Antonio Speranza

Air pollution is one of the most important environmental problems for rural, urban and industrial areas. This study assesses the concentrations, the possible interaction with the vegetation conditions and the sources of trace elements in atmospheric aerosol particles. To this aim, a novel holistic approach integrating biomonitoring techniques, satellite observations and multivariate statistical analysis was carried out in a semi-rural area before an on-shore reservoir (crude oil and gas) and an oil/gas pre-treatment plant identified as “Tempa Rossa” (High Sauro Valley—Southern Italy) were fully operative. The atmospheric trace element concentrations (i.e., Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, S, Ti and Zn) were assessed by “lichen-bag” monitoring. Satellite-derived normalized difference vegetation index (NDVI’) estimates were used to support the identification of environmental imbalances affecting vegetation conditions and linked to possible anthropogenic drivers. Principal component analysis (PCA) allowed identifying both natural and anthropogenic trace element sources, such as crustal resuspension, soil and road dust, traffic, biomass burning and agriculture practices. Empirical evidence highlighted an interaction between NDVI’ and S, Ni, Pb and Zn. The health risk impact of atmospheric trace elements on the exposed population, both adults and children, considering inhalation, ingestion and the dermal contact pathway, highlighted a possible non-carcinogenic risk concerning Ni and a not-negligible carcinogenic risk related to Cr(VI) for the adult population in the study area.

In the year 2020, Italy faced a pandemic due to the virus SARS-CoV-2 for short COVID-19. Following this pandemic, a national lockdown period was imposed and throughout the year 2020 various measures were taken by the government to limit the mobility of people and contain the mortality associated with COVID-19. In Italy, pandemic measures led to a reduction in anthropogenic activities and provided an unprecedented opportunity to evaluate the possible effects that restrictions on anthropogenic activities may have on the air quality. Two background site (i.e., Cipro and Cinecittà) and a traffic sites (i.e., Corso Francia) were studied in the city of Rome. PM₁₀ and PM_2.5 were considered for the years 2019 and 2020. Moreover, the vehicular mobility, the emission classes of the vehicles, and the people mobility were taken into consideration along with meteorological variables. A compositional data analysis was used to evaluate the effect of pandemic measures on the fine- and coarse-size fractions of PM in the three considered sites. The results showed that in the traffic site (i.e., Corso Francia site) in 2020, there was a reduction of fine-size fraction of PM of about 10% when compared to the data of 2019, whereas in the background site (i.e., Cinecittà site) in 2020 there was an increase of fine-size fraction of PM of about 14% when compared to the data of 2019. No variation in the coarse- and fine-size fractions of PM were observed at the background site Cipro. This study showed how, in an urban context, PM can be influenced by strong changes in people’s habits and in vehicular mobility such as those recorded during the investigated period and due to pandemic lockdown measures.

The proposed approach based on compositional data analysis was applied on simultaneous measurements of the mineral element concentrations of PM₁₀ and PM_2.5 from a typical suburban site with and without a Saharan event. The suburban site is located in the city of Rome. The selected mineral elements were Al, Si, Ca, Fe, Ti, Mg, and Sr. The data relating to these elements are reported in a previous study. The considered elements are mainly related to mineral matter. The proposed approach allows statistically validating that the mineral element concentrations of PM during days with a Saharan event differ from those without a Saharan event in terms of mineral element composition and size distribution. In particular, the results showed that the compositional data analysis applied to simultaneous measurements of mineral element concentrations of PM₁₀ and PM_2.5 is a helpful technique that can be used to study environmental sites affected by natural sources such as Saharan events. Moreover, the presented technique can be handy in all those conditions where it is important to discriminate whether the occurrence of an exceedance or a violation of the daily limit value established for PM could also be due to natural sources.

This study explores the use of a systematic approach in the comparison of simultaneous measurements of PM₁₀, PM_2.5, and PM₁ mass concentrations using Aitchison geometry. Three case studies in three different Asian cities where the PM coarse, fine, and ultrafine size fraction prevail were investigated and the data was displayed using a dedicated triangular diagram. Simultaneous size-segregated PM measurements, for each case study, were assessed in terms of PM ratios and PM₁₀ levels and were compared to similar measurements reported in literature. Non-central chi-squared distribution quantiles, for each case study, were evaluated and used to investigate the degree of similarity between simultaneous size-segregated PM ratios. Likewise, a comparative number k was used to show the proportion between PM₁₀ levels. The issues relating to the location of the simultaneous size-segregated PM ratios on the triangular diagram were examined and the effects of the non-centrality parameter λ on PM comparison were indicated. The results show that the proposed systematic approach can estimate an explorative quantile (i.e., 2.5%) within which the simultaneous size-segregated PM measurements from one site can be compared with simultaneous size-segregated PM measurements from other sites reported in literature highlighting the existence of possible similarities or correspondences in the kind of sources influencing the PM.

Compositional data analysis was applied on mineral element concentrations (i.e., Al, Ti, Si, Ca, Mg, Fe, Sr) content in PM₁₀, PM_2.5 and PM₁ simultaneous measurements at three characteristic environmental sites: kerbside, background and rural site. Different possible sources of mineral trace elements affecting the PM in the considered sites were highlighted. Particularly, results show that compositional data analysis allows for the assessment of chemical/physical differences between mineral element concentrations of PM. These differences can be associated with both different kinds of involved mineral sources and different mechanisms of accumulation/dispersion of PM at the considered sites.

Seasonal variability in near-surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere–ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between near-surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically, (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres, and (ii) at the annual frequency, estimates of the relative phase between near-surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1-month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3, but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterizing the cyclic response of current global atmosphere–ocean models to the external (solar) forcing that is of interest for seasonal forecasts.

Seasonal variability of surface air temperature and baroclinicity from the ECMWF ERA-Interim (ERAI) reanalysis and six coupled atmosphere-ocean general circulation models (AOGCMs) participating in the Coupled Model Intercomparison Project phase 3 and 5 (CMIP3 and CMIP5) are examined. In particular, the annual and semiannual cycles of hemispherically averaged fields are studied using spectral analysis. The aim is to assess the ability of coupled general circulation models to properly reproduce the observed amplitude and phase of these cycles, and investigate the relationship between surface temperature and baroclinicity (coherency and relative phase) in such frequency bands. The overall results of power spectra agree in displaying a statistically significant peak at the annual frequency in the zonally averaged fields of both hemispheres. The semiannual peak, instead, shows less power and in the NH seems to have a more regional character, as is observed in the North Pacific Ocean region. Results of bivariate analysis for such a region and Southern Hemisphere midlatitudes show some discrepancies between ERAI and model data, as well as among models, especially for the semiannual frequency. Specifically: (i) the coherency at the annual and semiannual frequency observed in the reanalysis data is well represented by models in both hemispheres; (ii) at the annual frequency, estimates of the relative phase between surface temperature and baroclinicity are bounded between about ±15° around an average value of 220° (i.e., approximately 1 month phase shift), while at the semiannual frequency model phases show a wider dispersion in both hemispheres with larger errors in the estimates, denoting increased uncertainty and some disagreement among models. The most recent CMIP climate models (CMIP5) show several improvements when compared with CMIP3 but a degree of discrepancy still persists though masked by the large errors characterizing the semiannual frequency. These findings contribute to better characterize the cyclic response of current global atmosphere-ocean models to the external (solar) forcing that is of interest for seasonal forecasts.