Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models
- Q1: Are changes to atmospheric composition limited to strongly polluted regions, or do they extend to remote and relatively pristine areas as well, such as the Alps?
- Q2: What is the magnitude, and even the sign (due to complex and non-linear effects), of the variations of surface air pollutant concentrations in the Alps during the confinement periods? Are these effects constant throughout 2020 or do they change in the distinct phases of the control measures?
- Q3: What source profiles can be identified in the Alps? Which of them actually change during the COVID-19 lockdown and which ones remain stable?
- Q4: Do the estimates of the «lockdown effect» from different methods agree with each other? How accurate are the existing chemical transport models (CTMs), their emission inventories, and, notably, their modifications during the pandemic?
- Q5: How large is the influence of Alpine meteorology in 2020 compared to the effect of curtailed emissions?
- We focus on a mountainous region in the European Alps, the Aosta Valley (Section 2.1). In particular, we consider measurements at five stations located at short spatial distance (<70 km) in different types of environments (traffic, urban background, industrial, semi-rural, and rural).
- In contrast to most of the scientific literature available until now, only covering the first half of year 2020, we analyse all-year-round measurements, and we also determine the air quality changes during the following “waves” of the pandemic.
- We employ a set of different methodologies to assess the atmospheric composition changes linked to the lockdown. We do not only examine the anomalies with reference to the average concentrations from previous years, but we also integrate statistical models including weather normalisation, CTMs, and source apportionment techniques based on aerosol chemical composition, size, and optical properties. Each of these techniques has merits and limitations, which are extensively discussed in Section 3.
- To support and complement the measurements at the surface, we take into consideration aerosol vertical profiles and column-integrated quantities (NO vertical column density and aerosol optical depth).
2.1. Investigated Area and Sampling Sites
2.2. Experimental Setup
2.3. Definition of the Lockdown Phases Based on Regional and National Regulations
3.1. Comparison to Previous Years’ Averages
3.2. Predictive Statistical Models (Random Forest)
3.3. Chemical Transport Model
3.3.1. Emissions and Their Modifications during the Pandemic
3.3.2. Diagnostic Meteorological Model and Turbulence Pre-Processor
3.4. Aerosol Source Apportionment
3.4.1. Positive Matrix Factorisation
3.4.2. Optical Properties at the Surface
4.1. Meteorological Context in 2020
- P1 presents only few days with easterly winds, while westerly circulation is above average. The temperature in P1 during 2020 is also higher, on average, than the previous years;
- P2, P3, and P4 in 2020 feature more days than average with easterly winds (indeed, 2020 holds the record of the last years in P2 and P4);
- Days in P5 with persistent westerly flows are more frequent in 2020 than average, while the opposite occurs for easterly winds. The total precipitation amount is larger than average in Aosta and Donnas;
- Days with westerly flows are fewer than average in P6 in 2020. Moreover, the temperature in Aosta in this period is lower than average. Thus, although precipitation is less abundant, snowfalls in Aosta are more frequent than average (about 9 days in 2020 compared to 1 day, e.g., in 2019 and 2018).
- P1 is characterised by some episodes of advection of polluted air masses from the Po basin (for a total of 25 days, i.e., 37% of the time in the period). Saharan dust is also transported on seven days overall in this period.
- P2 features an extraordinarily long series of transport episodes of fine particles from the Po basin (almost continuously from 14 March to 13 April, i.e., 88% of the days), according to the frequent easterly wind flows mentioned above, and mineral dust from Sahara (mainly floating at some km from the surface without settling on the ground but detected by the ALC and the sun/sky radiometer, Section 4.5). Within this period, moreover, we notice a remarkable and very unusual transport of dust particles from the area of the Caspian sea and Aral lake (e.g., ) between 28 and 30 March, leading to instantaneous PM concentrations g m in Aosta–downtown, with these particles being mostly concentrated in the coarse mode.
- During P3, transport from the Po basin occurs for a dozen days (62%, according to the larger-than-usual frequency of easterly winds), with both fine and coarse particles involved (these latter likely still circulating from the previous long-range events).
- More than 50% and about 45% of the days are affected by advection of fine and coarse aerosol from the Po basin in P4 and P5, respectively. In line with the 2020 increase in westerly winds in P5, the latter fraction is lower than average for the summer–autumn months, which, in 2020, feature a long sequence of events in September (19 days continuously) but almost no episodes in October.
- Finally, in about 38% of the days in P6 the air quality in the Aosta Valley is impacted by the transport of fine particles from the Po basin, although easterly winds are too weak and intermittent to be detected by our automatic weather pattern classification, while dust is identified (but not at the surface) on 3 days only.
