Helsinki is located in southern Finland, at the shore of the Gulf of Finland in the Baltic Sea. The capital is Finland's largest city, with 0.66 million inhabitants or 1.59 million inhabitants including its sub-regional units. Finland has 497 passenger cars per 1000 inhabitants, which is below the average motorisation rate in the European Union (EU). However, Helsinki's car density is ∼ 1035 cars km-2, which is comparable with densities observed in other cities across Europe.

Urban-background aerosol data were obtained from the SMEAR III research station (Jarvi et al., 2009), located on the Kumpula campus of the University of Helsinki. Measurements are taken at 4 m above ground level and at distances > 125 m from highly trafficked roads bordering the site. The busy roadways experience 44 000 vehicles per workday (Järvi et al., 2012). The station's immediate surroundings also include multi-storey buildings, access roads, allotted parking bays, and green space.

Roadside aerosol data were obtained from a supersite monitoring station along one of Helsinki's main thoroughfares known as Mäkelänkatu. The street is ∼ 42 m in width and is flanked by three- and four-storey buildings, yielding an aspect ratio of 0.40 (often referred to as an avenue canyon) (Rönkkö et al., 2017) and experiences 28 000 vehicles per day (Helin et al., 2018; Kuula et al., 2020). The station's immediate surroundings also include six lanes of traffic (three in each direction of travel), a central tramline bordered by tall vegetation, two footpaths, and on-street parking.

Leipzig is located in the German state of Saxony in eastern Germany. Leipzig is the eighth most populated city in Germany, with 0.6 million inhabitants. Germany has 574 passenger cars per 1000 inhabitants, which is comparable with the average motorisation rate in the EU. Leipzig's vehicle density is ∼ 913 vehicles km-2, which is comparable with densities observed in other cities across Europe.

Urban-background aerosol data were obtained from an atmospheric research station operated by the Leibniz Institute for Tropospheric Research (TROPOS) within the Leipzig Science Park. Measurements are taken on the roof of an institute building at 16 m above ground level and at distances > 100 m from highly trafficked roads bordering the site (Klose et al., 2009; Birmili et al., 2016). The Leipzig Science Park contains other research institutes and related companies, green space, and allotted parking bays, including a multi-storey car park. Its perimeter includes transport infrastructure (road, rail, and tramways), commercial property (restaurants, hotels, a petrol station, etc.), residential property, on-street parking, and green space.

Roadside aerosol data were obtained from a permanent observation site located along an important connecting road in the east of the city known as Eisenbahnstrasse. Measurements are taken from an apartment window at 6 m above ground level on the northern side of the street. The street is ∼ 20 m in width and is flanked by multi-storey period buildings, yielding an aspect ratio of 0.90, and is used by 12 000 vehicles per working day (Birmili et al., 2016). The station's immediate surroundings also include two lanes of traffic (one in each direction of travel), an integrated tramline, on-street parking, two bicycle lanes (one in each direction of travel), two footpaths, and scant vegetation.

Budapest is located in the Carpathian Basin in central Hungary. It is the capital and the largest city of the country, with 1.72 million inhabitants. Hungary has 395 passenger cars per 1000 inhabitants, which is one of the lowest motorisation rates in the EU. However, Budapest's car density is ∼ 1315 cars km-2, which is comparable with densities commonly observed in other European cities.

Urban-background aerosol data were obtained from the Budapest platform for Aerosol Research and Training (BpART) laboratory, located on the second-floor balcony of the northern block of the Lágymányos Campus of Eötvös Loránd University. The balcony is 11 m above the street level of the closest road and is situated 85 m from the right bank of the Danube River (Salma et al., 2016). Sampling inlets and sensors are set up at heights of between 80 and 150 cm above the rooftop level of the measurement container.

London is located in southeastern England (United Kingdom, UK). The capital is the UK's largest city, with 9 million people occupying Greater London. The UK has 589 passenger cars per 1000 inhabitants, which is comparable with the average motorisation rate in the EU. However, Greater London's car density is ∼ 1938 cars km-2, which is well above average densities commonly observed in other cities across Europe.

