, orders and prohibitions in connection with the outbreak of an epidemic. Journal of Laws of 2020, item 1972. 2020. https://isap.sejm.gov.pl/isap.nsf/download.xsp/WDU20200001972/O/D20201972.pdf\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PM10, PM2.5, COVID-19, air pollution, NO2, B(a)P, Poland","lastPublishedDoi":"10.21203/rs.3.rs-5888206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5888206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe COVID-19 pandemic, which began in 2019, compelled governments worldwide to implement various measures to limit the spread of the virus, including restrictions on mobility and economic activity. These restrictions directly impacted air pollutant emissions, typically linked to heavy road traffic, industry, air transport, and other forms of human activity. In Poland, as in many other countries, a notable change in air quality was observed in 2020, which became the focus of numerous studies. This article analysed the impact of the pandemic on air pollution in Poland in 2020, comparing data from this period with that of the previous year, 2019. The study was based on data from the General Inspectorate for Environmental Protection (GIOŚ), which included measurements of the concentrations of particulate matter (PM10, PM2.5), nitrogen dioxide (NO₂), and benzo(a)pyrene. The analysis results indicated an evident reduction in pollutant concentrations in 2020 compared to 2019. This decrease was especially noticeable during lockdowns, when transport, industry, and other emission sources faced restrictions. The pollution reduction was most pronounced in urban areas, where transport and economic activity were most concentrated. Another important element of the study was spatial differentiation, which considered differences in pollution levels between large cities and rural areas. It is also worth noting that the pandemic's impact on air quality was seasonal, resulting from meteorological conditions such as temperature, humidity, and wind speed. These conditions were crucial for the spread of pollutants and their concentration in different parts of the year. In addition, the article emphasises the role of transport, especially road transport, in pollutant emissions, indicating the impact that reducing the number of vehicles on the roads had on improving air quality. Findings highlight the substantial impact of reduced human activity on air pollutant levels during pandemic restrictions. However, it also draws attention to the need for further actions to improve air quality in the long term. The conclusions from this study can provide a basis for developing more effective environmental policies that consider both health and ecological aspects of air pollutant emissions.\u003c/p\u003e","manuscriptTitle":"Changes in air quality in Poland in 2020 in the context of the COVID-19 pandemic: spatial and seasonal analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-29 10:56:54","doi":"10.21203/rs.3.rs-5888206/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-19T20:53:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T13:55:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-07T11:53:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203887446444433925546019661091926697953","date":"2025-04-29T11:08:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46256844726313690677098794968205628249","date":"2025-04-28T05:37:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-27T08:40:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-23T14:18:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Sciences Europe","date":"2025-04-22T09:50:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-sciences-europe","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eseu","sideBox":"Learn more about [Environmental Sciences Europe](http://enveurope.springeropen.com)","snPcode":"12302","submissionUrl":"https://submission.nature.com/new-submission/12302/3","title":"Environmental Sciences Europe","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d96fc9af-7a05-4213-9834-baa379a42476","owner":[],"postedDate":"April 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-07T16:08:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-29 10:56:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5888206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5888206","identity":"rs-5888206","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}