4.2. Changes in Surface Gaseous Pollutant Concentrations
4.3. Changes in Surface PM Concentrations
4.4. Aerosol Source Apportionment
4.5. Vertical Profiles and Column Amounts
5. Discussion and Conclusions
- Q1–3: Changes in air pollutant concentrations, their magnitude, sign, and sources. At all examined stations, even the rural ones, relevant changes in air quality resulting from the confinement regulations can be identified. The largest variations occur for NO due to curtailed emissions from vehicular traffic. NO decreases by 60%–80% in March–May 2020 and by 20%–60% in November–December, depending on the site, while NO decreases slightly less, by about 40%–50% and 20%–25% in the two periods, respectively. These values agree with the results from previous studies in northern Italy and in other locations worldwide. A minor decrease at the beginning of the 2020–2021 winter season also highlights the importance of considering, as conducted here, a data set encompassing both the first and the following pandemic waves and the corresponding regulations. Among trace gases, the ozone does not show any relevant increase, contrary to what has been found in spring 2020 in more urbanised areas. Instead, O variations are modest and of different signs depending on the examined period and location and are likely affected by meteorology, e.g., Foehn winds bringing ozone-rich air masses from higher altitudes to the surface, and atmospheric exchanges with the Po basin. Particulate matter concentrations show maximum decreases of only 27% (when taking meteorology into account) due to their multifaceted nature and balance between contrasting processes. Notably, as found from the analysis of the aerosol microphysical properties (size distributions), fine particles represent a large fraction of the aerosol mass in the Aosta Valley, and they increase during the lockdown periods due to transport by intensified easterly winds (from the Po basin) in 2020 compared to the average of previous years. In particular, during the first lockdown period (P2), medium- and long-range transport contributes to the increase in PM concentrations by about 20%–30%, as determined from the chemical aerosol characterisation at the surface (secondary particles) and the retrieval of aerosol mass concentration along the vertical column with remote instruments (these latter also accounting for dust). Although not explicitly proven here, enhanced secondary aerosol production in their source area, in addition to meteorology, could contribute to the observed increase. Based on the optical source apportionment and chemical speciation, no relevant increase in biomass burning emissions from residential heating due to stay-at-home policies is observed in Aosta–downtown, although conditions in more rural areas might be different. Conversely, the mass concentration of the largest particles decreases, likely as a result of reduced resuspension by traffic, and, in Aosta, of the shutdown of the steel mill, as confirmed by the aerosol chemical speciation. The sum of the contributions from all local sources expected to decrease (traffic, soil, and industry) is consistent with the overall measured PM10 reduction.A limitation of this study is the availability of only measurements from stations located at the bottom of the valley, whereas no high-altitude station is yet available in our network to check if the air quality is influenced by the lockdown even there. As a partial integration, the analysis of the vertical column with remote sensing instrumentation shows that the aerosol profiles are mostly influenced by long-range transport, with the possible exception of a very shallow layer close to the surface, about 500 m thick, where we find negative concentration anomalies in correspondence to rush hours and mixing layer development. This aspect should be explored in more depth and in a wider context in future research. Conversely, the NO vertical column is strongly impacted by the lockdown, following similar changes as the ones found at the surface.The observed increase in atmospheric turbidity in spring 2020, compared to the previous years, is also noteworthy for another reason. Indeed, in the same period, central and southern Europe have been affected by the descent of ozone-poor air masses towards lower latitudes originating from a strong ozone column depletion over the Arctic. Simultaneously, an increase in the solar erythemal irradiance at ground by about 10% and 18% in April and May, respectively, is visible over the Aosta Valley . This increase, however, is found to be too large to be solely explained by the effect of ozone. Since the atmospheric turbidity, as found here, also increases, the most likely explanation for the irradiance increase is the unusually low cloud fraction, as already demonstrated over western Europe by another study . Sunshine duration measurements in the Aosta Valley, increasing up to 14% in that period compared to previous years’ average (not shown), support this hypothesis.
- Q4: Agreement between observations and models. A predictive statistical model was proven to work well with NO and PM, with correlation indices generally >0.9 and >0.7, respectively. The results are useful to take the effects of weather into consideration and to decouple meteorology and emissions. The deviations between the measured concentrations in 2020 and the output of the statistical model (representing the counterfactual scenario needed for the analysis) were compared with the difference between the output of the FARM chemical transport model run with a curtailed and a standard emission scenario. For NO and PM, the comparison of the two methods provides comparable relative changes of concentrations due to the lockdown, thus confirming that both emission sources and processes are well represented by the modelling chain and that the reasons of the observed variations are well understood. For O, the effect of the lockdown resulting from the statistical predictive model and the chemical transport model even differs in sign. This could be due to meteorological phenomena not taken into account in the same way by both methods and to the influence of atmospheric dynamics acting on a wider scale, e.g., over the whole northern Italy. However, even for O, the deviations between the concentration changes assessed by the statistical and the deterministic models are generally within 10%–20%.