Roadside aerosol data were obtained from a supersite monitoring station, located along Marylebone Road opposite one of London's top attractions, Madame Tussauds. Measurements are taken on the roof of a cabin positioned kerbside at 4 m above ground level (Harrison et al., 2019). The street is ∼ 34 m in width and is flanked by multi-storey buildings, yielding an aspect ratio of 1.00 (often referred to as a regular street canyon), and is used by 80 000 vehicles per day (Harrison et al., 2019). The monitoring station's surroundings also include six lanes of traffic (three in each direction of travel), two footpaths, and scant vegetation. Analyses of air quality data from this site have been reported by Kamara and Harrison (2021).

Factors attributed to nucleation were resolved at all sites. The factors had a major mode in the size distribution, which peaked at ∼ 11–22 nm (Fig. 2a), and a mass distribution dominated by particles in the accumulation mode (Fig. 2b). Factor contributions typically peaked in the afternoon and with busy traffic periods (Fig. 3a) and were higher on weekdays compared to weekends (Fig. 3b). The factors were associated to varying degrees with BC, NOx, SO2, O3, and PM2.5 (Fig. 4). Additionally, the factors were consistently associated with a low CS value (Fig. 4), which is a key determinant for NPF in urban environments (Deng et al., 2021). CS is the largest sink for vapours such as sulfuric acid, as well as other low-volatility molecules, and occurs synchronously with high coagulation losses of small particles. We inferred that this factor is likely the sum of particles produced by means of photochemically induced nucleation processes, as well as some combustion-related processes, such as ultrafine vehicle emissions and the formation of new particles through the dilution and cooling of vehicle exhaust (Charron and Harrison, 2003; Pérez et al., 2010). The diurnal profiles at most sites suggest a predominantly non-traffic formation source. However, the nucleation factor at HEL_RS is mainly related to the traffic source, since the diurnal variation shows clear morning and afternoon rush hour peaks and the contribution of NOx and BC are very high.

Factors attributed to road trafficsvf were resolved at all sites. The factors had a major mode in the size distribution, which peaked at ∼ 25–40 nm (Fig. 2a), and a mass distribution dominated by Aitken and/or accumulation mode particles (Fig. 2b). Factor contributions typically peaked in the morning and afternoon/evening (Fig. 3a); were higher on weekdays compared to weekends (Fig. 3b); and were associated to varying degrees with combustion-related pollutants including BC, NOx, SO2, and PM2.5 (Fig. 4). In Europe, diesel vehicles are responsible for much of the exhaust PM from road traffic (Damayanti et al., 2023). Particles emitted in diesel exhaust fall into two main categories: semi-volatile and solid graphitic (black carbon) particles (Harrison et al., 2018; Kittelson et al., 2006). We inferred that these factors likely represent the former particle type, as well as a likely contribution from other mobile and/or stationary combustion-related activities (i.e. cooking and heating emissions). The factors closely resemble those referred to as “traffic 1” in the literature, typically in reference to spark-ignition vehicle emissions or freshly emitted traffic particles (Hopke et al., 2022) and may include petrol vehicle emissions.

Factors attributed to road trafficsf were resolved at HEL_RS and LDN_RS. The factors had a major mode in the size distribution, which peaked at ∼ 55–90 nm (Fig. 2a), and a mass distribution dominated by particles in the Aitken and/or accumulation mode (Fig. 2b). Factor contributions typically peaked in the morning and afternoon/evening (Fig. 3a); were higher on weekdays compared to weekends (Fig. 3b); and were associated to varying degrees with combustion-related pollutants including BC, NOx, SO2, and PM2.5 (Fig. 4). We inferred that these factors predominantly represent the solid particle mode arising from diesel road traffic (Harrison et al., 2018; Kittelson et al., 2006). The factors closely resemble those referred to as “traffic 2” in the literature, typically in reference to diesel vehicle emissions or distant traffic particles (Hopke et al., 2022).

