Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models

Concentration and size distribution of atmospheric particles in southern Italy during COVID-19 lockdown period

Many countries imposed lockdown (LD) to limit the spread of COVID-19, which led to a reduction in the emission of anthropogenic atmospheric pollutants. Several studies have investigated the effects of LD on air quality, mostly in urban settings and criteria pollutants. However, less information is available on background sites, and virtually no information is available on particle number size distribution (PNSD). This study investigated the effect of LD on air quality at an urban background site representing a near coast area in the central Mediterranean. The analysis focused on equivalent black carbon (eBC), particle mass concentrations in different size fractions: PM_2.5 (aerodynamic diameter D_a < 2.5 μm), PM₁₀ (D_a < 10 μm), PM_10-2.5 (2.5 < D_a < 10 μm); and PNSD in a wide range of diameters (0.01-10 μm). Measurements in 2020 during the national LD in Italy and period immediately after LD (POST-LD period) were compared with those in the corresponding periods from 2015 to 2019. The results showed that LD reduced the frequency and intensity of high-pollution events. Reductions were more relevant during POST-LD than during LD period for all variables, except quasi-ultrafine particles and PM_10-2.5. Two events of long-range transport of dust were observed, which need to be identified and removed to determine the effect of LD. The decreases in the quasi-ultrafine particles and eBC concentrations were 20%, and 15-22%, respectively. PM_2.5 concentration was reduced by 13-44% whereas PM_10-2.5 concentration was unaffected. The concentration of accumulation mode particles followed the behaviour of PM_2.5, with reductions of 19-57%. The results obtained could be relevant for future strategies aimed at improving air quality and understanding the processes that influence the number and mass particle size distributions.

A spatiotemporal analysis of NO 2 concentrations during the Italian 2020 COVID-19 lockdown

When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify-in space and time-the effectiveness of the adopted strategy. The lockdown measures taken worldwide in 2020 to reduce the spread of the SARS-CoV-2 virus can be envisioned as a policy intervention with an indirect effect on air quality. In this paper we propose a statistical spatiotemporal model as a tool for intervention analysis, able to take into account the effect of weather and other confounding factor, as well as the spatial and temporal correlation existing in the data. In particular, we focus here on the 2019/2020 relative change in nitrogen dioxide (NO 2 ) concentrations in the north of Italy, for the period of March and April during which the lockdown measure was in force. We found that during March and April 2020 most of the studied area is characterized by negative relative changes (median values around - 25%), with the exception of the first week of March and the fourth week of April (median values around 5%). As these changes cannot be attributed to a weather effect, it is likely that they are a byproduct of the lockdown measures. There are two aspects of our research that are equally interesting. First, we provide a unique statistical perspective for calculating the relative change in the NO 2 by jointly modeling pollutant concentrations time series. Second, as an output we provide a collection of weekly continuous maps, describing the spatial pattern of the NO 2 2019/2020 relative changes.

COVID-19 lockdown shows how much natural mountain regions are affected by heavy tourism

Mountain areas in Poland are among the most frequented tourist destinations and such intensive tourism negatively affects the natural environment. The COVID-19 pandemic and the resulting lockdown restricted travel for a few months in 2020, providing a unique opportunity to observe the studied mountain environment without the impact of typical tourist traffic. This study is based on the determination of antibiotic content, hydrochemical parameters, enumeration of culturable bacterial water quality indicators, antimicrobial susceptibility tests together with extended spectrum beta-lactamase (ESBL) gene detection in waterborne E. coli and NGS-based bacterial community composition at six sites along the Białka river valley (one of the most popular touristic regions in Poland) in three periods: in summer and winter tourist seasons and during the COVID-19 lockdown. The results of individual measurements showed decreased numbers of bacterial indicators of water contamination (e.g. numbers of E. coli dropped from 99 × 10⁴ CFU/100 ml to 12 CFU/100 ml at the most contaminated site) and the share of antimicrobial resistant E. coli (total resistance dropped from 21% in summer to 9% during lockdown, share of multidrug resistant strains from 100 to 44%, and ESBL from 20% in summer to none during lockdown). Antibiotic concentrations were the highest during lockdown. The use of multivariate analysis (principal component analysis - PCA and heatmaps) revealed a clear pattern of tourism-related anthropogenic pressure on the water environment and positive impact of COVID-19 lockdown on water quality. PCA distinguished three major factors determining water quality: F1 shows strong effect of anthropogenic pressure; F2 describes the lockdown-related quality restoration processes; F3 is semi-natural and describes the differences between the most pristine and most anthropogenically-impacted waters.