- Q5: The influence of meteorology. The peculiar weather phenomena occurring in mountain valley regions, such as thermally driven circulation and Foehn winds, turn out to be relevant in this investigation, as well as larger-scale dynamics for aerosol transport. For example, without accounting for the increase in easterly winds, bringing secondary aerosol in the valley from March to June, the effect of the lockdown regulations on PM would have been underestimated. Indeed, the influence of the meteorology alone during the early lockdown phase in 2020, conducive to pollutant transport/accumulation, would have increased the surface concentrations by, e.g., 52%–89% (NO), 17%–18% (NO), and 8%–25% (PM and PM10) in Donnas and Aosta–downtown. Similarly, without accounting for the frequent westerly winds in summer–autumn, the effect of reduced emissions would have been overestimated. Finally, some of the observed O changes could not have been understood without a reference to meteorology.The random forest approach provides a very useful framework to quantitatively assess the relative importance of meteorological variables on air quality. Profiling instruments and retrievals of column amounts are helpful tools to identify long-range transport and to correctly interpret observations at the surface and their changes.
Data Availability Statement
Conflicts of Interest
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|Station||Measured Quantity||Instruments||Data Availability (Used)|
1325 m a.s.l.
45.82 N, 6.96 E
PM and PM hourly concentration
and size distribution
PM hourly concentration
Standard meteorological variables
2018–now a (2018–2020)
580 m a.s.l
45.73 N, 7.32 E
PM and PM daily concentration
PM and PM hourly concentration
and size distribution
Water-soluble anion-cation daily concentration
EC/OC on PM samples
Levoglucosan on PM samples
Metals on PM samples
Light absorption by particles
Standard meteorological variables
Dionex ion chromatography system
Sunset thermo-optical analyser
Trace1300 Thermo Scientific
Aethalometer AE33 Magee Sci.
2012–now b (2015–2020)
September 2019–now (2020)
2017–now c (2017–2020)
2018–now c (2018–2020)
2000–now d (2015–2020)
570 m a.s.l
45.73 N, 7.32 E
PM daily concentration
PM and PM hourly concentration
and size distribution
Metals on PM samples
|2018–now (not used here)|
2012–now (not used here)
560 m a.s.l
45.74 N, 7.35 E
Column aerosol properties
Aerosol vertical profile
PM and PM hourly concentration
and size distribution
|2007–now e (2015–2020)|
2012–now f (2015–2020)
April 2015–now (2016–2020)
June 2017–February 2019
(June 2017–February 2019)
341 m a.s.l.
45.60 N, 7.77 E
PM daily concentration
Standard meteorological variables
|Short Name||Key Dates (dd/mm/yyyy)||COVID-19 Restrictions|
|P1(JFM)||1 January 2020–8 March 2020||Pre-lockdown, business-as-usual phase|
|P2(MA)||9 March 2020–13 April 2020||Strict lockdown, stay-at-home policy,|
and steel mill closed
|P3(AM)||14 April 2020–4 May 2020||Confinement measures continue,|
steel mill reopens
|P4(MJ)||5 May 2020–3 June 2020||Progressive lockdown easing,|
justified movements within the region allowed
|P5(JJASO)||4 June 2020–31 October 2020||Further relaxation, travels between regions allowed,|
schools open in September
|P6(ND)||1 November 2020–31 December 2020||Schools partially close, ban on travels between regions|
|Site||Modelled Air Pollutants||Meteorological Variables|
(Same for All Stations)
(Same for All Stations)
|NO, NO, PM|
NO, NO, O,
NO, NO, O, PM
wind speed and direction,
global solar radiation,
daily precipitation amount
day of week,
date (Unix timestamp)
|Station||NO (%)||NO (%)||O (%)||PM (%)||PM (%)|
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Diémoz, H.; Magri, T.; Pession, G.; Tarricone, C.; Tombolato, I.K.F.; Fasano, G.; Zublena, M. Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models. Atmosphere 2021, 12, 1006. https://doi.org/10.3390/atmos12081006
Diémoz H, Magri T, Pession G, Tarricone C, Tombolato IKF, Fasano G, Zublena M. Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models. Atmosphere. 2021; 12(8):1006. https://doi.org/10.3390/atmos12081006Chicago/Turabian Style
Diémoz, Henri, Tiziana Magri, Giordano Pession, Claudia Tarricone, Ivan Karl Friedrich Tombolato, Gabriele Fasano, and Manuela Zublena. 2021. "Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models" Atmosphere 12, no. 8: 1006. https://doi.org/10.3390/atmos12081006