Factors attributed to diffuse urban were mainly resolved at urban-background sites. The factors had a major mode in the size distribution, which peaked at ∼ 75–90 nm (Fig. 2a), and a mass distribution dominated by accumulation mode particles (Fig. 2b). Factor contributions typically peaked in the morning and evening (Fig. 3a), were higher on weekends compared to weekdays (Fig. 3b), and were associated to varying degrees with combustion-related pollutants including NOx and SO2 (Fig. 4). The factors closely resemble those referred to as “urban background” by Beddows et al. (2015) and later “diffuse urban” by Beddows and Harrison (2019), representing aged wood smoke and road traffic emissions. A contribution of aged natural aerosol may also be present in this factor. Urban background has other connotations, and therefore we opted to use diffuse urban as a factor name as it better categorised the emission source, with less confusion with the literature.

Factors attributed to O3-associated SA were resolved at BUD_UB and HEL_RS. The factors had a major mode in the size distribution, which peaked at ∼ 125–175 nm (Fig. 2a), and a mass distribution dominated by particles in the accumulation mode (Fig. 2b). Factor contributions peaked in the daytime (Fig. 3a), were higher on weekdays compared to weekends (Fig. 3b), and were strongly associated with O3 (Fig. 4). The exact nature of these factors are uncertain; however, they are consistent with other such observations (often referred to as O3-rich SA) in the available literature (Ogulei et al., 2007; Liu et al., 2014; Squizzato et al., 2019) and likely represent particles which have grown through the condensation of secondary material (Hopke et al., 2022). In an urban environment it is reasonable to presume that most SA precursors are anthropogenic, but an influence of natural SA precursors will also contribute some fraction of total SA.

Factors attributed to SIA were resolved at all sites. The factors had a major mode in the size distribution, which peaked at ∼ 175–265 nm (Fig. 2a), and a mass distribution dominated by accumulation mode particles (Fig. 2b). Factor contributions typically peaked in the morning and evening/night (Fig. 3a), were higher on weekdays compared to weekends (Fig. 3b), and were associated with a host of auxiliary variables (Fig. 4). Multimodal number size distributions have also been observed at other locations and suggest the presence of both local and distant particles thought to have been formed through the atmospheric processing of NOx and other gaseous precursor emissions (Ogulei et al., 2007; Kasumba et al., 2009).

During lockdown, total mean PNCs were lower at most urban-background (Fig. 5 and Table 3) and all roadside sites (Fig. 5 and Table 4) included in this study, in comparison to the reference years. Regression estimates also showed that measured PNCs were lower than predicted at the majority of monitoring sites (Fig. S7a), and the diurnal cycle of each source-related factor is similar for both the lockdown and reference years (Fig. S5).

Among urban-background sites, total mean PNCs were higher at LEJ_UB and lower at HEL_UB and BUD_UB during lockdown compared to the equivalent periods in the reference years (Fig. 5 and Table 3). Nucleation, road trafficsvf, and diffuse urban factors were primarily responsible for the changes in total mean PNCs at LEJ_UB.

Mean PNCs were lower at all of the roadside sites during lockdown compared to the equivalent periods in the reference years (Fig. 5 and Table 4). Changes to nucleation and road traffic factors were primarily responsible for the fall in total mean PNCs at roadside sites.

Mean PNCs from factors attributed to road trafficsvf, during reference and lockdown periods, were amongst the largest of the resolved factors, at both roadside and urban-background sites (Fig. 5 and Tables 3, 4). The response of road trafficsvf to lockdown restrictions was varied. Mean PNCs from factors attributed to road trafficsf factors were also substantial, regardless of lockdown measures (Fig. 5 and Table 4). However, their decrease during lockdown restrictions was consistent across all sites.