Sensitivity of Pollutant Concentrations to the Turbulence Schemes of a Dispersion Modelling Chain over Complex Orography

Atmospheric circulation over mountainous regions is more complex than over flat terrain due to the interaction of flows on various scales: synoptic-scale flows, thermally-driven mesoscale winds and turbulent fluxes. In order to faithfully reconstruct the circulation affecting the dispersion and deposition of pollutants in mountainous areas, meteorological models should have a sub-kilometer grid spacing, where turbulent motions are partially resolved and the parametrizations of the sub-grid scale fluxes need to be evaluated. In this study, a modelling chain based on the Weather Research and Forecasting (WRF) model and the chemical transport model Flexible Air Quality Regional Model (FARM) is applied to estimate the pollutant concentrations at a 0.5 km horizontal resolution over the Aosta Valley, a mountainous region of the northwestern Alps. Two pollution episodes that occurred in this region are reconstructed: one summer episode dominated by thermally-driven winds, and one winter episode dominated by synoptic-scale flows. Three WRF configurations with specific planetary boundary layer and surface layer schemes are tested, and the numerical results are compared with the surface measurements of meteorological variables at twenty-four stations. For each WRF configuration, two different FARM runs are performed, with turbulence-related quantities provided by the SURface-atmosphere interFace PROcessor or directly by WRF. The chemical concentrations resulting from the different FARM runs are compared with the surface measurements of particulate matter of less than 10 µm in diameter and nitrogen dioxide taken at five air quality stations. Furthermore, these results are compared with the outputs of the modelling chain employed routinely by the Aosta Valley Environmental Protection Agency, based on FARM driven by COSMO-I2 (COnsortium for Small-scale MOdelling) at 2.8 km horizontal grid spacing. The pollution events are underestimated by the modelling chain, but the bias between simulated and measured surface concentrations is reduced using the configuration based on WRF turbulence parametrizations, which imply a reduced dispersion.

Change Points Detection and Trend Analysis to Characterize Changes in Meteorologically Normalized Air Pollutant Concentrations

Identifying changes in ambient air pollution levels and establishing causation is a research area of strategic importance to assess the effectiveness of air quality interventions. A major challenge in pursuing these objectives is represented by the confounding effects of the meteorological conditions which easily mask or emphasize changes in pollutants concentrations. In this study, a methodological procedure to analyze changes in pollutants concentrations levels after accounting for changes in meteorology over time was developed. The procedure integrated several statistical tools, such as the change points detection and trend analysis that are applied to the pollutants concentrations meteorologically normalized using a machine learning model. Data of air pollutants and meteorological parameters, collected over the period 2013–2019 in a rural area affected by anthropic emissive sources, were used to test the procedure. The joint analysis of the obtained results with the available metadata allowed providing plausible explanations of the observed air pollutants behavior. Consequently, the procedure appears promising in elucidating those changes in the air pollutant levels not easily identifiable in the original data, supplying valuable information to identify an atmospheric response after an intervention or an unplanned event.

The 2020 Arctic ozone depletion and signs of its effect on the ozone column at lower latitudes

The present study discusses the effect of the ozone depletion that occurred over the Arctic in 2020 on the ozone column in central and southern Europe by analysing a data set obtained from ground-based measurements at six stations placed from 79 to 42°N. Over the northernmost site (Ny-Ålesund), the ozone column decreased by about 45% compared to the climatological average at the beginning of April, and its values returned to the normal levels at the end of the month. Southwards, the anomaly gradually reduced to nearly 15% at 42°N (Rome) and the ozone minimum was detected with a delay from about 6 days at 65°N to 20 days at 42°N. At the same time, the evolution of the ozone column at the considered stations placed below the polar circle corresponded to that observed at Ny-Ålesund, but at 42°-46°N, the ozone column turned back to the typical values at the end of May. This similarity in the ozone evolutional patterns at different latitudes and the gradually increasing delay of the minimum occurrences towards the south allows the assumption that the ozone columns at lower latitudes were affected by the phenomenon in the Arctic. The ozone decrease observed at Aosta (46°N) combined with predominantly cloud-free conditions resulted in about an 18% increase in the erythemally weighted solar ultraviolet irradiance reaching the Earth's surface in May.