Among urban-background sites, mean PNCs from road trafficsvf factors were higher at LEJ_UB, comparable at HEL_UB, and lower at BUD_UB during lockdown compared to the equivalent periods in the reference years, with a mean change of +3.7 % across the three sites (Fig. 5 and Table 3). Large reductions in traffic volumes were observed on major roads across Finland (Riuttanen et al., 2021) and the German state of Saxony (Jaekel and Muley, 2022). However, the associated emission reductions may have been offset by increased emissions from private households. Fuel oils are regularly used in urban households for a variety of domestic activities and predominantly generate Aitken and nucleation mode particles (Tiwari et al., 2014). Lockdown restrictions had immediate and varied impacts on energy use, with increased residential demand due to people being confined to their homes. This points to a systematic misattribution of this factor throughout the literature, where this traffic factor contains some contribution from domestic heating. Road traffic volumes in central Budapest were also substantially reduced (Salma et al., 2020). These reductions were reflected in the road trafficsvf factor at BUD_UB.

At roadside sites, mean PNCs from road trafficsvf factors were comparable at HEL_RS and lower at LEJ_RS and LDN_RS during lockdown compared to the equivalent periods in the reference years, with a mean decrease of -21 % (Fig. 5 and Table 4). Mean PNCs from road trafficsf factors were also lower at HEL_RS and LDN_RS during lockdown, with a mean decrease of -39 % (Fig. 5 and Table 4). Changes to mean PNCs from road traffic factors were notably more pronounced at LDN_RS than at other roadside sites included in this study. This is in some measure due to the enormous volumes of traffic typically present along Marylebone Road which were significantly reduced during lockdown (Hicks et al., 2021). However, BC concentrations have reduced considerably in recent years (Fig. S7c), likely associated with the increased proportion of Euro 6-compliant (Euro VI-compliant) vehicles (Damayanti et al., 2023; Luoma et al., 2021). The adoption of Euro 6 (Euro VI) vehicle emission standards and the compulsory emission technologies (such as diesel particle filters, DPFs) will have impacted road traffic factors over time, especially the road trafficsf factors resolved at HEL_RS and LDN_RS. DPFs do not suppress the semi-volatile mode of the emissions with high efficiency (Damayanti et al., 2023), explaining the smaller reduction in road trafficsvf.

Mean PNCs from factors attributed to diffuse urban, during reference and lockdown periods, were amongst the largest of the resolved factors (Fig. 5 and Tables 3, 4). The response of these factors to lockdown measures was largely consistent, and the diurnal cycle in each source-related factor is similar for both the lockdown and reference years (Fig. S5).

Among urban-background sites, mean PNCs from diffuse urban factors were higher at LEJ_UB and lower at HEL_UB and BUD_UB during lockdown compared to the equivalent periods in the reference years, with a mean decrease of -11 % (Fig. 5 and Table 3). Mean PNCs from the factor were also lower at LEJ_RS during lockdown by -16 % (Fig. 5 and Table 4). Changes to mean PNCs from diffuse urban factors likely reflect variations in residential wood combustion and reductions in traffic volumes. As previously mentioned, large reductions in traffic volumes were reported across Helsinki (Riuttanen et al., 2021), the German state of Saxony (Jaekel and Muley, 2022), and central Budapest (Salma et al., 2020). Variations in residential wood combustion, on the other hand, may reflect responses to outdoor temperature fluctuations (Fig. S8), as well as the more social and cultural aspects of urban air pollution. It is commonplace in northern countries to use firewood in sauna stoves and various fireplaces as supplementary heating (Kukkonen et al., 2020). Reductions in BC concentrations in northern Helsinki may be related to decreased wood burning (Harni et al., 2023) and/or weather conditions during lockdown. Nevertheless, biomass burning has previously been identified as a major contributor to PM concentrations in Helsinki (PM2.5; Saarnio et al., 2012), Leipzig (PM10; van Pinxteren et al., 2016), and Budapest (PM2.5; Salma et al., 2017) during the heating period.

Mean PNCs from factors attributed to nucleation, during reference and lockdown periods, were amongst the largest of the resolved factors, irrespective of environment type (Fig. 5 and Tables 3, 4). The response of these factors to lockdown restrictions was varied.

Among urban-background sites, mean PNCs from nucleation factors were higher at HEL_UB and LEJ_UB and lower at BUD_UB during lockdown compared to the equivalent periods in the reference years, with a mean increase of 13 % (Fig. 5 and Table 3). Changes to mean PNCs from nucleation factors likely reflect variations to NPF, as well as reductions in primary and delayed primary emissions (Rönkkö et al., 2017). NPF in these urban areas is likely driven by sulfuric acid, bases such as dimethylamine, and OOMs likely from anthropogenic volatile organic compound (AVOC) oxidation (Lee et al., 2019), meaning our NPF is mostly driven by anthropogenic emissions. Variations in solar radiation (Fig. S8) could also influence NPF via photochemical processes (Shen et al., 2021) but do not explain the trends we see in our data. The insolation was markedly higher in London during the lockdown period than in previous years, but the other cities show only a small increase. Strong solar radiation favours OH production which through various formation and oxidation processes produces sulfuric acid and other low-volatility vapours in the atmosphere (Wang et al., 2023). NPF is inhibited by high particle surface area, which was lower during lockdowns at all sites except LEJ_UB (Fig. 6) (Du et al., 2022). Primary and delayed nucleation particles are linked to the number of vehicles on the road, as well as the associated emission technologies, which can significantly impact the formation mechanisms and composition of emitted nanocluster aerosol (Rönkkö et al., 2017). The mixed response of nucleation factors at urban-background sites to lockdown restrictions likely represents the interplay between these complex variables.

Across all urban-background sites, the largest increase to nucleation was at LEJ_UB, with a 92 % increase, where the greatest increase to traffic factors was also seen (51 % increase to road trafficsvf), while CS also increased (Fig. 6). The largest decrease in nucleation was at BUD_UB, with a 45 % decrease, where the greatest reduction in traffic factors was also seen (-36 % decrease to road trafficsvf), while CS decreased. Primary nanocluster aerosol will have a lifetime on the order of tens of minutes and will need to grow to 10 nm and also undergo dilution while being transported from the roadside to the urban-background measurement stations. Primary and delayed primary particle emissions will be less important here than at the roadside, and we infer a substantial role of primary gaseous traffic emissions in accelerating NPF (Brean et al., 2023).

Mean PNCs from factors attributed to secondary aerosols (O3-associated SA and SIA), during the reference and lockdown periods, were the smallest of the resolved factors, irrespective of environment type (Fig. 5 and Tables 3, 4). Though, SIA factors were the largest contributors to PMCs (Fig. 2b) due to the large median diameters of the modes. The response of these factors to the lockdown periods was consistent across all of the monitoring sites included in this study.

Mean PNCs from O3-associated SA and SIA factors were lower at urban-background and roadside sites during lockdown compared to the equivalent periods in the reference years, with mean decreases of -42 % in SIA at the urban-background sites and -42 % and -60 % for O3-associated SA and SIA at the roadside (Fig. 5 and Tables 3, 4). The response of SIA factors to lockdown restrictions may reflect reductions in gaseous precursor pollutants (Fig. 4). Mechanisms of secondary aerosol formation changed under lockdown conditions in Beijing, for example, when NOx levels substantially declined (Yan et al., 2023). SIA is generated by the transfer of inorganic material from the vapour to the aerosol phase following the chemical processing of emitted gas phase precursor emissions (McFiggans et al., 2015). Both precursors and particles may be emitted locally or transported over long distances from adjacent source regions. Road traffic is typically the largest source of NOx in an urban area, as well as an under-recognised source of ammonia (Cao et al., 2022). Ammonia reacts with acid pollutants such as oxidation products of NOx and SO2 to form ammonium nitrate and ammonium sulfate, which is essential for the generation of SIA in PM (Duan et al., 2021). These interactions may help to explain why changes to mean PNCs from SIA factors were typically more pronounced at roadside sites. Similarly, if O3-associated SA is generated through ozonolysis of VOCs, VOC concentrations will have declined substantially during lockdown periods, although O3 concentrations increased during lockdown periods (Shi et al., 2021). This decline to secondary aerosol is large, is consistent across all sites, and will result in a substantial reduction in PM mass.